mri-based simulation study: Topics by Science.gov

Sample records for mri-based simulation study

Realistic simulated MRI and SPECT databases. Application to SPECT/MRI registration evaluation.

PubMed

Aubert-Broche, Berengere; Grova, Christophe; Reilhac, Anthonin; Evans, Alan C; Collins, D Louis

2006-01-01

This paper describes the construction of simulated SPECT and MRI databases that account for realistic anatomical and functional variability. The data is used as a gold-standard to evaluate four SPECT/MRI similarity-based registration methods. Simulation realism was accounted for using accurate physical models of data generation and acquisition. MRI and SPECT simulations were generated from three subjects to take into account inter-subject anatomical variability. Functional SPECT data were computed from six functional models of brain perfusion. Previous models of normal perfusion and ictal perfusion observed in Mesial Temporal Lobe Epilepsy (MTLE) were considered to generate functional variability. We studied the impact noise and intensity non-uniformity in MRI simulations and SPECT scatter correction may have on registration accuracy. We quantified the amount of registration error caused by anatomical and functional variability. Registration involving ictal data was less accurate than registration involving normal data. MR intensity nonuniformity was the main factor decreasing registration accuracy. The proposed simulated database is promising to evaluate many functional neuroimaging methods, involving MRI and SPECT data.
MRI-based finite element modeling of facial mimics: a case study on the paired zygomaticus major muscles.

PubMed

Fan, Ang-Xiao; Dakpé, Stéphanie; Dao, Tien Tuan; Pouletaut, Philippe; Rachik, Mohamed; Ho Ba Tho, Marie Christine

2017-07-01

Finite element simulation of facial mimics provides objective indicators about soft tissue functions for improving diagnosis, treatment and follow-up of facial disorders. There is a lack of in vivo experimental data for model development and validation. In this study, the contribution of the paired Zygomaticus Major (ZM) muscle contraction on the facial mimics was investigated using in vivo experimental data derived from MRI. Maximal relative differences of 7.7% and 37% were noted between MRI-based measurements and numerical outcomes for ZM and skin deformation behaviors respectively. This study opens a new direction to simulate facial mimics with in vivo data.
The relevance of MRI for patient modeling in head and neck hyperthermia treatment planning: a comparison of CT and CT-MRI based tissue segmentation on simulated temperature.

PubMed

Verhaart, René F; Fortunati, Valerio; Verduijn, Gerda M; van der Lugt, Aad; van Walsum, Theo; Veenland, Jifke F; Paulides, Margarethus M

2014-12-01

In current clinical practice, head and neck (H&N) hyperthermia treatment planning (HTP) is solely based on computed tomography (CT) images. Magnetic resonance imaging (MRI) provides superior soft-tissue contrast over CT. The purpose of the authors' study is to investigate the relevance of using MRI in addition to CT for patient modeling in H&N HTP. CT and MRI scans were acquired for 11 patients in an immobilization mask. Three observers manually segmented on CT, MRI T1 weighted (MRI-T1w), and MRI T2 weighted (MRI-T2w) images the following thermo-sensitive tissues: cerebrum, cerebellum, brainstem, myelum, sclera, lens, vitreous humor, and the optical nerve. For these tissues that are used for patient modeling in H&N HTP, the interobserver variation of manual tissue segmentation in CT and MRI was quantified with the mean surface distance (MSD). Next, the authors compared the impact of CT and CT and MRI based patient models on the predicted temperatures. For each tissue, the modality was selected that led to the lowest observer variation and inserted this in the combined CT and MRI based patient model (CT and MRI), after a deformable image registration. In addition, a patient model with a detailed segmentation of brain tissues (including white matter, gray matter, and cerebrospinal fluid) was created (CT and MRIdb). To quantify the relevance of MRI based segmentation for H&N HTP, the authors compared the predicted maximum temperatures in the segmented tissues (Tmax) and the corresponding specific absorption rate (SAR) of the patient models based on (1) CT, (2) CT and MRI, and (3) CT and MRIdb. In MRI, a similar or reduced interobserver variation was found compared to CT (maximum of median MSD in CT: 0.93 mm, MRI-T1w: 0.72 mm, MRI-T2w: 0.66 mm). Only for the optical nerve the interobserver variation is significantly lower in CT compared to MRI (median MSD in CT: 0.58 mm, MRI-T1w: 1.27 mm, MRI-T2w: 1.40 mm). Patient models based on CT (Tmax: 38.0 °C) and CT and MRI (Tmax: 38.1 °C) result in similar simulated temperatures, while CT and MRIdb (Tmax: 38.5 °C) resulted in significantly higher temperatures. The SAR corresponding to these temperatures did not differ significantly. Although MR imaging reduces the interobserver variation in most tissues, it does not affect simulated local tissue temperatures. However, the improved soft-tissue contrast provided by MRI allows generating a detailed brain segmentation, which has a strong impact on the predicted local temperatures and hence may improve simulation guided hyperthermia.
Cardiac re-entry dynamics and self-termination in DT-MRI based model of Human Foetal Heart

NASA Astrophysics Data System (ADS)

Biktasheva, Irina V.; Anderson, Richard A.; Holden, Arun V.; Pervolaraki, Eleftheria; Wen, Fen Cai

2018-02-01

The effect of human foetal heart geometry and anisotropy on anatomy induced drift and self-termination of cardiac re-entry is studied here in MRI based 2D slice and 3D whole heart computer simulations. Isotropic and anisotropic models of 20 weeks of gestational age human foetal heart obtained from 100μm voxel diffusion tensor MRI data sets were used in the computer simulations. The fiber orientation angles of the heart were obtained from the orientation of the DT-MRI primary eigenvectors. In a spatially homogeneous electrophysiological monodomain model with the DT-MRI based heart geometries, cardiac re-entry was initiated at a prescribed location in a 2D slice, and in the 3D whole heart anatomy models. Excitation was described by simplified FitzHugh-Nagumo kinetics. In a slice of the heart, with propagation velocity twice as fast along the fibres than across the fibers, DT-MRI based fiber anisotropy changes the re-entry dynamics from pinned to an anatomical re-entry. In the 3D whole heart models, the fiber anisotropy changes cardiac re-entry dynamics from a persistent re-entry to the re-entry self-termination. The self-termination time depends on the re-entry’s initial position. In all the simulations with the DT-MRI based cardiac geometry, the anisotropy of the myocardial tissue shortens the time to re-entry self-termination several folds. The numerical simulations depend on the validity of the DT-MRI data set used. The ventricular wall showed the characteristic transmural rotation of the helix angle of the developed mammalian heart, while the fiber orientation in the atria was irregular.
MRI simulation: end-to-end testing for prostate radiation therapy using geometric pelvic MRI phantoms

NASA Astrophysics Data System (ADS)

Sun, Jidi; Dowling, Jason; Pichler, Peter; Menk, Fred; Rivest-Henault, David; Lambert, Jonathan; Parker, Joel; Arm, Jameen; Best, Leah; Martin, Jarad; Denham, James W.; Greer, Peter B.

2015-04-01

To clinically implement MRI simulation or MRI-alone treatment planning requires comprehensive end-to-end testing to ensure an accurate process. The purpose of this study was to design and build a geometric phantom simulating a human male pelvis that is suitable for both CT and MRI scanning and use it to test geometric and dosimetric aspects of MRI simulation including treatment planning and digitally reconstructed radiograph (DRR) generation. A liquid filled pelvic shaped phantom with simulated pelvic organs was scanned in a 3T MRI simulator with dedicated radiotherapy couch-top, laser bridge and pelvic coil mounts. A second phantom with the same external shape but with an internal distortion grid was used to quantify the distortion of the MR image. Both phantoms were also CT scanned as the gold-standard for both geometry and dosimetry. Deformable image registration was used to quantify the MR distortion. Dose comparison was made using a seven-field IMRT plan developed on the CT scan with the fluences copied to the MR image and recalculated using bulk electron densities. Without correction the maximum distortion of the MR compared with the CT scan was 7.5 mm across the pelvis, while this was reduced to 2.6 and 1.7 mm by the vendor’s 2D and 3D correction algorithms, respectively. Within the locations of the internal organs of interest, the distortion was <1.5 and <1 mm with 2D and 3D correction algorithms, respectively. The dose at the prostate isocentre calculated on CT and MRI images differed by 0.01% (1.1 cGy). Positioning shifts were within 1 mm when setup was performed using MRI generated DRRs compared to setup using CT DRRs. The MRI pelvic phantom allows end-to-end testing of the MRI simulation workflow with comparison to the gold-standard CT based process. MRI simulation was found to be geometrically accurate with organ dimensions, dose distributions and DRR based setup within acceptable limits compared to CT.
The relevance of MRI for patient modeling in head and neck hyperthermia treatment planning: A comparison of CT and CT-MRI based tissue segmentation on simulated temperature

DOE Office of Scientific and Technical Information (OSTI.GOV)

Verhaart, René F., E-mail: r.f.verhaart@erasmusmc.nl; Paulides, Margarethus M.; Fortunati, Valerio

Purpose: In current clinical practice, head and neck (H and N) hyperthermia treatment planning (HTP) is solely based on computed tomography (CT) images. Magnetic resonance imaging (MRI) provides superior soft-tissue contrast over CT. The purpose of the authors’ study is to investigate the relevance of using MRI in addition to CT for patient modeling in H and N HTP. Methods: CT and MRI scans were acquired for 11 patients in an immobilization mask. Three observers manually segmented on CT, MRI T1 weighted (MRI-T1w), and MRI T2 weighted (MRI-T2w) images the following thermo-sensitive tissues: cerebrum, cerebellum, brainstem, myelum, sclera, lens, vitreousmore » humor, and the optical nerve. For these tissues that are used for patient modeling in H and N HTP, the interobserver variation of manual tissue segmentation in CT and MRI was quantified with the mean surface distance (MSD). Next, the authors compared the impact of CT and CT and MRI based patient models on the predicted temperatures. For each tissue, the modality was selected that led to the lowest observer variation and inserted this in the combined CT and MRI based patient model (CT and MRI), after a deformable image registration. In addition, a patient model with a detailed segmentation of brain tissues (including white matter, gray matter, and cerebrospinal fluid) was created (CT and MRI{sub db}). To quantify the relevance of MRI based segmentation for H and N HTP, the authors compared the predicted maximum temperatures in the segmented tissues (T{sub max}) and the corresponding specific absorption rate (SAR) of the patient models based on (1) CT, (2) CT and MRI, and (3) CT and MRI{sub db}. Results: In MRI, a similar or reduced interobserver variation was found compared to CT (maximum of median MSD in CT: 0.93 mm, MRI-T1w: 0.72 mm, MRI-T2w: 0.66 mm). Only for the optical nerve the interobserver variation is significantly lower in CT compared to MRI (median MSD in CT: 0.58 mm, MRI-T1w: 1.27 mm, MRI-T2w: 1.40 mm). Patient models based on CT (T{sub max}: 38.0 °C) and CT and MRI (T{sub max}: 38.1 °C) result in similar simulated temperatures, while CT and MRI{sub db} (T{sub max}: 38.5 °C) resulted in significantly higher temperatures. The SAR corresponding to these temperatures did not differ significantly. Conclusions: Although MR imaging reduces the interobserver variation in most tissues, it does not affect simulated local tissue temperatures. However, the improved soft-tissue contrast provided by MRI allows generating a detailed brain segmentation, which has a strong impact on the predicted local temperatures and hence may improve simulation guided hyperthermia.« less
Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model.

PubMed

Liu, Fang; Velikina, Julia V; Block, Walter F; Kijowski, Richard; Samsonov, Alexey A

2017-02-01

We present MRiLab, a new comprehensive simulator for large-scale realistic MRI simulations on a regular PC equipped with a modern graphical processing unit (GPU). MRiLab combines realistic tissue modeling with numerical virtualization of an MRI system and scanning experiment to enable assessment of a broad range of MRI approaches including advanced quantitative MRI methods inferring microstructure on a sub-voxel level. A flexible representation of tissue microstructure is achieved in MRiLab by employing the generalized tissue model with multiple exchanging water and macromolecular proton pools rather than a system of independent proton isochromats typically used in previous simulators. The computational power needed for simulation of the biologically relevant tissue models in large 3D objects is gained using parallelized execution on GPU. Three simulated and one actual MRI experiments were performed to demonstrate the ability of the new simulator to accommodate a wide variety of voxel composition scenarios and demonstrate detrimental effects of simplified treatment of tissue micro-organization adapted in previous simulators. GPU execution allowed ∼ 200× improvement in computational speed over standard CPU. As a cross-platform, open-source, extensible environment for customizing virtual MRI experiments, MRiLab streamlines the development of new MRI methods, especially those aiming to infer quantitatively tissue composition and microstructure.
Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model

PubMed Central

Velikina, Julia V.; Block, Walter F.; Kijowski, Richard; Samsonov, Alexey A.

2017-01-01

We present MRiLab, a new comprehensive simulator for large-scale realistic MRI simulations on a regular PC equipped with a modern graphical processing unit (GPU). MRiLab combines realistic tissue modeling with numerical virtualization of an MRI system and scanning experiment to enable assessment of a broad range of MRI approaches including advanced quantitative MRI methods inferring microstructure on a sub-voxel level. A flexibl representation of tissue microstructure is achieved in MRiLab by employing the generalized tissue model with multiple exchanging water and macromolecular proton pools rather than a system of independent proton isochromats typically used in previous simulators. The computational power needed for simulation of the biologically relevant tissue models in large 3D objects is gained using parallelized execution on GPU. Three simulated and one actual MRI experiments were performed to demonstrate the ability of the new simulator to accommodate a wide variety of voxel composition scenarios and demonstrate detrimental effects of simplifie treatment of tissue micro-organization adapted in previous simulators. GPU execution allowed ∼200× improvement in computational speed over standard CPU. As a cross-platform, open-source, extensible environment for customizing virtual MRI experiments, MRiLab streamlines the development of new MRI methods, especially those aiming to infer quantitatively tissue composition and microstructure. PMID:28113746
Accuracy of UTE-MRI-based patient setup for brain cancer radiation therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Yingli; Cao, Minsong; Kaprealian, Tania

2016-01-15

Purpose: Radiation therapy simulations solely based on MRI have advantages compared to CT-based approaches. One feature readily available from computed tomography (CT) that would need to be reproduced with MR is the ability to compute digitally reconstructed radiographs (DRRs) for comparison against on-board radiographs commonly used for patient positioning. In this study, the authors generate MR-based bone images using a single ultrashort echo time (UTE) pulse sequence and quantify their 3D and 2D image registration accuracy to CT and radiographic images for treatments in the cranium. Methods: Seven brain cancer patients were scanned at 1.5 T using a radial UTEmore » sequence. The sequence acquired two images at two different echo times. The two images were processed using an in-house software to generate the UTE bone images. The resultant bone images were rigidly registered to simulation CT data and the registration error was determined using manually annotated landmarks as references. DRRs were created based on UTE-MRI and registered to simulated on-board images (OBIs) and actual clinical 2D oblique images from ExacTrac™. Results: UTE-MRI resulted in well visualized cranial, facial, and vertebral bones that quantitatively matched the bones in the CT images with geometric measurement errors of less than 1 mm. The registration error between DRRs generated from 3D UTE-MRI and the simulated 2D OBIs or the clinical oblique x-ray images was also less than 1 mm for all patients. Conclusions: UTE-MRI-based DRRs appear to be promising for daily patient setup of brain cancer radiotherapy with kV on-board imaging.« less
Image-Based Computational Fluid Dynamics in Blood Vessel Models: Toward Developing a Prognostic Tool to Assess Cardiovascular Function Changes in Prolonged Space Flights

NASA Technical Reports Server (NTRS)

Chatzimavroudis, George P.; Spirka, Thomas A.; Setser, Randolph M.; Myers, Jerry G.

2004-01-01

One of NASA's objectives is to be able to perform a complete, pre-flight, evaluation of cardiovascular changes in astronauts scheduled for prolonged space missions. Computational fluid dynamics (CFD) has shown promise as a method for estimating cardiovascular function during reduced gravity conditions. For this purpose, MRI can provide geometrical information, to reconstruct vessel geometries, and measure all spatial velocity components, providing location specific boundary conditions. The objective of this study was to investigate the reliability of MRI-based model reconstruction and measured boundary conditions for CFD simulations. An aortic arch model and a carotid bifurcation model were scanned in a 1.5T Siemens MRI scanner. Axial MRI acquisitions provided images for geometry reconstruction (slice thickness 3 and 5 mm; pixel size 1x1 and 0.5x0.5 square millimeters). Velocity acquisitions provided measured inlet boundary conditions and localized three-directional steady-flow velocity data (0.7-3.0 L/min). The vessel walls were isolated using NIH provided software (ImageJ) and lofted to form the geometric surface. Constructed and idealized geometries were imported into a commercial CFD code for meshing and simulation. Contour and vector plots of the velocity showed identical features between the MRI velocity data, the MRI-based CFD data, and the idealized-geometry CFD data, with less than 10% differences in the local velocity values. CFD results on models reconstructed from different MRI resolution settings showed insignificant differences (less than 5%). This study illustrated, quantitatively, that reliable CFD simulations can be performed with MRI reconstructed models and gives evidence that a future, subject-specific, computational evaluation of the cardiovascular system alteration during space travel is feasible.
Estimation of Error in Maximal Intensity Projection-Based Internal Target Volume of Lung Tumors: A Simulation and Comparison Study Using Dynamic Magnetic Resonance Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai Jing; Read, Paul W.; Baisden, Joseph M.

Purpose: To evaluate the error in four-dimensional computed tomography (4D-CT) maximal intensity projection (MIP)-based lung tumor internal target volume determination using a simulation method based on dynamic magnetic resonance imaging (dMRI). Methods and Materials: Eight healthy volunteers and six lung tumor patients underwent a 5-min MRI scan in the sagittal plane to acquire dynamic images of lung motion. A MATLAB program was written to generate re-sorted dMRI using 4D-CT acquisition methods (RedCAM) by segmenting and rebinning the MRI scans. The maximal intensity projection images were generated from RedCAM and dMRI, and the errors in the MIP-based internal target area (ITA)more » from RedCAM ({epsilon}), compared with those from dMRI, were determined and correlated with the subjects' respiratory variability ({nu}). Results: Maximal intensity projection-based ITAs from RedCAM were comparatively smaller than those from dMRI in both phantom studies ({epsilon} = -21.64% {+-} 8.23%) and lung tumor patient studies ({epsilon} = -20.31% {+-} 11.36%). The errors in MIP-based ITA from RedCAM correlated linearly ({epsilon} = -5.13{nu} - 6.71, r{sup 2} = 0.76) with the subjects' respiratory variability. Conclusions: Because of the low temporal resolution and retrospective re-sorting, 4D-CT might not accurately depict the excursion of a moving tumor. Using a 4D-CT MIP image to define the internal target volume might therefore cause underdosing and an increased risk of subsequent treatment failure. Patient-specific respiratory variability might also be a useful predictor of the 4D-CT-induced error in MIP-based internal target volume determination.« less
Estimation of error in maximal intensity projection-based internal target volume of lung tumors: a simulation and comparison study using dynamic magnetic resonance imaging.

PubMed

Cai, Jing; Read, Paul W; Baisden, Joseph M; Larner, James M; Benedict, Stanley H; Sheng, Ke

2007-11-01

To evaluate the error in four-dimensional computed tomography (4D-CT) maximal intensity projection (MIP)-based lung tumor internal target volume determination using a simulation method based on dynamic magnetic resonance imaging (dMRI). Eight healthy volunteers and six lung tumor patients underwent a 5-min MRI scan in the sagittal plane to acquire dynamic images of lung motion. A MATLAB program was written to generate re-sorted dMRI using 4D-CT acquisition methods (RedCAM) by segmenting and rebinning the MRI scans. The maximal intensity projection images were generated from RedCAM and dMRI, and the errors in the MIP-based internal target area (ITA) from RedCAM (epsilon), compared with those from dMRI, were determined and correlated with the subjects' respiratory variability (nu). Maximal intensity projection-based ITAs from RedCAM were comparatively smaller than those from dMRI in both phantom studies (epsilon = -21.64% +/- 8.23%) and lung tumor patient studies (epsilon = -20.31% +/- 11.36%). The errors in MIP-based ITA from RedCAM correlated linearly (epsilon = -5.13nu - 6.71, r(2) = 0.76) with the subjects' respiratory variability. Because of the low temporal resolution and retrospective re-sorting, 4D-CT might not accurately depict the excursion of a moving tumor. Using a 4D-CT MIP image to define the internal target volume might therefore cause underdosing and an increased risk of subsequent treatment failure. Patient-specific respiratory variability might also be a useful predictor of the 4D-CT-induced error in MIP-based internal target volume determination.
Feature-space-based FMRI analysis using the optimal linear transformation.

PubMed

Sun, Fengrong; Morris, Drew; Lee, Wayne; Taylor, Margot J; Mills, Travis; Babyn, Paul S

2010-09-01

The optimal linear transformation (OLT), an image analysis technique of feature space, was first presented in the field of MRI. This paper proposes a method of extending OLT from MRI to functional MRI (fMRI) to improve the activation-detection performance over conventional approaches of fMRI analysis. In this method, first, ideal hemodynamic response time series for different stimuli were generated by convolving the theoretical hemodynamic response model with the stimulus timing. Second, constructing hypothetical signature vectors for different activity patterns of interest by virtue of the ideal hemodynamic responses, OLT was used to extract features of fMRI data. The resultant feature space had particular geometric clustering properties. It was then classified into different groups, each pertaining to an activity pattern of interest; the applied signature vector for each group was obtained by averaging. Third, using the applied signature vectors, OLT was applied again to generate fMRI composite images with high SNRs for the desired activity patterns. Simulations and a blocked fMRI experiment were employed for the method to be verified and compared with the general linear model (GLM)-based analysis. The simulation studies and the experimental results indicated the superiority of the proposed method over the GLM-based analysis in detecting brain activities.
Improved sparse decomposition based on a smoothed L0 norm using a Laplacian kernel to select features from fMRI data.

PubMed

Zhang, Chuncheng; Song, Sutao; Wen, Xiaotong; Yao, Li; Long, Zhiying

2015-04-30

Feature selection plays an important role in improving the classification accuracy of multivariate classification techniques in the context of fMRI-based decoding due to the "few samples and large features" nature of functional magnetic resonance imaging (fMRI) data. Recently, several sparse representation methods have been applied to the voxel selection of fMRI data. Despite the low computational efficiency of the sparse representation methods, they still displayed promise for applications that select features from fMRI data. In this study, we proposed the Laplacian smoothed L0 norm (LSL0) approach for feature selection of fMRI data. Based on the fast sparse decomposition using smoothed L0 norm (SL0) (Mohimani, 2007), the LSL0 method used the Laplacian function to approximate the L0 norm of sources. Results of the simulated and real fMRI data demonstrated the feasibility and robustness of LSL0 for the sparse source estimation and feature selection. Simulated results indicated that LSL0 produced more accurate source estimation than SL0 at high noise levels. The classification accuracy using voxels that were selected by LSL0 was higher than that by SL0 in both simulated and real fMRI experiment. Moreover, both LSL0 and SL0 showed higher classification accuracy and required less time than ICA and t-test for the fMRI decoding. LSL0 outperformed SL0 in sparse source estimation at high noise level and in feature selection. Moreover, LSL0 and SL0 showed better performance than ICA and t-test for feature selection. Copyright © 2015 Elsevier B.V. All rights reserved.
An Example-Based Brain MRI Simulation Framework.

PubMed

He, Qing; Roy, Snehashis; Jog, Amod; Pham, Dzung L

2015-02-21

The simulation of magnetic resonance (MR) images plays an important role in the validation of image analysis algorithms such as image segmentation, due to lack of sufficient ground truth in real MR images. Previous work on MRI simulation has focused on explicitly modeling the MR image formation process. However, because of the overwhelming complexity of MR acquisition these simulations must involve simplifications and approximations that can result in visually unrealistic simulated images. In this work, we describe an example-based simulation framework, which uses an "atlas" consisting of an MR image and its anatomical models derived from the hard segmentation. The relationships between the MR image intensities and its anatomical models are learned using a patch-based regression that implicitly models the physics of the MR image formation. Given the anatomical models of a new brain, a new MR image can be simulated using the learned regression. This approach has been extended to also simulate intensity inhomogeneity artifacts based on the statistical model of training data. Results show that the example based MRI simulation method is capable of simulating different image contrasts and is robust to different choices of atlas. The simulated images resemble real MR images more than simulations produced by a physics-based model.
TH-A-BRF-11: Image Intensity Non-Uniformities Between MRI Simulation and Diagnostic MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paulson, E

2014-06-15

Purpose: MRI simulation for MRI-based radiotherapy demands that patients be setup in treatment position, which frequently involves use of alternative radiofrequency (RF) coil configurations to accommodate immobilized patients. However, alternative RF coil geometries may exacerbate image intensity non-uniformities (IINU) beyond those observed in diagnostic MRI, which may challenge image segmentation and registration accuracy as well as confound studies assessing radiotherapy response when MR simulation images are used as baselines for evaluation. The goal of this work was to determine whether differences in IINU exist between MR simulation and diagnostic MR images. Methods: ACR-MRI phantom images were acquired at 3T usingmore » a spin-echo sequence (TE/TR:20/500ms, rBW:62.5kHz, TH/skip:5/5mm). MR simulation images were obtained by wrapping two flexible phased-array RF coils around the phantom. Diagnostic MR images were obtained by placing the phantom into a commercial phased-array head coil. Pre-scan normalization was enabled in both cases. Images were transferred offline and corrected for IINU using the MNI N3 algorithm. Coefficients of variation (CV=σ/μ) were calculated for each slice. Wilcoxon matched-pairs and Mann-Whitney tests compared CV values between original and N3 images and between MR simulation and diagnostic MR images. Results: Significant differences in CV were detected between original and N3 images in both MRI simulation and diagnostic MRI groups (p=0.010, p=0.010). In addition, significant differences in CV were detected between original MR simulation and original and N3 diagnostic MR images (p=0.0256, p=0.0016). However, no significant differences in CV were detected between N3 MR simulation images and original or N3 diagnostic MR images, demonstrating the importance of correcting MR simulation images beyond pre-scan normalization prior to use in radiotherapy. Conclusions: Alternative RF coil configurations used in MRI simulation can Result in significant IINU differences compared to diagnostic MR images. The MNI N3 algorithm reduced MR simulation IINU to levels observed in diagnostic MR images. Funding provided by Advancing a Healthier Wisconsin.« less
Simulation of spatiotemporal CT data sets using a 4D MRI-based lung motion model.

PubMed

Marx, Mirko; Ehrhardt, Jan; Werner, René; Schlemmer, Heinz-Peter; Handels, Heinz

2014-05-01

Four-dimensional CT imaging is widely used to account for motion-related effects during radiotherapy planning of lung cancer patients. However, 4D CT often contains motion artifacts, cannot be used to measure motion variability, and leads to higher dose exposure. In this article, we propose using 4D MRI to acquire motion information for the radiotherapy planning process. From the 4D MRI images, we derive a time-continuous model of the average patient-specific respiratory motion, which is then applied to simulate 4D CT data based on a static 3D CT. The idea of the motion model is to represent the average lung motion over a respiratory cycle by cyclic B-spline curves. The model generation consists of motion field estimation in the 4D MRI data by nonlinear registration, assigning respiratory phases to the motion fields, and applying a B-spline approximation on a voxel-by-voxel basis to describe the average voxel motion over a breathing cycle. To simulate a patient-specific 4D CT based on a static CT of the patient, a multi-modal registration strategy is introduced to transfer the motion model from MRI to the static CT coordinates. Differences between model-based estimated and measured motion vectors are on average 1.39 mm for amplitude-based binning of the 4D MRI data of three patients. In addition, the MRI-to-CT registration strategy is shown to be suitable for the model transformation. The application of our 4D MRI-based motion model for simulating 4D CT images provides advantages over standard 4D CT (less motion artifacts, radiation-free). This makes it interesting for radiotherapy planning.
Computational studies of steering nanoparticles with magnetic gradients

NASA Astrophysics Data System (ADS)

Aylak, Sultan Suleyman

Magnetic Resonance Imaging (MRI) guided nanorobotic systems that could perform diagnostic, curative, and reconstructive treatments in the human body at the cellular and subcellular level in a controllable manner have recently been proposed. The concept of a MRI-guided nanorobotic system is based on the use of a MRI scanner to induce the required external driving forces to guide magnetic nanocapsules to a specific target. However, the maximum magnetic gradient specifications of existing clinical MRI systems are not capable of driving magnetic nanocapsules against the blood flow. This thesis presents the visualization of nanoparticles inside blood vessel, Graphical User Interface (GUI) for updating file including initial parameters and demonstrating the simulation of particles and C++ code for computing magnetic forces and fluidic forces. The visualization and GUI were designed using Virtual Reality Modeling Language (VRML), MATLAB and C#. The addition of software for MRI-guided nanorobotic system provides simulation results. Preliminary simulation results demonstrate that external magnetic field causes aggregation of nanoparticles while they flow in the vessel. This is a promising result --in accordance with similar experimental results- and encourages further investigation on the nanoparticle-based self-assembly structures for use in nanorobotic drug delivery.
Motion compensation for MRI-compatible patient-mounted needle guide device: estimation of targeting accuracy in MRI-guided kidney cryoablations

NASA Astrophysics Data System (ADS)

Tokuda, Junichi; Chauvin, Laurent; Ninni, Brian; Kato, Takahisa; King, Franklin; Tuncali, Kemal; Hata, Nobuhiko

2018-04-01

Patient-mounted needle guide devices for percutaneous ablation are vulnerable to patient motion. The objective of this study is to develop and evaluate a software system for an MRI-compatible patient-mounted needle guide device that can adaptively compensate for displacement of the device due to patient motion using a novel image-based automatic device-to-image registration technique. We have developed a software system for an MRI-compatible patient-mounted needle guide device for percutaneous ablation. It features fully-automated image-based device-to-image registration to track the device position, and a device controller to adjust the needle trajectory to compensate for the displacement of the device. We performed: (a) a phantom study using a clinical MR scanner to evaluate registration performance; (b) simulations using intraoperative time-series MR data acquired in 20 clinical cases of MRI-guided renal cryoablations to assess its impact on motion compensation; and (c) a pilot clinical study in three patients to test its feasibility during the clinical procedure. FRE, TRE, and success rate of device-to-image registration were mm, mm, and 98.3% for the phantom images. The simulation study showed that the motion compensation reduced the targeting error for needle placement from 8.2 mm to 5.4 mm (p < 0.0005) in patients under general anesthesia (GA), and from 14.4 mm to 10.0 mm () in patients under monitored anesthesia care (MAC). The pilot study showed that the software registered the device successfully in a clinical setting. Our simulation study demonstrated that the software system could significantly improve targeting accuracy in patients treated under both MAC and GA. Intraprocedural image-based device-to-image registration was feasible.
Improved application of independent component analysis to functional magnetic resonance imaging study via linear projection techniques.

PubMed

Long, Zhiying; Chen, Kewei; Wu, Xia; Reiman, Eric; Peng, Danling; Yao, Li

2009-02-01

Spatial Independent component analysis (sICA) has been widely used to analyze functional magnetic resonance imaging (fMRI) data. The well accepted implicit assumption is the spatially statistical independency of intrinsic sources identified by sICA, making the sICA applications difficult for data in which there exist interdependent sources and confounding factors. This interdependency can arise, for instance, from fMRI studies investigating two tasks in a single session. In this study, we introduced a linear projection approach and considered its utilization as a tool to separate task-related components from two-task fMRI data. The robustness and feasibility of the method are substantiated through simulation on computer data and fMRI real rest data. Both simulated and real two-task fMRI experiments demonstrated that sICA in combination with the projection method succeeded in separating spatially dependent components and had better detection power than pure model-based method when estimating activation induced by each task as well as both tasks.

Image-based computational fluid dynamics in blood vessel models: toward developing a prognostic tool to assess cardiovascular function changes in prolonged space flights

NASA Astrophysics Data System (ADS)

Chatzimavroudis, George P.; Spirka, Thomas A.; Setser, Randolph M.; Myers, Jerry G.

2005-04-01

One of NASA"s objectives is to be able to perform a complete pre-flight evaluation of possible cardiovascular changes in astronauts scheduled for prolonged space missions. Blood flow is an important component of cardiovascular function. Lately, attention has focused on using computational fluid dynamics (CFD) to analyze flow with realistic vessel geometries. MRI can provide detailed geometrical information and is the only clinical technique to measure all three spatial velocity components. The objective of this study was to investigate the reliability of MRI-based model reconstruction for CFD simulations. An aortic arch model and a carotid bifurcation model were scanned in a 1.5T MRI scanner. Axial MRI acquisitions provided images for geometry reconstruction using different resolution settings. The vessel walls were identified and the geometry was reconstructed using existing software. The geometry was then imported into a commercial CFD package for meshing and numerical solution. MRI velocity acquisitions provided true inlet boundary conditions for steady flow, as well as three-directional velocity data at several locations. In addition, an idealized version of each geometry was created from the model drawings. Contour and vector plots of the velocity showed identical features between the MRI velocity data, the MRI-based CFD data, and the idealized-geometry CFD data, with mean differences <10%. CFD results from different MRI resolution settings did not show significant differences (<5%). This study showed quantitatively that reliable CFD simulations can be performed in models reconstructed from MRI acquisitions and gives evidence that a future, subject-specific, computational evaluation of the cardiovascular system is possible.
Magnetic resonance electrical impedance tomography (MREIT): simulation study of J-substitution algorithm.

PubMed

Kwon, Ohin; Woo, Eung Je; Yoon, Jeong-Rock; Seo, Jin Keun

2002-02-01

We developed a new image reconstruction algorithm for magnetic resonance electrical impedance tomography (MREIT). MREIT is a new EIT imaging technique integrated into magnetic resonance imaging (MRI) system. Based on the assumption that internal current density distribution is obtained using magnetic resonance imaging (MRI) technique, the new image reconstruction algorithm called J-substitution algorithm produces cross-sectional static images of resistivity (or conductivity) distributions. Computer simulations show that the spatial resolution of resistivity image is comparable to that of MRI. MREIT provides accurate high-resolution cross-sectional resistivity images making resistivity values of various human tissues available for many biomedical applications.
Modeling and simulation of magnetic resonance imaging based on intermolecular multiple quantum coherences

NASA Astrophysics Data System (ADS)

Cai, Congbo; Dong, Jiyang; Cai, Shuhui; Cheng, En; Chen, Zhong

2006-11-01

Intermolecular multiple quantum coherences (iMQCs) have many potential applications since they can provide interaction information between different molecules within the range of dipolar correlation distance, and can provide new contrast in magnetic resonance imaging (MRI). Because of the non-localized property of dipolar field, and the non-linear property of the Bloch equations incorporating the dipolar field term, the evolution behavior of iMQC is difficult to deduce strictly in many cases. In such cases, simulation studies are very important. Simulation results can not only give a guide to optimize experimental conditions, but also help analyze unexpected experimental results. Based on our product operator matrix and the K-space method for dipolar field calculation, the MRI simulation software was constructed, running on Windows operation system. The non-linear Bloch equations are calculated by a fifth-order Cash-Karp Runge-Kutta formulism. Computational time can be efficiently reduced by separating the effects of chemical shifts and strong gradient field. Using this software, simulation of different kinds of complex MRI sequences can be done conveniently and quickly on general personal computers. Some examples were given. The results were discussed.
Four dimensional magnetic resonance imaging with retrospective k-space reordering: A feasibility study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yilin; Yin, Fang-Fang; Cai, Jing, E-mail: jing.cai@duke.edu

Purpose: Current four dimensional magnetic resonance imaging (4D-MRI) techniques lack sufficient temporal/spatial resolution and consistent tumor contrast. To overcome these limitations, this study presents the development and initial evaluation of a new strategy for 4D-MRI which is based on retrospective k-space reordering. Methods: We simulated a k-space reordered 4D-MRI on a 4D digital extended cardiac-torso (XCAT) human phantom. A 2D echo planar imaging MRI sequence [frame rate (F) = 0.448 Hz; image resolution (R) = 256 × 256; number of k-space segments (N{sub KS}) = 4] with sequential image acquisition mode was assumed for the simulation. Image quality of themore » simulated “4D-MRI” acquired from the XCAT phantom was qualitatively evaluated, and tumor motion trajectories were compared to input signals. In particular, mean absolute amplitude differences (D) and cross correlation coefficients (CC) were calculated. Furthermore, to evaluate the data sufficient condition for the new 4D-MRI technique, a comprehensive simulation study was performed using 30 cancer patients’ respiratory profiles to study the relationships between data completeness (C{sub p}) and a number of impacting factors: the number of repeated scans (N{sub R}), number of slices (N{sub S}), number of respiratory phase bins (N{sub P}), N{sub KS}, F, R, and initial respiratory phase at image acquisition (P{sub 0}). As a proof-of-concept, we implemented the proposed k-space reordering 4D-MRI technique on a T2-weighted fast spin echo MR sequence and tested it on a healthy volunteer. Results: The simulated 4D-MRI acquired from the XCAT phantom matched closely to the original XCAT images. Tumor motion trajectories measured from the simulated 4D-MRI matched well with input signals (D = 0.83 and 0.83 mm, and CC = 0.998 and 0.992 in superior–inferior and anterior–posterior directions, respectively). The relationship between C{sub p} and N{sub R} was found best represented by an exponential function (C{sub P}=100(1−e{sup −0.18N{sub R}}), when N{sub S} = 30, N{sub P} = 6). At a C{sub P} value of 95%, the relative error in tumor volume was 0.66%, indicating that N{sub R} at a C{sub P} value of 95% (N{sub R,95%}) is sufficient. It was found that N{sub R,95%} is approximately linearly proportional to N{sub P} (r = 0.99), and nearly independent of all other factors. The 4D-MRI images of the healthy volunteer clearly demonstrated respiratory motion in the diaphragm region with minimal motion induced noise or aliasing. Conclusions: It is feasible to generate respiratory correlated 4D-MRI by retrospectively reordering k-space based on respiratory phase. This new technology may lead to the next generation 4D-MRI with high spatiotemporal resolution and optimal tumor contrast, holding great promises to improve the motion management in radiotherapy of mobile cancers.« less
Magnetic field simulation and shimming analysis of 3.0T superconducting MRI system

NASA Astrophysics Data System (ADS)

Yue, Z. K.; Liu, Z. Z.; Tang, G. S.; Zhang, X. C.; Duan, L. J.; Liu, W. C.

2018-04-01

3.0T superconducting magnetic resonance imaging (MRI) system has become the mainstream of modern clinical MRI system because of its high field intensity and high degree of uniformity and stability. It has broad prospects in scientific research and other fields. We analyze the principle of magnet designing in this paper. We also perform the magnetic field simulation and shimming analysis of the first 3.0T/850 superconducting MRI system in the world using the Ansoft Maxwell simulation software. We guide the production and optimization of the prototype based on the results of simulation analysis. Thus the magnetic field strength, magnetic field uniformity and magnetic field stability of the prototype is guided to achieve the expected target.
SU-D-18C-01: A Novel 4D-MRI Technology Based On K-Space Retrospective Sorting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Y; Yin, F; Cai, J

2014-06-01

Purpose: Current 4D-MRI techniques lack sufficient temporal/spatial resolution and consistent tumor contrast. To overcome these limitations, this study presents the development and initial evaluation of an entirely new framework of 4D-MRI based on k-space retrospective sorting. Methods: An important challenge of the proposed technique is to determine the number of repeated scans(NR) required to obtain sufficient k-space data for 4D-MRI. To do that, simulations using 29 cancer patients' respiratory profiles were performed to derive the relationship between data acquisition completeness(Cp) and NR, also relationship between NR(Cp=95%) and the following factors: total slice(NS), respiratory phase bin length(Lb), frame rate(fr), resolution(R) andmore » image acquisition starting-phase(P0). To evaluate our technique, a computer simulation study on a 4D digital human phantom (XCAT) were conducted with regular breathing (fr=0.5Hz; R=256×256). A 2D echo planer imaging(EPI) MRI sequence were assumed to acquire raw k-space data, with respiratory signal and acquisition time for each k-space data line recorded simultaneously. K-space data was re-sorted based on respiratory phases. To evaluate 4D-MRI image quality, tumor trajectories were measured and compared with the input signal. Mean relative amplitude difference(D) and cross-correlation coefficient(CC) are calculated. Finally, phase-sharing sliding window technique was applied to investigate the feasibility of generating ultra-fast 4D-MRI. Result: Cp increased with NR(Cp=100*[1-exp(-0.19*NR)], when NS=30, Lb=100%/6). NR(Cp=95%) was inversely-proportional to Lb (r=0.97), but independent of other factors. 4D-MRI on XCAT demonstrated highly accurate motion information (D=0.67%, CC=0.996) with much less artifacts than those on image-based sorting 4D-MRI. Ultra-fast 4D-MRI with an apparent temporal resolution of 10 frames/second was reconstructed using the phase-sharing sliding window technique. Conclusions: A novel 4D-MRI technology based on k-space sorting has been successfully developed and evaluated on the digital phantom. Framework established can be applied to a variety of MR sequences, showing great promises to develop the optimal 4D-MRI technique for many radiation therapy applications. NIH (1R21CA165384-01A1)« less
An agent-based model identifies MRI regions of probable tumor invasion in a patient with glioblastoma

NASA Astrophysics Data System (ADS)

Chen, L. Leon; Ulmer, Stephan; Deisboeck, Thomas S.

2010-01-01

We present an application of a previously developed agent-based glioma model (Chen et al 2009 Biosystems 95 234-42) for predicting spatio-temporal tumor progression using a patient-specific MRI lattice derived from apparent diffusion coefficient (ADC) data. Agents representing collections of migrating glioma cells are initialized based upon voxels at the outer border of the tumor identified on T1-weighted (Gd+) MRI at an initial time point. These simulated migratory cells exhibit a specific biologically inspired spatial search paradigm, representing a weighting of the differential contribution from haptotactic permission and biomechanical resistance on the migration decision process. ADC data from 9 months after the initial tumor resection were used to select the best search paradigm for the simulation, which was initiated using data from 6 months after the initial operation. Using this search paradigm, 100 simulations were performed to derive a probabilistic map of tumor invasion locations. The simulation was able to successfully predict a recurrence in the dorsal/posterior aspect long before it was depicted on T1-weighted MRI, 18 months after the initial operation.
An agent-based model identifies MRI regions of probable tumor invasion in a patient with glioblastoma.

PubMed

Chen, L Leon; Ulmer, Stephan; Deisboeck, Thomas S

2010-01-21

We present an application of a previously developed agent-based glioma model (Chen et al 2009 Biosystems 95 234-42) for predicting spatio-temporal tumor progression using a patient-specific MRI lattice derived from apparent diffusion coefficient (ADC) data. Agents representing collections of migrating glioma cells are initialized based upon voxels at the outer border of the tumor identified on T1-weighted (Gd+) MRI at an initial time point. These simulated migratory cells exhibit a specific biologically inspired spatial search paradigm, representing a weighting of the differential contribution from haptotactic permission and biomechanical resistance on the migration decision process. ADC data from 9 months after the initial tumor resection were used to select the best search paradigm for the simulation, which was initiated using data from 6 months after the initial operation. Using this search paradigm, 100 simulations were performed to derive a probabilistic map of tumor invasion locations. The simulation was able to successfully predict a recurrence in the dorsal/posterior aspect long before it was depicted on T1-weighted MRI, 18 months after the initial operation.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Swanson, K; Corwin, D; Rockne, R

Purpose: To demonstrate a method of generating patient-specific, biologically-guided radiation therapy (RT) plans and to quantify and predict response to RT in glioblastoma. We investigate the biological correlates and imaging physics driving T2-MRI based response to radiation therapy using an MRI simulator. Methods: We have integrated a patient-specific biomathematical model of glioblastoma proliferation, invasion and radiotherapy with a multiobjective evolutionary algorithm for intensity-modulated RT optimization to construct individualized, biologically-guided plans. Patient-individualized simulations of the standard-of-care and optimized plans are compared in terms of several biological metrics quantified on MRI. An extension of the PI model is used to investigate themore » role of angiogenesis and its correlates in glioma response to therapy with the Proliferation-Invasion-Hypoxia- Necrosis-Angiogenesis model (PIHNA). The PIHNA model is used with a brain tissue phantom to predict tumor-induced vasogenic edema, tumor and tissue density that is used in a multi-compartmental MRI signal equation for generation of simulated T2- weighted MRIs. Results: Applying a novel metric of treatment response (Days Gained) to the patient-individualized simulation results predicted that the optimized RT plans would have a significant impact on delaying tumor progression, with Days Gained increases from 21% to 105%. For the T2- MRI simulations, initial validation tests compared average simulated T2 values for white matter, tumor, and peripheral edema to values cited in the literature. Simulated results closely match the characteristic T2 value for each tissue. Conclusion: Patient-individualized simulations using the combination of a biomathematical model with an optimization algorithm for RT generated biologically-guided doses that decreased normal tissue dose and increased therapeutic ratio with the potential to improve survival outcomes for treatment of glioblastoma. Simulated T2-MRI is shown to be consistent with known physics of MRI and can be used to further investigate biological drivers of imaging-based response to RT.« less
SQUIDs vs. Faraday coils for ultlra-low field nuclear magnetic resonance: experimental and simulation comparison

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matlashov, Andrei N; Espy, Michelle A; Kraus, Robert H

2010-01-01

Nuclear magnetic resonance (NMR) methods are widely used in medicine, chemistry and industry. One application area is magnetic resonance imaging or MRI. Recently it has become possible to perform NMR and MRI in ultra-low field (ULF) regime that requires measurement field strengths only of the order of 1 Gauss. These techniques exploit the advantages offered by superconducting quantum interference devices or SQUIDs. Our group at LANL has built SQUID based MRI systems for brain imaging and for liquid explosives detection at airports security checkpoints. The requirement for liquid helium cooling limits potential applications of ULF MRI for liquid identification andmore » security purposes. Our experimental comparative investigation shows that room temperature inductive magnetometers provide enough sensitivity in the 3-10 kHz range and can be used for fast liquid explosives detection based on ULF NMR/MRI technique. We describe an experimental and computer simulation comparison of the world's first multichannel SQUID based and Faraday coils based instruments that are capable of performing ULF MRI for liquids identification.« less
Sci-Thur PM - Colourful Interactions: Highlights 04: A Fast Quantitative MRI Acquisition and Processing Pipeline for Radiation Treatment Planning and Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jutras, Jean-David

MRI-only Radiation Treatment Planning (RTP) is becoming increasingly popular because of a simplified work-flow, and less inconvenience to the patient who avoids multiple scans. The advantages of MRI-based RTP over traditional CT-based RTP lie in its superior soft-tissue contrast, and absence of ionizing radiation dose. The lack of electron-density information in MRI can be addressed by automatic tissue classification. To distinguish bone from air, which both appear dark in MRI, an ultra-short echo time (UTE) pulse sequence may be used. Quantitative MRI parametric maps can provide improved tissue segmentation/classification and better sensitivity in monitoring disease progression and treatment outcome thanmore » standard weighted images. Superior tumor contrast can be achieved on pure T{sub 1} images compared to conventional T{sub 1}-weighted images acquired in the same scan duration and voxel resolution. In this study, we have developed a robust and fast quantitative MRI acquisition and post-processing work-flow that integrates these latest advances into the MRI-based RTP of brain lesions. Using 3D multi-echo FLASH images at two different optimized flip angles (both acquired in under 9 min, and 1mm isotropic resolution), parametric maps of T{sub 1}, proton-density (M{sub 0}), and T{sub 2}{sup *} are obtained with high contrast-to-noise ratio, and negligible geometrical distortions, water-fat shifts and susceptibility effects. An additional 3D UTE MRI dataset is acquired (in under 4 min) and post-processed to classify tissues for dose simulation. The pipeline was tested on four healthy volunteers and a clinical trial on brain cancer patients is underway.« less
SQUIDs vs. Induction Coils for Ultra-Low Field Nuclear Magnetic Resonance: Experimental and Simulation Comparison

PubMed Central

Matlashov, Andrei N.; Schultz, Larry J.; Espy, Michelle A.; Kraus, Robert H.; Savukov, Igor M.; Volegov, Petr L.; Wurden, Caroline J.

2011-01-01

Nuclear magnetic resonance (NMR) is widely used in medicine, chemistry and industry. One application area is magnetic resonance imaging (MRI). Recently it has become possible to perform NMR and MRI in the ultra-low field (ULF) regime requiring measurement field strengths of the order of only 1 Gauss. This technique exploits the advantages offered by superconducting quantum interference devices or SQUIDs. Our group has built SQUID based MRI systems for brain imaging and for liquid explosives detection at airport security checkpoints. The requirement for liquid helium cooling limits potential applications of ULF MRI for liquid identification and security purposes. Our experimental comparative investigation shows that room temperature inductive magnetometers may provide enough sensitivity in the 3–10 kHz range and can be used for fast liquid explosives detection based on ULF NMR technique. We describe experimental and computer-simulation results comparing multichannel SQUID based and induction coils based instruments that are capable of performing ULF MRI for liquid identification. PMID:21747638
Comprehensive MRI simulation methodology using a dedicated MRI scanner in radiation oncology for external beam radiation treatment planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paulson, Eric S., E-mail: epaulson@mcw.edu; Erickson, Beth; Schultz, Chris

Purpose: The use of magnetic resonance imaging (MRI) in radiation oncology is expanding rapidly, and more clinics are integrating MRI into their radiation therapy workflows. However, radiation therapy presents a new set of challenges and places additional constraints on MRI compared to diagnostic radiology that, if not properly addressed, can undermine the advantages MRI offers for radiation treatment planning (RTP). The authors introduce here strategies to manage several challenges of using MRI for virtual simulation in external beam RTP. Methods: A total of 810 clinical MRI simulation exams were performed using a dedicated MRI scanner for external beam RTP ofmore » brain, breast, cervix, head and neck, liver, pancreas, prostate, and sarcoma cancers. Patients were imaged in treatment position using MRI-optimal immobilization devices. Radiofrequency (RF) coil configurations and scan protocols were optimized based on RTP constraints. Off-resonance and gradient nonlinearity-induced geometric distortions were minimized or corrected prior to using images for RTP. A multidisciplinary MRI simulation guide, along with window width and level presets, was created to standardize use of MR images during RTP. A quality assurance program was implemented to maintain accuracy and repeatability of MRI simulation exams. Results: The combination of a large bore scanner, high field strength, and circumferentially wrapped, flexible phased array RF receive coils permitted acquisition of thin slice images with high contrast-to-noise ratio (CNR) and image intensity uniformity, while simultaneously accommodating patient setup and immobilization devices. Postprocessing corrections and alternative acquisition methods were required to reduce or correct off-resonance and gradient nonlinearity induced geometric distortions. Conclusions: The methodology described herein contains practical strategies the authors have implemented through lessons learned performing clinical MRI simulation exams. In their experience, these strategies provide robust, high fidelity, high contrast MR images suitable for external beam RTP.« less
Evaluation of B1 inhomogeneity effect on DCE-MRI data analysis of brain tumor patients at 3T.

PubMed

Sengupta, Anirban; Gupta, Rakesh Kumar; Singh, Anup

2017-12-02

Dynamic-contrast-enhanced (DCE) MRI data acquired using gradient echo based sequences is affected by errors in flip angle (FA) due to transmit B 1 inhomogeneity (B 1 inh). The purpose of the study was to evaluate the effect of B 1 inh on quantitative analysis of DCE-MRI data of human brain tumor patients and to evaluate the clinical significance of B 1 inh correction of perfusion parameters (PPs) on tumor grading. An MRI study was conducted on 35 glioma patients at 3T. The patients had histologically confirmed glioma with 23 high-grade (HG) and 12 low-grade (LG). Data for B 1 -mapping, T 1 -mapping and DCE-MRI were acquired. Relative B 1 maps (B 1rel ) were generated using the saturated-double-angle method. T 1 -maps were computed using the variable flip-angle method. Post-processing was performed for conversion of signal-intensity time (S(t)) curve to concentration-time (C(t)) curve followed by tracer kinetic analysis (K trans , Ve, Vp, Kep) and first pass analysis (CBV, CBF) using the general tracer-kinetic model. DCE-MRI data was analyzed without and with B 1 inh correction and errors in PPs were computed. Receiver-operating-characteristic (ROC) analysis was performed on HG and LG patients. Simulations were carried out to understand the effect of B 1 inhomogeneity on DCE-MRI data analysis in a systematic way. S(t) curves mimicking those in tumor tissue, were generated and FA errors were introduced followed by error analysis of PPs. Dependence of FA-based errors on the concentration of contrast agent and on the duration of DCE-MRI data was also studied. Simulations were also done to obtain K trans of glioma patients at different B 1rel values and see whether grading is affected or not. Current study shows that B 1rel value higher than nominal results in an overestimation of C(t) curves as well as derived PPs and vice versa. Moreover, at same B 1rel values, errors were large for larger values of C(t). Simulation results showed that grade of patients can change because of B 1 inh. B 1 inh in the human brain at 3T-MRI can introduce substantial errors in PPs derived from DCE-MRI data that might affect the accuracy of tumor grading, particularly for border zone cases. These errors can be mitigated using B 1 inh correction during DCE-MRI data analysis.
Self-regulation strategy, feedback timing and hemodynamic properties modulate learning in a simulated fMRI neurofeedback environment.

PubMed

Oblak, Ethan F; Lewis-Peacock, Jarrod A; Sulzer, James S

2017-07-01

Direct manipulation of brain activity can be used to investigate causal brain-behavior relationships. Current noninvasive neural stimulation techniques are too coarse to manipulate behaviors that correlate with fine-grained spatial patterns recorded by fMRI. However, these activity patterns can be manipulated by having people learn to self-regulate their own recorded neural activity. This technique, known as fMRI neurofeedback, faces challenges as many participants are unable to self-regulate. The causes of this non-responder effect are not well understood due to the cost and complexity of such investigation in the MRI scanner. Here, we investigated the temporal dynamics of the hemodynamic response measured by fMRI as a potential cause of the non-responder effect. Learning to self-regulate the hemodynamic response involves a difficult temporal credit-assignment problem because this signal is both delayed and blurred over time. Two factors critical to this problem are the prescribed self-regulation strategy (cognitive or automatic) and feedback timing (continuous or intermittent). Here, we sought to evaluate how these factors interact with the temporal dynamics of fMRI without using the MRI scanner. We first examined the role of cognitive strategies by having participants learn to regulate a simulated neurofeedback signal using a unidimensional strategy: pressing one of two buttons to rotate a visual grating that stimulates a model of visual cortex. Under these conditions, continuous feedback led to faster regulation compared to intermittent feedback. Yet, since many neurofeedback studies prescribe implicit self-regulation strategies, we created a computational model of automatic reward-based learning to examine whether this result held true for automatic processing. When feedback was delayed and blurred based on the hemodynamics of fMRI, this model learned more reliably from intermittent feedback compared to continuous feedback. These results suggest that different self-regulation mechanisms prefer different feedback timings, and that these factors can be effectively explored and optimized via simulation prior to deployment in the MRI scanner.
Self-regulation strategy, feedback timing and hemodynamic properties modulate learning in a simulated fMRI neurofeedback environment

PubMed Central

Sulzer, James S.

2017-01-01

Direct manipulation of brain activity can be used to investigate causal brain-behavior relationships. Current noninvasive neural stimulation techniques are too coarse to manipulate behaviors that correlate with fine-grained spatial patterns recorded by fMRI. However, these activity patterns can be manipulated by having people learn to self-regulate their own recorded neural activity. This technique, known as fMRI neurofeedback, faces challenges as many participants are unable to self-regulate. The causes of this non-responder effect are not well understood due to the cost and complexity of such investigation in the MRI scanner. Here, we investigated the temporal dynamics of the hemodynamic response measured by fMRI as a potential cause of the non-responder effect. Learning to self-regulate the hemodynamic response involves a difficult temporal credit-assignment problem because this signal is both delayed and blurred over time. Two factors critical to this problem are the prescribed self-regulation strategy (cognitive or automatic) and feedback timing (continuous or intermittent). Here, we sought to evaluate how these factors interact with the temporal dynamics of fMRI without using the MRI scanner. We first examined the role of cognitive strategies by having participants learn to regulate a simulated neurofeedback signal using a unidimensional strategy: pressing one of two buttons to rotate a visual grating that stimulates a model of visual cortex. Under these conditions, continuous feedback led to faster regulation compared to intermittent feedback. Yet, since many neurofeedback studies prescribe implicit self-regulation strategies, we created a computational model of automatic reward-based learning to examine whether this result held true for automatic processing. When feedback was delayed and blurred based on the hemodynamics of fMRI, this model learned more reliably from intermittent feedback compared to continuous feedback. These results suggest that different self-regulation mechanisms prefer different feedback timings, and that these factors can be effectively explored and optimized via simulation prior to deployment in the MRI scanner. PMID:28753639
SU-E-J-90: MRI-Based Treatment Simulation and Patient Setup for Radiation Therapy of Brain Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Y; Cao, M; Han, F

2014-06-01

Purpose: Traditional radiation therapy of cancer is heavily dependent on CT. CT provides excellent depiction of the bones but lacks good soft tissue contrast, which makes contouring difficult. Often, MRIs are fused with CT to take advantage of its superior soft tissue contrast. Such an approach has drawbacks. It is desirable to perform treatment simulation entirely based on MRI. To achieve MR-based simulation for radiation therapy, bone imaging is an important challenge because of the low MR signal intensity from bone due to its ultra-short T2 and T1, which presents difficulty for both dose calculation and patient setup in termsmore » of digitally reconstructed radiograph (DRR) generation. Current solutions will either require manual bone contouring or multiple MR scans. We present a technique to generate DRR using MRI with an Ultra Short Echo Time (UTE) sequence which is applicable to both OBI and ExacTrac 2D patient setup. Methods: Seven brain cancer patients were scanned at 1.5 Tesla using a radial UTE sequence. The sequence acquires two images at two different echo times. The two images were processed using in-house software. The resultant bone images were subsequently loaded into commercial systems to generate DRRs. Simulation and patient clinical on-board images were used to evaluate 2D patient setup with MRI-DRRs. Results: The majority bones are well visualized in all patients. The fused image of patient CT with the MR bone image demonstrates the accuracy of automatic bone identification using our technique. The generated DRR is of good quality. Accuracy of 2D patient setup by using MRI-DRR is comparable to CT-based 2D patient setup. Conclusion: This study shows the potential of DRR generation with single MR sequence. Further work will be needed on MR sequence development and post-processing procedure to achieve robust MR bone imaging for other human sites in addition to brain.« less
WE-G-BRD-06: Volumetric Cine MRI (VC-MRI) Estimated Based On Prior Knowledge for On-Board Target Localization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, W; Yin, F; Cai, J

Purpose: To develop a technique to generate on-board VC-MRI using patient prior 4D-MRI, motion modeling and on-board 2D-cine MRI for real-time 3D target verification of liver and lung radiotherapy. Methods: The end-expiration phase images of a 4D-MRI acquired during patient simulation are used as patient prior images. Principal component analysis (PCA) is used to extract 3 major respiratory deformation patterns from the Deformation Field Maps (DFMs) generated between end-expiration phase and all other phases. On-board 2D-cine MRI images are acquired in the axial view. The on-board VC-MRI at any instant is considered as a deformation of the prior MRI atmore » the end-expiration phase. The DFM is represented as a linear combination of the 3 major deformation patterns. The coefficients of the deformation patterns are solved by matching the corresponding 2D slice of the estimated VC-MRI with the acquired single 2D-cine MRI. The method was evaluated using both XCAT (a computerized patient model) simulation of lung cancer patients and MRI data from a real liver cancer patient. The 3D-MRI at every phase except end-expiration phase was used to simulate the ground-truth on-board VC-MRI at different instances, and the center-tumor slice was selected to simulate the on-board 2D-cine images. Results: Image subtraction of ground truth with estimated on-board VC-MRI shows fewer differences than image subtraction of ground truth with prior image. Excellent agreement between profiles was achieved. The normalized cross correlation coefficients between the estimated and ground-truth in the axial, coronal and sagittal views for each time step were >= 0.982, 0.905, 0.961 for XCAT data and >= 0.998, 0.911, 0.9541 for patient data. For XCAT data, the maximum-Volume-Percent-Difference between ground-truth and estimated tumor volumes was 1.6% and the maximum-Center-of-Mass-Shift was 0.9 mm. Conclusion: Preliminary studies demonstrated the feasibility to estimate real-time VC-MRI for on-board target localization before or during radiotherapy treatments. National Institutes of Health Grant No. R01-CA184173; Varian Medical System.« less
Methodology for functional MRI of simulated driving.

PubMed

Kan, Karen; Schweizer, Tom A; Tam, Fred; Graham, Simon J

2013-01-01

The developed world faces major socioeconomic and medical challenges associated with motor vehicle accidents caused by risky driving. Functional magnetic resonance imaging (fMRI) of individuals using virtual reality driving simulators may provide an important research tool to assess driving safety, based on brain activity and behavior. A fMRI-compatible driving simulator was developed and evaluated in the context of straight driving, turning, and stopping in 16 young healthy adults. Robust maps of brain activity were obtained, including activation of the primary motor cortex, cerebellum, visual cortex, and parietal lobe, with limited head motion (<1.5 mm deviation from mean head position in the superior∕inferior direction in all subjects) and only minor correlations between head motion, steering, or braking behavior. These results are consistent with previous literature and suggest that with care, fMRI of simulated driving is a feasible undertaking.
Dual-TRACER: High resolution fMRI with constrained evolution reconstruction.

PubMed

Li, Xuesong; Ma, Xiaodong; Li, Lyu; Zhang, Zhe; Zhang, Xue; Tong, Yan; Wang, Lihong; Sen Song; Guo, Hua

2018-01-01

fMRI with high spatial resolution is beneficial for studies in psychology and neuroscience, but is limited by various factors such as prolonged imaging time, low signal to noise ratio and scarcity of advanced facilities. Compressed Sensing (CS) based methods for accelerating fMRI data acquisition are promising. Other advanced algorithms like k-t FOCUSS or PICCS have been developed to improve performance. This study aims to investigate a new method, Dual-TRACER, based on Temporal Resolution Acceleration with Constrained Evolution Reconstruction (TRACER), for accelerating fMRI acquisitions using golden angle variable density spiral. Both numerical simulations and in vivo experiments at 3T were conducted to evaluate and characterize this method. Results show that Dual-TRACER can provide functional images with a high spatial resolution (1×1mm 2 ) under an acceleration factor of 20 while maintaining hemodynamic signals well. Compared with other investigated methods, dual-TRACER provides a better signal recovery, higher fMRI sensitivity and more reliable activation detection. Copyright © 2017 Elsevier Inc. All rights reserved.

BOLDSync: a MATLAB-based toolbox for synchronized stimulus presentation in functional MRI.

PubMed

Joshi, Jitesh; Saharan, Sumiti; Mandal, Pravat K

2014-02-15

Precise and synchronized presentation of paradigm stimuli in functional magnetic resonance imaging (fMRI) is central to obtaining accurate information about brain regions involved in a specific task. In this manuscript, we present a new MATLAB-based toolbox, BOLDSync, for synchronized stimulus presentation in fMRI. BOLDSync provides a user friendly platform for design and presentation of visual, audio, as well as multimodal audio-visual (AV) stimuli in functional imaging experiments. We present simulation experiments that demonstrate the millisecond synchronization accuracy of BOLDSync, and also illustrate the functionalities of BOLDSync through application to an AV fMRI study. BOLDSync gains an advantage over other available proprietary and open-source toolboxes by offering a user friendly and accessible interface that affords both precision in stimulus presentation and versatility across various types of stimulus designs and system setups. BOLDSync is a reliable, efficient, and versatile solution for synchronized stimulus presentation in fMRI study. Copyright © 2013 Elsevier B.V. All rights reserved.
Disrupted resting-state functional architecture of the brain after 45-day simulated microgravity

PubMed Central

Zhou, Yuan; Wang, Yun; Rao, Li-Lin; Liang, Zhu-Yuan; Chen, Xiao-Ping; Zheng, Dang; Tan, Cheng; Tian, Zhi-Qiang; Wang, Chun-Hui; Bai, Yan-Qiang; Chen, Shan-Guang; Li, Shu

2014-01-01

Long-term spaceflight induces both physiological and psychological changes in astronauts. To understand the neural mechanisms underlying these physiological and psychological changes, it is critical to investigate the effects of microgravity on the functional architecture of the brain. In this study, we used resting-state functional MRI (rs-fMRI) to study whether the functional architecture of the brain is altered after 45 days of −6° head-down tilt (HDT) bed rest, which is a reliable model for the simulation of microgravity. Sixteen healthy male volunteers underwent rs-fMRI scans before and after 45 days of −6° HDT bed rest. Specifically, we used a commonly employed graph-based measure of network organization, i.e., degree centrality (DC), to perform a full-brain exploration of the regions that were influenced by simulated microgravity. We subsequently examined the functional connectivities of these regions using a seed-based resting-state functional connectivity (RSFC) analysis. We found decreased DC in two regions, the left anterior insula (aINS) and the anterior part of the middle cingulate cortex (MCC; also called the dorsal anterior cingulate cortex in many studies), in the male volunteers after 45 days of −6° HDT bed rest. Furthermore, seed-based RSFC analyses revealed that a functional network anchored in the aINS and MCC was particularly influenced by simulated microgravity. These results provide evidence that simulated microgravity alters the resting-state functional architecture of the brains of males and suggest that the processing of salience information, which is primarily subserved by the aINS–MCC functional network, is particularly influenced by spaceflight. The current findings provide a new perspective for understanding the relationships between microgravity, cognitive function, autonomic neural function, and central neural activity. PMID:24926242
Enhancing 4D PC-MRI in an aortic phantom considering numerical simulations

NASA Astrophysics Data System (ADS)

Kratzke, Jonas; Schoch, Nicolai; Weis, Christian; Müller-Eschner, Matthias; Speidel, Stefanie; Farag, Mina; Beller, Carsten J.; Heuveline, Vincent

2015-03-01

To date, cardiovascular surgery enables the treatment of a wide range of aortic pathologies. One of the current challenges in this field is given by the detection of high-risk patients for adverse aortic events, who should be treated electively. Reliable diagnostic parameters, which indicate the urge of treatment, have to be determined. Functional imaging by means of 4D phase contrast-magnetic resonance imaging (PC-MRI) enables the time-resolved measurement of blood flow velocity in 3D. Applied to aortic phantoms, three dimensional blood flow properties and their relation to adverse dynamics can be investigated in vitro. Emerging "in silico" methods of numerical simulation can supplement these measurements in computing additional information on crucial parameters. We propose a framework that complements 4D PC-MRI imaging by means of numerical simulation based on the Finite Element Method (FEM). The framework is developed on the basis of a prototypic aortic phantom and validated by 4D PC-MRI measurements of the phantom. Based on physical principles of biomechanics, the derived simulation depicts aortic blood flow properties and characteristics. The framework might help identifying factors that induce aortic pathologies such as aortic dilatation or aortic dissection. Alarming thresholds of parameters such as wall shear stress distribution can be evaluated. The combined techniques of 4D PC-MRI and numerical simulation can be used as complementary tools for risk-stratification of aortic pathology.
SU-E-J-212: Identifying Bones From MRI: A Dictionary Learnign and Sparse Regression Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruan, D; Yang, Y; Cao, M

2014-06-01

Purpose: To develop an efficient and robust scheme to identify bony anatomy based on MRI-only simulation images. Methods: MRI offers important soft tissue contrast and functional information, yet its lack of correlation to electron-density has placed it as an auxiliary modality to CT in radiotherapy simulation and adaptation. An effective scheme to identify bony anatomy is an important first step towards MR-only simulation/treatment paradigm and would satisfy most practical purposes. We utilize a UTE acquisition sequence to achieve visibility of the bone. By contrast to manual + bulk or registration-to identify bones, we propose a novel learning-based approach for improvedmore » robustness to MR artefacts and environmental changes. Specifically, local information is encoded with MR image patch, and the corresponding label is extracted (during training) from simulation CT aligned to the UTE. Within each class (bone vs. nonbone), an overcomplete dictionary is learned so that typical patches within the proper class can be represented as a sparse combination of the dictionary entries. For testing, an acquired UTE-MRI is divided to patches using a sliding scheme, where each patch is sparsely regressed against both bone and nonbone dictionaries, and subsequently claimed to be associated with the class with the smaller residual. Results: The proposed method has been applied to the pilot site of brain imaging and it has showed general good performance, with dice similarity coefficient of greater than 0.9 in a crossvalidation study using 4 datasets. Importantly, it is robust towards consistent foreign objects (e.g., headset) and the artefacts relates to Gibbs and field heterogeneity. Conclusion: A learning perspective has been developed for inferring bone structures based on UTE MRI. The imaging setting is subject to minimal motion effects and the post-processing is efficient. The improved efficiency and robustness enables a first translation to MR-only routine. The scheme generalizes to multiple tissue classes.« less
Subject order-independent group ICA (SOI-GICA) for functional MRI data analysis.

PubMed

Zhang, Han; Zuo, Xi-Nian; Ma, Shuang-Ye; Zang, Yu-Feng; Milham, Michael P; Zhu, Chao-Zhe

2010-07-15

Independent component analysis (ICA) is a data-driven approach to study functional magnetic resonance imaging (fMRI) data. Particularly, for group analysis on multiple subjects, temporally concatenation group ICA (TC-GICA) is intensively used. However, due to the usually limited computational capability, data reduction with principal component analysis (PCA: a standard preprocessing step of ICA decomposition) is difficult to achieve for a large dataset. To overcome this, TC-GICA employs multiple-stage PCA data reduction. Such multiple-stage PCA data reduction, however, leads to variable outputs due to different subject concatenation orders. Consequently, the ICA algorithm uses the variable multiple-stage PCA outputs and generates variable decompositions. In this study, a rigorous theoretical analysis was conducted to prove the existence of such variability. Simulated and real fMRI experiments were used to demonstrate the subject-order-induced variability of TC-GICA results using multiple PCA data reductions. To solve this problem, we propose a new subject order-independent group ICA (SOI-GICA). Both simulated and real fMRI data experiments demonstrated the high robustness and accuracy of the SOI-GICA results compared to those of traditional TC-GICA. Accordingly, we recommend SOI-GICA for group ICA-based fMRI studies, especially those with large data sets. Copyright 2010 Elsevier Inc. All rights reserved.
Simulation study of the second-generation MR-compatible SPECT system based on the inverted compound-eye gamma camera design

NASA Astrophysics Data System (ADS)

Lai, Xiaochun; Meng, Ling-Jian

2018-02-01

In this paper, we present simulation studies for the second-generation MRI compatible SPECT system, MRC-SPECT-II, based on an inverted compound eye (ICE) gamma camera concept. The MRC-SPECT-II system consists of a total of 1536 independent micro-pinhole-camera-elements (MCEs) distributed in a ring with an inner diameter of 6 cm. This system provides a FOV of 1 cm diameter and a peak geometrical efficiency of approximately 1.3% (the typical levels of 0.1%-0.01% found in modern pre-clinical SPECT instrumentations), while maintaining a sub-500 μm spatial resolution. Compared to the first-generation MRC-SPECT system (MRC-SPECT-I) (Cai 2014 Nucl. Instrum. Methods Phys. Res. A 734 147-51) developed in our lab, the MRC-SPECT-II system offers a similar resolution with dramatically improved sensitivity and greatly reduced physical dimension. The latter should allow the system to be placed inside most clinical and pre-clinical MRI scanners for high-performance simultaneous MRI and SPECT imaging.
Numerical investigations of MRI RF field induced heating for external fixation devices

PubMed Central

2013-01-01

Background The magnetic resonance imaging (MRI) radio frequency (RF) field induced heating on external fixation devices can be very high in the vicinity of device screws. Such induced RF heating is related to device constructs, device placements, as well as the device insertion depth into human subjects. In this study, computational modeling is performed to determine factors associated with such induced heating. Methods Numerical modeling, based on the finite-difference time-domain (FDTD) method, is used to evaluate the temperature rises near external device screw tips inside the ASTM phantom for both 1.5-T and 3-T MRI systems. The modeling approach consists of 1) the development of RF coils for 1.5-T and 3-T, 2) the electromagnetic simulations of energy deposition near the screw tips of external fixation devices, and 3) the thermal simulations of temperature rises near the tips of these devices. Results It is found that changing insertion depth and screw spacing could largely affect the heating of these devices. In 1.5-T MRI system, smaller insertion depth and larger pin spacing will lead to higher temperature rise. However, for 3-T MRI system, the relation is not very clear when insertion depth is larger than 5 cm or when pin spacing became larger than 20 cm. The effect of connection bar material on device heating is also studied and the heating mechanism of the device is analysed. Conclusions Numerical simulation is used to study RF heating for external fixation devices in both 1.5-T and 3-T MRI coils. Typically, shallower insertion depth and larger pin spacing with conductive bar lead to higher RF heating. The heating mechanism is explained using induced current along the device and power decay inside ASTM phantom. PMID:23394173
Quantifying Turbulent Kinetic Energy in an Aortic Coarctation with Large Eddy Simulation and Magnetic Resonance Imaging

NASA Astrophysics Data System (ADS)

Lantz, Jonas; Ebbers, Tino; Karlsson, Matts

2012-11-01

In this study, turbulent kinetic energy (TKE) in an aortic coarctation was studied using both a numerical technique (large eddy simulation, LES) and in vivo measurements using magnetic resonance imaging (MRI). High levels of TKE are undesirable, as kinetic energy is extracted from the mean flow to feed the turbulent fluctuations. The patient underwent surgery to widen the coarctation, and the flow before and after surgery was computed and compared to MRI measurements. The resolution of the MRI was about 7 × 7 voxels in axial cross-section while 50x50 mesh cells with increased resolution near the walls was used in the LES simulation. In general, the numerical simulations and MRI measurements showed that the aortic arch had no or very low levels of TKE, while elevated values were found downstream the coarctation. It was also found that TKE levels after surgery were lowered, indicating that the diameter of the constriction was increased enough to decrease turbulence effects. In conclusion, both the numerical simulation and MRI measurements gave very similar results, thereby validating the simulations and suggesting that MRI measured TKE can be used as an initial estimation in clinical practice, while LES results can be used for detailed quantification and further research of aortic flows.
Simultaneous CT-MRI Reconstruction for Constrained Imaging Geometries using Structural Coupling and Compressive Sensing

PubMed Central

Xi, Yan; Zhao, Jun; Bennett, James R.; Stacy, Mitchel R.; Sinusas, Albert J.; Wang, Ge

2016-01-01

Objective A unified reconstruction framework is presented for simultaneous CT-MRI reconstruction. Significance Combined CT-MRI imaging has the potential for improved results in existing preclinical and clinical applications, as well as opening novel research directions for future applications. Methods In an ideal CT-MRI scanner, CT and MRI acquisitions would occur simultaneously, and hence would be inherently registered in space and time. Alternatively, separately acquired CT and MRI scans can be fused to simulate an instantaneous acquisition. In this study, structural coupling and compressive sensing techniques are combined to unify CT and MRI reconstructions. A bidirectional image estimation method was proposed to connect images from different modalities. Hence, CT and MRI data serve as prior knowledge to each other for better CT and MRI image reconstruction than what could be achieved with separate reconstruction. Results Our integrated reconstruction methodology is demonstrated with numerical phantom and real-dataset based experiments, and has yielded promising results. PMID:26672028
Inferring multi-scale neural mechanisms with brain network modelling

PubMed Central

Schirner, Michael; McIntosh, Anthony Randal; Jirsa, Viktor; Deco, Gustavo

2018-01-01

The neurophysiological processes underlying non-invasive brain activity measurements are incompletely understood. Here, we developed a connectome-based brain network model that integrates individual structural and functional data with neural population dynamics to support multi-scale neurophysiological inference. Simulated populations were linked by structural connectivity and, as a novelty, driven by electroencephalography (EEG) source activity. Simulations not only predicted subjects' individual resting-state functional magnetic resonance imaging (fMRI) time series and spatial network topologies over 20 minutes of activity, but more importantly, they also revealed precise neurophysiological mechanisms that underlie and link six empirical observations from different scales and modalities: (1) resting-state fMRI oscillations, (2) functional connectivity networks, (3) excitation-inhibition balance, (4, 5) inverse relationships between α-rhythms, spike-firing and fMRI on short and long time scales, and (6) fMRI power-law scaling. These findings underscore the potential of this new modelling framework for general inference and integration of neurophysiological knowledge to complement empirical studies. PMID:29308767
Fully Bayesian inference for structural MRI: application to segmentation and statistical analysis of T2-hypointensities.

PubMed

Schmidt, Paul; Schmid, Volker J; Gaser, Christian; Buck, Dorothea; Bührlen, Susanne; Förschler, Annette; Mühlau, Mark

2013-01-01

Aiming at iron-related T2-hypointensity, which is related to normal aging and neurodegenerative processes, we here present two practicable approaches, based on Bayesian inference, for preprocessing and statistical analysis of a complex set of structural MRI data. In particular, Markov Chain Monte Carlo methods were used to simulate posterior distributions. First, we rendered a segmentation algorithm that uses outlier detection based on model checking techniques within a Bayesian mixture model. Second, we rendered an analytical tool comprising a Bayesian regression model with smoothness priors (in the form of Gaussian Markov random fields) mitigating the necessity to smooth data prior to statistical analysis. For validation, we used simulated data and MRI data of 27 healthy controls (age: [Formula: see text]; range, [Formula: see text]). We first observed robust segmentation of both simulated T2-hypointensities and gray-matter regions known to be T2-hypointense. Second, simulated data and images of segmented T2-hypointensity were analyzed. We found not only robust identification of simulated effects but also a biologically plausible age-related increase of T2-hypointensity primarily within the dentate nucleus but also within the globus pallidus, substantia nigra, and red nucleus. Our results indicate that fully Bayesian inference can successfully be applied for preprocessing and statistical analysis of structural MRI data.
In vivo electric conductivity of cervical cancer patients based on B₁⁺ maps at 3T MRI.

PubMed

Balidemaj, E; de Boer, P; van Lier, A L H M W; Remis, R F; Stalpers, L J A; Westerveld, G H; Nederveen, A J; van den Berg, C A T; Crezee, J

2016-02-21

The in vivo electric conductivity (σ) values of tissue are essential for accurate electromagnetic simulations and specific absorption rate (SAR) assessment for applications such as thermal dose computations in hyperthermia. Currently used σ-values are mostly based on ex vivo measurements. In this study the conductivity of human muscle, bladder content and cervical tumors is acquired non-invasively in vivo using MRI. The conductivity of 20 cervical cancer patients was measured with the MR-based electric properties tomography method on a standard 3T MRI system. The average in vivo σ-value of muscle is 14% higher than currently used in human simulation models. The σ-value of bladder content is an order of magnitude higher than the value for bladder wall tissue that is used for the complete bladder in many models. Our findings are confirmed by various in vivo animal studies from the literature. In cervical tumors, the observed average conductivity was 13% higher than the literature value reported for cervical tissue. Considerable deviations were found for the electrical conductivity observed in this study and the commonly used values for SAR assessment, emphasizing the importance of acquiring in vivo conductivity for more accurate SAR assessment in various applications.
Efficient Blockwise Permutation Tests Preserving Exchangeability

PubMed Central

Zhou, Chunxiao; Zwilling, Chris E.; Calhoun, Vince D.; Wang, Michelle Y.

2014-01-01

In this paper, we present a new blockwise permutation test approach based on the moments of the test statistic. The method is of importance to neuroimaging studies. In order to preserve the exchangeability condition required in permutation tests, we divide the entire set of data into certain exchangeability blocks. In addition, computationally efficient moments-based permutation tests are performed by approximating the permutation distribution of the test statistic with the Pearson distribution series. This involves the calculation of the first four moments of the permutation distribution within each block and then over the entire set of data. The accuracy and efficiency of the proposed method are demonstrated through simulated experiment on the magnetic resonance imaging (MRI) brain data, specifically the multi-site voxel-based morphometry analysis from structural MRI (sMRI). PMID:25289113
Registration of 3D ultrasound computer tomography and MRI for evaluation of tissue correspondences

NASA Astrophysics Data System (ADS)

Hopp, T.; Dapp, R.; Zapf, M.; Kretzek, E.; Gemmeke, H.; Ruiter, N. V.

2015-03-01

3D Ultrasound Computer Tomography (USCT) is a new imaging method for breast cancer diagnosis. In the current state of development it is essential to correlate USCT with a known imaging modality like MRI to evaluate how different tissue types are depicted. Due to different imaging conditions, e.g. with the breast subject to buoyancy in USCT, a direct correlation is demanding. We present a 3D image registration method to reduce positioning differences and allow direct side-by-side comparison of USCT and MRI volumes. It is based on a two-step approach including a buoyancy simulation with a biomechanical model and free form deformations using cubic B-Splines for a surface refinement. Simulation parameters are optimized patient-specifically in a simulated annealing scheme. The method was evaluated with in-vivo datasets resulting in an average registration error below 5mm. Correlating tissue structures can thereby be located in the same or nearby slices in both modalities and three-dimensional non-linear deformations due to the buoyancy are reduced. Image fusion of MRI volumes and USCT sound speed volumes was performed for intuitive display. By applying the registration to data of our first in-vivo study with the KIT 3D USCT, we could correlate several tissue structures in MRI and USCT images and learn how connective tissue, carcinomas and breast implants observed in the MRI are depicted in the USCT imaging modes.
SU-E-J-193: Feasibility of MRI-Only Based IMRT Planning for Pancreatic Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prior, P; Botros, M; Chen, X

2014-06-01

Purpose: With the increasing use of MRI simulation and the advent of MRI-guided delivery, it is desirable to use MRI only for treatment planning. In this study, we assess the dosimetric difference between MRI- and CTbased IMRT planning for pancreatic cancer. Methods: Planning CTs and MRIs acquired for a representative pancreatic cancer patient were used. MRI-based planning utilized forced relative electron density (rED) assignment of organ specific values from IRCU report 46, where rED = 1.029 for PTV and a rED = 1.036 for non-specified tissue (NST). Six IMRT plans were generated with clinical dose-volume (DV) constraints using a researchmore » Monaco planning system employing Monte Carlo dose calculation with optional perpendicular magnetic field (MF) of 1.5T. The following five plans were generated and compared with the planning CT: 1.) CT plan with MF and dose recalculation without optimization; 2.) MRI (T2) plan with target and OARs redrawn based on MRI, forced rED, no MF, and recalculation without optimization; 3.) Similar as in 2 but with MF; 4.) MRI plan with MF but without optimization; and 5.) Similar as in 4 but with optimization. Results: Generally, noticeable differences in PTV point doses and DV parameters (DVPs) between the CT-and MRI-based plans with and without the MF were observed. These differences between the optimized plans were generally small, mostly within 2%. Larger differences were observed in point doses and mean doses for certain OARs between the CT and MRI plan, mostly due to differences between image acquisition times. Conclusion: MRI only based IMRT planning for pancreatic cancer is feasible. The differences observed between the optimized CT and MRI plans with or without the MF were practically negligible if excluding the differences between MRI and CT defined structures.« less
Comparison of velocity patterns in an AComA aneurysm measured with 2D phase contrast MRI and simulated with CFD.

PubMed

Karmonik, Christof; Klucznik, Richard; Benndorf, Goetz

2008-01-01

Computational Fluid Dynamic (CFD) is increasingly being used for modeling hemodynamics in intracranial aneurysms. While CFD techniques are well established, need for validation of the results remains. By quantifying features in velocity patterns measured with 2D phase contrast magnetic resonance (pcMRI) in vivo and simulated with CFD, the role of pcMRI for providing reference data for the CFD simulation is explored. Unsteady CFD simulations were performed with inflow boundary conditions obtained from 2D pcMRI measurements of an aneurysm of the anterior communication artery. Intra-aneurysmal velocity profiles were recorded with 2D pcMRI and calculated with CFD. Relative areas of positive and negative velocity were calculated in these profiles for maximum and minimum inflow. Areas of positive and of negative velocity similar in shape were found in the velocity profiles obtained with both methods. Relative difference in size of the relative areas for the whole cardiac cycle ranged from 1%-25% (average 12%). 2D pcMRI is able to record velocity profiles in an aneurysm of the anterior commuting artery in vivo. These velocity profiles can serve as reference data for validation of CFD simulations. Further studies are needed to explore the role of pcMRI in the context of CFD simulations.
Edge-oriented dual-dictionary guided enrichment (EDGE) for MRI-CT image reconstruction.

PubMed

Li, Liang; Wang, Bigong; Wang, Ge

2016-01-01

In this paper, we formulate the joint/simultaneous X-ray CT and MRI image reconstruction. In particular, a novel algorithm is proposed for MRI image reconstruction from highly under-sampled MRI data and CT images. It consists of two steps. First, a training dataset is generated from a series of well-registered MRI and CT images on the same patients. Then, an initial MRI image of a patient can be reconstructed via edge-oriented dual-dictionary guided enrichment (EDGE) based on the training dataset and a CT image of the patient. Second, an MRI image is reconstructed using the dictionary learning (DL) algorithm from highly under-sampled k-space data and the initial MRI image. Our algorithm can establish a one-to-one correspondence between the two imaging modalities, and obtain a good initial MRI estimation. Both noise-free and noisy simulation studies were performed to evaluate and validate the proposed algorithm. The results with different under-sampling factors show that the proposed algorithm performed significantly better than those reconstructed using the DL algorithm from MRI data alone.
ROCKETSHIP: a flexible and modular software tool for the planning, processing and analysis of dynamic MRI studies.

PubMed

Barnes, Samuel R; Ng, Thomas S C; Santa-Maria, Naomi; Montagne, Axel; Zlokovic, Berislav V; Jacobs, Russell E

2015-06-16

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a promising technique to characterize pathology and evaluate treatment response. However, analysis of DCE-MRI data is complex and benefits from concurrent analysis of multiple kinetic models and parameters. Few software tools are currently available that specifically focuses on DCE-MRI analysis with multiple kinetic models. Here, we developed ROCKETSHIP, an open-source, flexible and modular software for DCE-MRI analysis. ROCKETSHIP incorporates analyses with multiple kinetic models, including data-driven nested model analysis. ROCKETSHIP was implemented using the MATLAB programming language. Robustness of the software to provide reliable fits using multiple kinetic models is demonstrated using simulated data. Simulations also demonstrate the utility of the data-driven nested model analysis. Applicability of ROCKETSHIP for both preclinical and clinical studies is shown using DCE-MRI studies of the human brain and a murine tumor model. A DCE-MRI software suite was implemented and tested using simulations. Its applicability to both preclinical and clinical datasets is shown. ROCKETSHIP was designed to be easily accessible for the beginner, but flexible enough for changes or additions to be made by the advanced user as well. The availability of a flexible analysis tool will aid future studies using DCE-MRI. A public release of ROCKETSHIP is available at https://github.com/petmri/ROCKETSHIP .
A Technique for Generating Volumetric Cine-Magnetic Resonance Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, Wendy; Ren, Lei, E-mail: lei.ren@duke.edu; Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina

Purpose: The purpose of this study was to develop a techique to generate on-board volumetric cine-magnetic resonance imaging (VC-MRI) using patient prior images, motion modeling, and on-board 2-dimensional cine MRI. Methods and Materials: One phase of a 4-dimensional MRI acquired during patient simulation is used as patient prior images. Three major respiratory deformation patterns of the patient are extracted from 4-dimensional MRI based on principal-component analysis. The on-board VC-MRI at any instant is considered as a deformation of the prior MRI. The deformation field is represented as a linear combination of the 3 major deformation patterns. The coefficients of themore » deformation patterns are solved by the data fidelity constraint using the acquired on-board single 2-dimensional cine MRI. The method was evaluated using both digital extended-cardiac torso (XCAT) simulation of lung cancer patients and MRI data from 4 real liver cancer patients. The accuracy of the estimated VC-MRI was quantitatively evaluated using volume-percent-difference (VPD), center-of-mass-shift (COMS), and target tracking errors. Effects of acquisition orientation, region-of-interest (ROI) selection, patient breathing pattern change, and noise on the estimation accuracy were also evaluated. Results: Image subtraction of ground-truth with estimated on-board VC-MRI shows fewer differences than image subtraction of ground-truth with prior image. Agreement between normalized profiles in the estimated and ground-truth VC-MRI was achieved with less than 6% error for both XCAT and patient data. Among all XCAT scenarios, the VPD between ground-truth and estimated lesion volumes was, on average, 8.43 ± 1.52% and the COMS was, on average, 0.93 ± 0.58 mm across all time steps for estimation based on the ROI region in the sagittal cine images. Matching to ROI in the sagittal view achieved better accuracy when there was substantial breathing pattern change. The technique was robust against noise levels up to SNR = 20. For patient data, average tracking errors were less than 2 mm in all directions for all patients. Conclusions: Preliminary studies demonstrated the feasibility of generating real-time VC-MRI for on-board localization of moving targets in radiation therapy.« less
Musculoskeletal Simulation Model Generation from MRI Data Sets and Motion Capture Data

NASA Astrophysics Data System (ADS)

Schmid, Jérôme; Sandholm, Anders; Chung, François; Thalmann, Daniel; Delingette, Hervé; Magnenat-Thalmann, Nadia

Today computer models and computer simulations of the musculoskeletal system are widely used to study the mechanisms behind human gait and its disorders. The common way of creating musculoskeletal models is to use a generic musculoskeletal model based on data derived from anatomical and biomechanical studies of cadaverous specimens. To adapt this generic model to a specific subject, the usual approach is to scale it. This scaling has been reported to introduce several errors because it does not always account for subject-specific anatomical differences. As a result, a novel semi-automatic workflow is proposed that creates subject-specific musculoskeletal models from magnetic resonance imaging (MRI) data sets and motion capture data. Based on subject-specific medical data and a model-based automatic segmentation approach, an accurate modeling of the anatomy can be produced while avoiding the scaling operation. This anatomical model coupled with motion capture data, joint kinematics information, and muscle-tendon actuators is finally used to create a subject-specific musculoskeletal model.

Complex-Difference Constrained Compressed Sensing Reconstruction for Accelerated PRF Thermometry with Application to MRI Induced RF Heating

PubMed Central

Cao, Zhipeng; Oh, Sukhoon; Otazo, Ricardo; Sica, Christopher T.; Griswold, Mark A.; Collins, Christopher M.

2014-01-01

Purpose Introduce a novel compressed sensing reconstruction method to accelerate proton resonance frequency (PRF) shift temperature imaging for MRI induced radiofrequency (RF) heating evaluation. Methods A compressed sensing approach that exploits sparsity of the complex difference between post-heating and baseline images is proposed to accelerate PRF temperature mapping. The method exploits the intra- and inter-image correlations to promote sparsity and remove shared aliasing artifacts. Validations were performed on simulations and retrospectively undersampled data acquired in ex-vivo and in-vivo studies by comparing performance with previously proposed techniques. Results The proposed complex difference constrained compressed sensing reconstruction method improved the reconstruction of smooth and local PRF temperature change images compared to various available reconstruction methods in a simulation study, a retrospective study with heating of a human forearm in vivo, and a retrospective study with heating of a sample of beef ex vivo . Conclusion Complex difference based compressed sensing with utilization of a fully-sampled baseline image improves the reconstruction accuracy for accelerated PRF thermometry. It can be used to improve the volumetric coverage and temporal resolution in evaluation of RF heating due to MRI, and may help facilitate and validate temperature-based methods for safety assurance. PMID:24753099
Gd-EOB-DTPA-enhanced MRI is better than MDCT in decision making of curative treatment for hepatocellular carcinoma.

PubMed

Yoo, Sun Hong; Choi, Jong Young; Jang, Jeong Won; Bae, Si Hyun; Yoon, Seung Kew; Kim, Dong Goo; Yoo, Young Kyoung; Rha, Sung Eun; Lee, Young Joon; Jung, Eun Sun

2013-09-01

We assessed the change in the therapeutic decision among curative treatments after adding Gd-EOB-DTPA-enhanced MRI to triple-phase MDCT for patients with early-stage HCC. This study retrospectively investigated two groups: 33 pathologically confirmed HCC patients after liver transplantation in group 1; 34 HCC patients without pathology in group 2. In group 1, we simulated the therapeutic decision-making process by pretransplant MDCT and Gd-EOB-DTPA-enhanced MRI. In group 2, including the 34 early-stage HCC patients consecutively enrolled, we investigated the change of therapeutic decision after adding Gd-EOB-DTPA-enhanced MRI to MDCT. In the simulation from group 1, after adding Gd-EOB-DTPA-enhanced MRI, 33.3% (11/33 patients) of treatment decisions were changed from the decision based on MDCT alone. Among 22 patients considered eligible for resection and 33 patients for radiofrequency ablation, the therapeutic decision was changed for 10 patients in the surgical group and 4 patients for the RFA group (45.5 and 12.1%). In group 2, the rate of change in the therapeutic decision after adding Gd-EOB-DTPA-enhanced MRI to MDCT was 41.2% (14/34 patients). In group 1 with explants pathology, the median diameter of HCCs not detected by MDCT but detected by Gd-EOB-DTPA-enhanced MRI was 1.15 cm (0.3-3.0 cm). The median diameter of HCCs seen only in the explanted liver was 1.0 cm (0.3-1.7 cm), and 60.7% of them were well-differentiated HCCs. This study suggests that performing Gd-EOB-DTPA-enhanced MRI before deciding on curative treatment for early-stage HCC may improve the accuracy of treatment decision for early-stage HCC.
A methodology to investigate the impact of image distortions on the radiation dose when using magnetic resonance images for planning

NASA Astrophysics Data System (ADS)

Yan, Yue; Yang, Jinzhong; Beddar, Sam; Ibbott, Geoffrey; Wen, Zhifei; Court, Laurence E.; Hwang, Ken-Pin; Kadbi, Mo; Krishnan, Sunil; Fuller, Clifton D.; Frank, Steven J.; Yang, James; Balter, Peter; Kudchadker, Rajat J.; Wang, Jihong

2018-04-01

We developed a novel technique to study the impact of geometric distortion of magnetic resonance imaging (MRI) on intensity-modulated radiation therapy treatment planning. The measured 3D datasets of residual geometric distortion (a 1.5 T MRI component of an MRI linear accelerator system) was fitted with a second-order polynomial model to map the spatial dependence of geometric distortions. Then the geometric distortion model was applied to computed tomography (CT) image and structure data to simulate the distortion of MRI data and structures. Fourteen CT-based treatment plans were selected from patients treated for gastrointestinal, genitourinary, thoracic, head and neck, or spinal tumors. Plans based on the distorted CT and structure data were generated (as the distorted plans). Dose deviations of the distorted plans were calculated and compared with the original plans to study the dosimetric impact of MRI distortion. The MRI geometric distortion led to notable dose deviations in five of the 14 patients, causing loss of target coverage of up to 3.68% and dose deviations to organs at risk in three patients, increasing the mean dose to the chest wall by up to 6.19 Gy in a gastrointestinal patient, and increases the maximum dose to the lung by 5.17 Gy in a thoracic patient.
Accelerating volumetric cine MRI (VC-MRI) using undersampling for real-time 3D target localization/tracking in radiation therapy: a feasibility study

NASA Astrophysics Data System (ADS)

Harris, Wendy; Yin, Fang-Fang; Wang, Chunhao; Zhang, You; Cai, Jing; Ren, Lei

2018-01-01

Purpose. To accelerate volumetric cine MRI (VC-MRI) using undersampled 2D-cine MRI to provide real-time 3D guidance for gating/target tracking in radiotherapy. Methods. 4D-MRI is acquired during patient simulation. One phase of the prior 4D-MRI is selected as the prior images, designated as MRIprior. The on-board VC-MRI at each time-step is considered a deformation of the MRIprior. The deformation field map is represented as a linear combination of the motion components extracted by principal component analysis from the prior 4D-MRI. The weighting coefficients of the motion components are solved by matching the corresponding 2D-slice of the VC-MRI with the on-board undersampled 2D-cine MRI acquired. Undersampled Cartesian and radial k-space acquisition strategies were investigated. The effects of k-space sampling percentage (SP) and distribution, tumor sizes and noise on the VC-MRI estimation were studied. The VC-MRI estimation was evaluated using XCAT simulation of lung cancer patients and data from liver cancer patients. Volume percent difference (VPD) and Center of Mass Shift (COMS) of the tumor volumes and tumor tracking errors were calculated. Results. For XCAT, VPD/COMS were 11.93 ± 2.37%/0.90 ± 0.27 mm and 11.53 ± 1.47%/0.85 ± 0.20 mm among all scenarios with Cartesian sampling (SP = 10%) and radial sampling (21 spokes, SP = 5.2%), respectively. When tumor size decreased, higher sampling rate achieved more accurate VC-MRI than lower sampling rate. VC-MRI was robust against noise levels up to SNR = 20. For patient data, the tumor tracking errors in superior-inferior, anterior-posterior and lateral (LAT) directions were 0.46 ± 0.20 mm, 0.56 ± 0.17 mm and 0.23 ± 0.16 mm, respectively, for Cartesian-based sampling with SP = 20% and 0.60 ± 0.19 mm, 0.56 ± 0.22 mm and 0.42 ± 0.15 mm, respectively, for radial-based sampling with SP = 8% (32 spokes). Conclusions. It is feasible to estimate VC-MRI from a single undersampled on-board 2D cine MRI. Phantom and patient studies showed that the temporal resolution of VC-MRI can potentially be improved by 5-10 times using a 2D cine image acquired with 10-20% k-space sampling.
BlochSolver: A GPU-optimized fast 3D MRI simulator for experimentally compatible pulse sequences

NASA Astrophysics Data System (ADS)

Kose, Ryoichi; Kose, Katsumi

2017-08-01

A magnetic resonance imaging (MRI) simulator, which reproduces MRI experiments using computers, has been developed using two graphic-processor-unit (GPU) boards (GTX 1080). The MRI simulator was developed to run according to pulse sequences used in experiments. Experiments and simulations were performed to demonstrate the usefulness of the MRI simulator for three types of pulse sequences, namely, three-dimensional (3D) gradient-echo, 3D radio-frequency spoiled gradient-echo, and gradient-echo multislice with practical matrix sizes. The results demonstrated that the calculation speed using two GPU boards was typically about 7 TFLOPS and about 14 times faster than the calculation speed using CPUs (two 18-core Xeons). We also found that MR images acquired by experiment could be reproduced using an appropriate number of subvoxels, and that 3D isotropic and two-dimensional multislice imaging experiments for practical matrix sizes could be simulated using the MRI simulator. Therefore, we concluded that such powerful MRI simulators are expected to become an indispensable tool for MRI research and development.
On the origin of the Monoceros Ring - I. Kinematics, proper motions, and the nature of the progenitor

NASA Astrophysics Data System (ADS)

Guglielmo, Magda; Lane, Richard R.; Conn, Blair C.; Ho, Anna Y. Q.; Ibata, Rodrigo A.; Lewis, Geraint F.

2018-03-01

The Monoceros Ring (MRi) structure is an apparent stellar overdensity that has been postulated to entirely encircle the Galactic plane and has been variously described as being due to line-of-sight effects of the Galactic warp and flare or of extragalactic origin (via accretion). Despite being intensely scrutinized in the literature for more than a decade, no studies to date have been able to definitively uncover its origins. Here we use N-body simulations and a genetic algorithm to explore the parameter space for the initial position, orbital parameters, and, for the first time, the final location of a satellite progenitor. We fit our models to the latest Pan-STARRS data to determine whether an accretion scenario is capable of producing an in-plane ring-like structure matching the known parameters of the MRi. Our simulations produce streams that closely match the location, proper motion, and kinematics of the MRi structure. However, we are not able to reproduce the mass estimates from earlier studies based on Pan-STARRS data. Furthermore, in contrast to earlier studies, our best-fitting models are those for progenitors on retrograde orbits. If the MRi was produced by satellite accretion, we find that its progenitor has an initial mass upper limit of ˜1010 M⊙ and the remnant is likely located behind the Galactic bulge, making it difficult to locate observationally. While our models produce realistic MRi-like structures, we cannot definitively conclude that the MRi was produced by the accretion of a satellite galaxy.
MRI-Based Computational Fluid Dynamics in Experimental Vascular Models: Toward the Development of an Approach for Prediction of Cardiovascular Changes During Prolonged Space Missions

NASA Technical Reports Server (NTRS)

Spirka, T. A.; Myers, J. G.; Setser, R. M.; Halliburton, S. S.; White, R. D.; Chatzimavroudis, G. P.

2005-01-01

A priority of NASA is to identify and study possible risks to astronauts health during prolonged space missions [l]. The goal is to develop a procedure for a preflight evaluation of the cardiovascular system of an astronaut and to forecast how it will be affected during the mission. To predict these changes, a computational cardiovascular model must be constructed. Although physiology data can be used to make a general model, a more desirable subject-specific model requires anatomical, functional, and flow data from the specific astronaut. MRI has the unique advantage of providing images with all of the above information, including three-directional velocity data which can be used as boundary conditions in a computational fluid dynamics (CFD) program [2,3]. MRI-based CFD is very promising for reproduction of the flow patterns of a specific subject and prediction of changes in the absence of gravity. The aim of this study was to test the feasibility of this approach by reconstructing the geometry of MRI-scanned arterial models and reproducing the MRI-measured velocities using CFD simulations on these geometries.
A Review of Numerical Simulation and Analytical Modeling for Medical Devices Safety in MRI

PubMed Central

Kabil, J.; Belguerras, L.; Trattnig, S.; Pasquier, C.; Missoffe, A.

2016-01-01

Summary Objectives To review past and present challenges and ongoing trends in numerical simulation for MRI (Magnetic Resonance Imaging) safety evaluation of medical devices. Methods A wide literature review on numerical and analytical simulation on simple or complex medical devices in MRI electromagnetic fields shows the evolutions through time and a growing concern for MRI safety over the years. Major issues and achievements are described, as well as current trends and perspectives in this research field. Results Numerical simulation of medical devices is constantly evolving, supported by calculation methods now well-established. Implants with simple geometry can often be simulated in a computational human model, but one issue remaining today is the experimental validation of these human models. A great concern is to assess RF heating on implants too complex to be traditionally simulated, like pacemaker leads. Thus, ongoing researches focus on alternative hybrids methods, both numerical and experimental, with for example a transfer function method. For the static field and gradient fields, analytical models can be used for dimensioning simple implants shapes, but limited for complex geometries that cannot be studied with simplifying assumptions. Conclusions Numerical simulation is an essential tool for MRI safety testing of medical devices. The main issues remain the accuracy of simulations compared to real life and the studies of complex devices; but as the research field is constantly evolving, some promising ideas are now under investigation to take up the challenges. PMID:27830244
Computed tomography-magnetic resonance image fusion: a clinical evaluation of an innovative approach for improved tumor localization in primary central nervous system lesions.

PubMed

Lattanzi, J P; Fein, D A; McNeeley, S W; Shaer, A H; Movsas, B; Hanks, G E

1997-01-01

We describe our initial experience with the AcQSim (Picker International, St. David, PA) computed tomography-magnetic resonance imaging (CT-MRI) fusion software in eight patients with intracranial lesions. MRI data are electronically integrated into the CT-based treatment planning system. Since MRI is superior to CT in identifying intracranial abnormalities, we evaluated the precision and feasibility of this new localization method. Patients initially underwent CT simulation from C2 to the most superior portion of the scalp. T2 and post-contrast T1-weighted MRI of this area was then performed. Patient positioning was duplicated utilizing a head cup and bridge of nose to forehead angle measurements. First, a gross tumor volume (GTV) was identified utilizing the CT (CT/GTV). The CT and MRI scans were subsequently fused utilizing a point pair matching method and a second GTV (CT-MRI/GTV) was contoured with the aid of both studies. The fusion process was uncomplicated and completed in a timely manner. Volumetric analysis revealed the CT-MRI/GTV to be larger than the CT/GTV in all eight cases. The mean CT-MRI/GTV was 28.7 cm3 compared to 16.7 cm3 by CT alone. This translated into a 72% increase in the radiographic tumor volume by CT-MRI. A simulated dose-volume histogram in two patients revealed that marginal portions of the lesion, as identified by CT and MRI, were not included in the high dose treatment volume as contoured with the use of CT alone. Our initial experience with the fusion software demonstrated an improvement in tumor localization with this technique. Based on these patients the use of CT alone for treatment planning purposes in central nervous system (CNS) lesions is inadequate and would result in an unacceptable rate of marginal misses. The importation of MRI data into three-dimensional treatment planning is therefore crucial to accurate tumor localization. The fusion process simplifies and improves precision of this task.
Technical Note: Is bulk electron density assignment appropriate for MRI-only based treatment planning for lung cancer?

PubMed

Prior, Phil; Chen, Xinfeng; Gore, Elizabeth; Johnstone, Candice; Li, X Allen

2017-07-01

MRI-based treatment planning in radiation therapy (RT) is prohibitive, in part, due to the lack of electron density (ED) information within the image. The dosimetric differences between MRI- and CT-based planning for intensity modulated RT (IMRT) of lung cancer were investigated to assess the appropriateness of bulk ED assignment. Planning CTs acquired for six representative lung cancer patients were used to generate bulk ED IMRT plans. To avoid the effect of anatomic differences between CT and MRI, "simulated MRI-based plans" were generated by forcing the relative ED (rED) to water on CT-delineated structures using organ specific values from the ICRU Report 46 and using the mean rED value of the internal target volume (ITV) from the planning CT. The "simulated MRI-based plans" were generated using a research planning system (Monaco v5.09.07a, Elekta, AB) and employing Monte Carlo dose calculation. The following dose-volume-parameters (DVPs) were collected from both the "simulated MRI-based plans" and the original planning CT: D 95 , the dose delivered to 95% of the ITV & planning target volume (PTV), D 5 and V 5 , the volume of normal lung irradiated ≥5 Gy. The percent point difference and relative dose difference were used for comparison with the CT based plan for V 5 and D 95 respectively. A total of five plans per patient were generated; three with the ITV rED (rED ITV ) = 1.06, 1.0 and the mean value from the planning CT while the lung rED (rED lung ) was fixed at the ICRU value of 0.26 and two with rED lung = 0.1 and 0.5 while the rED ITV was fixed to the mean value from the planning CT. Noticeable differences in the ITV and PTV DVPs were observed. Variations of the normal lung V 5 can be as large as 9.6%. In some instances, varying the rED ITV between rED mean and 1.06 resulted in D 95 increases ranging from 3.9% to 6.3%. Bulk rED assignment on normal lung affected the DVPs of the ITV and PTV by 4.0-9.8% and 0.3-19.6% respectively. Dose volume histograms were presented for representative cases where the variations in the DVPs were found to be very large or very small. The commonly used bulk rED assignment in MRI-only based planning may not be appropriate for lung cancer. A voxel based method, e.g., synthetic CT generated from MRI data, is likely required for dosimetrically accurate MR-based planning for lung cancer. © 2017 American Association of Physicists in Medicine.
MITK-based segmentation of co-registered MRI for subject-related regional anesthesia simulation

NASA Astrophysics Data System (ADS)

Teich, Christian; Liao, Wei; Ullrich, Sebastian; Kuhlen, Torsten; Ntouba, Alexandre; Rossaint, Rolf; Ullisch, Marcus; Deserno, Thomas M.

2008-03-01

With a steadily increasing indication, regional anesthesia is still trained directly on the patient. To develop a virtual reality (VR)-based simulation, a patient model is needed containing several tissues, which have to be extracted from individual magnet resonance imaging (MRI) volume datasets. Due to the given modality and the different characteristics of the single tissues, an adequate segmentation can only be achieved by using a combination of segmentation algorithms. In this paper, we present a framework for creating an individual model from MRI scans of the patient. Our work splits in two parts. At first, an easy-to-use and extensible tool for handling the segmentation task on arbitrary datasets is provided. The key idea is to let the user create a segmentation for the given subject by running different processing steps in a purposive order and store them in a segmentation script for reuse on new datasets. For data handling and visualization, we utilize the Medical Imaging Interaction Toolkit (MITK), which is based on the Visualization Toolkit (VTK) and the Insight Segmentation and Registration Toolkit (ITK). The second part is to find suitable segmentation algorithms and respectively parameters for differentiating the tissues required by the RA simulation. For this purpose, a fuzzy c-means clustering algorithm combined with mathematical morphology operators and a geometric active contour-based approach is chosen. The segmentation process itself aims at operating with minimal user interaction, and the gained model fits the requirements of the simulation. First results are shown for both, male and female MRI of the pelvis.
Design and simulation of a 800 Mbit/s data link for magnetic resonance imaging wearables.

PubMed

Vogt, Christian; Buthe, Lars; Petti, Luisa; Cantarella, Giuseppe; Munzenrieder, Niko; Daus, Alwin; Troster, Gerhard

2015-08-01

This paper presents the optimization of electronic circuitry for operation in the harsh electro magnetic (EM) environment during a magnetic resonance imaging (MRI) scan. As demonstrator, a device small enough to be worn during the scan is optimized. Based on finite element method (FEM) simulations, the induced current densities due to magnetic field changes of 200 T s(-1) were reduced from 1 × 10(10) A m(-2) by one order of magnitude, predicting error-free operation of the 1.8V logic employed. The simulations were validated using a bit error rate test, which showed no bit errors during a MRI scan sequence. Therefore, neither the logic, nor the utilized 800 Mbit s(-1) low voltage differential swing (LVDS) data link of the optimized wearable device were significantly influenced by the EM interference. Next, the influence of ferro-magnetic components on the static magnetic field and consequently the image quality was simulated showing a MRI image loss with approximately 2 cm radius around a commercial integrated circuit of 1×1 cm(2). This was successively validated by a conventional MRI scan.
Defining the value of magnetic resonance imaging in prostate brachytherapy using time-driven activity-based costing.

PubMed

Thaker, Nikhil G; Orio, Peter F; Potters, Louis

Magnetic resonance imaging (MRI) simulation and planning for prostate brachytherapy (PBT) may deliver potential clinical benefits but at an unknown cost to the provider and healthcare system. Time-driven activity-based costing (TDABC) is an innovative bottom-up costing tool in healthcare that can be used to measure the actual consumption of resources required over the full cycle of care. TDABC analysis was conducted to compare patient-level costs for an MRI-based versus traditional PBT workflow. TDABC cost was only 1% higher for the MRI-based workflow, and utilization of MRI allowed for cost shifting from other imaging modalities, such as CT and ultrasound, to MRI during the PBT process. Future initiatives will be required to follow the costs of care over longer periods of time to determine if improvements in outcomes and toxicities with an MRI-based approach lead to lower resource utilization and spending over the long-term. Understanding provider costs will become important as healthcare reform transitions to value-based purchasing and other alternative payment models. Copyright © 2016 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.
Robust and efficient pharmacokinetic parameter non-linear least squares estimation for dynamic contrast enhanced MRI of the prostate.

PubMed

Kargar, Soudabeh; Borisch, Eric A; Froemming, Adam T; Kawashima, Akira; Mynderse, Lance A; Stinson, Eric G; Trzasko, Joshua D; Riederer, Stephen J

2018-05-01

To describe an efficient numerical optimization technique using non-linear least squares to estimate perfusion parameters for the Tofts and extended Tofts models from dynamic contrast enhanced (DCE) MRI data and apply the technique to prostate cancer. Parameters were estimated by fitting the two Tofts-based perfusion models to the acquired data via non-linear least squares. We apply Variable Projection (VP) to convert the fitting problem from a multi-dimensional to a one-dimensional line search to improve computational efficiency and robustness. Using simulation and DCE-MRI studies in twenty patients with suspected prostate cancer, the VP-based solver was compared against the traditional Levenberg-Marquardt (LM) strategy for accuracy, noise amplification, robustness to converge, and computation time. The simulation demonstrated that VP and LM were both accurate in that the medians closely matched assumed values across typical signal to noise ratio (SNR) levels for both Tofts models. VP and LM showed similar noise sensitivity. Studies using the patient data showed that the VP method reliably converged and matched results from LM with approximate 3× and 2× reductions in computation time for the standard (two-parameter) and extended (three-parameter) Tofts models. While LM failed to converge in 14% of the patient data, VP converged in the ideal 100%. The VP-based method for non-linear least squares estimation of perfusion parameters for prostate MRI is equivalent in accuracy and robustness to noise, while being more reliably (100%) convergent and computationally about 3× (TM) and 2× (ETM) faster than the LM-based method. Copyright © 2017 Elsevier Inc. All rights reserved.
Evaluation of three inverse problem models to quantify skin microcirculation using diffusion-weighted MRI

NASA Astrophysics Data System (ADS)

Cordier, G.; Choi, J.; Raguin, L. G.

2008-11-01

Skin microcirculation plays an important role in diseases such as chronic venous insufficiency and diabetes. Magnetic resonance imaging (MRI) can provide quantitative information with a better penetration depth than other noninvasive methods, such as laser Doppler flowmetry or optical coherence tomography. Moreover, successful MRI skin studies have recently been reported. In this article, we investigate three potential inverse models to quantify skin microcirculation using diffusion-weighted MRI (DWI), also known as q-space MRI. The model parameters are estimated based on nonlinear least-squares (NLS). For each of the three models, an optimal DWI sampling scheme is proposed based on D-optimality in order to minimize the size of the confidence region of the NLS estimates and thus the effect of the experimental noise inherent to DWI. The resulting covariance matrices of the NLS estimates are predicted by asymptotic normality and compared to the ones computed by Monte-Carlo simulations. Our numerical results demonstrate the effectiveness of the proposed models and corresponding DWI sampling schemes as compared to conventional approaches.
Four-Dimensional Dose Reconstruction for Scanned Proton Therapy Using Liver 4DCT-MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernatowicz, Kinga, E-mail: kinga.bernatowicz@psi.ch; Proton Therapy Center, Paul Scherrer Institute, PSI Villigen; Peroni, Marta

Purpose: Four-dimensional computed tomography-magnetic resonance imaging (4DCT-MRI) is an image-processing technique for simulating many 4DCT data sets from a static reference CT and motions extracted from 4DMRI studies performed using either volunteers or patients. In this work, different motion extraction approaches were tested using 6 liver cases, and a detailed comparison between 4DCT-MRI and 4DCT was performed. Methods and Materials: 4DCT-MRI has been generated using 2 approaches. The first approach used motion extracted from 4DMRI as being “most similar” to that of 4DCT from the same patient (subject-specific), and the second approach used the most similar motion obtained from amore » motion library derived from 4DMRI liver studies of 13 healthy volunteers (population-based). The resulting 4DCT-MRI and 4DCTs were compared using scanned proton 4D dose calculations (4DDC). Results: Dosimetric analysis showed that 93% ± 8% of points inside the clinical target volume (CTV) agreed between 4DCT and subject-specific 4DCT-MRI (gamma analysis: 3%/3 mm). The population-based approach however showed lower dosimetric agreement with only 79% ± 14% points in the CTV reaching the 3%/3 mm criteria. Conclusions: 4D CT-MRI extends the capabilities of motion modeling for dose calculations by accounting for realistic and variable motion patterns, which can be directly employed in clinical research studies. We have found that the subject-specific liver modeling appears more accurate than the population-based approach. The former is particularly interesting for clinical applications, such as improved target delineation and 4D dose reconstruction for patient-specific QA to allow for inter- and/or intra-fractional plan corrections.« less
Simulation of arthroscopic surgery using MRI data

NASA Technical Reports Server (NTRS)

Heller, Geoffrey; Genetti, Jon

1994-01-01

With the availability of Magnetic Resonance Imaging (MRI) technology in the medical field and the development of powerful graphics engines in the computer world the possibility now exists for the simulation of surgery using data obtained from an actual patient. This paper describes a surgical simulation system which will allow a physician or a medical student to practice surgery on a patient without ever entering an operating room. This could substantially lower the cost of medial training by providing an alternative to the use of cadavers. This project involves the use of volume data acquired by MRI which are converted to polygonal form using a corrected marching cubes algorithm. The data are then colored and a simulation of surface response based on springy structures is performed in real time. Control for the system is obtained through the use of an attached analog-to-digital unit. A remote electronic device is described which simulates an imaginary tool having features in common with both arthroscope and laparoscope.
Radio-frequency energy quantification in magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Alon, Leeor

Mapping of radio frequency (RF) energy deposition has been challenging for 50+ years, especially, when scanning patients in the magnetic resonance imaging (MRI) environment. As result, electromagnetic simulation software is often used for estimating the specific absorption rate (SAR), the rate of RF energy deposition in tissue. The thesis work presents challenges associated with aligning information provided by electromagnetic simulation and MRI experiments. As result of the limitations of simulations, experimental methods for the quantification of SAR were established. A system for quantification of the total RF energy deposition was developed for parallel transmit MRI (a system that uses multiple antennas to excite and image the body). The system is capable of monitoring and predicting channel-by-channel RF energy deposition, whole body SAR and capable of tracking potential hardware failures that occur in the transmit chain and may cause the deposition of excessive energy into patients. Similarly, we demonstrated that local RF power deposition can be mapped and predicted for parallel transmit systems based on a series of MRI temperature mapping acquisitions. Resulting from the work, we developed tools for optimal reconstruction temperature maps from MRI acquisitions. The tools developed for temperature mapping paved the way for utilizing MRI as a diagnostic tool for evaluation of RF/microwave emitting device safety. Quantification of the RF energy was demonstrated for both MRI compatible and non-MRI-compatible devices (such as cell phones), while having the advantage of being noninvasive, of providing millimeter resolution and high accuracy.
Exploiting the wavelet structure in compressed sensing MRI.

PubMed

Chen, Chen; Huang, Junzhou

2014-12-01

Sparsity has been widely utilized in magnetic resonance imaging (MRI) to reduce k-space sampling. According to structured sparsity theories, fewer measurements are required for tree sparse data than the data only with standard sparsity. Intuitively, more accurate image reconstruction can be achieved with the same number of measurements by exploiting the wavelet tree structure in MRI. A novel algorithm is proposed in this article to reconstruct MR images from undersampled k-space data. In contrast to conventional compressed sensing MRI (CS-MRI) that only relies on the sparsity of MR images in wavelet or gradient domain, we exploit the wavelet tree structure to improve CS-MRI. This tree-based CS-MRI problem is decomposed into three simpler subproblems then each of the subproblems can be efficiently solved by an iterative scheme. Simulations and in vivo experiments demonstrate the significant improvement of the proposed method compared to conventional CS-MRI algorithms, and the feasibleness on MR data compared to existing tree-based imaging algorithms. Copyright © 2014 Elsevier Inc. All rights reserved.
Stereotaxic 18F-FDG PET and MRI templates with three-dimensional digital atlas for statistical parametric mapping analysis of tree shrew brain.

PubMed

Huang, Qi; Nie, Binbin; Ma, Chen; Wang, Jing; Zhang, Tianhao; Duan, Shaofeng; Wu, Shang; Liang, Shengxiang; Li, Panlong; Liu, Hua; Sun, Hua; Zhou, Jiangning; Xu, Lin; Shan, Baoci

2018-01-01

Tree shrews are proposed as an alternative animal model to nonhuman primates due to their close affinity to primates. Neuroimaging techniques are widely used to study brain functions and structures of humans and animals. However, tree shrews are rarely applied in neuroimaging field partly due to the lack of available species specific analysis methods. In this study, 10 PET/CT and 10 MRI images of tree shrew brain were used to construct PET and MRI templates; based on histological atlas we reconstructed a three-dimensional digital atlas with 628 structures delineated; then the digital atlas and templates were aligned into a stereotaxic space. Finally, we integrated the digital atlas and templates into a toolbox for tree shrew brain spatial normalization, statistical analysis and results localization. We validated the feasibility of the toolbox by simulated data with lesions in laterodorsal thalamic nucleus (LD). The lesion volumes of simulated PET and MRI images were (12.97±3.91)mm 3 and (7.04±0.84)mm 3 . Statistical results at p<0.005 showed the lesion volumes of PET and MRI were 13.18mm 3 and 8.06mm 3 in LD. To our knowledge, we report the first PET template and digital atlas of tree shrew brain. Compared to the existing MRI templates, our MRI template was aligned into stereotaxic space. And the toolbox is the first software dedicated for tree shrew brain analysis. The templates and digital atlas of tree shrew brain, as well as the toolbox, facilitate the use of tree shrews in neuroimaging field. Copyright © 2017 Elsevier B.V. All rights reserved.

Validation of radiocarpal joint contact models based on images from a clinical MRI scanner.

PubMed

Johnson, Joshua E; McIff, Terence E; Lee, Phil; Toby, E Bruce; Fischer, Kenneth J

2014-01-01

This study was undertaken to assess magnetic resonance imaging (MRI)-based radiocarpal surface contact models of functional loading in a clinical MRI scanner for future in vivo studies, by comparison with experimental measures from three cadaver forearm specimens. Experimental data were acquired using a Tekscan sensor during simulated light grasp. Magnetic resonance (MR) images were used to obtain model geometry and kinematics (image registration). Peak contact pressures (PPs) and average contact pressures (APs), contact forces and contact areas were determined in the radiolunate and radioscaphoid joints. Contact area was also measured directly from MR images acquired with load and compared with model data. Based on the validation criteria (within 25% of experimental data), out of the six articulations (three specimens with two articulations each), two met the criterion for AP (0%, 14%); one for peak pressure (20%); one for contact force (5%); four for contact area with respect to experiment (8%, 13%, 19% and 23%), and three contact areas met the criterion with respect to direct measurements (14%, 21% and 21%). Absolute differences between model and experimental PPs were reasonably low (within 2.5 MPa). Overall, the results indicate that MRI-based models generated from 3T clinical MR scanner appear sufficient to obtain clinically relevant data.
MRI-Based Computed Tomography Metal Artifact Correction Method for Improving Proton Range Calculation Accuracy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, Peter C.; Schreibmann, Eduard; Roper, Justin

2015-03-15

Purpose: Computed tomography (CT) artifacts can severely degrade dose calculation accuracy in proton therapy. Prompted by the recently increased popularity of magnetic resonance imaging (MRI) in the radiation therapy clinic, we developed an MRI-based CT artifact correction method for improving the accuracy of proton range calculations. Methods and Materials: The proposed method replaces corrupted CT data by mapping CT Hounsfield units (HU number) from a nearby artifact-free slice, using a coregistered MRI. MRI and CT volumetric images were registered with use of 3-dimensional (3D) deformable image registration (DIR). The registration was fine-tuned on a slice-by-slice basis by using 2D DIR.more » Based on the intensity of paired MRI pixel values and HU from an artifact-free slice, we performed a comprehensive analysis to predict the correct HU for the corrupted region. For a proof-of-concept validation, metal artifacts were simulated on a reference data set. Proton range was calculated using reference, artifactual, and corrected images to quantify the reduction in proton range error. The correction method was applied to 4 unique clinical cases. Results: The correction method resulted in substantial artifact reduction, both quantitatively and qualitatively. On respective simulated brain and head and neck CT images, the mean error was reduced from 495 and 370 HU to 108 and 92 HU after correction. Correspondingly, the absolute mean proton range errors of 2.4 cm and 1.7 cm were reduced to less than 2 mm in both cases. Conclusions: Our MRI-based CT artifact correction method can improve CT image quality and proton range calculation accuracy for patients with severe CT artifacts.« less
An empirical comparison of SPM preprocessing parameters to the analysis of fMRI data.

PubMed

Della-Maggiore, Valeria; Chau, Wilkin; Peres-Neto, Pedro R; McIntosh, Anthony R

2002-09-01

We present the results from two sets of Monte Carlo simulations aimed at evaluating the robustness of some preprocessing parameters of SPM99 for the analysis of functional magnetic resonance imaging (fMRI). Statistical robustness was estimated by implementing parametric and nonparametric simulation approaches based on the images obtained from an event-related fMRI experiment. Simulated datasets were tested for combinations of the following parameters: basis function, global scaling, low-pass filter, high-pass filter and autoregressive modeling of serial autocorrelation. Based on single-subject SPM analysis, we derived the following conclusions that may serve as a guide for initial analysis of fMRI data using SPM99: (1) The canonical hemodynamic response function is a more reliable basis function to model the fMRI time series than HRF with time derivative. (2) Global scaling should be avoided since it may significantly decrease the power depending on the experimental design. (3) The use of a high-pass filter may be beneficial for event-related designs with fixed interstimulus intervals. (4) When dealing with fMRI time series with short interstimulus intervals (<8 s), the use of first-order autoregressive model is recommended over a low-pass filter (HRF) because it reduces the risk of inferential bias while providing a relatively good power. For datasets with interstimulus intervals longer than 8 seconds, temporal smoothing is not recommended since it decreases power. While the generalizability of our results may be limited, the methods we employed can be easily implemented by other scientists to determine the best parameter combination to analyze their data.
EEG-fMRI Bayesian framework for neural activity estimation: a simulation study

NASA Astrophysics Data System (ADS)

Croce, Pierpaolo; Basti, Alessio; Marzetti, Laura; Zappasodi, Filippo; Del Gratta, Cosimo

2016-12-01

Objective. Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework. Approach. We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF). Main results. First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements. Significance. The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.
EEG-fMRI Bayesian framework for neural activity estimation: a simulation study.

PubMed

Croce, Pierpaolo; Basti, Alessio; Marzetti, Laura; Zappasodi, Filippo; Gratta, Cosimo Del

2016-12-01

Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework. We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF). First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements. The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.
Non-invasive imaging using reporter genes altering cellular water permeability

NASA Astrophysics Data System (ADS)

Mukherjee, Arnab; Wu, Di; Davis, Hunter C.; Shapiro, Mikhail G.

2016-12-01

Non-invasive imaging of gene expression in live, optically opaque animals is important for multiple applications, including monitoring of genetic circuits and tracking of cell-based therapeutics. Magnetic resonance imaging (MRI) could enable such monitoring with high spatiotemporal resolution. However, existing MRI reporter genes based on metalloproteins or chemical exchange probes are limited by their reliance on metals or relatively low sensitivity. Here we introduce a new class of MRI reporters based on the human water channel aquaporin 1. We show that aquaporin overexpression produces contrast in diffusion-weighted MRI by increasing tissue water diffusivity without affecting viability. Low aquaporin levels or mixed populations comprising as few as 10% aquaporin-expressing cells are sufficient to produce MRI contrast. We characterize this new contrast mechanism through experiments and simulations, and demonstrate its utility in vivo by imaging gene expression in tumours. Our results establish an alternative class of sensitive, metal-free reporter genes for non-invasive imaging.
A 3-dimensional DTI MRI-based model of GBM growth and response to radiation therapy.

PubMed

Hathout, Leith; Patel, Vishal; Wen, Patrick

2016-09-01

Glioblastoma (GBM) is both the most common and the most aggressive intra-axial brain tumor, with a notoriously poor prognosis. To improve this prognosis, it is necessary to understand the dynamics of GBM growth, response to treatment and recurrence. The present study presents a mathematical diffusion-proliferation model of GBM growth and response to radiation therapy based on diffusion tensor (DTI) MRI imaging. This represents an important advance because it allows 3-dimensional tumor modeling in the anatomical context of the brain. Specifically, tumor infiltration is guided by the direction of the white matter tracts along which glioma cells infiltrate. This provides the potential to model different tumor growth patterns based on location within the brain, and to simulate the tumor's response to different radiation therapy regimens. Tumor infiltration across the corpus callosum is simulated in biologically accurate time frames. The response to radiation therapy, including changes in cell density gradients and how these compare across different radiation fractionation protocols, can be rendered. Also, the model can estimate the amount of subthreshold tumor which has extended beyond the visible MR imaging margins. When combined with the ability of being able to estimate the biological parameters of invasiveness and proliferation of a particular GBM from serial MRI scans, it is shown that the model has potential to simulate realistic tumor growth, response and recurrence patterns in individual patients. To the best of our knowledge, this is the first presentation of a DTI-based GBM growth and radiation therapy treatment model.
MRI and Related Astrophysical Instabilities in the Lab

NASA Astrophysics Data System (ADS)

Goodman, Jeremy

2018-06-01

The dynamics of accretion in astronomical disks is only partly understood. Magnetorotational instability (MRI) is surely important but has been studied largely through linear analysis and numerical simulations rather than experiments. Also, it is unclear whether MRI is effective in protostellar disks, which are likely poor electrical conductors. Shear-driven hydrodynamic turbulence is very familiar in terrestrial flows, but simulations indicate that it is inhibited in disks. I summarize experimental progress and challenges relevant to both types of instability.
A Kernel-Based Low-Rank (KLR) Model for Low-Dimensional Manifold Recovery in Highly Accelerated Dynamic MRI.

PubMed

Nakarmi, Ukash; Wang, Yanhua; Lyu, Jingyuan; Liang, Dong; Ying, Leslie

2017-11-01

While many low rank and sparsity-based approaches have been developed for accelerated dynamic magnetic resonance imaging (dMRI), they all use low rankness or sparsity in input space, overlooking the intrinsic nonlinear correlation in most dMRI data. In this paper, we propose a kernel-based framework to allow nonlinear manifold models in reconstruction from sub-Nyquist data. Within this framework, many existing algorithms can be extended to kernel framework with nonlinear models. In particular, we have developed a novel algorithm with a kernel-based low-rank model generalizing the conventional low rank formulation. The algorithm consists of manifold learning using kernel, low rank enforcement in feature space, and preimaging with data consistency. Extensive simulation and experiment results show that the proposed method surpasses the conventional low-rank-modeled approaches for dMRI.
The SAFIR experiment: Concept, status and perspectives

NASA Astrophysics Data System (ADS)

Becker, Robert; Buck, Alfred; Casella, Chiara; Dissertori, Günther; Fischer, Jannis; Howard, Alexander; Ito, Mikiko; Khateri, Parisa; Lustermann, Werner; Oliver, Josep F.; Röser, Ulf; Warnock, Geoffrey; Weber, Bruno

2017-02-01

The SAFIR development represents a novel Positron Emission Tomography (PET) detector, conceived for preclinical fast acquisitions inside the bore of a Magnetic Resonance Imaging (MRI) scanner. The goal is hybrid and simultaneous PET/MRI dynamic studies at unprecedented temporal resolutions of a few seconds. The detector relies on matrices of scintillating LSO-based crystals coupled one-to-one with SiPM arrays and readout by fast ASICs with excellent timing resolution and high rate capabilities. The paper describes the detector concept and the initial results in terms of simulations and characterisation measurements.
Technical Note: Radiological properties of tissue surrogates used in a multimodality deformable pelvic phantom for MR-guided radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niebuhr, Nina I., E-mail: n.niebuhr@dkfz.de; Johnen, Wibke; Güldaglar, Timur

Purpose: Phantom surrogates were developed to allow multimodal [computed tomography (CT), magnetic resonance imaging (MRI), and teletherapy] and anthropomorphic tissue simulation as well as materials and methods to construct deformable organ shapes and anthropomorphic bone models. Methods: Agarose gels of variable concentrations and loadings were investigated to simulate various soft tissue types. Oils, fats, and Vaseline were investigated as surrogates for adipose tissue and bone marrow. Anthropomorphic shapes of bone and organs were realized using 3D-printing techniques based on segmentations of patient CT-scans. All materials were characterized in dual energy CT and MRI to adapt CT numbers, electron density, effectivemore » atomic number, as well as T1- and T2-relaxation times to patient and literature values. Results: Soft tissue simulation could be achieved with agarose gels in combination with a gadolinium-based contrast agent and NaF to simulate muscle, prostate, and tumor tissues. Vegetable oils were shown to be a good representation for adipose tissue in all modalities. Inner bone was realized using a mixture of Vaseline and K{sub 2}HPO{sub 4}, resulting in both a fatty bone marrow signal in MRI and inhomogeneous areas of low and high attenuation in CT. The high attenuation of outer bone was additionally adapted by applying gypsum bandages to the 3D-printed hollow bone case with values up to 1200 HU. Deformable hollow organs were manufactured using silicone. Signal loss in the MR images based on the conductivity of the gels needs to be further investigated. Conclusions: The presented surrogates and techniques allow the customized construction of multimodality, anthropomorphic, and deformable phantoms as exemplarily shown for a pelvic phantom, which is intended to study adaptive treatment scenarios in MR-guided radiation therapy.« less
Technical Note: Radiological properties of tissue surrogates used in a multimodality deformable pelvic phantom for MR-guided radiotherapy.

PubMed

Niebuhr, Nina I; Johnen, Wibke; Güldaglar, Timur; Runz, Armin; Echner, Gernot; Mann, Philipp; Möhler, Christian; Pfaffenberger, Asja; Jäkel, Oliver; Greilich, Steffen

2016-02-01

Phantom surrogates were developed to allow multimodal [computed tomography (CT), magnetic resonance imaging (MRI), and teletherapy] and anthropomorphic tissue simulation as well as materials and methods to construct deformable organ shapes and anthropomorphic bone models. Agarose gels of variable concentrations and loadings were investigated to simulate various soft tissue types. Oils, fats, and Vaseline were investigated as surrogates for adipose tissue and bone marrow. Anthropomorphic shapes of bone and organs were realized using 3D-printing techniques based on segmentations of patient CT-scans. All materials were characterized in dual energy CT and MRI to adapt CT numbers, electron density, effective atomic number, as well as T1- and T2-relaxation times to patient and literature values. Soft tissue simulation could be achieved with agarose gels in combination with a gadolinium-based contrast agent and NaF to simulate muscle, prostate, and tumor tissues. Vegetable oils were shown to be a good representation for adipose tissue in all modalities. Inner bone was realized using a mixture of Vaseline and K2HPO4, resulting in both a fatty bone marrow signal in MRI and inhomogeneous areas of low and high attenuation in CT. The high attenuation of outer bone was additionally adapted by applying gypsum bandages to the 3D-printed hollow bone case with values up to 1200 HU. Deformable hollow organs were manufactured using silicone. Signal loss in the MR images based on the conductivity of the gels needs to be further investigated. The presented surrogates and techniques allow the customized construction of multimodality, anthropomorphic, and deformable phantoms as exemplarily shown for a pelvic phantom, which is intended to study adaptive treatment scenarios in MR-guided radiation therapy.
Canonical Correlation Analysis for Feature-Based Fusion of Biomedical Imaging Modalities and Its Application to Detection of Associative Networks in Schizophrenia.

PubMed

Correa, Nicolle M; Li, Yi-Ou; Adalı, Tülay; Calhoun, Vince D

2008-12-01

Typically data acquired through imaging techniques such as functional magnetic resonance imaging (fMRI), structural MRI (sMRI), and electroencephalography (EEG) are analyzed separately. However, fusing information from such complementary modalities promises to provide additional insight into connectivity across brain networks and changes due to disease. We propose a data fusion scheme at the feature level using canonical correlation analysis (CCA) to determine inter-subject covariations across modalities. As we show both with simulation results and application to real data, multimodal CCA (mCCA) proves to be a flexible and powerful method for discovering associations among various data types. We demonstrate the versatility of the method with application to two datasets, an fMRI and EEG, and an fMRI and sMRI dataset, both collected from patients diagnosed with schizophrenia and healthy controls. CCA results for fMRI and EEG data collected for an auditory oddball task reveal associations of the temporal and motor areas with the N2 and P3 peaks. For the application to fMRI and sMRI data collected for an auditory sensorimotor task, CCA results show an interesting joint relationship between fMRI and gray matter, with patients with schizophrenia showing more functional activity in motor areas and less activity in temporal areas associated with less gray matter as compared to healthy controls. Additionally, we compare our scheme with an independent component analysis based fusion method, joint-ICA that has proven useful for such a study and note that the two methods provide complementary perspectives on data fusion.
SU-F-I-27: Measurement of SAR and Temperature Elevation During MRI Scans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seo, Y

Purpose: The poor reliability and repeatability of the manufacturer-reported SAR values on clinical MRI systems have been acknowledged. The purpose of this study is to not only measure SAR values, but also RF-induced temperature elevation at 1.5 and 3T MRI systems. Methods: SAR measurement experiment was performed at 1.5 and 3T. Three MRI RF sequences (T1w TSE, T1w inversion recovery, and T2w TSE) with imaging parameters were selected. A hydroxyl-ethylcelluose (HEC) gelled saline phantom mimicking human body tissue was made. Human torso phantom were constructed, based on Korean adult standard anthropometric reference data (Fig.1). FDTD method was utilized to calculatemore » the SAR distribution using Sim4Life software. Based on the results of the simulation, 4 electrical field (E-field) sensors were located inside the phantom. 55 Fiber Bragg Grating (FBG) temperature sensors (27 sensors in upper and lower cover lids, and one sensor located in the center as a reference) were located inside the phantom to measure temperature change during MRI scan (Fig.2). Results: Simulation shows that SAR value is 0.4 W/kg in the periphery and 0.001 W/kg in the center (Fig.2). One 1.5T and one of two 3T MRI systems represent that the measured SAR values were lower than MRI scanner-reported SAR values. However, the other 3T MRI scanner shows that the averaged SAR values measured by probe 2, 3, and 4 are 6.83, 7.59, and 6.01 W/kg, compared to MRI scanner-reported whole body SAR value (<1.5 W/kg) for T2w TSE (Table 1). The temperature elevation measured by FBG sensors is 5.2°C in the lateral shoulder, 5.1°C in the underarm, 4.7°C in the anterior axilla, 4.8°C in the posterior axilla, and 4.8°C in the lateral waist for T2w TSE (Fig.3). Conclusion: It is essential to assess the safety of MRI system for patient by measuring accurate SAR deposited in the body during clinical MRI.« less
Comparison of a 3-D DEM simulation with MRI data

NASA Astrophysics Data System (ADS)

Ng, Tang-Tat; Wang, Changming

2001-04-01

This paper presents a comparison of a granular material studied experimentally and numerically. Simple shear tests were performed inside the magnetic core of magnetic resonance imaging (MRI) equipment. Spherical pharmaceutical pills were used as the granular material, with each pill's centre location determined by MRI. These centre locations in the initial assembly were then used as the initial configuration in the numerical simulation using the discrete element method. The contact properties between pharmaceutical pills used in the numerical simulation were obtained experimentally. The numerical predication was compared with experimental data at both macroscopic and microscopic levels. Good agreement was found at both levels.
GPU accelerated FDTD solver and its application in MRI.

PubMed

Chi, J; Liu, F; Jin, J; Mason, D G; Crozier, S

2010-01-01

The finite difference time domain (FDTD) method is a popular technique for computational electromagnetics (CEM). The large computational power often required, however, has been a limiting factor for its applications. In this paper, we will present a graphics processing unit (GPU)-based parallel FDTD solver and its successful application to the investigation of a novel B1 shimming scheme for high-field magnetic resonance imaging (MRI). The optimized shimming scheme exhibits considerably improved transmit B(1) profiles. The GPU implementation dramatically shortened the runtime of FDTD simulation of electromagnetic field compared with its CPU counterpart. The acceleration in runtime has made such investigation possible, and will pave the way for other studies of large-scale computational electromagnetic problems in modern MRI which were previously impractical.
Modeling contrast agent flow in cerebral aneurysms: comparison of CFD with medical imaging

NASA Astrophysics Data System (ADS)

Rayz, Vitaliy; Vali, Alireza; Sigovan, Monica; Lawton, Michael; Saloner, David; Boussel, Loic

2016-11-01

PURPOSE: The flow in cerebral aneurysms is routinely assessed with X-ray angiography, an imaging technique based on a contrast agent injection. In addition to requiring a patient's catheterization and radiation exposure, the X-ray angiography may inaccurately estimate the flow residence time, as the injection alters the native blood flow patterns. Numerical modeling of the contrast transport based on MRI imaging, provides a non-invasive alternative for the flow diagnostics. METHODS: The flow in 3 cerebral aneurysms was measured in vivo with 4D PC-MRI, which provides time-resolved, 3D velocity field. The measured velocities were used to simulate a contrast agent transport by solving the advection-diffusion equation. In addition, the flow in the same patient-specific geometries was simulated with CFD and the velocities obtained from the Navier-Stokes solution were used to model the transport of a virtual contrast. RESULTS: Contrast filling and washout patterns obtained in simulations based on MRI-measured velocities were in agreement with those obtained using the Navier-Stokes solution. Some discrepancies were observed in comparison to the X-ray angiography data, as numerical modeling of the contrast transport is based on the native blood flow unaffected by the contrast injection. NIH HL115267.
SU-E-J-205: Dose Distribution Differences Caused by System Related Geometric Distortion in MRI-Guided Radiation Treatment System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, J; Yang, J; Wen, Z

2015-06-15

Purpose: MRI has superb soft tissue contrast but is also known for geometric distortions. The concerns and uncertainty about MRI’s geometric distortion have contributed to the hesitation of using only MRI for simulation in radiation therapy. There are two major categories of geometric distortion in MRI; system related and patient related. In this presentation, we studied the impact of system-related geometric distortion on dose distribution in a digital body phantom under an MR-Linac environment. Methods: Residual geometric distortion (after built-in geometric correction) was modeled based on phantom measurements of the system-related geometric distortions of a MRI scanner of a combinedmore » MR guided Radiation Therapy (MRgRT) system. A digital oval shaped phantom (40×25 cm) as well as one ellipsoid shaped tumor volume was created to simulate a simplified human body. The simulated tumor volume was positioned at several locations between the isocenter and the body surface. CT numbers in HUs that approximate soft tissue and tumor were assigned to the respective regions in the digital phantom. To study the effect of geometric distortion caused by system imperfections, an IMRT plan was optimized with the distorted image set with the B field. Dose distributions were re-calculated on the undistorted image set with the B field (as in MR-Linac). Results: The maximum discrepancies in both body contour and tumor boundary was less than 2 mm, which leads to small dose distribution change. For the target in the center, coverage was reduced from 98.8% (with distortion) to 98.2%; for the other peripheral target coverage was reduced from 98.4% to 95.9%. Conclusion: System related geometric distortions over the 40×25 area were within 2mm and the resulted dosimetric effects were minor for the two tumor locations in the phantom. Patient study will be needed for further investigation. The authors received a corporate research grant from Elekta.« less
Simulation of brain tumors in MR images for evaluation of segmentation efficacy.

PubMed

Prastawa, Marcel; Bullitt, Elizabeth; Gerig, Guido

2009-04-01

Obtaining validation data and comparison metrics for segmentation of magnetic resonance images (MRI) are difficult tasks due to the lack of reliable ground truth. This problem is even more evident for images presenting pathology, which can both alter tissue appearance through infiltration and cause geometric distortions. Systems for generating synthetic images with user-defined degradation by noise and intensity inhomogeneity offer the possibility for testing and comparison of segmentation methods. Such systems do not yet offer simulation of sufficiently realistic looking pathology. This paper presents a system that combines physical and statistical modeling to generate synthetic multi-modal 3D brain MRI with tumor and edema, along with the underlying anatomical ground truth, Main emphasis is placed on simulation of the major effects known for tumor MRI, such as contrast enhancement, local distortion of healthy tissue, infiltrating edema adjacent to tumors, destruction and deformation of fiber tracts, and multi-modal MRI contrast of healthy tissue and pathology. The new method synthesizes pathology in multi-modal MRI and diffusion tensor imaging (DTI) by simulating mass effect, warping and destruction of white matter fibers, and infiltration of brain tissues by tumor cells. We generate synthetic contrast enhanced MR images by simulating the accumulation of contrast agent within the brain. The appearance of the the brain tissue and tumor in MRI is simulated by synthesizing texture images from real MR images. The proposed method is able to generate synthetic ground truth and synthesized MR images with tumor and edema that exhibit comparable segmentation challenges to real tumor MRI. Such image data sets will find use in segmentation reliability studies, comparison and validation of different segmentation methods, training and teaching, or even in evaluating standards for tumor size like the RECIST criteria (response evaluation criteria in solid tumors).
TU-H-BRA-05: A System Design for Integration of An Interior MRI and a Linear Accelerator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mao, W; Henry Ford Hospital, Detroit, MI; Wang, G

Purpose: MRI is a highly desirable modality to guide radiation therapy but it is difficult to combine a conventional MRI scanner directly with a linear accelerator (linac). An interior MRI (iMRI) concept has been proposed to acquire MRI images within a small field of view only covering targets and immediate surrounding tissues. The objective of this project is to design an interior MRI system to work with a linac using a magnet to provide a field around 0.2T in a cube of 20cm per side, and perform image reconstruction with a slightly inhomogeneous static magnetic fields. Methods: All the resultsmore » are simulated using a commercially available software package, FARADY. In our design, a ring structure holds the iMRI system and also imbeds a linac treatment head. The ring is synchronized to the linac gantry rotation. Half of the ring is made of steel and becomes a magnetic flux return path (yoke) so that a strong magnetic field will be limited inside the iron circuit and fringe fields will be very weak. In order to increase the static magnetic field homogeneity, special steel magnet boots or tips were simulated. Three curved boots were designed based on two-dimensional curves: arc, parabola and hyperbola. Results: Different boot surfaces modify magnetic field distributions differently. With the same pair of neodymium-iron-boron (NdFeB) magnets, the magnetic induction at the centers are 0.217T, 0.201T, 0.204T, and 0.212T for flat, arc, parabola and hyperbola boots, respectively. The hyperbola boots lead to the most homogeneous results, the static magnetic field deviations are within 0.5% in a cube of 20cm, and can be further improved using shimming techniques. Conclusion: This study supports the concept of an iMRI design. Successful development of iMRI will provide crucial information for tumor delineation in radiation therapy.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brezovich, I; Wu, X; Popple, R

Purpose: To test spatial and dosimetric accuracy of small cranial target irradiation based on 1.5 T MRI scans using static arcs with MLC-defined fields Methods: A plastic (PMMA) phantom simulating a small brain lesion was mounted on a GammaKnife headframe equipped with MRI localizer. The lesion was a 3 mm long, 3.175 mm diameter cylindrical cavity filled with MRI contrast. Radiochromic film passing through the cavity was marked with pin pricks at the cavity center. The cavity was contoured on an MRI image and fused with CT to simulate treatment of a lesion not visible on CT. The transfer ofmore » the target to CT involved registering the MRI contrast cannels of the localizer that were visible on both modalities. Treatments were planned to deliver 800 cGy to the cavity center using multiple static arcs with 5.0×2.4 mm MLC-defined fields. The phantom was aligned on a STx accelerator by registering the conebeam CT with the planning CT. Films from coronal and sagittal planes were scanned and evaluated using ImageJ software Results: Geographic errors in treatment based on 1.5 T scans agreed within 0.33, −0.27 and 1.21 mm in the vertical, lateral and longitudinal dimensions, respectively. The doses delivered to the cavity center were 7.2% higher than planned. The dose distributions were similar to those of a GammaKnife. Conclusion: Radiation can be delivered with an accelerator at mm accuracy to small cranial targets based on 1.5 MRI scans fused to CTs using a standard GammaKnife headframe and MRI localizer. MLC-defined static arcs produce isodose lines very similar to the GammaKnife.« less
Magnetic Resonance Imaging–Guided versus Surrogate-Based Motion Tracking in Liver Radiation Therapy: A Prospective Comparative Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paganelli, Chiara, E-mail: chiara.paganelli@polimi.it; Seregni, Matteo; Fattori, Giovanni

Purpose: This study applied automatic feature detection on cine–magnetic resonance imaging (MRI) liver images in order to provide a prospective comparison between MRI-guided and surrogate-based tracking methods for motion-compensated liver radiation therapy. Methods and Materials: In a population of 30 subjects (5 volunteers plus 25 patients), 2 oblique sagittal slices were acquired across the liver at high temporal resolution. An algorithm based on scale invariant feature transform (SIFT) was used to extract and track multiple features throughout the image sequence. The position of abdominal markers was also measured directly from the image series, and the internal motion of each featuremore » was quantified through multiparametric analysis. Surrogate-based tumor tracking with a state-of-the-art external/internal correlation model was simulated. The geometrical tracking error was measured, and its correlation with external motion parameters was also investigated. Finally, the potential gain in tracking accuracy relying on MRI guidance was quantified as a function of the maximum allowed tracking error. Results: An average of 45 features was extracted for each subject across the whole liver. The multi-parametric motion analysis reported relevant inter- and intrasubject variability, highlighting the value of patient-specific and spatially-distributed measurements. Surrogate-based tracking errors (relative to the motion amplitude) were were in the range 7% to 23% (1.02-3.57mm) and were significantly influenced by external motion parameters. The gain of MRI guidance compared to surrogate-based motion tracking was larger than 30% in 50% of the subjects when considering a 1.5-mm tracking error tolerance. Conclusions: Automatic feature detection applied to cine-MRI allows detailed liver motion description to be obtained. Such information was used to quantify the performance of surrogate-based tracking methods and to provide a prospective comparison with respect to MRI-guided radiation therapy, which could support the definition of patient-specific optimal treatment strategies.« less
2D dose distribution images of a hybrid low field MRI-γ detector

NASA Astrophysics Data System (ADS)

Abril, A.; Agulles-Pedrós, L.

2016-07-01

The proposed hybrid system is a combination of a low field MRI and dosimetric gel as a γ detector. The readout system is based on the polymerization process induced by the gel radiation. A gel dose map is obtained which represents the functional part of hybrid image alongside with the anatomical MRI one. Both images should be taken while the patient with a radiopharmaceutical is located inside the MRI system with a gel detector matrix. A relevant aspect of this proposal is that the dosimetric gel has never been used to acquire medical images. The results presented show the interaction of the 99mTc source with the dosimetric gel simulated in Geant4. The purpose was to obtain the planar γ 2D-image. The different source configurations are studied to explore the ability of the gel as radiation detector through the following parameters; resolution, shape definition and radio-pharmaceutical concentration.
Accurate reconstruction of 3D cardiac geometry from coarsely-sliced MRI.

PubMed

Ringenberg, Jordan; Deo, Makarand; Devabhaktuni, Vijay; Berenfeld, Omer; Snyder, Brett; Boyers, Pamela; Gold, Jeffrey

2014-02-01

We present a comprehensive validation analysis to assess the geometric impact of using coarsely-sliced short-axis images to reconstruct patient-specific cardiac geometry. The methods utilize high-resolution diffusion tensor MRI (DTMRI) datasets as reference geometries from which synthesized coarsely-sliced datasets simulating in vivo MRI were produced. 3D models are reconstructed from the coarse data using variational implicit surfaces through a commonly used modeling tool, CardioViz3D. The resulting geometries were then compared to the reference DTMRI models from which they were derived to analyze how well the synthesized geometries approximate the reference anatomy. Averaged over seven hearts, 95% spatial overlap, less than 3% volume variability, and normal-to-surface distance of 0.32 mm was observed between the synthesized myocardial geometries reconstructed from 8 mm sliced images and the reference data. The results provide strong supportive evidence to validate the hypothesis that coarsely-sliced MRI may be used to accurately reconstruct geometric ventricular models. Furthermore, the use of DTMRI for validation of in vivo MRI presents a novel benchmark procedure for studies which aim to substantiate their modeling and simulation methods using coarsely-sliced cardiac data. In addition, the paper outlines a suggested original procedure for deriving image-based ventricular models using the CardioViz3D software. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Hemodynamic Evaluation of a Biological and Mechanical Aortic Valve Prosthesis Using Patient-Specific MRI-Based CFD.

PubMed

Hellmeier, Florian; Nordmeyer, Sarah; Yevtushenko, Pavlo; Bruening, Jan; Berger, Felix; Kuehne, Titus; Goubergrits, Leonid; Kelm, Marcus

2018-01-01

Modeling different treatment options before a procedure is performed is a promising approach for surgical decision making and patient care in heart valve disease. This study investigated the hemodynamic impact of different prostheses through patient-specific MRI-based CFD simulations. Ten time-resolved MRI data sets with and without velocity encoding were obtained to reconstruct the aorta and set hemodynamic boundary conditions for simulations. Aortic hemodynamics after virtual valve replacement with a biological and mechanical valve prosthesis were investigated. Wall shear stress (WSS), secondary flow degree (SFD), transvalvular pressure drop (TPD), turbulent kinetic energy (TKE), and normalized flow displacement (NFD) were evaluated to characterize valve-induced hemodynamics. The biological prostheses induced significantly higher WSS (medians: 9.3 vs. 8.6 Pa, P = 0.027) and SFD (means: 0.78 vs. 0.49, P = 0.002) in the ascending aorta, TPD (medians: 11.4 vs. 2.7 mm Hg, P = 0.002), TKE (means: 400 vs. 283 cm 2 /s 2 , P = 0.037), and NFD (means: 0.0994 vs. 0.0607, P = 0.020) than the mechanical prostheses. The differences between the prosthesis types showed great inter-patient variability, however. Given this variability, a patient-specific evaluation is warranted. In conclusion, MRI-based CFD offers an opportunity to assess the interactions between prosthesis and patient-specific boundary conditions, which may help in optimizing surgical decision making and providing additional guidance to clinicians. © 2017 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.
Fully Kinetic Large-scale Simulations of the Collisionless Magnetorotational Instability

NASA Astrophysics Data System (ADS)

Inchingolo, Giannandrea; Grismayer, Thomas; Loureiro, Nuno F.; Fonseca, Ricardo A.; Silva, Luis O.

2018-06-01

We present two-dimensional particle-in-cell simulations of the fully kinetic collisionless magnetorotational instability (MRI) in weakly magnetized (high β) pair plasma. The central result of this numerical analysis is the emergence of a self-induced turbulent regime in the saturation state of the collisionless MRI, which can only be captured for large enough simulation domains. One of the underlying mechanisms for the development of this turbulent state is the drift-kink instability (DKI) of the current sheets resulting from the nonlinear evolution of the channel modes. The onset of the DKI can only be observed for simulation domain sizes exceeding several linear MRI wavelengths. The DKI and ensuing magnetic reconnection activate the turbulent motion of the plasma in the late stage of the nonlinear evolution of the MRI. At steady-state, the magnetic energy has an MHD-like spectrum with a slope of k ‑5/3 for kρ < 1 and k ‑3 for sub-Larmor scale (kρ > 1). We also examine the role of the collisionless MRI and associated magnetic reconnection in the development of pressure anisotropy. We study the stability of the system due to this pressure anisotropy, observing the development of mirror instability during the early-stage of the MRI. We further discuss the importance of magnetic reconnection for particle acceleration during the turbulence regime. In particular, consistent with reconnection studies, we show that at late times the kinetic energy presents a characteristic slope of ɛ ‑2 in the high-energy region.
Reliability of Classifying Multiple Sclerosis Disease Activity Using Magnetic Resonance Imaging in a Multiple Sclerosis Clinic

PubMed Central

Altay, Ebru Erbayat; Fisher, Elizabeth; Jones, Stephen E.; Hara-Cleaver, Claire; Lee, Jar-Chi; Rudick, Richard A.

2013-01-01

Objective To assess the reliability of new magnetic resonance imaging (MRI) lesion counts by clinicians in a multiple sclerosis specialty clinic. Design An observational study. Setting A multiple sclerosis specialty clinic. Patients Eighty-five patients with multiple sclerosis participating in a National Institutes of Health–supported longitudinal study were included. Intervention Each patient had a brain MRI scan at entry and 6 months later using a standardized protocol. Main Outcome Measures The number of new T2 lesions, newly enlarging T2 lesions, and gadolinium-enhancing lesions were measured on the 6-month MRI using a computer-based image analysis program for the original study. For this study, images were reanalyzed by an expert neuroradiologist and 3 clinician raters. The neuroradiologist evaluated the original image pairs; the clinicians evaluated image pairs that were modified to simulate clinical practice. New lesion counts were compared across raters, as was classification of patients as MRI active or inactive. Results Agreement on lesion counts was highest for gadolinium-enhancing lesions, intermediate for new T2 lesions, and poor for enlarging T2 lesions. In 18% to 25% of the cases, MRI activity was classified differently by the clinician raters compared with the neuroradiologist or computer program. Variability among the clinical raters for estimates of new T2 lesions was affected most strongly by the image modifications that simulated low image quality and different head position. Conclusions Between-rater variability in new T2 lesion counts may be reduced by improved standardization of image acquisitions, but this approach may not be practical in most clinical environments. Ultimately, more reliable, robust, and accessible image analysis methods are needed for accurate multiple sclerosis disease-modifying drug monitoring and decision making in the routine clinic setting. PMID:23599930
MRI-guided attenuation correction in whole-body PET/MR: assessment of the effect of bone attenuation.

PubMed

Akbarzadeh, A; Ay, M R; Ahmadian, A; Alam, N Riahi; Zaidi, H

2013-02-01

Hybrid PET/MRI presents many advantages in comparison with its counterpart PET/CT in terms of improved soft-tissue contrast, decrease in radiation exposure, and truly simultaneous and multi-parametric imaging capabilities. However, the lack of well-established methodology for MR-based attenuation correction is hampering further development and wider acceptance of this technology. We assess the impact of ignoring bone attenuation and using different tissue classes for generation of the attenuation map on the accuracy of attenuation correction of PET data. This work was performed using simulation studies based on the XCAT phantom and clinical input data. For the latter, PET and CT images of patients were used as input for the analytic simulation model using realistic activity distributions where CT-based attenuation correction was utilized as reference for comparison. For both phantom and clinical studies, the reference attenuation map was classified into various numbers of tissue classes to produce three (air, soft tissue and lung), four (air, lungs, soft tissue and cortical bones) and five (air, lungs, soft tissue, cortical bones and spongeous bones) class attenuation maps. The phantom studies demonstrated that ignoring bone increases the relative error by up to 6.8% in the body and up to 31.0% for bony regions. Likewise, the simulated clinical studies showed that the mean relative error reached 15% for lesions located in the body and 30.7% for lesions located in bones, when neglecting bones. These results demonstrate an underestimation of about 30% of tracer uptake when neglecting bone, which in turn imposes substantial loss of quantitative accuracy for PET images produced by hybrid PET/MRI systems. Considering bones in the attenuation map will considerably improve the accuracy of MR-guided attenuation correction in hybrid PET/MR to enable quantitative PET imaging on hybrid PET/MR technologies.
Toward implementing an MRI-based PET attenuation-correction method for neurologic studies on the MR-PET brain prototype.

PubMed

Catana, Ciprian; van der Kouwe, Andre; Benner, Thomas; Michel, Christian J; Hamm, Michael; Fenchel, Matthias; Fischl, Bruce; Rosen, Bruce; Schmand, Matthias; Sorensen, A Gregory

2010-09-01

Several factors have to be considered for implementing an accurate attenuation-correction (AC) method in a combined MR-PET scanner. In this work, some of these challenges were investigated, and an AC method based entirely on the MRI data obtained with a single dedicated sequence was developed and used for neurologic studies performed with the MR-PET human brain scanner prototype. The focus was on the problem of bone-air segmentation, selection of the linear attenuation coefficient for bone, and positioning of the radiofrequency coil. The impact of these factors on PET data quantification was studied in simulations and experimental measurements performed on the combined MR-PET scanner. A novel dual-echo ultrashort echo time (DUTE) MRI sequence was proposed for head imaging. Simultaneous MR-PET data were acquired, and the PET images reconstructed using the proposed DUTE MRI-based AC method were compared with the PET images that had been reconstructed using a CT-based AC method. Our data suggest that incorrectly accounting for the bone tissue attenuation can lead to large underestimations (>20%) of the radiotracer concentration in the cortex. Assigning a linear attenuation coefficient of 0.143 or 0.151 cm(-1) to bone tissue appears to give the best trade-off between bias and variability in the resulting images. Not identifying the internal air cavities introduces large overestimations (>20%) in adjacent structures. On the basis of these results, the segmented CT AC method was established as the silver standard for the segmented MRI-based AC method. For an integrated MR-PET scanner, in particular, ignoring the radiofrequency coil attenuation can cause large underestimations (i.e.,
Integrating EEG and fMRI in epilepsy.

PubMed

Formaggio, Emanuela; Storti, Silvia Francesca; Bertoldo, Alessandra; Manganotti, Paolo; Fiaschi, Antonio; Toffolo, Gianna Maria

2011-02-14

Integrating electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) studies enables to non-invasively investigate human brain function and to find the direct correlation of these two important measures of brain activity. Presurgical evaluation of patients with epilepsy is one of the areas where EEG and fMRI integration has considerable clinical relevance for localizing the brain regions generating interictal epileptiform activity. The conventional analysis of EEG-fMRI data is based on the visual identification of the interictal epileptiform discharges (IEDs) on scalp EEG. The convolution of these EEG events, represented as stick functions, with a model of the fMRI response, i.e. the hemodynamic response function, provides the regressor for general linear model (GLM) analysis of fMRI data. However, the conventional analysis is not automatic and suffers of some subjectivity in IEDs classification. Here, we present an easy-to-use and automatic approach for combined EEG-fMRI analysis able to improve IEDs identification based on Independent Component Analysis and wavelet analysis. EEG signal due to IED is reconstructed and its wavelet power is used as a regressor in GLM. The method was validated on simulated data and then applied on real data set consisting of 2 normal subjects and 5 patients with partial epilepsy. In all continuous EEG-fMRI recording sessions a good quality EEG was obtained allowing the detection of spontaneous IEDs and the analysis of the related BOLD activation. The main clinical finding in EEG-fMRI studies of patients with partial epilepsy is that focal interictal slow-wave activity was invariably associated with increased focal BOLD responses in a spatially related brain area. Our study extends current knowledge on epileptic foci localization and confirms previous reports suggesting that BOLD activation associated with slow activity might have a role in localizing the epileptogenic region even in the absence of clear interictal spikes. Copyright © 2010 Elsevier Inc. All rights reserved.
Probing Lung Microstructure with Hyperpolarized 3He Gradient Echo MRI

PubMed Central

Sukstanskii, Alexander L; Quirk, James D; Yablonskiy, Dmitriy A

2014-01-01

In this paper we demonstrate that Gradient Echo MRI with hyperpolarized 3He gas can be used for simultaneously extracting in vivo information about lung ventilation properties, alveolar geometrical parameters, and blood vessel network structure. This new approach is based on multi-gradient-echo experimental measurements of hyperpolarized 3He gas MRI signal from human lungs and a proposed theoretical model of this signal. Based on computer simulations of 3He atoms diffusing in the acinar airway tree in the presence of an inhomogeneous magnetic field induced by the susceptibility differences between lung tissue (alveolar septa, blood vessels) and lung airspaces we derive analytical expressions relating the time-dependent MR signal to the geometrical parameters of acinar airways and blood vessel network. Data obtained on 8 healthy volunteers are in good agreement with literature values. This information is complementary to the information that is obtained by means of in vivo lung morphometry technique with hyperpolarized 3He diffusion MRI previously developed by our group and opens new opportunities to study lung microstructure in health and disease. PMID:24920182
Pseudo CT estimation from MRI using patch-based random forest

NASA Astrophysics Data System (ADS)

Yang, Xiaofeng; Lei, Yang; Shu, Hui-Kuo; Rossi, Peter; Mao, Hui; Shim, Hyunsuk; Curran, Walter J.; Liu, Tian

2017-02-01

Recently, MR simulators gain popularity because of unnecessary radiation exposure of CT simulators being used in radiation therapy planning. We propose a method for pseudo CT estimation from MR images based on a patch-based random forest. Patient-specific anatomical features are extracted from the aligned training images and adopted as signatures for each voxel. The most robust and informative features are identified using feature selection to train the random forest. The well-trained random forest is used to predict the pseudo CT of a new patient. This prediction technique was tested with human brain images and the prediction accuracy was assessed using the original CT images. Peak signal-to-noise ratio (PSNR) and feature similarity (FSIM) indexes were used to quantify the differences between the pseudo and original CT images. The experimental results showed the proposed method could accurately generate pseudo CT images from MR images. In summary, we have developed a new pseudo CT prediction method based on patch-based random forest, demonstrated its clinical feasibility, and validated its prediction accuracy. This pseudo CT prediction technique could be a useful tool for MRI-based radiation treatment planning and attenuation correction in a PET/MRI scanner.
Double temporal sparsity based accelerated reconstruction of compressively sensed resting-state fMRI.

PubMed

Aggarwal, Priya; Gupta, Anubha

2017-12-01

A number of reconstruction methods have been proposed recently for accelerated functional Magnetic Resonance Imaging (fMRI) data collection. However, existing methods suffer with the challenge of greater artifacts at high acceleration factors. This paper addresses the issue of accelerating fMRI collection via undersampled k-space measurements combined with the proposed method based on l 1 -l 1 norm constraints, wherein we impose first l 1 -norm sparsity on the voxel time series (temporal data) in the transformed domain and the second l 1 -norm sparsity on the successive difference of the same temporal data. Hence, we name the proposed method as Double Temporal Sparsity based Reconstruction (DTSR) method. The robustness of the proposed DTSR method has been thoroughly evaluated both at the subject level and at the group level on real fMRI data. Results are presented at various acceleration factors. Quantitative analysis in terms of Peak Signal-to-Noise Ratio (PSNR) and other metrics, and qualitative analysis in terms of reproducibility of brain Resting State Networks (RSNs) demonstrate that the proposed method is accurate and robust. In addition, the proposed DTSR method preserves brain networks that are important for studying fMRI data. Compared to the existing methods, the DTSR method shows promising potential with an improvement of 10-12 dB in PSNR with acceleration factors upto 3.5 on resting state fMRI data. Simulation results on real data demonstrate that DTSR method can be used to acquire accelerated fMRI with accurate detection of RSNs. Copyright © 2017 Elsevier Ltd. All rights reserved.
Pattern classification of fMRI data: applications for analysis of spatially distributed cortical networks.

PubMed

Yourganov, Grigori; Schmah, Tanya; Churchill, Nathan W; Berman, Marc G; Grady, Cheryl L; Strother, Stephen C

2014-08-01

The field of fMRI data analysis is rapidly growing in sophistication, particularly in the domain of multivariate pattern classification. However, the interaction between the properties of the analytical model and the parameters of the BOLD signal (e.g. signal magnitude, temporal variance and functional connectivity) is still an open problem. We addressed this problem by evaluating a set of pattern classification algorithms on simulated and experimental block-design fMRI data. The set of classifiers consisted of linear and quadratic discriminants, linear support vector machine, and linear and nonlinear Gaussian naive Bayes classifiers. For linear discriminant, we used two methods of regularization: principal component analysis, and ridge regularization. The classifiers were used (1) to classify the volumes according to the behavioral task that was performed by the subject, and (2) to construct spatial maps that indicated the relative contribution of each voxel to classification. Our evaluation metrics were: (1) accuracy of out-of-sample classification and (2) reproducibility of spatial maps. In simulated data sets, we performed an additional evaluation of spatial maps with ROC analysis. We varied the magnitude, temporal variance and connectivity of simulated fMRI signal and identified the optimal classifier for each simulated environment. Overall, the best performers were linear and quadratic discriminants (operating on principal components of the data matrix) and, in some rare situations, a nonlinear Gaussian naïve Bayes classifier. The results from the simulated data were supported by within-subject analysis of experimental fMRI data, collected in a study of aging. This is the first study that systematically characterizes interactions between analysis model and signal parameters (such as magnitude, variance and correlation) on the performance of pattern classifiers for fMRI. Copyright © 2014 Elsevier Inc. All rights reserved.
A two-step super-Gaussian independent component analysis approach for fMRI data.

PubMed

Ge, Ruiyang; Yao, Li; Zhang, Hang; Long, Zhiying

2015-09-01

Independent component analysis (ICA) has been widely applied to functional magnetic resonance imaging (fMRI) data analysis. Although ICA assumes that the sources underlying data are statistically independent, it usually ignores sources' additional properties, such as sparsity. In this study, we propose a two-step super-GaussianICA (2SGICA) method that incorporates the sparse prior of the sources into the ICA model. 2SGICA uses the super-Gaussian ICA (SGICA) algorithm that is based on a simplified Lewicki-Sejnowski's model to obtain the initial source estimate in the first step. Using a kernel estimator technique, the source density is acquired and fitted to the Laplacian function based on the initial source estimates. The fitted Laplacian prior is used for each source at the second SGICA step. Moreover, the automatic target generation process for initial value generation is used in 2SGICA to guarantee the stability of the algorithm. An adaptive step size selection criterion is also implemented in the proposed algorithm. We performed experimental tests on both simulated data and real fMRI data to investigate the feasibility and robustness of 2SGICA and made a performance comparison between InfomaxICA, FastICA, mean field ICA (MFICA) with Laplacian prior, sparse online dictionary learning (ODL), SGICA and 2SGICA. Both simulated and real fMRI experiments showed that the 2SGICA was most robust to noises, and had the best spatial detection power and the time course estimation among the six methods. Copyright © 2015. Published by Elsevier Inc.
An improved cylindrical FDTD method and its application to field-tissue interaction study in MRI.

PubMed

Chi, Jieru; Liu, Feng; Xia, Ling; Shao, Tingting; Mason, David G; Crozier, Stuart

2010-01-01

This paper presents a three dimensional finite-difference time-domain (FDTD) scheme in cylindrical coordinates with an improved algorithm for accommodating the numerical singularity associated with the polar axis. The regularization of this singularity problem is entirely based on Ampere's law. The proposed algorithm has been detailed and verified against a problem with a known solution obtained from a commercial electromagnetic simulation package. The numerical scheme is also illustrated by modeling high-frequency RF field-human body interactions in MRI. The results demonstrate the accuracy and capability of the proposed algorithm.
Characterization of cardiac flow in heart disease patients by computational fluid dynamics and 4D flow MRI

NASA Astrophysics Data System (ADS)

Lantz, Jonas; Gupta, Vikas; Henriksson, Lilian; Karlsson, Matts; Persson, Ander; Carhall, Carljohan; Ebbers, Tino

2017-11-01

In this study, cardiac blood flow was simulated using Computational Fluid Dynamics and compared to in vivo flow measurements by 4D Flow MRI. In total, nine patients with various heart diseases were studied. Geometry and heart wall motion for the simulations were obtained from clinical CT measurements, with 0.3x0.3x0.3 mm spatial resolution and 20 time frames covering one heartbeat. The CFD simulations included pulmonary veins, left atrium and ventricle, mitral and aortic valve, and ascending aorta. Mesh sizes were on the order of 6-16 million cells, depending on the size of the heart, in order to resolve both papillary muscles and trabeculae. The computed flow field agreed visually very well with 4D Flow MRI, with characteristic vortices and flow structures seen in both techniques. Regression analysis showed that peak flow rate as well as stroke volume had an excellent agreement for the two techniques. We demonstrated the feasibility, and more importantly, fidelity of cardiac flow simulations by comparing CFD results to in vivo measurements. Both qualitative and quantitative results agreed well with the 4D Flow MRI measurements. Also, the developed simulation methodology enables ``what if'' scenarios, such as optimization of valve replacement and other surgical procedures. Funded by the Wallenberg Foundation.
A Non-Parametric Approach for the Activation Detection of Block Design fMRI Simulated Data Using Self-Organizing Maps and Support Vector Machine.

PubMed

Bahrami, Sheyda; Shamsi, Mousa

2017-01-01

Functional magnetic resonance imaging (fMRI) is a popular method to probe the functional organization of the brain using hemodynamic responses. In this method, volume images of the entire brain are obtained with a very good spatial resolution and low temporal resolution. However, they always suffer from high dimensionality in the face of classification algorithms. In this work, we combine a support vector machine (SVM) with a self-organizing map (SOM) for having a feature-based classification by using SVM. Then, a linear kernel SVM is used for detecting the active areas. Here, we use SOM for feature extracting and labeling the datasets. SOM has two major advances: (i) it reduces dimension of data sets for having less computational complexity and (ii) it is useful for identifying brain regions with small onset differences in hemodynamic responses. Our non-parametric model is compared with parametric and non-parametric methods. We use simulated fMRI data sets and block design inputs in this paper and consider the contrast to noise ratio (CNR) value equal to 0.6 for simulated datasets. fMRI simulated dataset has contrast 1-4% in active areas. The accuracy of our proposed method is 93.63% and the error rate is 6.37%.
An Adaptive MR-CT Registration Method for MRI-guided Prostate Cancer Radiotherapy

PubMed Central

Zhong, Hualiang; Wen, Ning; Gordon, James; Elshaikh, Mohamed A; Movsas, Benjamin; Chetty, Indrin J.

2015-01-01

Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ/cm3, and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume during the transformation between the MR and CT images and improves the accuracy of the B-spline registrations in the prostate region. The approach will be valuable for development of high-quality MRI-guided radiation therapy. PMID:25775937
An adaptive MR-CT registration method for MRI-guided prostate cancer radiotherapy

NASA Astrophysics Data System (ADS)

Zhong, Hualiang; Wen, Ning; Gordon, James J.; Elshaikh, Mohamed A.; Movsas, Benjamin; Chetty, Indrin J.

2015-04-01

Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ cm-3, and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume during the transformation between the MR and CT images and improves the accuracy of the B-spline registrations in the prostate region. The approach will be valuable for the development of high-quality MRI-guided radiation therapy.

MRI reconstruction with joint global regularization and transform learning.

PubMed

Tanc, A Korhan; Eksioglu, Ender M

2016-10-01

Sparsity based regularization has been a popular approach to remedy the measurement scarcity in image reconstruction. Recently, sparsifying transforms learned from image patches have been utilized as an effective regularizer for the Magnetic Resonance Imaging (MRI) reconstruction. Here, we infuse additional global regularization terms to the patch-based transform learning. We develop an algorithm to solve the resulting novel cost function, which includes both patchwise and global regularization terms. Extensive simulation results indicate that the introduced mixed approach has improved MRI reconstruction performance, when compared to the algorithms which use either of the patchwise transform learning or global regularization terms alone. Copyright © 2016 Elsevier Ltd. All rights reserved.
Multiparametric MRI followed by targeted prostate biopsy for men with suspected prostate cancer: a clinical decision analysis

PubMed Central

Willis, Sarah R; Ahmed, Hashim U; Moore, Caroline M; Donaldson, Ian; Emberton, Mark; Miners, Alec H; van der Meulen, Jan

2014-01-01

Objective To compare the diagnostic outcomes of the current approach of transrectal ultrasound (TRUS)-guided biopsy in men with suspected prostate cancer to an alternative approach using multiparametric MRI (mpMRI), followed by MRI-targeted biopsy if positive. Design Clinical decision analysis was used to synthesise data from recently emerging evidence in a format that is relevant for clinical decision making. Population A hypothetical cohort of 1000 men with suspected prostate cancer. Interventions mpMRI and, if positive, MRI-targeted biopsy compared with TRUS-guided biopsy in all men. Outcome measures We report the number of men expected to undergo a biopsy as well as the numbers of correctly identified patients with or without prostate cancer. A probabilistic sensitivity analysis was carried out using Monte Carlo simulation to explore the impact of statistical uncertainty in the diagnostic parameters. Results In 1000 men, mpMRI followed by MRI-targeted biopsy ‘clinically dominates’ TRUS-guided biopsy as it results in fewer expected biopsies (600 vs 1000), more men being correctly identified as having clinically significant cancer (320 vs 250), and fewer men being falsely identified (20 vs 50). The mpMRI-based strategy dominated TRUS-guided biopsy in 86% of the simulations in the probabilistic sensitivity analysis. Conclusions Our analysis suggests that mpMRI followed by MRI-targeted biopsy is likely to result in fewer and better biopsies than TRUS-guided biopsy. Future research in prostate cancer should focus on providing precise estimates of key diagnostic parameters. PMID:24934207
Phase-contrast MRI versus numerical simulation to quantify hemodynamical changes in cerebral aneurysms after flow diverter treatment

PubMed Central

Frolov, Sergey; Prothmann, Sascha; Liepsch, Dieter; Balasso, Andrea; Berg, Philipp; Kaczmarz, Stephan; Kirschke, Jan Stefan

2018-01-01

Cerebral aneurysms are a major risk factor for intracranial bleeding with devastating consequences for the patient. One recently established treatment is the implantation of flow-diverters (FD). Methods to predict their treatment success before or directly after implantation are not well investigated yet. The aim of this work was to quantitatively study hemodynamic parameters in patient-specific models of treated cerebral aneurysms and its correlation with the clinical outcome. Hemodynamics were evaluated using both computational fluid dynamics (CFD) and phase contrast (PC) MRI. CFD simulations and in vitro MRI measurements were done under similar flow conditions and results of both methods were comparatively analyzed. For preoperative and postoperative distribution of hemodynamic parameters, CFD simulations and PC-MRI velocity measurements showed similar results. In both cases where no occlusion of the aneurysm was observed after six months, a flow reduction of about 30-50% was found, while in the clinically successful case with complete occlusion of the aneurysm after 6 months, the flow reduction was about 80%. No vortex was observed in any of the three models after treatment. The results are in agreement with recent studies suggesting that CFD simulations can predict post-treatment aneurysm flow alteration already before implantation of a FD and PC-MRI could validate the predicted hemodynamic changes right after implantation of a FD. PMID:29304062
Super-resolution reconstruction of MR image with a novel residual learning network algorithm

NASA Astrophysics Data System (ADS)

Shi, Jun; Liu, Qingping; Wang, Chaofeng; Zhang, Qi; Ying, Shihui; Xu, Haoyu

2018-04-01

Spatial resolution is one of the key parameters of magnetic resonance imaging (MRI). The image super-resolution (SR) technique offers an alternative approach to improve the spatial resolution of MRI due to its simplicity. Convolutional neural networks (CNN)-based SR algorithms have achieved state-of-the-art performance, in which the global residual learning (GRL) strategy is now commonly used due to its effectiveness for learning image details for SR. However, the partial loss of image details usually happens in a very deep network due to the degradation problem. In this work, we propose a novel residual learning-based SR algorithm for MRI, which combines both multi-scale GRL and shallow network block-based local residual learning (LRL). The proposed LRL module works effectively in capturing high-frequency details by learning local residuals. One simulated MRI dataset and two real MRI datasets have been used to evaluate our algorithm. The experimental results show that the proposed SR algorithm achieves superior performance to all of the other compared CNN-based SR algorithms in this work.
Functional magnetic resonance imaging activation detection: fuzzy cluster analysis in wavelet and multiwavelet domains.

PubMed

Jahanian, Hesamoddin; Soltanian-Zadeh, Hamid; Hossein-Zadeh, Gholam-Ali

2005-09-01

To present novel feature spaces, based on multiscale decompositions obtained by scalar wavelet and multiwavelet transforms, to remedy problems associated with high dimension of functional magnetic resonance imaging (fMRI) time series (when they are used directly in clustering algorithms) and their poor signal-to-noise ratio (SNR) that limits accurate classification of fMRI time series according to their activation contents. Using randomization, the proposed method finds wavelet/multiwavelet coefficients that represent the activation content of fMRI time series and combines them to define new feature spaces. Using simulated and experimental fMRI data sets, the proposed feature spaces are compared to the cross-correlation (CC) feature space and their performances are evaluated. In these studies, the false positive detection rate is controlled using randomization. To compare different methods, several points of the receiver operating characteristics (ROC) curves, using simulated data, are estimated and compared. The proposed features suppress the effects of confounding signals and improve activation detection sensitivity. Experimental results show improved sensitivity and robustness of the proposed method compared to the conventional CC analysis. More accurate and sensitive activation detection can be achieved using the proposed feature spaces compared to CC feature space. Multiwavelet features show superior detection sensitivity compared to the scalar wavelet features. (c) 2005 Wiley-Liss, Inc.
Direct Patlak Reconstruction From Dynamic PET Data Using the Kernel Method With MRI Information Based on Structural Similarity.

PubMed

Gong, Kuang; Cheng-Liao, Jinxiu; Wang, Guobao; Chen, Kevin T; Catana, Ciprian; Qi, Jinyi

2018-04-01

Positron emission tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neuroscience. It is highly sensitive, but suffers from relatively poor spatial resolution, as compared with anatomical imaging modalities, such as magnetic resonance imaging (MRI). With the recent development of combined PET/MR systems, we can improve the PET image quality by incorporating MR information into image reconstruction. Previously, kernel learning has been successfully embedded into static and dynamic PET image reconstruction using either PET temporal or MRI information. Here, we combine both PET temporal and MRI information adaptively to improve the quality of direct Patlak reconstruction. We examined different approaches to combine the PET and MRI information in kernel learning to address the issue of potential mismatches between MRI and PET signals. Computer simulations and hybrid real-patient data acquired on a simultaneous PET/MR scanner were used to evaluate the proposed methods. Results show that the method that combines PET temporal information and MRI spatial information adaptively based on the structure similarity index has the best performance in terms of noise reduction and resolution improvement.
EKG-based detection of deep brain stimulation in fMRI studies.

PubMed

Fiveland, Eric; Madhavan, Radhika; Prusik, Julia; Linton, Renee; Dimarzio, Marisa; Ashe, Jeffrey; Pilitsis, Julie; Hancu, Ileana

2018-04-01

To assess the impact of synchronization errors between the assumed functional MRI paradigm timing and the deep brain stimulation (DBS) on/off cycling using a custom electrocardiogram-based triggering system METHODS: A detector for measuring and predicting the on/off state of cycling deep brain stimulation was developed and tested in six patients in office visits. Three-electrode electrocardiogram measurements, amplified by a commercial bio-amplifier, were used as input for a custom electronics box (e-box). The e-box transformed the deep brain stimulation waveforms into transistor-transistor logic pulses, recorded their timing, and propagated it in time. The e-box was used to trigger task-based deep brain stimulation functional MRI scans in 5 additional subjects; the impact of timing accuracy on t-test values was investigated in a simulation study using the functional MRI data. Following locking to each patient's individual waveform, the e-box was shown to predict stimulation onset with an average absolute error of 112 ± 148 ms, 30 min after disconnecting from the patients. The subsecond accuracy of the e-box in predicting timing onset is more than adequate for our slow varying, 30-/30-s on/off stimulation paradigm. Conversely, the experimental deep brain stimulation onset prediction accuracy in the absence of the e-box, which could be off by as much as 4 to 6 s, could significantly decrease activation strength. Using this detector, stimulation can be accurately synchronized to functional MRI acquisitions, without adding any additional hardware in the MRI environment. Magn Reson Med 79:2432-2439, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
Susceptibility-based functional brain mapping by 3D deconvolution of an MR-phase activation map.

PubMed

Chen, Zikuan; Liu, Jingyu; Calhoun, Vince D

2013-05-30

The underlying source of T2*-weighted magnetic resonance imaging (T2*MRI) for brain imaging is magnetic susceptibility (denoted by χ). T2*MRI outputs a complex-valued MR image consisting of magnitude and phase information. Recent research has shown that both the magnitude and the phase images are morphologically different from the source χ, primarily due to 3D convolution, and that the source χ can be reconstructed from complex MR images by computed inverse MRI (CIMRI). Thus, we can obtain a 4D χ dataset from a complex 4D MR dataset acquired from a brain functional MRI study by repeating CIMRI to reconstruct 3D χ volumes at each timepoint. Because the reconstructed χ is a more direct representation of neuronal activity than the MR image, we propose a method for χ-based functional brain mapping, which is numerically characterised by a temporal correlation map of χ responses to a stimulant task. Under the linear imaging conditions used for T2*MRI, we show that the χ activation map can be calculated from the MR phase map by CIMRI. We validate our approach using numerical simulations and Gd-phantom experiments. We also analyse real data from a finger-tapping visuomotor experiment and show that the χ-based functional mapping provides additional activation details (in the form of positive and negative correlation patterns) beyond those generated by conventional MR-magnitude-based mapping. Copyright © 2013 Elsevier B.V. All rights reserved.
Comparison of 4D Phase-Contrast MRI Flow Measurements to Computational Fluid Dynamics Simulations of Cerebrospinal Fluid Motion in the Cervical Spine

PubMed Central

Yiallourou, Theresia I.; Kröger, Jan Robert; Stergiopulos, Nikolaos; Maintz, David

2012-01-01

Cerebrospinal fluid (CSF) dynamics in the cervical spinal subarachnoid space (SSS) have been thought to be important to help diagnose and assess craniospinal disorders such as Chiari I malformation (CM). In this study we obtained time-resolved three directional velocity encoded phase-contrast MRI (4D PC MRI) in three healthy volunteers and four CM patients and compared the 4D PC MRI measurements to subject-specific 3D computational fluid dynamics (CFD) simulations. The CFD simulations considered the geometry to be rigid-walled and did not include small anatomical structures such as nerve roots, denticulate ligaments and arachnoid trabeculae. Results were compared at nine axial planes along the cervical SSS in terms of peak CSF velocities in both the cranial and caudal direction and visual interpretation of thru-plane velocity profiles. 4D PC MRI peak CSF velocities were consistently greater than the CFD peak velocities and these differences were more pronounced in CM patients than in healthy subjects. In the upper cervical SSS of CM patients the 4D PC MRI quantified stronger fluid jets than the CFD. Visual interpretation of the 4D PC MRI thru-plane velocity profiles showed greater pulsatile movement of CSF in the anterior SSS in comparison to the posterior and reduction in local CSF velocities near nerve roots. CFD velocity profiles were relatively uniform around the spinal cord for all subjects. This study represents the first comparison of 4D PC MRI measurements to CFD of CSF flow in the cervical SSS. The results highlight the utility of 4D PC MRI for evaluation of complex CSF dynamics and the need for improvement of CFD methodology. Future studies are needed to investigate whether integration of fine anatomical structures and gross motion of the brain and/or spinal cord into the computational model will lead to a better agreement between the two techniques. PMID:23284970
A Unified Framework for Brain Segmentation in MR Images

PubMed Central

Yazdani, S.; Yusof, R.; Karimian, A.; Riazi, A. H.; Bennamoun, M.

2015-01-01

Brain MRI segmentation is an important issue for discovering the brain structure and diagnosis of subtle anatomical changes in different brain diseases. However, due to several artifacts brain tissue segmentation remains a challenging task. The aim of this paper is to improve the automatic segmentation of brain into gray matter, white matter, and cerebrospinal fluid in magnetic resonance images (MRI). We proposed an automatic hybrid image segmentation method that integrates the modified statistical expectation-maximization (EM) method and the spatial information combined with support vector machine (SVM). The combined method has more accurate results than what can be achieved with its individual techniques that is demonstrated through experiments on both real data and simulated images. Experiments are carried out on both synthetic and real MRI. The results of proposed technique are evaluated against manual segmentation results and other methods based on real T1-weighted scans from Internet Brain Segmentation Repository (IBSR) and simulated images from BrainWeb. The Kappa index is calculated to assess the performance of the proposed framework relative to the ground truth and expert segmentations. The results demonstrate that the proposed combined method has satisfactory results on both simulated MRI and real brain datasets. PMID:26089978
Comparative ergonomic workflow and user experience analysis of MRI versus fluoroscopy-guided vascular interventions: an iliac angioplasty exemplar case study.

PubMed

Fernández-Gutiérrez, Fabiola; Martínez, Santiago; Rube, Martin A; Cox, Benjamin F; Fatahi, Mahsa; Scott-Brown, Kenneth C; Houston, J Graeme; McLeod, Helen; White, Richard D; French, Karen; Gueorguieva, Mariana; Immel, Erwin; Melzer, Andreas

2015-10-01

A methodological framework is introduced to assess and compare a conventional fluoroscopy protocol for peripheral angioplasty with a new magnetic resonant imaging (MRI)-guided protocol. Different scenarios were considered during interventions on a perfused arterial phantom with regard to time-based and cognitive task analysis, user experience and ergonomics. Three clinicians with different expertise performed a total of 43 simulated common iliac angioplasties (9 fluoroscopic, 34 MRI-guided) in two blocks of sessions. Six different configurations for MRI guidance were tested in the first block. Four of them were evaluated in the second block and compared to the fluoroscopy protocol. Relevant stages' durations were collected, and interventions were audio-visually recorded from different perspectives. A cued retrospective protocol analysis (CRPA) was undertaken, including personal interviews. In addition, ergonomic constraints in the MRI suite were evaluated. Significant differences were found when comparing the performance between MRI configurations versus fluoroscopy. Two configurations [with times of 8.56 (0.64) and 9.48 (1.13) min] led to reduce procedure time for MRI guidance, comparable to fluoroscopy [8.49 (0.75) min]. The CRPA pointed out the main influential factors for clinical procedure performance. The ergonomic analysis quantified musculoskeletal risks for interventional radiologists when utilising MRI. Several alternatives were suggested to prevent potential low-back injuries. This work presents a step towards the implementation of efficient operational protocols for MRI-guided procedures based on an integral and multidisciplinary framework, applicable to the assessment of current vascular protocols. The use of first-user perspective raises the possibility of establishing new forms of clinical training and education.
TU-AB-BRA-09: A Novel Method of Generating Ultrafast Volumetric Cine MRI (VC-MRI) Using Prior 4D-MRI and On-Board Phase-Skipped Encoding Acquisition for Radiotherapy Target Localization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, C; Yin, F; Harris, W

Purpose: To develop a technique generating ultrafast on-board VC-MRI using prior 4D-MRI and on-board phase-skipped encoding k-space acquisition for real-time 3D target tracking of liver and lung radiotherapy. Methods: The end-of-expiration (EOE) volume in 4D-MRI acquired during the simulation was selected as the prior volume. 3 major respiratory deformation patterns were extracted through the principal component analysis of the deformation field maps (DFMs) generated between EOE and all other phases. The on-board VC-MRI at each instant was considered as a deformation of the prior volume, and the deformation was modeled as a linear combination of the extracted 3 major deformationmore » patterns. To solve the weighting coefficients of the 3 major patterns, a 2D slice was extracted from VC-MRI volume to match with the 2D on-board sampling data, which was generated by 8-fold phase skipped-encoding k-space acquisition (i.e., sample 1 phase-encoding line out of every 8 lines) to achieve an ultrafast 16–24 volumes/s frame rate. The method was evaluated using XCAT digital phantom to simulate lung cancer patients. The 3D volume of end-ofinhalation (EOI) phase at the treatment day was used as ground-truth onboard VC-MRI with simulated changes in 1) breathing amplitude and 2) breathing amplitude/phase change from the simulation day. A liver cancer patient case was evaluated for in-vivo feasibility demonstration. Results: The comparison between ground truth and estimated on-board VC-MRI shows good agreements. In XCAT study with changed breathing amplitude, the volume-percent-difference(VPD) between ground-truth and estimated tumor volumes at EOI was 6.28% and the Center-of-Mass-Shift(COMS) was 0.82mm; with changed breathing amplitude and phase, the VPD was 8.50% and the COMS was 0.54mm. The study of liver patient case also demonstrated a promising in vivo feasibility of the proposed method Conclusion: Preliminary results suggest the feasibility to estimate ultrafast VC-MRI for on-board target localization with phase skipped-encoding k-space acquisition. Research grant from NIH R01-184173.« less
Cumulant expansions for measuring water exchange using diffusion MRI

NASA Astrophysics Data System (ADS)

Ning, Lipeng; Nilsson, Markus; Lasič, Samo; Westin, Carl-Fredrik; Rathi, Yogesh

2018-02-01

The rate of water exchange across cell membranes is a parameter of biological interest and can be measured by diffusion magnetic resonance imaging (dMRI). In this work, we investigate a stochastic model for the diffusion-and-exchange of water molecules. This model provides a general solution for the temporal evolution of dMRI signal using any type of gradient waveform, thereby generalizing the signal expressions for the Kärger model. Moreover, we also derive a general nth order cumulant expansion of the dMRI signal accounting for water exchange, which has not been explored in earlier studies. Based on this analytical expression, we compute the cumulant expansion for dMRI signals for the special case of single diffusion encoding (SDE) and double diffusion encoding (DDE) sequences. Our results provide a theoretical guideline on optimizing experimental parameters for SDE and DDE sequences, respectively. Moreover, we show that DDE signals are more sensitive to water exchange at short-time scale but provide less attenuation at long-time scale than SDE signals. Our theoretical analysis is also validated using Monte Carlo simulations on synthetic structures.
Parallel group independent component analysis for massive fMRI data sets.

PubMed

Chen, Shaojie; Huang, Lei; Qiu, Huitong; Nebel, Mary Beth; Mostofsky, Stewart H; Pekar, James J; Lindquist, Martin A; Eloyan, Ani; Caffo, Brian S

2017-01-01

Independent component analysis (ICA) is widely used in the field of functional neuroimaging to decompose data into spatio-temporal patterns of co-activation. In particular, ICA has found wide usage in the analysis of resting state fMRI (rs-fMRI) data. Recently, a number of large-scale data sets have become publicly available that consist of rs-fMRI scans from thousands of subjects. As a result, efficient ICA algorithms that scale well to the increased number of subjects are required. To address this problem, we propose a two-stage likelihood-based algorithm for performing group ICA, which we denote Parallel Group Independent Component Analysis (PGICA). By utilizing the sequential nature of the algorithm and parallel computing techniques, we are able to efficiently analyze data sets from large numbers of subjects. We illustrate the efficacy of PGICA, which has been implemented in R and is freely available through the Comprehensive R Archive Network, through simulation studies and application to rs-fMRI data from two large multi-subject data sets, consisting of 301 and 779 subjects respectively.
A hybrid approach for fusing 4D-MRI temporal information with 3D-CT for the study of lung and lung tumor motion.

PubMed

Yang, Y X; Teo, S-K; Van Reeth, E; Tan, C H; Tham, I W K; Poh, C L

2015-08-01

Accurate visualization of lung motion is important in many clinical applications, such as radiotherapy of lung cancer. Advancement in imaging modalities [e.g., computed tomography (CT) and MRI] has allowed dynamic imaging of lung and lung tumor motion. However, each imaging modality has its advantages and disadvantages. The study presented in this paper aims at generating synthetic 4D-CT dataset for lung cancer patients by combining both continuous three-dimensional (3D) motion captured by 4D-MRI and the high spatial resolution captured by CT using the authors' proposed approach. A novel hybrid approach based on deformable image registration (DIR) and finite element method simulation was developed to fuse a static 3D-CT volume (acquired under breath-hold) and the 3D motion information extracted from 4D-MRI dataset, creating a synthetic 4D-CT dataset. The study focuses on imaging of lung and lung tumor. Comparing the synthetic 4D-CT dataset with the acquired 4D-CT dataset of six lung cancer patients based on 420 landmarks, accurate results (average error <2 mm) were achieved using the authors' proposed approach. Their hybrid approach achieved a 40% error reduction (based on landmarks assessment) over using only DIR techniques. The synthetic 4D-CT dataset generated has high spatial resolution, has excellent lung details, and is able to show movement of lung and lung tumor over multiple breathing cycles.
Safety evaluation of a leadless transcatheter pacemaker for magnetic resonance imaging use.

PubMed

Soejima, Kyoko; Edmonson, Jonathan; Ellingson, Michael L; Herberg, Ben; Wiklund, Craig; Zhao, Jing

2016-10-01

Increased magnetic resonance imaging (MRI) adoption and demand are driving the need for device patients to have safe access to MRI. The aim of this study was to address the interactions of MRI with the Micra transcatheter pacemaker system. A strategy was developed to evaluate potential MRI risks including device heating, unintended cardiac stimulation, force, torque, vibration, and device malfunction. Assessment of MRI-induced device heating was conducted using a phantom containing gelled saline, and Monte Carlo simulations incorporating these results were conducted to simulate numerous combinations of human body models, position locations in the MRI scanner bore, and a variety of coil designs. Lastly, a patient with a Micra pacemaker who underwent a clinically indicated MRI scan is presented. Compared to traditional MRI conditional pacemakers, the overall risk with Micra was greatly reduced because of the small size of the device and the absence of a lead. The modeling results predicted that the nonperfused temperature rise of the device would be less than 0.4°C at 1.5 T and 0.5°C at 3 T and that the risk of device heating with multiple device implants was not increased as compared with a single device. The clinical case study revealed no MRI-related complications. The MRI safety assessment tests conducted for the Micra pacemaker demonstrate that patients with a single device or multiple devices can safely undergo MRI scans in both 1.5- and 3-T MRI scanners. No MRI-related complications were observed in a patient implanted with a Micra pacemaker undergoing a clinically indicated scan. Copyright © 2016 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.
Automated selection of brain regions for real-time fMRI brain-computer interfaces

NASA Astrophysics Data System (ADS)

Lührs, Michael; Sorger, Bettina; Goebel, Rainer; Esposito, Fabrizio

2017-02-01

Objective. Brain-computer interfaces (BCIs) implemented with real-time functional magnetic resonance imaging (rt-fMRI) use fMRI time-courses from predefined regions of interest (ROIs). To reach best performances, localizer experiments and on-site expert supervision are required for ROI definition. To automate this step, we developed two unsupervised computational techniques based on the general linear model (GLM) and independent component analysis (ICA) of rt-fMRI data, and compared their performances on a communication BCI. Approach. 3 T fMRI data of six volunteers were re-analyzed in simulated real-time. During a localizer run, participants performed three mental tasks following visual cues. During two communication runs, a letter-spelling display guided the subjects to freely encode letters by performing one of the mental tasks with a specific timing. GLM- and ICA-based procedures were used to decode each letter, respectively using compact ROIs and whole-brain distributed spatio-temporal patterns of fMRI activity, automatically defined from subject-specific or group-level maps. Main results. Letter-decoding performances were comparable to supervised methods. In combination with a similarity-based criterion, GLM- and ICA-based approaches successfully decoded more than 80% (average) of the letters. Subject-specific maps yielded optimal performances. Significance. Automated solutions for ROI selection may help accelerating the translation of rt-fMRI BCIs from research to clinical applications.
Respiratory motion correction in dynamic MRI using robust data decomposition registration - application to DCE-MRI.

PubMed

Hamy, Valentin; Dikaios, Nikolaos; Punwani, Shonit; Melbourne, Andrew; Latifoltojar, Arash; Makanyanga, Jesica; Chouhan, Manil; Helbren, Emma; Menys, Alex; Taylor, Stuart; Atkinson, David

2014-02-01

Motion correction in Dynamic Contrast Enhanced (DCE-) MRI is challenging because rapid intensity changes can compromise common (intensity based) registration algorithms. In this study we introduce a novel registration technique based on robust principal component analysis (RPCA) to decompose a given time-series into a low rank and a sparse component. This allows robust separation of motion components that can be registered, from intensity variations that are left unchanged. This Robust Data Decomposition Registration (RDDR) is demonstrated on both simulated and a wide range of clinical data. Robustness to different types of motion and breathing choices during acquisition is demonstrated for a variety of imaged organs including liver, small bowel and prostate. The analysis of clinically relevant regions of interest showed both a decrease of error (15-62% reduction following registration) in tissue time-intensity curves and improved areas under the curve (AUC60) at early enhancement. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.
Simulating the Effect of Spectroscopic MRI as a Metric for Radiation Therapy Planning in Patients with Glioblastoma

PubMed Central

Cordova, J. Scott; Kandula, Shravan; Gurbani, Saumya; Zhong, Jim; Tejani, Mital; Kayode, Oluwatosin; Patel, Kirtesh; Prabhu, Roshan; Schreibmann, Eduard; Crocker, Ian; Holder, Chad A.; Shim, Hyunsuk; Shu, Hui-Kuo

2017-01-01

Due to glioblastoma’s infiltrative nature, an optimal radiation therapy (RT) plan requires targeting infiltration not identified by anatomical magnetic resonance imaging (MRI). Here, high-resolution, whole-brain spectroscopic MRI (sMRI) is used to describe tumor infiltration alongside anatomical MRI and simulate the degree to which it modifies RT target planning. In 11 patients with glioblastoma, data from preRT sMRI scans were processed to give high-resolution, whole-brain metabolite maps normalized by contralateral white matter. Maps depicting choline to N-Acetylaspartate (Cho/NAA) ratios were registered to contrast-enhanced T1-weighted RT planning MRI for each patient. Volumes depicting metabolic abnormalities (1.5−, 1.75−, and 2.0-fold increases in Cho/NAA ratios) were compared with conventional target volumes and contrast-enhancing tumor at recurrence. sMRI-modified RT plans were generated to evaluate target volume coverage and organ-at-risk dose constraints. Conventional clinical target volumes and Cho/NAA abnormalities identified significantly different regions of microscopic infiltration with substantial Cho/NAA abnormalities falling outside of the conventional 60 Gy isodose line (41.1, 22.2, and 12.7 cm3, respectively). Clinical target volumes using Cho/NAA thresholds exhibited significantly higher coverage of contrast enhancement at recurrence on average (92.4%, 90.5%, and 88.6%, respectively) than conventional plans (82.5%). sMRI-based plans targeting tumor infiltration met planning objectives in all cases with no significant change in target coverage. In 2 cases, the sMRI-modified plan exhibited better coverage of contrast-enhancing tumor at recurrence than the original plan. Integration of the high-resolution, whole-brain sMRI into RT planning is feasible, resulting in RT target volumes that can effectively target tumor infiltration while adhering to conventional constraints. PMID:28105468
Simulated Design Strategies for SPECT Collimators to Reduce the Eddy Currents Induced by MRI Gradient Fields

NASA Astrophysics Data System (ADS)

Samoudi, Amine M.; Van Audenhaege, Karen; Vermeeren, Günter; Verhoyen, Gregory; Martens, Luc; Van Holen, Roel; Joseph, Wout

2015-10-01

Combining single photon emission computed tomography (SPECT) with magnetic resonance imaging (MRI) requires the insertion of highly conductive SPECT collimators inside the MRI scanner, resulting in an induced eddy current disturbing the combined system. We reduced the eddy currents due to the insert of a novel tungsten collimator inside transverse and longitudinal gradient coils. The collimator was produced with metal additive manufacturing, that is part of a microSPECT insert for a preclinical SPECT/MRI scanner. We characterized the induced magnetic field due to the gradient field and adapted the collimators to reduce the induced eddy currents. We modeled the x-, y-, and z-gradient coil and the different collimator designs and simulated them with FEKO, a three-dimensional method of moments / finite element methods (MoM/FEM) full-wave simulation tool. We used a time analysis approach to generate the pulsed magnetic field gradient. Simulation results show that the maximum induced field can be reduced by 50.82% in the final design bringing the maximum induced magnetic field to less than 2% of the applied gradient for all the gradient coils. The numerical model was validated with measurements and was proposed as a tool for studying the effect of a SPECT collimator within the MRI gradient coils.

Technical Note: Multipurpose CT, ultrasound, and MRI breast phantom for use in radiotherapy and minimally invasive interventions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruschin, Mark, E-mail: Mark.Ruschin@sunnybrook.ca; Chin, Lee; Ravi, Ananth

Purpose: To develop a multipurpose gel-based breast phantom consisting of a simulated tumor with realistic imaging properties in CT, ultrasound and MRI, or a postsurgical cavity on CT. Applications for the phantom include: deformable image registration (DIR) quality assurance (QA), autosegmentation validation, and localization testing and training for minimally invasive image-guided procedures such as those involving catheter or needle insertion. Methods: A thermoplastic mask of a typical breast patient lying supine was generated and then filled to make an array of phantoms. The background simulated breast tissue consisted of 32.4 g each of ballistic gelatin (BG) powder and Metamusil™ (MM)more » dissolved in 800 ml of water. Simulated tumors were added using the following recipe: 12 g of barium sulfate (1.4% v/v) plus 0.000 14 g copper sulfate plus 0.7 g of MM plus 7.2 g of BG all dissolved in 75 ml of water. The phantom was evaluated quantitatively in CT by comparing Hounsfield units (HUs) with actual breast tissue. For ultrasound and MRI, the phantoms were assessed based on subjective image quality and signal-difference to noise (SDNR) ratio, respectively. The stiffness of the phantom was evaluated based on ultrasound elastography measurements to yield an average Young’s modulus. In addition, subjective tactile assessment of phantom was performed under needle insertion. Results: The simulated breast tissue had a mean background value of 24 HU on CT imaging, which more closely resembles fibroglandular tissue (40 HU) as opposed to adipose (−100 HU). The tumor had a mean CT number of 45 HU, which yielded a qualitatively realistic image contrast relative to the background either as an intact tumor or postsurgical cavity. The tumor appeared qualitatively realistic on ultrasound images, exhibiting hypoechoic characteristics compared to background. On MRI, the tumor exhibited a SDNR of 3.7. The average Young’s modulus was computed to be 15.8 ± 0.7 kPa (1 SD). Conclusions: We have developed a process to efficiently and inexpensively produce multipurpose breast phantoms containing simulated tumors visible on CT, ultrasound, and MRI. The phantoms have been evaluated for image quality and elasticity and can serve as a medium for DIR QA, autosegmentation QA, and training for minimally invasive procedures.« less
The Virtual Mouse Brain: A Computational Neuroinformatics Platform to Study Whole Mouse Brain Dynamics.

PubMed

Melozzi, Francesca; Woodman, Marmaduke M; Jirsa, Viktor K; Bernard, Christophe

2017-01-01

Connectome-based modeling of large-scale brain network dynamics enables causal in silico interrogation of the brain's structure-function relationship, necessitating the close integration of diverse neuroinformatics fields. Here we extend the open-source simulation software The Virtual Brain (TVB) to whole mouse brain network modeling based on individual diffusion magnetic resonance imaging (dMRI)-based or tracer-based detailed mouse connectomes. We provide practical examples on how to use The Virtual Mouse Brain (TVMB) to simulate brain activity, such as seizure propagation and the switching behavior of the resting state dynamics in health and disease. TVMB enables theoretically driven experimental planning and ways to test predictions in the numerous strains of mice available to study brain function in normal and pathological conditions.
A virtual reality system for neurobehavioral and functional MRI studies.

PubMed

Baumann, Stephen; Neff, Chris; Fetzick, Scott; Stangl, Gregg; Basler, Lee; Vereneck, Ray; Schneider, Walter

2003-06-01

We are developing a VR system of integrated software and hardware for scientific research and clinical application. The system is sufficiently flexible and broad-based in appeal that neurobehavioral researchers from a variety of disciplines might be interested in using it for basic research and clinical studies. The system runs on a standard Windows-based personal computer with a high-performance graphics card. Options allow a head-mounted display, dataglove, simultaneous physiological monitoring or use within neuroimaging machines such as magnetic resonance imaging (MRI) scanners. Currently, the software consists of a virtual world of nearly a dozen interconnected environments that the subject can freely navigate. Additional environments can be built and easily added to the application. A startup interface provides menus for selecting characters and objects that a researcher might want to put at specific locations within the simulation. Interactivity is provided for many typical objects such as doors, chairs and money. There are more than 50 characters in the world, most of them animated or interactive. All movements and actions of the subject within the world are tracked and recorded to an Excel spreadsheet for data analysis. Overlay maps are available as navigational aids. Concurrent physiological data can be acquired on up to 16 channels. The system provides synchronization of the VR simulation with physiological recordings and functional MR images. A spatial navigation memory task was performed with the integrated VR/fMRI system, and some pilot data is presented that shows robust activation in multiple cortical areas appropriate to the task.
Validation of Shared and Specific Independent Component Analysis (SSICA) for Between-Group Comparisons in fMRI

PubMed Central

Maneshi, Mona; Vahdat, Shahabeddin; Gotman, Jean; Grova, Christophe

2016-01-01

Independent component analysis (ICA) has been widely used to study functional magnetic resonance imaging (fMRI) connectivity. However, the application of ICA in multi-group designs is not straightforward. We have recently developed a new method named “shared and specific independent component analysis” (SSICA) to perform between-group comparisons in the ICA framework. SSICA is sensitive to extract those components which represent a significant difference in functional connectivity between groups or conditions, i.e., components that could be considered “specific” for a group or condition. Here, we investigated the performance of SSICA on realistic simulations, and task fMRI data and compared the results with one of the state-of-the-art group ICA approaches to infer between-group differences. We examined SSICA robustness with respect to the number of allowable extracted specific components and between-group orthogonality assumptions. Furthermore, we proposed a modified formulation of the back-reconstruction method to generate group-level t-statistics maps based on SSICA results. We also evaluated the consistency and specificity of the extracted specific components by SSICA. The results on realistic simulated and real fMRI data showed that SSICA outperforms the regular group ICA approach in terms of reconstruction and classification performance. We demonstrated that SSICA is a powerful data-driven approach to detect patterns of differences in functional connectivity across groups/conditions, particularly in model-free designs such as resting-state fMRI. Our findings in task fMRI show that SSICA confirms results of the general linear model (GLM) analysis and when combined with clustering analysis, it complements GLM findings by providing additional information regarding the reliability and specificity of networks. PMID:27729843
PET and MRI image fusion based on combination of 2-D Hilbert transform and IHS method.

PubMed

Haddadpour, Mozhdeh; Daneshvar, Sabalan; Seyedarabi, Hadi

2017-08-01

The process of medical image fusion is combining two or more medical images such as Magnetic Resonance Image (MRI) and Positron Emission Tomography (PET) and mapping them to a single image as fused image. So purpose of our study is assisting physicians to diagnose and treat the diseases in the least of the time. We used Magnetic Resonance Image (MRI) and Positron Emission Tomography (PET) as input images, so fused them based on combination of two dimensional Hilbert transform (2-D HT) and Intensity Hue Saturation (IHS) method. Evaluation metrics that we apply are Discrepancy (D k ) as an assessing spectral features and Average Gradient (AG k ) as an evaluating spatial features and also Overall Performance (O.P) to verify properly of the proposed method. In this paper we used three common evaluation metrics like Average Gradient (AG k ) and the lowest Discrepancy (D k ) and Overall Performance (O.P) to evaluate the performance of our method. Simulated and numerical results represent the desired performance of proposed method. Since that the main purpose of medical image fusion is preserving both spatial and spectral features of input images, so based on numerical results of evaluation metrics such as Average Gradient (AG k ), Discrepancy (D k ) and Overall Performance (O.P) and also desired simulated results, it can be concluded that our proposed method can preserve both spatial and spectral features of input images. Copyright © 2017 Chang Gung University. Published by Elsevier B.V. All rights reserved.
Evaluation of a new satellite-based precipitation dataset for climate studies in the Xiang River basin, Southern China

NASA Astrophysics Data System (ADS)

Zhu, Q.; Xu, Y. P.; Hsu, K. L.

2017-12-01

A new satellite-based precipitation dataset, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) with long-term time series dating back to 1983 can be one valuable dataset for climate studies. This study investigates the feasibility of using PERSIANN-CDR as a reference dataset for climate studies. Sixteen CMIP5 models are evaluated over the Xiang River basin, southern China, by comparing their performance on precipitation projection and streamflow simulation, particularly on extreme precipitation and streamflow events. The results show PERSIANN-CDR is a valuable dataset for climate studies, even on extreme precipitation events. The precipitation estimates and their extreme events from CMIP5 models are improved significantly compared with rain gauge observations after bias-correction by the PERSIANN-CDR precipitation estimates. Given streamflows simulated with raw and bias-corrected precipitation estimates from 16 CMIP5 models, 10 out of 16 are improved after bias-correction. The impact of bias-correction on extreme events for streamflow simulations are unstable, with eight out of 16 models can be clearly claimed they are improved after the bias-correction. Concerning the performance of raw CMIP5 models on precipitation, IPSL-CM5A-MR excels the other CMIP5 models, while MRI-CGCM3 outperforms on extreme events with its better performance on six extreme precipitation metrics. Case studies also show that raw CCSM4, CESM1-CAM5, and MRI-CGCM3 outperform other models on streamflow simulation, while MIROC5-ESM-CHEM, MIROC5-ESM and IPSL-CM5A-MR behaves better than the other models after bias-correction.
From Complex B1 Mapping to Local SAR Estimation for Human Brain MR Imaging Using Multi-channel Transceiver Coil at 7T

PubMed Central

Zhang, Xiaotong; Schmitter, Sebastian; Van de Moortel, Pierre-François; Liu, Jiaen

2014-01-01

Elevated Specific Absorption Rate (SAR) associated with increased main magnetic field strength remains as a major safety concern in ultra-high-field (UHF) Magnetic Resonance Imaging (MRI) applications. The calculation of local SAR requires the knowledge of the electric field induced by radiofrequency (RF) excitation, and the local electrical properties of tissues. Since electric field distribution cannot be directly mapped in conventional MR measurements, SAR estimation is usually performed using numerical model-based electromagnetic simulations which, however, are highly time consuming and cannot account for the specific anatomy and tissue properties of the subject undergoing a scan. In the present study, starting from the measurable RF magnetic fields (B1) in MRI, we conducted a series of mathematical deduction to estimate the local, voxel-wise and subject-specific SAR for each single coil element using a multi-channel transceiver array coil. We first evaluated the feasibility of this approach in numerical simulations including two different human head models. We further conducted experimental study in a physical phantom and in two human subjects at 7T using a multi-channel transceiver head coil. Accuracy of the results is discussed in the context of predicting local SAR in the human brain at UHF MRI using multi-channel RF transmission. PMID:23508259
Cost-Effectiveness of Diagnostic Strategies for Suspected Scaphoid Fractures.

PubMed

Yin, Zhong-Gang; Zhang, Jian-Bing; Gong, Ke-Tong

2015-08-01

The aim of this study was to assess the cost effectiveness of multiple competing diagnostic strategies for suspected scaphoid fractures. With published data, the authors created a decision-tree model simulating the diagnosis of suspected scaphoid fractures. Clinical outcomes, costs, and cost effectiveness of immediate computed tomography (CT), day 3 magnetic resonance imaging (MRI), day 3 bone scan, week 2 radiographs alone, week 2 radiographs-CT, week 2 radiographs-MRI, week 2 radiographs-bone scan, and immediate MRI were evaluated. The primary clinical outcome was the detection of scaphoid fractures. The authors adopted societal perspective, including both the costs of healthcare and the cost of lost productivity. The incremental cost-effectiveness ratio (ICER), which expresses the incremental cost per incremental scaphoid fracture detected using a strategy, was calculated to compare these diagnostic strategies. Base case analysis, 1-way sensitivity analyses, and "worst case scenario" and "best case scenario" sensitivity analyses were performed. In the base case, the average cost per scaphoid fracture detected with immediate CT was $2553. The ICER of immediate MRI and day 3 MRI compared with immediate CT was $7483 and $32,000 per scaphoid fracture detected, respectively. The ICER of week 2 radiographs-MRI was around $170,000. Day 3 bone scan, week 2 radiographs alone, week 2 radiographs-CT, and week 2 radiographs-bone scan strategy were dominated or extendedly dominated by MRI strategies. The results were generally robust in multiple sensitivity analyses. Immediate CT and MRI were the most cost-effective strategies for diagnosing suspected scaphoid fractures. Economic and Decision Analyses Level II. See Instructions for Authors for a complete description of levels of evidence.
MRI of retinoblastoma

PubMed Central

Razek, A A K A; Elkhamary, S

2011-01-01

We review the role of MRI in retinoblastoma and simulating lesions. Retinoblastoma is the most common paediatric intra-ocular tumour. It may be endophytic, exophytic or a diffuse infiltrating tumour. MRI can detect intra-ocular, extra-ocular and intracranial extension of the tumour. MRI is essential for monitoring patients after treatment and detection of associated second malignancies. It helps to differentiating the tumour from simulating lesions with leukocoria. PMID:21849363
Atlas-based fuzzy connectedness segmentation and intensity nonuniformity correction applied to brain MRI.

PubMed

Zhou, Yongxin; Bai, Jing

2007-01-01

A framework that combines atlas registration, fuzzy connectedness (FC) segmentation, and parametric bias field correction (PABIC) is proposed for the automatic segmentation of brain magnetic resonance imaging (MRI). First, the atlas is registered onto the MRI to initialize the following FC segmentation. Original techniques are proposed to estimate necessary initial parameters of FC segmentation. Further, the result of the FC segmentation is utilized to initialize a following PABIC algorithm. Finally, we re-apply the FC technique on the PABIC corrected MRI to get the final segmentation. Thus, we avoid expert human intervention and provide a fully automatic method for brain MRI segmentation. Experiments on both simulated and real MRI images demonstrate the validity of the method, as well as the limitation of the method. Being a fully automatic method, it is expected to find wide applications, such as three-dimensional visualization, radiation therapy planning, and medical database construction.
Predicting individual brain functional connectivity using a Bayesian hierarchical model.

PubMed

Dai, Tian; Guo, Ying

2017-02-15

Network-oriented analysis of functional magnetic resonance imaging (fMRI), especially resting-state fMRI, has revealed important association between abnormal connectivity and brain disorders such as schizophrenia, major depression and Alzheimer's disease. Imaging-based brain connectivity measures have become a useful tool for investigating the pathophysiology, progression and treatment response of psychiatric disorders and neurodegenerative diseases. Recent studies have started to explore the possibility of using functional neuroimaging to help predict disease progression and guide treatment selection for individual patients. These studies provide the impetus to develop statistical methodology that would help provide predictive information on disease progression-related or treatment-related changes in neural connectivity. To this end, we propose a prediction method based on Bayesian hierarchical model that uses individual's baseline fMRI scans, coupled with relevant subject characteristics, to predict the individual's future functional connectivity. A key advantage of the proposed method is that it can improve the accuracy of individualized prediction of connectivity by combining information from both group-level connectivity patterns that are common to subjects with similar characteristics as well as individual-level connectivity features that are particular to the specific subject. Furthermore, our method also offers statistical inference tools such as predictive intervals that help quantify the uncertainty or variability of the predicted outcomes. The proposed prediction method could be a useful approach to predict the changes in individual patient's brain connectivity with the progression of a disease. It can also be used to predict a patient's post-treatment brain connectivity after a specified treatment regimen. Another utility of the proposed method is that it can be applied to test-retest imaging data to develop a more reliable estimator for individual functional connectivity. We show there exists a nice connection between our proposed estimator and a recently developed shrinkage estimator of connectivity measures in the neuroimaging community. We develop an expectation-maximization (EM) algorithm for estimation of the proposed Bayesian hierarchical model. Simulations studies are performed to evaluate the accuracy of our proposed prediction methods. We illustrate the application of the methods with two data examples: the longitudinal resting-state fMRI from ADNI2 study and the test-retest fMRI data from Kirby21 study. In both the simulation studies and the fMRI data applications, we demonstrate that the proposed methods provide more accurate prediction and more reliable estimation of individual functional connectivity as compared with alternative methods. Copyright © 2017 Elsevier Inc. All rights reserved.
Cost-effectiveness of magnetic resonance imaging versus ultrasound for the detection of symptomatic full-thickness supraspinatus tendon tears.

PubMed

Gyftopoulos, Soterios; Guja, Kip E; Subhas, Naveen; Virk, Mandeep S; Gold, Heather T

2017-12-01

The purpose of this study was to determine the value of magnetic resonance imaging (MRI) and ultrasound-based imaging strategies in the evaluation of a hypothetical population with a symptomatic full-thickness supraspinatus tendon (FTST) tear using formal cost-effectiveness analysis. A decision analytic model from the health care system perspective for 60-year-old patients with symptoms secondary to a suspected FTST tear was used to evaluate the incremental cost-effectiveness of 3 imaging strategies during a 2-year time horizon: MRI, ultrasound, and ultrasound followed by MRI. Comprehensive literature search and expert opinion provided data on cost, probability, and quality of life estimates. The primary effectiveness outcome was quality-adjusted life-years (QALYs) through 2 years, with a willingness-to-pay threshold set to $100,000/QALY gained (2016 U.S. dollars). Costs and health benefits were discounted at 3%. Ultrasound was the least costly strategy ($1385). MRI was the most effective (1.332 QALYs). Ultrasound was the most cost-effective strategy but was not dominant. The incremental cost-effectiveness ratio for MRI was $22,756/QALY gained, below the willingness-to-pay threshold. Two-way sensitivity analysis demonstrated that MRI was favored over the other imaging strategies over a wide range of reasonable costs. In probabilistic sensitivity analysis, MRI was the preferred imaging strategy in 78% of the simulations. MRI and ultrasound represent cost-effective imaging options for evaluation of the patient thought to have a symptomatic FTST tear. The results indicate that MRI is the preferred strategy based on cost-effectiveness criteria, although the decision between MRI and ultrasound for an imaging center is likely to be dependent on additional factors, such as available resources and workflow. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.
Modeling fMRI signals can provide insights into neural processing in the cerebral cortex

PubMed Central

Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo

2015-01-01

Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals. PMID:25972586
Modeling fMRI signals can provide insights into neural processing in the cerebral cortex.

PubMed

Vanni, Simo; Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo

2015-08-01

Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals. Copyright © 2015 the American Physiological Society.
MO-FG-CAMPUS-IeP3-01: Evaluation of Specific Absorption Rate and Temperature Increase Induced by Artificial Medical Implants During MRI Scan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seo, Y

Purpose: Heating of patients or burning of biological tissues around medical implants by RF power during MRI scan is a significant patient safety concern. The purpose of this study is to not only measure SAR values, but also RF-induced temperature elevation due to artificial hip joints during MRI scans. Methods: SAR measurement experiment was performed on three discrete manufacturers at 1.5 and 3T. Three MRI RF sequences (T1w TSE, T2w inversion recovery, and T2w TSE) with imaging parameters were selected. A gelled saline phantom mimicking human body tissue was made (Fig.1). FDTD method was utilized to calculate the SAR distributionmore » using Sim4Life software. Based on the results of the simulation, 4 electrical field (E-field) sensors were located around two artificial hip joints inside the phantom. 56 Fiber Bragg Grating (FBG) temperature sensors (28 sensors on each artificial hip joint) were located on both left and right artificial hip joints to measure temperature change during MRI scan (Fig.1). Both E-field and FBG temperature sensors were calibrated with traceability at Korea Research Institute of Standards and Science (KRISS). Results: Simulation shows that high SAR values occur in the head and tail of the implanted artificial hip joints (Fig.1 lower right). 3T MRI scanner shows that the local averaged-SAR values measured by probe 1, 2, and 3 are 2.30, 2.77, and 1.68 W/kg, compared to MRI scanner-reported whole body SAR value (≤1.5 W/kg) for T1w TSE and T2w-IR (Table 1). The maximum temperature elevation measured by FBG sensors is 1.49°C at 1.5 T, 2.0°C at 3 T, and 2.56°C at 3 T for T1w TSE, respectively (Table 2). Conclusion: It is essential to assess the safety of MRI system for patient with medical implant by measuring not only accurate SAR deposited in the body, but also temperature elevation due to the deposited SAR during clinical MRI.« less
Mathematical Development and Computational Analysis of Harmonic Phase-Magnetic Resonance Imaging (HARP-MRI) Based on Bloch Nuclear Magnetic Resonance (NMR) Diffusion Model for Myocardial Motion.

PubMed

Dada, Michael O; Jayeoba, Babatunde; Awojoyogbe, Bamidele O; Uno, Uno E; Awe, Oluseyi E

2017-09-13

Harmonic Phase-Magnetic Resonance Imaging (HARP-MRI) is a tagged image analysis method that can measure myocardial motion and strain in near real-time and is considered a potential candidate to make magnetic resonance tagging clinically viable. However, analytical expressions of radially tagged transverse magnetization in polar coordinates (which is required to appropriately describe the shape of the heart) have not been explored because the physics required to directly connect myocardial deformation of tagged Nuclear Magnetic Resonance (NMR) transverse magnetization in polar geometry and the appropriate harmonic phase parameters are not yet available. The analytical solution of Bloch NMR diffusion equation in spherical geometry with appropriate spherical wave tagging function is important for proper analysis and monitoring of heart systolic and diastolic deformation with relevant boundary conditions. In this study, we applied Harmonic Phase MRI method to compute the difference between tagged and untagged NMR transverse magnetization based on the Bloch NMR diffusion equation and obtained radial wave tagging function for analysis of myocardial motion. The analytical solution of the Bloch NMR equations and the computational simulation of myocardial motion as developed in this study are intended to significantly improve healthcare for accurate diagnosis, prognosis and treatment of cardiovascular related deceases at the lowest cost because MRI scan is still one of the most expensive anywhere. The analysis is fundamental and significant because all Magnetic Resonance Imaging techniques are based on the Bloch NMR flow equations.
Quantitative analysis of image quality for acceptance and commissioning of an MRI simulator with a semiautomatic method.

PubMed

Chen, Xinyuan; Dai, Jianrong

2018-05-01

Magnetic Resonance Imaging (MRI) simulation differs from diagnostic MRI in purpose, technical requirements, and implementation. We propose a semiautomatic method for image acceptance and commissioning for the scanner, the radiofrequency (RF) coils, and pulse sequences for an MRI simulator. The ACR MRI accreditation large phantom was used for image quality analysis with seven parameters. Standard ACR sequences with a split head coil were adopted to examine the scanner's basic performance. The performance of simulation RF coils were measured and compared using the standard sequence with different clinical diagnostic coils. We used simulation sequences with simulation coils to test the quality of image and advanced performance of the scanner. Codes and procedures were developed for semiautomatic image quality analysis. When using standard ACR sequences with a split head coil, image quality passed all ACR recommended criteria. The image intensity uniformity with a simulation RF coil decreased about 34% compared with the eight-channel diagnostic head coil, while the other six image quality parameters were acceptable. Those two image quality parameters could be improved to more than 85% by built-in intensity calibration methods. In the simulation sequences test, the contrast resolution was sensitive to the FOV and matrix settings. The geometric distortion of simulation sequences such as T1-weighted and T2-weighted images was well-controlled in the isocenter and 10 cm off-center within a range of ±1% (2 mm). We developed a semiautomatic image quality analysis method for quantitative evaluation of images and commissioning of an MRI simulator. The baseline performances of simulation RF coils and pulse sequences have been established for routine QA. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.
Understanding Accretion Disks through Three Dimensional Radiation MHD Simulations

NASA Astrophysics Data System (ADS)

Jiang, Yan-Fei

I study the structures and thermal properties of black hole accretion disks in the radiation pressure dominated regime. Angular momentum transfer in the disk is provided by the turbulence generated by the magneto-rotational instability (MRI), which is calculated self-consistently with a recently developed 3D radiation magneto-hydrodynamics (MHD) code based on Athena. This code, developed by my collaborators and myself, couples both the radiation momentum and energy source terms with the ideal MHD equations by modifying the standard Godunov method to handle the stiff radiation source terms. We solve the two momentum equations of the radiation transfer equations with a variable Eddington tensor (VET), which is calculated with a time independent short characteristic module. This code is well tested and accurate in both optically thin and optically thick regimes. It is also accurate for both radiation pressure and gas pressure dominated flows. With this code, I find that when photon viscosity becomes significant, the ratio between Maxwell stress and Reynolds stress from the MRI turbulence can increase significantly with radiation pressure. The thermal instability of the radiation pressure dominated disk is then studied with vertically stratified shearing box simulations. Unlike the previous results claiming that the radiation pressure dominated disk with MRI turbulence can reach a steady state without showing any unstable behavior, I find that the radiation pressure dominated disks always either collapse or expand until we have to stop the simulations. During the thermal runaway, the heating and cooling rates from the simulations are consistent with the general criterion of thermal instability. However, details of the thermal runaway are different from the predictions of the standard alpha disk model, as many assumptions in that model are not satisfied in the simulations. We also identify the key reasons why previous simulations do not find the instability. The thermal instability has many important implications for understanding the observations of both X-ray binaries and Active Galactic Nuclei (AGNs). However, direct comparisons between observations and the simulations require global radiation MHD simulations, which will be the main focus of my future work.
Adaptive smoothing based on Gaussian processes regression increases the sensitivity and specificity of fMRI data.

PubMed

Strappini, Francesca; Gilboa, Elad; Pitzalis, Sabrina; Kay, Kendrick; McAvoy, Mark; Nehorai, Arye; Snyder, Abraham Z

2017-03-01

Temporal and spatial filtering of fMRI data is often used to improve statistical power. However, conventional methods, such as smoothing with fixed-width Gaussian filters, remove fine-scale structure in the data, necessitating a tradeoff between sensitivity and specificity. Specifically, smoothing may increase sensitivity (reduce noise and increase statistical power) but at the cost loss of specificity in that fine-scale structure in neural activity patterns is lost. Here, we propose an alternative smoothing method based on Gaussian processes (GP) regression for single subjects fMRI experiments. This method adapts the level of smoothing on a voxel by voxel basis according to the characteristics of the local neural activity patterns. GP-based fMRI analysis has been heretofore impractical owing to computational demands. Here, we demonstrate a new implementation of GP that makes it possible to handle the massive data dimensionality of the typical fMRI experiment. We demonstrate how GP can be used as a drop-in replacement to conventional preprocessing steps for temporal and spatial smoothing in a standard fMRI pipeline. We present simulated and experimental results that show the increased sensitivity and specificity compared to conventional smoothing strategies. Hum Brain Mapp 38:1438-1459, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
A novel electron accelerator for MRI-Linac radiotherapy.

PubMed

Whelan, Brendan; Gierman, Stephen; Holloway, Lois; Schmerge, John; Keall, Paul; Fahrig, Rebecca

2016-03-01

MRI guided radiotherapy is a rapidly growing field; however, current electron accelerators are not designed to operate in the magnetic fringe fields of MRI scanners. As such, current MRI-Linac systems require magnetic shielding, which can degrade MR image quality and limit system flexibility. The purpose of this work was to develop and test a novel medical electron accelerator concept which is inherently robust to operation within magnetic fields for in-line MRI-Linac systems. Computational simulations were utilized to model the accelerator, including the thermionic emission process, the electromagnetic fields within the accelerating structure, and resulting particle trajectories through these fields. The spatial and energy characteristics of the electron beam were quantified at the accelerator target and compared to published data for conventional accelerators. The model was then coupled to the fields from a simulated 1 T superconducting magnet and solved for cathode to isocenter distances between 1.0 and 2.4 m; the impact on the electron beam was quantified. For the zero field solution, the average current at the target was 146.3 mA, with a median energy of 5.8 MeV (interquartile spread of 0.1 MeV), and a spot size diameter of 1.5 mm full-width-tenth-maximum. Such an electron beam is suitable for therapy, comparing favorably to published data for conventional systems. The simulated accelerator showed increased robustness to operation in in-line magnetic fields, with a maximum current loss of 3% compared to 85% for a conventional system in the same magnetic fields. Computational simulations suggest that replacing conventional DC electron sources with a RF based source could be used to develop medical electron accelerators which are robust to operation in in-line magnetic fields. This would enable the development of MRI-Linac systems with no magnetic shielding around the Linac and reduce the requirements for optimization of magnetic fringe field, simplify design of the high-field magnet, and increase system flexibility.

A novel electron accelerator for MRI-Linac radiotherapy

PubMed Central

Whelan, Brendan; Gierman, Stephen; Holloway, Lois; Schmerge, John; Keall, Paul; Fahrig, Rebecca

2016-01-01

Purpose: MRI guided radiotherapy is a rapidly growing field; however, current electron accelerators are not designed to operate in the magnetic fringe fields of MRI scanners. As such, current MRI-Linac systems require magnetic shielding, which can degrade MR image quality and limit system flexibility. The purpose of this work was to develop and test a novel medical electron accelerator concept which is inherently robust to operation within magnetic fields for in-line MRI-Linac systems. Methods: Computational simulations were utilized to model the accelerator, including the thermionic emission process, the electromagnetic fields within the accelerating structure, and resulting particle trajectories through these fields. The spatial and energy characteristics of the electron beam were quantified at the accelerator target and compared to published data for conventional accelerators. The model was then coupled to the fields from a simulated 1 T superconducting magnet and solved for cathode to isocenter distances between 1.0 and 2.4 m; the impact on the electron beam was quantified. Results: For the zero field solution, the average current at the target was 146.3 mA, with a median energy of 5.8 MeV (interquartile spread of 0.1 MeV), and a spot size diameter of 1.5 mm full-width-tenth-maximum. Such an electron beam is suitable for therapy, comparing favorably to published data for conventional systems. The simulated accelerator showed increased robustness to operation in in-line magnetic fields, with a maximum current loss of 3% compared to 85% for a conventional system in the same magnetic fields. Conclusions: Computational simulations suggest that replacing conventional DC electron sources with a RF based source could be used to develop medical electron accelerators which are robust to operation in in-line magnetic fields. This would enable the development of MRI-Linac systems with no magnetic shielding around the Linac and reduce the requirements for optimization of magnetic fringe field, simplify design of the high-field magnet, and increase system flexibility. PMID:26936713
Under-sampling trajectory design for compressed sensing based DCE-MRI.

PubMed

Liu, Duan-duan; Liang, Dong; Zhang, Na; Liu, Xin; Zhang, Yuan-ting

2013-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) needs high temporal and spatial resolution to accurately estimate quantitative parameters and characterize tumor vasculature. Compressed Sensing (CS) has the potential to accomplish this mutual importance. However, the randomness in CS under-sampling trajectory designed using the traditional variable density (VD) scheme may translate to uncertainty in kinetic parameter estimation when high reduction factors are used. Therefore, accurate parameter estimation using VD scheme usually needs multiple adjustments on parameters of Probability Density Function (PDF), and multiple reconstructions even with fixed PDF, which is inapplicable for DCE-MRI. In this paper, an under-sampling trajectory design which is robust to the change on PDF parameters and randomness with fixed PDF is studied. The strategy is to adaptively segment k-space into low-and high frequency domain, and only apply VD scheme in high-frequency domain. Simulation results demonstrate high accuracy and robustness comparing to VD design.
A hybrid approach for fusing 4D-MRI temporal information with 3D-CT for the study of lung and lung tumor motion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Y. X.; Van Reeth, E.; Poh, C. L., E-mail: clpoh@ntu.edu.sg

2015-08-15

Purpose: Accurate visualization of lung motion is important in many clinical applications, such as radiotherapy of lung cancer. Advancement in imaging modalities [e.g., computed tomography (CT) and MRI] has allowed dynamic imaging of lung and lung tumor motion. However, each imaging modality has its advantages and disadvantages. The study presented in this paper aims at generating synthetic 4D-CT dataset for lung cancer patients by combining both continuous three-dimensional (3D) motion captured by 4D-MRI and the high spatial resolution captured by CT using the authors’ proposed approach. Methods: A novel hybrid approach based on deformable image registration (DIR) and finite elementmore » method simulation was developed to fuse a static 3D-CT volume (acquired under breath-hold) and the 3D motion information extracted from 4D-MRI dataset, creating a synthetic 4D-CT dataset. Results: The study focuses on imaging of lung and lung tumor. Comparing the synthetic 4D-CT dataset with the acquired 4D-CT dataset of six lung cancer patients based on 420 landmarks, accurate results (average error <2 mm) were achieved using the authors’ proposed approach. Their hybrid approach achieved a 40% error reduction (based on landmarks assessment) over using only DIR techniques. Conclusions: The synthetic 4D-CT dataset generated has high spatial resolution, has excellent lung details, and is able to show movement of lung and lung tumor over multiple breathing cycles.« less
An image warping technique for rodent brain MRI-histology registration based on thin-plate splines with landmark optimization

NASA Astrophysics Data System (ADS)

Liu, Yutong; Uberti, Mariano; Dou, Huanyu; Mosley, R. Lee; Gendelman, Howard E.; Boska, Michael D.

2009-02-01

Coregistration of in vivo magnetic resonance imaging (MRI) with histology provides validation of disease biomarker and pathobiology studies. Although thin-plate splines are widely used in such image registration, point landmark selection is error prone and often time-consuming. We present a technique to optimize landmark selection for thin-plate splines and demonstrate its usefulness in warping rodent brain MRI to histological sections. In this technique, contours are drawn on the corresponding MRI slices and images of histological sections. The landmarks are extracted from the contours by equal spacing then optimized by minimizing a cost function consisting of the landmark displacement and contour curvature. The technique was validated using simulation data and brain MRI-histology coregistration in a murine model of HIV-1 encephalitis. Registration error was quantified by calculating target registration error (TRE). The TRE of approximately 8 pixels for 20-80 landmarks without optimization was stable at different landmark numbers. The optimized results were more accurate at low landmark numbers (TRE of approximately 2 pixels for 50 landmarks), while the accuracy decreased (TRE approximately 8 pixels for larger numbers of landmarks (70- 80). The results demonstrated that registration accuracy decreases with the increasing landmark numbers offering more confidence in MRI-histology registration using thin-plate splines.
An evaluation of independent component analyses with an application to resting-state fMRI

PubMed Central

Matteson, David S.; Ruppert, David; Eloyan, Ani; Caffo, Brian S.

2013-01-01

Summary We examine differences between independent component analyses (ICAs) arising from different as-sumptions, measures of dependence, and starting points of the algorithms. ICA is a popular method with diverse applications including artifact removal in electrophysiology data, feature extraction in microarray data, and identifying brain networks in functional magnetic resonance imaging (fMRI). ICA can be viewed as a generalization of principal component analysis (PCA) that takes into account higher-order cross-correlations. Whereas the PCA solution is unique, there are many ICA methods–whose solutions may differ. Infomax, FastICA, and JADE are commonly applied to fMRI studies, with FastICA being arguably the most popular. Hastie and Tibshirani (2003) demonstrated that ProDenICA outperformed FastICA in simulations with two components. We introduce the application of ProDenICA to simulations with more components and to fMRI data. ProDenICA was more accurate in simulations, and we identified differences between biologically meaningful ICs from ProDenICA versus other methods in the fMRI analysis. ICA methods require nonconvex optimization, yet current practices do not recognize the importance of, nor adequately address sensitivity to, initial values. We found that local optima led to dramatically different estimates in both simulations and group ICA of fMRI, and we provide evidence that the global optimum from ProDenICA is the best estimate. We applied a modification of the Hungarian (Kuhn-Munkres) algorithm to match ICs from multiple estimates, thereby gaining novel insights into how brain networks vary in their sensitivity to initial values and ICA method. PMID:24350655
WE-B-BRD-00: MRI for Radiation Oncology

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

The use of MRI in radiation therapy is rapidly increasing. Applications vary from the MRI simulator, to the MRI fused with CT, and to the integrated MRI+RT system. Compared with the standard MRI QA, a broader scope of QA features has to be defined in order to maximize the benefits of using MRI in radiation therapy. These QA features include geometric fidelity, image registration, motion management, cross-system alignment, and hardware interference. Advanced MRI techniques require a specific type of QA, as they are being widely used in radiation therapy planning, dose calculations, post-implant dosimetry, and prognoses. A vigorous and adaptivemore » QA program is crucial to defining the responsibility of the entire radiation therapy group and detecting deviations from the performance of high-quality treatment. As a drastic departure from CT simulation, MRI simulation requires changes in the work flow of treatment planning and image guidance. MRI guided radiotherapy platforms are being developed and commercialized to take the advantage of the advance in knowledge, technology and clinical experience. This symposium will from an educational perspective discuss the scope and specific issues related to MRI guided radiotherapy. Learning Objectives: Understand the difference between a standard and a radiotherapy-specific MRI QA program. Understand the effects of MRI artifacts (geometric distortion and motion) on radiotherapy. Understand advanced MRI techniques (ultrashort echo, fast MRI including dynamic MRI and 4DMRI, diffusion, perfusion, and MRS) and related QA. Understand the methods to prepare MRI for treatment planning (electron density assignment, multimodality image registration, segmentation and motion management). Current status of MRI guided treatment platforms. Dr. Jihong Wang has a research grant with Elekta-MRL project. Dr. Ke Sheng receives research grants from Varian Medical systems.« less
MRI-based three-dimensional thermal physiological characterization of thyroid gland of human body.

PubMed

Jin, Chao; He, Zhi Zhu; Yang, Yang; Liu, Jing

2014-01-01

This article is dedicated to present a MRI (magnetic resonance imaging) based three-dimensional finite element modeling on the thermal manifestations relating to the pathophysiology of thyroid gland. An efficient approach for identifying the metabolic dysfunctions of thyroid has also been demonstrated through tracking the localized non-uniform thermal distribution or enhanced dynamic imaging. The temperature features over the skin surface and thyroid domain have been characterized using the numerical simulation and experimental measurement which will help better interpret the thermal physiological mechanisms of the thyroid under steady-state or water-cooling condition. Further, parametric simulations on the hypermetabolism symptoms of hyperthyroidism and thermal effects within thyroid domain caused by varying breathing airflow in the trachea and blood-flow in artery and vein were performed. It was disclosed that among all the parameters, the airflow volume has the largest effect on the total heat flux of thyroid surface. However, thermal contributions caused by varying the breathing frequency and blood-flow velocity are negligibly small. The present study suggests a generalized way for simulating the close to reality physiological behavior or process of human thyroid, which is of significance for disease diagnosis and treatment planning. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.
Flow in cerebral aneurysms: 4D Flow MRI measurements and CFD models

NASA Astrophysics Data System (ADS)

Rayz, Vitaliy; Schnell, Susanne

2017-11-01

4D Flow MRI is capable of measuring blood flow in vivo, providing time-resolved velocity fields in 3D. The dynamic range of the 4D Flow MRI is determined by a velocity sensitivity parameter (venc), set above the expected maximum velocity, which can result in noisy data for slow flow regions. A dual-venc 4D flow MRI technique, where both low- and high-venc data are acquired, can improve velocity-to-noise ratio and, therefore, quantification of clinically-relevant hemodynamic metrics. In this study, patient-specific CFD simulations were used to evaluate the advantages of the dual-venc approach for assessment of the flow in cerebral aneurysms. The flow in 2 cerebral aneurysms was measured in vivo with dual-venc 4D Flow MRI and simulated with CFD, using the MRI data to prescribe flow boundary conditions. The flow fields obtained with computations were compared to those measured with a single- and dual-venc 4D Flow MRI. The numerical models resolved small flow structures near the aneurysmal wall, that were not detected with a single-venc acquisition. Comparison of the numerical and imaging results shows that the dual-venc approach can improve the accuracy of the 4D Flow MRI measurements in regions characterized by high-velocity jets and slow recirculating flows.
Interval From Imaging to Treatment Delivery in the Radiation Surgery Age: How Long Is Too Long?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seymour, Zachary A., E-mail: seymourz@radonc.ucsf.edu; Fogh, Shannon E.; Westcott, Sarah K.

Purpose: The purpose of this study was to evaluate workflow and patient outcomes related to frameless stereotactic radiation surgery (SRS) for brain metastases. Methods and Materials: We reviewed all treatment demographics, clinical outcomes, and workflow timing, including time from magnetic resonance imaging (MRI), computed tomography (CT) simulation, insurance authorization, and consultation to the start of SRS for brain metastases. Results: A total of 82 patients with 151 brain metastases treated with SRS were evaluated. The median times from consultation, insurance authorization, CT simulation, and MRI for treatment planning were 15, 7, 6, and 11 days to SRS. Local freedom from progressionmore » (LFFP) was lower in metastases with MRI ≥14 days before treatment (P=.0003, log rank). The 6- and 12-month LFFP rate were 95% and 75% for metastasis with interval of <14 days from MRI to treatment compared to 56% and 34% for metastases with MRI ≥14 days before treatment. On multivariate analysis, LFFP remained significantly lower for lesions with MRI ≥14 days at SRS (P=.002, Cox proportional hazards; hazard ratio: 3.4, 95% confidence interval: 1.6-7.3). Conclusions: Delay from MRI to SRS treatment delivery for brain metastases appears to reduce local control. Future studies should monitor the timing from imaging acquisition to treatment delivery. Our experience suggests that the time from MRI to treatment should be <14 days.« less
MO-D-PinS Room/Hall E-00: MR Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

2016-06-15

MRI, with its excellent soft tissue contrast and its ability to provide physiological as well as anatomical information, is becoming increasingly used in radiation therapy for treatment planning, image-guided radiation therapy, and treatment evaluation. This session will explore solutions to integrating MRI into the simulation process. Obstacles for using MRI for simulation include distortions and artifacts, image acquisition speed, complexity of imaging techniques, and lack of electron density information. Partners in Solutions presents vendor representatives who will present their approaches to meeting these challenges and others. An increased awareness of how MRI simulation works will allow physicists to better understandmore » and use this powerful technique. The speakers are all employees who are presenting information about their company’s products.« less
Evaluating Dynamic Bivariate Correlations in Resting-state fMRI: A comparison study and a new approach

PubMed Central

Lindquist, Martin A.; Xu, Yuting; Nebel, Mary Beth; Caffo, Brain S.

2014-01-01

To date, most functional Magnetic Resonance Imaging (fMRI) studies have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant across time. However, recently, there has been increased interest in quantifying possible dynamic changes in FC during fMRI experiments, as it is thought this may provide insight into the fundamental workings of brain networks. In this work we focus on the specific problem of estimating the dynamic behavior of pair-wise correlations between time courses extracted from two different regions of the brain. We critique the commonly used sliding-windows technique, and discuss some alternative methods used to model volatility in the finance literature that could also prove useful in the neuroimaging setting. In particular, we focus on the Dynamic Conditional Correlation (DCC) model, which provides a model-based approach towards estimating dynamic correlations. We investigate the properties of several techniques in a series of simulation studies and find that DCC achieves the best overall balance between sensitivity and specificity in detecting dynamic changes in correlations. We also investigate its scalability beyond the bivariate case to demonstrate its utility for studying dynamic correlations between more than two brain regions. Finally, we illustrate its performance in an application to test-retest resting state fMRI data. PMID:24993894
Regional alveolar partial pressure of oxygen measurement with parallel accelerated hyperpolarized gas MRI.

PubMed

Kadlecek, Stephen; Hamedani, Hooman; Xu, Yinan; Emami, Kiarash; Xin, Yi; Ishii, Masaru; Rizi, Rahim

2013-10-01

Alveolar oxygen tension (Pao2) is sensitive to the interplay between local ventilation, perfusion, and alveolar-capillary membrane permeability, and thus reflects physiologic heterogeneity of healthy and diseased lung function. Several hyperpolarized helium ((3)He) magnetic resonance imaging (MRI)-based Pao2 mapping techniques have been reported, and considerable effort has gone toward reducing Pao2 measurement error. We present a new Pao2 imaging scheme, using parallel accelerated MRI, which significantly reduces measurement error. The proposed Pao2 mapping scheme was computer-simulated and was tested on both phantoms and five human subjects. Where possible, correspondence between actual local oxygen concentration and derived values was assessed for both bias (deviation from the true mean) and imaging artifact (deviation from the true spatial distribution). Phantom experiments demonstrated a significantly reduced coefficient of variation using the accelerated scheme. Simulation results support this observation and predict that correspondence between the true spatial distribution and the derived map is always superior using the accelerated scheme, although the improvement becomes less significant as the signal-to-noise ratio increases. Paired measurements in the human subjects, comparing accelerated and fully sampled schemes, show a reduced Pao2 distribution width for 41 of 46 slices. In contrast to proton MRI, acceleration of hyperpolarized imaging has no signal-to-noise penalty; its use in Pao2 measurement is therefore always beneficial. Comparison of multiple schemes shows that the benefit arises from a longer time-base during which oxygen-induced depolarization modifies the signal strength. Demonstration of the accelerated technique in human studies shows the feasibility of the method and suggests that measurement error is reduced here as well, particularly at low signal-to-noise levels. Copyright © 2013 AUR. Published by Elsevier Inc. All rights reserved.
75 FR 28200 - Safety Zone; Washington State Department of Transportation Ferries Division Marine Rescue...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-20

... (M2R) Full-Scale Exercise for a Mass Rescue Incident (MRI) AGENCY: Coast Guard, DHS. ACTION: Temporary... simulate a mass rescue incident (MRI) and will involve an abandon ship scenario with multiple response... full scale exercise which will simulate a MRI to provide training in specific emergency response...
Multiclass fMRI data decoding and visualization using supervised self-organizing maps.

PubMed

Hausfeld, Lars; Valente, Giancarlo; Formisano, Elia

2014-08-01

When multivariate pattern decoding is applied to fMRI studies entailing more than two experimental conditions, a most common approach is to transform the multiclass classification problem into a series of binary problems. Furthermore, for decoding analyses, classification accuracy is often the only outcome reported although the topology of activation patterns in the high-dimensional features space may provide additional insights into underlying brain representations. Here we propose to decode and visualize voxel patterns of fMRI datasets consisting of multiple conditions with a supervised variant of self-organizing maps (SSOMs). Using simulations and real fMRI data, we evaluated the performance of our SSOM-based approach. Specifically, the analysis of simulated fMRI data with varying signal-to-noise and contrast-to-noise ratio suggested that SSOMs perform better than a k-nearest-neighbor classifier for medium and large numbers of features (i.e. 250 to 1000 or more voxels) and similar to support vector machines (SVMs) for small and medium numbers of features (i.e. 100 to 600voxels). However, for a larger number of features (>800voxels), SSOMs performed worse than SVMs. When applied to a challenging 3-class fMRI classification problem with datasets collected to examine the neural representation of three human voices at individual speaker level, the SSOM-based algorithm was able to decode speaker identity from auditory cortical activation patterns. Classification performances were similar between SSOMs and other decoding algorithms; however, the ability to visualize decoding models and underlying data topology of SSOMs promotes a more comprehensive understanding of classification outcomes. We further illustrated this visualization ability of SSOMs with a re-analysis of a dataset examining the representation of visual categories in the ventral visual cortex (Haxby et al., 2001). This analysis showed that SSOMs could retrieve and visualize topography and neighborhood relations of the brain representation of eight visual categories. We conclude that SSOMs are particularly suited for decoding datasets consisting of more than two classes and are optimally combined with approaches that reduce the number of voxels used for classification (e.g. region-of-interest or searchlight approaches). Copyright © 2014. Published by Elsevier Inc.
Advances in locally constrained k-space-based parallel MRI.

PubMed

Samsonov, Alexey A; Block, Walter F; Arunachalam, Arjun; Field, Aaron S

2006-02-01

In this article, several theoretical and methodological developments regarding k-space-based, locally constrained parallel MRI (pMRI) reconstruction are presented. A connection between Parallel MRI with Adaptive Radius in k-Space (PARS) and GRAPPA methods is demonstrated. The analysis provides a basis for unified treatment of both methods. Additionally, a weighted PARS reconstruction is proposed, which may absorb different weighting strategies for improved image reconstruction. Next, a fast and efficient method for pMRI reconstruction of data sampled on non-Cartesian trajectories is described. In the new technique, the computational burden associated with the numerous matrix inversions in the original PARS method is drastically reduced by limiting direct calculation of reconstruction coefficients to only a few reference points. The rest of the coefficients are found by interpolating between the reference sets, which is possible due to the similar configuration of points participating in reconstruction for highly symmetric trajectories, such as radial and spirals. As a result, the time requirements are drastically reduced, which makes it practical to use pMRI with non-Cartesian trajectories in many applications. The new technique was demonstrated with simulated and actual data sampled on radial trajectories. Copyright 2006 Wiley-Liss, Inc.
Effect of pulse sequence parameter selection on signal strength in positive-contrast MRI markers for MRI-based prostate postimplant assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lim, Tze Yee

Purpose: For postimplant dosimetric assessment, computed tomography (CT) is commonly used to identify prostate brachytherapy seeds, at the expense of accurate anatomical contouring. Magnetic resonance imaging (MRI) is superior to CT for anatomical delineation, but identification of the negative-contrast seeds is challenging. Positive-contrast MRI markers were proposed to replace spacers to assist seed localization on MRI images. Visualization of these markers under varying scan parameters was investigated. Methods: To simulate a clinical scenario, a prostate phantom was implanted with 66 markers and 86 seeds, and imaged on a 3.0T MRI scanner using a 3D fast radiofrequency-spoiled gradient recalled echo acquisitionmore » with various combinations of scan parameters. Scan parameters, including flip angle, number of excitations, bandwidth, field-of-view, slice thickness, and encoding steps were systematically varied to study their effects on signal, noise, scan time, image resolution, and artifacts. Results: The effects of pulse sequence parameter selection on the marker signal strength and image noise were characterized. The authors also examined the tradeoff between signal-to-noise ratio, scan time, and image artifacts, such as the wraparound artifact, susceptibility artifact, chemical shift artifact, and partial volume averaging artifact. Given reasonable scan time and managable artifacts, the authors recommended scan parameter combinations that can provide robust visualization of the MRI markers. Conclusions: The recommended MRI pulse sequence protocol allows for consistent visualization of the markers to assist seed localization, potentially enabling MRI-only prostate postimplant dosimetry.« less
High success rates of sedation-free brain MRI scanning in young children using simple subject preparation protocols with and without a commercial mock scanner–the Diabetes Research in Children Network (DirecNet) experience

PubMed Central

Barnea-Goraly, Naama; Weinzimer, Stuart A.; Mauras, Nelly; Beck, Roy W.; Marzelli, Matt J.; Mazaika, Paul K.; Aye, Tandy; White, Neil H.; Tsalikian, Eva; Fox, Larry; Kollman, Craig; Cheng, Peiyao; Reiss, Allan L.

2013-01-01

Background The ability to lie still in an MRI scanner is essential for obtaining usable image data. To reduce motion, young children are often sedated, adding significant cost and risk. Objective We assessed the feasibility of using a simple and affordable behavioral desensitization program to yield high-quality brain MRI scans in sedation-free children. Materials and methods 222 children (4–9.9 years), 147 with type 1 diabetes and 75 age-matched non-diabetic controls, participated in a multi-site study focused on effects of type 1 diabetes on the developing brain. T1-weighted and diffusion-weighted imaging (DWI) MRI scans were performed. All children underwent behavioral training and practice MRI sessions using either a commercial MRI simulator or an inexpensive mock scanner consisting of a toy tunnel, vibrating mat, and video player to simulate the sounds and feel of the MRI scanner. Results 205 children (92.3%), mean age 7±1.7 years had high-quality T1-W scans and 174 (78.4%) had high-quality diffusion-weighted scans after the first scan session. With a second scan session, success rates were 100% and 92.5% for T1-and diffusion-weighted scans, respectively. Success rates did not differ between children with type 1 diabetes and children without diabetes, or between centers using a commercial MRI scan simulator and those using the inexpensive mock scanner. Conclusion Behavioral training can lead to a high success rate for obtaining high-quality T1-and diffusion-weighted brain images from a young population without sedation. PMID:24096802
Identification and mitigation of interference sources present in SSB-based wireless MRI receiver arrays

PubMed Central

Riffe, Matthew J.; Twieg, Michael D.; Gudino, Natalia; Blumenthal, Colin J.; Heilman, Jeremy A.; Griswold, Mark A.

2013-01-01

Purpose Single sideband amplitude modulation (SSB) is an appealing platform for highly parallel wireless MRI detector arrays because the spacing between channels is ideally limited only by the MRI signal bandwidth. However this assumes that no other sources of interference are present outside that bandwidth. This work investigates the practical interference between multiple SSB-encoded MRI signals. Methods Noise from coil preamplifiers and carrier bleed-through are identified as sources of interference. Two different SSB systems were designed for 1.5T with different noise filtering properties. We show how the differences between the filtered noise profiles impact the received MR signal’s dynamic range (DRsig) and image signal-to-noise ratio (SNR) through simulation, bench measurements, and phantom imaging experiments. Results When operating individually in the MR scanner, both SSB systems were shown to minimally impact the original DRsig and SNR. On the other hand, when all eight channels were operating simultaneously, an average SNR loss was observed to be 12% in the one system, while a second system with more complex filtering was able to achieve a 3% loss in SNR. Conclusion Successful wireless transmission of multiple SSB-encoded MRI signals is possible as long as channel interference is properly managed through design and simulation. PMID:23413242
The Potential for an Enhanced Role for MRI in Radiation-therapy Treatment Planning

PubMed Central

Metcalfe, P.; Liney, G. P.; Holloway, L.; Walker, A.; Barton, M.; Delaney, G. P.; Vinod, S.; Tomé, W.

2013-01-01

The exquisite soft-tissue contrast of magnetic resonance imaging (MRI) has meant that the technique is having an increasing role in contouring the gross tumor volume (GTV) and organs at risk (OAR) in radiation therapy treatment planning systems (TPS). MRI-planning scans from diagnostic MRI scanners are currently incorporated into the planning process by being registered to CT data. The soft-tissue data from the MRI provides target outline guidance and the CT provides a solid geometric and electron density map for accurate dose calculation on the TPS computer. There is increasing interest in MRI machine placement in radiotherapy clinics as an adjunct to CT simulators. Most vendors now offer 70 cm bores with flat couch inserts and specialised RF coil designs. We would refer to these devices as MR-simulators. There is also research into the future application of MR-simulators independent of CT and as in-room image-guidance devices. It is within the background of this increased interest in the utility of MRI in radiotherapy treatment planning that this paper is couched. The paper outlines publications that deal with standard MRI sequences used in current clinical practice. It then discusses the potential for using processed functional diffusion maps (fDM) derived from diffusion weighted image sequences in tracking tumor activity and tumor recurrence. Next, this paper reviews publications that describe the use of MRI in patient-management applications that may, in turn, be relevant to radiotherapy treatment planning. The review briefly discusses the concepts behind functional techniques such as dynamic contrast enhanced (DCE), diffusion-weighted (DW) MRI sequences and magnetic resonance spectroscopic imaging (MRSI). Significant applications of MR are discussed in terms of the following treatment sites: brain, head and neck, breast, lung, prostate and cervix. While not yet routine, the use of apparent diffusion coefficient (ADC) map analysis indicates an exciting future application for functional MRI. Although DW-MRI has not yet been routinely used in boost adaptive techniques, it is being assessed in cohort studies for sub-volume boosting in prostate tumors. PMID:23617289
Alcohol Dose Effects on Brain Circuits During Simulated Driving: An fMRI Study

PubMed Central

Meda, Shashwath A.; Calhoun, Vince D.; Astur, Robert S.; Turner, Beth M.; Ruopp, Kathryn; Pearlson, Godfrey D.

2009-01-01

Driving while intoxicated remains a major public health hazard. Driving is a complex task involving simultaneous recruitment of multiple cognitive functions. The investigators studied the neural substrates of driving and their response to different blood alcohol concentrations (BACs), using functional magnetic resonance imaging (fMRI) and a virtual reality driving simulator. We used independent component analysis (ICA) to isolate spatially independent and temporally correlated driving-related brain circuits in 40 healthy, adult moderate social drinkers. Each subject received three individualized, separate single-blind doses of beverage alcohol to produce BACs of 0.05% (moderate), 0.10% (high), or 0% (placebo). 3 T fMRI scanning and continuous behavioral measurement occurred during simulated driving. Brain function was assessed and compared using both ICA and a conventional general linear model (GLM) analysis. ICA results replicated and significantly extended our previous 1.5T study (Calhoun et al. [2004a]: Neuropsychopharmacology 29:2097–2017). GLM analysis revealed significant dose-related functional differences, complementing ICA data. Driving behaviors including opposite white line crossings and mean speed independently demonstrated significant dose-dependent changes. Behavior-based factors also predicted a frontal-basal-temporal circuit to be functionally impaired with alcohol dosage across baseline scaled, good versus poorly performing drivers. We report neural correlates of driving behavior and found dose-related spatio-temporal disruptions in critical driving-associated regions including the superior, middle and orbito frontal gyri, anterior cingulate, primary/supplementary motor areas, basal ganglia, and cerebellum. Overall, results suggest that alcohol (especially at high doses) causes significant impairment of both driving behavior and brain functionality related to motor planning and control, goal directedness, error monitoring, and memory. PMID:18571794

MRI-guided fluorescence tomography of the breast: a phantom study

NASA Astrophysics Data System (ADS)

Davis, Scott C.; Pogue, Brian W.; Dehghani, Hamid; Paulsen, Keith D.

2009-02-01

Tissue phantoms simulating the human breast were used to demonstrate the imaging capabilities of an MRI-coupled fluorescence molecular tomography (FMT) imaging system. Specifically, phantoms with low tumor-to-normal drug contrast and complex internal structure were imaged with the MR-coupled FMT system. Images of indocyanine green (ICG) fluorescence yield were recovered using a diffusion model-based approach capable of estimating the distribution of fluorescence activity in a tissue volume from tissue-boundary measurements of transmitted light. Tissue structural information, which can be determined from standard T1 and T2 MR images, was used to guide the recovery of fluorescence activity. The study revealed that this spatial guidance is critical for recovering images of fluorescence yield in tissue with low tumor-to-normal drug contrast.
A New MRI-Based Model of Heart Function with Coupled Hemodynamics and Application to Normal and Diseased Canine Left Ventricles

PubMed Central

Choi, Young Joon; Constantino, Jason; Vedula, Vijay; Trayanova, Natalia; Mittal, Rajat

2015-01-01

A methodology for the simulation of heart function that combines an MRI-based model of cardiac electromechanics (CE) with a Navier–Stokes-based hemodynamics model is presented. The CE model consists of two coupled components that simulate the electrical and the mechanical functions of the heart. Accurate representations of ventricular geometry and fiber orientations are constructed from the structural magnetic resonance and the diffusion tensor MR images, respectively. The deformation of the ventricle obtained from the electromechanical model serves as input to the hemodynamics model in this one-way coupled approach via imposed kinematic wall velocity boundary conditions and at the same time, governs the blood flow into and out of the ventricular volume. The time-dependent endocardial surfaces are registered using a diffeomorphic mapping algorithm, while the intraventricular blood flow patterns are simulated using a sharp-interface immersed boundary method-based flow solver. The utility of the combined heart-function model is demonstrated by comparing the hemodynamic characteristics of a normal canine heart beating in sinus rhythm against that of the dyssynchronously beating failing heart. We also discuss the potential of coupled CE and hemodynamics models for various clinical applications. PMID:26442254
MRI-based modeling for radiocarpal joint mechanics: validation criteria and results for four specimen-specific models.

PubMed

Fischer, Kenneth J; Johnson, Joshua E; Waller, Alexander J; McIff, Terence E; Toby, E Bruce; Bilgen, Mehmet

2011-10-01

The objective of this study was to validate the MRI-based joint contact modeling methodology in the radiocarpal joints by comparison of model results with invasive specimen-specific radiocarpal contact measurements from four cadaver experiments. We used a single validation criterion for multiple outcome measures to characterize the utility and overall validity of the modeling approach. For each experiment, a Pressurex film and a Tekscan sensor were sequentially placed into the radiocarpal joints during simulated grasp. Computer models were constructed based on MRI visualization of the cadaver specimens without load. Images were also acquired during the loaded configuration used with the direct experimental measurements. Geometric surface models of the radius, scaphoid and lunate (including cartilage) were constructed from the images acquired without the load. The carpal bone motions from the unloaded state to the loaded state were determined using a series of 3D image registrations. Cartilage thickness was assumed uniform at 1.0 mm with an effective compressive modulus of 4 MPa. Validation was based on experimental versus model contact area, contact force, average contact pressure and peak contact pressure for the radioscaphoid and radiolunate articulations. Contact area was also measured directly from images acquired under load and compared to the experimental and model data. Qualitatively, there was good correspondence between the MRI-based model data and experimental data, with consistent relative size, shape and location of radioscaphoid and radiolunate contact regions. Quantitative data from the model generally compared well with the experimental data for all specimens. Contact area from the MRI-based model was very similar to the contact area measured directly from the images. For all outcome measures except average and peak pressures, at least two specimen models met the validation criteria with respect to experimental measurements for both articulations. Only the model for one specimen met the validation criteria for average and peak pressure of both articulations; however the experimental measures for peak pressure also exhibited high variability. MRI-based modeling can reliably be used for evaluating the contact area and contact force with similar confidence as in currently available experimental techniques. Average contact pressure, and peak contact pressure were more variable from all measurement techniques, and these measures from MRI-based modeling should be used with some caution.
Analysis of a simulation algorithm for direct brain drug delivery

PubMed Central

Rosenbluth, Kathryn Hammond; Eschermann, Jan Felix; Mittermeyer, Gabriele; Thomson, Rowena; Mittermeyer, Stephan; Bankiewicz, Krystof S.

2011-01-01

Convection enhanced delivery (CED) achieves targeted delivery of drugs with a pressure-driven infusion through a cannula placed stereotactically in the brain. This technique bypasses the blood brain barrier and gives precise distributions of drugs, minimizing off-target effects of compounds such as viral vectors for gene therapy or toxic chemotherapy agents. The exact distribution is affected by the cannula positioning, flow rate and underlying tissue structure. This study presents an analysis of a simulation algorithm for predicting the distribution using baseline MRI images acquired prior to inserting the cannula. The MRI images included diffusion tensor imaging (DTI) to estimate the tissue properties. The algorithm was adapted for the devices and protocols identified for upcoming trials and validated with direct MRI visualization of Gadolinium in 20 infusions in non-human primates. We found strong agreement between the size and location of the simulated and gadolinium volumes, demonstrating the clinical utility of this surgical planning algorithm. PMID:21945468
Performance of the general circulation models in simulating temperature and precipitation over Iran

NASA Astrophysics Data System (ADS)

Abbasian, Mohammadsadegh; Moghim, Sanaz; Abrishamchi, Ahmad

2018-03-01

General Circulation Models (GCMs) are advanced tools for impact assessment and climate change studies. Previous studies show that the performance of the GCMs in simulating climate variables varies significantly over different regions. This study intends to evaluate the performance of the Coupled Model Intercomparison Project phase 5 (CMIP5) GCMs in simulating temperature and precipitation over Iran. Simulations from 37 GCMs and observations from the Climatic Research Unit (CRU) were obtained for the period of 1901-2005. Six measures of performance including mean bias, root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), linear correlation coefficient (r), Kolmogorov-Smirnov statistic (KS), Sen's slope estimator, and the Taylor diagram are used for the evaluation. GCMs are ranked based on each statistic at seasonal and annual time scales. Results show that most GCMs perform reasonably well in simulating the annual and seasonal temperature over Iran. The majority of the GCMs have a poor skill to simulate precipitation, particularly at seasonal scale. Based on the results, the best GCMs to represent temperature and precipitation simulations over Iran are the CMCC-CMS (Euro-Mediterranean Center on Climate Change) and the MRI-CGCM3 (Meteorological Research Institute), respectively. The results are valuable for climate and hydrometeorological studies and can help water resources planners and managers to choose the proper GCM based on their criteria.
A hierarchical model for probabilistic independent component analysis of multi-subject fMRI studies

PubMed Central

Tang, Li

2014-01-01

Summary An important goal in fMRI studies is to decompose the observed series of brain images to identify and characterize underlying brain functional networks. Independent component analysis (ICA) has been shown to be a powerful computational tool for this purpose. Classic ICA has been successfully applied to single-subject fMRI data. The extension of ICA to group inferences in neuroimaging studies, however, is challenging due to the unavailability of a pre-specified group design matrix. Existing group ICA methods generally concatenate observed fMRI data across subjects on the temporal domain and then decompose multi-subject data in a similar manner to single-subject ICA. The major limitation of existing methods is that they ignore between-subject variability in spatial distributions of brain functional networks in group ICA. In this paper, we propose a new hierarchical probabilistic group ICA method to formally model subject-specific effects in both temporal and spatial domains when decomposing multi-subject fMRI data. The proposed method provides model-based estimation of brain functional networks at both the population and subject level. An important advantage of the hierarchical model is that it provides a formal statistical framework to investigate similarities and differences in brain functional networks across subjects, e.g., subjects with mental disorders or neurodegenerative diseases such as Parkinson’s as compared to normal subjects. We develop an EM algorithm for model estimation where both the E-step and M-step have explicit forms. We compare the performance of the proposed hierarchical model with that of two popular group ICA methods via simulation studies. We illustrate our method with application to an fMRI study of Zen meditation. PMID:24033125
Risk of breast cancer after a diagnosis of ovarian cancer in BRCA mutation carriers: Is preventive mastectomy warranted?

PubMed

McGee, Jacob; Giannakeas, Vasily; Karlan, Beth; Lubinski, Jan; Gronwald, Jacek; Rosen, Barry; McLaughlin, John; Risch, Harvey; Sun, Ping; Foulkes, William D; Neuhausen, Susan L; Kotsopoulos, Joanne; Narod, Steven A

2017-05-01

Preventive breast surgery and MRI screening are offered to unaffected BRCA mutation carriers. The clinical benefit of these two modalities has not been evaluated among mutation carriers with a history of ovarian cancer. Thus, we sought to determine whether or not BRCA mutation carriers with ovarian cancer would benefit from preventive mastectomy or from MRI screening. First, the annual mortality rate for ovarian cancer patients was estimated for a cohort of 178 BRCA mutation carriers from Ontario, Canada. Next, the actuarial risk of developing breast cancer was estimated using an international registry of 509 BRCA mutation carriers with ovarian cancer. A series of simulations was conducted to evaluate the reduction in the probability of death (from all causes) associated with mastectomy and with MRI-based breast surveillance. Cox proportional hazards models were used to evaluate the impacts of mastectomy and MRI screening on breast cancer incidence as well as on all-cause mortality. Twenty (3.9%) of the 509 patients developed breast cancer within ten years following ovarian cancer diagnosis. The actuarial risk of developing breast cancer at ten years post-diagnosis, conditional on survival from ovarian cancer and other causes of mortality was 7.8%. Based on our simulation results, among all BRCA mutation-carrying patients diagnosed with stage III/IV ovarian cancer at age 50, the chance of dying before age 80 was reduced by less than 1% with MRI and by less than 2% with mastectomy. Greater improvements in survival with MRI or mastectomy were observed for women who had already survived 10years after ovarian cancer, and for women with stage I or II ovarian cancer. Among BRCA mutation-carrying ovarian cancer patients without a personal history of breast cancer, neither preventive mastectomy nor MRI screening is warranted, except for those who have survived ovarian cancer without recurrence for ten years and for those with early stage ovarian cancer. Copyright © 2017 Elsevier Inc. All rights reserved.
Large-scale dynamo action precedes turbulence in shearing box simulations of the magnetorotational instability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhat, Pallavi; Ebrahimi, Fatima; Blackman, Eric G.

Here, we study the dynamo generation (exponential growth) of large-scale (planar averaged) fields in unstratified shearing box simulations of the magnetorotational instability (MRI). In contrast to previous studies restricted to horizontal (x–y) averaging, we also demonstrate the presence of large-scale fields when vertical (y–z) averaging is employed instead. By computing space–time planar averaged fields and power spectra, we find large-scale dynamo action in the early MRI growth phase – a previously unidentified feature. Non-axisymmetric linear MRI modes with low horizontal wavenumbers and vertical wavenumbers near that of expected maximal growth, amplify the large-scale fields exponentially before turbulence and high wavenumbermore » fluctuations arise. Thus the large-scale dynamo requires only linear fluctuations but not non-linear turbulence (as defined by mode–mode coupling). Vertical averaging also allows for monitoring the evolution of the large-scale vertical field and we find that a feedback from horizontal low wavenumber MRI modes provides a clue as to why the large-scale vertical field sustains against turbulent diffusion in the non-linear saturation regime. We compute the terms in the mean field equations to identify the individual contributions to large-scale field growth for both types of averaging. The large-scale fields obtained from vertical averaging are found to compare well with global simulations and quasi-linear analytical analysis from a previous study by Ebrahimi & Blackman. We discuss the potential implications of these new results for understanding the large-scale MRI dynamo saturation and turbulence.« less
Large-scale dynamo action precedes turbulence in shearing box simulations of the magnetorotational instability

DOE PAGES

Bhat, Pallavi; Ebrahimi, Fatima; Blackman, Eric G.

2016-07-06

Here, we study the dynamo generation (exponential growth) of large-scale (planar averaged) fields in unstratified shearing box simulations of the magnetorotational instability (MRI). In contrast to previous studies restricted to horizontal (x–y) averaging, we also demonstrate the presence of large-scale fields when vertical (y–z) averaging is employed instead. By computing space–time planar averaged fields and power spectra, we find large-scale dynamo action in the early MRI growth phase – a previously unidentified feature. Non-axisymmetric linear MRI modes with low horizontal wavenumbers and vertical wavenumbers near that of expected maximal growth, amplify the large-scale fields exponentially before turbulence and high wavenumbermore » fluctuations arise. Thus the large-scale dynamo requires only linear fluctuations but not non-linear turbulence (as defined by mode–mode coupling). Vertical averaging also allows for monitoring the evolution of the large-scale vertical field and we find that a feedback from horizontal low wavenumber MRI modes provides a clue as to why the large-scale vertical field sustains against turbulent diffusion in the non-linear saturation regime. We compute the terms in the mean field equations to identify the individual contributions to large-scale field growth for both types of averaging. The large-scale fields obtained from vertical averaging are found to compare well with global simulations and quasi-linear analytical analysis from a previous study by Ebrahimi & Blackman. We discuss the potential implications of these new results for understanding the large-scale MRI dynamo saturation and turbulence.« less
Carotid DSA based CFD simulation in assessing the patient with asymptomatic carotid stenosis: a preliminary study.

PubMed

Zhang, Dong; Xu, Pengcheng; Qiao, Hongyu; Liu, Xin; Luo, Liangping; Huang, Wenhua; Zhang, Heye; Shi, Changzheng

2018-03-12

Cerebrovascular events are frequently associated with hemodynamic disturbance caused by internal carotid artery (ICA) stenosis. It is challenging to determine the ischemia-related carotid stenosis during the intervention only using digital subtracted angiography (DSA). Inspired by the performance of well-established FFRct technique in hemodynamic assessment of significant coronary stenosis, we introduced a pressure-based carotid arterial functional assessment (CAFA) index generated from computational fluid dynamic (CFD) simulation in DSA data, and investigated its feasibility in the assessment of hemodynamic disturbance preliminarily using pressure-wired measurement and arterial spin labeling (ASL) MRI as references. The cerebral multi-delay multi-parametric ASL-MRI and carotid DSA including trans-stenotic pressure-wired measurement were implemented on a 65-year-old man with asymptomatic unilateral (left) ICA stenosis. A CFD simulation using simplified boundary condition was performed in DSA data to calculate the CAFA index. The cerebral blood flow (CBF) and arterial transit time (ATT) of ICA territories were acquired. CFD simulation showed good correlation (r = 0.839, P = 0.001) with slight systematic overestimation (mean difference - 0.007, standard deviation 0.017) compared with pressure-wired measurement. No significant difference was observed between them (P = 0.09). Though the narrowing degree of in the involved ICA was about 70%, the simulated and measured CAFA (0.942/0.937) revealed a functionally nonsignificant stenosis which was also verified by a compensatory final CBF (fronto-temporal/fronto-parietal region: 51.58/45.62 ml/100 g/min) and slightly prolonged ATT (1.23/1.4 s) in the involved territories, together with a normal left-right percentage difference (2.1-8.85%). The DSA based CFD simulation showed good consistence with invasive approach and could be used as a cost-saving and efficient way to study the relationship between hemodynamic disorder caused by ICA stenosis and subsequent perfusion variations in brain. Further research should focus on the role of noninvasive pressure-based CAFA in screening asymptomatic ischemia-causing carotid stenosis.
Automatic segmentation of invasive breast carcinomas from dynamic contrast-enhanced MRI using time series analysis.

PubMed

Jayender, Jagadaeesan; Chikarmane, Sona; Jolesz, Ferenc A; Gombos, Eva

2014-08-01

To accurately segment invasive ductal carcinomas (IDCs) from dynamic contrast-enhanced MRI (DCE-MRI) using time series analysis based on linear dynamic system (LDS) modeling. Quantitative segmentation methods based on black-box modeling and pharmacokinetic modeling are highly dependent on imaging pulse sequence, timing of bolus injection, arterial input function, imaging noise, and fitting algorithms. We modeled the underlying dynamics of the tumor by an LDS and used the system parameters to segment the carcinoma on the DCE-MRI. Twenty-four patients with biopsy-proven IDCs were analyzed. The lesions segmented by the algorithm were compared with an expert radiologist's segmentation and the output of a commercial software, CADstream. The results are quantified in terms of the accuracy and sensitivity of detecting the lesion and the amount of overlap, measured in terms of the Dice similarity coefficient (DSC). The segmentation algorithm detected the tumor with 90% accuracy and 100% sensitivity when compared with the radiologist's segmentation and 82.1% accuracy and 100% sensitivity when compared with the CADstream output. The overlap of the algorithm output with the radiologist's segmentation and CADstream output, computed in terms of the DSC was 0.77 and 0.72, respectively. The algorithm also shows robust stability to imaging noise. Simulated imaging noise with zero mean and standard deviation equal to 25% of the base signal intensity was added to the DCE-MRI series. The amount of overlap between the tumor maps generated by the LDS-based algorithm from the noisy and original DCE-MRI was DSC = 0.95. The time-series analysis based segmentation algorithm provides high accuracy and sensitivity in delineating the regions of enhanced perfusion corresponding to tumor from DCE-MRI. © 2013 Wiley Periodicals, Inc.
Automatic Segmentation of Invasive Breast Carcinomas from DCE-MRI using Time Series Analysis

PubMed Central

Jayender, Jagadaeesan; Chikarmane, Sona; Jolesz, Ferenc A.; Gombos, Eva

2013-01-01

Purpose Quantitative segmentation methods based on black-box modeling and pharmacokinetic modeling are highly dependent on imaging pulse sequence, timing of bolus injection, arterial input function, imaging noise and fitting algorithms. To accurately segment invasive ductal carcinomas (IDCs) from dynamic contrast enhanced MRI (DCE-MRI) using time series analysis based on linear dynamic system (LDS) modeling. Methods We modeled the underlying dynamics of the tumor by a LDS and use the system parameters to segment the carcinoma on the DCE-MRI. Twenty-four patients with biopsy-proven IDCs were analyzed. The lesions segmented by the algorithm were compared with an expert radiologist’s segmentation and the output of a commercial software, CADstream. The results are quantified in terms of the accuracy and sensitivity of detecting the lesion and the amount of overlap, measured in terms of the Dice similarity coefficient (DSC). Results The segmentation algorithm detected the tumor with 90% accuracy and 100% sensitivity when compared to the radiologist’s segmentation and 82.1% accuracy and 100% sensitivity when compared to the CADstream output. The overlap of the algorithm output with the radiologist’s segmentation and CADstream output, computed in terms of the DSC was 0.77 and 0.72 respectively. The algorithm also shows robust stability to imaging noise. Simulated imaging noise with zero mean and standard deviation equal to 25% of the base signal intensity was added to the DCE-MRI series. The amount of overlap between the tumor maps generated by the LDS-based algorithm from the noisy and original DCE-MRI was DSC=0.95. Conclusion The time-series analysis based segmentation algorithm provides high accuracy and sensitivity in delineating the regions of enhanced perfusion corresponding to tumor from DCE-MRI. PMID:24115175
Linearization improves the repeatability of quantitative dynamic contrast-enhanced MRI.

PubMed

Jones, Kyle M; Pagel, Mark D; Cárdenas-Rodríguez, Julio

2018-04-01

The purpose of this study was to compare the repeatabilities of the linear and nonlinear Tofts and reference region models (RRM) for dynamic contrast-enhanced MRI (DCE-MRI). Simulated and experimental DCE-MRI data from 12 rats with a flank tumor of C6 glioma acquired over three consecutive days were analyzed using four quantitative and semi-quantitative DCE-MRI metrics. The quantitative methods used were: 1) linear Tofts model (LTM), 2) non-linear Tofts model (NTM), 3) linear RRM (LRRM), and 4) non-linear RRM (NRRM). The following semi-quantitative metrics were used: 1) maximum enhancement ratio (MER), 2) time to peak (TTP), 3) initial area under the curve (iauc64), and 4) slope. LTM and NTM were used to estimate K trans , while LRRM and NRRM were used to estimate K trans relative to muscle (R Ktrans ). Repeatability was assessed by calculating the within-subject coefficient of variation (wSCV) and the percent intra-subject variation (iSV) determined with the Gage R&R analysis. The iSV for R Ktrans using LRRM was two-fold lower compared to NRRM at all simulated and experimental conditions. A similar trend was observed for the Tofts model, where LTM was at least 50% more repeatable than the NTM under all experimental and simulated conditions. The semi-quantitative metrics iauc64 and MER were as equally repeatable as K trans and R Ktrans estimated by LTM and LRRM respectively. The iSV for iauc64 and MER were significantly lower than the iSV for slope and TTP. In simulations and experimental results, linearization improves the repeatability of quantitative DCE-MRI by at least 30%, making it as repeatable as semi-quantitative metrics. Copyright © 2017 Elsevier Inc. All rights reserved.
Extracting intrinsic functional networks with feature-based group independent component analysis.

PubMed

Calhoun, Vince D; Allen, Elena

2013-04-01

There is increasing use of functional imaging data to understand the macro-connectome of the human brain. Of particular interest is the structure and function of intrinsic networks (regions exhibiting temporally coherent activity both at rest and while a task is being performed), which account for a significant portion of the variance in functional MRI data. While networks are typically estimated based on the temporal similarity between regions (based on temporal correlation, clustering methods, or independent component analysis [ICA]), some recent work has suggested that these intrinsic networks can be extracted from the inter-subject covariation among highly distilled features, such as amplitude maps reflecting regions modulated by a task or even coordinates extracted from large meta analytic studies. In this paper our goal was to explicitly compare the networks obtained from a first-level ICA (ICA on the spatio-temporal functional magnetic resonance imaging (fMRI) data) to those from a second-level ICA (i.e., ICA on computed features rather than on the first-level fMRI data). Convergent results from simulations, task-fMRI data, and rest-fMRI data show that the second-level analysis is slightly noisier than the first-level analysis but yields strikingly similar patterns of intrinsic networks (spatial correlations as high as 0.85 for task data and 0.65 for rest data, well above the empirical null) and also preserves the relationship of these networks with other variables such as age (for example, default mode network regions tended to show decreased low frequency power for first-level analyses and decreased loading parameters for second-level analyses). In addition, the best-estimated second-level results are those which are the most strongly reflected in the input feature. In summary, the use of feature-based ICA appears to be a valid tool for extracting intrinsic networks. We believe it will become a useful and important approach in the study of the macro-connectome, particularly in the context of data fusion.
Constructing fMRI connectivity networks: a whole brain functional parcellation method for node definition.

PubMed

Maggioni, Eleonora; Tana, Maria Gabriella; Arrigoni, Filippo; Zucca, Claudio; Bianchi, Anna Maria

2014-05-15

Functional Magnetic Resonance Imaging (fMRI) is used for exploring brain functionality, and recently it was applied for mapping the brain connection patterns. To give a meaningful neurobiological interpretation to the connectivity network, it is fundamental to properly define the network framework. In particular, the choice of the network nodes may affect the final connectivity results and the consequent interpretation. We introduce a novel method for the intra subject topological characterization of the nodes of fMRI brain networks, based on a whole brain parcellation scheme. The proposed whole brain parcellation algorithm divides the brain into clusters that are homogeneous from the anatomical and functional point of view, each of which constitutes a node. The functional parcellation described is based on the Tononi's cluster index, which measures instantaneous correlation in terms of intrinsic and extrinsic statistical dependencies. The method performance and reliability were first tested on simulated data, then on a real fMRI dataset acquired on healthy subjects during visual stimulation. Finally, the proposed algorithm was applied to epileptic patients' fMRI data recorded during seizures, to verify its usefulness as preparatory step for effective connectivity analysis. For each patient, the nodes of the network involved in ictal activity were defined according to the proposed parcellation scheme and Granger Causality Analysis (GCA) was applied to infer effective connectivity. We showed that the algorithm 1) performed well on simulated data, 2) was able to produce reliable inter subjects results and 3) led to a detailed definition of the effective connectivity pattern. Copyright © 2014 Elsevier B.V. All rights reserved.
Augmenting intraoperative MRI with preoperative fMRI and DTI by biomechanical simulation of brain deformation

NASA Astrophysics Data System (ADS)

Warfield, Simon K.; Talos, Florin; Kemper, Corey; Cosman, Eric; Tei, Alida; Ferrant, Matthieu; Macq, Benoit M. M.; Wells, William M., III; Black, Peter M.; Jolesz, Ferenc A.; Kikinis, Ron

2003-05-01

The key challenge facing the neurosurgeon during neurosurgery is to be able to remove from the brain as much tumor tissue as possible while preserving healthy tissue and minimizing the disruption of critical anatomical structures. The purpose of this work was to demonstrate the use of biomechanical simulation of brain deformation to project preoperative fMRI and DTI data into the coordinate system of the patient brain deformed during neurosurgery. This projection enhances the visualization of relevant critical structures available to the neurosurgeon. Our approach to tracking brain changes during neurosurgery has been previously described. We applied this procedure to warp preoperative fMRI and DTI to match intraoperative MRI. We constructed visualizations of preoperative fMRI and DTI, and intraoperative MRI showing a close correspondence between the matched data. We have previously demonstrated our biomechanical simulation of brain deformation can be executed entirely during neurosurgery. We previously used a generic atlas as a substitute for patient specific data. Here we report the successful alignment of patient-specific DTI and fMRI preoperative data into the intraoperative configuration of the patient's brain. This can significantly enhance the information available to the neurosurgeon.
Numerical Prediction of the Onset of the Magnetorotational Instability in the Princeton MRI Apparatus

NASA Astrophysics Data System (ADS)

Gilson, Erik; Caspary, Kyle; Ebrahimi, Fatima; Goodman, Jeremy; Ji, Hantao; Nuñez, Tahiri; Wei, Xing

2016-10-01

The liquid metal magnetorotational instability experiment at PPPL is designed to search for the MRI in a controlled laboratory setup. MRI is thought to be the primary mechanism behind turbulence in accretion disks, leading to an enhanced effective viscosity that can explain observed fast accretion rates. The apparatus has several key differences from an accretion disk. The top and bottom surfaces of the vessel exert stresses on the surfaces of the working fluid. There are no surface stresses on an accretion disk, but rather a free-surface. To interpret experimental results, the Spectral Finite Element Maxwell and Navier Stokes (SFEMaNS) code (Guermond et al., 2009) has been used to simulate experiments in the MRI apparatus and study MRI onset in the presence of residual flows induced by the boundaries. These Ekman flows lead to the generation of radial magnetic fields that can obfuscate the MRI signal. Simulation results are presented that show the full spatial distribution of the velocity field and the magnetic field over a range of experimental operating parameters, including both above and below the expected MRI threshold. Both the residual flow and the radial magnetic field at the location of the diagnostics are computed for comparisons with experimental results. This research is supported by DOE, NSF, and NASA.
Passive Ventricular Mechanics Modelling Using MRI of Structure and Function

PubMed Central

Wang, V.Y.; Lam, H.I.; Ennis, D.B.; Young, A.A.; Nash, M.P.

2009-01-01

Patients suffering from dilated cardiomyopathy or myocardial infarction can develop left ventricular (LV) diastolic impairment. The LV remodels its structure and function to adapt to pathophysiological changes in geometry and loading conditions and this remodeling process can alter the passive ventricular mechanics. In order to better understand passive ventricular mechanics, a LV finite element model was developed to incorporate physiological and mechanical information derived from in vivo magnetic resonance imaging (MRI) tissue tagging, in vivo LV cavity pressure recording and ex vivo diffusion tensor MRI (DTMRI) of a canine heart. MRI tissue tagging enables quantitative evaluation of cardiac mechanical function with high spatial and temporal resolution, whilst the direction of maximum water diffusion (the primary eigenvector) in each voxel of a DTMRI directly correlates with the myocardial fibre orientation. This model was customized to the geometry of the canine LV during diastasis by fitting the segmented epicardial and endocardial surface data from tagged MRI using nonlinear finite element fitting techniques. Myofibre orientations, extracted from DTMRI of the same heart, were incorporated into this geometric model using a free form deformation methodology. Pressure recordings, temporally synchronized to the tissue tagging MRI data, were used to simulate the LV deformation during diastole. Simulation of the diastolic LV mechanics allowed us to estimate the stiffness of the passive LV myocardium based on kinematic data obtained from tagged MRI. This integrated physiological model will allow more insight into the regional passive diastolic mechanics of the LV on an individualized basis, thereby improving our understanding of the underlying structural basis of mechanical dysfunction in pathological conditions. PMID:18982680
Passive ventricular mechanics modelling using MRI of structure and function.

PubMed

Wang, V Y; Lam, H I; Ennis, D B; Young, A A; Nash, M P

2008-01-01

Patients suffering from dilated cardiomyopathy or myocardial infarction can develop left ventricular (LV) diastolic impairment. The LV remodels its structure and function to adapt to pathophysiological changes in geometry and loading conditions and this remodeling process can alter the passive ventricular mechanics. In order to better understand passive ventricular mechanics, a LV finite element model was developed to incorporate physiological and mechanical information derived from in vivo magnetic resonance imaging (MRI) tissue tagging, in vivo LV cavity pressure recording and ex vivo diffusion tensor MRI (DTMRI) of a canine heart. MRI tissue tagging enables quantitative evaluation of cardiac mechanical function with high spatial and temporal resolution, whilst the direction of maximum water diffusion (the primary eigenvector) in each voxel of a DTMRI directly correlates with the myocardial fibre orientation. This model was customized to the geometry of the canine LV during diastasis by fitting the segmented epicardial and endocardial surface data from tagged MRI using nonlinear finite element fitting techniques. Myofibre orientations, extracted from DTMRI of the same heart, were incorporated into this geometric model using a free form deformation methodology. Pressure recordings, temporally synchronized to the tissue tagging MRI data, were used to simulate the LV deformation during diastole. Simulation of the diastolic LV mechanics allowed us to estimate the stiffness of the passive LV myocardium based on kinematic data obtained from tagged MRI. This integrated physiological model will allow more insight into the regional passive diastolic mechanics of the LV on an individualized basis, thereby improving our understanding of the underlying structural basis of mechanical dysfunction in pathological conditions.
Neural correlates of olfactory and visual memory performance in 3D-simulated mazes after intranasal insulin application.

PubMed

Brünner, Yvonne F; Rodriguez-Raecke, Rea; Mutic, Smiljana; Benedict, Christian; Freiherr, Jessica

2016-10-01

This fMRI study intended to establish 3D-simulated mazes with olfactory and visual cues and examine the effect of intranasally applied insulin on memory performance in healthy subjects. The effect of insulin on hippocampus-dependent brain activation was explored using a double-blind and placebo-controlled design. Following intranasal administration of either insulin (40IU) or placebo, 16 male subjects participated in two experimental MRI sessions with olfactory and visual mazes. Each maze included two separate runs. The first was an encoding maze during which subjects learned eight olfactory or eight visual cues at different target locations. The second was a recall maze during which subjects were asked to remember the target cues at spatial locations. For eleven included subjects in the fMRI analysis we were able to validate brain activation for odor perception and visuospatial tasks. However, we did not observe an enhancement of declarative memory performance in our behavioral data or hippocampal activity in response to insulin application in the fMRI analysis. It is therefore possible that intranasal insulin application is sensitive to the methodological variations e.g. timing of task execution and dose of application. Findings from this study suggest that our method of 3D-simulated mazes is feasible for studying neural correlates of olfactory and visual memory performance. Copyright © 2016 Elsevier Inc. All rights reserved.

Monte Carlo study of the impact of a magnetic field on the dose distribution in MRI-guided HDR brachytherapy using Ir-192

NASA Astrophysics Data System (ADS)

Beld, E.; Seevinck, P. R.; Lagendijk, J. J. W.; Viergever, M. A.; Moerland, M. A.

2016-09-01

In the process of developing a robotic MRI-guided high-dose-rate (HDR) prostate brachytherapy treatment, the influence of the MRI scanner’s magnetic field on the dose distribution needs to be investigated. A magnetic field causes a deflection of electrons in the plane perpendicular to the magnetic field, and it leads to less lateral scattering along the direction parallel with the magnetic field. Monte Carlo simulations were carried out to determine the influence of the magnetic field on the electron behavior and on the total dose distribution around an Ir-192 source. Furthermore, the influence of air pockets being present near the source was studied. The Monte Carlo package Geant4 was utilized for the simulations. The simulated geometries consisted of a simplified point source inside a water phantom. Magnetic field strengths of 0 T, 1.5 T, 3 T, and 7 T were considered. The simulation results demonstrated that the dose distribution was nearly unaffected by the magnetic field for all investigated magnetic field strengths. Evidence was found that, from a dose perspective, the HDR prostate brachytherapy treatment using Ir-192 can be performed safely inside the MRI scanner. No need was found to account for the magnetic field during treatment planning. Nevertheless, the presence of air pockets in close vicinity to the source, particularly along the direction parallel with the magnetic field, appeared to be an important point for consideration.
Monte Carlo study of the impact of a magnetic field on the dose distribution in MRI-guided HDR brachytherapy using Ir-192.

PubMed

Beld, E; Seevinck, P R; Lagendijk, J J W; Viergever, M A; Moerland, M A

2016-09-21

In the process of developing a robotic MRI-guided high-dose-rate (HDR) prostate brachytherapy treatment, the influence of the MRI scanner's magnetic field on the dose distribution needs to be investigated. A magnetic field causes a deflection of electrons in the plane perpendicular to the magnetic field, and it leads to less lateral scattering along the direction parallel with the magnetic field. Monte Carlo simulations were carried out to determine the influence of the magnetic field on the electron behavior and on the total dose distribution around an Ir-192 source. Furthermore, the influence of air pockets being present near the source was studied. The Monte Carlo package Geant4 was utilized for the simulations. The simulated geometries consisted of a simplified point source inside a water phantom. Magnetic field strengths of 0 T, 1.5 T, 3 T, and 7 T were considered. The simulation results demonstrated that the dose distribution was nearly unaffected by the magnetic field for all investigated magnetic field strengths. Evidence was found that, from a dose perspective, the HDR prostate brachytherapy treatment using Ir-192 can be performed safely inside the MRI scanner. No need was found to account for the magnetic field during treatment planning. Nevertheless, the presence of air pockets in close vicinity to the source, particularly along the direction parallel with the magnetic field, appeared to be an important point for consideration.
Diffusion tensor tracking of neuronal fiber pathways in the living human brain

NASA Astrophysics Data System (ADS)

Lori, Nicolas Francisco

2001-11-01

The technique of diffusion tensor tracking (DTT) is described, in which diffusion tensor magnetic resonance imaging (DT-MRI) data are processed to allow the visualization of white matter (WM) tracts in a living human brain. To illustrate the methods, a detailed description is given of the physics of DT-MRI, the structure of the DT-MRI experiment, the computer tools that were developed to visualize WM tracts, the anatomical consistency of the obtained WM tracts, and the accuracy and precision of DTT using computer simulations. When presenting the physics of DT-MRI, a completely quantum-mechanical view of DT-MRI is given where some of the results are new. Examples of anatomical tracts viewed using DTT are presented, including the genu and the splenium of the corpus callosum, the ventral pathway with its amygdala connection highlighted, the geniculo- calcarine tract separated into anterior and posterior parts, the geniculo-calcarine tract defined using functional magnetic resonance imaging (MRI), and U- fibers. In the simulation, synthetic DT-MRI data were constructed that would be obtained for a cylindrical WM tract with a helical trajectory surrounded by gray matter. Noise was then added to the synthetic DT-MRI data, and DTT trajectories were calculated using the noisy data (realistic tracks). Simulated DTT errors were calculated as the vector distance between the realistic tracks and the ideal trajectory. The simulation tested the effects of a comprehensive set of experimental conditions, including voxel size, data sampling, data averaging, type of tract tissue, tract diameter and type of tract trajectory. Simulated DTT accuracy and precision were typically below the voxel dimension, and precision was compatible with the experimental results.
Radiological characteristics of MRI-based VIP polymer gel under carbon beam irradiation

NASA Astrophysics Data System (ADS)

Maeyama, T.; Fukunishi, N.; Ishikawa, K. L.; Furuta, T.; Fukasaku, K.; Takagi, S.; Noda, S.; Himeno, R.; Fukuda, S.

2015-02-01

We study the radiological characteristics of VIP polymer gel dosimeters under carbon beam irradiation with energy of 135 and 290 AMeV. To evaluate dose response of VIP polymer gels, the transverse (or spin-spin) relaxation rate R2 of the dosimeters measured by magnetic resonance imaging (MRI) as a function of linear energy transfer (LET), rather than penetration depth, as is usually done in previous reports. LET is evaluated by use of the particle transport simulation code PHITS. Our results reveal that the dose response decreases with increasing dose-averaged LET and that the dose response-LET relation also varies with incident carbon beam energy. The latter can be explained by taking into account the contribution from fragmentation products.
Characterization of dynamic changes of current source localization based on spatiotemporal fMRI constrained EEG source imaging

NASA Astrophysics Data System (ADS)

Nguyen, Thinh; Potter, Thomas; Grossman, Robert; Zhang, Yingchun

2018-06-01

Objective. Neuroimaging has been employed as a promising approach to advance our understanding of brain networks in both basic and clinical neuroscience. Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) represent two neuroimaging modalities with complementary features; EEG has high temporal resolution and low spatial resolution while fMRI has high spatial resolution and low temporal resolution. Multimodal EEG inverse methods have attempted to capitalize on these properties but have been subjected to localization error. The dynamic brain transition network (DBTN) approach, a spatiotemporal fMRI constrained EEG source imaging method, has recently been developed to address these issues by solving the EEG inverse problem in a Bayesian framework, utilizing fMRI priors in a spatial and temporal variant manner. This paper presents a computer simulation study to provide a detailed characterization of the spatial and temporal accuracy of the DBTN method. Approach. Synthetic EEG data were generated in a series of computer simulations, designed to represent realistic and complex brain activity at superficial and deep sources with highly dynamical activity time-courses. The source reconstruction performance of the DBTN method was tested against the fMRI-constrained minimum norm estimates algorithm (fMRIMNE). The performances of the two inverse methods were evaluated both in terms of spatial and temporal accuracy. Main results. In comparison with the commonly used fMRIMNE method, results showed that the DBTN method produces results with increased spatial and temporal accuracy. The DBTN method also demonstrated the capability to reduce crosstalk in the reconstructed cortical time-course(s) induced by neighboring regions, mitigate depth bias and improve overall localization accuracy. Significance. The improved spatiotemporal accuracy of the reconstruction allows for an improved characterization of complex neural activity. This improvement can be extended to any subsequent brain connectivity analyses used to construct the associated dynamic brain networks.
The inclusion of functional connectivity information into fMRI-based neurofeedback improves its efficacy in the reduction of cigarette cravings.

PubMed

Kim, Dong-Youl; Yoo, Seung-Schik; Tegethoff, Marion; Meinlschmidt, Gunther; Lee, Jong-Hwan

2015-08-01

Real-time fMRI (rtfMRI) neurofeedback (NF) facilitates volitional control over brain activity and the modulation of associated mental functions. The NF signals of traditional rtfMRI-NF studies predominantly reflect neuronal activity within ROIs. In this study, we describe a novel rtfMRI-NF approach that includes a functional connectivity (FC) component in the NF signal (FC-added rtfMRI-NF). We estimated the efficacy of the FC-added rtfMRI-NF method by applying it to nicotine-dependent heavy smokers in an effort to reduce cigarette craving. ACC and medial pFC as well as the posterior cingulate cortex and precuneus are associated with cigarette craving and were chosen as ROIs. Fourteen heavy smokers were randomly assigned to receive one of two types of NF: traditional activity-based rtfMRI-NF or FC-added rtfMRI-NF. Participants received rtfMRI-NF training during two separate visits after overnight smoking cessation, and cigarette craving score was assessed. The FC-added rtfMRI-NF resulted in greater neuronal activity and increased FC between the targeted ROIs than the traditional activity-based rtfMRI-NF and resulted in lower craving score. In the FC-added rtfMRI-NF condition, the average of neuronal activity and FC was tightly associated with craving score (Bonferroni-corrected p = .028). However, in the activity-based rtfMRI-NF condition, no association was detected (uncorrected p > .081). Non-rtfMRI data analysis also showed enhanced neuronal activity and FC with FC-added NF than with activity-based NF. These results demonstrate that FC-added rtfMRI-NF facilitates greater volitional control over brain activity and connectivity and greater modulation of mental function than activity-based rtfMRI-NF.
Quantification of intensity variations in functional MR images using rotated principal components

NASA Astrophysics Data System (ADS)

Backfrieder, W.; Baumgartner, R.; Sámal, M.; Moser, E.; Bergmann, H.

1996-08-01

In functional MRI (fMRI), the changes in cerebral haemodynamics related to stimulated neural brain activity are measured using standard clinical MR equipment. Small intensity variations in fMRI data have to be detected and distinguished from non-neural effects by careful image analysis. Based on multivariate statistics we describe an algorithm involving oblique rotation of the most significant principal components for an estimation of the temporal and spatial distribution of the stimulated neural activity over the whole image matrix. This algorithm takes advantage of strong local signal variations. A mathematical phantom was designed to generate simulated data for the evaluation of the method. In simulation experiments, the potential of the method to quantify small intensity changes, especially when processing data sets containing multiple sources of signal variations, was demonstrated. In vivo fMRI data collected in both visual and motor stimulation experiments were analysed, showing a proper location of the activated cortical regions within well known neural centres and an accurate extraction of the activation time profile. The suggested method yields accurate absolute quantification of in vivo brain activity without the need of extensive prior knowledge and user interaction.
Measurement of pulsatile motion with millisecond resolution by MRI.

PubMed

Souchon, Rémi; Gennisson, Jean-Luc; Tanter, Mickael; Salomir, Rares; Chapelon, Jean-Yves; Rouvière, Olivier

2012-06-01

We investigated a technique based on phase-contrast cine MRI combined with deconvolution of the phase shift waveforms to measure rapidly varying pulsatile motion waveforms. The technique does not require steady-state displacement during motion encoding. Simulations and experiments were performed in porcine liver samples in view of a specific application, namely the observation of transient displacements induced by acoustic radiation force. Simulations illustrate the advantages and shortcomings of the methods. For experimental validation, the waveforms were acquired with an ultrafast ultrasound scanner (Supersonic Imagine Aixplorer), and the rates of decay of the waveforms (relaxation time) were compared. With bipolar motion-encoding gradient of 8.4 ms, the method was able to measure displacement waveforms with a temporal resolution of 1 ms over a time course of 40 ms. Reasonable agreement was found between the rate of decay of the waveforms measured in ultrasound (2.8 ms) and in MRI (2.7-3.3 ms). Copyright © 2011 Wiley-Liss, Inc.
Exploring connectivity with large-scale Granger causality on resting-state functional MRI.

PubMed

DSouza, Adora M; Abidin, Anas Z; Leistritz, Lutz; Wismüller, Axel

2017-08-01

Large-scale Granger causality (lsGC) is a recently developed, resting-state functional MRI (fMRI) connectivity analysis approach that estimates multivariate voxel-resolution connectivity. Unlike most commonly used multivariate approaches, which establish coarse-resolution connectivity by aggregating voxel time-series avoiding an underdetermined problem, lsGC estimates voxel-resolution, fine-grained connectivity by incorporating an embedded dimension reduction. We investigate application of lsGC on realistic fMRI simulations, modeling smoothing of neuronal activity by the hemodynamic response function and repetition time (TR), and empirical resting-state fMRI data. Subsequently, functional subnetworks are extracted from lsGC connectivity measures for both datasets and validated quantitatively. We also provide guidelines to select lsGC free parameters. Results indicate that lsGC reliably recovers underlying network structure with area under receiver operator characteristic curve (AUC) of 0.93 at TR=1.5s for a 10-min session of fMRI simulations. Furthermore, subnetworks of closely interacting modules are recovered from the aforementioned lsGC networks. Results on empirical resting-state fMRI data demonstrate recovery of visual and motor cortex in close agreement with spatial maps obtained from (i) visuo-motor fMRI stimulation task-sequence (Accuracy=0.76) and (ii) independent component analysis (ICA) of resting-state fMRI (Accuracy=0.86). Compared with conventional Granger causality approach (AUC=0.75), lsGC produces better network recovery on fMRI simulations. Furthermore, it cannot recover functional subnetworks from empirical fMRI data, since quantifying voxel-resolution connectivity is not possible as consequence of encountering an underdetermined problem. Functional network recovery from fMRI data suggests that lsGC gives useful insight into connectivity patterns from resting-state fMRI at a multivariate voxel-resolution. Copyright © 2017 Elsevier B.V. All rights reserved.
Large-scale Density Structures in Magneto-rotational Disk Turbulence

NASA Astrophysics Data System (ADS)

Youdin, Andrew; Johansen, A.; Klahr, H.

2009-01-01

Turbulence generated by the magneto-rotational instability (MRI) is a strong candidate to drive accretion flows in disks, including sufficiently ionized regions of protoplanetary disks. The MRI is often studied in local shearing boxes, which model a small section of the disk at high resolution. I will present simulations of large, stratified shearing boxes which extend up to 10 gas scale-heights across. These simulations are a useful bridge to fully global disk simulations. We find that MRI turbulence produces large-scale, axisymmetric density perturbations . These structures are part of a zonal flow --- analogous to the banded flow in Jupiter's atmosphere --- which survives in near geostrophic balance for tens of orbits. The launching mechanism is large-scale magnetic tension generated by an inverse cascade. We demonstrate the robustness of these results by careful study of various box sizes, grid resolutions, and microscopic diffusion parameterizations. These gas structures can trap solid material (in the form of large dust or ice particles) with important implications for planet formation. Resolved disk images at mm-wavelengths (e.g. from ALMA) will verify or constrain the existence of these structures.
Improved FastICA algorithm in fMRI data analysis using the sparsity property of the sources.

PubMed

Ge, Ruiyang; Wang, Yubao; Zhang, Jipeng; Yao, Li; Zhang, Hang; Long, Zhiying

2016-04-01

As a blind source separation technique, independent component analysis (ICA) has many applications in functional magnetic resonance imaging (fMRI). Although either temporal or spatial prior information has been introduced into the constrained ICA and semi-blind ICA methods to improve the performance of ICA in fMRI data analysis, certain types of additional prior information, such as the sparsity, has seldom been added to the ICA algorithms as constraints. In this study, we proposed a SparseFastICA method by adding the source sparsity as a constraint to the FastICA algorithm to improve the performance of the widely used FastICA. The source sparsity is estimated through a smoothed ℓ0 norm method. We performed experimental tests on both simulated data and real fMRI data to investigate the feasibility and robustness of SparseFastICA and made a performance comparison between SparseFastICA, FastICA and Infomax ICA. Results of the simulated and real fMRI data demonstrated the feasibility and robustness of SparseFastICA for the source separation in fMRI data. Both the simulated and real fMRI experimental results showed that SparseFastICA has better robustness to noise and better spatial detection power than FastICA. Although the spatial detection power of SparseFastICA and Infomax did not show significant difference, SparseFastICA had faster computation speed than Infomax. SparseFastICA was comparable to the Infomax algorithm with a faster computation speed. More importantly, SparseFastICA outperformed FastICA in robustness and spatial detection power and can be used to identify more accurate brain networks than FastICA algorithm. Copyright © 2016 Elsevier B.V. All rights reserved.
Computational Simulation of Breast Compression Based on Segmented Breast and Fibroglandular Tissues on Magnetic Resonance Images

PubMed Central

Shih, Tzu-Ching; Chen, Jeon-Hor; Liu, Dongxu; Nie, Ke; Sun, Lizhi; Lin, Muqing; Chang, Daniel; Nalcioglu, Orhan; Su, Min-Ying

2010-01-01

This study presents a finite element based computational model to simulate the three-dimensional deformation of the breast and the fibroglandular tissues under compression. The simulation was based on 3D MR images of the breast, and the craniocaudal and mediolateral oblique compression as used in mammography was applied. The geometry of whole breast and the segmented fibroglandular tissues within the breast were reconstructed using triangular meshes by using the Avizo® 6.0 software package. Due to the large deformation in breast compression, a finite element model was used to simulate the non-linear elastic tissue deformation under compression, using the MSC.Marc® software package. The model was tested in 4 cases. The results showed a higher displacement along the compression direction compared to the other two directions. The compressed breast thickness in these 4 cases at 60% compression ratio was in the range of 5-7 cm, which is the typical range of thickness in mammography. The projection of the fibroglandular tissue mesh at 60% compression ratio was compared to the corresponding mammograms of two women, and they demonstrated spatially matched distributions. However, since the compression was based on MRI, which has much coarser spatial resolution than the in-plane resolution of mammography, this method is unlikely to generate a synthetic mammogram close to the clinical quality. Whether this model may be used to understand the technical factors that may impact the variations in breast density measurements needs further investigation. Since this method can be applied to simulate compression of the breast at different views and different compression levels, another possible application is to provide a tool for comparing breast images acquired using different imaging modalities – such as MRI, mammography, whole breast ultrasound, and molecular imaging – that are performed using different body positions and different compression conditions. PMID:20601773
Computational simulation of breast compression based on segmented breast and fibroglandular tissues on magnetic resonance images.

PubMed

Shih, Tzu-Ching; Chen, Jeon-Hor; Liu, Dongxu; Nie, Ke; Sun, Lizhi; Lin, Muqing; Chang, Daniel; Nalcioglu, Orhan; Su, Min-Ying

2010-07-21

This study presents a finite element-based computational model to simulate the three-dimensional deformation of a breast and fibroglandular tissues under compression. The simulation was based on 3D MR images of the breast, and craniocaudal and mediolateral oblique compression, as used in mammography, was applied. The geometry of the whole breast and the segmented fibroglandular tissues within the breast were reconstructed using triangular meshes by using the Avizo 6.0 software package. Due to the large deformation in breast compression, a finite element model was used to simulate the nonlinear elastic tissue deformation under compression, using the MSC.Marc software package. The model was tested in four cases. The results showed a higher displacement along the compression direction compared to the other two directions. The compressed breast thickness in these four cases at a compression ratio of 60% was in the range of 5-7 cm, which is a typical range of thickness in mammography. The projection of the fibroglandular tissue mesh at a compression ratio of 60% was compared to the corresponding mammograms of two women, and they demonstrated spatially matched distributions. However, since the compression was based on magnetic resonance imaging (MRI), which has much coarser spatial resolution than the in-plane resolution of mammography, this method is unlikely to generate a synthetic mammogram close to the clinical quality. Whether this model may be used to understand the technical factors that may impact the variations in breast density needs further investigation. Since this method can be applied to simulate compression of the breast at different views and different compression levels, another possible application is to provide a tool for comparing breast images acquired using different imaging modalities--such as MRI, mammography, whole breast ultrasound and molecular imaging--that are performed using different body positions and under different compression conditions.
ADAPTIVE REAL-TIME CARDIAC MRI USING PARADISE: VALIDATION BY THE PHYSIOLOGICALLY IMPROVED NCAT PHANTOM

PubMed Central

Sharif, Behzad; Bresler, Yoram

2013-01-01

Patient-Adaptive Reconstruction and Acquisition Dynamic Imaging with Sensitivity Encoding (PARADISE) is a dynamic MR imaging scheme that optimally combines parallel imaging and model-based adaptive acquisition. In this work, we propose the application of PARADISE to real-time cardiac MRI. We introduce a physiologically improved version of a realistic four-dimensional cardiac-torso (NCAT) phantom, which incorporates natural beat-to-beat heart rate and motion variations. Cardiac cine imaging using PARADISE is simulated and its performance is analyzed by virtue of the improved phantom. Results verify the effectiveness of PARADISE for high resolution un-gated real-time cardiac MRI and its superiority over conventional acquisition methods. PMID:24398475
A Comparison of Lumpectomy Cavity Delineations Between Use of Magnetic Resonance Imaging and Computed Tomography Acquired With Patient in Prone Position for Radiation Therapy Planning of Breast Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Wei; Department of Radiation Oncology, Shandong's Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Jinan; Currey, Adam

2016-03-15

Purpose: To compare lumpectomy cavity (LC) and planning target volume (PTV) delineated with the use of magnetic resonance imaging (MRI) and computed tomography (CT) and to examine the possibility of replacing CT with MRI for radiation therapy (RT) planning for breast cancer. Methods and Materials: MRI and CT data were acquired for 15 patients with early-stage breast cancer undergoing lumpectomy during RT simulation in prone positions, the same as their RT treatment positions. The LCs were delineated manually on both CT (LC-CT) and MRI acquired with 4 sequences: T1, T2, STIR, and DCE. Various PTVs were created by expanding amore » 15-mm margin from the corresponding LCs and from the union of the LCs for the 4 MRI sequences (PTV-MRI). Differences were measured in terms of cavity visualization score (CVS) and dice coefficient (DC). Results: The mean CVSs for T1, T2, STIR, DCE, and CT defined LCs were 3.47, 3.47, 3.87, 3.50. and 2.60, respectively, implying that the LC is mostly visible with a STIR sequence. The mean reductions of LCs from those for CT were 22%, 43%, 36%, and 17% for T1, T2, STIR, and DCE, respectively. In 14 of 15 cases, MRI (union of T1, T2, STIR, and DCE) defined LC included extra regions that would not be visible from CT. The DCs between CT and MRI (union of T1, T2, STIR, and DCE) defined volumes were 0.65 ± 0.20 for LCs and 0.85 ± 0.06 for PTVs. There was no obvious difference between the volumes of PTV-MRI and PTV-CT, and the average PTV-STIR/PTV-CT volume ratio was 0.83 ± 0.23. Conclusions: The use of MRI improves the visibility of LC in comparison with CT. The volumes of LC and PTV generated based on a MRI sequence are substantially smaller than those based on CT, and the PTV-MRI volumes, defined by the union of T1, T2, STIR, and DCE, were comparable with those of PTV-CT for most of the cases studied.« less
Impact of Autocorrelation on Functional Connectivity

PubMed Central

Arbabshirani, Mohammad R.; Damaraju, Eswar; Phlypo, Ronald; Plis, Sergey; Allen, Elena; Ma, Sai; Mathalon, Daniel; Preda, Adrian; Vaidya, Jatin G.; Adali, Tülay; Calhoun, Vince D.

2014-01-01

Although the impact of serial correlation (autocorrelation) in residuals of general linear models for fMRI time-series has been studied extensively, the effect of autocorrelation on functional connectivity studies has been largely neglected until recently. Some recent studies based on results from economics have questioned the conventional estimation of functional connectivity and argue that not correcting for autocorrelation in fMRI time-series results in “spurious” correlation coefficients. In this paper, first we assess the effect of autocorrelation on Pearson correlation coefficient through theoretical approximation and simulation. Then we present this effect on real fMRI data. To our knowledge this is the first work comprehensively investigating the effect of autocorrelation on functional connectivity estimates. Our results show that although FC values are altered, even following correction for autocorrelation, results of hypothesis testing on FC values remain very similar to those before correction. In real data we show this is true for main effects and also for group difference testing between healthy controls and schizophrenia patients. We further discuss model order selection in the context of autoregressive processes, effects of frequency filtering and propose a preprocessing pipeline for connectivity studies. PMID:25072392
Assessment of turbulent viscous stress using ICOSA 4D Flow MRI for prediction of hemodynamic blood damage

NASA Astrophysics Data System (ADS)

Ha, Hojin; Lantz, Jonas; Haraldsson, Henrik; Casas, Belen; Ziegler, Magnus; Karlsson, Matts; Saloner, David; Dyverfeldt, Petter; Ebbers, Tino

2016-12-01

Flow-induced blood damage plays an important role in determining the hemodynamic impact of abnormal blood flow, but quantifying of these effects, which are dominated by shear stresses in highly fluctuating turbulent flow, has not been feasible. This study evaluated the novel application of turbulence tensor measurements using simulated 4D Flow MRI data with six-directional velocity encoding for assessing hemodynamic stresses and corresponding blood damage index (BDI) in stenotic turbulent blood flow. The results showed that 4D Flow MRI underestimates the maximum principal shear stress of laminar viscous stress (PLVS), and overestimates the maximum principal shear stress of Reynolds stress (PRSS) with increasing voxel size. PLVS and PRSS were also overestimated by about 1.2 and 4.6 times at medium signal to noise ratio (SNR) = 20. In contrast, the square sum of the turbulent viscous shear stress (TVSS), which is used for blood damage index (BDI) estimation, was not severely affected by SNR and voxel size. The square sum of TVSS and the BDI at SNR >20 were underestimated by less than 1% and 10%, respectively. In conclusion, this study demonstrated the feasibility of 4D Flow MRI based quantification of TVSS and BDI which are closely linked to blood damage.
Efficient bias correction for magnetic resonance image denoising.

PubMed

Mukherjee, Partha Sarathi; Qiu, Peihua

2013-05-30

Magnetic resonance imaging (MRI) is a popular radiology technique that is used for visualizing detailed internal structure of the body. Observed MRI images are generated by the inverse Fourier transformation from received frequency signals of a magnetic resonance scanner system. Previous research has demonstrated that random noise involved in the observed MRI images can be described adequately by the so-called Rician noise model. Under that model, the observed image intensity at a given pixel is a nonlinear function of the true image intensity and of two independent zero-mean random variables with the same normal distribution. Because of such a complicated noise structure in the observed MRI images, denoised images by conventional denoising methods are usually biased, and the bias could reduce image contrast and negatively affect subsequent image analysis. Therefore, it is important to address the bias issue properly. To this end, several bias-correction procedures have been proposed in the literature. In this paper, we study the Rician noise model and the corresponding bias-correction problem systematically and propose a new and more effective bias-correction formula based on the regression analysis and Monte Carlo simulation. Numerical studies show that our proposed method works well in various applications. Copyright © 2012 John Wiley & Sons, Ltd.
Upright Magnetic Resonance Imaging Tasks in the Knee Osteoarthritis Population: Relationships Between Knee Flexion Angle, Self-Reported Pain, and Performance.

PubMed

Gade, Venkata; Allen, Jerome; Cole, Jeffrey L; Barrance, Peter J

2016-07-01

To characterize the ability of patients with symptomatic knee osteoarthritis (OA) to perform a weight-bearing activity compatible with upright magnetic resonance imaging (MRI) scanning and how this ability is affected by knee pain symptoms and flexion angles. Cross-sectional observational study assessing effects of knee flexion angle, pain level, and study sequence on accuracy and duration of performing a task used in weight-bearing MRI evaluation. Visual feedback of knee position from an MRI compatible sensor was provided. Pain levels were self-reported on a standardized scale. Simulated MRI setup in a research laboratory. Convenience sample of individuals (N=14; 9 women, 5 men; mean, 69±14y) with symptomatic knee OA. Not applicable. Averaged absolute and signed angle error from target knee flexion for each minute of trial and duration tolerance (the duration that subjects maintained position within a prescribed error threshold). Absolute targeting error increased at longer trial durations (P<.001). Duration tolerance decreased with increasing pain (mean ± SE, no pain: 3min 19s±11s; severe pain: 1min 49s±23s; P=.008). Study sequence affected duration tolerance (first knee: 3min 5s±9.1s; second knee: 2min 19s±9.7s; P=.015). The study provided evidence that weight-bearing MRI evaluations based on imaging protocols in the range of 2 to 3 minutes are compatible with patients reporting mild to moderate knee OA-related pain. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.
An MRI-based leg model used to simulate biomechanical phenomena during cuff algometry: a finite element study.

PubMed

Manafi-Khanian, Bahram; Arendt-Nielsen, Lars; Graven-Nielsen, Thomas

2016-03-01

Cuff pressure stimulation is applicable for assessing deep-tissue pain sensitivity by exciting a variety of deep-tissue nociceptors. In this study, the relative transfer of biomechanical stresses and strains from the cuff via the skin to the muscle and the somatic tissue layers around bones were investigated. Cuff pressure was applied on the lower leg at three different stimulation intensities (mild pressure to pain). Three-dimensional finite element models including bones and three different layers of deep tissues were developed based on magnetic resonance images (MRI). The skin indentation maps at mild pressure, pain threshold, and intense painful stimulations were extracted from MRI and applied to the model. The mean stress under the cuff position around tibia was 4.6, 4.9 and around fibula 14.8, 16.4 times greater than mean stress of muscle surface in the same section at pain threshold and intense painful stimulations, respectively. At the same stimulation intensities, the mean strains around tibia were 36.4, 42.3 % and around fibula 32.9, 35.0 %, respectively, of mean strain on the muscle surface. Assuming strain as the ideal stimulus for nociceptors the results suggest that cuff algometry is less capable to challenge the nociceptors of tissues around bones as compared to more superficially located muscles.

Diffusion properties of conventional and calcium-sensitive MRI contrast agents in the rat cerebral cortex.

PubMed

Hagberg, Gisela E; Mamedov, Ilgar; Power, Anthony; Beyerlein, Michael; Merkle, Hellmut; Kiselev, Valerij G; Dhingra, Kirti; Kubìček, Vojtĕch; Angelovski, Goran; Logothetis, Nikos K

2014-01-01

Calcium-sensitive MRI contrast agents can only yield quantitative results if the agent concentration in the tissue is known. The agent concentration could be determined by diffusion modeling, if relevant parameters were available. We have established an MRI-based method capable of determining diffusion properties of conventional and calcium-sensitive agents. Simulations and experiments demonstrate that the method is applicable both for conventional contrast agents with a fixed relaxivity value and for calcium-sensitive contrast agents. The full pharmacokinetic time-course of gadolinium concentration estimates was observed by MRI before, during and after intracerebral administration of the agent, and the effective diffusion coefficient D* was determined by voxel-wise fitting of the solution to the diffusion equation. The method yielded whole brain coverage with a high spatial and temporal sampling. The use of two types of MRI sequences for sampling of the diffusion time courses was investigated: Look-Locker-based quantitative T(1) mapping, and T(1) -weighted MRI. The observation times of the proposed MRI method is long (up to 20 h) and consequently the diffusion distances covered are also long (2-4 mm). Despite this difference, the D* values in vivo were in agreement with previous findings using optical measurement techniques, based on observation times of a few minutes. The effective diffusion coefficient determined for the calcium-sensitive contrast agents may be used to determine local tissue concentrations and to design infusion protocols that maintain the agent concentration at a steady state, thereby enabling quantitative sensing of the local calcium concentration. Copyright © 2014 John Wiley & Sons, Ltd.
An anisotropic diffusion method for denoising dynamic susceptibility contrast-enhanced magnetic resonance images

NASA Astrophysics Data System (ADS)

Murase, Kenya; Yamazaki, Youichi; Shinohara, Masaaki; Kawakami, Kazunori; Kikuchi, Keiichi; Miki, Hitoshi; Mochizuki, Teruhito; Ikezoe, Junpei

2001-10-01

The purpose of this study was to present an application of a novel denoising technique for improving the accuracy of cerebral blood flow (CBF) images generated from dynamic susceptibility contrast-enhanced magnetic resonance imaging (DSC-MRI). The method presented in this study was based on anisotropic diffusion (AD). The usefulness of this method was firstly investigated using computer simulations. We applied this method to patient data acquired using a 1.5 T MR system. After a bolus injection of Gd-DTPA, we obtained 40-50 dynamic images with a 1.32-2.08 s time resolution in 4-6 slices. The dynamic images were processed using the AD method, and then the CBF images were generated using pixel-by-pixel deconvolution analysis. For comparison, the CBF images were also generated with or without processing the dynamic images using a median or Gaussian filter. In simulation studies, the standard deviation of the CBF values obtained after processing by the AD method was smaller than that of the CBF values obtained without any processing, while the mean value agreed well with the true CBF value. Although the median and Gaussian filters also reduced image noise, the mean CBF values were considerably underestimated compared with the true values. Clinical studies also suggested that the AD method was capable of reducing the image noise while preserving the quantitative accuracy of CBF images. In conclusion, the AD method appears useful for denoising DSC-MRI, which will make the CBF images generated from DSC-MRI more reliable.
Resting-State Seed-Based Analysis: An Alternative to Task-Based Language fMRI and Its Laterality Index.

PubMed

Smitha, K A; Arun, K M; Rajesh, P G; Thomas, B; Kesavadas, C

2017-06-01

Language is a cardinal function that makes human unique. Preservation of language function poses a great challenge for surgeons during resection. The aim of the study was to assess the efficacy of resting-state fMRI in the lateralization of language function in healthy subjects to permit its further testing in patients who are unable to perform task-based fMRI. Eighteen healthy right-handed volunteers were prospectively evaluated with resting-state fMRI and task-based fMRI to assess language networks. The laterality indices of Broca and Wernicke areas were calculated by using task-based fMRI via a voxel-value approach. We adopted seed-based resting-state fMRI connectivity analysis together with parameters such as amplitude of low-frequency fluctuation and fractional amplitude of low-frequency fluctuation (fALFF). Resting-state fMRI connectivity maps for language networks were obtained from Broca and Wernicke areas in both hemispheres. We performed correlation analysis between the laterality index and the z scores of functional connectivity, amplitude of low-frequency fluctuation, and fALFF. Pearson correlation analysis between signals obtained from the z score of fALFF and the laterality index yielded a correlation coefficient of 0.849 ( P < .05). Regression analysis of the fALFF with the laterality index yielded an R 2 value of 0.721, indicating that 72.1% of the variance in the laterality index of task-based fMRI could be predicted from the fALFF of resting-state fMRI. The present study demonstrates that fALFF can be used as an alternative to task-based fMRI for assessing language laterality. There was a strong positive correlation between the fALFF of the Broca area of resting-state fMRI with the laterality index of task-based fMRI. Furthermore, we demonstrated the efficacy of fALFF for predicting the laterality of task-based fMRI. © 2017 by American Journal of Neuroradiology.
Is MRI-based CFD able to improve clinical treatment of coarctations of aorta?

PubMed

Goubergrits, L; Riesenkampff, E; Yevtushenko, P; Schaller, J; Kertzscher, U; Berger, F; Kuehne, T

2015-01-01

Pressure drop associated with coarctation of the aorta (CoA) can be successfully treated surgically or by stent placement. However, a decreased life expectancy associated with altered aortic hemodynamics was found in long-term studies. Image-based computational fluid dynamics (CFD) is intended to support particular diagnoses, to help in choosing between treatment options, and to improve performance of treatment procedures. This study aimed to prove the ability of CFD to improve aortic hemodynamics in CoA patients. In 13 patients (6 males, 7 females; mean age 25 ± 14 years), we compared pre- and post-treatment peak systole hemodynamics [pressure drops and wall shear stress (WSS)] vs. virtual treatment as proposed by biomedical engineers. Anatomy and flow data for CFD were based on MRI and angiography. Segmentation, geometry reconstruction and virtual treatment geometry were performed using the software ZIBAmira, whereas peak systole flow conditions were simulated with the software ANSYS(®) Fluent(®). Virtual treatment significantly reduced pressure drop compared to post-treatment values by a mean of 2.8 ± 3.15 mmHg, which significantly reduced mean WSS by 3.8 Pa. Thus, CFD has the potential to improve post-treatment hemodynamics associated with poor long-term prognosis of patients with coarctation of the aorta. MRI-based CFD has a huge potential to allow the slight reduction of post-treatment pressure drop, which causes significant improvement (reduction) of the WSS at the stenosis segment.
Estimating the irreversible pressure drop across a stenosis by quantifying turbulence production using 4D Flow MRI

PubMed Central

Ha, Hojin; Lantz, Jonas; Ziegler, Magnus; Casas, Belen; Karlsson, Matts; Dyverfeldt, Petter; Ebbers, Tino

2017-01-01

The pressure drop across a stenotic vessel is an important parameter in medicine, providing a commonly used and intuitive metric for evaluating the severity of the stenosis. However, non-invasive estimation of the pressure drop under pathological conditions has remained difficult. This study demonstrates a novel method to quantify the irreversible pressure drop across a stenosis using 4D Flow MRI by calculating the total turbulence production of the flow. Simulation MRI acquisitions showed that the energy lost to turbulence production can be accurately quantified with 4D Flow MRI within a range of practical spatial resolutions (1–3 mm; regression slope = 0.91, R2 = 0.96). The quantification of the turbulence production was not substantially influenced by the signal-to-noise ratio (SNR), resulting in less than 2% mean bias at SNR > 10. Pressure drop estimation based on turbulence production robustly predicted the irreversible pressure drop, regardless of the stenosis severity and post-stenosis dilatation (regression slope = 0.956, R2 = 0.96). In vitro validation of the technique in a 75% stenosis channel confirmed that pressure drop prediction based on the turbulence production agreed with the measured pressure drop (regression slope = 1.15, R2 = 0.999, Bland-Altman agreement = 0.75 ± 3.93 mmHg). PMID:28425452
A task-related and resting state realistic fMRI simulator for fMRI data validation

NASA Astrophysics Data System (ADS)

Hill, Jason E.; Liu, Xiangyu; Nutter, Brian; Mitra, Sunanda

2017-02-01

After more than 25 years of published functional magnetic resonance imaging (fMRI) studies, careful scrutiny reveals that most of the reported results lack fully decisive validation. The complex nature of fMRI data generation and acquisition results in unavoidable uncertainties in the true estimation and interpretation of both task-related activation maps and resting state functional connectivity networks, despite the use of various statistical data analysis methodologies. The goal of developing the proposed STANCE (Spontaneous and Task-related Activation of Neuronally Correlated Events) simulator is to generate realistic task-related and/or resting-state 4D blood oxygenation level dependent (BOLD) signals, given the experimental paradigm and scan protocol, by using digital phantoms of twenty normal brains available from BrainWeb (http://brainweb.bic.mni.mcgill.ca/brainweb/). The proposed simulator will include estimated system and modelled physiological noise as well as motion to serve as a reference to measured brain activities. In its current form, STANCE is a MATLAB toolbox with command line functions serving as an open-source add-on to SPM8 (http://www.fil.ion.ucl.ac.uk/spm/software/spm8/). The STANCE simulator has been designed in a modular framework so that the hemodynamic response (HR) and various noise models can be iteratively improved to include evolving knowledge about such models.
A Hierarchical Model for Simultaneous Detection and Estimation in Multi-subject fMRI Studies

PubMed Central

Degras, David; Lindquist, Martin A.

2014-01-01

In this paper we introduce a new hierarchical model for the simultaneous detection of brain activation and estimation of the shape of the hemodynamic response in multi-subject fMRI studies. The proposed approach circumvents a major stumbling block in standard multi-subject fMRI data analysis, in that it both allows the shape of the hemodynamic response function to vary across region and subjects, while still providing a straightforward way to estimate population-level activation. An e cient estimation algorithm is presented, as is an inferential framework that not only allows for tests of activation, but also for tests for deviations from some canonical shape. The model is validated through simulations and application to a multi-subject fMRI study of thermal pain. PMID:24793829
Investigation of factors affecting hypothermic pelvic tissue cooling using bio-heat simulation based on MRI-segmented anatomic models.

PubMed

Lin, Yuting; Lin, Wei-Ching; Fwu, Peter T; Shih, Tzu-Ching; Yeh, Lee-Ren; Su, Min-Ying; Chen, Jeon-Hor

2015-10-01

This study applied a simulation method to map the temperature distribution based on magnetic resonance imaging (MRI) of individual patients, and investigated the influence of different pelvic tissue types as well as the choice of thermal property parameters on the efficiency of endorectal cooling balloon (ECB). MR images of four subjects with different prostate sizes and pelvic tissue compositions, including fatty tissue and venous plexus, were analyzed. The MR images acquired using endorectal coil provided a realistic geometry of deformed prostate that resembled the anatomy in the presence of ECB. A single slice with the largest two-dimensional (2D) cross-sectional area of the prostate gland was selected for analysis. The rectal wall, prostate gland, peri-rectal fatty tissue, peri-prostatic fatty tissue, peri-prostatic venous plexus, and urinary bladder were manually segmented. Pennes' bioheat thermal model was used to simulate the temperature distribution dynamics, by using an in-house finite element mesh based solver written in MATLAB. The results showed that prostate size and periprostatic venous plexus were two major factors affecting ECB cooling efficiency. For cases with negligible amount of venous plexus and small prostate, the average temperature in the prostate and neurovascular bundles could be cooled down to 25 °C within 30 min. For cases with abundant venous plexus and large prostate, the temperature could not reach 25 °C at the end of 3 h cooling. Large prostate made the cooling difficult to propagate through. The impact of fatty tissue on cooling effect was small. The filling of bladder with warm urine during the ECB cooling procedure did not affect the temperature in the prostate or NVB. In addition to the 2D simulation, in one case a 3D pelvic model was constructed for volumetric simulation. It was found that the 2D slice with the largest cross-sectional area of prostate had the most abundant venous plexus, and was the most difficult slice to cool, thus it may provide a conservative prediction of the cooling effect. This feasibility study demonstrated that the simulation tool could potentially be used for adjusting the setting of ECB for individual patients during hypothermic radical prostatectomy. Further studies using MR thermometry are required to validate the in silico results obtained using simulation. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Investigation of factors affecting hypothermic pelvic tissue cooling using bio-heat simulation based on MRI-segmented anatomic models

PubMed Central

Lin, Yuting; Lin, Wei-Ching; Fwu, Peter T.; Shih, Tzu-Ching; Yeh, Lee-Ren; Su, Min-Ying; Chen, Jeon-Hor

2015-01-01

This study applied a simulation method to map the temperature distribution based on magnetic resonance imaging (MRI) of individual patients, and investigated the influence of different pelvic tissue types as well as the choice of thermal property parameters on the efficiency of endorectal cooling balloon (ECB). MR images of four subjects with different prostate sizes and pelvic tissue compositions, including fatty tissue and venous plexus, were analyzed. The MR images acquired using endorectal coil provided a realistic geometry of deformed prostate that resembled the anatomy in the presence of ECB. A single slice with the largest two-dimensional (2D) cross-sectional area of the prostate gland was selected for analysis. The rectal wall, prostate gland, peri-rectal fatty tissue, peri-prostatic fatty tissue, peri-prostatic venous plexus, and urinary bladder were manually segmented. Pennes’ bioheat thermal model was used to simulate the temperature distribution dynamics, by using an in-house finite element mesh based solver written in Matlab. The results showed that prostate size and periprostatic venous plexus were two major factors affecting ECB cooling efficiency. For cases with negligible amount of venous plexus and small prostate, the averaged temperature in the prostate and neurovascular bundles could be cooled down to 25°C within 30 minutes. For cases with abundant venous plexus and large prostate, the temperature could not reach 25°C at the end of 3 hours cooling. Large prostate made the cooling difficult to propagate through. The impact of fatty tissue on cooling effect was small. The filling of bladder with warm urine during the ECB cooling procedure did not affect the temperature in the prostate or NVB. In addition to the 2D simulation, in one case a 3D pelvic model was constructed for volumetric simulation. It was found that the 2D slice with the largest cross-sectional area of prostate had the most abundant venous plexus, and was the most difficult slice to cool, thus it may provide a conservative prediction of the cooling effect. This feasibility study demonstrated that the simulation tool could potentially be used for adjusting the setting of ECB for individual patients during hypothermic radical prostatectomy. Further studies using MR thermometry are required to validate the in silico results obtained using simulation. PMID:26198131
Active control of the spatial MRI phase distribution with optimal control theory

NASA Astrophysics Data System (ADS)

Lefebvre, Pauline M.; Van Reeth, Eric; Ratiney, Hélène; Beuf, Olivier; Brusseau, Elisabeth; Lambert, Simon A.; Glaser, Steffen J.; Sugny, Dominique; Grenier, Denis; Tse Ve Koon, Kevin

2017-08-01

This paper investigates the use of Optimal Control (OC) theory to design Radio-Frequency (RF) pulses that actively control the spatial distribution of the MRI magnetization phase. The RF pulses are generated through the application of the Pontryagin Maximum Principle and optimized so that the resulting transverse magnetization reproduces various non-trivial and spatial phase patterns. Two different phase patterns are defined and the resulting optimal pulses are tested both numerically with the ODIN MRI simulator and experimentally with an agar gel phantom on a 4.7 T small-animal MR scanner. Phase images obtained in simulations and experiments are both consistent with the defined phase patterns. A practical application of phase control with OC-designed pulses is also presented, with the generation of RF pulses adapted for a Magnetic Resonance Elastography experiment. This study demonstrates the possibility to use OC-designed RF pulses to encode information in the magnetization phase and could have applications in MRI sequences using phase images.
Initial Validation for the Estimation of Resting-State fMRI Effective Connectivity by a Generalization of the Correlation Approach.

PubMed

Xu, Nan; Spreng, R Nathan; Doerschuk, Peter C

2017-01-01

Resting-state functional MRI (rs-fMRI) is widely used to noninvasively study human brain networks. Network functional connectivity is often estimated by calculating the timeseries correlation between blood-oxygen-level dependent (BOLD) signal from different regions of interest (ROIs). However, standard correlation cannot characterize the direction of information flow between regions. In this paper, we introduce and test a new concept, prediction correlation, to estimate effective connectivity in functional brain networks from rs-fMRI. In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal system driven by another BOLD signal. Three validations are described: (1) Prediction correlation performed well on simulated data where the ground truth was known, and outperformed four other methods. (2) On simulated data designed to display the "common driver" problem, prediction correlation did not introduce false connections between non-interacting driven ROIs. (3) On experimental data, prediction correlation recovered the previously identified network organization of human brain. Prediction correlation scales well to work with hundreds of ROIs, enabling it to assess whole brain interregional connectivity at the single subject level. These results provide an initial validation that prediction correlation can capture the direction of information flow and estimate the duration of extended temporal delays in information flow between regions of interest ROIs based on BOLD signal. This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also performs well in the estimation of causal information flow in the brain.
Polymer film-nanoparticle composites as new multimodality, non-migrating breast biopsy markers.

PubMed

Kaplan, Jonah A; Grinstaff, Mark W; Bloch, B Nicolas

2016-03-01

To develop a breast biopsy marker that resists fast and slow migration and has permanent visibility under commonly used imaging modalities. A polymer-nanoparticle composite film was prepared by embedding superparamagnetic iron oxide nanoparticles and a superelastic Nitinol wire within a flexible polyethylene matrix. MRI, mammography, and ultrasound were used to visualize the marker in agar, ex vivo chicken breast, bovine liver, brisket, and biopsy training phantoms. Fast migration caused by the "accordion effect" was quantified after simulated stereotactic, vacuum-assisted core biopsy/marker placement, and centrifugation was used to simulate accelerated long-term (i.e., slow) migration in ex vivo bovine tissue phantoms. Clear marker visualization under MRI, mammography, and ultrasound was observed. After deployment, the marker partially unfolds to give a geometrically constrained structure preventing fast and slow migration. The marker can be deployed through an 11G introducer without fast migration occurring, and shows substantially less slow migration than conventional markers. The polymer-nanoparticle composite biopsy marker is clearly visible on all clinical imaging modalities and does not show substantial migration, which ensures multimodal assessment of the correct spatial information of the biopsy site, allowing for more accurate diagnosis and treatment planning and improved breast cancer patient care. Polymer-nanoparticle composite biopsy markers are visualized using ultrasound, MRI, and mammography. Embedded iron oxide nanoparticles provide tuneable contrast for MRI visualization. Permanent ultrasound visibility is achieved with a non-biodegradable polymer having a distinct ultrasound signal. Flexible polymer-based biopsy markers undergo shape change upon deployment to minimize migration. Non-migrating multimodal markers will help improve accuracy of pre/post-treatment planning studies.
Haptic fMRI: combining functional neuroimaging with haptics for studying the brain's motor control representation.

PubMed

Menon, Samir; Brantner, Gerald; Aholt, Chris; Kay, Kendrick; Khatib, Oussama

2013-01-01

A challenging problem in motor control neuroimaging studies is the inability to perform complex human motor tasks given the Magnetic Resonance Imaging (MRI) scanner's disruptive magnetic fields and confined workspace. In this paper, we propose a novel experimental platform that combines Functional MRI (fMRI) neuroimaging, haptic virtual simulation environments, and an fMRI-compatible haptic device for real-time haptic interaction across the scanner workspace (above torso ∼ .65×.40×.20m(3)). We implement this Haptic fMRI platform with a novel haptic device, the Haptic fMRI Interface (HFI), and demonstrate its suitability for motor neuroimaging studies. HFI has three degrees-of-freedom (DOF), uses electromagnetic motors to enable high-fidelity haptic rendering (>350Hz), integrates radio frequency (RF) shields to prevent electromagnetic interference with fMRI (temporal SNR >100), and is kinematically designed to minimize currents induced by the MRI scanner's magnetic field during motor displacement (<2cm). HFI possesses uniform inertial and force transmission properties across the workspace, and has low friction (.05-.30N). HFI's RF noise levels, in addition, are within a 3 Tesla fMRI scanner's baseline noise variation (∼.85±.1%). Finally, HFI is haptically transparent and does not interfere with human motor tasks (tested for .4m reaches). By allowing fMRI experiments involving complex three-dimensional manipulation with haptic interaction, Haptic fMRI enables-for the first time-non-invasive neuroscience experiments involving interactive motor tasks, object manipulation, tactile perception, and visuo-motor integration.
Simulating magnetic resonance images based on a model of tumor growth incorporating microenvironment

NASA Astrophysics Data System (ADS)

Jackson, Pamela R.; Hawkins-Daarud, Andrea; Partridge, Savannah C.; Kinahan, Paul E.; Swanson, Kristin R.

2018-03-01

Glioblastoma (GBM), the most aggressive primary brain tumor, is primarily diagnosed and monitored using gadoliniumenhanced T1-weighted and T2-weighted (T2W) magnetic resonance imaging (MRI). Hyperintensity on T2W images is understood to correspond with vasogenic edema and infiltrating tumor cells. GBM's inherent heterogeneity and resulting non-specific MRI image features complicate assessing treatment response. To better understand treatment response, we propose creating a patient-specific untreated virtual imaging control (UVIC), which represents an individual tumor's growth if it had not been treated, for comparison with actual post-treatment images. We generated a T2W MRI UVIC by combining a patient-specific mathematical model of tumor growth with a multi-compartmental MRI signal equation. GBM growth was mathematically modeled using the previously developed Proliferation-Invasion-Hypoxia-Necrosis- Angiogenesis-Edema (PIHNA-E) model, which simulated tumor as being comprised of three cellular phenotypes: normoxic, hypoxic and necrotic cells interacting with a vasculature species, angiogenic factors and extracellular fluid. Within the PIHNA-E model, both hypoxic and normoxic cells emitted angiogenic factors, which recruited additional vessels and caused the vessels to leak, allowing fluid, or edema, to escape into the extracellular space. The model's output was spatial volume fraction maps for each glioma cell type and edema/extracellular space. Volume fraction maps and corresponding T2 values were then incorporated into a multi-compartmental Bloch signal equation to create simulated T2W images. T2 values for individual compartments were estimated from the literature and a normal volunteer. T2 maps calculated from simulated images had normal white matter, normal gray matter, and tumor tissue T2 values within range of literature values.
Analysis of appropriateness of outpatient CT and MRI referred from primary care clinics at an academic medical center: how critical is the need for improved decision support?

PubMed

Lehnert, Bruce E; Bree, Robert L

2010-03-01

The aim of this study was to retrospectively analyze a large group of CT and MRI examinations for appropriateness using evidence-based guidelines. The authors reviewed medical records from 459 elective outpatient CT and MR examinations from primary care physicians. Evidence-based appropriateness criteria from a radiology benefit management company were used to determine if the examination would have met criteria for approval. Submitted clinical history at the time of interpretation and clinic notes and laboratory results preceding the date of the imaging study were examined to simulate a real-time consultation with the referring provider. The radiology reports and subsequent clinic visits were analyzed for outcomes. Of the 459 examinations reviewed, 284 (62%) were CT and 175 (38%) were MRI. Three hundred forty-one (74%) were considered appropriate, and 118 (26%) were not considered appropriate. Examples of inappropriate examinations included brain CT for chronic headache, lumbar spine MR for acute back pain, knee or shoulder MRI in patients with osteoarthritis, and CT for hematuria during a urinary tract infection. Fifty-eight percent of the appropriate studies had positive results and affected subsequent management, whereas only thirteen percent [corrected] of inappropriate studies had positive results and affected management. A high percentage of examinations not meeting appropriateness criteria and subsequently yielding negative results suggests a need for tools to help primary care physicians improve the quality of their imaging decision requests. In the current environment, which stresses cost containment and comparative effectiveness, traditional radiology benefit management tools are being challenged by clinical decision support, with an emphasis on provider education coupled with electronic order entry systems.
In vitro flow assessment: from PC-MRI to computational fluid dynamics including fluid-structure interaction

NASA Astrophysics Data System (ADS)

Kratzke, Jonas; Rengier, Fabian; Weis, Christian; Beller, Carsten J.; Heuveline, Vincent

2016-04-01

Initiation and development of cardiovascular diseases can be highly correlated to specific biomechanical parameters. To examine and assess biomechanical parameters, numerical simulation of cardiovascular dynamics has the potential to complement and enhance medical measurement and imaging techniques. As such, computational fluid dynamics (CFD) have shown to be suitable to evaluate blood velocity and pressure in scenarios, where vessel wall deformation plays a minor role. However, there is a need for further validation studies and the inclusion of vessel wall elasticity for morphologies being subject to large displacement. In this work, we consider a fluid-structure interaction (FSI) model including the full elasticity equation to take the deformability of aortic wall soft tissue into account. We present a numerical framework, in which either a CFD study can be performed for less deformable aortic segments or an FSI simulation for regions of large displacement such as the aortic root and arch. Both of the methods are validated by means of an aortic phantom experiment. The computational results are in good agreement with 2D phase-contrast magnetic resonance imaging (PC-MRI) velocity measurements as well as catheter-based pressure measurements. The FSI simulation shows a characteristic vessel compliance effect on the flow field induced by the elasticity of the vessel wall, which the CFD model is not capable of. The in vitro validated FSI simulation framework can enable the computation of complementary biomechanical parameters such as the stress distribution within the vessel wall.
MRI Simulation Study Investigating Effects of Vessel Topology, Diffusion, and Susceptibility on Transverse Relaxation Rates Using a Cylinder Fork Model.

PubMed

Shazeeb, Mohammed Salman; Kalpathy-Cramer, Jayashree; Issa, Bashar

2017-11-24

Brain vasculature is conventionally represented as straight cylinders when simulating blood oxygenation level dependent (BOLD) contrast effects in functional magnetic resonance imaging (fMRI). In reality, the vasculature is more complicated with branching and coiling especially in tumors. Diffusion and susceptibility changes can also introduce variations in the relaxation mechanisms within tumors. This study introduces a simple cylinder fork model (CFM) and investigates the effects of vessel topology, diffusion, and susceptibility on the transverse relaxation rates R2* and R2. Simulations using Monte Carlo methods were performed to quantify R2* and R2 by manipulating the CFM at different orientations, bifurcation angles, and rotation angles. Other parameters of the CFM were chosen based on physiologically relevant values: vessel diameters (~2‒10 µm), diffusion rates (1 × 10 -11 ‒1 × 10 -9 m 2 /s), and susceptibility values (3 × 10 -8 -4 × 10 -7 cgs units). R2* and R2 measurements showed a significant dependence on the bifurcation and rotation angles in several scenarios using different vessel diameters, orientations, diffusion rates, and susceptibility values. The angular dependence of R2* and R2 using the CFM could potentially be exploited as a tool to differentiate between normal and tumor vessels. The CFM can also serve as the elementary building block to simulate a capillary network reflecting realistic topological features.
Brain atrophy can introduce age-related differences in BOLD response.

PubMed

Liu, Xueqing; Gerraty, Raphael T; Grinband, Jack; Parker, David; Razlighi, Qolamreza R

2017-04-11

Use of functional magnetic resonance imaging (fMRI) in studies of aging is often hampered by uncertainty about age-related differences in the amplitude and timing of the blood oxygenation level dependent (BOLD) response (i.e., hemodynamic impulse response function (HRF)). Such uncertainty introduces a significant challenge in the interpretation of the fMRI results. Even though this issue has been extensively investigated in the field of neuroimaging, there is currently no consensus about the existence and potential sources of age-related hemodynamic alterations. Using an event-related fMRI experiment with two robust and well-studied stimuli (visual and auditory), we detected a significant age-related difference in the amplitude of response to auditory stimulus. Accounting for brain atrophy by circumventing spatial normalization and processing the data in subjects' native space eliminated these observed differences. In addition, we simulated fMRI data using age differences in brain morphology while controlling HRF shape. Analyzing these simulated fMRI data using standard image processing resulted in differences in HRF amplitude, which were eliminated when the data were analyzed in subjects' native space. Our results indicate that age-related atrophy introduces inaccuracy in co-registration to standard space, which subsequently appears as attenuation in BOLD response amplitude. Our finding could explain some of the existing contradictory reports regarding age-related differences in the fMRI BOLD responses. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
PARTICLE FILTERING WITH SEQUENTIAL PARAMETER LEARNING FOR NONLINEAR BOLD fMRI SIGNALS.

PubMed

Xia, Jing; Wang, Michelle Yongmei

Analyzing the blood oxygenation level dependent (BOLD) effect in the functional magnetic resonance imaging (fMRI) is typically based on recent ground-breaking time series analysis techniques. This work represents a significant improvement over existing approaches to system identification using nonlinear hemodynamic models. It is important for three reasons. First, instead of using linearized approximations of the dynamics, we present a nonlinear filtering based on the sequential Monte Carlo method to capture the inherent nonlinearities in the physiological system. Second, we simultaneously estimate the hidden physiological states and the system parameters through particle filtering with sequential parameter learning to fully take advantage of the dynamic information of the BOLD signals. Third, during the unknown static parameter learning, we employ the low-dimensional sufficient statistics for efficiency and avoiding potential degeneration of the parameters. The performance of the proposed method is validated using both the simulated data and real BOLD fMRI data.
Individual differences in transcranial electrical stimulation current density

PubMed Central

Russell, Michael J; Goodman, Theodore; Pierson, Ronald; Shepherd, Shane; Wang, Qiang; Groshong, Bennett; Wiley, David F

2013-01-01

Transcranial electrical stimulation (TCES) is effective in treating many conditions, but it has not been possible to accurately forecast current density within the complex anatomy of a given subject's head. We sought to predict and verify TCES current densities and determine the variability of these current distributions in patient-specific models based on magnetic resonance imaging (MRI) data. Two experiments were performed. The first experiment estimated conductivity from MRIs and compared the current density results against actual measurements from the scalp surface of 3 subjects. In the second experiment, virtual electrodes were placed on the scalps of 18 subjects to model simulated current densities with 2 mA of virtually applied stimulation. This procedure was repeated for 4 electrode locations. Current densities were then calculated for 75 brain regions. Comparison of modeled and measured external current in experiment 1 yielded a correlation of r = .93. In experiment 2, modeled individual differences were greatest near the electrodes (ten-fold differences were common), but simulated current was found in all regions of the brain. Sites that were distant from the electrodes (e.g. hypothalamus) typically showed two-fold individual differences. MRI-based modeling can effectively predict current densities in individual brains. Significant variation occurs between subjects with the same applied electrode configuration. Individualized MRI-based modeling should be considered in place of the 10-20 system when accurate TCES is needed. PMID:24285948

POCS-enhanced correction of motion artifacts in parallel MRI.

PubMed

Samsonov, Alexey A; Velikina, Julia; Jung, Youngkyoo; Kholmovski, Eugene G; Johnson, Chris R; Block, Walter F

2010-04-01

A new method for correction of MRI motion artifacts induced by corrupted k-space data, acquired by multiple receiver coils such as phased arrays, is presented. In our approach, a projections onto convex sets (POCS)-based method for reconstruction of sensitivity encoded MRI data (POCSENSE) is employed to identify corrupted k-space samples. After the erroneous data are discarded from the dataset, the artifact-free images are restored from the remaining data using coil sensitivity profiles. The error detection and data restoration are based on informational redundancy of phased-array data and may be applied to full and reduced datasets. An important advantage of the new POCS-based method is that, in addition to multicoil data redundancy, it can use a priori known properties about the imaged object for improved MR image artifact correction. The use of such information was shown to improve significantly k-space error detection and image artifact correction. The method was validated on data corrupted by simulated and real motion such as head motion and pulsatile flow.
Ranking and averaging independent component analysis by reproducibility (RAICAR).

PubMed

Yang, Zhi; LaConte, Stephen; Weng, Xuchu; Hu, Xiaoping

2008-06-01

Independent component analysis (ICA) is a data-driven approach that has exhibited great utility for functional magnetic resonance imaging (fMRI). Standard ICA implementations, however, do not provide the number and relative importance of the resulting components. In addition, ICA algorithms utilizing gradient-based optimization give decompositions that are dependent on initialization values, which can lead to dramatically different results. In this work, a new method, RAICAR (Ranking and Averaging Independent Component Analysis by Reproducibility), is introduced to address these issues for spatial ICA applied to fMRI. RAICAR utilizes repeated ICA realizations and relies on the reproducibility between them to rank and select components. Different realizations are aligned based on correlations, leading to aligned components. Each component is ranked and thresholded based on between-realization correlations. Furthermore, different realizations of each aligned component are selectively averaged to generate the final estimate of the given component. Reliability and accuracy of this method are demonstrated with both simulated and experimental fMRI data. Copyright 2007 Wiley-Liss, Inc.
PROMO – Real-time Prospective Motion Correction in MRI using Image-based Tracking

PubMed Central

White, Nathan; Roddey, Cooper; Shankaranarayanan, Ajit; Han, Eric; Rettmann, Dan; Santos, Juan; Kuperman, Josh; Dale, Anders

2010-01-01

Artifacts caused by patient motion during scanning remain a serious problem in most MRI applications. The prospective motion correction technique attempts to address this problem at its source by keeping the measurement coordinate system fixed with respect to the patient throughout the entire scan process. In this study, a new image-based approach for prospective motion correction is described, which utilizes three orthogonal 2D spiral navigator acquisitions (SP-Navs) along with a flexible image-based tracking method based on the Extended Kalman Filter (EKF) algorithm for online motion measurement. The SP-Nav/EKF framework offers the advantages of image-domain tracking within patient-specific regions-of-interest and reduced sensitivity to off-resonance-induced corruption of rigid-body motion estimates. The performance of the method was tested using offline computer simulations and online in vivo head motion experiments. In vivo validation results covering a broad range of staged head motions indicate a steady-state error of the SP-Nav/EKF motion estimates of less than 10 % of the motion magnitude, even for large compound motions that included rotations over 15 degrees. A preliminary in vivo application in 3D inversion recovery spoiled gradient echo (IR-SPGR) and 3D fast spin echo (FSE) sequences demonstrates the effectiveness of the SP-Nav/EKF framework for correcting 3D rigid-body head motion artifacts prospectively in high-resolution 3D MRI scans. PMID:20027635
MR-based measurements and simulations of the magnetic field created by a realistic transcranial magnetic stimulation (TMS) coil and stimulator.

PubMed

Mandija, Stefano; Petrov, Petar I; Neggers, Sebastian F W; Luijten, Peter R; van den Berg, Cornelis A T

2016-11-01

Transcranial magnetic stimulation (TMS) is an emerging technique that allows non-invasive neurostimulation. However, the correct validation of electromagnetic models of typical TMS coils and the correct assessment of the incident TMS field (B TMS ) produced by standard TMS stimulators are still lacking. Such a validation can be performed by mapping B TMS produced by a realistic TMS setup. In this study, we show that MRI can provide precise quantification of the magnetic field produced by a realistic TMS coil and a clinically used TMS stimulator in the region in which neurostimulation occurs. Measurements of the phase accumulation created by TMS pulses applied during a tailored MR sequence were performed in a phantom. Dedicated hardware was developed to synchronize a typical, clinically used, TMS setup with a 3-T MR scanner. For comparison purposes, electromagnetic simulations of B TMS were performed. MR-based measurements allow the mapping and quantification of B TMS starting 2.5 cm from the TMS coil. For closer regions, the intra-voxel dephasing induced by B TMS prohibits TMS field measurements. For 1% TMS output, the maximum measured value was ~0.1 mT. Simulations reflect quantitatively the experimental data. These measurements can be used to validate electromagnetic models of TMS coils, to guide TMS coil positioning, and for dosimetry and quality assessment of concurrent TMS-MRI studies without the need for crude methods, such as motor threshold, for stimulation dose determination. Copyright © 2016 John Wiley & Sons, Ltd.
Resting-State Functional Connectivity-Based Biomarkers and Functional MRI-Based Neurofeedback for Psychiatric Disorders: A Challenge for Developing Theranostic Biomarkers.

PubMed

Yamada, Takashi; Hashimoto, Ryu-Ichiro; Yahata, Noriaki; Ichikawa, Naho; Yoshihara, Yujiro; Okamoto, Yasumasa; Kato, Nobumasa; Takahashi, Hidehiko; Kawato, Mitsuo

2017-10-01

Psychiatric research has been hampered by an explanatory gap between psychiatric symptoms and their neural underpinnings, which has resulted in poor treatment outcomes. This situation has prompted us to shift from symptom-based diagnosis to data-driven diagnosis, aiming to redefine psychiatric disorders as disorders of neural circuitry. Promising candidates for data-driven diagnosis include resting-state functional connectivity MRI (rs-fcMRI)-based biomarkers. Although biomarkers have been developed with the aim of diagnosing patients and predicting the efficacy of therapy, the focus has shifted to the identification of biomarkers that represent therapeutic targets, which would allow for more personalized treatment approaches. This type of biomarker (i.e., "theranostic biomarker") is expected to elucidate the disease mechanism of psychiatric conditions and to offer an individualized neural circuit-based therapeutic target based on the neural cause of a condition. To this end, researchers have developed rs-fcMRI-based biomarkers and investigated a causal relationship between potential biomarkers and disease-specific behavior using functional MRI (fMRI)-based neurofeedback on functional connectivity. In this review, we introduce a recent approach for creating a theranostic biomarker, which consists mainly of 2 parts: (1) developing an rs-fcMRI-based biomarker that can predict diagnosis and/or symptoms with high accuracy, and (2) the introduction of a proof-of-concept study investigating the relationship between normalizing the biomarker and symptom changes using fMRI-based neurofeedback. In parallel with the introduction of recent studies, we review rs-fcMRI-based biomarker and fMRI-based neurofeedback, focusing on the technological improvements and limitations associated with clinical use. © The Author 2017. Published by Oxford University Press on behalf of CINP.
Resting-State Functional Connectivity-Based Biomarkers and Functional MRI-Based Neurofeedback for Psychiatric Disorders: A Challenge for Developing Theranostic Biomarkers

PubMed Central

Yamada, Takashi; Hashimoto, Ryu-ichiro; Yahata, Noriaki; Ichikawa, Naho; Yoshihara, Yujiro; Okamoto, Yasumasa; Kato, Nobumasa; Takahashi, Hidehiko

2017-01-01

Abstract Psychiatric research has been hampered by an explanatory gap between psychiatric symptoms and their neural underpinnings, which has resulted in poor treatment outcomes. This situation has prompted us to shift from symptom-based diagnosis to data-driven diagnosis, aiming to redefine psychiatric disorders as disorders of neural circuitry. Promising candidates for data-driven diagnosis include resting-state functional connectivity MRI (rs-fcMRI)-based biomarkers. Although biomarkers have been developed with the aim of diagnosing patients and predicting the efficacy of therapy, the focus has shifted to the identification of biomarkers that represent therapeutic targets, which would allow for more personalized treatment approaches. This type of biomarker (i.e., “theranostic biomarker”) is expected to elucidate the disease mechanism of psychiatric conditions and to offer an individualized neural circuit-based therapeutic target based on the neural cause of a condition. To this end, researchers have developed rs-fcMRI-based biomarkers and investigated a causal relationship between potential biomarkers and disease-specific behavior using functional MRI (fMRI)-based neurofeedback on functional connectivity. In this review, we introduce a recent approach for creating a theranostic biomarker, which consists mainly of 2 parts: (1) developing an rs-fcMRI-based biomarker that can predict diagnosis and/or symptoms with high accuracy, and (2) the introduction of a proof-of-concept study investigating the relationship between normalizing the biomarker and symptom changes using fMRI-based neurofeedback. In parallel with the introduction of recent studies, we review rs-fcMRI-based biomarker and fMRI-based neurofeedback, focusing on the technological improvements and limitations associated with clinical use. PMID:28977523
Multichannel Compressive Sensing MRI Using Noiselet Encoding

PubMed Central

Pawar, Kamlesh; Egan, Gary; Zhang, Jingxin

2015-01-01

The incoherence between measurement and sparsifying transform matrices and the restricted isometry property (RIP) of measurement matrix are two of the key factors in determining the performance of compressive sensing (CS). In CS-MRI, the randomly under-sampled Fourier matrix is used as the measurement matrix and the wavelet transform is usually used as sparsifying transform matrix. However, the incoherence between the randomly under-sampled Fourier matrix and the wavelet matrix is not optimal, which can deteriorate the performance of CS-MRI. Using the mathematical result that noiselets are maximally incoherent with wavelets, this paper introduces the noiselet unitary bases as the measurement matrix to improve the incoherence and RIP in CS-MRI. Based on an empirical RIP analysis that compares the multichannel noiselet and multichannel Fourier measurement matrices in CS-MRI, we propose a multichannel compressive sensing (MCS) framework to take the advantage of multichannel data acquisition used in MRI scanners. Simulations are presented in the MCS framework to compare the performance of noiselet encoding reconstructions and Fourier encoding reconstructions at different acceleration factors. The comparisons indicate that multichannel noiselet measurement matrix has better RIP than that of its Fourier counterpart, and that noiselet encoded MCS-MRI outperforms Fourier encoded MCS-MRI in preserving image resolution and can achieve higher acceleration factors. To demonstrate the feasibility of the proposed noiselet encoding scheme, a pulse sequences with tailored spatially selective RF excitation pulses was designed and implemented on a 3T scanner to acquire the data in the noiselet domain from a phantom and a human brain. The results indicate that noislet encoding preserves image resolution better than Fouirer encoding. PMID:25965548
Validation of voxel-based morphometry (VBM) based on MRI

NASA Astrophysics Data System (ADS)

Yang, Xueyu; Chen, Kewei; Guo, Xiaojuan; Yao, Li

2007-03-01

Voxel-based morphometry (VBM) is an automated and objective image analysis technique for detecting differences in regional concentration or volume of brain tissue composition based on structural magnetic resonance (MR) images. VBM has been used widely to evaluate brain morphometric differences between different populations, but there isn't an evaluation system for its validation until now. In this study, a quantitative and objective evaluation system was established in order to assess VBM performance. We recruited twenty normal volunteers (10 males and 10 females, age range 20-26 years, mean age 22.6 years). Firstly, several focal lesions (hippocampus, frontal lobe, anterior cingulate, back of hippocampus, back of anterior cingulate) were simulated in selected brain regions using real MRI data. Secondly, optimized VBM was performed to detect structural differences between groups. Thirdly, one-way ANOVA and post-hoc test were used to assess the accuracy and sensitivity of VBM analysis. The results revealed that VBM was a good detective tool in majority of brain regions, even in controversial brain region such as hippocampus in VBM study. Generally speaking, much more severity of focal lesion was, better VBM performance was. However size of focal lesion had little effects on VBM analysis.
Groupwise registration of cardiac perfusion MRI sequences using normalized mutual information in high dimension

NASA Astrophysics Data System (ADS)

Hamrouni, Sameh; Rougon, Nicolas; Pr"teux, Françoise

2011-03-01

In perfusion MRI (p-MRI) exams, short-axis (SA) image sequences are captured at multiple slice levels along the long-axis of the heart during the transit of a vascular contrast agent (Gd-DTPA) through the cardiac chambers and muscle. Compensating cardio-thoracic motions is a requirement for enabling computer-aided quantitative assessment of myocardial ischaemia from contrast-enhanced p-MRI sequences. The classical paradigm consists of registering each sequence frame on a reference image using some intensity-based matching criterion. In this paper, we introduce a novel unsupervised method for the spatio-temporal groupwise registration of cardiac p-MRI exams based on normalized mutual information (NMI) between high-dimensional feature distributions. Here, local contrast enhancement curves are used as a dense set of spatio-temporal features, and statistically matched through variational optimization to a target feature distribution derived from a registered reference template. The hard issue of probability density estimation in high-dimensional state spaces is bypassed by using consistent geometric entropy estimators, allowing NMI to be computed directly from feature samples. Specifically, a computationally efficient kth-nearest neighbor (kNN) estimation framework is retained, leading to closed-form expressions for the gradient flow of NMI over finite- and infinite-dimensional motion spaces. This approach is applied to the groupwise alignment of cardiac p-MRI exams using a free-form Deformation (FFD) model for cardio-thoracic motions. Experiments on simulated and natural datasets suggest its accuracy and robustness for registering p-MRI exams comprising more than 30 frames.
Non-Cartesian MRI Reconstruction With Automatic Regularization Via Monte-Carlo SURE

PubMed Central

Weller, Daniel S.; Nielsen, Jon-Fredrik; Fessler, Jeffrey A.

2013-01-01

Magnetic resonance image (MRI) reconstruction from undersampled k-space data requires regularization to reduce noise and aliasing artifacts. Proper application of regularization however requires appropriate selection of associated regularization parameters. In this work, we develop a data-driven regularization parameter adjustment scheme that minimizes an estimate (based on the principle of Stein’s unbiased risk estimate—SURE) of a suitable weighted squared-error measure in k-space. To compute this SURE-type estimate, we propose a Monte-Carlo scheme that extends our previous approach to inverse problems (e.g., MRI reconstruction) involving complex-valued images. Our approach depends only on the output of a given reconstruction algorithm and does not require knowledge of its internal workings, so it is capable of tackling a wide variety of reconstruction algorithms and nonquadratic regularizers including total variation and those based on the ℓ1-norm. Experiments with simulated and real MR data indicate that the proposed approach is capable of providing near mean squared-error (MSE) optimal regularization parameters for single-coil undersampled non-Cartesian MRI reconstruction. PMID:23591478
MHD simulation of transition process from the magneto-rotational instability to magnetic turbulence by using a high-order MHD simulation scheme

NASA Astrophysics Data System (ADS)

Hirai, K.; Katoh, Y.; Terada, N.; Kawai, S.

2016-12-01

In accretion disks, magneto-rotational instability (MRI; Balbus & Hawley, 1991) makes the disk gas in the magnetic turbulent state and drives efficient mass accretion into a central star. MRI drives turbulence through the evolution of the parasitic instability (PI; Goodman & Xu, 1994), which is related to both Kelvin-Helmholtz (K-H) instability and magnetic reconnection. The wave number vector of PI is strongly affected by both magnetic diffusivity and fluid viscosity (Pessah, 2010). This fact makes MHD simulation of MRI difficult, because we need to employ the numerical diffusivity for treating discontinuities in compressible MHD simulation schemes. Therefore, it is necessary to use an MHD scheme that has both high-order accuracy so as to resolve MRI driven turbulence and small numerical diffusivity enough to treat discontinuities. We have originally developed an MHD code by employing the scheme proposed by Kawai (2013). This scheme focuses on resolving turbulence accurately by using a high-order compact difference scheme (Lele, 1992), and meanwhile, the scheme treats discontinuities by using the localized artificial diffusivity method (Kawai, 2013). Our code also employs the pipeline algorithm (Matsuura & Kato, 2007) for MPI parallelization without diminishing the accuracy of the compact difference scheme. We carry out a 3-dimensional ideal MHD simulation with a net vertical magnetic field in the local shearing box disk model. We use 256x256x128 grids. Simulation results show that the spatially averaged turbulent stress induced by MRI linearly grows until around 2.8 orbital periods, and decreases after the saturation. We confirm the strong enhancement of the K-H mode PI at a timing just before the saturation, identified by the enhancement of its anisotropic wavenumber spectra in the 2-dimensional wavenumber space. The wave number of the maximum growth of PI reproduced in the simulation result is larger than the linear analysis. This discrepancy is explained by the simulation result that a shear flow created by MRI locally becomes thinner and faster due to interactions between antiparallel vortices induced by K-H mode PI, and this structure induces small scale waves which break the shear flow itself. We report the results of the simulation, and discuss how the saturation amplitude of MRI is determined.
Multi-tissue partial volume quantification in multi-contrast MRI using an optimised spectral unmixing approach.

PubMed

Collewet, Guylaine; Moussaoui, Saïd; Deligny, Cécile; Lucas, Tiphaine; Idier, Jérôme

2018-06-01

Multi-tissue partial volume estimation in MRI images is investigated with a viewpoint related to spectral unmixing as used in hyperspectral imaging. The main contribution of this paper is twofold. It firstly proposes a theoretical analysis of the statistical optimality conditions of the proportion estimation problem, which in the context of multi-contrast MRI data acquisition allows to appropriately set the imaging sequence parameters. Secondly, an efficient proportion quantification algorithm based on the minimisation of a penalised least-square criterion incorporating a regularity constraint on the spatial distribution of the proportions is proposed. Furthermore, the resulting developments are discussed using empirical simulations. The practical usefulness of the spectral unmixing approach for partial volume quantification in MRI is illustrated through an application to food analysis on the proving of a Danish pastry. Copyright © 2018 Elsevier Inc. All rights reserved.
Mapping B(1)-induced eddy current effects near metallic structures in MR images: a comparison of simulation and experiment.

PubMed

Vashaee, S; Goora, F; Britton, M M; Newling, B; Balcom, B J

2015-01-01

Magnetic resonance imaging (MRI) in the presence of metallic structures is very common in medical and non-medical fields. Metallic structures cause MRI image distortions by three mechanisms: (1) static field distortion through magnetic susceptibility mismatch, (2) eddy currents induced by switched magnetic field gradients and (3) radio frequency (RF) induced eddy currents. Single point ramped imaging with T1 enhancement (SPRITE) MRI measurements are largely immune to susceptibility and gradient induced eddy current artifacts. As a result, one can isolate the effects of metal objects on the RF field. The RF field affects both the excitation and detection of the magnetic resonance (MR) signal. This is challenging with conventional MRI methods, which cannot readily separate the three effects. RF induced MRI artifacts were investigated experimentally at 2.4 T by analyzing image distortions surrounding two geometrically identical metallic strips of aluminum and lead. The strips were immersed in agar gel doped with contrast agent and imaged employing the conical SPRITE sequence. B1 mapping with pure phase encode SPRITE was employed to measure the B1 field around the strips of metal. The strip geometry was chosen to mimic metal electrodes employed in electrochemistry studies. Simulations are employed to investigate the RF field induced eddy currents in the two metallic strips. The RF simulation results are in good agreement with experimental results. Experimental and simulation results show that the metal has a pronounced effect on the B1 distribution and B1 amplitude in the surrounding space. The electrical conductivity of the metal has a minimal effect. Copyright © 2014 Elsevier Inc. All rights reserved.
Adenomyosis with extensive glandular proliferation simulating infiltrating malignancy on magnetic resonance imaging.

PubMed

Funaki, Kaoru; Fukunishi, Hidenobu; Maeda, Tetsuo; Ohbayashi, Chiho; Yamaguchi, Satoshi

2011-05-01

We report a case of multicystic adenomyosis, which is an exceedingly rare benign tumor. The patient complained of an irregular menstrual cycle and abnormal genital bleeding that gradually increased in amount and frequency. The patient finally became severely anemic, and a hysterectomy was therefore performed. T2-weighted magnetic resonance imaging (MRI) indicated hyperplasia of the endometrium, with a myometrial lesion, where a high signal intensity multicystic mass was observed. The preoperative diagnosis was complicated by confusing MRI results. Postoperative macroscopic examination revealed a villous endometrium and a myometrium thickened with multiple small cysts containing serous transparent fluid. The final diagnosis, based on the hysterectomy specimen, was adenomyosis coexisting with simple endometrial hyperplasia. The MRI and positron emission tomography images are presented.
AFFINE-CORRECTED PARADISE: FREE-BREATHING PATIENT-ADAPTIVE CARDIAC MRI WITH SENSITIVITY ENCODING

PubMed Central

Sharif, Behzad; Bresler, Yoram

2013-01-01

We propose a real-time cardiac imaging method with parallel MRI that allows for free breathing during imaging and does not require cardiac or respiratory gating. The method is based on the recently proposed PARADISE (Patient-Adaptive Reconstruction and Acquisition Dynamic Imaging with Sensitivity Encoding) scheme. The new acquisition method adapts the PARADISE k-t space sampling pattern according to an affine model of the respiratory motion. The reconstruction scheme involves multi-channel time-sequential imaging with time-varying channels. All model parameters are adapted to the imaged patient as part of the experiment and drive both data acquisition and cine reconstruction. Simulated cardiac MRI experiments using the realistic NCAT phantom show high quality cine reconstructions and robustness to modeling inaccuracies. PMID:24390159
Restoration of fMRI Decodability Does Not Imply Latent Working Memory States

PubMed Central

Schneegans, Sebastian; Bays, Paul M.

2018-01-01

Recent imaging studies have challenged the prevailing view that working memory is mediated by sustained neural activity. Using machine learning methods to reconstruct memory content, these studies found that previously diminished representations can be restored by retrospective cueing or other forms of stimulation. These findings have been interpreted as evidence for an activity-silent working memory state that can be reactivated dependent on task demands. Here, we test the validity of this conclusion by formulating a neural process model of working memory based on sustained activity and using this model to emulate a spatial recall task with retrocueing. The simulation reproduces both behavioral and fMRI results previously taken as evidence for latent states, in particular the restoration of spatial reconstruction quality following an informative cue. Our results demonstrate that recovery of the decodability of an imaging signal does not provide compelling evidence for an activity-silent working memory state. PMID:28820674
Fundamentals of Filament Interaction

DTIC Science & Technology

2017-05-19

MRI was very specific. Based in on our other studies we focused this MRI program in two very important areas –filament interaction with gases, and...shown in the figure adjacent. The focus of this MRI was very specific. Based in on our other studies we focused this MRI program in two very important...PROJECT. 2.0.0 Program on Interaction with Gases 2.1.0 Molecular alignment studies Following the observations by Béjot et al. [Optics Express 16
Investigating the enhancement of template-free activation detection of event-related fMRI data using wavelet shrinkage and figures of merit.

PubMed

Ngan, Shing-Chung; Hu, Xiaoping; Khong, Pek-Lan

2011-03-01

We propose a method for preprocessing event-related functional magnetic resonance imaging (fMRI) data that can lead to enhancement of template-free activation detection. The method is based on using a figure of merit to guide the wavelet shrinkage of a given fMRI data set. Several previous studies have demonstrated that in the root-mean-square error setting, wavelet shrinkage can improve the signal-to-noise ratio of fMRI time courses. However, preprocessing fMRI data in the root-mean-square error setting does not necessarily lead to enhancement of template-free activation detection. Motivated by this observation, in this paper, we move to the detection setting and investigate the possibility of using wavelet shrinkage to enhance template-free activation detection of fMRI data. The main ingredients of our method are (i) forward wavelet transform of the voxel time courses, (ii) shrinking the resulting wavelet coefficients as directed by an appropriate figure of merit, (iii) inverse wavelet transform of the shrunk data, and (iv) submitting these preprocessed time courses to a given activation detection algorithm. Two figures of merit are developed in the paper, and two other figures of merit adapted from the literature are described. Receiver-operating characteristic analyses with simulated fMRI data showed quantitative evidence that data preprocessing as guided by the figures of merit developed in the paper can yield improved detectability of the template-free measures. We also demonstrate the application of our methodology on an experimental fMRI data set. The proposed method is useful for enhancing template-free activation detection in event-related fMRI data. It is of significant interest to extend the present framework to produce comprehensive, adaptive and fully automated preprocessing of fMRI data optimally suited for subsequent data analysis steps. Copyright © 2010 Elsevier B.V. All rights reserved.
In vitro quantitative ((1))H and ((19))F nuclear magnetic resonance spectroscopy and imaging studies of fluvastatin™ in Lescol® XL tablets in a USP-IV dissolution cell.

PubMed

Zhang, Qilei; Gladden, Lynn; Avalle, Paolo; Mantle, Michael

2011-12-20

Swellable polymeric matrices are key systems in the controlled drug release area. Currently, the vast majority of research is still focused on polymer swelling dynamics. This study represents the first quantitative multi-nuclear (((1))H and ((19))F) fast magnetic resonance imaging study of the complete dissolution process of a commercial (Lescol® XL) tablet, whose formulation is based on the hydroxypropyl methylcellulose (HPMC) polymer under in vitro conditions in a standard USP-IV (United States Pharmacopeia apparatus IV) flow-through cell that is incorporated into high field superconducting magnetic resonance spectrometer. Quantitative RARE ((1))H magnetic resonance imaging (MRI) and ((19))F nuclear magnetic resonance (NMR) spectroscopy and imaging methods have been used to give information on: (i) dissolution media uptake and hydrodynamics; (ii) active pharmaceutical ingredient (API) mobilisation and dissolution; (iii) matrix swelling and dissolution and (iv) media activity within the swelling matrix. In order to better reflect the in vivo conditions, the bio-relevant media Simulated Gastric Fluid (SGF) and Fasted State Simulated Intestinal Fluid (FaSSIF) were used. A newly developed quantitative ultra-fast MRI technique was applied and the results clearly show the transport dynamics of media penetration and hydrodynamics along with the polymer swelling processes. The drug dissolution and mobility inside the gel matrix was characterised, in parallel to the ((1))H measurements, by ((19))F NMR spectroscopy and MRI, and the drug release profile in the bulk solution was recorded offline by UV spectrometer. We found that NMR spectroscopy and 1D-MRI can be uniquely used to monitor the drug dissolution/mobilisation process within the gel layer, and the results from ((19))F NMR spectra indicate that in the gel layer, the physical mobility of the drug changes from "dissolved immobilised drug" to "dissolved mobilised drug". Copyright © 2011 Elsevier B.V. All rights reserved.
A study of MRI gradient echo signals from discrete magnetic particles with considerations of several parameters in simulations.

PubMed

Kokeny, Paul; Cheng, Yu-Chung N; Xie, He

2018-05-01

Modeling MRI signal behaviors in the presence of discrete magnetic particles is important, as magnetic particles appear in nanoparticle labeled cells, contrast agents, and other biological forms of iron. Currently, many models that take into account the discrete particle nature in a system have been used to predict magnitude signal decays in the form of R2* or R2' from one single voxel. Little work has been done for predicting phase signals. In addition, most calculations of phase signals rely on the assumption that a system containing discrete particles behaves as a continuous medium. In this work, numerical simulations are used to investigate MRI magnitude and phase signals from discrete particles, without diffusion effects. Factors such as particle size, number density, susceptibility, volume fraction, particle arrangements for their randomness, and field of view have been considered in simulations. The results are compared to either a ground truth model, theoretical work based on continuous mediums, or previous literature. Suitable parameters used to model particles in several voxels that lead to acceptable magnetic field distributions around particle surfaces and accurate MR signals are identified. The phase values as a function of echo time from a central voxel filled by particles can be significantly different from those of a continuous cubic medium. However, a completely random distribution of particles can lead to an R2' value which agrees with the prediction from the static dephasing theory. A sphere with a radius of at least 4 grid points used in simulations is found to be acceptable to generate MR signals equivalent from a larger sphere. Increasing number of particles with a fixed volume fraction in simulations reduces the resulting variance in the phase behavior, and converges to almost the same phase value for different particle numbers at each echo time. The variance of phase values is also reduced when increasing the number of particles in a fixed voxel. These results indicate that MRI signals from voxels containing discrete particles, even with a sufficient number of particles per voxel, cannot be properly modeled by a continuous medium with an equivalent susceptibility value in the voxel. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparison of region-of-interest-averaged and pixel-averaged analysis of DCE-MRI data based on simulations and pre-clinical experiments

NASA Astrophysics Data System (ADS)

He, Dianning; Zamora, Marta; Oto, Aytekin; Karczmar, Gregory S.; Fan, Xiaobing

2017-09-01

Differences between region-of-interest (ROI) and pixel-by-pixel analysis of dynamic contrast enhanced (DCE) MRI data were investigated in this study with computer simulations and pre-clinical experiments. ROIs were simulated with 10, 50, 100, 200, 400, and 800 different pixels. For each pixel, a contrast agent concentration as a function of time, C(t), was calculated using the Tofts DCE-MRI model with randomly generated physiological parameters (K trans and v e) and the Parker population arterial input function. The average C(t) for each ROI was calculated and then K trans and v e for the ROI was extracted. The simulations were run 100 times for each ROI with new K trans and v e generated. In addition, white Gaussian noise was added to C(t) with 3, 6, and 12 dB signal-to-noise ratios to each C(t). For pre-clinical experiments, Copenhagen rats (n = 6) with implanted prostate tumors in the hind limb were used in this study. The DCE-MRI data were acquired with a temporal resolution of ~5 s in a 4.7 T animal scanner, before, during, and after a bolus injection (<5 s) of Gd-DTPA for a total imaging duration of ~10 min. K trans and v e were calculated in two ways: (i) by fitting C(t) for each pixel, and then averaging the pixel values over the entire ROI, and (ii) by averaging C(t) over the entire ROI, and then fitting averaged C(t) to extract K trans and v e. The simulation results showed that in heterogeneous ROIs, the pixel-by-pixel averaged K trans was ~25% to ~50% larger (p < 0.01) than the ROI-averaged K trans. At higher noise levels, the pixel-averaged K trans was greater than the ‘true’ K trans, but the ROI-averaged K trans was lower than the ‘true’ K trans. The ROI-averaged K trans was closer to the true K trans than pixel-averaged K trans for high noise levels. In pre-clinical experiments, the pixel-by-pixel averaged K trans was ~15% larger than the ROI-averaged K trans. Overall, with the Tofts model, the extracted physiological parameters from the pixel-by-pixel averages were larger than the ROI averages. These differences were dependent on the heterogeneity of the ROI.
A Simulation Tool for Dynamic Contrast Enhanced MRI

PubMed Central

Mauconduit, Franck; Christen, Thomas; Barbier, Emmanuel Luc

2013-01-01

The quantification of bolus-tracking MRI techniques remains challenging. The acquisition usually relies on one contrast and the analysis on a simplified model of the various phenomena that arise within a voxel, leading to inaccurate perfusion estimates. To evaluate how simplifications in the interstitial model impact perfusion estimates, we propose a numerical tool to simulate the MR signal provided by a dynamic contrast enhanced (DCE) MRI experiment. Our model encompasses the intrinsic and relaxations, the magnetic field perturbations induced by susceptibility interfaces (vessels and cells), the diffusion of the water protons, the blood flow, the permeability of the vessel wall to the the contrast agent (CA) and the constrained diffusion of the CA within the voxel. The blood compartment is modeled as a uniform compartment. The different blocks of the simulation are validated and compared to classical models. The impact of the CA diffusivity on the permeability and blood volume estimates is evaluated. Simulations demonstrate that the CA diffusivity slightly impacts the permeability estimates ( for classical blood flow and CA diffusion). The effect of long echo times is investigated. Simulations show that DCE-MRI performed with an echo time may already lead to significant underestimation of the blood volume (up to 30% lower for brain tumor permeability values). The potential and the versatility of the proposed implementation are evaluated by running the simulation with realistic vascular geometry obtained from two photons microscopy and with impermeable cells in the extravascular environment. In conclusion, the proposed simulation tool describes DCE-MRI experiments and may be used to evaluate and optimize acquisition and processing strategies. PMID:23516414
DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu Zhaohuan; Stone, James M.; Rafikov, Roman R., E-mail: zhzhu@astro.princeton.edu, E-mail: jstone@astro.princeton.edu, E-mail: rrr@astro.princeton.edu

Some regions in protoplanetary disks are turbulent, while some regions are quiescent (e.g. the dead zone). In order to study how planets open gaps in both inviscid hydrodynamic disk (e.g. the dead zone) and the disk subject to magnetorotational instability (MRI), we carried out both shearing box two-dimensional inviscid hydrodynamical simulations and three-dimensional unstratified magnetohydrodynamical (MHD) simulations (having net vertical magnetic fields) with a planet at the box center. We found that, due to the nonlinear wave steepening, even a low mass planet can open gaps in both cases, in contradiction to the ''thermal criterion'' for gap opening. In ordermore » to understand if we can represent the MRI turbulent stress with the viscous {alpha} prescription for studying gap opening, we compare gap properties in MRI-turbulent disks to those in viscous HD disks having the same stress, and found that the same mass planet opens a significantly deeper and wider gap in net vertical flux MHD disks than in viscous HD disks. This difference arises due to the efficient magnetic field transport into the gap region in MRI disks, leading to a larger effective {alpha} within the gap. Thus, across the gap, the Maxwell stress profile is smoother than the gap density profile, and a deeper gap is needed for the Maxwell stress gradient to balance the planetary torque density. Comparison with previous results from net toroidal flux/zero flux MHD simulations indicates that the magnetic field geometry plays an important role in the gap opening process. We also found that long-lived density features (termed zonal flows) produced by the MRI can affect planet migration. Overall, our results suggest that gaps can be commonly produced by low mass planets in realistic protoplanetary disks, and caution the use of a constant {alpha}-viscosity to model gaps in protoplanetary disks.« less
Pressure-anisotropy-induced nonlinearities in the kinetic magnetorotational instability

NASA Astrophysics Data System (ADS)

Squire, J.; Quataert, E.; Kunz, M. W.

2017-12-01

In collisionless and weakly collisional plasmas, such as hot accretion flows onto compact objects, the magnetorotational instability (MRI) can differ significantly from the standard (collisional) MRI. In particular, pressure anisotropy with respect to the local magnetic-field direction can both change the linear MRI dispersion relation and cause nonlinear modifications to the mode structure and growth rate, even when the field and flow perturbations are very small. This work studies these pressure-anisotropy-induced nonlinearities in the weakly nonlinear, high-ion-beta regime, before the MRI saturates into strong turbulence. Our goal is to better understand how the saturation of the MRI in a low-collisionality plasma might differ from that in the collisional regime. We focus on two key effects: (i) the direct impact of self-induced pressure-anisotropy nonlinearities on the evolution of an MRI mode, and (ii) the influence of pressure anisotropy on the `parasitic instabilities' that are suspected to cause the mode to break up into turbulence. Our main conclusions are: (i) The mirror instability regulates the pressure anisotropy in such a way that the linear MRI in a collisionless plasma is an approximate nonlinear solution once the mode amplitude becomes larger than the background field (just as in magnetohyrodynamics). This implies that differences between the collisionless and collisional MRI become unimportant at large amplitudes. (ii) The break up of large-amplitude MRI modes into turbulence via parasitic instabilities is similar in collisionless and collisional plasmas. Together, these conclusions suggest that the route to magnetorotational turbulence in a collisionless plasma may well be similar to that in a collisional plasma, as suggested by recent kinetic simulations. As a supplement to these findings, we offer guidance for the design of future kinetic simulations of magnetorotational turbulence.
MRI-based hip cartilage measures in osteoarthritic and non-osteoarthritic individuals: a systematic review

PubMed Central

Aguilar, Hector N; Battié, Michele C

2017-01-01

Osteoarthritis is a common hip joint disease, involving loss of articular cartilage. The prevalence and prognosis of hip osteoarthritis have been difficult to determine, with various clinical and radiological methods used to derive epidemiological estimates exhibiting significant heterogeneity. MRI-based methods directly visualise hip joint cartilage, and offer potential to more reliably define presence and severity of osteoarthritis, but have been underused. We performed a systematic review of MRI-based estimates of hip articular cartilage in the general population and in patients with established osteoarthritis, using MEDLINE, EMBASE and SCOPUS current to June 2016, with search terms such as ‘hip’, ‘femoral head’, ‘cartilage’, ‘volume’, ‘thickness’, ‘MRI’, etc. Ultimately, 11 studies were found appropriate for inclusion, but they were heterogeneous in osteoarthritis assessment methodology and composition. Overall, the studies consistently demonstrate the reliability and potential clinical utility of MRI-based estimates. However, no longitudinal data or reference values for hip cartilage thickness or volume have been published, limiting the ability of MRI to define or risk-stratify hip osteoarthritis. MRI-based techniques are available to quantify articular cartilage signal, volume, thickness and defects, which could establish the sequence and rate of articular cartilage changes at the hip that yield symptomatic osteoarthritis. However, prevalence and rates of progression of hip osteoarthritis have not been established in any MRI studies in the general population. Future investigations could fill this important knowledge gap using robust MRI methods in population-based cross-sectional and longitudinal studies. PMID:28405471
SU-F-J-173: Online Replanning for Dose Painting Based On Changing ADC Map of Pancreas Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ates, O; Ahunbay, E; Erickson, B

Purpose: The introduction of MR-guided radiation therapy (RT), e.g., MR-Linac, would allow dose painting to adapt spatial RT response revealed from MRI data during the RT delivery. The purpose of this study is to investigate the use of an online replanning method to adapt dose painting from the MRI Apparent Diffusion Coefficient (ADC) map acquired during the delivery of RT for pancreatic cancers. Methods: Original dose painting plans were created based on multi-parametric simulation MRI including T1, T2 and ADC, using a treatment planning system (MONACO, Elekta) equipped with an online replanning algorithm (WSO, warm start optimization). Multiple GTVs, identifiedmore » based on various ADC levels were prescribed to different doses ranging from 50–70 Gy with simultaneous integrated boost in 28 fractions. The MRI acquired after RT were used to mimic weekly MRI, on which the changing GTVs, pancreatic head and other organs-at-risk (OAR) (duodenum, stomach, small bowel) were delineated. The adaptive plan was generated by applying WSO algorithm starting from the deformed original plan based on the weekly MRI using a deformable image registration (DIR) software (ADMIRE, Elekta). The online replanning method takes <10 min. including DIR, target delineation, WSO execution and final dose calculation. Standard IGRT repositioning and full-blown reoptimization plans were also generated to compare with the adaptive plans. Results: The online replanning method significantly improved the multiple target coverages and OAR sparing for pancreatic cancers. For example, for a case with two GTVs with prescriptions of 60 and 70 Gy in pancreatic head, V100-GTV70 (the volume covered by 100% of prescription dose for GTV with 70 Gy)/V100-GTV60/V100-CTV50/V45-duodenum were (95.1/22.2/69.5/85.7), (95.0/97.0/98.6/34.3), and (95.0/98.1/100.0/38.7) for the IGRT, adaptive and reoptimization plans, respectively. Conclusion: The introduced online adaptive replanning method can effectively account for interfractional changes including tumor spatial response during MR-guided RT delivery, allowing precise delivery of dose painting. This study was partially supported by Elekta Inc.« less
MRI-guided brain PET image filtering and partial volume correction

NASA Astrophysics Data System (ADS)

Yan, Jianhua; Chu-Shern Lim, Jason; Townsend, David W.

2015-02-01

Positron emission tomography (PET) image quantification is a challenging problem due to limited spatial resolution of acquired data and the resulting partial volume effects (PVE), which depend on the size of the structure studied in relation to the spatial resolution and which may lead to over or underestimation of the true tissue tracer concentration. In addition, it is usually necessary to perform image smoothing either during image reconstruction or afterwards to achieve a reasonable signal-to-noise ratio. Typically, an isotropic Gaussian filtering (GF) is used for this purpose. However, the noise suppression is at the cost of deteriorating spatial resolution. As hybrid imaging devices such as PET/MRI have become available, the complementary information derived from high definition morphologic images could be used to improve the quality of PET images. In this study, first of all, we propose an MRI-guided PET filtering method by adapting a recently proposed local linear model and then incorporate PVE into the model to get a new partial volume correction (PVC) method without parcellation of MRI. In addition, both the new filtering and PVC are voxel-wise non-iterative methods. The performance of the proposed methods were investigated with simulated dynamic FDG brain dataset and 18F-FDG brain data of a cervical cancer patient acquired with a simultaneous hybrid PET/MR scanner. The initial simulation results demonstrated that MRI-guided PET image filtering can produce less noisy images than traditional GF and bias and coefficient of variation can be further reduced by MRI-guided PET PVC. Moreover, structures can be much better delineated in MRI-guided PET PVC for real brain data.
Preclinical evaluation of implantable cardioverter-defibrillator developed for magnetic resonance imaging use.

PubMed

Gold, Michael R; Kanal, Emanuel; Schwitter, Juerg; Sommer, Torsten; Yoon, Hyun; Ellingson, Michael; Landborg, Lynn; Bratten, Tara

2015-03-01

Many patients with an implantable cardioverter-defibrillator (ICD) have indications for magnetic resonance imaging (MRI). However, MRI is generally contraindicated in ICD patients because of potential risks from hazardous interactions between the MRI and ICD system. The purpose of this study was to use preclinical computer modeling, animal studies, and bench and scanner testing to demonstrate the safety of an ICD system developed for 1.5-T whole-body MRI. MRI hazards were assessed and mitigated using multiple approaches: design decisions to increase safety and reliability, modeling and simulation to quantify clinical MRI exposure levels, animal studies to quantify the physiologic effects of MRI exposure, and bench testing to evaluate safety margin. Modeling estimated the incidence of a chronic change in pacing capture threshold >0.5 V and 1.0 V to be less than 1 in 160,000 and less than 1 in 1,000,000 cases, respectively. Modeling also estimated the incidence of unintended cardiac stimulation to occur in less than 1 in 1,000,000 cases. Animal studies demonstrated no delay in ventricular fibrillation detection and no reduction in ventricular fibrillation amplitude at clinical MRI exposure levels, even with multiple exposures. Bench and scanner testing demonstrated performance and safety against all other MRI-induced hazards. A preclinical strategy that includes comprehensive computer modeling, animal studies, and bench and scanner testing predicts that an ICD system developed for the magnetic resonance environment is safe and poses very low risks when exposed to 1.5-T normal operating mode whole-body MRI. Copyright © 2015 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.
Modelling passive diastolic mechanics with quantitative MRI of cardiac structure and function.

PubMed

Wang, Vicky Y; Lam, H I; Ennis, Daniel B; Cowan, Brett R; Young, Alistair A; Nash, Martyn P

2009-10-01

The majority of patients with clinically diagnosed heart failure have normal systolic pump function and are commonly categorized as suffering from diastolic heart failure. The left ventricle (LV) remodels its structure and function to adapt to pathophysiological changes in geometry and loading conditions, which in turn can alter the passive ventricular mechanics. In order to better understand passive ventricular mechanics, a LV finite element (FE) model was customized to geometric data segmented from in vivo tagged magnetic resonance images (MRI) data and myofibre orientation derived from ex vivo diffusion tensor MRI (DTMRI) of a canine heart using nonlinear finite element fitting techniques. MRI tissue tagging enables quantitative evaluation of cardiac mechanical function with high spatial and temporal resolution, whilst the direction of maximum water diffusion in each voxel of a DTMRI directly corresponds to the local myocardial fibre orientation. Due to differences in myocardial geometry between in vivo and ex vivo imaging, myofibre orientations were mapped into the geometric FE model using host mesh fitting (a free form deformation technique). Pressure recordings, temporally synchronized to the tagging data, were used as the loading constraints to simulate the LV deformation during diastole. Simulation of diastolic LV mechanics allowed us to estimate the stiffness of the passive LV myocardium based on kinematic data obtained from tagged MRI. Integrated physiological modelling of this kind will allow more insight into mechanics of the LV on an individualized basis, thereby improving our understanding of the underlying structural basis of mechanical dysfunction under pathological conditions.
Compressively sampled MR image reconstruction using generalized thresholding iterative algorithm

NASA Astrophysics Data System (ADS)

Elahi, Sana; kaleem, Muhammad; Omer, Hammad

2018-01-01

Compressed sensing (CS) is an emerging area of interest in Magnetic Resonance Imaging (MRI). CS is used for the reconstruction of the images from a very limited number of samples in k-space. This significantly reduces the MRI data acquisition time. One important requirement for signal recovery in CS is the use of an appropriate non-linear reconstruction algorithm. It is a challenging task to choose a reconstruction algorithm that would accurately reconstruct the MR images from the under-sampled k-space data. Various algorithms have been used to solve the system of non-linear equations for better image quality and reconstruction speed in CS. In the recent past, iterative soft thresholding algorithm (ISTA) has been introduced in CS-MRI. This algorithm directly cancels the incoherent artifacts produced because of the undersampling in k -space. This paper introduces an improved iterative algorithm based on p -thresholding technique for CS-MRI image reconstruction. The use of p -thresholding function promotes sparsity in the image which is a key factor for CS based image reconstruction. The p -thresholding based iterative algorithm is a modification of ISTA, and minimizes non-convex functions. It has been shown that the proposed p -thresholding iterative algorithm can be used effectively to recover fully sampled image from the under-sampled data in MRI. The performance of the proposed method is verified using simulated and actual MRI data taken at St. Mary's Hospital, London. The quality of the reconstructed images is measured in terms of peak signal-to-noise ratio (PSNR), artifact power (AP), and structural similarity index measure (SSIM). The proposed approach shows improved performance when compared to other iterative algorithms based on log thresholding, soft thresholding and hard thresholding techniques at different reduction factors.
Population-based respiratory 4D motion atlas construction and its application for VR simulations of liver punctures

NASA Astrophysics Data System (ADS)

Mastmeyer, Andre; Wilms, Matthias; Handels, Heinz

2018-03-01

Virtual reality (VR) training simulators of liver needle insertion in the hepatic area of breathing virtual patients often need 4D image data acquisitions as a prerequisite. Here, first a population-based breathing virtual patient 4D atlas is built and second the requirement of a dose-relevant or expensive acquisition of a 4D CT or MRI data set for a new patient can be mitigated by warping the mean atlas motion. The breakthrough contribution of this work is the construction and reuse of population-based, learned 4D motion models.
Comparing brain graphs in which nodes are regions of interest or independent components: A simulation study.

PubMed

Yu, Qingbao; Du, Yuhui; Chen, Jiayu; He, Hao; Sui, Jing; Pearlson, Godfrey; Calhoun, Vince D

2017-11-01

A key challenge in building a brain graph using fMRI data is how to define the nodes. Spatial brain components estimated by independent components analysis (ICA) and regions of interest (ROIs) determined by brain atlas are two popular methods to define nodes in brain graphs. It is difficult to evaluate which method is better in real fMRI data. Here we perform a simulation study and evaluate the accuracies of a few graph metrics in graphs with nodes of ICA components, ROIs, or modified ROIs in four simulation scenarios. Graph measures with ICA nodes are more accurate than graphs with ROI nodes in all cases. Graph measures with modified ROI nodes are modulated by artifacts. The correlations of graph metrics across subjects between graphs with ICA nodes and ground truth are higher than the correlations between graphs with ROI nodes and ground truth in scenarios with large overlapped spatial sources. Moreover, moving the location of ROIs would largely decrease the correlations in all scenarios. Evaluating graphs with different nodes is promising in simulated data rather than real data because different scenarios can be simulated and measures of different graphs can be compared with a known ground truth. Since ROIs defined using brain atlas may not correspond well to real functional boundaries, overall findings of this work suggest that it is more appropriate to define nodes using data-driven ICA than ROI approaches in real fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.
Evaluation of the impact of carotid artery bifurcation angle on hemodynamics by use of computational fluid dynamics: a simulation and volunteer study.

PubMed

Saho, Tatsunori; Onishi, Hideo

2016-07-01

In this study, we evaluated the hemodynamics of carotid artery bifurcation with various geometries using simulated and volunteer models based on magnetic resonance imaging (MRI). Computational fluid dynamics (CFD) was analyzed by use of OpenFOAM. The velocity distribution, streamline, and wall shear stress (WSS) were evaluated in a simulated model with known bifurcation angles (30°, 40°, 50°, 60°, derived from patients' data) and in three-dimensional (3D) healthy volunteer models. Separated flow was observed at the outer side of the bifurcation, and large bifurcation models represented upstream transfer of the point. Local WSS values at the outer bifurcation [both simulated (<30 Pa) and volunteer (<50 Pa) models] were lower than those in the inner region (>100 Pa). The bifurcation angle had a significant negative correlation with the WSS value (p<0.05). The results of this study show that the carotid artery bifurcation angle is related to the WSS value. This suggests that hemodynamic stress can be estimated based on the carotid artery geometry. The construction of a clinical database for estimation of developing atherosclerosis is warranted.
T2-weighted four dimensional magnetic resonance imaging with result-driven phase sorting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yilin; Yin, Fang-Fang; Cai, Jing, E-mail: jing.cai@duke.edu

2015-08-15

Purpose: T2-weighted MRI provides excellent tumor-to-tissue contrast for target volume delineation in radiation therapy treatment planning. This study aims at developing a novel T2-weighted retrospective four dimensional magnetic resonance imaging (4D-MRI) phase sorting technique for imaging organ/tumor respiratory motion. Methods: A 2D fast T2-weighted half-Fourier acquisition single-shot turbo spin-echo MR sequence was used for image acquisition of 4D-MRI, with a frame rate of 2–3 frames/s. Respiratory motion was measured using an external breathing monitoring device. A phase sorting method was developed to sort the images by their corresponding respiratory phases. Besides, a result-driven strategy was applied to effectively utilize redundantmore » images in the case when multiple images were allocated to a bin. This strategy, selecting the image with minimal amplitude error, will generate the most representative 4D-MRI. Since we are using a different image acquisition mode for 4D imaging (the sequential image acquisition scheme) with the conventionally used cine or helical image acquisition scheme, the 4D dataset sufficient condition was not obviously and directly predictable. An important challenge of the proposed technique was to determine the number of repeated scans (N{sub R}) required to obtain sufficient phase information at each slice position. To tackle this challenge, the authors first conducted computer simulations using real-time position management respiratory signals of the 29 cancer patients under an IRB-approved retrospective study to derive the relationships between N{sub R} and the following factors: number of slices (N{sub S}), number of 4D-MRI respiratory bins (N{sub B}), and starting phase at image acquisition (P{sub 0}). To validate the authors’ technique, 4D-MRI acquisition and reconstruction were simulated on a 4D digital extended cardiac-torso (XCAT) human phantom using simulation derived parameters. Twelve healthy volunteers were involved in an IRB-approved study to investigate the feasibility of this technique. Results: 4D data acquisition completeness (C{sub p}) increases as NR increases in an inverse-exponential fashion (C{sub p} = 100 − 99 × exp(−0.18 × N{sub R}), when N{sub B} = 6, fitted using 29 patients’ data). The N{sub R} required for 4D-MRI reconstruction (defined as achieving 95% completeness, C{sub p} = 95%, N{sub R} = N{sub R,95}) is proportional to N{sub B} (N{sub R,95} ∼ 2.86 × N{sub B}, r = 1.0), but independent of N{sub S} and P{sub 0}. Simulated XCAT 4D-MRI showed a clear pattern of respiratory motion. Tumor motion trajectories measured on 4D-MRI were comparable to the average input signal, with a mean relative amplitude error of 2.7% ± 2.9%. Reconstructed 4D-MRI for healthy volunteers illustrated clear respiratory motion on three orthogonal planes, with minimal image artifacts. The artifacts were presumably caused by breathing irregularity and incompleteness of data acquisition (95% acquired only). The mean relative amplitude error between critical structure trajectory and average breathing curve for 12 healthy volunteers is 2.5 ± 0.3 mm in superior–inferior direction. Conclusions: A novel T2-weighted retrospective phase sorting 4D-MRI technique has been developed and successfully applied on digital phantom and healthy volunteers.« less
Identifying effective connectivity parameters in simulated fMRI: a direct comparison of switching linear dynamic system, stochastic dynamic causal, and multivariate autoregressive models

PubMed Central

Smith, Jason F.; Chen, Kewei; Pillai, Ajay S.; Horwitz, Barry

2013-01-01

The number and variety of connectivity estimation methods is likely to continue to grow over the coming decade. Comparisons between methods are necessary to prune this growth to only the most accurate and robust methods. However, the nature of connectivity is elusive with different methods potentially attempting to identify different aspects of connectivity. Commonalities of connectivity definitions across methods upon which base direct comparisons can be difficult to derive. Here, we explicitly define “effective connectivity” using a common set of observation and state equations that are appropriate for three connectivity methods: dynamic causal modeling (DCM), multivariate autoregressive modeling (MAR), and switching linear dynamic systems for fMRI (sLDSf). In addition while deriving this set, we show how many other popular functional and effective connectivity methods are actually simplifications of these equations. We discuss implications of these connections for the practice of using one method to simulate data for another method. After mathematically connecting the three effective connectivity methods, simulated fMRI data with varying numbers of regions and task conditions is generated from the common equation. This simulated data explicitly contains the type of the connectivity that the three models were intended to identify. Each method is applied to the simulated data sets and the accuracy of parameter identification is analyzed. All methods perform above chance levels at identifying correct connectivity parameters. The sLDSf method was superior in parameter estimation accuracy to both DCM and MAR for all types of comparisons. PMID:23717258
Extraction of temporal information in functional MRI

NASA Astrophysics Data System (ADS)

Singh, M.; Sungkarat, W.; Jeong, Jeong-Won; Zhou, Yongxia

2002-10-01

The temporal resolution of functional MRI (fMRI) is limited by the shape of the haemodynamic response function (hrf) and the vascular architecture underlying the activated regions. Typically, the temporal resolution of fMRI is on the order of 1 s. We have developed a new data processing approach to extract temporal information on a pixel-by-pixel basis at the level of 100 ms from fMRI data. Instead of correlating or fitting the time-course of each pixel to a single reference function, which is the common practice in fMRI, we correlate each pixel's time-course to a series of reference functions that are shifted with respect to each other by 100 ms. The reference function yielding the highest correlation coefficient for a pixel is then used as a time marker for that pixel. A Monte Carlo simulation and experimental study of this approach were performed to estimate the temporal resolution as a function of signal-to-noise ratio (SNR) in the time-course of a pixel. Assuming a known and stationary hrf, the simulation and experimental studies suggest a lower limit in the temporal resolution of approximately 100 ms at an SNR of 3. The multireference function approach was also applied to extract timing information from an event-related motor movement study where the subjects flexed a finger on cue. The event was repeated 19 times with the event's presentation staggered to yield an approximately 100-ms temporal sampling of the haemodynamic response over the entire presentation cycle. The timing differences among different regions of the brain activated by the motor task were clearly visualized and quantified by this method. The results suggest that it is possible to achieve a temporal resolution of /spl sim/200 ms in practice with this approach.
Surface-Based fMRI-Driven Diffusion Tractography in the Presence of Significant Brain Pathology: A Study Linking Structure and Function in Cerebral Palsy

PubMed Central

Cunnington, Ross; Boyd, Roslyn N.; Rose, Stephen E.

2016-01-01

Diffusion MRI (dMRI) tractography analyses are difficult to perform in the presence of brain pathology. Automated methods that rely on cortical parcellation for structural connectivity studies often fail, while manually defining regions is extremely time consuming and can introduce human error. Both methods also make assumptions about structure-function relationships that may not hold after cortical reorganisation. Seeding tractography with functional-MRI (fMRI) activation is an emerging method that reduces these confounds, but inherent smoothing of fMRI signal may result in the inclusion of irrelevant pathways. This paper describes a novel fMRI-seeded dMRI-analysis pipeline based on surface-meshes that reduces these issues and utilises machine-learning to generate task specific white matter pathways, minimising the requirement for manually-drawn ROIs. We directly compared this new strategy to a standard voxelwise fMRI-dMRI approach, by investigating correlations between clinical scores and dMRI metrics of thalamocortical and corticomotor tracts in 31 children with unilateral cerebral palsy. The surface-based approach successfully processed more participants (87%) than the voxel-based approach (65%), and provided significantly more-coherent tractography. Significant correlations between dMRI metrics and five clinical scores of function were found for the more superior regions of these tracts. These significant correlations were stronger and more frequently found with the surface-based method (15/20 investigated were significant; R2 = 0.43–0.73) than the voxelwise analysis (2 sig. correlations; 0.38 & 0.49). More restricted fMRI signal, better-constrained tractography, and the novel track-classification method all appeared to contribute toward these differences. PMID:27487011
Time-frequency dynamics of resting-state brain connectivity measured with fMRI.

PubMed

Chang, Catie; Glover, Gary H

2010-03-01

Most studies of resting-state functional connectivity using fMRI employ methods that assume temporal stationarity, such as correlation and data-driven decompositions computed across the duration of the scan. However, evidence from both task-based fMRI studies and animal electrophysiology suggests that functional connectivity may exhibit dynamic changes within time scales of seconds to minutes. In the present study, we investigated the dynamic behavior of resting-state connectivity across the course of a single scan, performing a time-frequency coherence analysis based on the wavelet transform. We focused on the connectivity of the posterior cingulate cortex (PCC), a primary node of the default-mode network, examining its relationship with both the "anticorrelated" ("task-positive") network as well as other nodes of the default-mode network. It was observed that coherence and phase between the PCC and the anticorrelated network was variable in time and frequency, and statistical testing based on Monte Carlo simulations revealed the presence of significant scale-dependent temporal variability. In addition, a sliding-window correlation procedure identified other regions across the brain that exhibited variable connectivity with the PCC across the scan, which included areas previously implicated in attention and salience processing. Although it is unclear whether the observed coherence and phase variability can be attributed to residual noise or modulation of cognitive state, the present results illustrate that resting-state functional connectivity is not static, and it may therefore prove valuable to consider measures of variability, in addition to average quantities, when characterizing resting-state networks. Copyright (c) 2009 Elsevier Inc. All rights reserved.
Initial Validation for the Estimation of Resting-State fMRI Effective Connectivity by a Generalization of the Correlation Approach

PubMed Central

Xu, Nan; Spreng, R. Nathan; Doerschuk, Peter C.

2017-01-01

Resting-state functional MRI (rs-fMRI) is widely used to noninvasively study human brain networks. Network functional connectivity is often estimated by calculating the timeseries correlation between blood-oxygen-level dependent (BOLD) signal from different regions of interest (ROIs). However, standard correlation cannot characterize the direction of information flow between regions. In this paper, we introduce and test a new concept, prediction correlation, to estimate effective connectivity in functional brain networks from rs-fMRI. In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal system driven by another BOLD signal. Three validations are described: (1) Prediction correlation performed well on simulated data where the ground truth was known, and outperformed four other methods. (2) On simulated data designed to display the “common driver” problem, prediction correlation did not introduce false connections between non-interacting driven ROIs. (3) On experimental data, prediction correlation recovered the previously identified network organization of human brain. Prediction correlation scales well to work with hundreds of ROIs, enabling it to assess whole brain interregional connectivity at the single subject level. These results provide an initial validation that prediction correlation can capture the direction of information flow and estimate the duration of extended temporal delays in information flow between regions of interest ROIs based on BOLD signal. This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also performs well in the estimation of causal information flow in the brain. PMID:28559793
SU-F-P-26: Study of Radiation Dose Evaluation for Organs at Risk Using MRI in Intensity Modulated Radiation Therapy for Nasopharyngeal Carcinoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gong, G; Guo, Y; Yin, Y

Purpose: To study the contour and dosimetric feature of organs at risk (OARs) applying magnetic resonance imaging (MRI) images in intensity modulated radiation therapy (IMRT) of nasopharyngeal carcinoma (NPC) compared to computed tomography (CT) images. Methods: 35 NPC patients was selected into this trail. CT simulation with non-contrast and contrast enhanced scan, MRI simulation with non-contrast and contrast enhanced T1, T2 and diffusion weighted imaging were achieved sequentially. And the OARs were contoured on the CT and MRI images after rigid registration respectively. 9 beams IMRT plan with equal division angle were designed for every patients, and the prescription dosemore » for tumor target was set as 72Gy (2.4Gy/ fration). The boundary display, volume and dose-volume indices of each organ were compared between on MRI and CT images. Results: Compared to CT, MRI showed clearer boundary of brainstem, spinal cord, the deep lobe of Parotid gland and the optical nerve in canal. MRI images increase the volume of lens, optical nerve, while reducing the volume of eye slightly, and the maximum dose of lens, the mean dose of eyes and optical raised in different percentage, while there was no statistical differences were found. The left and right parotid volume on MRI increased by 7.07%, 8.13%, and the mean dose raised by 14.95% (4.01Gy), 18.76% (4.95Gy) with statistical significant difference (p<0.05). The brainstem volume reduced by 9.33% (p<0.05), and the dose of 0.1cm3 volume (D0.1cm3) reduced by mean 8.46% (4.32Gy), and D0.1cm3 of spinal cord increased by 1.5Gy on MRI. Conclusion: It is credible to evaluate the radiation dose of lens, eye and the spinal cord, while it should be necessary to evaluate the dose of brainstem, parotid and the optical nerve applying MRI images sometime, it will be more meaningful for these organs with high risk of radiation injury.« less

MR Imaging Based Treatment Planning for Radiotherapy of Prostate Cancer

DTIC Science & Technology

2008-02-01

Radiotherapy, MR-based treatment planning, dosimetry, Monte Carlo dose verification, Prostate Cancer, MRI -based DRRs 16. SECURITY CLASSIFICATION...AcQPlan system Version 5 was used for the study , which is capable of performing dose calculation on both CT and MRI . A four field 3D conformal planning...prostate motion studies for 3DCRT and IMRT of prostate cancer; (2) to investigate and improve the accuracy of MRI -based treatment planning dose calculation
Spatio-temporal models of mental processes from fMRI.

PubMed

Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos

2011-07-15

Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed. Copyright © 2011 Elsevier Inc. All rights reserved.
A theoretical framework for determining cerebral vascular function and heterogeneity from dynamic susceptibility contrast MRI.

PubMed

Digernes, Ingrid; Bjørnerud, Atle; Vatnehol, Svein Are S; Løvland, Grete; Courivaud, Frédéric; Vik-Mo, Einar; Meling, Torstein R; Emblem, Kyrre E

2017-06-01

Mapping the complex heterogeneity of vascular tissue in the brain is important for understanding cerebrovascular disease. In this translational study, we build on previous work using vessel architectural imaging (VAI) and present a theoretical framework for determining cerebral vascular function and heterogeneity from dynamic susceptibility contrast magnetic resonance imaging (MRI). Our tissue model covers realistic structural architectures for vessel branching and orientations, as well as a range of hemodynamic scenarios for blood flow, capillary transit times and oxygenation. In a typical image voxel, our findings show that the apparent MRI relaxation rates are independent of the mean vessel orientation and that the vortex area, a VAI-based parameter, is determined by the relative oxygen saturation level and the vessel branching of the tissue. Finally, in both simulated and patient data, we show that the relative distributions of the vortex area parameter as a function of capillary transit times show unique characteristics in normal-appearing white and gray matter tissue, whereas tumour-voxels in comparison display a heterogeneous distribution. Collectively, our study presents a comprehensive framework that may serve as a roadmap for in vivo and per-voxel determination of vascular status and heterogeneity in cerebral tissue.
Multiple imputation of missing fMRI data in whole brain analysis

PubMed Central

Vaden, Kenneth I.; Gebregziabher, Mulugeta; Kuchinsky, Stefanie E.; Eckert, Mark A.

2012-01-01

Whole brain fMRI analyses rarely include the entire brain because of missing data that result from data acquisition limits and susceptibility artifact, in particular. This missing data problem is typically addressed by omitting voxels from analysis, which may exclude brain regions that are of theoretical interest and increase the potential for Type II error at cortical boundaries or Type I error when spatial thresholds are used to establish significance. Imputation could significantly expand statistical map coverage, increase power, and enhance interpretations of fMRI results. We examined multiple imputation for group level analyses of missing fMRI data using methods that leverage the spatial information in fMRI datasets for both real and simulated data. Available case analysis, neighbor replacement, and regression based imputation approaches were compared in a general linear model framework to determine the extent to which these methods quantitatively (effect size) and qualitatively (spatial coverage) increased the sensitivity of group analyses. In both real and simulated data analysis, multiple imputation provided 1) variance that was most similar to estimates for voxels with no missing data, 2) fewer false positive errors in comparison to mean replacement, and 3) fewer false negative errors in comparison to available case analysis. Compared to the standard analysis approach of omitting voxels with missing data, imputation methods increased brain coverage in this study by 35% (from 33,323 to 45,071 voxels). In addition, multiple imputation increased the size of significant clusters by 58% and number of significant clusters across statistical thresholds, compared to the standard voxel omission approach. While neighbor replacement produced similar results, we recommend multiple imputation because it uses an informed sampling distribution to deal with missing data across subjects that can include neighbor values and other predictors. Multiple imputation is anticipated to be particularly useful for 1) large fMRI data sets with inconsistent missing voxels across subjects and 2) addressing the problem of increased artifact at ultra-high field, which significantly limit the extent of whole brain coverage and interpretations of results. PMID:22500925
High performance MRI simulations of motion on multi-GPU systems.

PubMed

Xanthis, Christos G; Venetis, Ioannis E; Aletras, Anthony H

2014-07-04

MRI physics simulators have been developed in the past for optimizing imaging protocols and for training purposes. However, these simulators have only addressed motion within a limited scope. The purpose of this study was the incorporation of realistic motion, such as cardiac motion, respiratory motion and flow, within MRI simulations in a high performance multi-GPU environment. Three different motion models were introduced in the Magnetic Resonance Imaging SIMULator (MRISIMUL) of this study: cardiac motion, respiratory motion and flow. Simulation of a simple Gradient Echo pulse sequence and a CINE pulse sequence on the corresponding anatomical model was performed. Myocardial tagging was also investigated. In pulse sequence design, software crushers were introduced to accommodate the long execution times in order to avoid spurious echoes formation. The displacement of the anatomical model isochromats was calculated within the Graphics Processing Unit (GPU) kernel for every timestep of the pulse sequence. Experiments that would allow simulation of custom anatomical and motion models were also performed. Last, simulations of motion with MRISIMUL on single-node and multi-node multi-GPU systems were examined. Gradient Echo and CINE images of the three motion models were produced and motion-related artifacts were demonstrated. The temporal evolution of the contractility of the heart was presented through the application of myocardial tagging. Better simulation performance and image quality were presented through the introduction of software crushers without the need to further increase the computational load and GPU resources. Last, MRISIMUL demonstrated an almost linear scalable performance with the increasing number of available GPU cards, in both single-node and multi-node multi-GPU computer systems. MRISIMUL is the first MR physics simulator to have implemented motion with a 3D large computational load on a single computer multi-GPU configuration. The incorporation of realistic motion models, such as cardiac motion, respiratory motion and flow may benefit the design and optimization of existing or new MR pulse sequences, protocols and algorithms, which examine motion related MR applications.
Assessment of dosimetric impact of system specific geometric distortion in an MRI only based radiotherapy workflow for prostate

NASA Astrophysics Data System (ADS)

Gustafsson, C.; Nordström, F.; Persson, E.; Brynolfsson, J.; Olsson, L. E.

2017-04-01

Dosimetric errors in a magnetic resonance imaging (MRI) only radiotherapy workflow may be caused by system specific geometric distortion from MRI. The aim of this study was to evaluate the impact on planned dose distribution and delineated structures for prostate patients, originating from this distortion. A method was developed, in which computer tomography (CT) images were distorted using the MRI distortion field. The displacement map for an optimized MRI treatment planning sequence was measured using a dedicated phantom in a 3 T MRI system. To simulate the distortion aspects of a synthetic CT (electron density derived from MR images), the displacement map was applied to CT images, referred to as distorted CT images. A volumetric modulated arc prostate treatment plan was applied to the original CT and the distorted CT, creating a reference and a distorted CT dose distribution. By applying the inverse of the displacement map to the distorted CT dose distribution, a dose distribution in the same geometry as the original CT images was created. For 10 prostate cancer patients, the dose difference between the reference dose distribution and inverse distorted CT dose distribution was analyzed in isodose level bins. The mean magnitude of the geometric distortion was 1.97 mm for the radial distance of 200-250 mm from isocenter. The mean percentage dose differences for all isodose level bins, were ⩽0.02% and the radiotherapy structure mean volume deviations were <0.2%. The method developed can quantify the dosimetric effects of MRI system specific distortion in a prostate MRI only radiotherapy workflow, separated from dosimetric effects originating from synthetic CT generation. No clinically relevant dose difference or structure deformation was found when 3D distortion correction and high acquisition bandwidth was used. The method could be used for any MRI sequence together with any anatomy of interest.
Assessment of dosimetric impact of system specific geometric distortion in an MRI only based radiotherapy workflow for prostate.

PubMed

Gustafsson, C; Nordström, F; Persson, E; Brynolfsson, J; Olsson, L E

2017-04-21

Dosimetric errors in a magnetic resonance imaging (MRI) only radiotherapy workflow may be caused by system specific geometric distortion from MRI. The aim of this study was to evaluate the impact on planned dose distribution and delineated structures for prostate patients, originating from this distortion. A method was developed, in which computer tomography (CT) images were distorted using the MRI distortion field. The displacement map for an optimized MRI treatment planning sequence was measured using a dedicated phantom in a 3 T MRI system. To simulate the distortion aspects of a synthetic CT (electron density derived from MR images), the displacement map was applied to CT images, referred to as distorted CT images. A volumetric modulated arc prostate treatment plan was applied to the original CT and the distorted CT, creating a reference and a distorted CT dose distribution. By applying the inverse of the displacement map to the distorted CT dose distribution, a dose distribution in the same geometry as the original CT images was created. For 10 prostate cancer patients, the dose difference between the reference dose distribution and inverse distorted CT dose distribution was analyzed in isodose level bins. The mean magnitude of the geometric distortion was 1.97 mm for the radial distance of 200-250 mm from isocenter. The mean percentage dose differences for all isodose level bins, were ⩽0.02% and the radiotherapy structure mean volume deviations were <0.2%. The method developed can quantify the dosimetric effects of MRI system specific distortion in a prostate MRI only radiotherapy workflow, separated from dosimetric effects originating from synthetic CT generation. No clinically relevant dose difference or structure deformation was found when 3D distortion correction and high acquisition bandwidth was used. The method could be used for any MRI sequence together with any anatomy of interest.
Spatial Precision in Magnetic Resonance Imaging–Guided Radiation Therapy: The Role of Geometric Distortion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weygand, Joseph, E-mail: jw2899@columbia.edu; The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, Texas; Fuller, Clifton David

2016-07-15

Because magnetic resonance imaging–guided radiation therapy (MRIgRT) offers exquisite soft tissue contrast and the ability to image tissues in arbitrary planes, the interest in this technology has increased dramatically in recent years. However, intrinsic geometric distortion stemming from both the system hardware and the magnetic properties of the patient affects MR images and compromises the spatial integrity of MRI-based radiation treatment planning, given that for real-time MRIgRT, precision within 2 mm is desired. In this article, we discuss the causes of geometric distortion, describe some well-known distortion correction algorithms, and review geometric distortion measurements from 12 studies, while taking into accountmore » relevant imaging parameters. Eleven of the studies reported phantom measurements quantifying system-dependent geometric distortion, while 2 studies reported simulation data quantifying magnetic susceptibility–induced geometric distortion. Of the 11 studies investigating system-dependent geometric distortion, 5 reported maximum measurements less than 2 mm. The simulation studies demonstrated that magnetic susceptibility–induced distortion is typically smaller than system-dependent distortion but still nonnegligible, with maximum distortion ranging from 2.1 to 2.6 mm at a field strength of 1.5 T. As expected, anatomic landmarks containing interfaces between air and soft tissue had the largest distortions. The evidence indicates that geometric distortion reduces the spatial integrity of MRI-based radiation treatment planning and likely diminishes the efficacy of MRIgRT. Better phantom measurement techniques and more effective distortion correction algorithms are needed to achieve the desired spatial precision.« less
TH-EF-BRA-08: A Novel Technique for Estimating Volumetric Cine MRI (VC-MRI) From Multi-Slice Sparsely Sampled Cine Images Using Motion Modeling and Free Form Deformation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, W; Yin, F; Wang, C

Purpose: To develop a technique to estimate on-board VC-MRI using multi-slice sparsely-sampled cine images, patient prior 4D-MRI, motion-modeling and free-form deformation for real-time 3D target verification of lung radiotherapy. Methods: A previous method has been developed to generate on-board VC-MRI by deforming prior MRI images based on a motion model(MM) extracted from prior 4D-MRI and a single-slice on-board 2D-cine image. In this study, free-form deformation(FD) was introduced to correct for errors in the MM when large anatomical changes exist. Multiple-slice sparsely-sampled on-board 2D-cine images located within the target are used to improve both the estimation accuracy and temporal resolution ofmore » VC-MRI. The on-board 2D-cine MRIs are acquired at 20–30frames/s by sampling only 10% of the k-space on Cartesian grid, with 85% of that taken at the central k-space. The method was evaluated using XCAT(computerized patient model) simulation of lung cancer patients with various anatomical and respirational changes from prior 4D-MRI to onboard volume. The accuracy was evaluated using Volume-Percent-Difference(VPD) and Center-of-Mass-Shift(COMS) of the estimated tumor volume. Effects of region-of-interest(ROI) selection, 2D-cine slice orientation, slice number and slice location on the estimation accuracy were evaluated. Results: VCMRI estimated using 10 sparsely-sampled sagittal 2D-cine MRIs achieved VPD/COMS of 9.07±3.54%/0.45±0.53mm among all scenarios based on estimation with ROI-MM-ROI-FD. The FD optimization improved estimation significantly for scenarios with anatomical changes. Using ROI-FD achieved better estimation than global-FD. Changing the multi-slice orientation to axial, coronal, and axial/sagittal orthogonal reduced the accuracy of VCMRI to VPD/COMS of 19.47±15.74%/1.57±2.54mm, 20.70±9.97%/2.34±0.92mm, and 16.02±13.79%/0.60±0.82mm, respectively. Reducing the number of cines to 8 enhanced temporal resolution of VC-MRI by 25% while maintaining the estimation accuracy. Estimation using slices sampled uniformly through the tumor achieved better accuracy than slices sampled non-uniformly. Conclusions: Preliminary studies showed that it is feasible to generate VC-MRI from multi-slice sparsely-sampled 2D-cine images for real-time 3D-target verification. This work was supported by the National Institutes of Health under Grant No. R01-CA184173 and a research grant from Varian Medical Systems.« less
Multistability of the Brain Network for Self-other Processing

PubMed Central

Chen, Yi-An; Huang, Tsung-Ren

2017-01-01

Early fMRI studies suggested that brain areas processing self-related and other-related information were highly overlapping. Hypothesising functional localisation of the cortex, researchers have tried to locate “self-specific” and “other-specific” regions within these overlapping areas by subtracting suspected confounding signals in task-based fMRI experiments. Inspired by recent advances in whole-brain dynamic modelling, we instead explored an alternative hypothesis that similar spatial activation patterns could be associated with different processing modes in the form of different synchronisation patterns. Combining an automated synthesis of fMRI data with a presumption-free diffusion spectrum image (DSI) fibre-tracking algorithm, we isolated a network putatively composed of brain areas and white matter tracts involved in self-other processing. We sampled synchronisation patterns from the dynamical systems of this network using various combinations of physiological parameters. Our results showed that the self-other processing network, with simulated gamma-band activity, tended to stabilise at a number of distinct synchronisation patterns. This phenomenon, termed “multistability,” could serve as an alternative model in theorising the mechanism of processing self-other information. PMID:28256520
SPECT data acquisition and image reconstruction in a stationary small animal SPECT/MRI system

NASA Astrophysics Data System (ADS)

Xu, Jingyan; Chen, Si; Yu, Jianhua; Meier, Dirk; Wagenaar, Douglas J.; Patt, Bradley E.; Tsui, Benjamin M. W.

2010-04-01

The goal of the study was to investigate data acquisition strategies and image reconstruction methods for a stationary SPECT insert that can operate inside an MRI scanner with a 12 cm bore diameter for simultaneous SPECT/MRI imaging of small animals. The SPECT insert consists of 3 octagonal rings of 8 MR-compatible CZT detectors per ring surrounding a multi-pinhole (MPH) collimator sleeve. Each pinhole is constructed to project the field-of-view (FOV) to one CZT detector. All 24 pinholes are focused to a cylindrical FOV of 25 mm in diameter and 34 mm in length. The data acquisition strategies we evaluated were optional collimator rotations to improve tomographic sampling; and the image reconstruction methods were iterative ML-EM with and without compensation for the geometric response function (GRF) of the MPH collimator. For this purpose, we developed an analytic simulator that calculates the system matrix with the GRF models of the MPH collimator. The simulator was used to generate projection data of a digital rod phantom with pinhole aperture sizes of 1 mm and 2 mm and with different collimator rotation patterns. Iterative ML-EM reconstruction with and without GRF compensation were used to reconstruct the projection data from the central ring of 8 detectors only, and from all 24 detectors. Our results indicated that without GRF compensation and at the default design of 24 projection views, the reconstructed images had significant artifacts. Accurate GRF compensation substantially improved the reconstructed image resolution and reduced image artifacts. With accurate GRF compensation, useful reconstructed images can be obtained using 24 projection views only. This last finding potentially enables dynamic SPECT (and/or MRI) studies in small animals, one of many possible application areas of the SPECT/MRI system. Further research efforts are warranted including experimentally measuring the system matrix for improved geometrical accuracy, incorporating the co-registered MRI image in SPECT reconstruction, and exploring potential applications of the simultaneous SPECT/MRI SA system including dynamic SPECT studies.
MR Imaging-based Semi-quantitative Methods for Knee Osteoarthritis

PubMed Central

JARRAYA, Mohamed; HAYASHI, Daichi; ROEMER, Frank Wolfgang; GUERMAZI, Ali

2016-01-01

Magnetic resonance imaging (MRI)-based semi-quantitative (SQ) methods applied to knee osteoarthritis (OA) have been introduced during the last decade and have fundamentally changed our understanding of knee OA pathology since then. Several epidemiological studies and clinical trials have used MRI-based SQ methods to evaluate different outcome measures. Interest in MRI-based SQ scoring system has led to continuous update and refinement. This article reviews the different SQ approaches for MRI-based whole organ assessment of knee OA and also discuss practical aspects of whole joint assessment. PMID:26632537
Collimator design for a multipinhole brain SPECT insert for MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Van Audenhaege, Karen; Van Holen, Roel; Vanhove, Christian

Purpose: Brain single photon emission computed tomography (SPECT) imaging is an important clinical tool, with unique tracers for studying neurological diseases. Nowadays, most commercial SPECT systems are combined with x-ray computed tomography (CT) in so-called SPECT/CT systems to obtain an anatomical background for the functional information. However, while CT images have a high spatial resolution, they have a low soft-tissue contrast, which is an important disadvantage for brain imaging. Magnetic resonance imaging (MRI), on the other hand, has a very high soft-tissue contrast and does not involve extra ionizing radiation. Therefore, the authors designed a brain SPECT insert that canmore » operate inside a clinical MRI. Methods: The authors designed and simulated a compact stationary multipinhole SPECT insert based on digital silicon photomultiplier detector modules, which have shown to be MR-compatible and have an excellent intrinsic resolution (0.5 mm) when combined with a monolithic 2 mm thick LYSO crystal. First, the authors optimized the different parameters of the SPECT system to maximize sensitivity for a given target resolution of 7.2 mm in the center of the field-of-view, given the spatial constraints of the MR system. Second, the authors performed noiseless simulations of two multipinhole configurations to evaluate sampling and reconstructed resolution. Finally, the authors performed Monte Carlo simulations and compared the SPECT insert with a clinical system with ultrahigh-resolution (UHR) fan beam collimators, based on contrast-to-noise ratio and a visual comparison of a Hoffman phantom with a 9 mm cold lesion. Results: The optimization resulted in a stationary multipinhole system with a collimator radius of 150.2 mm and a detector radius of 172.67 mm, which corresponds to four rings of 34 diSPM detector modules. This allows the authors to include eight rings of 24 pinholes, which results in a system volume sensitivity of 395 cps/MBq. Noiseless simulations show sufficient axial sampling (in a Defrise phantom) and a reconstructed resolution of 5.0 mm (in a cold-rod phantom). The authors compared the 24-pinhole setup with a 34-pinhole system (with the same detector radius but a collimator radius of 156.63 mm) and found that 34 pinholes result in better uniformity but a worse reconstruction of the cold-rod phantom. The authors also compared the 24-pinhole system with a clinical triple-head UHR fan beam system based on contrast-to-noise ratio and found that the 24-pinhole setup performs better for the 6 mm hot and the 16 mm cold lesions and worse for the 8 and 10 mm hot lesions. Finally, the authors reconstructed noisy projection data of a Hoffman phantom with a 9 mm cold lesion and found that the lesion was slightly better visible on the multipinhole image compared to the fan beam image. Conclusions: The authors have optimized a stationary multipinhole SPECT insert for MRI and showed the feasibility of doing brain SPECT imaging inside a MRI with an image quality similar to the best clinical SPECT systems available.« less
A methodology for generating normal and pathological brain perfusion SPECT images for evaluation of MRI/SPECT fusion methods: application in epilepsy

NASA Astrophysics Data System (ADS)

Grova, C.; Jannin, P.; Biraben, A.; Buvat, I.; Benali, H.; Bernard, A. M.; Scarabin, J. M.; Gibaud, B.

2003-12-01

Quantitative evaluation of brain MRI/SPECT fusion methods for normal and in particular pathological datasets is difficult, due to the frequent lack of relevant ground truth. We propose a methodology to generate MRI and SPECT datasets dedicated to the evaluation of MRI/SPECT fusion methods and illustrate the method when dealing with ictal SPECT. The method consists in generating normal or pathological SPECT data perfectly aligned with a high-resolution 3D T1-weighted MRI using realistic Monte Carlo simulations that closely reproduce the response of a SPECT imaging system. Anatomical input data for the SPECT simulations are obtained from this 3D T1-weighted MRI, while functional input data result from an inter-individual analysis of anatomically standardized SPECT data. The method makes it possible to control the 'brain perfusion' function by proposing a theoretical model of brain perfusion from measurements performed on real SPECT images. Our method provides an absolute gold standard for assessing MRI/SPECT registration method accuracy since, by construction, the SPECT data are perfectly registered with the MRI data. The proposed methodology has been applied to create a theoretical model of normal brain perfusion and ictal brain perfusion characteristic of mesial temporal lobe epilepsy. To approach realistic and unbiased perfusion models, real SPECT data were corrected for uniform attenuation, scatter and partial volume effect. An anatomic standardization was used to account for anatomic variability between subjects. Realistic simulations of normal and ictal SPECT deduced from these perfusion models are presented. The comparison of real and simulated SPECT images showed relative differences in regional activity concentration of less than 20% in most anatomical structures, for both normal and ictal data, suggesting realistic models of perfusion distributions for evaluation purposes. Inter-hemispheric asymmetry coefficients measured on simulated data were found within the range of asymmetry coefficients measured on corresponding real data. The features of the proposed approach are compared with those of other methods previously described to obtain datasets appropriate for the assessment of fusion methods.
Mapping Informative Clusters in a Hierarchial Framework of fMRI Multivariate Analysis

PubMed Central

Xu, Rui; Zhen, Zonglei; Liu, Jia

2010-01-01

Pattern recognition methods have become increasingly popular in fMRI data analysis, which are powerful in discriminating between multi-voxel patterns of brain activities associated with different mental states. However, when they are used in functional brain mapping, the location of discriminative voxels varies significantly, raising difficulties in interpreting the locus of the effect. Here we proposed a hierarchical framework of multivariate approach that maps informative clusters rather than voxels to achieve reliable functional brain mapping without compromising the discriminative power. In particular, we first searched for local homogeneous clusters that consisted of voxels with similar response profiles. Then, a multi-voxel classifier was built for each cluster to extract discriminative information from the multi-voxel patterns. Finally, through multivariate ranking, outputs from the classifiers were served as a multi-cluster pattern to identify informative clusters by examining interactions among clusters. Results from both simulated and real fMRI data demonstrated that this hierarchical approach showed better performance in the robustness of functional brain mapping than traditional voxel-based multivariate methods. In addition, the mapped clusters were highly overlapped for two perceptually equivalent object categories, further confirming the validity of our approach. In short, the hierarchical framework of multivariate approach is suitable for both pattern classification and brain mapping in fMRI studies. PMID:21152081
Multi-Objective Memetic Search for Robust Motion and Distortion Correction in Diffusion MRI.

PubMed

Hering, Jan; Wolf, Ivo; Maier-Hein, Klaus H

2016-10-01

Effective image-based artifact correction is an essential step in the analysis of diffusion MR images. Many current approaches are based on retrospective registration, which becomes challenging in the realm of high b -values and low signal-to-noise ratio, rendering the corresponding correction schemes more and more ineffective. We propose a novel registration scheme based on memetic search optimization that allows for simultaneous exploitation of different signal intensity relationships between the images, leading to more robust registration results. We demonstrate the increased robustness and efficacy of our method on simulated as well as in vivo datasets. In contrast to the state-of-art methods, the median target registration error (TRE) stayed below the voxel size even for high b -values (3000 s ·mm -2 and higher) and low SNR conditions. We also demonstrate the increased precision in diffusion-derived quantities by evaluating Neurite Orientation Dispersion and Density Imaging (NODDI) derived measures on a in vivo dataset with severe motion artifacts. These promising results will potentially inspire further studies on metaheuristic optimization in diffusion MRI artifact correction and image registration in general.
In vivo estimation of normal amygdala volume from structural MRI scans with anatomical-based segmentation.

PubMed

Siozopoulos, Achilleas; Thomaidis, Vasilios; Prassopoulos, Panos; Fiska, Aliki

2018-02-01

Literature includes a number of studies using structural MRI (sMRI) to determine the volume of the amygdala, which is modified in various pathologic conditions. The reported values vary widely mainly because of different anatomical approaches to the complex. This study aims at estimating of the normal amygdala volume from sMRI scans using a recent anatomical definition described in a study based on post-mortem material. The amygdala volume has been calculated in 106 healthy subjects, using sMRI and anatomical-based segmentation. The resulting volumes have been analyzed for differences related to hemisphere, sex, and age. The mean amygdalar volume was estimated at 1.42 cm 3 . The mean right amygdala volume has been found larger than the left, but the difference for the raw values was within the limits of the method error. No intersexual differences or age-related alterations have been observed. The study provides a method for determining the boundaries of the amygdala in sMRI scans based on recent anatomical considerations and an estimation of the mean normal amygdala volume from a quite large number of scans for future use in comparative studies.
Design of an fMRI-compatible optical touch stripe based on frustrated total internal reflection.

PubMed

Jarrahi, Behnaz; Wanek, Johann

2014-01-01

Previously we developed a low-cost, multi-configurable handheld response system, using a reflective-type intensity modulated fiber-optic sensor (FOS) to accurately gather participants' behavioral responses during functional magnetic resonance imaging (fMRI). Inspired by the popularity and omnipresence of the fingertip-based touch sensing user interface devices, in this paper we present the design of a prototype fMRI-compatible optical touch stripe (OTS) as an alternative configuration. The prototype device takes advantage of a proven frustrated total internal reflection (FTIR) technique. By using a custom-built wedge-shaped optically transparent acrylic prism as an optical waveguide, and a plano-concave lens to provide the required light beam profile, the position of a fingertip touching the surface of the wedge prism can be determined from the deflected light beams that become trapped within the prism by total internal reflection. To achieve maximum sensitivity, the optical design of the wedge prism and lens were optimized through a series of light beam simulations using WinLens 3D Basic software suite. Furthermore, OTS performance and MRI-compatibility were assessed on a 3.0 Tesla MRI scanner running echo planar imaging (EPI) sequences. The results show that the OTS can detect a touch signal at high spatial resolution (about 0.5 cm), and is well suited for use within the MRI environment with average time-variant signal-to-noise ratio (tSNR) loss < 3%.
Fiber estimation and tractography in diffusion MRI: Development of simulated brain images and comparison of multi-fiber analysis methods at clinical b-values

PubMed Central

Wilkins, Bryce; Lee, Namgyun; Gajawelli, Niharika; Law, Meng; Leporé, Natasha

2015-01-01

Advances in diffusion-weighted magnetic resonance imaging (DW-MRI) have led to many alternative diffusion sampling strategies and analysis methodologies. A common objective among methods is estimation of white matter fiber orientations within each voxel, as doing so permits in-vivo fiber-tracking and the ability to study brain connectivity and networks. Knowledge of how DW-MRI sampling schemes affect fiber estimation accuracy, and consequently tractography and the ability to recover complex white-matter pathways, as well as differences between results due to choice of analysis method and which method(s) perform optimally for specific data sets, all remain important problems, especially as tractography-based studies become common. In this work we begin to address these concerns by developing sets of simulated diffusion-weighted brain images which we then use to quantitatively evaluate the performance of six DW-MRI analysis methods in terms of estimated fiber orientation accuracy, false-positive (spurious) and false-negative (missing) fiber rates, and fiber-tracking. The analysis methods studied are: 1) a two-compartment “ball and stick” model (BSM) (Behrens et al., 2003); 2) a non-negativity constrained spherical deconvolution (CSD) approach (Tournier et al., 2007); 3) analytical q-ball imaging (QBI) (Descoteaux et al., 2007); 4) q-ball imaging with Funk-Radon and Cosine Transform (FRACT) (Haldar and Leahy, 2013); 5) q-ball imaging within constant solid angle (CSA) (Aganj et al., 2010); and 6) a generalized Fourier transform approach known as generalized q-sampling imaging (GQI) (Yeh et al., 2010). We investigate these methods using 20, 30, 40, 60, 90 and 120 evenly distributed q-space samples of a single shell, and focus on a signal-to-noise ratio (SNR = 18) and diffusion-weighting (b = 1000 s/mm2) common to clinical studies. We found the BSM and CSD methods consistently yielded the least fiber orientation error and simultaneously greatest detection rate of fibers. Fiber detection rate was found to be the most distinguishing characteristic between the methods, and a significant factor for complete recovery of tractography through complex white-matter pathways. For example, while all methods recovered similar tractography of prominent white matter pathways of limited fiber crossing, CSD (which had the highest fiber detection rate, especially for voxels containing three fibers) recovered the greatest number of fibers and largest fraction of correct tractography for a complex three-fiber crossing region. The synthetic data sets, ground-truth, and tools for quantitative evaluation are publically available on the NITRC website as the project “Simulated DW-MRI Brain Data Sets for Quantitative Evaluation of Estimated Fiber Orientations” at http://www.nitrc.org/projects/sim_dwi_brain PMID:25555998
Fiber estimation and tractography in diffusion MRI: development of simulated brain images and comparison of multi-fiber analysis methods at clinical b-values.

PubMed

Wilkins, Bryce; Lee, Namgyun; Gajawelli, Niharika; Law, Meng; Leporé, Natasha

2015-04-01

Advances in diffusion-weighted magnetic resonance imaging (DW-MRI) have led to many alternative diffusion sampling strategies and analysis methodologies. A common objective among methods is estimation of white matter fiber orientations within each voxel, as doing so permits in-vivo fiber-tracking and the ability to study brain connectivity and networks. Knowledge of how DW-MRI sampling schemes affect fiber estimation accuracy, tractography and the ability to recover complex white-matter pathways, differences between results due to choice of analysis method, and which method(s) perform optimally for specific data sets, all remain important problems, especially as tractography-based studies become common. In this work, we begin to address these concerns by developing sets of simulated diffusion-weighted brain images which we then use to quantitatively evaluate the performance of six DW-MRI analysis methods in terms of estimated fiber orientation accuracy, false-positive (spurious) and false-negative (missing) fiber rates, and fiber-tracking. The analysis methods studied are: 1) a two-compartment "ball and stick" model (BSM) (Behrens et al., 2003); 2) a non-negativity constrained spherical deconvolution (CSD) approach (Tournier et al., 2007); 3) analytical q-ball imaging (QBI) (Descoteaux et al., 2007); 4) q-ball imaging with Funk-Radon and Cosine Transform (FRACT) (Haldar and Leahy, 2013); 5) q-ball imaging within constant solid angle (CSA) (Aganj et al., 2010); and 6) a generalized Fourier transform approach known as generalized q-sampling imaging (GQI) (Yeh et al., 2010). We investigate these methods using 20, 30, 40, 60, 90 and 120 evenly distributed q-space samples of a single shell, and focus on a signal-to-noise ratio (SNR = 18) and diffusion-weighting (b = 1000 s/mm(2)) common to clinical studies. We found that the BSM and CSD methods consistently yielded the least fiber orientation error and simultaneously greatest detection rate of fibers. Fiber detection rate was found to be the most distinguishing characteristic between the methods, and a significant factor for complete recovery of tractography through complex white-matter pathways. For example, while all methods recovered similar tractography of prominent white matter pathways of limited fiber crossing, CSD (which had the highest fiber detection rate, especially for voxels containing three fibers) recovered the greatest number of fibers and largest fraction of correct tractography for complex three-fiber crossing regions. The synthetic data sets, ground-truth, and tools for quantitative evaluation are publically available on the NITRC website as the project "Simulated DW-MRI Brain Data Sets for Quantitative Evaluation of Estimated Fiber Orientations" at http://www.nitrc.org/projects/sim_dwi_brain. Copyright © 2014 Elsevier Inc. All rights reserved.

Optimizing Within-Subject Experimental Designs for jICA of Multi-Channel ERP and fMRI

PubMed Central

Mangalathu-Arumana, Jain; Liebenthal, Einat; Beardsley, Scott A.

2018-01-01

Joint independent component analysis (jICA) can be applied within subject for fusion of multi-channel event-related potentials (ERP) and functional magnetic resonance imaging (fMRI), to measure brain function at high spatiotemporal resolution (Mangalathu-Arumana et al., 2012). However, the impact of experimental design choices on jICA performance has not been systematically studied. Here, the sensitivity of jICA for recovering neural sources in individual data was evaluated as a function of imaging SNR, number of independent representations of the ERP/fMRI data, relationship between instantiations of the joint ERP/fMRI activity (linear, non-linear, uncoupled), and type of sources (varying parametrically and non-parametrically across representations of the data), using computer simulations. Neural sources were simulated with spatiotemporal and noise attributes derived from experimental data. The best performance, maximizing both cross-modal data fusion and the separation of brain sources, occurred with a moderate number of representations of the ERP/fMRI data (10–30), as in a mixed block/event related experimental design. Importantly, the type of relationship between instantiations of the ERP/fMRI activity, whether linear, non-linear or uncoupled, did not in itself impact jICA performance, and was accurately recovered in the common profiles (i.e., mixing coefficients). Thus, jICA provides an unbiased way to characterize the relationship between ERP and fMRI activity across brain regions, in individual data, rendering it potentially useful for characterizing pathological conditions in which neurovascular coupling is adversely affected. PMID:29410611
FPGA-based RF interference reduction techniques for simultaneous PET–MRI

PubMed Central

Gebhardt, P; Wehner, J; Weissler, B; Botnar, R; Marsden, P K; Schulz, V

2016-01-01

Abstract The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) as a multi-modal imaging technique is considered very promising and powerful with regard to in vivo disease progression examination, therapy response monitoring and drug development. However, PET–MRI system design enabling simultaneous operation with unaffected intrinsic performance of both modalities is challenging. As one of the major issues, both the PET detectors and the MRI radio-frequency (RF) subsystem are exposed to electromagnetic (EM) interference, which may lead to PET and MRI signal-to-noise ratio (SNR) deteriorations. Early digitization of electronic PET signals within the MRI bore helps to preserve PET SNR, but occurs at the expense of increased amount of PET electronics inside the MRI and associated RF field emissions. This raises the likelihood of PET-related MRI interference by coupling into the MRI RF coil unwanted spurious signals considered as RF noise, as it degrades MRI SNR and results in MR image artefacts. RF shielding of PET detectors is a commonly used technique to reduce PET-related RF interferences, but can introduce eddy-current-related MRI disturbances and hinder the highest system integration. In this paper, we present RF interference reduction methods which rely on EM field coupling–decoupling principles of RF receive coils rather than suppressing emitted fields. By modifying clock frequencies and changing clock phase relations of digital circuits, the resulting RF field emission is optimised with regard to a lower field coupling into the MRI RF coil, thereby increasing the RF silence of PET detectors. Our methods are demonstrated by performing FPGA-based clock frequency and phase shifting of digital silicon photo-multipliers (dSiPMs) used in the PET modules of our MR-compatible Hyperion IID PET insert. We present simulations and magnetic-field map scans visualising the impact of altered clock phase pattern on the spatial RF field distribution, followed by MRI noise and SNR scans performed with an operating PET module using different clock frequencies and phase patterns. The methods were implemented via firmware design changes without any hardware modifications. This introduces new means of flexibility by enabling adaptive RF interference reduction optimisations in the field, e.g. when using a PET insert with different MRI systems or when different MRI RF coil types are to be operated with the same PET detector. PMID:27049898
FPGA-based RF interference reduction techniques for simultaneous PET-MRI.

PubMed

Gebhardt, P; Wehner, J; Weissler, B; Botnar, R; Marsden, P K; Schulz, V

2016-05-07

The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) as a multi-modal imaging technique is considered very promising and powerful with regard to in vivo disease progression examination, therapy response monitoring and drug development. However, PET-MRI system design enabling simultaneous operation with unaffected intrinsic performance of both modalities is challenging. As one of the major issues, both the PET detectors and the MRI radio-frequency (RF) subsystem are exposed to electromagnetic (EM) interference, which may lead to PET and MRI signal-to-noise ratio (SNR) deteriorations. Early digitization of electronic PET signals within the MRI bore helps to preserve PET SNR, but occurs at the expense of increased amount of PET electronics inside the MRI and associated RF field emissions. This raises the likelihood of PET-related MRI interference by coupling into the MRI RF coil unwanted spurious signals considered as RF noise, as it degrades MRI SNR and results in MR image artefacts. RF shielding of PET detectors is a commonly used technique to reduce PET-related RF interferences, but can introduce eddy-current-related MRI disturbances and hinder the highest system integration. In this paper, we present RF interference reduction methods which rely on EM field coupling-decoupling principles of RF receive coils rather than suppressing emitted fields. By modifying clock frequencies and changing clock phase relations of digital circuits, the resulting RF field emission is optimised with regard to a lower field coupling into the MRI RF coil, thereby increasing the RF silence of PET detectors. Our methods are demonstrated by performing FPGA-based clock frequency and phase shifting of digital silicon photo-multipliers (dSiPMs) used in the PET modules of our MR-compatible Hyperion II (D) PET insert. We present simulations and magnetic-field map scans visualising the impact of altered clock phase pattern on the spatial RF field distribution, followed by MRI noise and SNR scans performed with an operating PET module using different clock frequencies and phase patterns. The methods were implemented via firmware design changes without any hardware modifications. This introduces new means of flexibility by enabling adaptive RF interference reduction optimisations in the field, e.g. when using a PET insert with different MRI systems or when different MRI RF coil types are to be operated with the same PET detector.
FPGA-based RF interference reduction techniques for simultaneous PET-MRI

NASA Astrophysics Data System (ADS)

Gebhardt, P.; Wehner, J.; Weissler, B.; Botnar, R.; Marsden, P. K.; Schulz, V.

2016-05-01

The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) as a multi-modal imaging technique is considered very promising and powerful with regard to in vivo disease progression examination, therapy response monitoring and drug development. However, PET-MRI system design enabling simultaneous operation with unaffected intrinsic performance of both modalities is challenging. As one of the major issues, both the PET detectors and the MRI radio-frequency (RF) subsystem are exposed to electromagnetic (EM) interference, which may lead to PET and MRI signal-to-noise ratio (SNR) deteriorations. Early digitization of electronic PET signals within the MRI bore helps to preserve PET SNR, but occurs at the expense of increased amount of PET electronics inside the MRI and associated RF field emissions. This raises the likelihood of PET-related MRI interference by coupling into the MRI RF coil unwanted spurious signals considered as RF noise, as it degrades MRI SNR and results in MR image artefacts. RF shielding of PET detectors is a commonly used technique to reduce PET-related RF interferences, but can introduce eddy-current-related MRI disturbances and hinder the highest system integration. In this paper, we present RF interference reduction methods which rely on EM field coupling-decoupling principles of RF receive coils rather than suppressing emitted fields. By modifying clock frequencies and changing clock phase relations of digital circuits, the resulting RF field emission is optimised with regard to a lower field coupling into the MRI RF coil, thereby increasing the RF silence of PET detectors. Our methods are demonstrated by performing FPGA-based clock frequency and phase shifting of digital silicon photo-multipliers (dSiPMs) used in the PET modules of our MR-compatible Hyperion II D PET insert. We present simulations and magnetic-field map scans visualising the impact of altered clock phase pattern on the spatial RF field distribution, followed by MRI noise and SNR scans performed with an operating PET module using different clock frequencies and phase patterns. The methods were implemented via firmware design changes without any hardware modifications. This introduces new means of flexibility by enabling adaptive RF interference reduction optimisations in the field, e.g. when using a PET insert with different MRI systems or when different MRI RF coil types are to be operated with the same PET detector.
Directly detected 55Mn MRI: Application to phantoms for human hyperpolarized 13C MRI development

PubMed Central

von Morze, Cornelius; Carvajal, Lucas; Reed, Galen D.; Swisher, Christine Leon; Tropp, James; Vigneron, Daniel B.

2014-01-01

In this work we demonstrate for the first time directly detected manganese-55 (55Mn) MRI using a clinical 3T MRI scanner designed for human hyperpolarized 13C clinical studies with no additional hardware modifications. Due to the similar frequency of the 55Mn and 13C resonances, the use of aqueous permanganate for large, signal-dense, and cost-effective “13C” MRI phantoms was investigated, addressing the clear need for new phantoms for these studies. Due to 100% natural abundance, higher intrinsic sensitivity, and favorable relaxation properties, 55Mn MRI of aqueous permanganate demonstrates dramatically increased sensitivity over typical 13C phantom MRI, at greatly reduced cost as compared with large 13C-enriched phantoms. A large sensitivity advantage (22-fold) was demonstrated. A cylindrical phantom (d= 8 cm) containing concentrated aqueous sodium permanganate (2.7M) was scanned rapidly by 55Mn MRI in a human head coil tuned for 13C, using a balanced SSFP acquisition. The requisite penetration of RF magnetic fields into concentrated permanganate was investigated by experiments and high frequency electromagnetic simulations, and found to be sufficient for 55Mn MRI with reasonably sized phantoms. A sub-second slice-selective acquisition yielded mean image SNR of ~60 at 0.5cm3 spatial resolution, distributed with minimum central signal ~40% of the maximum edge signal. We anticipate that permanganate phantoms will be very useful for testing HP 13C coils and methods designed for human studies. PMID:25179135
Physiologic Simulation of the Fontan Surgery with Variable Wall Properties and Respiration

NASA Astrophysics Data System (ADS)

Long, Christopher; Bazilevs, Yuri; Feinstein, Jeffrey; Marsden, Alison

2010-11-01

Children born with single ventricle heart defects typically undergo a surgical procedure known as a total cavopulmonary connection (TCPC). The goal of this work is to perform hemodynamic simulations accounting for motion of the arterial walls in the TCPC. We perform fluid structure interactions (FSI) simulations using an Arbitrary Lagrangian Eulerian (ALE) finite element framework into a patient-specific model of the TCPC. The patient's post-op anatomy is reconstructed from MRI data. Respiration rate, heart rate, and venous pressures are obtained from catheterization data, and flowrates are obtained from phase contrast MRI data and are used together with a respiratory model. Lumped parameter (RCR) boundary conditions are used at the outlets. This study is the first to introduce variable elastic properties for the different areas of the TCPC, including a Gore-Tex conduit. Quantities such as wall shear stresses and pressures at critical junctions are extracted from the simulation and are compared with pressure tracings from clinical data as well as with rigid wall simulations.
Overcoming spatio-temporal limitations using dynamically scaled in vitro PC-MRI - A flow field comparison to true-scale computer simulations of idealized, stented and patient-specific left main bifurcations.

PubMed

Beier, Susann; Ormiston, John; Webster, Mark; Cater, John; Norris, Stuart; Medrano-Gracia, Pau; Young, Alistair; Gilbert, Kathleen; Cowan, Brett

2016-08-01

The majority of patients with angina or heart failure have coronary artery disease. Left main bifurcations are particularly susceptible to pathological narrowing. Flow is a major factor of atheroma development, but limitations in imaging technology such as spatio-temporal resolution, signal-to-noise ratio (SNRv), and imaging artefacts prevent in vivo investigations. Computational fluid dynamics (CFD) modelling is a common numerical approach to study flow, but it requires a cautious and rigorous application for meaningful results. Left main bifurcation angles of 40°, 80° and 110° were found to represent the spread of an atlas based 100 computed tomography angiograms. Three left mains with these bifurcation angles were reconstructed with 1) idealized, 2) stented, and 3) patient-specific geometry. These were then approximately 7× scaled-up and 3D printing as large phantoms. Their flow was reproduced using a blood-analogous, dynamically scaled steady flow circuit, enabling in vitro phase-contrast magnetic resonance (PC-MRI) measurements. After threshold segmentation the image data was registered to true-scale CFD of the same coronary geometry using a coherent point drift algorithm, yielding a small covariance error (σ 2 <;5.8×10 -4 ). Natural-neighbour interpolation of the CFD data onto the PC-MRI grid enabled direct flow field comparison, showing very good agreement in magnitude (error 2-12%) and directional changes (r 2 0.87-0.91), and stent induced flow alternations were measureable for the first time. PC-MRI over-estimated velocities close to the wall, possibly due to partial voluming. Bifurcation shape determined the development of slow flow regions, which created lower SNRv regions and increased discrepancies. These can likely be minimised in future by testing different similarity parameters to reduce acquisition error and improve correlation further. It was demonstrated that in vitro large phantom acquisition correlates to true-scale coronary flow simulations when dynamically scaled, and thus can overcome current PC-MRI's spatio-temporal limitations. This novel method enables experimental assessment of stent induced flow alternations, and in future may elevate CFD coronary flow simulations by providing sophisticated boundary conditions, and enable investigations of stenosis phantoms.
Study of the Transition from MRI to Magnetic Turbulence via Parasitic Instability by a High-order MHD Simulation Code

NASA Astrophysics Data System (ADS)

Hirai, Kenichiro; Katoh, Yuto; Terada, Naoki; Kawai, Soshi

2018-02-01

Magnetic turbulence in accretion disks under ideal magnetohydrodynamic (MHD) conditions is expected to be driven by the magneto-rotational instability (MRI) followed by secondary parasitic instabilities. We develop a three-dimensional ideal MHD code that can accurately resolve turbulent structures, and carry out simulations with a net vertical magnetic field in a local shearing box disk model to investigate the role of parasitic instabilities in the formation process of magnetic turbulence. Our simulations reveal that a highly anisotropic Kelvin–Helmholtz (K–H) mode parasitic instability evolves just before the first peak in turbulent stress and then breaks large-scale shear flows created by MRI. The wavenumber of the enhanced parasitic instability is larger than the theoretical estimate, because the shear flow layers sometimes become thinner than those assumed in the linear analysis. We also find that interaction between antiparallel vortices caused by the K–H mode parasitic instability induces small-scale waves that break the shear flows. On the other hand, at repeated peaks in the nonlinear phase, anisotropic wavenumber spectra are observed only in the small wavenumber region and isotropic waves dominate at large wavenumbers unlike for the first peak. Restructured channel flows due to MRI at the peaks in nonlinear phase seem to be collapsed by the advection of small-scale shear structures into the restructured flow and resultant mixing.
Cerebellar Functional Parcellation Using Sparse Dictionary Learning Clustering.

PubMed

Wang, Changqing; Kipping, Judy; Bao, Chenglong; Ji, Hui; Qiu, Anqi

2016-01-01

The human cerebellum has recently been discovered to contribute to cognition and emotion beyond the planning and execution of movement, suggesting its functional heterogeneity. We aimed to identify the functional parcellation of the cerebellum using information from resting-state functional magnetic resonance imaging (rs-fMRI). For this, we introduced a new data-driven decomposition-based functional parcellation algorithm, called Sparse Dictionary Learning Clustering (SDLC). SDLC integrates dictionary learning, sparse representation of rs-fMRI, and k-means clustering into one optimization problem. The dictionary is comprised of an over-complete set of time course signals, with which a sparse representation of rs-fMRI signals can be constructed. Cerebellar functional regions were then identified using k-means clustering based on the sparse representation of rs-fMRI signals. We solved SDLC using a multi-block hybrid proximal alternating method that guarantees strong convergence. We evaluated the reliability of SDLC and benchmarked its classification accuracy against other clustering techniques using simulated data. We then demonstrated that SDLC can identify biologically reasonable functional regions of the cerebellum as estimated by their cerebello-cortical functional connectivity. We further provided new insights into the cerebello-cortical functional organization in children.
An integrated system for dissolution studies and magnetic resonance imaging of controlled release, polymer-based dosage forms-a tool for quantitative assessment of hydrogel formation processes.

PubMed

Kulinowski, Piotr; Dorozyński, Przemysław; Jachowicz, Renata; Weglarz, Władysław P

2008-11-04

Controlled release (CR) dosage forms are often based on polymeric matrices, e.g., sustained-release tablets and capsules. It is crucial to visualise and quantify processes of the hydrogel formation during the standard dissolution study. A method for imaging of CR, polymer-based dosage forms during dissolution study in vitro is presented. Imaging was performed in a non-invasive way by means of the magnetic resonance imaging (MRI). This study was designed to simulate in vivo conditions regarding temperature, volume, state and composition of dissolution media. Two formulations of hydrodynamically balanced systems (HBS) were chosen as model CR dosage forms. HBS release active substance in stomach while floating on the surface of the gastric content. Time evolutions of the diffusion region, hydrogel formation region and "dry core" region were obtained during a dissolution study of L-dopa as a model drug in two simulated gastric fluids (i.e. in fed and fasted state). This method seems to be a very promising tool for examining properties of new formulations of CR, polymer-based dosage forms or for comparison of generic and originator dosage forms before carrying out bioequivalence studies.
Stereotactic ultrasound for target volume definition in a patient with prostate cancer and bilateral total hip replacement.

PubMed

Boda-Heggemann, Judit; Haneder, Stefan; Ehmann, Michael; Sihono, Dwi Seno Kuncoro; Wertz, Hansjörg; Mai, Sabine; Kegel, Stefan; Heitmann, Sigrun; von Swietochowski, Sandra; Lohr, Frank; Wenz, Frederik

2015-01-01

Target-volume definition for prostate cancer in patients with bilateral metal total hip replacements (THRs) is a challenge because of metal artifacts in the planning computed tomography (CT) scans. Magnetic resonance imaging (MRI) can be used for matching and prostate delineation; however, at a spatial and temporal distance from the planning CT, identical rectal and vesical filling is difficult to achieve. In addition, MRI may also be impaired by metal artifacts, even resulting in spatial image distortion. Here, we present a method to define prostate target volumes based on ultrasound images acquired during CT simulation and online-matched to the CT data set directly at the planning CT. A 78-year-old patient with cT2cNxM0 prostate cancer with bilateral metal THRs was referred to external beam radiation therapy. T2-weighted MRI was performed on the day of the planning CT with preparation according to a protocol for reproducible bladder and rectal filling. The planning CT was obtained with the immediate acquisition of a 3-dimensional ultrasound data set with a dedicated stereotactic ultrasound system for online intermodality image matching referenced to the isocenter by ceiling-mounted infrared cameras. MRI (offline) and ultrasound images (online) were thus both matched to the CT images for planning. Daily image guided radiation therapy (IGRT) was performed with transabdominal ultrasound and compared with cone beam CT. Because of variations in bladder and rectal filling and metal-induced image distortion in MRI, soft-tissue-based matching of the MRI to CT was not sufficient for unequivocal prostate target definition. Ultrasound-based images could be matched, and prostate, seminal vesicles, and target volumes were reliably defined. Daily IGRT could be successfully completed with transabdominal ultrasound with good accordance between cone beam CT and ultrasound. For prostate cancer patients with bilateral THRs causing artifacts in planning CTs, ultrasound referenced to the isocenter of the CT simulator and acquired with intermodal online coregistration directly at the planning CT is a fast and easy method to reliably delineate the prostate and target volumes and for daily IGRT. Copyright © 2015 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.
3D Fast Spin Echo T2-weighted Contrast for Imaging the Female Cervix

NASA Astrophysics Data System (ADS)

Vargas Sanchez, Andrea Fernanda

Magnetic Resonance Imaging (MRI) with T2-weighted contrast is the preferred modality for treatment planning and monitoring of cervical cancer. Current clinical protocols image the volume of interest multiple times with two dimensional (2D) T2-weighted MRI techniques. It is of interest to replace these multiple 2D acquisitions with a single three dimensional (3D) MRI acquisition to save time. However, at present the image contrast of standard 3D MRI does not distinguish cervical healthy tissue from cancerous tissue. The purpose of this thesis is to better understand the underlying factors that govern the contrast of 3D MRI and exploit this understanding via sequence modifications to improve the contrast. Numerical simulations are developed to predict observed contrast alterations and to propose an improvement. Improvements of image contrast are shown in simulation and with healthy volunteers. Reported results are only preliminary but a promising start to establish definitively 3D MRI for cervical cancer applications.
Comparative diagnostic value of 18F-fluoride PET-CT versus MRI for skull-base bone invasion in nasopharyngeal carcinoma.

PubMed

Le, Yali; Chen, Yu; Zhou, Fan; Liu, Guangfu; Huang, Zhanwen; Chen, Yue

2016-10-01

This study compared the diagnostic value of F-fluoride PET-computed tomography (PET-CT) and MRI in skull-base bone erosion in nasopharyngeal carcinoma (NPC) patients. A total of 93 patients with biopsy-confirmed NPC were enrolled, including 68 men and 25 women between 23 and 74 years of age. All patients were evaluated by both F-fluoride PET-CT and MRI, and the interval between the two imaging examinations was less than 20 days. The patients received no treatment either before or between scans. The studies were interpreted by two nuclear medicine physicians or two radiologists with more than 10 years of professional experience who were blinded to both the diagnosis and the results of the other imaging studies. The reference standard was skull-base bone erosion at a 20-week follow-up imaging study. On the basis of the results of the follow-up imaging studies, 52 patients showed skull-base bone erosion. The numbers of true positives, false positives, true negatives, and false negatives with F-fluoride PET-CT were 49, 4, 37, and 3, respectively. The numbers of true positives, false positives, true negatives, and false negatives with MRI were 46, 5, 36, and 6, respectively. The sensitivity, specificity, and crude accuracy of F-fluoride PET-CT were 94.23, 90.24, and 92.47%, respectively; for MRI, these values were 88.46, 87.80, and 88.17%. Of the 52 patients, 43 showed positive findings both on F-fluoride PET-CT and on MRI. Within the patient cohort, F-fluoride PET-CT and MRI detected 178 and 135 bone lesions, respectively. Both F-fluoride PET-CT and MRI have high sensitivity, specificity, and crude accuracy for detecting skull-base bone invasion in patients with NPC. F-fluoride PET-CT detected more lesions than did MRI in the skull-base bone. This suggests that F-fluoride PET-CT has a certain advantage in evaluating the skull-base bone of NPC patients. Combining the two methods could improve the diagnostic accuracy of skull-base bone invasion for NPC.
Diagnostic tests in urology: magnetic resonance imaging (MRI) for the staging of prostate cancer.

PubMed

Preston, Mark A; Harisinghani, Mukesh G; Mucci, Lorelei; Witiuk, Kelsey; Breau, Rodney H

2013-03-01

WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: The use of MRI for prostate cancer diagnosis and staging is increasing. Indications for prostate MRI are not defined and many clinicians are unsure of how best to use MRI to aid clinical decisions. This evidence-based medicine article addresses the clinical utility of prostate MRI for preoperative staging. Based on a common patient scenario, a guide to calculating the probability of extraprostatic extension is provided. © 2013 BJU International.
Feasibility of Using Linearly Polarized Rotating Birdcage Transmitters and Close-Fitting Receive Arrays in MRI to Reduce SAR in the Vicinity of Deep Brain Simulation Implants

PubMed Central

Golestanirad, Laleh; Keil, Boris; Angelone, Leonardo M.; Bonmassar, Giorgio; Mareyam, Azma; Wald, Lawrence L.

2016-01-01

Purpose MRI of patients with deep brain stimulation (DBS) implants is strictly limited due to safety concerns, including high levels of local specific absorption rate (SAR) of radiofrequency (RF) fields near the implant and related RF-induced heating. This study demonstrates the feasibility of using a rotating linearly polarized birdcage transmitter and a 32-channel close-fit receive array to significantly reduce local SAR in MRI of DBS patients. Methods Electromagnetic simulations and phantom experiments were performed with generic DBS lead geometries and implantation paths. The technique was based on mechanically rotating a linear birdcage transmitter to align its zero electric-field region with the implant while using a close-fit receive array to significantly increase signal to noise ratio of the images. Results It was found that the zero electric-field region of the transmitter is thick enough at 1.5 Tesla to encompass DBS lead trajectories with wire segments that were up to 30 degrees out of plane, as well as leads with looped segments. Moreover, SAR reduction was not sensitive to tissue properties, and insertion of a close-fit 32-channel receive array did not degrade the SAR reduction performance. Conclusion The ensemble of rotating linear birdcage and 32-channel close-fit receive array introduces a promising technology for future improvement of imaging in patients with DBS implants. PMID:27059266
A Java-based fMRI processing pipeline evaluation system for assessment of univariate general linear model and multivariate canonical variate analysis-based pipelines.

PubMed

Zhang, Jing; Liang, Lichen; Anderson, Jon R; Gatewood, Lael; Rottenberg, David A; Strother, Stephen C

2008-01-01

As functional magnetic resonance imaging (fMRI) becomes widely used, the demands for evaluation of fMRI processing pipelines and validation of fMRI analysis results is increasing rapidly. The current NPAIRS package, an IDL-based fMRI processing pipeline evaluation framework, lacks system interoperability and the ability to evaluate general linear model (GLM)-based pipelines using prediction metrics. Thus, it can not fully evaluate fMRI analytical software modules such as FSL.FEAT and NPAIRS.GLM. In order to overcome these limitations, a Java-based fMRI processing pipeline evaluation system was developed. It integrated YALE (a machine learning environment) into Fiswidgets (a fMRI software environment) to obtain system interoperability and applied an algorithm to measure GLM prediction accuracy. The results demonstrated that the system can evaluate fMRI processing pipelines with univariate GLM and multivariate canonical variates analysis (CVA)-based models on real fMRI data based on prediction accuracy (classification accuracy) and statistical parametric image (SPI) reproducibility. In addition, a preliminary study was performed where four fMRI processing pipelines with GLM and CVA modules such as FSL.FEAT and NPAIRS.CVA were evaluated with the system. The results indicated that (1) the system can compare different fMRI processing pipelines with heterogeneous models (NPAIRS.GLM, NPAIRS.CVA and FSL.FEAT) and rank their performance by automatic performance scoring, and (2) the rank of pipeline performance is highly dependent on the preprocessing operations. These results suggest that the system will be of value for the comparison, validation, standardization and optimization of functional neuroimaging software packages and fMRI processing pipelines.
Image-driven, model-based 3D abdominal motion estimation for MR-guided radiotherapy

NASA Astrophysics Data System (ADS)

Stemkens, Bjorn; Tijssen, Rob H. N.; de Senneville, Baudouin Denis; Lagendijk, Jan J. W.; van den Berg, Cornelis A. T.

2016-07-01

Respiratory motion introduces substantial uncertainties in abdominal radiotherapy for which traditionally large margins are used. The MR-Linac will open up the opportunity to acquire high resolution MR images just prior to radiation and during treatment. However, volumetric MRI time series are not able to characterize 3D tumor and organ-at-risk motion with sufficient temporal resolution. In this study we propose a method to estimate 3D deformation vector fields (DVFs) with high spatial and temporal resolution based on fast 2D imaging and a subject-specific motion model based on respiratory correlated MRI. In a pre-beam phase, a retrospectively sorted 4D-MRI is acquired, from which the motion is parameterized using a principal component analysis. This motion model is used in combination with fast 2D cine-MR images, which are acquired during radiation, to generate full field-of-view 3D DVFs with a temporal resolution of 476 ms. The geometrical accuracies of the input data (4D-MRI and 2D multi-slice acquisitions) and the fitting procedure were determined using an MR-compatible motion phantom and found to be 1.0-1.5 mm on average. The framework was tested on seven healthy volunteers for both the pancreas and the kidney. The calculated motion was independently validated using one of the 2D slices, with an average error of 1.45 mm. The calculated 3D DVFs can be used retrospectively for treatment simulations, plan evaluations, or to determine the accumulated dose for both the tumor and organs-at-risk on a subject-specific basis in MR-guided radiotherapy.
Image-driven, model-based 3D abdominal motion estimation for MR-guided radiotherapy.

PubMed

Stemkens, Bjorn; Tijssen, Rob H N; de Senneville, Baudouin Denis; Lagendijk, Jan J W; van den Berg, Cornelis A T

2016-07-21

Respiratory motion introduces substantial uncertainties in abdominal radiotherapy for which traditionally large margins are used. The MR-Linac will open up the opportunity to acquire high resolution MR images just prior to radiation and during treatment. However, volumetric MRI time series are not able to characterize 3D tumor and organ-at-risk motion with sufficient temporal resolution. In this study we propose a method to estimate 3D deformation vector fields (DVFs) with high spatial and temporal resolution based on fast 2D imaging and a subject-specific motion model based on respiratory correlated MRI. In a pre-beam phase, a retrospectively sorted 4D-MRI is acquired, from which the motion is parameterized using a principal component analysis. This motion model is used in combination with fast 2D cine-MR images, which are acquired during radiation, to generate full field-of-view 3D DVFs with a temporal resolution of 476 ms. The geometrical accuracies of the input data (4D-MRI and 2D multi-slice acquisitions) and the fitting procedure were determined using an MR-compatible motion phantom and found to be 1.0-1.5 mm on average. The framework was tested on seven healthy volunteers for both the pancreas and the kidney. The calculated motion was independently validated using one of the 2D slices, with an average error of 1.45 mm. The calculated 3D DVFs can be used retrospectively for treatment simulations, plan evaluations, or to determine the accumulated dose for both the tumor and organs-at-risk on a subject-specific basis in MR-guided radiotherapy.
Cortical hot spots and labyrinths: why cortical neuromodulation for episodic migraine with aura should be personalized

PubMed Central

Dahlem, Markus A.; Schmidt, Bernd; Bojak, Ingo; Boie, Sebastian; Kneer, Frederike; Hadjikhani, Nouchine; Kurths, Jürgen

2015-01-01

Stimulation protocols for medical devices should be rationally designed. For episodic migraine with aura we outline model-based design strategies toward preventive and acute therapies using stereotactic cortical neuromodulation. To this end, we regard a localized spreading depression (SD) wave segment as a central element in migraine pathophysiology. To describe nucleation and propagation features of the SD wave segment, we define the new concepts of cortical hot spots and labyrinths, respectively. In particular, we firstly focus exclusively on curvature-induced dynamical properties by studying a generic reaction-diffusion model of SD on the folded cortical surface. This surface is described with increasing level of details, including finally personalized simulations using patient's magnetic resonance imaging (MRI) scanner readings. At this stage, the only relevant factor that can modulate nucleation and propagation paths is the Gaussian curvature, which has the advantage of being rather readily accessible by MRI. We conclude with discussing further anatomical factors, such as areal, laminar, and cellular heterogeneity, that in addition to and in relation to Gaussian curvature determine the generalized concept of cortical hot spots and labyrinths as target structures for neuromodulation. Our numerical simulations suggest that these target structures are like fingerprints, they are individual features of each migraine sufferer. The goal in the future will be to provide individualized neural tissue simulations. These simulations should predict the clinical data and therefore can also serve as a test bed for exploring stereotactic cortical neuromodulation. PMID:25798103
Technical Note: A Monte Carlo study of magnetic-field-induced radiation dose effects in mice

PubMed Central

Liao, Zhongxing; Melancon, Adam D.; Guindani, Michele; Followill, David S.; Tailor, Ramesh C.; Hazle, John D.; Court, Laurence E.

2015-01-01

Purpose: Magnetic fields are known to alter radiation dose deposition. Before patients receive treatment using an MRI-linear accelerator (MRI-Linac), preclinical studies are needed to understand the biological consequences of magnetic-field-induced dose effects. In the present study, the authors sought to identify a beam energy and magnetic field strength combination suitable for preclinical murine experiments. Methods: Magnetic field dose effects were simulated in a mouse lung phantom using various beam energies (225 kVp, 350 kVp, 662 keV [Cs-137], 2 MV, and 1.25 MeV [Co-60]) and magnetic field strengths (0.75, 1.5, and 3 T). The resulting dose distributions were compared with those in a simulated human lung phantom irradiated with a 6 or 8 MV beam and orthogonal 1.5 T magnetic field. Results: In the human lung phantom, the authors observed a dose increase of 45% and 54% at the soft-tissue-to-lung interface and a dose decrease of 41% and 48% at the lung-to-soft-tissue interface for the 6 and 8 MV beams, respectively. In the mouse simulations, the magnetic fields had no measurable effect on the 225 or 350 kVp dose distribution. The dose increases with the Cs-137 beam for the 0.75, 1.5, and 3 T magnetic fields were 9%, 29%, and 42%, respectively. The dose decreases were 9%, 21%, and 37%. For the 2 MV beam, the dose increases were 16%, 33%, and 31% and the dose decreases were 9%, 19%, and 30%. For the Co-60 beam, the dose increases were 19%, 54%, and 44%, and the dose decreases were 19%, 42%, and 40%. Conclusions: The magnetic field dose effects in the mouse phantom using a Cs-137, 3 T combination or a Co-60, 1.5 or 3 T combination most closely resemble those in simulated human treatments with a 6 MV, 1.5 T MRI-Linac. The effects with a Co-60, 1.5 T combination most closely resemble those in simulated human treatments with an 8 MV, 1.5 T MRI-Linac. PMID:26328998

A Role for the Left Angular Gyrus in Episodic Simulation and Memory.

PubMed

Thakral, Preston P; Madore, Kevin P; Schacter, Daniel L

2017-08-23

Functional magnetic resonance imaging (fMRI) studies indicate that episodic simulation (i.e., imagining specific future experiences) and episodic memory (i.e., remembering specific past experiences) are associated with enhanced activity in a common set of neural regions referred to as the core network. This network comprises the hippocampus, medial prefrontal cortex, and left angular gyrus, among other regions. Because fMRI data are correlational, it is unknown whether activity increases in core network regions are critical for episodic simulation and episodic memory. In the current study, we used MRI-guided transcranial magnetic stimulation (TMS) to assess whether temporary disruption of the left angular gyrus would impair both episodic simulation and memory (16 participants, 10 females). Relative to TMS to a control site (vertex), disruption of the left angular gyrus significantly reduced the number of internal (i.e., episodic) details produced during the simulation and memory tasks, with a concomitant increase in external detail production (i.e., semantic, repetitive, or off-topic information), reflected by a significant detail by TMS site interaction. Difficulty in the simulation and memory tasks also increased after TMS to the left angular gyrus relative to the vertex. In contrast, performance in a nonepisodic control task did not differ statistically as a function of TMS site (i.e., number of free associates produced or difficulty in performing the free associate task). Together, these results are the first to demonstrate that the left angular gyrus is critical for both episodic simulation and episodic memory. SIGNIFICANCE STATEMENT Humans have the ability to imagine future episodes (i.e., episodic simulation) and remember episodes from the past (i.e., episodic memory). A wealth of neuroimaging studies have revealed that these abilities are associated with enhanced activity in a core network of neural regions, including the hippocampus, medial prefrontal cortex, and left angular gyrus. However, neuroimaging data are correlational and do not tell us whether core regions support critical processes for simulation and memory. In the current study, we used transcranial magnetic stimulation and demonstrated that temporary disruption of the left angular gyrus leads to impairments in simulation and memory. The present study provides the first causal evidence to indicate that this region is critical for these fundamental abilities. Copyright © 2017 the authors 0270-6474/17/378142-08$15.00/0.
A Role for the Left Angular Gyrus in Episodic Simulation and Memory

PubMed Central

2017-01-01

Functional magnetic resonance imaging (fMRI) studies indicate that episodic simulation (i.e., imagining specific future experiences) and episodic memory (i.e., remembering specific past experiences) are associated with enhanced activity in a common set of neural regions referred to as the core network. This network comprises the hippocampus, medial prefrontal cortex, and left angular gyrus, among other regions. Because fMRI data are correlational, it is unknown whether activity increases in core network regions are critical for episodic simulation and episodic memory. In the current study, we used MRI-guided transcranial magnetic stimulation (TMS) to assess whether temporary disruption of the left angular gyrus would impair both episodic simulation and memory (16 participants, 10 females). Relative to TMS to a control site (vertex), disruption of the left angular gyrus significantly reduced the number of internal (i.e., episodic) details produced during the simulation and memory tasks, with a concomitant increase in external detail production (i.e., semantic, repetitive, or off-topic information), reflected by a significant detail by TMS site interaction. Difficulty in the simulation and memory tasks also increased after TMS to the left angular gyrus relative to the vertex. In contrast, performance in a nonepisodic control task did not differ statistically as a function of TMS site (i.e., number of free associates produced or difficulty in performing the free associate task). Together, these results are the first to demonstrate that the left angular gyrus is critical for both episodic simulation and episodic memory. SIGNIFICANCE STATEMENT Humans have the ability to imagine future episodes (i.e., episodic simulation) and remember episodes from the past (i.e., episodic memory). A wealth of neuroimaging studies have revealed that these abilities are associated with enhanced activity in a core network of neural regions, including the hippocampus, medial prefrontal cortex, and left angular gyrus. However, neuroimaging data are correlational and do not tell us whether core regions support critical processes for simulation and memory. In the current study, we used transcranial magnetic stimulation and demonstrated that temporary disruption of the left angular gyrus leads to impairments in simulation and memory. The present study provides the first causal evidence to indicate that this region is critical for these fundamental abilities. PMID:28733357
Intelligent and automatic in vivo detection and quantification of transplanted cells in MRI.

PubMed

Afridi, Muhammad Jamal; Ross, Arun; Liu, Xiaoming; Bennewitz, Margaret F; Shuboni, Dorela D; Shapiro, Erik M

2017-11-01

Magnetic resonance imaging (MRI)-based cell tracking has emerged as a useful tool for identifying the location of transplanted cells, and even their migration. Magnetically labeled cells appear as dark contrast in T2*-weighted MRI, with sensitivities of individual cells. One key hurdle to the widespread use of MRI-based cell tracking is the inability to determine the number of transplanted cells based on this contrast feature. In the case of single cell detection, manual enumeration of spots in three-dimensional (3D) MRI in principle is possible; however, it is a tedious and time-consuming task that is prone to subjectivity and inaccuracy on a large scale. This research presents the first comprehensive study on how a computer-based intelligent, automatic, and accurate cell quantification approach can be designed for spot detection in MRI scans. Magnetically labeled mesenchymal stem cells (MSCs) were transplanted into rats using an intracardiac injection, accomplishing single cell seeding in the brain. T2*-weighted MRI of these rat brains were performed where labeled MSCs appeared as spots. Using machine learning and computer vision paradigms, approaches were designed to systematically explore the possibility of automatic detection of these spots in MRI. Experiments were validated against known in vitro scenarios. Using the proposed deep convolutional neural network (CNN) architecture, an in vivo accuracy up to 97.3% and in vitro accuracy of up to 99.8% was achieved for automated spot detection in MRI data. The proposed approach for automatic quantification of MRI-based cell tracking will facilitate the use of MRI in large-scale cell therapy studies. Magn Reson Med 78:1991-2002, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.
Quantitative chemical exchange saturation transfer (qCEST) MRI--RF spillover effect-corrected omega plot for simultaneous determination of labile proton fraction ratio and exchange rate.

PubMed

Sun, Phillip Zhe; Wang, Yu; Dai, ZhuoZhi; Xiao, Gang; Wu, Renhua

2014-01-01

Chemical exchange saturation transfer (CEST) MRI is sensitive to dilute proteins and peptides as well as microenvironmental properties. However, the complexity of the CEST MRI effect, which varies with the labile proton content, exchange rate and experimental conditions, underscores the need for developing quantitative CEST (qCEST) analysis. Towards this goal, it has been shown that omega plot is capable of quantifying paramagnetic CEST MRI. However, the use of the omega plot is somewhat limited for diamagnetic CEST (DIACEST) MRI because it is more susceptible to direct radio frequency (RF) saturation (spillover) owing to the relatively small chemical shift. Recently, it has been found that, for dilute DIACEST agents that undergo slow to intermediate chemical exchange, the spillover effect varies little with the labile proton ratio and exchange rate. Therefore, we postulated that the omega plot analysis can be improved if RF spillover effect could be estimated and taken into account. Specifically, simulation showed that both labile proton ratio and exchange rate derived using the spillover effect-corrected omega plot were in good agreement with simulated values. In addition, the modified omega plot was confirmed experimentally, and we showed that the derived labile proton ratio increased linearly with creatine concentration (p < 0.01), with little difference in their exchange rate (p = 0.32). In summary, our study extends the conventional omega plot for quantitative analysis of DIACEST MRI. Copyright © 2014 John Wiley & Sons, Ltd.
High-fidelity meshes from tissue samples for diffusion MRI simulations.

PubMed

Panagiotaki, Eleftheria; Hall, Matt G; Zhang, Hui; Siow, Bernard; Lythgoe, Mark F; Alexander, Daniel C

2010-01-01

This paper presents a method for constructing detailed geometric models of tissue microstructure for synthesizing realistic diffusion MRI data. We construct three-dimensional mesh models from confocal microscopy image stacks using the marching cubes algorithm. Random-walk simulations within the resulting meshes provide synthetic diffusion MRI measurements. Experiments optimise simulation parameters and complexity of the meshes to achieve accuracy and reproducibility while minimizing computation time. Finally we assess the quality of the synthesized data from the mesh models by comparison with scanner data as well as synthetic data from simple geometric models and simplified meshes that vary only in two dimensions. The results support the extra complexity of the three-dimensional mesh compared to simpler models although sensitivity to the mesh resolution is quite robust.
Interleaved EPI based fMRI improved by multiplexed sensitivity encoding (MUSE) and simultaneous multi-band imaging.

PubMed

Chang, Hing-Chiu; Gaur, Pooja; Chou, Ying-hui; Chu, Mei-Lan; Chen, Nan-kuei

2014-01-01

Functional magnetic resonance imaging (fMRI) is a non-invasive and powerful imaging tool for detecting brain activities. The majority of fMRI studies are performed with single-shot echo-planar imaging (EPI) due to its high temporal resolution. Recent studies have demonstrated that, by increasing the spatial-resolution of fMRI, previously unidentified neuronal networks can be measured. However, it is challenging to improve the spatial resolution of conventional single-shot EPI based fMRI. Although multi-shot interleaved EPI is superior to single-shot EPI in terms of the improved spatial-resolution, reduced geometric distortions, and sharper point spread function (PSF), interleaved EPI based fMRI has two main limitations: 1) the imaging throughput is lower in interleaved EPI; 2) the magnitude and phase signal variations among EPI segments (due to physiological noise, subject motion, and B0 drift) are translated to significant in-plane aliasing artifact across the field of view (FOV). Here we report a method that integrates multiple approaches to address the technical limitations of interleaved EPI-based fMRI. Firstly, the multiplexed sensitivity-encoding (MUSE) post-processing algorithm is used to suppress in-plane aliasing artifacts resulting from time-domain signal instabilities during dynamic scans. Secondly, a simultaneous multi-band interleaved EPI pulse sequence, with a controlled aliasing scheme incorporated, is implemented to increase the imaging throughput. Thirdly, the MUSE algorithm is then generalized to accommodate fMRI data obtained with our multi-band interleaved EPI pulse sequence, suppressing both in-plane and through-plane aliasing artifacts. The blood-oxygenation-level-dependent (BOLD) signal detectability and the scan throughput can be significantly improved for interleaved EPI-based fMRI. Our human fMRI data obtained from 3 Tesla systems demonstrate the effectiveness of the developed methods. It is expected that future fMRI studies requiring high spatial-resolvability and fidelity will largely benefit from the reported techniques.
Pairwise Classifier Ensemble with Adaptive Sub-Classifiers for fMRI Pattern Analysis.

PubMed

Kim, Eunwoo; Park, HyunWook

2017-02-01

The multi-voxel pattern analysis technique is applied to fMRI data for classification of high-level brain functions using pattern information distributed over multiple voxels. In this paper, we propose a classifier ensemble for multiclass classification in fMRI analysis, exploiting the fact that specific neighboring voxels can contain spatial pattern information. The proposed method converts the multiclass classification to a pairwise classifier ensemble, and each pairwise classifier consists of multiple sub-classifiers using an adaptive feature set for each class-pair. Simulated and real fMRI data were used to verify the proposed method. Intra- and inter-subject analyses were performed to compare the proposed method with several well-known classifiers, including single and ensemble classifiers. The comparison results showed that the proposed method can be generally applied to multiclass classification in both simulations and real fMRI analyses.
Respiratory motion-resolved, self-gated 4D-MRI using Rotating Cartesian K-space (ROCK): Initial clinical experience on an MRI-guided radiotherapy system.

PubMed

Han, Fei; Zhou, Ziwu; Du, Dongsu; Gao, Yu; Rashid, Shams; Cao, Minsong; Shaverdian, Narek; Hegde, John V; Steinberg, Michael; Lee, Percy; Raldow, Ann; Low, Daniel A; Sheng, Ke; Yang, Yingli; Hu, Peng

2018-06-01

To optimize and evaluate the respiratory motion-resolved, self-gated 4D-MRI using Rotating Cartesian K-space (ROCK-4D-MRI) method in a 0.35 T MRI-guided radiotherapy (MRgRT) system. The study included seven patients with abdominal tumors treated on the MRgRT system. ROCK-4D-MRI and 2D-CINE, was performed immediately after one of the treatment fractions. Motion quantification based on 4D-MRI was compared with those based on 2D-CINE. The image quality of 4D-MRI was evaluated against 4D-CT. The gross tumor volumes (GTV) were defined based on individual respiratory phases of both 4D-MRI and 4D-CT and compared for their variability over the respiratory cycle. The motion measurements based on 4D-MRI matched well with 2D-CINE, with differences of 1.04 ± 0.52 mm in the superior-inferior and 0.54 ± 0.21 mm in the anterior-posterior directions. The image quality scores of 4D-MRI were significantly higher than 4D-CT, with better tumor contrast (3.29 ± 0.76 vs. 1.86 ± 0.90) and less motion artifacts (3.57 ± 0.53 vs. 2.29 ± 0.95). The GTVs were more consistent in 4D-MRI than in 4D-CT, with significantly smaller GTV variability (9.31 ± 4.58% vs. 34.27 ± 23.33%). Our study demonstrated the clinical feasibility of using the ROCK-4D-MRI to acquire high quality, respiratory motion-resolved 4D-MRI in a low-field MRgRT system. The 4D-MRI image could provide accurate dynamic information for radiotherapy treatment planning. Copyright © 2018 Elsevier B.V. All rights reserved.
The effect of resolution on viscous dissipation measured with 4D flow MRI in patients with Fontan circulation: Evaluation using computational fluid dynamics

PubMed Central

Cibis, Merih; Jarvis, Kelly; Markl, Michael; Rose, Michael; Rigsby, Cynthia; Barker, Alex J.; Wentzel, Jolanda J.

2016-01-01

Viscous dissipation inside Fontan circulation, a parameter associated with the exercise intolerance of Fontan patients, can be derived from computational fluid dynamics (CFD) or 4D flow MRI velocities. However, the impact of spatial resolution and measurement noise on the estimation of viscous dissipation is unclear. Our aim was to evaluate the influence of these parameters on viscous dissipation calculation. Six Fontan patients underwent whole heart 4D flow MRI. Subject-specific CFD simulations were performed. The CFD velocities were down-sampled to isotropic spatial resolutions of 0.5 mm, 1 mm, 2 mm and to MRI resolution. Viscous dissipation was compared between (1) high resolution CFD velocities, (2) CFD velocities down-sampled to MRI resolution, (3) down-sampled CFD velocities with MRI mimicked noise levels, and (4) in-vivo 4D flow MRI velocities. Relative viscous dissipation between subjects was also calculated. 4D flow MRI velocities (15.6±3.8 cm/s) were higher, although not significantly different than CFD velocities (13.8±4.7 cm/s, p=0.16), down-sampled CFD velocities (12.3±4.4 cm/s, p=0.06) and the down-sampled CFD velocities with noise (13.2±4.2 cm/s, p=0.06). CFD-based viscous dissipation (0.81±0.55 mW) was significantly higher than those based on down-sampled CFD (0.25±0.19 mW, p=0.03), down-sampled CFD with noise (0.49±0.26 mW, p=0.03) and 4D flow MRI (0.56±0.28 mW, p=0.06). Nevertheless, relative viscous dissipation between different subjects was maintained irrespective of resolution and noise, suggesting that comparison of viscous dissipation between patients is still possible. PMID:26298492
Seasonal and interannual variability of carbon monoxide based on MOZAIC observations, MACC reanalysis, and model simulations over an urban site in India

NASA Astrophysics Data System (ADS)

Sheel, Varun; Sahu, L. K.; Kajino, M.; Deushi, M.; Stein, O.; Nedelec, P.

2014-07-01

The spatial and temporal variations of carbon monoxide (CO) are analyzed over a tropical urban site, Hyderabad (17°27'N, 78°28'E) in central India. We have used vertical profiles from the Measurement of ozone and water vapor by Airbus in-service aircraft (MOZAIC) aircraft observations, Monitoring Atmospheric Composition and Climate (MACC) reanalysis, and two chemical transport model simulations (Model for Ozone And Related Tracers (MOZART) and MRI global Chemistry Climate Model (MRI-CCM2)) for the years 2006-2008. In the lower troposphere, the CO mixing ratio showed strong seasonality, with higher levels (>300 ppbv) during the winter and premonsoon seasons associated with a stable anticyclonic circulation, while lower CO values (up to 100 ppbv) were observed in the monsoon season. In the planetary boundary layer (PBL), the seasonal distribution of CO shows the impact of both local meteorology and emissions. While the PBL CO is predominantly influenced by strong winds, bringing regional background air from marine and biomass burning regions, under calm conditions CO levels are elevated by local emissions. On the other hand, in the free troposphere, seasonal variation reflects the impact of long-range transport associated with the Intertropical Convergence Zone and biomass burning. The interannual variations were mainly due to transition from El Niño to La Niña conditions. The overall modified normalized mean biases (normalization based on the observed and model mean values) with respect to the observed CO profiles were lower for the MACC reanalysis than the MOZART and MRI-CCM2 models. The CO in the PBL region was consistently underestimated by MACC reanalysis during all the seasons, while MOZART and MRI-CCM2 show both positive and negative biases depending on the season.
MRI for the detection of calcific features of vertebral haemangioma.

PubMed

Bender, Y Y; Böker, S M; Diederichs, G; Walter, T; Wagner, M; Fallenberg, E; Liebig, T; Rickert, M; Hamm, B; Makowski, M R

2017-08-01

To evaluate the diagnostic performance of susceptibility-weighted-magnetic-resonance imaging (SW-MRI) for the detection of vertebral haemangiomas (VHs) compared to T1/T2-weighted MRI sequences, radiographs, and computed tomography (CT). The study was approved by the local ethics review board. An SW-MRI sequence was added to the clinical spine imaging protocol. The image-based diagnosis of 56 VHs in 46 patients was established using T1/T2 MRI in combination with radiography/CT as the reference standard. VHs were assessed based on T1/T2-weighted MRI images alone and in combination with SW-MRI, while radiographs/CT images were excluded from the analysis. Fifty-one of 56 VHs could be identified on T1/T2 MRI images alone, if radiographs/CT images were excluded from analysis. In five cases (9.1%), additional radiographs/CT images were required for the imaging-based diagnosis. If T1/T2 and SW-MRI images were used in combination, all VHs could be diagnosed, without the need for radiography/CT. Size measurements revealed a close correlation between CT and SW-MRI (R 2 =0.94; p<0.05). This study demonstrates that SW-MRI enables reliable detection of the typical calcified features of VHs. This is of importance for routine MRI of the spine, as the use of additional CT/radiography can be minimized. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
Pharmacological MRI (phMRI) of the Human Central Nervous System.

PubMed

Lanfermann, H; Schindler, C; Jordan, J; Krug, N; Raab, P

2015-10-01

Pharmacological magnetic resonance imaging (phMRI) of the central nervous system (CNS) addresses the increasing demands in the biopharma industry for new methods that can accurately predict, as early as possible, whether novel CNS agents will be effective and safe. Imaging of physiological and molecular-level function can provide a more direct measure of a drug mechanism of action, enabling more predictive measures of drug activity. The availability of phMRI of the nervous system within the professional infrastructure of the Clinical Research Center (CRC) Hannover as proof of concept center ensures that advances in basic science progress swiftly into benefits for patients. Advanced standardized MRI techniques including quantitative MRI, kurtosis determination, functional MRI, and spectroscopic imaging of the entire brain are necessary for phMRI. As a result, MR scanners will evolve into high-precision measuring instruments for assessment of desirable and undesirable effects of drugs as the basic precondition for individually tailored therapy. The CRC's Imaging Unit with high-end large-scale equipment will allow the following unique opportunities: for example, identification of MR-based biomarkers to assess the effect of drugs (surrogate parameters), establishment of normal levels and reference ranges for MRI-based biomarkers, evaluation of the most relevant MRI sequences for drug monitoring in outpatient care. Another very important prerequisite for phMRI is the MHH Core Facility as the scientific and operational study unit of the CRC partner Hannover Medical School. This unit is responsible for the study coordination, conduction, complete study logistics, administration, and application of the quality assurance system based on required industry standards.
SU-D-207A-07: The Effects of Inter-Cycle Respiratory Motion Variation On Dose Accumulation in Single Fraction MR-Guided SBRT Treatment of Renal Cell Carcinoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stemkens, B; Glitzner, M; Kontaxis, C

Purpose: To assess the dose deposition in simulated single-fraction MR-Linac treatments of renal cell carcinoma, when inter-cycle respiratory motion variation is taken into account using online MRI. Methods: Three motion characterization methods, with increasing complexity, were compared to evaluate the effect of inter-cycle motion variation and drifts on the accumulated dose for an SBRT kidney MR-Linac treatment: 1) STATIC, in which static anatomy was assumed, 2) AVG-RESP, in which 4D-MRI phase-volumes were time-weighted, based on the respiratory phase and 3) PCA, in which 3D volumes were generated using a PCA-model, enabling the detection of inter-cycle variations and drifts. An experimentalmore » ITV-based kidney treatment was simulated in a 1.5T magnetic field on three volunteer datasets. For each volunteer a retrospectively sorted 4D-MRI (ten respiratory phases) and fast 2D cine-MR images (temporal resolution = 476ms) were acquired to simulate MR-imaging during radiation. For each method, the high spatio-temporal resolution 3D volumes were non-rigidly registered to obtain deformation vector fields (DVFs). Using the DVFs, pseudo-CTs (generated from the 4D-MRI) were deformed and the dose was accumulated for the entire treatment. The accuracies of all methods were independently determined using an additional, orthogonal 2D-MRI slice. Results: Motion was most accurately estimated using the PCA method, which correctly estimated drifts and inter-cycle variations (RMSE=3.2, 2.2, 1.1mm on average for STATIC, AVG-RESP and PCA, compared to the 2DMRI slice). Dose-volume parameters on the ITV showed moderate changes (D99=35.2, 32.5, 33.8Gy for STATIC, AVG-RESP and PCA). AVG-RESP showed distinct hot/cold spots outside the ITV margin, which were more distributed for the PCA scenario, since inter-cycle variations were not modeled by the AVG-RESP method. Conclusion: Dose differences were observed when inter-cycle variations were taken into account. The increased inter-cycle randomness in motion as captured by the PCA model mitigates the local (erroneous) hotspots estimated by the AVG-RESP method.« less
Head-to-Head Comparison of Chest X-Ray/Head and Neck MRI, Chest CT/Head and Neck MRI, and 18F-FDG PET/CT for Detection of Distant Metastases and Synchronous Cancer in Oral, Pharyngeal, and Laryngeal Cancer.

PubMed

Rohde, Max; Nielsen, Anne L; Johansen, Jørgen; Sørensen, Jens A; Nguyen, Nina; Diaz, Anabel; Nielsen, Mie K; Asmussen, Jon T; Christiansen, Janus M; Gerke, Oke; Thomassen, Anders; Alavi, Abass; Høilund-Carlsen, Poul Flemming; Godballe, Christian

2017-12-01

The purpose of this study was to determine the detection rate of distant metastasis and synchronous cancer, comparing clinically used imaging strategies based on chest x-ray + head and neck MRI (CXR/MRI) and chest CT + head and neck MRI (CHCT/MRI) with 18 F-FDG PET/CT upfront in the diagnostic workup of patients with oral, pharyngeal, or laryngeal cancer. Methods: This was a prospective cohort study based on paired data. Consecutive patients with histologically verified primary head and squamous cell carcinoma at Odense University Hospital from September 2013 to March 2016 were considered for the study. Included patients underwent CXR/MRI and CHCT/MRI as well as PET/CT on the same day and before biopsy. Scans were read masked by separate teams of experienced nuclear physicians or radiologists. The true detection rate of distant metastasis and synchronous cancer was assessed for CXR/MRI, CHCT/MRI, and PET/CT. Results: A total of 307 patients were included. CXR/MRI correctly detected 3 (1%) patients with distant metastasis, CHCT/MRI detected 11 (4%) patients, and PET/CT detected 18 (6%) patients. The absolute differences of 5% and 2%, respectively, were statistically significant in favor of PET/CT. Also, PET/CT correctly detected 25 (8%) synchronous cancers, which was significantly more than CXR/MRI (3 patients, 1%) and CHCT/MRI (6 patients, 2%). The true detection rate of distant metastasis or synchronous cancer with PET/CT was 13% (40 patients), which was significantly higher than 2% (6 patients) for CXR/MRI and 6% (17 patients) for CHCT/MRI. Conclusion: A clinical imaging strategy based on PET/CT demonstrated a significantly higher detection rate of distant metastasis or synchronous cancer than strategies in current clinical imaging guidelines, of which European ones primarily recommend CXR/MRI, whereas U.S. guidelines preferably point to CHCT/MRI in patients with head and neck squamous cell carcinoma. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.
Multiparametric imaging with heterogeneous radiofrequency fields

NASA Astrophysics Data System (ADS)

Cloos, Martijn A.; Knoll, Florian; Zhao, Tiejun; Block, Kai T.; Bruno, Mary; Wiggins, Graham C.; Sodickson, Daniel K.

2016-08-01

Magnetic resonance imaging (MRI) has become an unrivalled medical diagnostic technique able to map tissue anatomy and physiology non-invasively. MRI measurements are meticulously engineered to control experimental conditions across the sample. However, residual radiofrequency (RF) field inhomogeneities are often unavoidable, leading to artefacts that degrade the diagnostic and scientific value of the images. Here we show that, paradoxically, these artefacts can be eliminated by deliberately interweaving freely varying heterogeneous RF fields into a magnetic resonance fingerprinting data-acquisition process. Observations made based on simulations are experimentally confirmed at 7 Tesla (T), and the clinical implications of this new paradigm are illustrated with in vivo measurements near an orthopaedic implant at 3T. These results show that it is possible to perform quantitative multiparametric imaging with heterogeneous RF fields, and to liberate MRI from the traditional struggle for control over the RF field uniformity.
Dependency Network Analysis (DEPNA) Reveals Context Related Influence of Brain Network Nodes

PubMed Central

Jacob, Yael; Winetraub, Yonatan; Raz, Gal; Ben-Simon, Eti; Okon-Singer, Hadas; Rosenberg-Katz, Keren; Hendler, Talma; Ben-Jacob, Eshel

2016-01-01

Communication between and within brain regions is essential for information processing within functional networks. The current methods to determine the influence of one region on another are either based on temporal resolution, or require a predefined model for the connectivity direction. However these requirements are not always achieved, especially in fMRI studies, which have poor temporal resolution. We thus propose a new graph theory approach that focuses on the correlation influence between selected brain regions, entitled Dependency Network Analysis (DEPNA). Partial correlations are used to quantify the level of influence of each node during task performance. As a proof of concept, we conducted the DEPNA on simulated datasets and on two empirical motor and working memory fMRI tasks. The simulations revealed that the DEPNA correctly captures the network’s hierarchy of influence. Applying DEPNA to the functional tasks reveals the dynamics between specific nodes as would be expected from prior knowledge. To conclude, we demonstrate that DEPNA can capture the most influencing nodes in the network, as they emerge during specific cognitive processes. This ability opens a new horizon for example in delineating critical nodes for specific clinical interventions. PMID:27271458
Spontaneous low frequency BOLD signal variations from resting-state fMRI are decreased in Alzheimer disease

PubMed Central

Manning, Kathryn Y.; Rajakumar, Nagalingam; Gómez, Francisco A.; Soddu, Andrea; Borrie, Michael J.

2017-01-01

Previous studies have demonstrated altered brain activity in Alzheimer's disease using task based functional MRI (fMRI), network based resting-state fMRI, and glucose metabolism from 18F fluorodeoxyglucose-PET (FDG-PET). Our goal was to define a novel indicator of neuronal activity based on a first-order textural feature of the resting state functional MRI (RS-fMRI) signal. Furthermore, we examined the association between this neuronal activity metric and glucose metabolism from 18F FDG-PET. We studied 15 normal elderly controls (NEC) and 15 probable Alzheimer disease (AD) subjects from the AD Neuroimaging Initiative. An independent component analysis was applied to the RS-fMRI, followed by template matching to identify neuronal components (NC). A regional brain activity measurement was constructed based on the variation of the RS-fMRI signal of these NC. The standardized glucose uptake values of several brain regions relative to the cerebellum (SUVR) were measured from partial volume corrected FDG-PET images. Comparing the AD and NEC groups, the mean brain activity metric was significantly lower in the accumbens, while the glucose SUVR was significantly lower in the amygdala and hippocampus. The RS-fMRI brain activity metric was positively correlated with cognitive measures and amyloid β1–42 cerebral spinal fluid levels; however, these did not remain significant following Bonferroni correction. There was a significant linear correlation between the brain activity metric and the glucose SUVR measurements. This proof of concept study demonstrates that this novel and easy to implement RS-fMRI brain activity metric can differentiate a group of healthy elderly controls from a group of people with AD. PMID:28582450
Spontaneous low frequency BOLD signal variations from resting-state fMRI are decreased in Alzheimer disease.

PubMed

Kazemifar, Samaneh; Manning, Kathryn Y; Rajakumar, Nagalingam; Gómez, Francisco A; Soddu, Andrea; Borrie, Michael J; Menon, Ravi S; Bartha, Robert

2017-01-01

Previous studies have demonstrated altered brain activity in Alzheimer's disease using task based functional MRI (fMRI), network based resting-state fMRI, and glucose metabolism from 18F fluorodeoxyglucose-PET (FDG-PET). Our goal was to define a novel indicator of neuronal activity based on a first-order textural feature of the resting state functional MRI (RS-fMRI) signal. Furthermore, we examined the association between this neuronal activity metric and glucose metabolism from 18F FDG-PET. We studied 15 normal elderly controls (NEC) and 15 probable Alzheimer disease (AD) subjects from the AD Neuroimaging Initiative. An independent component analysis was applied to the RS-fMRI, followed by template matching to identify neuronal components (NC). A regional brain activity measurement was constructed based on the variation of the RS-fMRI signal of these NC. The standardized glucose uptake values of several brain regions relative to the cerebellum (SUVR) were measured from partial volume corrected FDG-PET images. Comparing the AD and NEC groups, the mean brain activity metric was significantly lower in the accumbens, while the glucose SUVR was significantly lower in the amygdala and hippocampus. The RS-fMRI brain activity metric was positively correlated with cognitive measures and amyloid β1-42 cerebral spinal fluid levels; however, these did not remain significant following Bonferroni correction. There was a significant linear correlation between the brain activity metric and the glucose SUVR measurements. This proof of concept study demonstrates that this novel and easy to implement RS-fMRI brain activity metric can differentiate a group of healthy elderly controls from a group of people with AD.
Intervertebral disc biomechanical analysis using the finite element modeling based on medical images.

PubMed

Li, Haiyun; Wang, Zheng

2006-01-01

In this paper, a 3D geometric model of the intervertebral and lumbar disks has been presented, which integrated the spine CT and MRI data-based anatomical structure. Based on the geometric model, a 3D finite element model of an L1-L2 segment was created. Loads, which simulate the pressure from above were applied to the FEM, while a boundary condition describing the relative L1-L2 displacement is imposed on the FEM to account for 3D physiological states. The simulation calculation illustrates the stress and strain distribution and deformation of the spine. The method has two characteristics compared to previous studies: first, the finite element model of the lumbar are based on the data directly derived from medical images such as CTs and MRIs. Second, the result of analysis will be more accurate than using the data of geometric parameters. The FEM provides a promising tool in clinical diagnosis and for optimizing individual therapy in the intervertebral disc herniation.
Dynamic Granger causality based on Kalman filter for evaluation of functional network connectivity in fMRI data

PubMed Central

Havlicek, Martin; Jan, Jiri; Brazdil, Milan; Calhoun, Vince D.

2015-01-01

Increasing interest in understanding dynamic interactions of brain neural networks leads to formulation of sophisticated connectivity analysis methods. Recent studies have applied Granger causality based on standard multivariate autoregressive (MAR) modeling to assess the brain connectivity. Nevertheless, one important flaw of this commonly proposed method is that it requires the analyzed time series to be stationary, whereas such assumption is mostly violated due to the weakly nonstationary nature of functional magnetic resonance imaging (fMRI) time series. Therefore, we propose an approach to dynamic Granger causality in the frequency domain for evaluating functional network connectivity in fMRI data. The effectiveness and robustness of the dynamic approach was significantly improved by combining a forward and backward Kalman filter that improved estimates compared to the standard time-invariant MAR modeling. In our method, the functional networks were first detected by independent component analysis (ICA), a computational method for separating a multivariate signal into maximally independent components. Then the measure of Granger causality was evaluated using generalized partial directed coherence that is suitable for bivariate as well as multivariate data. Moreover, this metric provides identification of causal relation in frequency domain, which allows one to distinguish the frequency components related to the experimental paradigm. The procedure of evaluating Granger causality via dynamic MAR was demonstrated on simulated time series as well as on two sets of group fMRI data collected during an auditory sensorimotor (SM) or auditory oddball discrimination (AOD) tasks. Finally, a comparison with the results obtained from a standard time-invariant MAR model was provided. PMID:20561919

[Injection Pressure Evaluation of the New Venous Catheter with Side Holes for Contrast-enhanced CT/MRI].

PubMed

Fukuda, Junya; Arai, Keisuke; Miyazawa, Hitomi; Kobayashi, Kyouko; Nakamura, Junpei; Suto, Takayuki; Tsushima, Yoshito

2018-01-01

The simulation study was conducted for the new venous catheter with side holes of contrast-enhanced computed tomography (CT) and magnetic resonance imaging (MRI) to evaluate the infusion pressure on four contrast media and several injection speeds. All infusion pressure of the new venous catheter with side holes were less than 15 kg/cm 2 as limitation of extension tube and also reduced the infusion pressure by 15% at the maximum compared to the catheter with single hole. The results suggest that the new venous catheter with side holes can reduce the infusion pressure by power injection of contrast-enhanced CT and MRI.
Improving the realism of white matter numerical phantoms: a step towards a better understanding of the influence of structural disorders in diffusion MRI

NASA Astrophysics Data System (ADS)

Ginsburger, Kévin; Poupon, Fabrice; Beaujoin, Justine; Estournet, Delphine; Matuschke, Felix; Mangin, Jean-François; Axer, Markus; Poupon, Cyril

2018-02-01

White matter is composed of irregularly packed axons leading to a structural disorder in the extra-axonal space. Diffusion MRI experiments using oscillating gradient spin echo sequences have shown that the diffusivity transverse to axons in this extra-axonal space is dependent on the frequency of the employed sequence. In this study, we observe the same frequency-dependence using 3D simulations of the diffusion process in disordered media. We design a novel white matter numerical phantom generation algorithm which constructs biomimicking geometric configurations with few design parameters, and enables to control the level of disorder of the generated phantoms. The influence of various geometrical parameters present in white matter, such as global angular dispersion, tortuosity, presence of Ranvier nodes, beading, on the extra-cellular perpendicular diffusivity frequency dependence was investigated by simulating the diffusion process in numerical phantoms of increasing complexity and fitting the resulting simulated diffusion MR signal attenuation with an adequate analytical model designed for trapezoidal OGSE sequences. This work suggests that angular dispersion and especially beading have non-negligible effects on this extracellular diffusion metrics that may be measured using standard OGSE DW-MRI clinical protocols.
MRI-based score helps in assessing the severity and in follow-up of pediatric patients with perianal Crohn disease.

PubMed

Kulkarni, Sakil; Gomara, Roberto; Reeves-Garcia, Jesse; Hernandez, Erick; Restrepo, Ricardo

2014-02-01

The radiologic healing of perianal fistulizing Crohn disease (PfCD) lags behind the clinical healing. Contrast-enhanced pelvic magnetic resonance imaging (MRI) is the radiologic study of choice used to diagnose PfCD in children. The aim was to study whether the various MRI-based radiologic parameters and score can help in staging and follow-up of patients with PfCD. We performed a retrospective chart review of children with PfCD who underwent contrast-enhanced MRI of the pelvis. The demographic profile, clinical status, and laboratory data of the patients at the time of each MRI examination were noted. Based on the clinical status of the patient at the time of MRI examinations, the MRIs were classified into 3 groups: severe disease, mild-to-moderate disease, and asymptomatic. Each MRI examination was reviewed by a radiologist, who was blinded to the clinical status of the patient. Of the radiologic parameters, the number of fistulas, the complexity of fistulas, and the number of abscesses were significantly lower in the asymptomatic group compared with the mild-to-moderate and severe disease groups. The Van Assche MRI-based score was significantly lower in the asymptomatic group compared with the mild-to-moderate disease (P = 0.01) and the severe disease group (P = 0.002). The percentage increase in fistula activity after gadolinium administration was significantly lower in the asymptomatic group compared with the mild-to-moderate disease (P = 0.026) and severe disease (P = 0.019) groups. The MRI-based scores were significantly higher in the MRI examinations performed at diagnosis compared with those that were performed while the patients were receiving the treatment (P = 0.017). The Van Assche MRI score and the percentage increase in fistula activity after gadolinium administration help in assessing the severity perianal Crohn disease. The Van Assche MRI score may be helpful in documenting healing during therapy of perianal Crohn disease.
On the feasibility of concurrent human TMS-EEG-fMRI measurements

PubMed Central

Reithler, Joel; Schuhmann, Teresa; de Graaf, Tom; Uludağ, Kâmil; Goebel, Rainer; Sack, Alexander T.

2013-01-01

Simultaneously combining the complementary assets of EEG, functional MRI (fMRI), and transcranial magnetic stimulation (TMS) within one experimental session provides synergetic results, offering insights into brain function that go beyond the scope of each method when used in isolation. The steady increase of concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI studies further underlines the added value of such multimodal imaging approaches. Whereas concurrent EEG-fMRI enables monitoring of brain-wide network dynamics with high temporal and spatial resolution, the combination with TMS provides insights in causal interactions within these networks. Thus the simultaneous use of all three methods would allow studying fast, spatially accurate, and distributed causal interactions in the perturbed system and its functional relevance for intact behavior. Concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI experiments are already technically challenging, and the three-way combination of TMS-EEG-fMRI might yield additional difficulties in terms of hardware strain or signal quality. The present study explored the feasibility of concurrent TMS-EEG-fMRI studies by performing safety and quality assurance tests based on phantom and human data combining existing commercially available hardware. Results revealed that combined TMS-EEG-fMRI measurements were technically feasible, safe in terms of induced temperature changes, allowed functional MRI acquisition with comparable image quality as during concurrent EEG-fMRI or TMS-fMRI, and provided artifact-free EEG before and from 300 ms after TMS pulse application. Based on these empirical findings, we discuss the conceptual benefits of this novel complementary approach to investigate the working human brain and list a number of precautions and caveats to be heeded when setting up such multimodal imaging facilities with current hardware. PMID:23221407
Topological Distances Between Brain Networks

PubMed Central

Lee, Hyekyoung; Solo, Victor; Davidson, Richard J.; Pollak, Seth D.

2018-01-01

Many existing brain network distances are based on matrix norms. The element-wise differences may fail to capture underlying topological differences. Further, matrix norms are sensitive to outliers. A few extreme edge weights may severely affect the distance. Thus it is necessary to develop network distances that recognize topology. In this paper, we introduce Gromov-Hausdorff (GH) and Kolmogorov-Smirnov (KS) distances. GH-distance is often used in persistent homology based brain network models. The superior performance of KS-distance is contrasted against matrix norms and GH-distance in random network simulations with the ground truths. The KS-distance is then applied in characterizing the multimodal MRI and DTI study of maltreated children.
Analysis of eddy currents induced by transverse and longitudinal gradient coils in different tungsten collimators geometries for SPECT/MRI integration.

PubMed

Samoudi, Amine M; Van Audenhaege, Karen; Vermeeren, Günter; Poole, Michael; Tanghe, Emmeric; Martens, Luc; Van Holen, Roel; Joseph, Wout

2015-12-01

We investigated the temporal variation of the induced magnetic field due to the transverse and the longitudinal gradient coils in tungsten collimators arranged in hexagonal and pentagonal geometries with and without gaps between the collimators. We modeled x-, y-, and z-gradient coils and different arrangements of single-photon emission computed tomography (SPECT) collimators using FEKO, a three-dimensional electromagnetic simulation tool. A time analysis approach was used to generate the pulsed magnetic field gradient. The approach was validated with measurements using a 7T MRI scanner. Simulations showed an induced magnetic field representing 4.66% and 0.87% of the applied gradient field (gradient strength = 500 mT/m) for longitudinal and transverse gradient coils, respectively. These values can be reduced by 75% by adding gaps between the collimators for the pentagonal arrangement, bringing the maximum induced magnetic field to less than 2% of the applied gradient for all of the gradient coils. Characterization of the maximum induced magnetic field shows that by adding gaps between the collimators for an integrated SPECT/MRI system, eddy currents can be corrected by the MRI system to avoid artifact. The numerical model was validated and was proposed as a tool for studying the effect of a SPECT collimator within the MRI gradient coils. © 2014 Wiley Periodicals, Inc.
Wireless Medical Devices for MRI-Guided Interventions

NASA Astrophysics Data System (ADS)

Venkateswaran, Madhav

Wireless techniques can play an important role in next-generation, image-guided surgical techniques with integration strategies being the key. We present our investigations on three wireless applications. First, we validate a position and orientation independent method to noninvasively monitor wireless power delivery using current perturbation measurements of switched load modulation of the RF carrier. This is important for safe and efficient powering without using bulky batteries or invasive cables. Use of MRI transmit RF pulses for simultaneous powering is investigated in the second part. We develop system models for the MRI transmit chain, wireless powering circuits and a typical load. Detailed analysis and validation of nonlinear and cascaded modeling strategies are performed, useful for decoupled optimization of the harvester coil and RF-DC converter. MRI pulse sequences are investigated for suitability for simultaneous powering. Simulations indicate that a 1.8V, 2 mA load can be powered with a 100% duty cycle using a 30° fGRE sequence, despite the RF duty cycle being 44 mW for a 30° flip angle, consistent with model predictions. Investigations on imaging artifacts indicates that distortion is mostly restricted to within the physical span of the harvester coil in the imaging volume, with the homogeneous B1+ transmit field providing positioning flexibility to minimize this for simultaneous powering. The models are potentially valuable in designing wireless powering solutions for implantable devices with simultaneous real-time imaging in MRI-guided surgical suites. Finally in the last section, we model endovascular MRI coil coupling during RF transmit. FEM models for a series-resonant multimode coil and quadrature birdcage coil fields are developed and computationally efficient, circuit and full-wave simulations are used to model inductive coupling. The Bloch Siegert B1 mapping sequence is used for validating at 24, 28 and 34 microT background excitation. Quantitative performance metrics are successfully predicted and the role of simulation in geometric optimization is demonstrated. In a pig study, we demonstrate navigation of a catheter, with tip-tracking and high-resolution intravascular imaging, through the vasculature into the heart, followed by contextual visualization. A potentially significant application is in MRI-guided cardiac ablation procedures.
Patch-based generation of a pseudo CT from conventional MRI sequences for MRI-only radiotherapy of the brain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andreasen, Daniel, E-mail: dana@dtu.dk; Van Leemput, Koen; Hansen, Rasmus H.

Purpose: In radiotherapy (RT) based on magnetic resonance imaging (MRI) as the only modality, the information on electron density must be derived from the MRI scan by creating a so-called pseudo computed tomography (pCT). This is a nontrivial task, since the voxel-intensities in an MRI scan are not uniquely related to electron density. To solve the task, voxel-based or atlas-based models have typically been used. The voxel-based models require a specialized dual ultrashort echo time MRI sequence for bone visualization and the atlas-based models require deformable registrations of conventional MRI scans. In this study, we investigate the potential of amore » patch-based method for creating a pCT based on conventional T{sub 1}-weighted MRI scans without using deformable registrations. We compare this method against two state-of-the-art methods within the voxel-based and atlas-based categories. Methods: The data consisted of CT and MRI scans of five cranial RT patients. To compare the performance of the different methods, a nested cross validation was done to find optimal model parameters for all the methods. Voxel-wise and geometric evaluations of the pCTs were done. Furthermore, a radiologic evaluation based on water equivalent path lengths was carried out, comparing the upper hemisphere of the head in the pCT and the real CT. Finally, the dosimetric accuracy was tested and compared for a photon treatment plan. Results: The pCTs produced with the patch-based method had the best voxel-wise, geometric, and radiologic agreement with the real CT, closely followed by the atlas-based method. In terms of the dosimetric accuracy, the patch-based method had average deviations of less than 0.5% in measures related to target coverage. Conclusions: We showed that a patch-based method could generate an accurate pCT based on conventional T{sub 1}-weighted MRI sequences and without deformable registrations. In our evaluations, the method performed better than existing voxel-based and atlas-based methods and showed a promising potential for RT of the brain based only on MRI.« less
Inter-operator Reliability of Magnetic Resonance Image-Based Computational Fluid Dynamics Prediction of Cerebrospinal Fluid Motion in the Cervical Spine.

PubMed

Martin, Bryn A; Yiallourou, Theresia I; Pahlavian, Soroush Heidari; Thyagaraj, Suraj; Bunck, Alexander C; Loth, Francis; Sheffer, Daniel B; Kröger, Jan Robert; Stergiopulos, Nikolaos

2016-05-01

For the first time, inter-operator dependence of MRI based computational fluid dynamics (CFD) modeling of cerebrospinal fluid (CSF) in the cervical spinal subarachnoid space (SSS) is evaluated. In vivo MRI flow measurements and anatomy MRI images were obtained at the cervico-medullary junction of a healthy subject and a Chiari I malformation patient. 3D anatomies of the SSS were reconstructed by manual segmentation by four independent operators for both cases. CFD results were compared at nine axial locations along the SSS in terms of hydrodynamic and geometric parameters. Intraclass correlation (ICC) assessed the inter-operator agreement for each parameter over the axial locations and coefficient of variance (CV) compared the percentage of variance for each parameter between the operators. Greater operator dependence was found for the patient (0.19 < ICC < 0.99) near the craniovertebral junction compared to the healthy subject (ICC > 0.78). For the healthy subject, hydraulic diameter and Womersley number had the least variance (CV = ~2%). For the patient, peak diastolic velocity and Reynolds number had the smallest variance (CV = ~3%). These results show a high degree of inter-operator reliability for MRI-based CFD simulations of CSF flow in the cervical spine for healthy subjects and a lower degree of reliability for patients with Type I Chiari malformation.
Inter-Operator Dependence of Magnetic Resonance Image-Based Computational Fluid Dynamics Prediction of Cerebrospinal Fluid Motion in the Cervical Spine

PubMed Central

Martin, Bryn A.; Yiallourou, Theresia I.; Pahlavian, Soroush Heidari; Thyagaraj, Suraj; Bunck, Alexander C.; Loth, Francis; Sheffer, Daniel B.; Kröger, Jan Robert; Stergiopulos, Nikolaos

2015-01-01

For the first time, inter-operator dependence of MRI based computational fluid dynamics (CFD) modeling of cerebrospinal fluid (CSF) in the cervical spinal subarachnoid space (SSS) is evaluated. In vivo MRI flow measurements and anatomy MRI images were obtained at the cervico-medullary junction of a healthy subject and a Chiari I malformation patient. 3D anatomies of the SSS were reconstructed by manual segmentation by four independent operators for both cases. CFD results were compared at nine axial locations along the SSS in terms of hydrodynamic and geometric parameters. Intraclass correlation (ICC) assessed the inter-operator agreement for each parameter over the axial locations and coefficient of variance (CV) compared the percentage of variance for each parameter between the operators. Greater operator dependence was found for the patient (0.19 0.78). For the healthy subject, hydraulic diameter and Womersley number had the least variance (CV= ~2%). For the patient, peak diastolic velocity and Reynolds number had the smallest variance (CV= ~3%). These results show a high degree of inter-operator reliability for MRI-based CFD simulations of CSF flow in the cervical spine for healthy subjects and a lower degree of reliability for patients with Type I Chiari malformation. PMID:26446009
Study of ocular transport of drugs released from an intravitreal implant using magnetic resonance imaging.

PubMed

Kim, Hyuncheol; Lizak, Martin J; Tansey, Ginger; Csaky, Karl G; Robinson, Michael R; Yuan, Peng; Wang, Nam Sun; Lutz, Robert J

2005-02-01

Ensuring optimum delivery of therapeutic agents in the eye requires detailed information about the transport mechanisms and elimination pathways available. This knowledge can guide the development of new drug delivery devices. In this study, we investigated the movement of a drug surrogate, Gd-DTPA (Magnevist) released from a polymer-based implant in rabbit vitreous using T1-weighted magnetic resonance imaging (MRI). Intensity values in the MRI data were converted to concentration by comparison with calibration samples. Concentration profiles approaching pseudosteady state showed gradients from the implant toward the retinal surface, suggesting that diffusion was occurring into the retinal-choroidal-scleral (RCS) membrane. Gd-DTPA concentration varied from high values near the implant to lower values distal to the implant. Such regional concentration differences throughout the vitreous may have clinical significance when attempting to treat ubiquitous eye diseases using a single positional implant. We developed a finite element mathematical model of the rabbit eye and compared the MRI experimental concentration data with simulation concentration profiles. The model utilized a diffusion coefficient of Gd-DTPA in the vitreous of 2.8 x 10(-6) cm2 s(-1) and yielded a diffusion coefficient for Gd-DTPA through the simulated composite posterior membrane (representing the retina-choroidsclera membrane) of 6.0 x 10(-8) cm2 s(-1). Since the model membrane was 0.03-cm thick, this resulted in an effective membrane permeability of 2.0 x 10(-6) cm s(-1). Convective movement of Gd-DTPA was shown to have minimal effect on the concentration profiles since the Peclet number was 0.09 for this system.
Efficient gradient calibration based on diffusion MRI.

PubMed

Teh, Irvin; Maguire, Mahon L; Schneider, Jürgen E

2017-01-01

To propose a method for calibrating gradient systems and correcting gradient nonlinearities based on diffusion MRI measurements. The gradient scaling in x, y, and z were first offset by up to 5% from precalibrated values to simulate a poorly calibrated system. Diffusion MRI data were acquired in a phantom filled with cyclooctane, and corrections for gradient scaling errors and nonlinearity were determined. The calibration was assessed with diffusion tensor imaging and independently validated with high resolution anatomical MRI of a second structured phantom. The errors in apparent diffusion coefficients along orthogonal axes ranged from -9.2% ± 0.4% to + 8.8% ± 0.7% before calibration and -0.5% ± 0.4% to + 0.8% ± 0.3% after calibration. Concurrently, fractional anisotropy decreased from 0.14 ± 0.03 to 0.03 ± 0.01. Errors in geometric measurements in x, y and z ranged from -5.5% to + 4.5% precalibration and were likewise reduced to -0.97% to + 0.23% postcalibration. Image distortions from gradient nonlinearity were markedly reduced. Periodic gradient calibration is an integral part of quality assurance in MRI. The proposed approach is both accurate and efficient, can be setup with readily available materials, and improves accuracy in both anatomical and diffusion MRI to within ±1%. Magn Reson Med 77:170-179, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. © 2016 Wiley Periodicals, Inc.
Efficient gradient calibration based on diffusion MRI

PubMed Central

Teh, Irvin; Maguire, Mahon L.

2016-01-01

Purpose To propose a method for calibrating gradient systems and correcting gradient nonlinearities based on diffusion MRI measurements. Methods The gradient scaling in x, y, and z were first offset by up to 5% from precalibrated values to simulate a poorly calibrated system. Diffusion MRI data were acquired in a phantom filled with cyclooctane, and corrections for gradient scaling errors and nonlinearity were determined. The calibration was assessed with diffusion tensor imaging and independently validated with high resolution anatomical MRI of a second structured phantom. Results The errors in apparent diffusion coefficients along orthogonal axes ranged from −9.2% ± 0.4% to + 8.8% ± 0.7% before calibration and −0.5% ± 0.4% to + 0.8% ± 0.3% after calibration. Concurrently, fractional anisotropy decreased from 0.14 ± 0.03 to 0.03 ± 0.01. Errors in geometric measurements in x, y and z ranged from −5.5% to + 4.5% precalibration and were likewise reduced to −0.97% to + 0.23% postcalibration. Image distortions from gradient nonlinearity were markedly reduced. Conclusion Periodic gradient calibration is an integral part of quality assurance in MRI. The proposed approach is both accurate and efficient, can be setup with readily available materials, and improves accuracy in both anatomical and diffusion MRI to within ±1%. Magn Reson Med 77:170–179, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. PMID:26749277
Neurophysiological Basis of Multi-Scale Entropy of Brain Complexity and Its Relationship With Functional Connectivity.

PubMed

Wang, Danny J J; Jann, Kay; Fan, Chang; Qiao, Yang; Zang, Yu-Feng; Lu, Hanbing; Yang, Yihong

2018-01-01

Recently, non-linear statistical measures such as multi-scale entropy (MSE) have been introduced as indices of the complexity of electrophysiology and fMRI time-series across multiple time scales. In this work, we investigated the neurophysiological underpinnings of complexity (MSE) of electrophysiology and fMRI signals and their relations to functional connectivity (FC). MSE and FC analyses were performed on simulated data using neural mass model based brain network model with the Brain Dynamics Toolbox, on animal models with concurrent recording of fMRI and electrophysiology in conjunction with pharmacological manipulations, and on resting-state fMRI data from the Human Connectome Project. Our results show that the complexity of regional electrophysiology and fMRI signals is positively correlated with network FC. The associations between MSE and FC are dependent on the temporal scales or frequencies, with higher associations between MSE and FC at lower temporal frequencies. Our results from theoretical modeling, animal experiment and human fMRI indicate that (1) Regional neural complexity and network FC may be two related aspects of brain's information processing: the more complex regional neural activity, the higher FC this region has with other brain regions; (2) MSE at high and low frequencies may represent local and distributed information processing across brain regions. Based on literature and our data, we propose that the complexity of regional neural signals may serve as an index of the brain's capacity of information processing-increased complexity may indicate greater transition or exploration between different states of brain networks, thereby a greater propensity for information processing.
QUESPOWR MRI: QUantification of Exchange as a function of Saturation Power On the Water Resonance

PubMed Central

Randtke, Edward A.; Pagel, Mark D.; Cárdenas-Rodríguez, Julio

2018-01-01

QUantification of Exchange as a function of Saturation Power On the Water Resonance (QUESPOWR) MRI is a new method that can estimate chemical exchange rates. This method acquires a series of OPARACHEE MRI acquisitions with a range of RF powers for the WALTZ16* pulse train, which are applied on the water resonance. A QUESPOWR plot can be generated from the power dependence of the % water signal, which is similar to a QUESP plot that is generated from CEST MRI acquisition methods with RF saturation applied off-resonance from water. A QUESPOWR plot can be quantitatively analyzed using linear fitting methods to provide estimates of average chemical exchange rates. Analyses of the shapes of QUESPOWR plots can also be used to estimate relative differences in average chemical exchange rates and concentrations of biomolecules. The performance of QUESPOWR MRI was assessed via simulations, an in vitro study with iopamidol, and an in vivo study with a mouse model of mammary carcinoma. The results showed that QUESPOWR MRI is especially sensitive to chemical exchange between water and biomolecules that have intermediate to fast chemical exchange rates and chemical shifts that are close to water, which are notoriously difficult to assess with other CEST MRI methods. In addition, in vivo QUESPOWR MRI detected acidic tumor tissues relative to normal tissues that are pH-neutral, and therefore may be a new paradigm for tumor detection with MRI. PMID:27404128
Preclinical evaluation of a low-frequency transcranial MRI-guided focused ultrasound system in a primate model

NASA Astrophysics Data System (ADS)

McDannold, Nathan; Livingstone, Margaret; Barış Top, Can; Sutton, Jonathan; Todd, Nick; Vykhodtseva, Natalia

2016-11-01

This study investigated thermal ablation and skull-induced heating with a 230 kHz transcranial MRI-guided focused ultrasound (TcMRgFUS) system in nonhuman primates. We evaluated real-time acoustic feedback and aimed to understand whether cavitation contributed to the heating and the lesion formation. In four macaques, we sonicated thalamic targets at acoustic powers of 34-560 W (896-7590 J). Tissue effects evaluated with MRI and histology were compared to MRI-based temperature and thermal dose measurements, acoustic emissions recorded during the experiments, and acoustic and thermal simulations. Peak temperatures ranged from 46 to 57 °C, and lesions were produced in 5/8 sonicated targets. A linear relationship was observed between the applied acoustic energy and both the focal and brain surface heating. Thermal dose thresholds were 15-50 cumulative equivalent minutes at 43 °C, similar to prior studies at higher frequencies. Histology was also consistent with earlier studies of thermal effects in the brain. The system successfully controlled the power level and maintained a low level of cavitation activity. Increased acoustic emissions observed in 3/4 animals occurred when the focal temperature rise exceeded approximately 16 °C. Thresholds for thermally-significant subharmonic and wideband emissions were 129 and 140 W, respectively, corresponding to estimated pressure amplitudes of 2.1 and 2.2 MPa. Simulated focal heating was consistent with the measurements for sonications without thermally-significant acoustic emissions; otherwise it was consistently lower than the measurements. Overall, these results suggest that the lesions were produced by thermal mechanisms. The detected acoustic emissions, however, and their association with heating suggest that cavitation might have contributed to the focal heating. Compared to earlier work with a 670 kHz TcMRgFUS system, the brain surface heating was substantially reduced and the focal heating was higher with this 230 kHz system, suggesting that a reduced frequency can increase the treatment envelope for TcMRgFUS and potentially reduce the risk of skull heating.
Investigating the neural correlates of smoking: Feasibility and results of combining electronic cigarettes with fMRI.

PubMed

Wall, Matthew B; Mentink, Alexander; Lyons, Georgina; Kowalczyk, Oliwia S; Demetriou, Lysia; Newbould, Rexford D

2017-09-12

Cigarette addiction is driven partly by the physiological effects of nicotine, but also by the distinctive sensory and behavioural aspects of smoking, and understanding the neural effects of such processes is vital. There are many practical difficulties associated with subjects smoking in the modern neuroscientific laboratory environment, however electronic cigarettes obviate many of these issues, and provide a close simulation of smoking tobacco cigarettes. We have examined the neural effects of 'smoking' electronic cigarettes with concurrent functional Magnetic Resonance Imaging (fMRI). The results demonstrate the feasibility of using these devices in the MRI environment, and show brain activation in a network of cortical (motor cortex, insula, cingulate, amygdala) and sub-cortical (putamen, thalamus, globus pallidus, cerebellum) regions. Concomitant relative deactivations were seen in the ventral striatum and orbitofrontal cortex. These results reveal the brain processes involved in (simulated) smoking for the first time, and validate a novel approach to the study of smoking, and addiction more generally.
[A study of magnetic shielding design for a magnetic resonance imaging linac system].

PubMed

Zhang, Zheshun; Chen, Wenjing; Qiu, Yang; Zhu, Jianming

2017-12-01

One of the main technical challenges when integrating magnetic resonance imaging (MRI) systems with medical linear accelerator is the strong interference of fringe magnetic fields from the MRI system with the electron beams of linear accelerator, making the linear accelerator not to work properly. In order to minimize the interference of magnetic fields, a magnetic shielding cylinder with an open structure made of high permeability materials is designed. ANSYS Maxwell was used to simulate Helmholtz coil which generate uniform magnetic field instead of the fringe magnetic fields which affect accelerator gun. The parameters of shielding tube, such as permeability, radius, length, side thickness, bottom thickness and fringe magnetic fields strength are simulated, and the data is processed by MATLAB to compare the shielding performance. This article gives out a list of magnetic shielding effectiveness with different side thickness and bottom thickness under the optimal radius and length, which showes that this design can meet the shielding requirement for the MRI-linear accelerator system.
Role of MRI in differentiating various causes of non-traumatic paraparesis and tetraparesis.

PubMed

Ahmed, Nisar; Akram, Hamid; Qureshi, Ishtiaq Ahmed

2004-10-01

To assess the frequency of various causes of non-traumatic paraparesis and tetraparesis in adults based only on the findings of magnetic resonance imaging (MRI). Non-interventional descriptive study carried out from May 2001 to October 2002 at Radiology Department, CMH, Rawalpindi. A total of 100 adult patients who presented with non-traumatic paraparesis or tetraparesis, were studied. MRI spine of all the patients and MRI brain of selected patients, was carried out. Based on MRI findings alone causes of non-traumatic paraparesis and tetraparesis were categorized. Paraparesis was more frequent than tetraparesis. Cord compression was found in 72% cases. Neoplastic compression, infective spondylitis and non-compressive myelopathies were the main causes of paraparesis while spondylotic myelopathy was the main cause of tetraparesis. Based upon MRI findings causes of non-traumatic paraparesis or tetraparesis can be subcategorized into spondylotic, infective or neoplastic cord compression and non-compressive myelopathies. Further subcategorization of neoplastic lesions according to their compartment of origin can also be done.
Evolution of the magnetorotational instability on initially tangled magnetic fields

NASA Astrophysics Data System (ADS)

Bhat, Pallavi; Ebrahimi, Fatima; Blackman, Eric G.; Subramanian, Kandaswamy

2017-12-01

The initial magnetic field of previous magnetorotational instability (MRI) simulations has always included a significant system-scale component, even if stochastic. However, it is of conceptual and practical interest to assess whether the MRI can grow when the initial field is turbulent. The ubiquitous presence of turbulent or random flows in astrophysical plasmas generically leads to a small-scale dynamo (SSD), which would provide initial seed turbulent velocity and magnetic fields in the plasma that becomes an accretion disc. Can the MRI grow from these more realistic initial conditions? To address this, we supply a standard shearing box with isotropically forced SSD generated magnetic and velocity fields as initial conditions and remove the forcing. We find that if the initially supplied fields are too weak or too incoherent, they decay from the initial turbulent cascade faster than they can grow via the MRI. When the initially supplied fields are sufficient to allow MRI growth and sustenance, the saturated stresses, large-scale fields and power spectra match those of the standard zero net flux MRI simulation with an initial large-scale vertical field.

High performance MRI simulations of motion on multi-GPU systems

PubMed Central

2014-01-01

Background MRI physics simulators have been developed in the past for optimizing imaging protocols and for training purposes. However, these simulators have only addressed motion within a limited scope. The purpose of this study was the incorporation of realistic motion, such as cardiac motion, respiratory motion and flow, within MRI simulations in a high performance multi-GPU environment. Methods Three different motion models were introduced in the Magnetic Resonance Imaging SIMULator (MRISIMUL) of this study: cardiac motion, respiratory motion and flow. Simulation of a simple Gradient Echo pulse sequence and a CINE pulse sequence on the corresponding anatomical model was performed. Myocardial tagging was also investigated. In pulse sequence design, software crushers were introduced to accommodate the long execution times in order to avoid spurious echoes formation. The displacement of the anatomical model isochromats was calculated within the Graphics Processing Unit (GPU) kernel for every timestep of the pulse sequence. Experiments that would allow simulation of custom anatomical and motion models were also performed. Last, simulations of motion with MRISIMUL on single-node and multi-node multi-GPU systems were examined. Results Gradient Echo and CINE images of the three motion models were produced and motion-related artifacts were demonstrated. The temporal evolution of the contractility of the heart was presented through the application of myocardial tagging. Better simulation performance and image quality were presented through the introduction of software crushers without the need to further increase the computational load and GPU resources. Last, MRISIMUL demonstrated an almost linear scalable performance with the increasing number of available GPU cards, in both single-node and multi-node multi-GPU computer systems. Conclusions MRISIMUL is the first MR physics simulator to have implemented motion with a 3D large computational load on a single computer multi-GPU configuration. The incorporation of realistic motion models, such as cardiac motion, respiratory motion and flow may benefit the design and optimization of existing or new MR pulse sequences, protocols and algorithms, which examine motion related MR applications. PMID:24996972
A Novel Marker Based Method to Teeth Alignment in MRI

NASA Astrophysics Data System (ADS)

Luukinen, Jean-Marc; Aalto, Daniel; Malinen, Jarmo; Niikuni, Naoko; Saunavaara, Jani; Jääsaari, Päivi; Ojalammi, Antti; Parkkola, Riitta; Soukka, Tero; Happonen, Risto-Pekka

2018-04-01

Magnetic resonance imaging (MRI) can precisely capture the anatomy of the vocal tract. However, the crowns of teeth are not visible in standard MRI scans. In this study, a marker-based teeth alignment method is presented and evaluated. Ten patients undergoing orthognathic surgery were enrolled. Supraglottal airways were imaged preoperatively using structural MRI. MRI visible markers were developed, and they were attached to maxillary teeth and corresponding locations on the dental casts. Repeated measurements of intermarker distances in MRI and in a replica model was compared using linear regression analysis. Dental cast MRI and corresponding caliper measurements did not differ significantly. In contrast, the marker locations in vivo differed somewhat from the dental cast measurements likely due to marker placement inaccuracies. The markers were clearly visible in MRI and allowed for dental models to be aligned to head and neck MRI scans.
Is MRI of the Liver Needed During Routine Preoperative Workup for Colorectal Cancer?

PubMed

Kang, Sung Il; Kim, Duck-Woo; Cho, Jai Young; Park, Jihoon; Lee, Kyung Ho; Son, Il Tae; Oh, Heung-Kwon; Kang, Sung-Bum

2017-09-01

The clinical efficacy of gadoxetic acid-enhanced liver MRI as a routine preoperative procedure for all patients with colorectal cancer remains unclear. The purpose of this study was to evaluate the efficacy of preoperative gadoxetic acid-enhanced liver MRI for the diagnosis of liver metastasis in patients with colorectal cancer. This was a retrospective analysis from a prospective cohort database. All of the patients were from a subspecialty practice at a tertiary referral hospital. Patients who received preoperative gadoxetic acid-enhanced liver MRI after CT and attempted curative surgery for colorectal cancer were included. The number of equivocal hepatic lesions based on CT and gadoxetic acid-enhanced liver MRI and diagnostic use of the gadoxetic acid-enhanced liver MRI were measured. We reviewed the records of 690 patients with colorectal cancer. Equivocal hepatic lesions were present in 17.2% of patients based on CT and in 4.5% based on gadoxetic acid-enhanced liver MRI. Among 496 patients with no liver metastasis based on CT, gadoxetic acid-enhanced liver MRI detected equivocal lesions in 15 patients and metastasis in 3 patients. Among 119 patients who had equivocal liver lesions on CT, gadoxetic acid-enhanced liver MRI indicated hepatic lesions in 103 patients (86.6%), including 90 with no metastasis and 13 with metastasis. Among 75 patients who had liver metastasis on CT, gadoxetic acid-enhanced liver MRI indicated that the hepatic lesions in 2 patients were benign, in contrast to CT findings. The initial surgical plans for hepatic lesions according to CT were changed in 17 patients (3%) after gadoxetic acid-enhanced liver MRI. This study was limited by its retrospective design. The clinical efficacy of gadoxetic acid-enhanced liver MRI as a routine preoperative procedure for all patients with colorectal cancer is low, in spite of its high diagnostic value for detecting liver metastasis. However, this study showed gadoxetic acid-enhanced liver MRI was helpful in characterizing equivocal hepatic lesions identified in CT and could lead to change in treatment plans for some patients. See Video Abstract at http://links.lww.com/DCR/A420.
Automatic segmentation of brain MRI in high-dimensional local and non-local feature space based on sparse representation.

PubMed

Khalilzadeh, Mohammad Mahdi; Fatemizadeh, Emad; Behnam, Hamid

2013-06-01

Automatic extraction of the varying regions of magnetic resonance images is required as a prior step in a diagnostic intelligent system. The sparsest representation and high-dimensional feature are provided based on learned dictionary. The classification is done by employing the technique that computes the reconstruction error locally and non-locally of each pixel. The acquired results from the real and simulated images are superior to the best MRI segmentation method with regard to the stability advantages. In addition, it is segmented exactly through a formula taken from the distance and sparse factors. Also, it is done automatically taking sparse factor in unsupervised clustering methods whose results have been improved. Copyright © 2013 Elsevier Inc. All rights reserved.
Pilot study assessing differentiation of steatosis hepatis, hepatic iron overload, and combined disease using two-point dixon MRI at 3 T: in vitro and in vivo results of a 2D decomposition technique.

PubMed

Boll, Daniel T; Marin, Daniele; Redmon, Grace M; Zink, Stephen I; Merkle, Elmar M

2010-04-01

The purpose of our study was to evaluate whether two-point Dixon MRI using a 2D decomposition technique facilitates metabolite differentiation between lipids and iron in standardized in vitro liver phantoms with in vivo patient validation and allows semiquantitative in vitro assessment of metabolites associated with steatosis, iron overload, and combined disease. The acrylamide-based phantoms were made to reproduce the T1- and T2-weighted MRI appearances of physiologic hepatic parenchyma and hepatic steatosis-iron overload by the admixture of triglycerides and ferumoxides. Combined disease was simulated using joint admixtures of triglycerides and ferumoxides at various concentrations. For phantom validation, 30 patients were included, of whom 10 had steatosis, 10 had iron overload, and 10 had no liver disease. For MRI an in-phase/opposed-phase T1-weighted sequence with TR/TE(opposed-phase)/TE(in-phase) of 4.19/1.25/2.46 was used. Fat/water series were obtained by Dixon-based algorithms. In-phase and opposed-phase and fat/water ratios were calculated. Statistical cluster analysis assessed ratio pairs of physiologic liver, steatosis, iron overload, and combined disease in 2D metabolite discrimination plots. Statistical assessment proved that metabolite decomposition in phantoms simulating steatosis (1.77|0.22; in-phase/opposed-phase|fat/water ratios), iron overload (0.75|0.21), and healthy control subjects (1.09|0.05) formed three clusters with distinct ratio pairs. Patient validation for hepatic steatosis (3.29|0.51), iron overload (0.56|0.41), and normal control subjects (0.99|0.05) confirmed this clustering (p < 0.001). One-dimensional analysis assessing in vitro combined disease only with in-phase/opposed-phase ratios would have failed to characterize metabolites. The 2D analysis plotting in-phase/opposed-phase and fat/water ratios (2.16|0.59) provided accurate semiquantitative metabolite decomposition (p < 0.001). MR Dixon imaging facilitates metabolite decomposition of intrahepatic lipids and iron using in vitro phantoms with in vivo patient validation. The proposed decomposition technique identified distinct in-phase/opposed-phase and fat/water ratios for in vitro steatosis, iron overload, and combined disease.
Real-time MRI-guided needle intervention for cryoablation: a phantom study

NASA Astrophysics Data System (ADS)

Gao, Wenpeng; Jiang, Baichuan; Kacher, Dan F.; Fetics, Barry; Nevo, Erez; Lee, Thomas C.; Jayender, Jagadeesan

2017-03-01

MRI-guided needle intervention for cryoablation is a promising way to relieve the pain and treat the cancer. However, the limited size of MRI bore makes it impossible for clinicians to perform the operation in the bore. The patients had to be moved into the bore for scanning to verify the position of the needle's tip and out for adjusting the needle's trajectory. Real-time needle tracking and shown in MR images is of importance for clinicians to perform the operation more efficiently. In this paper, we have instrumented the cryotherapy needle with a MRI-safe electromagnetic (EM) sensor and optical sensor to measure the needle's position and orientation. To overcome the limitation of line-of-sight for optical sensor and the poor dynamic performance of the EM sensor, Kalman filter based data fusion is developed. Further, we developed a navigation system in open-source software, 3D Slicer, to provide accurate visualization of the needle and the surrounding anatomy. Experiment of simulation the needle intervention at the entrance was performed with a realistic spine phantom to quantify the accuracy of the navigation using the retrospective analysis method. Eleven trials of needle insertion were performed independently. The target accuracy with the navigation using only EM sensor, only optical sensor and data fusion are 2.27 +/-1.60 mm, 4.11 +/- 1.77 mm and 1.91 - 1.10 mm, respectively.
Accelerating Dynamic Magnetic Resonance Imaging (MRI) for Lung Tumor Tracking Based on Low-Rank Decomposition in the Spatial–Temporal Domain: A Feasibility Study Based on Simulation and Preliminary Prospective Undersampled MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sarma, Manoj; Department of Radiation Oncology, University of California, Los Angeles, California; Hu, Peng

Purpose: To evaluate a low-rank decomposition method to reconstruct down-sampled k-space data for the purpose of tumor tracking. Methods and Materials: Seven retrospective lung cancer patients were included in the simulation study. The fully-sampled k-space data were first generated from existing 2-dimensional dynamic MR images and then down-sampled by 5 × -20 × before reconstruction using a Cartesian undersampling mask. Two methods, a low-rank decomposition method using combined dynamic MR images (k-t SLR based on sparsity and low-rank penalties) and a total variation (TV) method using individual dynamic MR frames, were used to reconstruct images. The tumor trajectories were derived on the basis ofmore » autosegmentation of the resultant images. To further test its feasibility, k-t SLR was used to reconstruct prospective data of a healthy subject. An undersampled balanced steady-state free precession sequence with the same undersampling mask was used to acquire the imaging data. Results: In the simulation study, higher imaging fidelity and low noise levels were achieved with the k-t SLR compared with TV. At 10 × undersampling, the k-t SLR method resulted in an average normalized mean square error <0.05, as opposed to 0.23 by using the TV reconstruction on individual frames. Less than 6% showed tracking errors >1 mm with 10 × down-sampling using k-t SLR, as opposed to 17% using TV. In the prospective study, k-t SLR substantially reduced reconstruction artifacts and retained anatomic details. Conclusions: Magnetic resonance reconstruction using k-t SLR on highly undersampled dynamic MR imaging data results in high image quality useful for tumor tracking. The k-t SLR was superior to TV by better exploiting the intrinsic anatomic coherence of the same patient. The feasibility of k-t SLR was demonstrated by prospective imaging acquisition and reconstruction.« less
Computational Fluid Dynamics Simulations of Inhaled Nano-and Micro-Particle Deposition in the Rhesus Monkey Nasal Passages

DTIC Science & Technology

2016-12-01

reconstruction of the adult model was originally developed by Kepler et al. (1998) from serial Magnetic Resonance Imaging ( MRI ) sections of the right...upper airways and MRI imaging of a lung cast to form a contiguous reconstruction from the nostrils through 19 airway generations of the lung. For this...and Musante, C. J. (2001). A nonhuman primate aerosol deposition model for toxicological and pharmaceutical studies. Inhal. Toxicol. 13:307-324
Computational Fluid Dynamics Simulations of Inhaled Nano- and Micro-Particle Deposition in the Rhesus Monkey Nasal Passages

DTIC Science & Technology

2016-12-01

reconstruction of the adult model was originally developed by Kepler et al. (1998) from serial Magnetic Resonance Imaging ( MRI ) sections of the right...upper airways and MRI imaging of a lung cast to form a contiguous reconstruction from the nostrils through 19 airway generations of the lung. For this...and Musante, C. J. (2001). A nonhuman primate aerosol deposition model for toxicological and pharmaceutical studies. Inhal. Toxicol. 13:307-324
Geometric validation of self-gating k-space-sorted 4D-MRI vs 4D-CT using a respiratory motion phantom

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yue, Yong, E-mail: yong.yue@cshs.org; Yang, Wensha; McKenzie, Elizabeth

Purpose: MRI is increasingly being used for radiotherapy planning, simulation, and in-treatment-room motion monitoring. To provide more detailed temporal and spatial MR data for these tasks, we have recently developed a novel self-gated (SG) MRI technique with advantage of k-space phase sorting, high isotropic spatial resolution, and high temporal resolution. The current work describes the validation of this 4D-MRI technique using a MRI- and CT-compatible respiratory motion phantom and comparison to 4D-CT. Methods: The 4D-MRI sequence is based on a spoiled gradient echo-based 3D projection reconstruction sequence with self-gating for 4D-MRI at 3 T. Respiratory phase is resolved by usingmore » SG k-space lines as the motion surrogate. 4D-MRI images are reconstructed into ten temporal bins with spatial resolution 1.56 × 1.56 × 1.56 mm{sup 3}. A MRI-CT compatible phantom was designed to validate the performance of the 4D-MRI sequence and 4D-CT imaging. A spherical target (diameter 23 mm, volume 6.37 ml) filled with high-concentration gadolinium (Gd) gel is embedded into a plastic box (35 × 40 × 63 mm{sup 3}) and stabilized with low-concentration Gd gel. The phantom, driven by an air pump, is able to produce human-type breathing patterns between 4 and 30 respiratory cycles/min. 4D-CT of the phantom has been acquired in cine mode, and reconstructed into ten phases with slice thickness 1.25 mm. The 4D images sets were imported into a treatment planning software for target contouring. The geometrical accuracy of the 4D MRI and CT images has been quantified using target volume, flattening, and eccentricity. The target motion was measured by tracking the centroids of the spheres in each individual phase. Motion ground-truth was obtained from input signals and real-time video recordings. Results: The dynamic phantom has been operated in four respiratory rate (RR) settings, 6, 10, 15, and 20/min, and was scanned with 4D-MRI and 4D-CT. 4D-CT images have target-stretching, partial-missing, and other motion artifacts in various phases, whereas the 4D-MRI images are visually free of those artifacts. Volume percentage difference for the 6.37 ml target ranged from 5.3% ± 4.3% to 10.3% ± 5.9% for 4D-CT, and 1.47 ± 0.52 to 2.12 ± 1.60 for 4D-MRI. With an increase of respiratory rate, the target volumetric and geometric deviations increase for 4D-CT images while remaining stable for the 4D-MRI images. Target motion amplitude errors at different RRs were measured with a range of 0.66–1.25 mm for 4D-CT and 0.2–0.42 mm for 4D-MRI. The results of Mann–Whitney tests indicated that 4D-MRI significantly outperforms 4D-CT in phase-based target volumetric (p = 0.027) and geometric (p < 0.001) measures. Both modalities achieve equivalent accuracy in measuring motion amplitude (p = 0.828). Conclusions: The k-space self-gated 4D-MRI technique provides a robust method for accurately imaging phase-based target motion and geometry. Compared to 4D-CT, the current 4D-MRI technique demonstrates superior spatiotemporal resolution, and robust resistance to motion artifacts caused by fast target motion and irregular breathing patterns. The technique can be used extensively in abdominal targeting, motion gating, and toward implementing MRI-based adaptive radiotherapy.« less
A new concept of a unified parameter management, experiment control, and data analysis in fMRI: application to real-time fMRI at 3T and 7T.

PubMed

Hollmann, M; Mönch, T; Mulla-Osman, S; Tempelmann, C; Stadler, J; Bernarding, J

2008-10-30

In functional MRI (fMRI) complex experiments and applications require increasingly complex parameter handling as the experimental setup usually consists of separated soft- and hardware systems. Advanced real-time applications such as neurofeedback-based training or brain computer interfaces (BCIs) may even require adaptive changes of the paradigms and experimental setup during the measurement. This would be facilitated by an automated management of the overall workflow and a control of the communication between all experimental components. We realized a concept based on an XML software framework called Experiment Description Language (EDL). All parameters relevant for real-time data acquisition, real-time fMRI (rtfMRI) statistical data analysis, stimulus presentation, and activation processing are stored in one central EDL file, and processed during the experiment. A usability study comparing the central EDL parameter management with traditional approaches showed an improvement of the complete experimental handling. Based on this concept, a feasibility study realizing a dynamic rtfMRI-based brain computer interface showed that the developed system in combination with EDL was able to reliably detect and evaluate activation patterns in real-time. The implementation of a centrally controlled communication between the subsystems involved in the rtfMRI experiments reduced potential inconsistencies, and will open new applications for adaptive BCIs.
Kinetic effects on turbulence driven by the magnetorotational instability in black hole accretion

NASA Astrophysics Data System (ADS)

Sharma, Prateek

Many astrophysical objects (e.g., spiral galaxies, the solar system, Saturn's rings, and luminous disks around compact objects) occur in the form of a disk. One of the important astrophysical problems is to understand how rotationally supported disks lose angular momentum, and accrete towards the bottom of the gravitational potential, converting gravitational energy into thermal (and radiation) energy. The magnetorotational instability (MRI), an instability causing turbulent transport in ionized accretion disks, is studied in the kinetic regime. Kinetic effects are important because radiatively inefficient accretion flows (RIAFs), like the one around the supermassive black hole in the center of our Galaxy, are collisionless. The ion Larmor radius is tiny compared to the scale of MHD turbulence so that the drift kinetic equation (DKE), obtained by averaging the Vlasov equation over the fast gyromotion, is appropriate for evolving the distribution function. The kinetic MHD formalism, based on the moments of the DKE, is used for linear and nonlinear studies. A Landau fluid closure for parallel heat flux, which models kinetic effects like collisionless damping, is used to close the moment hierarchy. We show, that the kinetic MHD and drift kinetic formalisms give the same set of linear modes for a Keplerian disk. The BGK collision operator is used to study the transition of the MRI from kinetic to the MHD regime. The ZEUS MHD code is modified to include the key kinetic MHD terms: anisotropy, pressure tensor and anisotropic thermal conduction. The modified code is used to simulate the collisionless MRI in a local shearing box. As magnetic field is amplified by the MRI, pressure anisotropy ( p [perpendicular] > p || ) is created because of the adiabatic invariance (m 0( p [perpendicular] / B ). Larmor radius scale instabilities---mirror, ion-cyclotron, and firehose---are excited even at small pressure anisotropies (D p/p ~ 1/b). Pressure isotropization due to pitch angle scattering by these instabilities is included as a subgrid model. A key result of the kinetic MHD simulations is that the anisotropy stress can be as large as the Maxwell stress. It is shown, with the help of simple tests, that the centered differencing of anisotropic thermal conduction can cause the heat to flow from lower to higher temperatures, giving negative temperatures in regions with large temperature gradients. A new method, based on limiting the transverse temperature gradient, allows heat to flow only from higher to lower temperatures. Several tests and convergence studies are presented to compare the different methods.
High resolution, MRI-based, segmented, computerized head phantom

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zubal, I.G.; Harrell, C.R.; Smith, E.O.

1999-01-01

The authors have created a high-resolution software phantom of the human brain which is applicable to voxel-based radiation transport calculations yielding nuclear medicine simulated images and/or internal dose estimates. A software head phantom was created from 124 transverse MRI images of a healthy normal individual. The transverse T2 slices, recorded in a 256x256 matrix from a GE Signa 2 scanner, have isotropic voxel dimensions of 1.5 mm and were manually segmented by the clinical staff. Each voxel of the phantom contains one of 62 index numbers designating anatomical, neurological, and taxonomical structures. The result is stored as a 256x256x128 bytemore » array. Internal volumes compare favorably to those described in the ICRP Reference Man. The computerized array represents a high resolution model of a typical human brain and serves as a voxel-based anthropomorphic head phantom suitable for computer-based modeling and simulation calculations. It offers an improved realism over previous mathematically described software brain phantoms, and creates a reference standard for comparing results of newly emerging voxel-based computations. Such voxel-based computations lead the way to developing diagnostic and dosimetry calculations which can utilize patient-specific diagnostic images. However, such individualized approaches lack fast, automatic segmentation schemes for routine use; therefore, the high resolution, typical head geometry gives the most realistic patient model currently available.« less
Generate the scale-free brain music from BOLD signals

PubMed Central

Lu, Jing; Guo, Sijia; Chen, Mingming; Wang, Weixia; Yang, Hua; Guo, Daqing; Yao, Dezhong

2018-01-01

Abstract Many methods have been developed to translate a human electroencephalogram (EEG) into music. In addition to EEG, functional magnetic resonance imaging (fMRI) is another method used to study the brain and can reflect physiological processes. In 2012, we established a method to use simultaneously recorded fMRI and EEG signals to produce EEG-fMRI music, which represents a step toward scale-free brain music. In this study, we used a neural mass model, the Jansen–Rit model, to simulate activity in several cortical brain regions. The interactions between different brain regions were represented by the average normalized diffusion tensor imaging (DTI) structural connectivity with a coupling coefficient that modulated the coupling strength. Seventy-eight brain regions were adopted from the Automated Anatomical Labeling (AAL) template. Furthermore, we used the Balloon–Windkessel hemodynamic model to transform neural activity into a blood-oxygen-level dependent (BOLD) signal. Because the fMRI BOLD signal changes slowly, we used a sampling rate of 250 Hz to produce the temporal series for music generation. Then, the BOLD music was generated for each region using these simulated BOLD signals. Because the BOLD signal is scale free, these music pieces were also scale free, which is similar to classic music. Here, to simulate the case of an epileptic patient, we changed the parameter that determined the amplitude of the excitatory postsynaptic potential (EPSP) in the neural mass model. Finally, we obtained BOLD music for healthy and epileptic patients. The differences in levels of arousal between the 2 pieces of music may provide a potential tool for discriminating the different populations if the differences can be confirmed by more real data. PMID:29480872
Generate the scale-free brain music from BOLD signals.

PubMed

Lu, Jing; Guo, Sijia; Chen, Mingming; Wang, Weixia; Yang, Hua; Guo, Daqing; Yao, Dezhong

2018-01-01

Many methods have been developed to translate a human electroencephalogram (EEG) into music. In addition to EEG, functional magnetic resonance imaging (fMRI) is another method used to study the brain and can reflect physiological processes. In 2012, we established a method to use simultaneously recorded fMRI and EEG signals to produce EEG-fMRI music, which represents a step toward scale-free brain music. In this study, we used a neural mass model, the Jansen-Rit model, to simulate activity in several cortical brain regions. The interactions between different brain regions were represented by the average normalized diffusion tensor imaging (DTI) structural connectivity with a coupling coefficient that modulated the coupling strength. Seventy-eight brain regions were adopted from the Automated Anatomical Labeling (AAL) template. Furthermore, we used the Balloon-Windkessel hemodynamic model to transform neural activity into a blood-oxygen-level dependent (BOLD) signal. Because the fMRI BOLD signal changes slowly, we used a sampling rate of 250 Hz to produce the temporal series for music generation. Then, the BOLD music was generated for each region using these simulated BOLD signals. Because the BOLD signal is scale free, these music pieces were also scale free, which is similar to classic music. Here, to simulate the case of an epileptic patient, we changed the parameter that determined the amplitude of the excitatory postsynaptic potential (EPSP) in the neural mass model. Finally, we obtained BOLD music for healthy and epileptic patients. The differences in levels of arousal between the 2 pieces of music may provide a potential tool for discriminating the different populations if the differences can be confirmed by more real data. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.
Theoretical Analysis of the Accuracy and Safety of MRI-Guided Transurethral 3-D Conformal Ultrasound Prostate Therapy

NASA Astrophysics Data System (ADS)

Burtnyk, Mathieu; Chopra, Rajiv; Bronskill, Michael

2009-04-01

MRI-guided transurethral ultrasound therapy is a promising new approach for the treatment of localized prostate cancer. Several studies have demonstrated the feasibility of producing large regions of thermal coagulation adequate for prostate therapy; however, the quantitative assessment of shaping these regions to complex 3-D human prostate geometries has not been fully explored. This study used numerical simulations and twenty manually-segmented pelvic anatomical models derived from high-quality MR images of prostate cancer patients to evaluate the treatment accuracy and safety of 3-D conformal MRI-guided transurethral ultrasound therapy. The simulations incorporated a rotating multi-element planar dual-frequency ultrasound transducer (seventeen 4×3 mm elements) operating at 4.7/9.7 MHz and 10 W/cm2 maximum acoustic power. Results using a novel feedback control algorithm which modulated the ultrasound frequency, power and device rate of rotation showed that regions of thermal coagulation could be shaped to predefined prostate volumes within 1.0 mm across the vast majority of these glands. Treatment times were typically 30 min and remained below 60 min for large 60 cc prostates. With a rectal cooling temperature of 15° C, the rectal wall did not exceed 30EM43 in half of the twenty patient models with only a few 1 mm3 voxels above this threshold in the other cases. At 4.7 MHz, heating of the pelvic bone can become significant when it is located less than 10 mm from the prostate. Numerical simulations show that MRI-guided transurethral ultrasound therapy can thermally coagulate whole prostate glands accurately and safely in 3-D.
Inferring functional connectivity in MRI using Bayesian network structure learning with a modified PC algorithm

PubMed Central

Iyer, Swathi; Shafran, Izhak; Grayson, David; Gates, Kathleen; Nigg, Joel; Fair, Damien

2013-01-01

Resting state functional connectivity MRI (rs-fcMRI) is a popular technique used to gauge the functional relatedness between regions in the brain for typical and special populations. Most of the work to date determines this relationship by using Pearson's correlation on BOLD fMRI timeseries. However, it has been recognized that there are at least two key limitations to this method. First, it is not possible to resolve the direct and indirect connections/influences. Second, the direction of information flow between the regions cannot be differentiated. In the current paper, we follow-up on recent work by Smith et al (2011), and apply a Bayesian approach called the PC algorithm to both simulated data and empirical data to determine whether these two factors can be discerned with group average, as opposed to single subject, functional connectivity data. When applied on simulated individual subjects, the algorithm performs well determining indirect and direct connection but fails in determining directionality. However, when applied at group level, PC algorithm gives strong results for both indirect and direct connections and the direction of information flow. Applying the algorithm on empirical data, using a diffusion-weighted imaging (DWI) structural connectivity matrix as the baseline, the PC algorithm outperformed the direct correlations. We conclude that, under certain conditions, the PC algorithm leads to an improved estimate of brain network structure compared to the traditional connectivity analysis based on correlations. PMID:23501054
INTERCOMPARISON OF PERFORMANCE OF RF COIL GEOMETRIES FOR HIGH FIELD MOUSE CARDIAC MRI

PubMed Central

Constantinides, Christakis; Angeli, S.; Gkagkarellis, S.; Cofer, G.

2012-01-01

Multi-turn spiral surface coils are constructed in flat and cylindrical arrangements and used for high field (7.1 T) mouse cardiac MRI. Their electrical and imaging performances, based on experimental measurements, simulations, and MRI experiments in free space, and under phantom, and animal loading conditions, are compared with a commercially available birdcage coil. Results show that the four-turn cylindrical spiral coil exhibits improved relative SNR (rSNR) performance to the flat coil counterpart, and compares fairly well with a commercially available birdcage coil. Phantom experiments indicate a 50% improvement in the SNR for penetration depths ≤ 6.1 mm from the coil surface compared to the birdcage coil, and an increased penetration depth at the half-maximum field response of 8 mm in the 4-spiral cylindrical coil case, in contrast to 2.9 mm in the flat 4-turn spiral case. Quantitative comparison of the performance of the two spiral coil geometries in anterior, lateral, inferior, and septal regions of the murine heart yield maximum mean percentage rSNR increases of the order of 27–167% in vivo post-mortem (cylindrical compared to flat coil). The commercially available birdcage outperforms the cylindrical spiral coil in rSNR by a factor of 3–5 times. The comprehensive approach and methodology adopted to accurately design, simulate, implement, and test radiofrequency coils of any geometry and type, under any loading conditions, can be generalized for any application of high field mouse cardiac MRI. PMID:23204945
Combining self-organizing mapping and supervised affinity propagation clustering approach to investigate functional brain networks involved in motor imagery and execution with fMRI measurements.

PubMed

Zhang, Jiang; Liu, Qi; Chen, Huafu; Yuan, Zhen; Huang, Jin; Deng, Lihua; Lu, Fengmei; Zhang, Junpeng; Wang, Yuqing; Wang, Mingwen; Chen, Liangyin

2015-01-01

Clustering analysis methods have been widely applied to identifying the functional brain networks of a multitask paradigm. However, the previously used clustering analysis techniques are computationally expensive and thus impractical for clinical applications. In this study a novel method, called SOM-SAPC that combines self-organizing mapping (SOM) and supervised affinity propagation clustering (SAPC), is proposed and implemented to identify the motor execution (ME) and motor imagery (MI) networks. In SOM-SAPC, SOM was first performed to process fMRI data and SAPC is further utilized for clustering the patterns of functional networks. As a result, SOM-SAPC is able to significantly reduce the computational cost for brain network analysis. Simulation and clinical tests involving ME and MI were conducted based on SOM-SAPC, and the analysis results indicated that functional brain networks were clearly identified with different response patterns and reduced computational cost. In particular, three activation clusters were clearly revealed, which include parts of the visual, ME and MI functional networks. These findings validated that SOM-SAPC is an effective and robust method to analyze the fMRI data with multitasks.
Volumetric Assessment of Swallowing Muscles: A Comparison of CT and MRI Segmentation.

PubMed

Sporns, Kim Barbara; Hanning, Uta; Schmidt, Rene; Muhle, Paul; Wirth, Rainer; Zimmer, Sebastian; Dziewas, Rainer; Suntrup-Krueger, Sonja; Sporns, Peter Bernhard; Heindel, Walter; Schwindt, Wolfram

2018-05-01

Recent retrospective studies have proposed a high correlation between atrophy of swallowing muscles, age, severity of dysphagia and aspiration status based on computed tomography (CT). However, ionizing radiation poses an ethical barrier to research in prospective non-patient populations. Hence, there is a need to prove the efficacy of techniques that rely on noninvasive methods and produce high-resolution soft tissue images such as magnetic resonance imaging (MRI). The objective of this study was therefore to compare the segmentation results of swallowing muscles using CT and MRI. Retrospective study of 21 patients (median age: 46.6; gender: 11 female) who underwent CT and MRI of the head and neck region within a time frame of less than 50 days because of suspected head and neck cancer using contrast agent. CT and MR images were segmented by two blinded readers using Medical Imaging Toolkit (MITK) and both modalities were tested (with the equivalence test) regarding the segmented muscle volumes. Adjustment for multiple testing was performed using the Bonferroni test and the potential time effect of the muscle volumes and the time interval between the modalities was assessed by a spearman correlation. The study was approved by the local ethics committee. The median volumes for each muscle belly of the digastric muscle derived from CT were 3051 mm 3 (left) and 2969 mm 3 (right), and from MRI they were 3218 mm 3 (left) and 3027 mm 3 (right). The median volume of the geniohyoid muscle was 6580 mm 3 on CT and 6648 mm 3 on MRI. The interrater reliability was high for all segmented muscles. The mean time interval between the CT and MRI examinations was 34 days (IQR 25; 41). The muscle differences of each muscle between the two modalities did not reveal significant correlation to the time interval between the examinations (digastric left r = 0.003 and digastric right r = -0.008; geniohyoid muscle r = 0.075). CT-based segmentation and MRI-based segmentation of the digastric and geniohyoid muscle are equally feasible. The potential advantage of MRI for prospective studies is the absence of ionizing radiation. · CT-based segmentation and MRI-based segmentation of the swallowing muscles are equally feasible.. · The advantage of MRI is the absence of ionizing radiation.. · MRI should therefore be deployed for future prospective studies.. · Sporns KB, Hanning U, Schmidt R et al. Volumetric Assessment of Swallowing Muscles: A Comparison of CT and MRI Segmentation. Fortschr Röntgenstr 2018; 190: 441 - 446. © Georg Thieme Verlag KG Stuttgart · New York.

A computer simulated phantom study of tomotherapy dose optimization based on probability density functions (PDF) and potential errors caused by low reproducibility of PDF.

PubMed

Sheng, Ke; Cai, Jing; Brookeman, James; Molloy, Janelle; Christopher, John; Read, Paul

2006-09-01

Lung tumor motion trajectories measured by four-dimensional CT or dynamic MRI can be converted to a probability density function (PDF), which describes the probability of the tumor at a certain position, for PDF based treatment planning. Using this method in simulated sequential tomotherapy, we study the dose reduction of normal tissues and more important, the effect of PDF reproducibility on the accuracy of dosimetry. For these purposes, realistic PDFs were obtained from two dynamic MRI scans of a healthy volunteer within a 2 week interval. The first PDF was accumulated from a 300 s scan and the second PDF was calculated from variable scan times from 5 s (one breathing cycle) to 300 s. Optimized beam fluences based on the second PDF were delivered to the hypothetical gross target volume (GTV) of a lung phantom that moved following the first PDF The reproducibility between two PDFs varied from low (78%) to high (94.8%) when the second scan time increased from 5 s to 300 s. When a highly reproducible PDF was used in optimization, the dose coverage of GTV was maintained; phantom lung receiving 10%-20% prescription dose was reduced by 40%-50% and the mean phantom lung dose was reduced by 9.6%. However, optimization based on PDF with low reproducibility resulted in a 50% underdosed GTV. The dosimetric error increased nearly exponentially as the PDF error increased. Therefore, although the dose of the tumor surrounding tissue can be theoretically reduced by PDF based treatment planning, the reliability and applicability of this method highly depend on if a reproducible PDF exists and is measurable. By correlating the dosimetric error and PDF error together, a useful guideline for PDF data acquisition and patient qualification for PDF based planning can be derived.
A computer simulated phantom study of tomotherapy dose optimization based on probability density functions (PDF) and potential errors caused by low reproducibility of PDF

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheng, Ke; Cai Jing; Brookeman, James

2006-09-15

Lung tumor motion trajectories measured by four-dimensional CT or dynamic MRI can be converted to a probability density function (PDF), which describes the probability of the tumor at a certain position, for PDF based treatment planning. Using this method in simulated sequential tomotherapy, we study the dose reduction of normal tissues and more important, the effect of PDF reproducibility on the accuracy of dosimetry. For these purposes, realistic PDFs were obtained from two dynamic MRI scans of a healthy volunteer within a 2 week interval. The first PDF was accumulated from a 300 s scan and the second PDF wasmore » calculated from variable scan times from 5 s (one breathing cycle) to 300 s. Optimized beam fluences based on the second PDF were delivered to the hypothetical gross target volume (GTV) of a lung phantom that moved following the first PDF. The reproducibility between two PDFs varied from low (78%) to high (94.8%) when the second scan time increased from 5 s to 300 s. When a highly reproducible PDF was used in optimization, the dose coverage of GTV was maintained; phantom lung receiving 10%-20% prescription dose was reduced by 40%-50% and the mean phantom lung dose was reduced by 9.6%. However, optimization based on PDF with low reproducibility resulted in a 50% underdosed GTV. The dosimetric error increased nearly exponentially as the PDF error increased. Therefore, although the dose of the tumor surrounding tissue can be theoretically reduced by PDF based treatment planning, the reliability and applicability of this method highly depend on if a reproducible PDF exists and is measurable. By correlating the dosimetric error and PDF error together, a useful guideline for PDF data acquisition and patient qualification for PDF based planning can be derived.« less
Digital anthropomorphic phantoms of non-rigid human respiratory and voluntary body motion for investigating motion correction in emission imaging

NASA Astrophysics Data System (ADS)

Könik, Arda; Connolly, Caitlin M.; Johnson, Karen L.; Dasari, Paul; Segars, Paul W.; Pretorius, P. H.; Lindsay, Clifford; Dey, Joyoni; King, Michael A.

2014-07-01

The development of methods for correcting patient motion in emission tomography has been receiving increased attention. Often the performance of these methods is evaluated through simulations using digital anthropomorphic phantoms, such as the commonly used extended cardiac torso (XCAT) phantom, which models both respiratory and cardiac motion based on human studies. However, non-rigid body motion, which is frequently seen in clinical studies, is not present in the standard XCAT phantom. In addition, respiratory motion in the standard phantom is limited to a single generic trend. In this work, to obtain a more realistic representation of motion, we developed a series of individual-specific XCAT phantoms, modeling non-rigid respiratory and non-rigid body motions derived from the magnetic resonance imaging (MRI) acquisitions of volunteers. Acquisitions were performed in the sagittal orientation using the Navigator methodology. Baseline (no motion) acquisitions at end-expiration were obtained at the beginning of each imaging session for each volunteer. For the body motion studies, MRI was again acquired only at end-expiration for five body motion poses (shoulder stretch, shoulder twist, lateral bend, side roll, and axial slide). For the respiratory motion studies, an MRI was acquired during free/regular breathing. The magnetic resonance slices were then retrospectively sorted into 14 amplitude-binned respiratory states, end-expiration, end-inspiration, six intermediary states during inspiration, and six during expiration using the recorded Navigator signal. XCAT phantoms were then generated based on these MRI data by interactive alignment of the organ contours of the XCAT with the MRI slices using a graphical user interface. Thus far we have created five body motion and five respiratory motion XCAT phantoms from the MRI acquisitions of six healthy volunteers (three males and three females). Non-rigid motion exhibited by the volunteers was reflected in both respiratory and body motion phantoms with a varying extent and character for each individual. In addition to these phantoms, we recorded the position of markers placed on the chest of the volunteers for the body motion studies, which could be used as external motion measurement. Using these phantoms and external motion data, investigators will be able to test their motion correction approaches for realistic motion obtained from different individuals. The non-uniform rational B-spline data and the parameter files for these phantoms are freely available for downloading and can be used with the XCAT license.
SU-G-JeP2-15: Proton Beam Behavior in the Presence of Realistic Magnet Fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Santos, D M; Wachowicz, K; Fallone, B G

2016-06-15

Purpose: To investigate the effects of magnetic fields on proton therapy beams for integration with MRI. Methods: 3D magnetic fields from an open-bore superconducting MRI model (previously developed by our group) and 3D magnetic fields from an in-house gradient coil design were applied to various mono energetic proton pencil beam (80MeV to 250MeV) simulations. In all simulations, the z-axis of the simulation geometry coincided with the direction of the B0 field and magnet isocentre. In each simulation, the initial beam trajectory was varied. The first set of simulations performed was based on analytic magnetic force equations (analytic simulations), which couldmore » be rapidly calculated yet were limited to propagating proton beams in vacuum. The second set is full Monte Carlo (MC) simulations, which used GEANT4 MC toolkit. Metrics such as the beam position and dose profiles were extracted. Comparisons between the cases with and without magnetic fields present were made. Results: The analytic simulations served as verification checks for the MC simulations when the same simulation geometries were used. The results of the analytic simulations agreed with the MC simulations performed in vacuum. The presence of the MRI’s static magnetic field causes proton pencil beams to follow a slight helical trajectory when there were some initial off-axis components. The 80MeV, 150MeV, and 250MeV proton beams rotated by 4.9o, 3.6o, and 2.8o, respectively, when they reached z=0cm. The deflections caused by gradient coils’ magnetic fields show spatially invariant patterns with a maximum range of 0.5mm at z=0cm. Conclusion: This investigation reveals that both the MRI’s B0 and gradient magnetic fields can cause small but observable deflections of proton beams at energies studied. The MRI’s static field caused a rotation of the beam while the gradient coils’ fields effects were spatially invariant. Dr. B Gino Fallone is a co-founder and CEO of MagnetTx Oncology Solutions (under discussions to license Alberta bi-planar linac MR for commercialization)« less
Spatial independent component analysis of functional MRI time-series: to what extent do results depend on the algorithm used?

PubMed

Esposito, Fabrizio; Formisano, Elia; Seifritz, Erich; Goebel, Rainer; Morrone, Renato; Tedeschi, Gioacchino; Di Salle, Francesco

2002-07-01

Independent component analysis (ICA) has been successfully employed to decompose functional MRI (fMRI) time-series into sets of activation maps and associated time-courses. Several ICA algorithms have been proposed in the neural network literature. Applied to fMRI, these algorithms might lead to different spatial or temporal readouts of brain activation. We compared the two ICA algorithms that have been used so far for spatial ICA (sICA) of fMRI time-series: the Infomax (Bell and Sejnowski [1995]: Neural Comput 7:1004-1034) and the Fixed-Point (Hyvärinen [1999]: Adv Neural Inf Proc Syst 10:273-279) algorithms. We evaluated the Infomax- and Fixed Point-based sICA decompositions of simulated motor, and real motor and visual activation fMRI time-series using an ensemble of measures. Log-likelihood (McKeown et al. [1998]: Hum Brain Mapp 6:160-188) was used as a measure of how significantly the estimated independent sources fit the statistical structure of the data; receiver operating characteristics (ROC) and linear correlation analyses were used to evaluate the algorithms' accuracy of estimating the spatial layout and the temporal dynamics of simulated and real activations; cluster sizing calculations and an estimation of a residual gaussian noise term within the components were used to examine the anatomic structure of ICA components and for the assessment of noise reduction capabilities. Whereas both algorithms produced highly accurate results, the Fixed-Point outperformed the Infomax in terms of spatial and temporal accuracy as long as inferential statistics were employed as benchmarks. Conversely, the Infomax sICA was superior in terms of global estimation of the ICA model and noise reduction capabilities. Because of its adaptive nature, the Infomax approach appears to be better suited to investigate activation phenomena that are not predictable or adequately modelled by inferential techniques. Copyright 2002 Wiley-Liss, Inc.
MRI-assisted PET motion correction for neurologic studies in an integrated MR-PET scanner.

PubMed

Catana, Ciprian; Benner, Thomas; van der Kouwe, Andre; Byars, Larry; Hamm, Michael; Chonde, Daniel B; Michel, Christian J; El Fakhri, Georges; Schmand, Matthias; Sorensen, A Gregory

2011-01-01

Head motion is difficult to avoid in long PET studies, degrading the image quality and offsetting the benefit of using a high-resolution scanner. As a potential solution in an integrated MR-PET scanner, the simultaneously acquired MRI data can be used for motion tracking. In this work, a novel algorithm for data processing and rigid-body motion correction (MC) for the MRI-compatible BrainPET prototype scanner is described, and proof-of-principle phantom and human studies are presented. To account for motion, the PET prompt and random coincidences and sensitivity data for postnormalization were processed in the line-of-response (LOR) space according to the MRI-derived motion estimates. The processing time on the standard BrainPET workstation is approximately 16 s for each motion estimate. After rebinning in the sinogram space, the motion corrected data were summed, and the PET volume was reconstructed using the attenuation and scatter sinograms in the reference position. The accuracy of the MC algorithm was first tested using a Hoffman phantom. Next, human volunteer studies were performed, and motion estimates were obtained using 2 high-temporal-resolution MRI-based motion-tracking techniques. After accounting for the misalignment between the 2 scanners, perfectly coregistered MRI and PET volumes were reproducibly obtained. The MRI output gates inserted into the PET list-mode allow the temporal correlation of the 2 datasets within 0.2 ms. The Hoffman phantom volume reconstructed by processing the PET data in the LOR space was similar to the one obtained by processing the data using the standard methods and applying the MC in the image space, demonstrating the quantitative accuracy of the procedure. In human volunteer studies, motion estimates were obtained from echo planar imaging and cloverleaf navigator sequences every 3 s and 20 ms, respectively. Motion-deblurred PET images, with excellent delineation of specific brain structures, were obtained using these 2 MRI-based estimates. An MRI-based MC algorithm was implemented for an integrated MR-PET scanner. High-temporal-resolution MRI-derived motion estimates (obtained while simultaneously acquiring anatomic or functional MRI data) can be used for PET MC. An MRI-based MC method has the potential to improve PET image quality, increasing its reliability, reproducibility, and quantitative accuracy, and to benefit many neurologic applications.
Technical aspects of MRI signal change quantification after gadolinium-based contrast agents' administration.

PubMed

Ramalho, Joana; Ramalho, Miguel; AlObaidy, Mamdoh; Semelka, Richard C

2016-12-01

Over the last 2years several studies have been published regarding gadolinium deposition in brain structures in patients with normal renal function after repeated administrations of gadolinium-based contrast agents (GBCAs). Most of the publications are magnetic resonance imaging (MRI) based retrospective studies, where gadolinium deposition may be indirectly measured by evaluating changes in T1 signal intensity (SI) in brain tissue, particularly in the dentate nucleus (DN) and/or globus pallidi (GP). The direct correlation between T1 signal changes and gadolinium deposition was validated by human pathology studies. However, the variability of the MR equipment and parameters used across different publications, along with the inherent limitations of MRI to assess gadolinium in human tissues should be acknowledged when interpreting those studies. Nevertheless, MRI studies remain essential regarding gadolinium bio-distribution knowledge. The aim of this paper is to overview current knowledge of technical aspects of T1 signal intensity evaluation by MRI and describe confounding factors, with the intention to achieve higher accuracy and maximize reproducibility. Copyright © 2016 Elsevier Inc. All rights reserved.
Multi-Sectional Views Textural Based SVM for MS Lesion Segmentation in Multi-Channels MRIs

PubMed Central

Abdullah, Bassem A; Younis, Akmal A; John, Nigel M

2012-01-01

In this paper, a new technique is proposed for automatic segmentation of multiple sclerosis (MS) lesions from brain magnetic resonance imaging (MRI) data. The technique uses a trained support vector machine (SVM) to discriminate between the blocks in regions of MS lesions and the blocks in non-MS lesion regions mainly based on the textural features with aid of the other features. The classification is done on each of the axial, sagittal and coronal sectional brain view independently and the resultant segmentations are aggregated to provide more accurate output segmentation. The main contribution of the proposed technique described in this paper is the use of textural features to detect MS lesions in a fully automated approach that does not rely on manually delineating the MS lesions. In addition, the technique introduces the concept of the multi-sectional view segmentation to produce verified segmentation. The proposed textural-based SVM technique was evaluated using three simulated datasets and more than fifty real MRI datasets. The results were compared with state of the art methods. The obtained results indicate that the proposed method would be viable for use in clinical practice for the detection of MS lesions in MRI. PMID:22741026
Simultaneous experimental determination of labile proton fraction ratio and exchange rate with irradiation radio frequency power-dependent quantitative CEST MRI analysis.

PubMed

Sun, Phillip Zhe; Wang, Yu; Xiao, Gang; Wu, Renhua

2013-01-01

Chemical exchange saturation transfer (CEST) imaging is sensitive to dilute proteins/peptides and microenvironmental properties, and has been increasingly evaluated for molecular imaging and in vivo applications. However, the experimentally measured CEST effect depends on the CEST agent concentration, exchange rate and relaxation time. In addition, there may be non-negligible direct radio-frequency (RF) saturation effects, particularly severe for diamagnetic CEST (DIACEST) agents owing to their relatively small chemical shift difference from that of the bulk water resonance. As such, the commonly used asymmetry analysis only provides CEST-weighted information. Recently, it has been shown with numerical simulation that both labile proton concentration and exchange rate can be determined by evaluating the RF power dependence of DIACEST effect. To validate the simulation results, we prepared and imaged two CEST phantoms: a pH phantom of serially titrated pH at a fixed creatine concentration and a concentration phantom of serially varied creatine concentration titrated to the same pH, and solved the labile proton fraction ratio and exchange rate per-pixel. For the concentration phantom, we showed that the labile proton fraction ratio is proportional to the CEST agent concentration with negligible change in the exchange rate. Additionally, we found the exchange rate of the pH phantom is dominantly base-catalyzed with little difference in the labile proton fraction ratio. In summary, our study demonstrated quantitative DIACEST MRI, which remains promising to augment the conventional CEST-weighted MRI analysis. Copyright © 2013 John Wiley & Sons, Ltd.
Early classification of Alzheimer's disease using hippocampal texture from structural MRI

NASA Astrophysics Data System (ADS)

Zhao, Kun; Ding, Yanhui; Wang, Pan; Dou, Xuejiao; Zhou, Bo; Yao, Hongxiang; An, Ningyu; Zhang, Yongxin; Zhang, Xi; Liu, Yong

2017-03-01

Convergent evidence has been collected to support that Alzheimer's disease (AD) is associated with reduction in hippocampal volume based on anatomical magnetic resonance imaging (MRI) and impaired functional connectivity based on functional MRI. Radiomics texture analysis has been previously successfully used to identify MRI biomarkers of several diseases, including AD, mild cognitive impairment and multiple sclerosis. In this study, our goal was to determine if MRI hippocampal textures, including the intensity, shape, texture and wavelet features, could be served as an MRI biomarker of AD. For this purpose, the texture marker was trained and evaluated from MRI data of 48 AD and 39 normal samples. The result highlights the presence of hippocampal texture abnormalities in AD, and the possibility that texture may serve as a neuroimaging biomarker for AD.
Population based MRI and DTI templates of the adult ferret brain and tools for voxelwise analysis.

PubMed

Hutchinson, E B; Schwerin, S C; Radomski, K L; Sadeghi, N; Jenkins, J; Komlosh, M E; Irfanoglu, M O; Juliano, S L; Pierpaoli, C

2017-05-15

Non-invasive imaging has the potential to play a crucial role in the characterization and translation of experimental animal models to investigate human brain development and disorders, especially when employed to study animal models that more accurately represent features of human neuroanatomy. The purpose of this study was to build and make available MRI and DTI templates and analysis tools for the ferret brain as the ferret is a well-suited species for pre-clinical MRI studies with folded cortical surface, relatively high white matter volume and body dimensions that allow imaging with pre-clinical MRI scanners. Four ferret brain templates were built in this study - in-vivo MRI and DTI and ex-vivo MRI and DTI - using brain images across many ferrets and region of interest (ROI) masks corresponding to established ferret neuroanatomy were generated by semi-automatic and manual segmentation. The templates and ROI masks were used to create a web-based ferret brain viewing software for browsing the MRI and DTI volumes with annotations based on the ROI masks. A second objective of this study was to provide a careful description of the imaging methods used for acquisition, processing, registration and template building and to demonstrate several voxelwise analysis methods including Jacobian analysis of morphometry differences between the female and male brain and bias-free identification of DTI abnormalities in an injured ferret brain. The templates, tools and methodological optimization presented in this study are intended to advance non-invasive imaging approaches for human-similar animal species that will enable the use of pre-clinical MRI studies for understanding and treating brain disorders. Published by Elsevier Inc.
A theoretical signal processing framework for linear diffusion MRI: Implications for parameter estimation and experiment design.

PubMed

Varadarajan, Divya; Haldar, Justin P

2017-11-01

The data measured in diffusion MRI can be modeled as the Fourier transform of the Ensemble Average Propagator (EAP), a probability distribution that summarizes the molecular diffusion behavior of the spins within each voxel. This Fourier relationship is potentially advantageous because of the extensive theory that has been developed to characterize the sampling requirements, accuracy, and stability of linear Fourier reconstruction methods. However, existing diffusion MRI data sampling and signal estimation methods have largely been developed and tuned without the benefit of such theory, instead relying on approximations, intuition, and extensive empirical evaluation. This paper aims to address this discrepancy by introducing a novel theoretical signal processing framework for diffusion MRI. The new framework can be used to characterize arbitrary linear diffusion estimation methods with arbitrary q-space sampling, and can be used to theoretically evaluate and compare the accuracy, resolution, and noise-resilience of different data acquisition and parameter estimation techniques. The framework is based on the EAP, and makes very limited modeling assumptions. As a result, the approach can even provide new insight into the behavior of model-based linear diffusion estimation methods in contexts where the modeling assumptions are inaccurate. The practical usefulness of the proposed framework is illustrated using both simulated and real diffusion MRI data in applications such as choosing between different parameter estimation methods and choosing between different q-space sampling schemes. Copyright © 2017 Elsevier Inc. All rights reserved.
Comparative study of microelectrode recording-based STN location and MRI-based STN location in low to ultra-high field (7.0 T) T2-weighted MRI images

NASA Astrophysics Data System (ADS)

Verhagen, Rens; Schuurman, P. Richard; van den Munckhof, Pepijn; Fiorella Contarino, M.; de Bie, Rob M. A.; Bour, Lo J.

2016-12-01

Objective. The correspondence between the anatomical STN and the STN observed in T2-weighted MRI images used for deep brain stimulation (DBS) targeting remains unclear. Using a new method, we compared the STN borders seen on MRI images with those estimated by intraoperative microelectrode recordings (MER). Approach. We developed a method to automatically generate a detailed estimation of STN shape and the location of its borders, based on multiple-channel MER measurements. In 33 STNs of 19 Parkinson patients, we quantitatively compared the dorsal and lateral borders of this MER-based STN model with the STN borders visualized by 1.5 T (n = 14), 3.0 T (n = 10) and 7.0 T (n = 9) T2-weighted MRI. Main results. The dorsal border was identified more dorsally on coronal T2 MRI than by the MER-based STN model, with a significant difference in the 3.0 T (range 0.97-1.19 mm) and 7.0 T (range 1.23-1.25 mm) groups. The lateral border was significantly more medial on 1.5 T (mean: 1.97 mm) and 3.0 T (mean: 2.49 mm) MRI than in the MER-based STN; a difference that was not found in the 7.0 T group. Significance. The STN extends further in the dorsal direction on coronal T2 MRI images than is measured by MER. Increasing MRI field strength to 3.0 T or 7.0 T yields similar discrepancies between MER and MRI at the dorsal STN border. In contrast, increasing MRI field strength to 7.0 T may be useful for identification of the lateral STN border and thereby improve DBS targeting.
Accuracy of PDFF estimation by magnitude-based and complex-based MRI in children with MR spectroscopy as a reference.

PubMed

Haufe, William M; Wolfson, Tanya; Hooker, Catherine A; Hooker, Jonathan C; Covarrubias, Yesenia; Schlein, Alex N; Hamilton, Gavin; Middleton, Michael S; Angeles, Jorge E; Hernando, Diego; Reeder, Scott B; Schwimmer, Jeffrey B; Sirlin, Claude B

2017-12-01

To assess and compare the accuracy of magnitude-based magnetic resonance imaging (MRI-M) and complex-based MRI (MRI-C) for estimating hepatic proton density fat fraction (PDFF) in children, using MR spectroscopy (MRS) as the reference standard. A secondary aim was to assess the agreement between MRI-M and MRI-C. This was a HIPAA-compliant, retrospective analysis of data collected in children enrolled in prospective, Institutional Review Board (IRB)-approved studies between 2012 and 2014. Informed consent was obtained from 200 children (ages 8-19 years) who subsequently underwent 3T MR exams that included MRI-M, MRI-C, and T 1 -independent, T 2 -corrected, single-voxel stimulated echo acquisition mode (STEAM) MRS. Both MRI methods acquired six echoes at low flip angles. T2*-corrected PDFF parametric maps were generated. PDFF values were recorded from regions of interest (ROIs) drawn on the maps in each of the nine Couinaud segments and three ROIs colocalized to the MRS voxel location. Regression analyses assessing agreement with MRS were performed to evaluate the accuracy of each MRI method, and Bland-Altman and intraclass correlation coefficient (ICC) analyses were performed to assess agreement between the MRI methods. MRI-M and MRI-C PDFF were accurate relative to the colocalized MRS reference standard, with regression intercepts of 0.63% and -0.07%, slopes of 0.998 and 0.975, and proportion-of-explained-variance values (R 2 ) of 0.982 and 0.979, respectively. For individual Couinaud segments and for the whole liver averages, Bland-Altman biases between MRI-M and MRI-C were small (ranging from 0.04 to 1.11%) and ICCs were high (≥0.978). Both MRI-M and MRI-C accurately estimated hepatic PDFF in children, and high intermethod agreement was observed. 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1641-1647. © 2017 International Society for Magnetic Resonance in Medicine.
Quantitative comparison of high-resolution MRI and myelin-stained histology of the human cerebral cortex.

PubMed

Osechinskiy, Sergey; Kruggel, Frithjof

2009-01-01

The architectonic analysis of the human cerebral cortex is presently based on the examination of stained tissue sections. Recent progress in high-resolution magnetic resonance imaging (MRI) promotes the feasibility of an in vivo architectonic analysis. Since the exact relationship between the laminar fine-structure of a cortical MRI signal and histological cyto-and myeloarchitectonic staining patterns is not known, a quantitative study comparing high-resolution MRI to histological ground truth images is necessary for validating a future MRI based architectonic analysis. This communication describes an ongoing study comparing post mortem MR images to a myelin-stained histology of the brain cortex. After establishing a close spatial correspondence between histological sections and MRI using a slice-to-volume nonrigid registration algorithm, transcortical intensity profiles, extracted from both imaging modalities along curved trajectories of a Laplacian vector field, are compared via a cross-correlational analysis.
Hepatic fat quantification using the two-point Dixon method and fat color maps based on non-alcoholic fatty liver disease activity score.

PubMed

Hayashi, Tatsuya; Saitoh, Satoshi; Takahashi, Junji; Tsuji, Yoshinori; Ikeda, Kenji; Kobayashi, Masahiro; Kawamura, Yusuke; Fujii, Takeshi; Inoue, Masafumi; Miyati, Tosiaki; Kumada, Hiromitsu

2017-04-01

The two-point Dixon method for magnetic resonance imaging (MRI) is commonly used to non-invasively measure fat deposition in the liver. The aim of the present study was to assess the usefulness of MRI-fat fraction (MRI-FF) using the two-point Dixon method based on the non-alcoholic fatty liver disease activity score. This retrospective study included 106 patients who underwent liver MRI and MR spectroscopy, and 201 patients who underwent liver MRI and histological assessment. The relationship between MRI-FF and MR spectroscopy-fat fraction was used to estimate the corrected MRI-FF for hepatic multi-peaks of fat. Then, a color FF map was generated with the corrected MRI-FF based on the non-alcoholic fatty liver disease activity score. We defined FF variability as the standard deviation of FF in regions of interest. Uniformity of hepatic fat was visually graded on a three-point scale using both gray-scale and color FF maps. Confounding effects of histology (iron, inflammation and fibrosis) on corrected MRI-FF were assessed by multiple linear regression. The linear correlations between MRI-FF and MR spectroscopy-fat fraction, and between corrected MRI-FF and histological steatosis were strong (R 2 = 0.90 and R 2 = 0.88, respectively). Liver fat variability significantly increased with visual fat uniformity grade using both of the maps (ρ = 0.67-0.69, both P < 0.001). Hepatic iron, inflammation and fibrosis had no significant confounding effects on the corrected MRI-FF (all P > 0.05). The two-point Dixon method and the gray-scale or color FF maps based on the non-alcoholic fatty liver disease activity score were useful for fat quantification in the liver of patients without severe iron deposition. © 2016 The Japan Society of Hepatology.
SU-D-207A-04: Use of Gradient Echo Plural Contrast Imaging (GEPCI) in MR-Guided Radiation Therapy: A Feasibility Study Targeting Brain Treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai, B; Rao, Y; Tsien, C

Purpose: To implement the Gradient Echo Plural Contrast Imaging(GEPCI) technique in MRI-simulation for radiation therapy and assess the feasibility of using GEPCI images with advanced inhomogeneity correction in MRI-guided radiotherapy for brain treatment. Methods: An optimized multigradient-echo GRE sequence (TR=50ms;TE1=4ms;delta-TE=4ms;flip angle=300,11 Echoes) was developed to generate both structural (T1w and T2*w) and functional MRIs (field and susceptibility maps) from a single acquisition. One healthy subject (Subject1) and one post-surgical brain cancer patient (Subject2) were scanned on a Philips Ingenia 1.5T MRI used for radiation therapy simulation. Another healthy subject (Subject3) was scanned on a 0.35T MRI-guided radiotherapy (MR-IGRT) system (ViewRay).more » A voxel spread function (VSF) was used to correct the B0 inhomogeneities caused by surgical cavities and edema for Subject2. GEPCI images and standard radiotherapy planning MRIs for this patient were compared focusing the delineation of radiotherapy target region. Results: GEPCI brain images were successfully derived from all three subjects with scan times of <7 minutes. The images derived for Subjects1&2 demonstrated that GEPCI can be applied and combined into radiotherapy MRI simulation. Despite low field, T1-weighted and R2* images were successfully reconstructed for Subject3 and were satisfactory for contour and target delineation. The R2* distribution of grey matter (center=12,FWHM=4.5) and white matter (center=14.6, FWHM=2) demonstrated the feasibility for tissue segmentation and quantification. The voxel spread function(VSF) corrected surgical site related inhomogeneities for Subject2. R2* and quantitative susceptibility map(QSM) images for Subject2 can be used to quantitatively assess the brain structure response to radiation over the treatment course. Conclusion: We implemented the GEPCI technique in MRI-simulation and in MR-IGRT system for radiation therapy. The images demonstrated that it is feasible to adopt this technique in radiotherapy for structural delineation. The preliminary data also enable the opportunity for quantitative assessment of radiation response of the target region and normal tissue.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)

Parkin, E. R.; Bicknell, G. V., E-mail: parkin@mso.anu.edu.au

Global three-dimensional magnetohydrodynamic (MHD) simulations of turbulent accretion disks are presented which start from fully equilibrium initial conditions in which the magnetic forces are accounted for and the induction equation is satisfied. The local linear theory of the magnetorotational instability (MRI) is used as a predictor of the growth of magnetic field perturbations in the global simulations. The linear growth estimates and global simulations diverge when nonlinear motions-perhaps triggered by the onset of turbulence-upset the velocity perturbations used to excite the MRI. The saturated state is found to be independent of the initially excited MRI mode, showing that once themore » disk has expelled the initially net flux field and settled into quasi-periodic oscillations in the toroidal magnetic flux, the dynamo cycle regulates the global saturation stress level. Furthermore, time-averaged measures of converged turbulence, such as the ratio of magnetic energies, are found to be in agreement with previous works. In particular, the globally averaged stress normalized to the gas pressure <{alpha}{sub P}>bar = 0.034, with notably higher values achieved for simulations with higher azimuthal resolution. Supplementary tests are performed using different numerical algorithms and resolutions. Convergence with resolution during the initial linear MRI growth phase is found for 23-35 cells per scale height (in the vertical direction).« less
Recovering task fMRI signals from highly under-sampled data with low-rank and temporal subspace constraints.

PubMed

Chiew, Mark; Graedel, Nadine N; Miller, Karla L

2018-07-01

Recent developments in highly accelerated fMRI data acquisition have employed low-rank and/or sparsity constraints for image reconstruction, as an alternative to conventional, time-independent parallel imaging. When under-sampling factors are high or the signals of interest are low-variance, however, functional data recovery can be poor or incomplete. We introduce a method for improving reconstruction fidelity using external constraints, like an experimental design matrix, to partially orient the estimated fMRI temporal subspace. Combining these external constraints with low-rank constraints introduces a new image reconstruction model that is analogous to using a mixture of subspace-decomposition (PCA/ICA) and regression (GLM) models in fMRI analysis. We show that this approach improves fMRI reconstruction quality in simulations and experimental data, focusing on the model problem of detecting subtle 1-s latency shifts between brain regions in a block-design task-fMRI experiment. Successful latency discrimination is shown at acceleration factors up to R = 16 in a radial-Cartesian acquisition. We show that this approach works with approximate, or not perfectly informative constraints, where the derived benefit is commensurate with the information content contained in the constraints. The proposed method extends low-rank approximation methods for under-sampled fMRI data acquisition by leveraging knowledge of expected task-based variance in the data, enabling improvements in the speed and efficiency of fMRI data acquisition without the loss of subtle features. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Evaluating the potential of chelation therapy to prevent and treat gadolinium deposition from MRI contrast agents

DOE PAGES

Rees, Julian A.; Deblonde, Gauthier J. -P.; An, Dahlia D.; ...

2018-03-13

Several MRI contrast agent clinical formulations are now known to leave deposits of the heavy metal gadolinium in the brain, bones, and other organs of patients. This persistent biological accumulation of gadolinium has been recently recognized as a deleterious outcome in patients administered Gd-based contrast agents (GBCAs) for MRI, prompting the European Medicines Agency to recommend discontinuing the use of over half of the GBCAs currently approved for clinical applications. Here, to address this problem, we find that the orally-available metal decorporation agent 3,4,3-LI(1,2-HOPO) demonstrates superior efficacy at chelating and removing Gd from the body compared to diethylenetriaminepentaacetic acid, amore » ligand commonly used in the United States in the GBCA Gadopentetate (Magnevist). Using the radiotracer 153Gd to obtain precise biodistribution data, the results herein, supported by speciation simulations, suggest that the prophylactic or post-hoc therapeutic use of 3,4,3-LI(1,2-HOPO) may provide a means to mitigate Gd retention in patients requiring contrast-enhanced MRI.« less

Evaluating the potential of chelation therapy to prevent and treat gadolinium deposition from MRI contrast agents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rees, Julian A.; Deblonde, Gauthier J. -P.; An, Dahlia D.

Several MRI contrast agent clinical formulations are now known to leave deposits of the heavy metal gadolinium in the brain, bones, and other organs of patients. This persistent biological accumulation of gadolinium has been recently recognized as a deleterious outcome in patients administered Gd-based contrast agents (GBCAs) for MRI, prompting the European Medicines Agency to recommend discontinuing the use of over half of the GBCAs currently approved for clinical applications. Here, to address this problem, we find that the orally-available metal decorporation agent 3,4,3-LI(1,2-HOPO) demonstrates superior efficacy at chelating and removing Gd from the body compared to diethylenetriaminepentaacetic acid, amore » ligand commonly used in the United States in the GBCA Gadopentetate (Magnevist). Using the radiotracer 153Gd to obtain precise biodistribution data, the results herein, supported by speciation simulations, suggest that the prophylactic or post-hoc therapeutic use of 3,4,3-LI(1,2-HOPO) may provide a means to mitigate Gd retention in patients requiring contrast-enhanced MRI.« less
Biparametric MRI of the prostate.

PubMed

Scialpi, Michele; D'Andrea, Alfredo; Martorana, Eugenio; Malaspina, Corrado Maria; Aisa, Maria Cristina; Napoletano, Maria; Orlandi, Emanuele; Rondoni, Valeria; Scialpi, Pietro; Pacchiarini, Diamante; Palladino, Diego; Dragone, Michele; Di Renzo, Giancarlo; Simeone, Annalisa; Bianchi, Giampaolo; Brunese, Luca

2017-12-01

Biparametric Magnetic Resonance Imaging (bpMRI) of the prostate combining both morphologic T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) is emerging as an alternative to multiparametric MRI (mpMRI) to detect, to localize and to guide prostatic targeted biopsy in patients with suspicious prostate cancer (PCa). BpMRI overcomes some limitations of mpMRI such as the costs, the time required to perform the study, the use of gadolinium-based contrast agents and the lack of a guidance for management of score 3 lesions equivocal for significant PCa. In our experience the optimal and similar clinical results of the bpMRI in comparison to mpMRI are essentially related to the DWI that we consider the dominant sequence for detection suspicious PCa both in transition and in peripheral zone. In clinical practice, the adoption of bpMRI standardized scoring system, indicating the likelihood to diagnose a clinically significant PCa and establishing the management of each suspicious category (from 1 to 4), could represent the rationale to simplify and to improve the current interpretation of mpMRI based on Prostate Imaging and Reporting Archiving Data System version 2 (PI-RADS v2). In this review article we report and describe the current knowledge about bpMRI in the detection of suspicious PCa and a simplified PI-RADS based on bpMRI for management of each suspicious PCa categories to facilitate the communication between radiologists and urologists.
Biparametric MRI of the prostate

PubMed Central

Scialpi, Michele; D’Andrea, Alfredo; Martorana, Eugenio; Malaspina, Corrado Maria; Aisa, Maria Cristina; Napoletano, Maria; Orlandi, Emanuele; Rondoni, Valeria; Scialpi, Pietro; Pacchiarini, Diamante; Palladino, Diego; Dragone, Michele; Di Renzo, Giancarlo; Simeone, Annalisa; Bianchi, Giampaolo; Brunese, Luca

2017-01-01

Biparametric Magnetic Resonance Imaging (bpMRI) of the prostate combining both morphologic T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) is emerging as an alternative to multiparametric MRI (mpMRI) to detect, to localize and to guide prostatic targeted biopsy in patients with suspicious prostate cancer (PCa). BpMRI overcomes some limitations of mpMRI such as the costs, the time required to perform the study, the use of gadolinium-based contrast agents and the lack of a guidance for management of score 3 lesions equivocal for significant PCa. In our experience the optimal and similar clinical results of the bpMRI in comparison to mpMRI are essentially related to the DWI that we consider the dominant sequence for detection suspicious PCa both in transition and in peripheral zone. In clinical practice, the adoption of bpMRI standardized scoring system, indicating the likelihood to diagnose a clinically significant PCa and establishing the management of each suspicious category (from 1 to 4), could represent the rationale to simplify and to improve the current interpretation of mpMRI based on Prostate Imaging and Reporting Archiving Data System version 2 (PI-RADS v2). In this review article we report and describe the current knowledge about bpMRI in the detection of suspicious PCa and a simplified PI-RADS based on bpMRI for management of each suspicious PCa categories to facilitate the communication between radiologists and urologists. PMID:29201499
Artificial neural network for suppression of banding artifacts in balanced steady-state free precession MRI.

PubMed

Kim, Ki Hwan; Park, Sung-Hong

2017-04-01

The balanced steady-state free precession (bSSFP) MR sequence is frequently used in clinics, but is sensitive to off-resonance effects, which can cause banding artifacts. Often multiple bSSFP datasets are acquired at different phase cycling (PC) angles and then combined in a special way for banding artifact suppression. Many strategies of combining the datasets have been suggested for banding artifact suppression, but there are still limitations in their performance, especially when the number of phase-cycled bSSFP datasets is small. The purpose of this study is to develop a learning-based model to combine the multiple phase-cycled bSSFP datasets for better banding artifact suppression. Multilayer perceptron (MLP) is a feedforward artificial neural network consisting of three layers of input, hidden, and output layers. MLP models were trained by input bSSFP datasets acquired from human brain and knee at 3T, which were separately performed for two and four PC angles. Banding-free bSSFP images were generated by maximum-intensity projection (MIP) of 8 or 12 phase-cycled datasets and were used as targets for training the output layer. The trained MLP models were applied to another brain and knee datasets acquired with different scan parameters and also to multiple phase-cycled bSSFP functional MRI datasets acquired on rat brain at 9.4T, in comparison with the conventional MIP method. Simulations were also performed to validate the MLP approach. Both the simulations and human experiments demonstrated that MLP suppressed banding artifacts significantly, superior to MIP in both banding artifact suppression and SNR efficiency. MLP demonstrated superior performance over MIP for the 9.4T fMRI data as well, which was not used for training the models, while visually preserving the fMRI maps very well. Artificial neural network is a promising technique for combining multiple phase-cycled bSSFP datasets for banding artifact suppression. Copyright Â© 2016 Elsevier Inc. All rights reserved.
SU-F-J-125: Effects of Couch Position Variability On Dosimetric Accuracy with An MRI-Guided Co-60 Radiation Therapy Machine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chow, P; Thomas, D; Agazaryan, N

2016-06-15

Purpose: Magnetic resonance imaging (MRI) guidance in radiation therapy brings real-time imaging and adaptive planning into the treatment vault where it can account for interfraction and intrafraction movement of soft tissue. The only commercially-available MRI-guided radiation therapy device is a three-head 60Co and MRI system with an integrated treatment planning system (TPS). An up to 20% attenuation of the beam by the couch is well modeled in the TPS. However, variations in the patient’s day-to-day position introduce discrepancies in the actual couch position relative its location as modeled in the treatment plan. For this reason, our institution avoids plans withmore » beams that pass through or near the couch edges. This study looks at plans without restriction on beam angles and investigates the effects of couch shift by simulating shifts of the couch relative to the patient, in order to determine whether couch edge avoidance restrictions can be lifted. Methods: A total of 27 plans from 23 patients were investigated. Couch shifts of 1 and 2 cm were introduced in combinations of lateral and vertical direction to simulate variations in patient positioning on the couch giving 16 shifted plans per reference plan. The shift values of 1 and 2 cm were based on shifts recorded in 320 treatment fractions. Results: Measured couch attenuation versus TPS modeled agreed within 2.1%. Planning Target Volume (PTV) D95 changed less than 1% for 1 and 2 cm couch shifts in only the x-direction and less than 3% for all directions. Conclusion: The dosimetry of all plans with shifts up to ±2 cm was within reasonable clinical tolerances. Robustness of a plan to couch shifts can be tested in the TPS. Inclusion of beams traversing the couch edges should be considered if an improvement in plan quality or delivery time can be achieved.« less
Technical Note: Dosimetric effects of couch position variability on treatment plan quality with an MRI-guided Co-60 radiation therapy machine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chow, Phillip E., E-mail: pechow@mednet.ucla.edu

2016-08-15

Purpose: Magnetic resonance imaging (MRI) guidance in radiation therapy brings real-time imaging and adaptive planning into the treatment vault where it can account for interfraction and intrafraction movement of soft tissue. The only commercially available MRI-guided radiation therapy device is a three-head {sup 60}Co and MRI system with an integrated treatment planning system (TPS). Couch attenuation of the beam of up to 20% is well modeled in the TPS. Variations in the patient’s day-to-day position introduce discrepancies in the actual couch attenuation as modeled in the treatment plan. For this reason, the authors’ institution avoids plans with beams that passmore » through or near the couch edges. This study investigates the effects of differential beam attenuation by the couch due to couch shifts in order to determine whether couch edge avoidance restrictions can be lifted. Couch shifts were simulated using a Monte Carlo treatment planning system and ion chamber measurements performed for validation. Methods: A total of 27 plans from 23 patients were investigated. Couch shifts of 1 and 2 cm were introduced in combinations of lateral and vertical directions to simulate patient position variations giving 16 shifted plans per reference plan. The 1 and 2 cm shifts were based on shifts recorded in 320 treatment fractions. Results: Following TG176 recommendations for measurement methods, couch attenuation measurements agreed with TPS modeled attenuation to within 2.1%. Planning target volume D95 changed less than 1% for 1 and 2 cm couch shifts in only the x-direction and less than 3% for all directions. Conclusions: Dosimetry of all plans tested was robust to couch shifts up to ±2 cm. In general, couch shifts resulted in clinically insignificant dosimetric deviations. It is conceivable that in certain cases with large systematic couch shifts and plans that are particularly sensitive to shifts, dosimetric changes might rise to a clinically significant level.« less
Variation in uterus position prior to brachytherapy of the cervix: A case report.

PubMed

Georgescu, M T; Anghel, R

2017-01-01

Rationale: brachytherapy is administered in the treatment of patients with locally advanced cervical cancer following chemoradiotherapy. Lack of local anatomy evaluation prior to this procedure might lead to the selection of an inappropriate brachytherapy applicator, increasing the risk of side effects (e.g. uterus perforation, painful procedure ...). Objective: To assess the movement of the uterus and cervix prior to brachytherapy in patients with gynecological cancer, in order to select the proper type of brachytherapy applicator. Also we wanted to promote the replacement of the plain X-ray brachytherapy with the image-guided procedure. Methods and results: We presented the case of a 41-year-old female diagnosed with a biopsy that was proven cervical cancer stage IIIB. At diagnosis, the imaging studies identified an anteverted uterus. The patient underwent preoperative chemoradiotherapy. Prior to brachytherapy, the patient underwent a pelvic magnetic resonance imaging (MRI), which identified a displacement of the uterus in the retroverted position. Discussion: A great variety of brachytherapy applicators is available nowadays. Major changes in uterus position and lack of evaluation prior to brachytherapy might lead to a higher rate of incidents during this procedure. Also, by using orthogonal simulation and bidimensional (2D) treatment planning, brachytherapy would undoubtedly fail to treat the remaining tumoral tissue. This is the reason why we proposed the implementation of a prior imaging of the uterus and computed tomography (CT)/ MRI-based simulation in the brachytherapy procedure. Abbreviations: MRI = magnetic resonance imaging, CT = computed tomography, CTV = clinical target volume, DVH = dose-volume histogram, EBRT = external beam radiotherapy, GTV = gross tumor volume, Gy = Gray (unit), ICRU = International Commission of Radiation Units, IGRT = image guided radiotherapy, IM = internal margin, IMRT = image modulated radiotherapy, ITV = internal target volume, MRI = magnetic resonance imaging, OAR = organs at risk, PTV = planning target volume, QUANTEC = Quantitative Analyses of Normal Tissue Effects in the Clinic.
Reproducibility of CMRO2 determination using dynamic 17 O MRI.

PubMed

Niesporek, Sebastian C; Umathum, Reiner; Lommen, Jonathan M; Behl, Nicolas G R; Paech, Daniel; Bachert, Peter; Ladd, Mark E; Nagel, Armin M

2018-06-01

To assess the reproducibility of 17 O MRI-based determination of the cerebral metabolic rate of oxygen consumption (CMRO 2 ) in healthy volunteers. To assess the influence of image acquisition and reconstruction parameters on dynamic quantification of functional parameters such as CMRO 2 . Dynamic 17 O MRI data were simulated and used to investigate influences of temporal resolution (Δt) and partial volume correction (PVC) on the determination of CMRO 2 . Three healthy volunteers were examined in two separate examinations. In vivo 17 O MRI measurements were conducted with a nominal spatial resolution of (7.5 mm) 3 using a density-adapted radial sequence with golden angle acquisition scheme. In each measurement, 4.0 ± 0.1 L of 70%-enriched 17 O gas were administered using a rebreathing system. Data were corrected with a PVC algorithm, and CMRO 2 was determined in gray matter (GM) and white matter (WM) compartments using a three-phase metabolic model (baseline, 17 O inhalation, decay phase). Comparison with the ground truth of simulations revealed improved CMRO 2 determination after application of PVC and with Δt ≤ 2:00 min. Evaluation of in vivo data yields to CMRO 2,GM = 2.31 ± 0.1 μmol/g/min and to CMRO 2,WM = 0.69 ± 0.04 μmol/g/min with coefficients of variation (CoV) of 0.3-5.5% and 4.3-5.0% for intra-volunteer and inter-volunteer data, respectively. This in vivo 17 O inhalation study demonstrated that the proposed experimental setup enables reproducible determination of CMRO 2 in healthy volunteers. Magn Reson Med 79:2923-2934, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
Inputs for subject-specific computational fluid dynamics simulation of blood flow in the mouse aorta.

PubMed

Van Doormaal, Mark; Zhou, Yu-Qing; Zhang, Xiaoli; Steinman, David A; Henkelman, R Mark

2014-10-01

Mouse models are an important way for exploring relationships between blood hemodynamics and eventual plaque formation. We have developed a mouse model of aortic regurgitation (AR) that produces large changes in plaque burden with charges in hemodynamics [Zhou et al., 2010, "Aortic Regurgitation Dramatically Alters the Distribution of Atherosclerotic Lesions and Enhances Atherogenesis in Mice," Arterioscler. Thromb. Vasc. Biol., 30(6), pp. 1181-1188]. In this paper, we explore the amount of detail needed for realistic computational fluid dynamics (CFD) calculations in this experimental model. The CFD calculations use inputs based on experimental measurements from ultrasound (US), micro computed tomography (CT), and both anatomical magnetic resonance imaging (MRI) and phase contrast MRI (PC-MRI). The adequacy of five different levels of model complexity (a) subject-specific CT data from a single mouse; (b) subject-specific CT centerlines with radii from US; (c) same as (b) but with MRI derived centerlines; (d) average CT centerlines and averaged vessel radius and branching vessels; and (e) same as (d) but with averaged MRI centerlines) is evaluated by demonstrating their impact on relative residence time (RRT) outputs. The paper concludes by demonstrating the necessity of subject-specific geometry and recommends for inputs the use of CT or anatomical MRI for establishing the aortic centerlines, M-mode US for scaling the aortic diameters, and a combination of PC-MRI and Doppler US for estimating the spatial and temporal characteristics of the input wave forms.
Evaluating MRI based vascular wall motion as a biomarker of Fontan hemodynamic performance

NASA Astrophysics Data System (ADS)

Menon, Prahlad G.; Hong, Haifa

2015-03-01

The Fontan procedure for single-ventricle heart disease involves creation of pathways to divert venous blood from the superior & inferior venacavae (SVC, IVC) directly into the pulmonary arteries (PA), bypassing the right ventricle. For optimal surgical outcomes, venous flow energy loss in the resulting vascular construction must be minimized and ensuring close to equal flow distribution from the Fontan conduit connecting IVC to the left & right PA is paramount. This requires patient-specific hemodynamic evaluation using computational fluid dynamics (CFD) simulations which are often time and resource intensive, limiting applicability for real-time patient management in the clinic. In this study, we report preliminary efforts at identifying a new non-invasive imaging based surrogate for CFD simulated hemodynamics. We establish correlations between computed hemodynamic criteria from CFD modeling and cumulative wall displacement characteristics of the Fontan conduit quantified from cine cardiovascular MRI segmentations over time (i.e. 20 cardiac phases gated from the start of ventricular systole), in 5 unique Fontan surgical connections. To focus our attention on diameter variations while discounting side-to-side swaying motion of the Fontan conduit, the difference between its instantaneous regional expansion and inward contraction (averaged across the conduit) was computed and analyzed. Maximum Fontan conduit-average expansion over the cardiac cycle correlated with the anatomy-specific diametric offset between the axis of the IVC and SVC (r2=0.13, p=0.55) - a known factor correlated with Fontan energy loss and IVC-to-PA flow distribution. Investigation in a larger study cohort is needed to establish stronger statistical correlations.
Real-Time MRI-Guided Cardiac Cryo-Ablation: A Feasibility Study.

PubMed

Kholmovski, Eugene G; Coulombe, Nicolas; Silvernagel, Joshua; Angel, Nathan; Parker, Dennis; Macleod, Rob; Marrouche, Nassir; Ranjan, Ravi

2016-05-01

MRI-based ablation provides an attractive capability of seeing ablation-related tissue changes in real time. Here we describe a real-time MRI-based cardiac cryo-ablation system. Studies were performed in canine model (n = 4) using MR-compatible cryo-ablation devices built for animal use: focal cryo-catheter with 8 mm tip and 28 mm diameter cryo-balloon. The main steps of MRI-guided cardiac cryo-ablation procedure (real-time navigation, confirmation of tip-tissue contact, confirmation of vessel occlusion, real-time monitoring of a freeze zone formation, and intra-procedural assessment of lesions) were validated in a 3 Tesla clinical MRI scanner. The MRI compatible cryo-devices were advanced to the right atrium (RA) and right ventricle (RV) and their position was confirmed by real-time MRI. Specifically, contact between catheter tip and myocardium and occlusion of superior vena cava (SVC) by the balloon was visually validated. Focal cryo-lesions were created in the RV septum. Circumferential ablation of SVC-RA junction with no gaps was achieved using the cryo-balloon. Real-time visualization of freeze zone formation was achieved in all studies when lesions were successfully created. The ablations and presence of collateral damage were confirmed by T1-weighted and late gadolinium enhancement MRI and gross pathological examination. This study confirms the feasibility of a MRI-based cryo-ablation system in performing cardiac ablation procedures. The system allows real-time catheter navigation, confirmation of catheter tip-tissue contact, validation of vessel occlusion by cryo-balloon, real-time monitoring of a freeze zone formation, and intra-procedural assessment of ablations including collateral damage. © 2016 Wiley Periodicals, Inc.
Differential activation of brain regions involved with error-feedback and imitation based motor simulation when observing self and an expert's actions in pilots and non-pilots on a complex glider landing task.

PubMed

Callan, Daniel E; Terzibas, Cengiz; Cassel, Daniel B; Callan, Akiko; Kawato, Mitsuo; Sato, Masa-Aki

2013-05-15

In this fMRI study we investigate neural processes related to the action observation network using a complex perceptual-motor task in pilots and non-pilots. The task involved landing a glider (using aileron, elevator, rudder, and dive brake) as close to a target as possible, passively observing a replay of one's own previous trial, passively observing a replay of an expert's trial, and a baseline do nothing condition. The objective of this study is to investigate two types of motor simulation processes used during observation of action: imitation based motor simulation and error-feedback based motor simulation. It has been proposed that the computational neurocircuitry of the cortex is well suited for unsupervised imitation based learning, whereas, the cerebellum is well suited for error-feedback based learning. Consistent with predictions, pilots (to a greater extent than non-pilots) showed significant differential activity when observing an expert landing the glider in brain regions involved with imitation based motor simulation (including premotor cortex PMC, inferior frontal gyrus IFG, anterior insula, parietal cortex, superior temporal gyrus, and middle temporal MT area) than when observing one's own previous trial which showed significant differential activity in the cerebellum (only for pilots) thought to be concerned with error-feedback based motor simulation. While there was some differential brain activity for pilots in regions involved with both Execution and Observation of the flying task (potential Mirror System sites including IFG, PMC, superior parietal lobule) the majority was adjacent to these areas (Observation Only Sites) (predominantly in PMC, IFG, and inferior parietal loblule). These regions showing greater activity for observation than for action may be involved with processes related to motor-based representational transforms that are not necessary when actually carrying out the task. Copyright © 2013 Elsevier Inc. All rights reserved.
A hybrid method for classifying cognitive states from fMRI data.

PubMed

Parida, S; Dehuri, S; Cho, S-B; Cacha, L A; Poznanski, R R

2015-09-01

Functional magnetic resonance imaging (fMRI) makes it possible to detect brain activities in order to elucidate cognitive-states. The complex nature of fMRI data requires under-standing of the analyses applied to produce possible avenues for developing models of cognitive state classification and improving brain activity prediction. While many models of classification task of fMRI data analysis have been developed, in this paper, we present a novel hybrid technique through combining the best attributes of genetic algorithms (GAs) and ensemble decision tree technique that consistently outperforms all other methods which are being used for cognitive-state classification. Specifically, this paper illustrates the combined effort of decision-trees ensemble and GAs for feature selection through an extensive simulation study and discusses the classification performance with respect to fMRI data. We have shown that our proposed method exhibits significant reduction of the number of features with clear edge classification accuracy over ensemble of decision-trees.
Combining transrectal ultrasound and CT for image-guided adaptive brachytherapy of cervical cancer: Proof of concept.

PubMed

Nesvacil, Nicole; Schmid, Maximilian P; Pötter, Richard; Kronreif, Gernot; Kirisits, Christian

To investigate the feasibility of a treatment planning workflow for three-dimensional image-guided cervix cancer brachytherapy, combining volumetric transrectal ultrasound (TRUS) for target definition with CT for dose optimization to organs at risk (OARs), for settings with no access to MRI. A workflow for TRUS/CT-based volumetric treatment planning was developed, based on a customized system including ultrasound probe, stepper unit, and software for image volume acquisition. A full TRUS/CT-based workflow was simulated in a clinical case and compared with MR- or CT-only delineation. High-risk clinical target volume was delineated on TRUS, and OARs were delineated on CT. Manually defined tandem/ring applicator positions on TRUS and CT were used as a reference for rigid registration of the image volumes. Treatment plan optimization for TRUS target and CT organ volumes was performed and compared to MRI and CT target contours. TRUS/CT-based contouring, applicator reconstruction, image fusion, and treatment planning were feasible, and the full workflow could be successfully demonstrated. The TRUS/CT plan fulfilled all clinical planning aims. Dose-volume histogram evaluation of the TRUS/CT-optimized plan (high-risk clinical target volume D 90 , OARs D 2cm³ for) on different image modalities showed good agreement between dose values reported for TRUS/CT and MRI-only reference contours and large deviations for CT-only target parameters. A TRUS/CT-based workflow for full three-dimensional image-guided cervix brachytherapy treatment planning seems feasible and may be clinically comparable to MRI-based treatment planning. Further development to solve challenges with applicator definition in the TRUS volume is required before systematic applicability of this workflow. Copyright Â© 2016 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.
Blunt forehead trauma and optic canal involvement: finite element analysis of anterior skull base and orbit on causes of vision impairment.

PubMed

Huempfner-Hierl, Heike; Bohne, Alexander; Wollny, Gert; Sterker, Ina; Hierl, Thomas

2015-10-01

Clinical studies report on vision impairment after blunt frontal head trauma. A possible cause is damage to the optic nerve bundle within the optic canal due to microfractures of the anterior skull base leading to indirect traumatic optic neuropathy. A finite element study simulating impact forces on the paramedian forehead in different grades was initiated. The set-up consisted of a high-resolution skull model with about 740 000 elements, a blunt impactor and was solved in a transient time-dependent simulation. Individual bone material parameters were calculated for each volume element to increase realism. Results showed stress propagation from the frontal impact towards the optic foramen and the chiasm even at low-force fist-like impacts. Higher impacts produced stress patterns corresponding to typical fracture patterns of the anterior skull base including the optic canal. Transient simulation discerned two stress peaks equalling oscillation. It can be concluded that even comparatively low stresses and oscillation in the optic foramen may cause micro damage undiscerned by CT or MRI explaining consecutive vision loss. Higher impacts lead to typical comminuted fractures, which may affect the integrity of the optic canal. Finite element simulation can be effectively used in studying head trauma and its clinical consequences. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Intersession reliability of fMRI activation for heat pain and motor tasks

PubMed Central

Quiton, Raimi L.; Keaser, Michael L.; Zhuo, Jiachen; Gullapalli, Rao P.; Greenspan, Joel D.

2014-01-01

As the practice of conducting longitudinal fMRI studies to assess mechanisms of pain-reducing interventions becomes more common, there is a great need to assess the test–retest reliability of the pain-related BOLD fMRI signal across repeated sessions. This study quantitatively evaluated the reliability of heat pain-related BOLD fMRI brain responses in healthy volunteers across 3 sessions conducted on separate days using two measures: (1) intraclass correlation coefficients (ICC) calculated based on signal amplitude and (2) spatial overlap. The ICC analysis of pain-related BOLD fMRI responses showed fair-to-moderate intersession reliability in brain areas regarded as part of the cortical pain network. Areas with the highest intersession reliability based on the ICC analysis included the anterior midcingulate cortex, anterior insula, and second somatosensory cortex. Areas with the lowest intersession reliability based on the ICC analysis also showed low spatial reliability; these regions included pregenual anterior cingulate cortex, primary somatosensory cortex, and posterior insula. Thus, this study found regional differences in pain-related BOLD fMRI response reliability, which may provide useful information to guide longitudinal pain studies. A simple motor task (finger-thumb opposition) was performed by the same subjects in the same sessions as the painful heat stimuli were delivered. Intersession reliability of fMRI activation in cortical motor areas was comparable to previously published findings for both spatial overlap and ICC measures, providing support for the validity of the analytical approach used to assess intersession reliability of pain-related fMRI activation. A secondary finding of this study is that the use of standard ICC alone as a measure of reliability may not be sufficient, as the underlying variance structure of an fMRI dataset can result in inappropriately high ICC values; a method to eliminate these false positive results was used in this study and is recommended for future studies of test–retest reliability. PMID:25161897
Parameter estimation of brain tumors using intraoperative thermal imaging based on artificial tactile sensing in conjunction with artificial neural network

NASA Astrophysics Data System (ADS)

Sadeghi-Goughari, M.; Mojra, A.; Sadeghi, S.

2016-02-01

Intraoperative Thermal Imaging (ITI) is a new minimally invasive diagnosis technique that can potentially locate margins of brain tumor in order to achieve maximum tumor resection with least morbidity. This study introduces a new approach to ITI based on artificial tactile sensing (ATS) technology in conjunction with artificial neural networks (ANN) and feasibility and applicability of this method in diagnosis and localization of brain tumors is investigated. In order to analyze validity and reliability of the proposed method, two simulations were performed. (i) An in vitro experimental setup was designed and fabricated using a resistance heater embedded in agar tissue phantom in order to simulate heat generation by a tumor in the brain tissue; and (ii) A case report patient with parafalcine meningioma was presented to simulate ITI in the neurosurgical procedure. In the case report, both brain and tumor geometries were constructed from MRI data and tumor temperature and depth of location were estimated. For experimental tests, a novel assisted surgery robot was developed to palpate the tissue phantom surface to measure temperature variations and ANN was trained to estimate the simulated tumor’s power and depth. Results affirm that ITI based ATS is a non-invasive method which can be useful to detect, localize and characterize brain tumors.
Design and development of MR-compatible SPECT systems for simultaneous SPECT-MR imaging of small animals

NASA Astrophysics Data System (ADS)

Tsui, Benjamin M. W.; Hugg, James W.; Xu, Jingyan; Chen, Si; Meier, Dirk; Edelstein, William; El-Sharkawy, Abdel; Wagenaar, Douglas J.; Patt, Bradley E.

2011-03-01

We describe a continuing design and development of MR-compatible SPECT systems for simultaneous SPECT-MR imaging of small animals. A first generation prototype SPECT system was designed and constructed to fit inside a MRI system with a gradient bore inner diameter of 12 cm. It consists of 3 angularly offset rings of 8 detectors (1"x1", 16x16 pixels MR-compatible solid-state CZT). A matching 24-pinhole collimator sleeve, made of a tungsten-compound, provides projections from a common FOV of ~25 mm. A birdcage RF coil for MRI data acquisition surrounds the collimator. The SPECT system was tested inside a clinical 3T MRI system. Minimal interference was observed on the simultaneously acquired SPECT and MR images. We developed a sparse-view image reconstruction method based on accurate modeling of the point response function (PRF) of each of the 24 pinholes to provide artifact-free SPECT images. The stationary SPECT system provides relatively low resolution of 3-5 mm but high geometric efficiency of 0.5- 1.2% for fast dynamic acquisition, demonstrated in a SPECT renal kinetics study using Tc-99m DTPA. Based on these results, a second generation prototype MR-compatible SPECT system with an outer diameter of 20 cm that fits inside a mid-sized preclinical MRI system is being developed. It consists of 5 rings of 19 CZT detectors. The larger ring diameter allows the use of optimized multi-pinhole collimator designs, such as high system resolution up to ~1 mm, high geometric efficiency, or lower system resolution without collimator rotation. The anticipated performance of the new system is supported by simulation data.
MRI-based, wireless determination of the transfer function of a linear implant: Introduction of the transfer matrix.

PubMed

Tokaya, Janot P; Raaijmakers, Alexander J E; Luijten, Peter R; van den Berg, Cornelis A T

2018-04-24

We introduce the transfer matrix (TM) that makes MR-based wireless determination of transfer functions (TFs) possible. TFs are implant specific measures for RF-safety assessment of linear implants. The TF relates an incident tangential electric field on an implant to a scattered electric field at its tip that generally governs local heating. The TM extends this concept and relates an incident tangential electric field to a current distribution in the implant therewith characterizing the RF response along the entire implant. The TM is exploited to measure TFs with MRI without hardware alterations. A model of rightward and leftward propagating attenuated waves undergoing multiple reflections is used to derive an analytical expression for the TM. This allows parameterization of the TM of generic implants, e.g., (partially) insulated single wires, in a homogeneous medium in a few unknowns that simultaneously describe the TF. These unknowns can be determined with MRI making it possible to measure the TM and, therefore, also the TF. The TM is able to predict an induced current due to an incident electric field and can be accurately parameterized with a limited number of unknowns. Using this description the TF is determined accurately (with a Pearson correlation coefficient R ≥ 0.9 between measurements and simulations) from MRI acquisitions. The TM enables measuring of TFs with MRI of the tested generic implant models. The MR-based method does not need hardware alterations and is wireless hence making TF determination in more realistic scenarios conceivable. © 2018 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
Detection of infarct lesions from single MRI modality using inconsistency between voxel intensity and spatial location--a 3-D automatic approach.

PubMed

Shen, Shan; Szameitat, André J; Sterr, Annette

2008-07-01

Detection of infarct lesions using traditional segmentation methods is always problematic due to intensity similarity between lesions and normal tissues, so that multispectral MRI modalities were often employed for this purpose. However, the high costs of MRI scan and the severity of patient conditions restrict the collection of multiple images. Therefore, in this paper, a new 3-D automatic lesion detection approach was proposed, which required only a single type of anatomical MRI scan. It was developed on a theory that, when lesions were present, the voxel-intensity-based segmentation and the spatial-location-based tissue distribution should be inconsistent in the regions of lesions. The degree of this inconsistency was calculated, which indicated the likelihood of tissue abnormality. Lesions were identified when the inconsistency exceeded a defined threshold. In this approach, the intensity-based segmentation was implemented by the conventional fuzzy c-mean (FCM) algorithm, while the spatial location of tissues was provided by prior tissue probability maps. The use of simulated MRI lesions allowed us to quantitatively evaluate the performance of the proposed method, as the size and location of lesions were prespecified. The results showed that our method effectively detected lesions with 40-80% signal reduction compared to normal tissues (similarity index > 0.7). The capability of the proposed method in practice was also demonstrated on real infarct lesions from 15 stroke patients, where the lesions detected were in broad agreement with true lesions. Furthermore, a comparison to a statistical segmentation approach presented in the literature suggested that our 3-D lesion detection approach was more reliable. Future work will focus on adapting the current method to multiple sclerosis lesion detection.

Dynamic contrast-enhanced MRI: Study of inter-software accuracy and reproducibility using simulated and clinical data.

PubMed

Beuzit, Luc; Eliat, Pierre-Antoine; Brun, Vanessa; Ferré, Jean-Christophe; Gandon, Yves; Bannier, Elise; Saint-Jalmes, Hervé

2016-06-01

To test the reproducibility and accuracy of pharmacokinetic parameter measurements on five analysis software packages (SPs) for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), using simulated and clinical data. This retrospective study was Institutional Review Board-approved. Simulated tissues consisted of pixel clusters of calculated dynamic signal changes for combinations of Tofts model pharmacokinetic parameters (volume transfer constant [K(trans) ], extravascular extracellular volume fraction [ve ]), longitudinal relaxation time (T1 ). The clinical group comprised 27 patients treated for rectal cancer, with 36 3T DCE-MR scans performed between November 2012 and February 2014, including dual-flip-angle T1 mapping and a dynamic postcontrast T1 -weighted, 3D spoiled gradient-echo sequence. The clinical and simulated images were postprocessed with five SPs to measure K(trans) , ve , and the initial area under the gadolinium curve (iAUGC). Modified Bland-Altman analysis was conducted, intraclass correlation coefficients (ICCs) and within-subject coefficients of variation were calculated. Thirty-one examinations from 23 patients were of sufficient technical quality and postprocessed. Measurement errors were observed on the simulated data for all the pharmacokinetic parameters and SPs, with a bias ranging from -0.19 min(-1) to 0.09 min(-1) for K(trans) , -0.15 to 0.01 for ve , and -0.65 to 1.66 mmol.L(-1) .min for iAUGC. The ICC between SPs revealed moderate agreement for the simulated data (K(trans) : 0.50; ve : 0.67; iAUGC: 0.77) and very poor agreement for the clinical data (K(trans) : 0.10; ve : 0.16; iAUGC: 0.21). Significant errors were found in the calculated DCE-MRI pharmacokinetic parameters for the perfusion analysis SPs, resulting in poor inter-software reproducibility. J. Magn. Reson. Imaging 2016;43:1288-1300. © 2015 Wiley Periodicals, Inc.
Efficient method to design RF pulses for parallel excitation MRI using gridding and conjugate gradient

PubMed Central

Feng, Shuo

2014-01-01

Parallel excitation (pTx) techniques with multiple transmit channels have been widely used in high field MRI imaging to shorten the RF pulse duration and/or reduce the specific absorption rate (SAR). However, the efficiency of pulse design still needs substantial improvement for practical real-time applications. In this paper, we present a detailed description of a fast pulse design method with Fourier domain gridding and a conjugate gradient method. Simulation results of the proposed method show that the proposed method can design pTx pulses at an efficiency 10 times higher than that of the conventional conjugate-gradient based method, without reducing the accuracy of the desirable excitation patterns. PMID:24834420
Efficient method to design RF pulses for parallel excitation MRI using gridding and conjugate gradient.

PubMed

Feng, Shuo; Ji, Jim

2014-04-01

Parallel excitation (pTx) techniques with multiple transmit channels have been widely used in high field MRI imaging to shorten the RF pulse duration and/or reduce the specific absorption rate (SAR). However, the efficiency of pulse design still needs substantial improvement for practical real-time applications. In this paper, we present a detailed description of a fast pulse design method with Fourier domain gridding and a conjugate gradient method. Simulation results of the proposed method show that the proposed method can design pTx pulses at an efficiency 10 times higher than that of the conventional conjugate-gradient based method, without reducing the accuracy of the desirable excitation patterns.
Phase unwrapping using region-based markov random field model.

PubMed

Dong, Ying; Ji, Jim

2010-01-01

Phase unwrapping is a classical problem in Magnetic Resonance Imaging (MRI), Interferometric Synthetic Aperture Radar and Sonar (InSAR/InSAS), fringe pattern analysis, and spectroscopy. Although many methods have been proposed to address this problem, robust and effective phase unwrapping remains a challenge. This paper presents a novel phase unwrapping method using a region-based Markov Random Field (MRF) model. Specifically, the phase image is segmented into regions within which the phase is not wrapped. Then, the phase image is unwrapped between different regions using an improved Highest Confidence First (HCF) algorithm to optimize the MRF model. The proposed method has desirable theoretical properties as well as an efficient implementation. Simulations and experimental results on MRI images show that the proposed method provides similar or improved phase unwrapping than Phase Unwrapping MAx-flow/min-cut (PUMA) method and ZpM method.
Cost Analysis of MRI Services in Iran: An Application of Activity Based Costing Technique

PubMed Central

Bayati, Mohsen; Mahboub Ahari, Alireza; Badakhshan, Abbas; Gholipour, Mahin; Joulaei, Hassan

2015-01-01

Background: Considerable development of MRI technology in diagnostic imaging, high cost of MRI technology and controversial issues concerning official charges (tariffs) have been the main motivations to define and implement this study. Objectives: The present study aimed to calculate the unit-cost of MRI services using activity-based costing (ABC) as a modern cost accounting system and to fairly compare calculated unit-costs with official charges (tariffs). Materials and Methods: We included both direct and indirect costs of MRI services delivered in fiscal year 2011 in Shiraz Shahid Faghihi hospital. Direct allocation method was used for distribution of overhead costs. We used micro-costing approach to calculate unit-cost of all different MRI services. Clinical cost data were retrieved from the hospital registering system. Straight-line method was used for depreciation cost estimation. To cope with uncertainty and to increase the robustness of study results, unit costs of 33 MRI services was calculated in terms of two scenarios. Results: Total annual cost of MRI activity center (AC) was calculated at USD 400,746 and USD 532,104 based on first and second scenarios, respectively. Ten percent of the total cost was allocated from supportive departments. The annual variable costs of MRI center were calculated at USD 295,904. Capital costs measured at USD 104,842 and USD 236, 200 resulted from the first and second scenario, respectively. Existing tariffs for more than half of MRI services were above the calculated costs. Conclusion: As a public hospital, there are considerable limitations in both financial and administrative databases of Shahid Faghihi hospital. Labor cost has the greatest share of total annual cost of Shahid Faghihi hospital. The gap between unit costs and tariffs implies that the claim for extra budget from health providers may not be relevant for all services delivered by the studied MRI center. With some adjustments, ABC could be implemented in MRI centers. With the settlement of a reliable cost accounting system such as ABC technique, hospitals would be able to generate robust evidences for financial management of their overhead, intermediate and final ACs. PMID:26715979
Cost Analysis of MRI Services in Iran: An Application of Activity Based Costing Technique.

PubMed

Bayati, Mohsen; Mahboub Ahari, Alireza; Badakhshan, Abbas; Gholipour, Mahin; Joulaei, Hassan

2015-10-01

Considerable development of MRI technology in diagnostic imaging, high cost of MRI technology and controversial issues concerning official charges (tariffs) have been the main motivations to define and implement this study. The present study aimed to calculate the unit-cost of MRI services using activity-based costing (ABC) as a modern cost accounting system and to fairly compare calculated unit-costs with official charges (tariffs). We included both direct and indirect costs of MRI services delivered in fiscal year 2011 in Shiraz Shahid Faghihi hospital. Direct allocation method was used for distribution of overhead costs. We used micro-costing approach to calculate unit-cost of all different MRI services. Clinical cost data were retrieved from the hospital registering system. Straight-line method was used for depreciation cost estimation. To cope with uncertainty and to increase the robustness of study results, unit costs of 33 MRI services was calculated in terms of two scenarios. Total annual cost of MRI activity center (AC) was calculated at USD 400,746 and USD 532,104 based on first and second scenarios, respectively. Ten percent of the total cost was allocated from supportive departments. The annual variable costs of MRI center were calculated at USD 295,904. Capital costs measured at USD 104,842 and USD 236, 200 resulted from the first and second scenario, respectively. Existing tariffs for more than half of MRI services were above the calculated costs. As a public hospital, there are considerable limitations in both financial and administrative databases of Shahid Faghihi hospital. Labor cost has the greatest share of total annual cost of Shahid Faghihi hospital. The gap between unit costs and tariffs implies that the claim for extra budget from health providers may not be relevant for all services delivered by the studied MRI center. With some adjustments, ABC could be implemented in MRI centers. With the settlement of a reliable cost accounting system such as ABC technique, hospitals would be able to generate robust evidences for financial management of their overhead, intermediate and final ACs.
Measuring neuroplasticity associated with cerebral palsy rehabilitation: An MRI based power analysis.

PubMed

Reid, Lee B; Pagnozzi, Alex M; Fiori, Simona; Boyd, Roslyn N; Dowson, Nicholas; Rose, Stephen E

2017-05-01

Researchers in the field of child neurology are increasingly looking to supplement clinical trials of motor rehabilitation with neuroimaging in order to better understand the relationship between behavioural training, brain changes, and clinical improvements. Randomised controlled trials are typically accompanied by sample size calculations to detect clinical improvements but, despite the large cost of neuroimaging, not equivalent calculations for concurrently acquired imaging neuroimaging measures of changes in response to intervention. To aid in this regard, a power analysis was conducted for two measures of brain changes that may be indexed in a trial of rehabilitative therapy for cerebral palsy: cortical thickness of the impaired primary sensorimotor cortex, and fractional anisotropy of the impaired, delineated corticospinal tract. Power for measuring fractional anisotropy was assessed for both region-of-interest-seeded and fMRI-seeded diffusion tractography. Taking into account practical limitations, as well as data loss due to behavioural and image-processing issues, estimated required participant numbers were 101, 128 and 59 for cortical thickness, region-of-interest-based tractography, and fMRI-seeded tractography, respectively. These numbers are not adjusted for study attrition. Although these participant numbers may be out of reach of many trials, several options are available to improve statistical power, including careful preparation of participants for scanning using mock simulators, careful consideration of image processing options, and enrolment of as homogeneous a cohort as possible. This work suggests that smaller and moderate sized studies give genuine consideration to harmonising scanning protocols between groups to allow the pooling of data. Copyright © 2017 ISDN. All rights reserved.
Can the Diagnostics of Triangular Fibrocartilage Complex Lesions Be Improved by MRI-Based Soft-Tissue Reconstruction? An Imaging-Based Workup and Case Presentation.

PubMed

Hammer, Niels; Hirschfeld, Ulrich; Strunz, Hendrik; Werner, Michael; Wolfskämpf, Thomas; Löffler, Sabine

2017-01-01

Introduction . The triangular fibrocartilage complex (TFCC) provides both mobility and stability of the radiocarpal joint. TFCC lesions are difficult to diagnose due to the complex anatomy. The standard treatment for TFCC lesions is arthroscopy, posing surgery-related risks onto the patients. This feasibility study aimed at developing a workup for soft-tissue reconstruction using clinical imaging, to verify these results in retrospective patient data. Methods . Microcomputed tomography ( μ -CT), 3 T magnetic resonance imaging (MRI), and plastination were used to visualize the TFCC in cadaveric specimens applying segmentation-based 3D reconstruction. This approach further trialed the MRI dataset of a patient with minor radiological TFCC alterations but persistent pain. Results . TFCC reconstruction was impossible using μ -CT only but feasible using MRI, resulting in an appreciation of its substructures, as seen in the plastinates. Applying this approach allowed for visualizing a Palmer 2C lesion in a patient, confirming ex postum the arthroscopy findings, being markedly different from MRI (Palmer 1B). Discussion . This preliminary study showed that image-based TFCC reconstruction may help to identify pathologies invisible in standard MRI. The combined approach of μ -CT, MRI, and plastination allowed for a three-dimensional appreciation of the TFCC. Image quality and time expenditure limit the approach's usefulness as a diagnostic tool.
Can the Diagnostics of Triangular Fibrocartilage Complex Lesions Be Improved by MRI-Based Soft-Tissue Reconstruction? An Imaging-Based Workup and Case Presentation

PubMed Central

Hirschfeld, Ulrich; Strunz, Hendrik; Werner, Michael; Wolfskämpf, Thomas; Löffler, Sabine

2017-01-01

Introduction. The triangular fibrocartilage complex (TFCC) provides both mobility and stability of the radiocarpal joint. TFCC lesions are difficult to diagnose due to the complex anatomy. The standard treatment for TFCC lesions is arthroscopy, posing surgery-related risks onto the patients. This feasibility study aimed at developing a workup for soft-tissue reconstruction using clinical imaging, to verify these results in retrospective patient data. Methods. Microcomputed tomography (μ-CT), 3 T magnetic resonance imaging (MRI), and plastination were used to visualize the TFCC in cadaveric specimens applying segmentation-based 3D reconstruction. This approach further trialed the MRI dataset of a patient with minor radiological TFCC alterations but persistent pain. Results. TFCC reconstruction was impossible using μ-CT only but feasible using MRI, resulting in an appreciation of its substructures, as seen in the plastinates. Applying this approach allowed for visualizing a Palmer 2C lesion in a patient, confirming ex postum the arthroscopy findings, being markedly different from MRI (Palmer 1B). Discussion. This preliminary study showed that image-based TFCC reconstruction may help to identify pathologies invisible in standard MRI. The combined approach of μ-CT, MRI, and plastination allowed for a three-dimensional appreciation of the TFCC. Image quality and time expenditure limit the approach's usefulness as a diagnostic tool. PMID:28246600
Permittivity and performance of dielectric pads with sintered ceramic beads in MRI: early experiments and simulations at 3 T.

PubMed

Luo, Wei; Lanagan, Michael T; Sica, Christopher T; Ryu, Yeunchul; Oh, Sukhoon; Ketterman, Matthew; Yang, Qing X; Collins, Christopher M

2013-07-01

Passive dielectric materials have been used to improve aspects of MRI by affecting the distribution of radiofrequency electromagnetic fields. Recently, interest in such materials has increased with the number of high-field MRI sites. Here, we introduce a new material composed of sintered high-permittivity ceramic beads in deuterated water. This arrangement maintains the ability to create flexible pads for conforming to individual subjects. The properties of the material are measured and the performance of the material is compared to previously used materials in both simulation and experiment at 3 T. Results show that both permittivity of the beads and effect on signal-to-noise ratio and required transmit power in MRI are greater than those of materials consisting of ceramic powder in water. Importantly, use of beads results in both higher permittivity and lower conductivity than use of powder. Copyright © 2012 Wiley Periodicals, Inc.
Magnetorotational dynamo chimeras. The missing link to turbulent accretion disk dynamo models?

NASA Astrophysics Data System (ADS)

Riols, A.; Rincon, F.; Cossu, C.; Lesur, G.; Ogilvie, G. I.; Longaretti, P.-Y.

2017-02-01

In Keplerian accretion disks, turbulence and magnetic fields may be jointly excited through a subcritical dynamo mechanisminvolving magnetorotational instability (MRI). This dynamo may notably contribute to explaining the time-variability of various accreting systems, as high-resolution simulations of MRI dynamo turbulence exhibit statistical self-organization into large-scale cyclic dynamics. However, understanding the physics underlying these statistical states and assessing their exact astrophysical relevance is theoretically challenging. The study of simple periodic nonlinear MRI dynamo solutions has recently proven useful in this respect, and has highlighted the role of turbulent magnetic diffusion in the seeming impossibility of a dynamo at low magnetic Prandtl number (Pm), a common regime in disks. Arguably though, these simple laminar structures may not be fully representative of the complex, statistically self-organized states expected in astrophysical regimes. Here, we aim at closing this seeming discrepancy by reporting the numerical discovery of exactly periodic, yet semi-statistical "chimeral MRI dynamo states" which are the organized outcome of a succession of MRI-unstable, non-axisymmetric dynamical stages of different forms and amplitudes. Interestingly, these states, while reminiscent of the statistical complexity of turbulent simulations, involve the same physical principles as simpler laminar cycles, and their analysis further confirms the theory that subcritical turbulent magnetic diffusion impedes the sustainment of an MRI dynamo at low Pm. Overall, chimera dynamo cycles therefore offer an unprecedented dual physical and statistical perspective on dynamos in rotating shear flows, which may prove useful in devising more accurate, yet intuitive mean-field models of time-dependent turbulent disk dynamos. Movies associated to Fig. 1 are available at http://www.aanda.org
Lung dynamic MRI deblurring using low-rank decomposition and dictionary learning.

PubMed

Gou, Shuiping; Wang, Yueyue; Wu, Jiaolong; Lee, Percy; Sheng, Ke

2015-04-01

Lung dynamic MRI (dMRI) has emerged to be an appealing tool to quantify lung motion for both planning and treatment guidance purposes. However, this modality can result in blurry images due to intrinsically low signal-to-noise ratio in the lung and spatial/temporal interpolation. The image blurring could adversely affect the image processing that depends on the availability of fine landmarks. The purpose of this study is to reduce dMRI blurring using image postprocessing. To enhance the image quality and exploit the spatiotemporal continuity of dMRI sequences, a low-rank decomposition and dictionary learning (LDDL) method was employed to deblur lung dMRI and enhance the conspicuity of lung blood vessels. Fifty frames of continuous 2D coronal dMRI frames using a steady state free precession sequence were obtained from five subjects including two healthy volunteer and three lung cancer patients. In LDDL, the lung dMRI was decomposed into sparse and low-rank components. Dictionary learning was employed to estimate the blurring kernel based on the whole image, low-rank or sparse component of the first image in the lung MRI sequence. Deblurring was performed on the whole image sequences using deconvolution based on the estimated blur kernel. The deblurring results were quantified using an automated blood vessel extraction method based on the classification of Hessian matrix filtered images. Accuracy of automated extraction was calculated using manual segmentation of the blood vessels as the ground truth. In the pilot study, LDDL based on the blurring kernel estimated from the sparse component led to performance superior to the other ways of kernel estimation. LDDL consistently improved image contrast and fine feature conspicuity of the original MRI without introducing artifacts. The accuracy of automated blood vessel extraction was on average increased by 16% using manual segmentation as the ground truth. Image blurring in dMRI images can be effectively reduced using a low-rank decomposition and dictionary learning method using kernels estimated by the sparse component.
Functional Nanoparticles for Magnetic Resonance Imaging

PubMed Central

Mao, Xinpei; Xu, Jiadi; Cui, Honggang

2016-01-01

Nanoparticle-based magnetic resonance imaging (MRI) contrast agents have received much attention over the past decade. By virtue of a high payload of magnetic moieties, enhanced accumulation at disease sites, and a large surface area for additional modification with targeting ligands, nanoparticle-based contrast agents offer promising new platforms to further enhance the high resolution and sensitivity of MRI for various biomedical applications. T2* superparamagnetic iron oxide nanoparticles (SPIONs) first demonstrated superior improvement on MRI sensitivity. The prevailing SPION attracted growing interest in the development of refined nanoscale versions of MRI contrast agents. Afterwards, T1-based contrast agents were developed, and became the most studied subject in MRI due to the positive contrast they provide that avoids the susceptibility associated with MRI signal reduction. Recently, chemical exchange saturation transfer (CEST) contrast agents have emerged and rapidly gained popularity. The unique aspect of CEST contrast agents is that their contrast can be selectively turned “on” and “off” by radiofrequency (RF) saturation. Their performance can be further enhanced by incorporating a large number of exchangeable protons into well-defined nanostructure. Besides activatable CEST contrast agents, there is growing interest in developing nanoparticle-based activatable MRI contrast agents responsive to stimuli (pH, enzyme, etc.), which improves sensitivity and specificity. In this review, we summarize the recent development of various types of nanoparticle-based MRI contrast agents, and have focused our discussions on the key advantages of introducing nanoparticles in MRI. PMID:27040463
INVESTIGATING DIFFERENCES IN BRAIN FUNCTIONAL NETWORKS USING HIERARCHICAL COVARIATE-ADJUSTED INDEPENDENT COMPONENT ANALYSIS.

PubMed

Shi, Ran; Guo, Ying

2016-12-01

Human brains perform tasks via complex functional networks consisting of separated brain regions. A popular approach to characterize brain functional networks in fMRI studies is independent component analysis (ICA), which is a powerful method to reconstruct latent source signals from their linear mixtures. In many fMRI studies, an important goal is to investigate how brain functional networks change according to specific clinical and demographic variabilities. Existing ICA methods, however, cannot directly incorporate covariate effects in ICA decomposition. Heuristic post-ICA analysis to address this need can be inaccurate and inefficient. In this paper, we propose a hierarchical covariate-adjusted ICA (hc-ICA) model that provides a formal statistical framework for estimating covariate effects and testing differences between brain functional networks. Our method provides a more reliable and powerful statistical tool for evaluating group differences in brain functional networks while appropriately controlling for potential confounding factors. We present an analytically tractable EM algorithm to obtain maximum likelihood estimates of our model. We also develop a subspace-based approximate EM that runs significantly faster while retaining high accuracy. To test the differences in functional networks, we introduce a voxel-wise approximate inference procedure which eliminates the need of computationally expensive covariance matrix estimation and inversion. We demonstrate the advantages of our methods over the existing method via simulation studies. We apply our method to an fMRI study to investigate differences in brain functional networks associated with post-traumatic stress disorder (PTSD).
TU-F-CAMPUS-J-05: Fast Volumetric MRI On An MRI-Linac Enables On-Line QA On Dose Deposition in the Patient

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crijns, S; Glitzner, M; Kontaxis, C

Purpose: The introduction of the MRI-linac in radiotherapy brings MRI-guided treatment with daily plan adaptions within reach. This paradigm demands on-line QA. With its ability to perform continuous volumetric imaging in an outstanding soft-tissue contrast, the MRI- linac promises to elucidate the dose deposition process during a treatment session. Here we study for a prostate case how dynamic MRI combined with linac machine parameters and a fast dose-engine can be used for on-line dose accumulation. Methods: Prostate imaging was performed in healthy volunteer on a 1.5T MR-scanner (Philips, Best, NL) according to a clinical MR-sim protocol, followed by 10min ofmore » dynamic imaging (FLASH, 4s/volume, FOV 40×40×12cm{sup 3}, voxels 3×3×3mm{sup 3}, TR/TE/α=3.5ms/1.7ms/5°). An experienced radiation oncologist made delineations, considering the prostate CTV. Planning was performed on a two-compartment pseudoCT (air/water density) according to clinical constraints (77Gy in PTV) using a Monte-Carlo (MC) based TPS that accounts for magnetic fields. Delivery of one fraction (2.2Gy) was simulated on an emulator for the Axesse linac (Elekta, Stockholm, SE). Machine parameters (MLC settings, gantry angle, dose rate, etc.) were recorded at 25Hz. These were re-grouped per dynamic volume and fed into the MC-engine to calculate a dose delivered for each of the dynamics. Deformations derived from non-rigid registration of each dynamic against the first allowed dose accumulation on a common reference grid. Results: The DVH parameters on the PTV compared to the optimized plan showed little changes. Local deformations however resulted in local deviations, primarily around the air/rectum interface. This clearly indicates the potential of intra-fraction adaptations based on the accumulated dose. Application in each fraction helps to track the influence of plan adaptations to the eventual dose distribution. Calculation times were about twice the delivery time. Conclusion: The current Result paves the way to perform on-line treatment delivery QA on the MRI-linac in the near future.« less
Improvements in RF Shimming in High Field MRI Using High Permittivity Materials With Low Order Pre-Fractal Geometries.

PubMed

Schmidt, Rita; Webb, Andrew

2016-08-01

Ultra-high field MRI is an area of great interest for clinical research and basic science due to the increased signal-to-noise, spatial resolution and magnetic-susceptibility-based contrast. However, the fact that the electromagnetic wavelength in tissue is comparable to the relevant body dimensions means that the uniformity of the excitation field is much poorer than at lower field strengths. In addition to techniques such as transmit arrays, one simple but effective method to counteract this effect is to use high permittivity "pads". Very high permittivities enable thinner, flexible pads to be used, but the limiting factor is wavelength effects within the pads themselves, which can lead to image artifacts. So far, all studies have used simple continuous rectangular/circular pad geometries. In this work we investigate how the wavelength effects can be partially mitigated utilizing shaped pad with holes. Several arrangements have been simulated, including low order pre-fractal geometries, which maintain the overall coverage of the pad, but can provide better image homogeneity in the region of interest or higher sensitivity depending on the setup. Experimental data in the form of in vivo human images at 7T were acquired to validate the simulation results.
In Vivo Noninvasive Analysis of Human Forearm Muscle Function and Fatigue: Applications to EVA Operations and Training Maneuvers

NASA Technical Reports Server (NTRS)

Fotedar, L. K.; Marshburn, T.; Quast, M. J.; Feeback, D. L.

1999-01-01

Forearm muscle fatigue is one of the major limiting factors affecting endurance during performance of deep-space extravehicular activity (EVA) by crew members. Magnetic resonance (MR) provides in vivo noninvasive analysis of tissue level metabolism and fluid exchange dynamics in exercised forearm muscles through the monitoring of proton magnetic resonance imaging (MRI) and phosphorus magnetic resonance spectroscopy (P-31-MRS) parameter variations. Using a space glove box and EVA simulation protocols, we conducted a preliminary MRS/MRI study in a small group of human test subjects during submaximal exercise and recovery and following exhaustive exercise. In assessing simulated EVA-related muscle fatigue and function, this pilot study revealed substantial changes in the MR image longitudinal relaxation times (T2) as an indicator of specific muscle activation and proton flux as well as changes in spectral phosphocreatine-to-phosphate (PCr/Pi) levels as a function of tissue bioenergetic potential.
Anthropomorphic thorax phantom for cardio-respiratory motion simulation in tomographic imaging

NASA Astrophysics Data System (ADS)

Bolwin, Konstantin; Czekalla, Björn; Frohwein, Lynn J.; Büther, Florian; Schäfers, Klaus P.

2018-02-01

Patient motion during medical imaging using techniques such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), or single emission computed tomography (SPECT) is well known to degrade images, leading to blurring effects or severe artifacts. Motion correction methods try to overcome these degrading effects. However, they need to be validated under realistic conditions. In this work, a sophisticated anthropomorphic thorax phantom is presented that combines several aspects of a simulator for cardio-respiratory motion. The phantom allows us to simulate various types of cardio-respiratory motions inside a human-like thorax, including features such as inflatable lungs, beating left ventricular myocardium, respiration-induced motion of the left ventricle, moving lung lesions, and moving coronary artery plaques. The phantom is constructed to be MR-compatible. This means that we can not only perform studies in PET, SPECT and CT, but also inside an MRI system. The technical features of the anthropomorphic thorax phantom Wilhelm are presented with regard to simulating motion effects in hybrid emission tomography and radiotherapy. This is supplemented by a study on the detectability of small coronary plaque lesions in PET/CT under the influence of cardio-respiratory motion, and a study on the accuracy of left ventricular blood volumes.
Focal dose escalation for prostate cancer using 68Ga-HBED-CC PSMA PET/CT and MRI: a planning study based on histology reference.

PubMed

Zamboglou, Constantinos; Thomann, Benedikt; Koubar, Khodor; Bronsert, Peter; Krauss, Tobias; Rischke, Hans C; Sachpazidis, Ilias; Drendel, Vanessa; Salman, Nasr; Reichel, Kathrin; Jilg, Cordula A; Werner, Martin; Meyer, Philipp T; Bock, Michael; Baltas, Dimos; Grosu, Anca L

2018-05-02

Focal radiation therapy has gained of interest in treatment of patients with primary prostate cancer (PCa). The question of how to define the intraprostatic boost volume is still open. Previous studies showed that multiparametric MRI (mpMRI) or PSMA PET alone could be used for boost volume definition. However, other studies proposed that the combined usage of both has the highest sensitivity in detection of intraprostatic lesions. The aim of this study was to demonstrate the feasibility and to evaluate the tumour control probability (TCP) and normal tissue complication probability (NTCP) of radiation therapy dose painting using 68 Ga-HBED-CC PSMA PET/CT, mpMRI or the combination of both in primary PCa. Ten patients underwent PSMA PET/CT and mpMRI followed by prostatectomy. Three gross tumour volumes (GTVs) were created based on PET (GTV-PET), mpMRI (GTV-MRI) and the union of both (GTV-union). Two plans were generated for each GTV. Plan95 consisted of whole-prostate IMRT to 77 Gy in 35 fractions and a simultaneous boost to 95 Gy (Plan95 PET /Plan95 MRI /Plan95 union ). Plan80 consisted of whole-prostate IMRT to 76 Gy in 38 fractions and a simultaneous boost to 80 Gy (Plan80 PET /Plan80 MRI /Plan80 union ). TCPs were calculated for GTV-histo (TCP-histo), which was delineated based on PCa distribution in co-registered histology slices. NTCPs were assessed for bladder and rectum. Dose constraints of published protocols were reached in every treatment plan. Mean TCP-histo were 99.7% (range: 97%-100%) and 75.5% (range: 33%-95%) for Plan95 union and Plan80 union , respectively. Plan95 union had significantly higher TCP-histo values than Plan95 MRI (p = 0.008) and Plan95 PET (p = 0.008). Plan80 union had significantly higher TCP-histo values than Plan80 MRI (p = 0.012), but not than Plan80 PET (p = 0.472). Plan95 MRI had significantly lower NTCP-rectum than Plan95 union (p = 0.012). No significant differences in NTCP-rectum and NTCP-bladder were observed for all other plans (p > 0.05). IMRT dose escalation on GTVs based on mpMRI, PSMA PET/CT and the combination of both was feasible. Boosting GTV-union resulted in significantly higher TCP-histo with no or minimal increase of NTCPs compared to the other plans.
Sparsity-promoting orthogonal dictionary updating for image reconstruction from highly undersampled magnetic resonance data.

PubMed

Huang, Jinhong; Guo, Li; Feng, Qianjin; Chen, Wufan; Feng, Yanqiu

2015-07-21

Image reconstruction from undersampled k-space data accelerates magnetic resonance imaging (MRI) by exploiting image sparseness in certain transform domains. Employing image patch representation over a learned dictionary has the advantage of being adaptive to local image structures and thus can better sparsify images than using fixed transforms (e.g. wavelets and total variations). Dictionary learning methods have recently been introduced to MRI reconstruction, and these methods demonstrate significantly reduced reconstruction errors compared to sparse MRI reconstruction using fixed transforms. However, the synthesis sparse coding problem in dictionary learning is NP-hard and computationally expensive. In this paper, we present a novel sparsity-promoting orthogonal dictionary updating method for efficient image reconstruction from highly undersampled MRI data. The orthogonality imposed on the learned dictionary enables the minimization problem in the reconstruction to be solved by an efficient optimization algorithm which alternately updates representation coefficients, orthogonal dictionary, and missing k-space data. Moreover, both sparsity level and sparse representation contribution using updated dictionaries gradually increase during iterations to recover more details, assuming the progressively improved quality of the dictionary. Simulation and real data experimental results both demonstrate that the proposed method is approximately 10 to 100 times faster than the K-SVD-based dictionary learning MRI method and simultaneously improves reconstruction accuracy.

Simultaneous acquisition sequence for improved hepatic pharmacokinetics quantification accuracy (SAHA) for dynamic contrast-enhanced MRI of liver.

PubMed

Ning, Jia; Sun, Yongliang; Xie, Sheng; Zhang, Bida; Huang, Feng; Koken, Peter; Smink, Jouke; Yuan, Chun; Chen, Huijun

2018-05-01

To propose a simultaneous acquisition sequence for improved hepatic pharmacokinetics quantification accuracy (SAHA) method for liver dynamic contrast-enhanced MRI. The proposed SAHA simultaneously acquired high temporal-resolution 2D images for vascular input function extraction using Cartesian sampling and 3D large-coverage high spatial-resolution liver dynamic contrast-enhanced images using golden angle stack-of-stars acquisition in an interleaved way. Simulations were conducted to investigate the accuracy of SAHA in pharmacokinetic analysis. A healthy volunteer and three patients with cirrhosis or hepatocellular carcinoma were included in the study to investigate the feasibility of SAHA in vivo. Simulation studies showed that SAHA can provide closer results to the true values and lower root mean square error of estimated pharmacokinetic parameters in all of the tested scenarios. The in vivo scans of subjects provided fair image quality of both 2D images for arterial input function and portal venous input function and 3D whole liver images. The in vivo fitting results showed that the perfusion parameters of healthy liver were significantly different from those of cirrhotic liver and HCC. The proposed SAHA can provide improved accuracy in pharmacokinetic modeling and is feasible in human liver dynamic contrast-enhanced MRI, suggesting that SAHA is a potential tool for liver dynamic contrast-enhanced MRI. Magn Reson Med 79:2629-2641, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
Technical Note: Independent component analysis for quality assurance in functional MRI.

PubMed

Astrakas, Loukas G; Kallistis, Nikolaos S; Kalef-Ezra, John A

2016-02-01

Independent component analysis (ICA) is an established method of analyzing human functional MRI (fMRI) data. Here, an ICA-based fMRI quality control (QC) tool was developed and used. ICA-based fMRI QC tool to be used with a commercial phantom was developed. In an attempt to assess the performance of the tool relative to preexisting alternative tools, it was used seven weeks before and eight weeks after repair of a faulty gradient amplifier of a non-state-of-the-art MRI unit. More specifically, its performance was compared with the AAPM 100 acceptance testing and quality assurance protocol and two fMRI QC protocols, proposed by Freidman et al. ["Report on a multicenter fMRI quality assurance protocol," J. Magn. Reson. Imaging 23, 827-839 (2006)] and Stocker et al. ["Automated quality assurance routines for fMRI data applied to a multicenter study," Hum. Brain Mapp. 25, 237-246 (2005)], respectively. The easily developed and applied ICA-based QC protocol provided fMRI QC indices and maps equally sensitive to fMRI instabilities with the indices and maps of other established protocols. The ICA fMRI QC indices were highly correlated with indices of other fMRI QC protocols and in some cases theoretically related to them. Three or four independent components with slow varying time series are detected under normal conditions. ICA applied on phantom measurements is an easy and efficient tool for fMRI QC. Additionally, it can protect against misinterpretations of artifact components as human brain activations. Evaluating fMRI QC indices in the central region of a phantom is not always the optimal choice.
Voxelwise multivariate analysis of multimodality magnetic resonance imaging

PubMed Central

Naylor, Melissa G.; Cardenas, Valerie A.; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin

2015-01-01

Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remains a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. PMID:23408378
Reproducibility of MR-Based Liver Fat Quantification Across Field Strength: Same-Day Comparison Between 1.5T and 3T in Obese Subjects

PubMed Central

Artz, Nathan S.; Haufe, William M.; Hooker, Catherine A.; Hamilton, Gavin; Wolfson, Tanya; Campos, Guilherme M.; Gamst, Anthony C.; Schwimmer, Jeffrey B.; Sirlin, Claude B.; Reeder, Scott B.

2016-01-01

Purpose To examine the reproducibility of quantitative magnetic resonance (MR) methods to estimate hepatic proton density fat-fraction (PDFF) at different magnetic field strengths. Materials and Methods This Health Insurance Portability and Accountability Act (HIPAA)-compliant study was approved by the Institutional Review Board. Following informed consent, 25 severely obese subjects (mean body mass index [BMI]: 45 ± 4, range: 38–53 kg/m2) were scanned at 1.5T and 3T on the same day. Two confounder-corrected multiecho chemical shift-encoded gradient-echo-based imaging methods were acquired to estimate PDFF over the entire liver: 3D complex-based (MRI-C) and 2D magnitude-based (MRI-M) MRI. Single-voxel MR spectroscopy (MRS) was performed in the right liver lobe. Using linear regression, pairwise comparisons of estimated PDFF were made between methods (MRI-C, MRI-M, MRS) at each field strength and for each method across field strengths. Results 1.5T vs. 3T regression analyses for MRI-C, MRI-M, and MRS PDFF measurements yielded R2 values of 0.99, 0.97, and 0.90, respectively. The best-fit line was near unity (slope(m) = 1, intercept(b) = 0), indicating excellent agreement for each case: MRI-C (m = 0.92 [0.87, 0.99], b = 1.4 [0.7, 1.8]); MRI-M (m = 1.0 [0.90, 1.08], b = −1.4 [−2.4, −0.5]); MRS (m = 0.98 [0.82, 1.15], b = 1.2 [−0.2, 3.0]). Comparing MRI-C and MRI-M yielded an R2 = 0.98 (m = 1.1 [1.02, 1.16], b = −1.8 [−2.8, −1.1]) at 1.5T, and R2 = 0.99 (m = 0.98 [0.93, 1.03], b = 1.2 [0.7, 1.7]) at 3T. Conclusion This study demonstrates that PDFF estimation is reproducible across field strengths and across two confounder-corrected MR-based methods. PMID:25620624
Reproducibility of MR-based liver fat quantification across field strength: Same-day comparison between 1.5T and 3T in obese subjects.

PubMed

Artz, Nathan S; Haufe, William M; Hooker, Catherine A; Hamilton, Gavin; Wolfson, Tanya; Campos, Guilherme M; Gamst, Anthony C; Schwimmer, Jeffrey B; Sirlin, Claude B; Reeder, Scott B

2015-09-01

To examine the reproducibility of quantitative magnetic resonance (MR) methods to estimate hepatic proton density fat-fraction (PDFF) at different magnetic field strengths. This Health Insurance Portability and Accountability Act (HIPAA)-compliant study was approved by the Institutional Review Board. Following informed consent, 25 severely obese subjects (mean body mass index [BMI]: 45 ± 4, range: 38-53 kg/m(2) ) were scanned at 1.5T and 3T on the same day. Two confounder-corrected multiecho chemical shift-encoded gradient-echo-based imaging methods were acquired to estimate PDFF over the entire liver: 3D complex-based (MRI-C) and 2D magnitude-based (MRI-M) MRI. Single-voxel MR spectroscopy (MRS) was performed in the right liver lobe. Using linear regression, pairwise comparisons of estimated PDFF were made between methods (MRI-C, MRI-M, MRS) at each field strength and for each method across field strengths. 1.5T vs. 3T regression analyses for MRI-C, MRI-M, and MRS PDFF measurements yielded R(2) values of 0.99, 0.97, and 0.90, respectively. The best-fit line was near unity (slope(m) = 1, intercept(b) = 0), indicating excellent agreement for each case: MRI-C (m = 0.92 [0.87, 0.99], b = 1.4 [0.7, 1.8]); MRI-M (m = 1.0 [0.90, 1.08], b = -1.4 [-2.4, -0.5]); MRS (m = 0.98 [0.82, 1.15], b = 1.2 [-0.2, 3.0]). Comparing MRI-C and MRI-M yielded an R(2) = 0.98 (m = 1.1 [1.02, 1.16], b = -1.8 [-2.8, -1.1]) at 1.5T, and R(2) = 0.99 (m = 0.98 [0.93, 1.03], b = 1.2 [0.7, 1.7]) at 3T. This study demonstrates that PDFF estimation is reproducible across field strengths and across two confounder-corrected MR-based methods. © 2015 Wiley Periodicals, Inc.
Clinical implications of magnetic resonance imaging in temporomandibular disorders patients presenting ear fullness.

PubMed

Lee, Sang Yeon; Park, Ji Woon; Park, Seo Eun; Nam, Dong Woo; Lim, Hyun Jung; Kim, Young Ho

2017-12-14

The aim of this study was to investigate whether findings detected by temporomandibular joint magnetic resonance imaging (TMJ-MRI) can provide pathognomonic evidence of temporomandibular disorders (TMD) in patients with nonspecific ear fullness (EF). The association of nonspecific EF with clinical characteristics of TMD based on TMJ-MRI findings was examined. Retrospective analysis. Thirty-four subjects (42 ears) who had no detectable otologic problems as a cause of EF were enrolled in this study. Each subject underwent TMJ-MRI to identify pathology of the TMJ as a possible cause of nonspecific EF. All subjects participated in the re-evaluation process following TMD treatment. Anatomical abnormalities in TMJ-MRI, irrespective of TMD signs, were observed in 34 of the 42 ears (80.9%), such as degenerative change of the TMJ (16 ears), articular disc displacement (11 ears), and joint effusion (seven ears). Specific abnormalities of the TMJ were associated with nonspecific EF, and this symptom showed improvement following individualized TMD treatment in those with internal derangement and/or effusion of the TMJ. However, abnormal TMJ-MRI findings were also observed in seven of nine ears with no TMD signs, and there was no significant association between the presence of TMD signs and abnormal TMJ-MRI findings (χ 2 = 0.075, P = .784). Patients presenting with nonspecific EF may have TMD, which can be effectively diagnosed using TMJ-MRI. The present study revealed the causal relationship between nonspecific EF and abnormal TMJ findings based on MRI. Individualized TMD treatments based on TMJ-MRI led to improved treatment outcomes with special regard to nonspecific EF LEVEL OF EVIDENCE: 4 Laryngoscope, 2017. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.
First Application of 7-T Magnetic Resonance Imaging in Endoscopic Endonasal Surgery of Skull Base Tumors.

PubMed

Barrett, Thomas F; Dyvorne, Hadrien A; Padormo, Francesco; Pawha, Puneet S; Delman, Bradley N; Shrivastava, Raj K; Balchandani, Priti

2017-07-01

Successful endoscopic endonasal surgery for the resection of skull base tumors is reliant on preoperative imaging to delineate pathology from the surrounding anatomy. The increased signal-to-noise ratio afforded by 7-T MRI can be used to increase spatial and contrast resolution, which may lend itself to improved imaging of the skull base. In this study, we apply a 7-T imaging protocol to patients with skull base tumors and compare the images with clinical standard of care. Images were acquired at 7 T on 11 patients with skull base lesions. Two neuroradiologists evaluated clinical 1.5-, 3-, and 7-T scans for detection of intracavernous cranial nerves and internal carotid artery (ICA) branches. Detection rates were compared. Images were used for surgical planning and uploaded to a neuronavigation platform and used to guide surgery. Image analysis yielded improved detection rates of cranial nerves and ICA branches at 7 T. The 7-T images were successfully incorporated into preoperative planning and intraoperative neuronavigation. Our study represents the first application of 7-T MRI to the full neurosurgical workflow for endoscopic endonasal surgery. We detected higher rates of cranial nerves and ICA branches at 7-T MRI compared with 3- and 1.5-T MRI, and found that integration of 7 T into surgical planning and guidance was feasible. These results suggest a potential for 7-T MRI to reduce surgical complications. Future studies comparing standardized 7-, 3-, and 1.5-T MRI protocols in a larger number of patients are warranted to determine the relative benefit of 7-T MRI for endonasal endoscopic surgical efficacy. Copyright © 2017 Elsevier Inc. All rights reserved.
The mental simulation of state/psychological verbs in the adolescent brain: An fMRI study.

PubMed

Tomasino, Barbara; Nobile, Maria; Re, Marta; Bellina, Monica; Garzitto, Marco; Arrigoni, Filippo; Molteni, Massimo; Fabbro, Franco; Brambilla, Paolo

2018-06-01

This fMRI study investigated mental simulation of state/psychological and action verbs during adolescence. Sixteen healthy subjects silently read verbs describing a motor scene or not (STIMULUS: motor, state/psychological verbs) and they were explicitly asked to imagine the situation or they performed letter detection preventing them from using simulation (TASK: imagery vs. letter detection). A significant task by stimuli interaction showed that imagery of state/psychological verbs, as compared to action stimuli (controlled by the letter detection) selectively increased activation in the right supramarginal gyrus/rolandic operculum and in the right insula, and decreased activation in the right intraparietal sulcus. We compared these data to those from a group of older participants (Tomasino et al. 2014a). Activation in the left supramarginal gyrus decreased for the latter group (as compared to the present group) for imagery of state/psychological verbs. By contrast, activation in the right superior frontal gyrus decreased for the former group (as compared to the older group) for imagery of state/psychological verbs. Copyright © 2018 Elsevier Inc. All rights reserved.
Phase-Contrast MRI and CFD Modeling of Apparent 3He Gas Flow in Rat Pulmonary Airways

PubMed Central

Minard, Kevin R.; Kuprat, Andrew P.; Kabilan, Senthil; Jacob, Richard E.; Einstein, Daniel R.; Carson, James P.; Corley, Richard A.

2012-01-01

Phase-contrast (PC) magnetic resonance imaging (MRI) with hyperpolarized 3He is potentially useful for developing and testing patient-specific models of pulmonary airflow. One challenge, however, is that PC-MRI provides apparent values of local 3He velocity that not only depend on actual airflow but also on gas diffusion. This not only blurs laminar flow patterns in narrow airways but also introduces anomalous airflow structure that reflects gas-wall interactions. Here, both effects are predicted in a live rat using computational fluid dynamics (CFD), and for the first time, simulated patterns of apparent 3He gas velocity are compared with in-vivo PC-MRI. Results show 1) that correlations (R2) between measured and simulated airflow patterns increase from 0.23 to 0.79 simply by accounting for apparent 3He transport, and 2) that remaining differences are mainly due to uncertain airway segmentation and partial volume effects stemming from relatively coarse MRI resolution. Higher-fidelity testing of pulmonary airflow predictions should therefore be possible with future imaging improvements. PMID:22771528
Phase-contrast MRI and CFD modeling of apparent 3He gas flow in rat pulmonary airways

NASA Astrophysics Data System (ADS)

Minard, Kevin R.; Kuprat, Andrew P.; Kabilan, Senthil; Jacob, Richard E.; Einstein, Daniel R.; Carson, James P.; Corley, Richard A.

2012-08-01

Phase-contrast (PC) magnetic resonance imaging (MRI) with hyperpolarized 3He is potentially useful for developing and testing patient-specific models of pulmonary airflow. One challenge, however, is that PC-MRI provides apparent values of local 3He velocity that not only depend on actual airflow but also on gas diffusion. This not only blurs laminar flow patterns in narrow airways but also introduces anomalous airflow structure that reflects gas-wall interactions. Here, both effects are predicted in a live rat using computational fluid dynamics (CFD), and for the first time, simulated patterns of apparent 3He gas velocity are compared with in vivo PC-MRI. Results show (1) that correlations (R2) between measured and simulated airflow patterns increase from 0.23 to 0.79 simply by accounting for apparent 3He transport, and (2) that remaining differences are mainly due to uncertain airway segmentation and partial volume effects stemming from relatively coarse MRI resolution. Higher-fidelity testing of pulmonary airflow predictions should therefore be possible with future imaging improvements.
Design analysis of an MPI human functional brain scanner

PubMed Central

Mason, Erica E.; Cooley, Clarissa Z.; Cauley, Stephen F.; Griswold, Mark A.; Conolly, Steven M.; Wald, Lawrence L.

2017-01-01

MPI’s high sensitivity makes it a promising modality for imaging brain function. Functional contrast is proposed based on blood SPION concentration changes due to Cerebral Blood Volume (CBV) increases during activation, a mechanism utilized in fMRI studies. MPI offers the potential for a direct and more sensitive measure of SPION concentration, and thus CBV, than fMRI. As such, fMPI could surpass fMRI in sensitivity, enhancing the scientific and clinical value of functional imaging. As human-sized MPI systems have not been attempted, we assess the technical challenges of scaling MPI from rodent to human brain. We use a full-system MPI simulator to test arbitrary hardware designs and encoding practices, and we examine tradeoffs imposed by constraints that arise when scaling to human size as well as safety constraints (PNS and central nervous system stimulation) not considered in animal scanners, thereby estimating spatial resolutions and sensitivities achievable with current technology. Using a projection FFL MPI system, we examine coil hardware options and their implications for sensitivity and spatial resolution. We estimate that an fMPI brain scanner is feasible, although with reduced sensitivity (20×) and spatial resolution (5×) compared to existing rodent systems. Nonetheless, it retains sufficient sensitivity and spatial resolution to make it an attractive future instrument for studying the human brain; additional technical innovations can result in further improvements. PMID:28752130
Mapping cardiac fiber orientations from high-resolution DTI to high-frequency 3D ultrasound

NASA Astrophysics Data System (ADS)

Qin, Xulei; Wang, Silun; Shen, Ming; Zhang, Xiaodong; Wagner, Mary B.; Fei, Baowei

2014-03-01

The orientation of cardiac fibers affects the anatomical, mechanical, and electrophysiological properties of the heart. Although echocardiography is the most common imaging modality in clinical cardiac examination, it can only provide the cardiac geometry or motion information without cardiac fiber orientations. If the patient's cardiac fiber orientations can be mapped to his/her echocardiography images in clinical examinations, it may provide quantitative measures for diagnosis, personalized modeling, and image-guided cardiac therapies. Therefore, this project addresses the feasibility of mapping personalized cardiac fiber orientations to three-dimensional (3D) ultrasound image volumes. First, the geometry of the heart extracted from the MRI is translated to 3D ultrasound by rigid and deformable registration. Deformation fields between both geometries from MRI and ultrasound are obtained after registration. Three different deformable registration methods were utilized for the MRI-ultrasound registration. Finally, the cardiac fiber orientations imaged by DTI are mapped to ultrasound volumes based on the extracted deformation fields. Moreover, this study also demonstrated the ability to simulate electricity activations during the cardiac resynchronization therapy (CRT) process. The proposed method has been validated in two rat hearts and three canine hearts. After MRI/ultrasound image registration, the Dice similarity scores were more than 90% and the corresponding target errors were less than 0.25 mm. This proposed approach can provide cardiac fiber orientations to ultrasound images and can have a variety of potential applications in cardiac imaging.
Improved Parameter-Estimation With MRI-Constrained PET Kinetic Modeling: A Simulation Study

NASA Astrophysics Data System (ADS)

Erlandsson, Kjell; Liljeroth, Maria; Atkinson, David; Arridge, Simon; Ourselin, Sebastien; Hutton, Brian F.

2016-10-01

Kinetic analysis can be applied both to dynamic PET and dynamic contrast enhanced (DCE) MRI data. We have investigated the potential of MRI-constrained PET kinetic modeling using simulated [ 18F]2-FDG data for skeletal muscle. The volume of distribution, Ve, for the extra-vascular extra-cellular space (EES) is the link between the two models: It can be estimated by DCE-MRI, and then used to reduce the number of parameters to estimate in the PET model. We used a 3 tissue-compartment model with 5 rate constants (3TC5k), in order to distinguish between EES and the intra-cellular space (ICS). Time-activity curves were generated by simulation using the 3TC5k model for 3 different Ve values under basal and insulin stimulated conditions. Noise was added and the data were fitted with the 2TC3k model and with the 3TC5k model with and without Ve constraint. One hundred noise-realisations were generated at 4 different noise-levels. The results showed reductions in bias and variance with Ve constraint in the 3TC5k model. We calculated the parameter k3", representing the combined effect of glucose transport across the cellular membrane and phosphorylation, as an extra outcome measure. For k3", the average coefficient of variation was reduced from 52% to 9.7%, while for k3 in the standard 2TC3k model it was 3.4%. The accuracy of the parameters estimated with our new modeling approach depends on the accuracy of the assumed Ve value. In conclusion, we have shown that, by utilising information that could be obtained from DCE-MRI in the kinetic analysis of [ 18F]2-FDG-PET data, it is in principle possible to obtain better parameter estimates with a more complex model, which may provide additional information as compared to the standard model.
The Brain/MINDS 3D digital marmoset brain atlas

PubMed Central

Woodward, Alexander; Hashikawa, Tsutomu; Maeda, Masahide; Kaneko, Takaaki; Hikishima, Keigo; Iriki, Atsushi; Okano, Hideyuki; Yamaguchi, Yoko

2018-01-01

We present a new 3D digital brain atlas of the non-human primate, common marmoset monkey (Callithrix jacchus), with MRI and coregistered Nissl histology data. To the best of our knowledge this is the first comprehensive digital 3D brain atlas of the common marmoset having normalized multi-modal data, cortical and sub-cortical segmentation, and in a common file format (NIfTI). The atlas can be registered to new data, is useful for connectomics, functional studies, simulation and as a reference. The atlas was based on previously published work but we provide several critical improvements to make this release valuable for researchers. Nissl histology images were processed to remove illumination and shape artifacts and then normalized to the MRI data. Brain region segmentation is provided for both hemispheres. The data is in the NIfTI format making it easy to integrate into neuroscience pipelines, whereas the previous atlas was in an inaccessible file format. We also provide cortical, mid-cortical and white matter boundary segmentations useful for visualization and analysis. PMID:29437168
Magnetic resonance imaging (MRI) and prognostication in neonatal hypoxic-ischemic injury: a vignette-based study of Canadian specialty physicians.

PubMed

Bell, Emily; Rasmussen, Lisa Anne; Mazer, Barbara; Shevell, Michael; Miller, Steven P; Synnes, Anne; Yager, Jerome Y; Majnemer, Annette; Muhajarine, Nazeem; Chouinard, Isabelle; Racine, Eric

2015-02-01

Magnetic resonance imaging (MRI) could improve prognostication in neonatal brain injury; however, factors beyond technical or scientific refinement may impact its use and interpretation. We surveyed Canadian neonatologists and pediatric neurologists using general and vignette-based questions about the use of MRI for prognostication in neonates with hypoxic-ischemic injury. There was inter- and intra-vignette variability in prognosis and in ratings about the usefulness of MRI. Severity of predicted outcome correlated with certainty about the outcome. A majority of physicians endorsed using MRI results in discussing prognosis with families, and most suggested that MRI results contribute to end-of-life decisions. Participating neonatologists, when compared to participating pediatric neurologists, had significantly less confidence in the interpretation of MRI by colleagues in neurology and radiology. Further investigation is needed to understand the complexity of MRI and of its application. Potential gaps relative to our understanding of the ethical importance of these findings should be addressed. © The Author(s) 2014.
Breast MRI: patterns of utilization and impact on patient management in the community hospital setting.

PubMed

Lobrano, Mary Beth; Stolier, Alan; L'Hoste, Robert; Luttrell, Carol Anne

2012-01-01

The objective of our study was to investigate the indications for breast magnetic resonance imaging, or MRI, in our community hospital, determine how many probably benign MRI findings were malignant at follow-up, determine how many cancers were identified by MRI in screening patients, and evaluate the utility of MRI for surgical planning and problem-solving. Five hundred twenty-eight contrast-enhanced MRI's of the breast in 434 patients were retrospectively reviewed. MRI images/reports were compared to surgical pathology reports and the results of follow-up studies. Screening was the most common indication for breast MRI in our patient population. Five percent of findings termed "probably benign" on MRI proved to be malignant at follow-up. Eight malignancies were detected in six of 202 screened patients. Ten malignancies were diagnosed in 66 patients referred to MRI for problem-solving. In two of 74 patients with known breast cancer, an unsuspected ipsilateral cancer was identified on MRI. MRI proved useful in the community hospital setting for screening high-risk patients and problem-solving. The rate of malignancy in probably benign MRI findings was higher than the corresponding rate in mammography. The detection of additional ipsilateral and contralateral cancers in pre-operative patients with known breast cancer was not as high as expected, based on prior studies.
Evaluation of liver function using gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid enhanced magnetic resonance imaging based on a three-dimensional volumetric analysis system.

PubMed

Kudo, Masashi; Gotohda, Naoto; Sugimoto, Motokazu; Kobayashi, Tatsushi; Kojima, Motohiro; Takahashi, Shinichiro; Konishi, Masaru; Hayashi, Ryuichi

2018-06-02

Magnetic resonance imaging with gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (EOB-MRI) is a diagnostic modality for liver tumors. Three-dimensional (3D) volumetric analysis systems using EOB-MRI data are used to simulate liver anatomy for surgery. This study was conducted to investigate clinical utility of a 3D volumetric analysis system on EOB-MRI to evaluate liver function. Between August 2014 and December 2015, 181 patients underwent laboratory and radiological exams as standardized preoperative evaluation for liver surgery. The liver-spleen contrast-enhanced ratio (LSR) was measured by a semi-automated 3D volumetric analysis system on EOB-MRI. First, the inter-evaluator variability of the calculated LSR was evaluated. Additionally, a subset of liver surgical specimens was evaluated histologically by using immunohistochemical staining. Finally, the correlations between the LSR and grading systems of liver function, laboratory data, or histological findings were analyzed. The inter-evaluator correlation coefficient of the measured LSR was 0.986. The mean LSR was significantly correlated with the Child-Pugh score (p = 0.014) and the ALBI score (p < 0.001). Significant correlations were also observed between the LSR and indocyanine green retention rate at 15 min (r = - 0.601, p < 0.001), between the LSR and liver fibrosis stage (r = - 0.556, p < 0.001), and between the LSR and liver steatosis grade (r = - 0.396, p < 0.001). The LSR calculated by a 3D volumetric analysis system on EOB-MRI was highly reproducible and was shown to be correlated with liver function parameters and liver histology. These data suggest that this imaging modality can be a reliable tool to evaluate liver function.
Estimation of Dynamic Sparse Connectivity Patterns From Resting State fMRI.

PubMed

Cai, Biao; Zille, Pascal; Stephen, Julia M; Wilson, Tony W; Calhoun, Vince D; Wang, Yu Ping

2018-05-01

Functional connectivity (FC) estimated from functional magnetic resonance imaging (fMRI) time series, especially during resting state periods, provides a powerful tool to assess human brain functional architecture in health, disease, and developmental states. Recently, the focus of connectivity analysis has shifted toward the subnetworks of the brain, which reveals co-activating patterns over time. Most prior works produced a dense set of high-dimensional vectors, which are hard to interpret. In addition, their estimations to a large extent were based on an implicit assumption of spatial and temporal stationarity throughout the fMRI scanning session. In this paper, we propose an approach called dynamic sparse connectivity patterns (dSCPs), which takes advantage of both matrix factorization and time-varying fMRI time series to improve the estimation power of FC. The feasibility of analyzing dynamic FC with our model is first validated through simulated experiments. Then, we use our framework to measure the difference between young adults and children with real fMRI data set from the Philadelphia Neurodevelopmental Cohort (PNC). The results from the PNC data set showed significant FC differences between young adults and children in four different states. For instance, young adults had reduced connectivity between the default mode network and other subnetworks, as well as hyperconnectivity within the visual system in states 1 and 3, and hypoconnectivity in state 2. Meanwhile, they exhibited temporal correlation patterns that changed over time within functional subnetworks. In addition, the dSCPs model indicated that older people tend to spend more time within a relatively connected FC pattern. Overall, the proposed method provides a valid means to assess dynamic FC, which could facilitate the study of brain networks.
In vivo self-gated 23 Na MRI at 7 T using an oval-shaped body resonator.

PubMed

Platt, Tanja; Umathum, Reiner; Fiedler, Thomas M; Nagel, Armin M; Bitz, Andreas K; Maier, Florian; Bachert, Peter; Ladd, Mark E; Wielpütz, Mark O; Kauczor, Hans-Ulrich; Behl, Nicolas G R

2018-02-09

This work faces three challenges of sodium ( 23 Na) torso MRI on the way to quantitative 23 Na MRI: Development of a 23 Na radiofrequency transmit and receive coil covering a large part of the human body in width and length for 23 Na MRI at 7 T; reduction of blurring due to respiration in free-breathing 23 Na MRI using a self-gating approach; and reduction of image noise using a compressed-sensing reconstruction. An oval-shaped birdcage resonator with a large field of view of (400 mm) 3 and a homogeneous transmit and receive field distribution was designed, simulated, and implemented on a 7T MR system. In free-breathing 3-dimensional radial 23 Na MRI (acquisition time ≈ 30 minutes), retrospective respiratory self-gating was applied, which sorts the acquired projections into two respiratory states based on the intrinsic respiration-dependent signal changes. Furthermore, a 3-dimensional dictionary-learning compressed-sensing reconstruction was applied. The developed body coil provided homogeneous radiofrequency excitation (flip angle error of 4.9% in central region of interest of 23 × 13 × 10 cm 3 ) and homogeneous signal reception. The self-gating approach allowed for separation of the full data set into two subsets associated with different respiratory states (inhaled and exhaled), and thereby reduced blurring due to respiration in the separated images. Image noise was markedly reduced by the compressed-sensing algorithm. The presented body coil enables full body width 23 Na MRI with long z-axis coverage at 7 T for the first time. Additionally, the retrospective respiratory self-gating performance is demonstrated for free-breathing lung and abdominal 23 Na MRI in 3 subjects. © 2018 International Society for Magnetic Resonance in Medicine.
Nonthermal ablation of deep brain targets: A simulation study on a large animal model

PubMed Central

Top, Can Barış; White, P. Jason; McDannold, Nathan J.

2016-01-01

Purpose: Thermal ablation with transcranial MRI-guided focused ultrasound (FUS) is currently limited to central brain targets because of heating and other beam effects caused by the presence of the skull. Recently, it was shown that it is possible to ablate tissues without depositing thermal energy by driving intravenously administered microbubbles to inertial cavitation using low-duty-cycle burst sonications. A recent study demonstrated that this ablation method could ablate tissue volumes near the skull base in nonhuman primates without thermally damaging the nearby bone. However, blood–brain disruption was observed in the prefocal region, and in some cases, this region contained small areas of tissue damage. The objective of this study was to analyze the experimental model with simulations and to interpret the cause of these effects. Methods: The authors simulated prior experiments where nonthermal ablation was performed in the brain in anesthetized rhesus macaques using a 220 kHz clinical prototype transcranial MRI-guided FUS system. Low-duty-cycle sonications were applied at deep brain targets with the ultrasound contrast agent Definity. For simulations, a 3D pseudospectral finite difference time domain tool was used. The effects of shear mode conversion, focal steering, skull aberrations, nonlinear propagation, and the presence of skull base on the pressure field were investigated using acoustic and elastic wave propagation models. Results: The simulation results were in agreement with the experimental findings in the prefocal region. In the postfocal region, however, side lobes were predicted by the simulations, but no effects were evident in the experiments. The main beam was not affected by the different simulated scenarios except for a shift of about 1 mm in peak position due to skull aberrations. However, the authors observed differences in the volume, amplitude, and distribution of the side lobes. In the experiments, a single element passive cavitation detector was used to measure the inertial cavitation threshold and to determine the pressure amplitude to use for ablation. Simulations of the detector’s acoustic field suggest that its maximum sensitivity was in the lower part of the main beam, which may have led to excessive exposure levels in the experiments that may have contributed to damage in the prefocal area. Conclusions: Overall, these results suggest that case-specific full wave simulations before the procedure can be useful to predict the focal and the prefocal side lobes and the extent of the resulting bioeffects produced by nonthermal ablation. Such simulations can also be used to optimally position passive cavitation detectors. The disagreement between the simulations and the experiments in the postfocal region may have been due to shielding of the ultrasound field due to microbubble activity in the focal region. Future efforts should include the effects of microbubble activity and vascularization on the pressure field. PMID:26843248

Reconstruction of human brain spontaneous activity based on frequency-pattern analysis of magnetoencephalography data

PubMed Central

Llinás, Rodolfo R.; Ustinin, Mikhail N.; Rykunov, Stanislav D.; Boyko, Anna I.; Sychev, Vyacheslav V.; Walton, Kerry D.; Rabello, Guilherme M.; Garcia, John

2015-01-01

A new method for the analysis and localization of brain activity has been developed, based on multichannel magnetic field recordings, over minutes, superimposed on the MRI of the individual. Here, a high resolution Fourier Transform is obtained over the entire recording period, leading to a detailed multi-frequency spectrum. Further analysis implements a total decomposition of the frequency components into functionally invariant entities, each having an invariant field pattern localizable in recording space. The method, addressed as functional tomography, makes it possible to find the distribution of magnetic field sources in space. Here, the method is applied to the analysis of simulated data, to oscillating signals activating a physical current dipoles phantom, and to recordings of spontaneous brain activity in 10 healthy adults. In the analysis of simulated data, 61 dipoles are localized with 0.7 mm precision. Concerning the physical phantom the method is able to localize three simultaneously activated current dipoles with 1 mm precision. Spatial resolution 3 mm was attained when localizing spontaneous alpha rhythm activity in 10 healthy adults, where the alpha peak was specified for each subject individually. Co-registration of the functional tomograms with each subject's head MRI localized alpha range activity to the occipital and/or posterior parietal brain region. This is the first application of this new functional tomography to human brain activity. The method successfully provides an overall view of brain electrical activity, a detailed spectral description and, combined with MRI, the localization of sources in anatomical brain space. PMID:26528119
Imaging Electric Properties of Biological Tissues by RF Field Mapping in MRI

PubMed Central

Zhang, Xiaotong; Zhu, Shanan; He, Bin

2010-01-01

The electric properties (EPs) of biological tissue, i.e., the electric conductivity and permittivity, can provide important information in the diagnosis of various diseases. The EPs also play an important role in specific absorption rate (SAR) calculation, a major concern in high-field Magnetic Resonance Imaging (MRI), as well as in non-medical areas such as wireless-telecommunications. The high-field MRI system is accompanied by significant wave propagation effects, and the radio frequency (RF) radiation is dependent on the EPs of biological tissue. Based on the measurement of the active transverse magnetic component of the applied RF field (known as B1-mapping technique), we propose a dual-excitation algorithm, which uses two sets of measured B1 data to noninvasively reconstruct the electric properties of biological tissues. The Finite Element Method (FEM) was utilized in three-dimensional (3D) modeling and B1 field calculation. A series of computer simulations were conducted to evaluate the feasibility and performance of the proposed method on a 3D head model within a transverse electromagnetic (TEM) coil and a birdcage (BC) coil. Using a TEM coil, when noise free, the reconstructed EP distribution of tissues in the brain has relative errors of 12% ∼ 28% and correlated coefficients of greater than 0.91. Compared with other B1-mapping based reconstruction algorithms, our approach provides superior performance without the need for iterative computations. The present simulation results suggest that good reconstruction of electric properties from B1 mapping can be achieved. PMID:20129847
The Virtual Brain: a simulator of primate brain network dynamics.

PubMed

Sanz Leon, Paula; Knock, Stuart A; Woodman, M Marmaduke; Domide, Lia; Mersmann, Jochen; McIntosh, Anthony R; Jirsa, Viktor

2013-01-01

We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications.
The Virtual Brain: a simulator of primate brain network dynamics

PubMed Central

Sanz Leon, Paula; Knock, Stuart A.; Woodman, M. Marmaduke; Domide, Lia; Mersmann, Jochen; McIntosh, Anthony R.; Jirsa, Viktor

2013-01-01

We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications. PMID:23781198
Unwrapping eddy current compensation: improved compensation of eddy current induced baseline shifts in high-resolution phase-contrast MRI at 9.4 Tesla.

PubMed

Espe, Emil K S; Zhang, Lili; Sjaastad, Ivar

2014-10-01

Phase-contrast MRI (PC-MRI) is a versatile tool allowing evaluation of in vivo motion, but is sensitive to eddy current induced phase offsets, causing errors in the measured velocities. In high-resolution PC-MRI, these offsets can be sufficiently large to cause wrapping in the baseline phase, rendering conventional eddy current compensation (ECC) inadequate. The purpose of this study was to develop an improved ECC technique (unwrapping ECC) able to handle baseline phase discontinuities. Baseline phase discontinuities are unwrapped by minimizing the spatiotemporal standard deviation of the static-tissue phase. Computer simulations were used for demonstrating the theoretical foundation of the proposed technique. The presence of baseline wrapping was confirmed in high-resolution myocardial PC-MRI of a normal rat heart at 9.4 Tesla (T), and the performance of unwrapping ECC was compared with conventional ECC. Areas of phase wrapping in static regions were clearly evident in high-resolution PC-MRI. The proposed technique successfully eliminated discontinuities in the baseline, and resulted in significantly better ECC than the conventional approach. We report the occurrence of baseline phase wrapping in PC-MRI, and provide an improved ECC technique capable of handling its presence. Unwrapping ECC offers improved correction of eddy current induced baseline shifts in high-resolution PC-MRI. Copyright © 2013 Wiley Periodicals, Inc.
A PET/CT-Based Strategy Is a Stronger Predictor of Survival Than a Standard Imaging Strategy in Patients with Head and Neck Squamous Cell Carcinoma.

PubMed

Rohde, Max; Nielsen, Anne L; Pareek, Manan; Johansen, Jørgen; Sørensen, Jens A; Diaz, Anabel; Nielsen, Mie K; Christiansen, Janus M; Asmussen, Jon T; Nguyen, Nina; Gerke, Oke; Thomassen, Anders; Alavi, Abass; Høilund-Carlsen, Poul Flemming; Godballe, Christian

2018-04-01

Our purpose was to examine whether staging of head and neck squamous cell carcinoma (HNSCC) by upfront 18 F-FDG PET/CT (i.e., on the day of biopsy and before the biopsy) discriminates survival better than the traditional imaging strategies based on chest x-ray plus head and neck MRI (CXR/MRI) or chest CT plus head and neck MRI (CCT/MRI). Methods: We performed a masked prospective cohort study based on paired data. Consecutive patients with histologically verified primary HNSCC were recruited from Odense University Hospital from September 2013 to March 2016. All patients underwent CXR/MRI, CCT/MRI, and PET/CT on the same day. Tumors were categorized as localized (stages I and II), locally advanced (stages III and IVB), or metastatic (stage IVC). Discriminative ability for each imaging modality with respect to HNSCC staging were compared using Kaplan-Meier analysis, Cox proportional hazards regression with the Harrell C-index, and net reclassification improvement. Results: In total, 307 patients with histologically verified HNSCC were included. Use of PET/CT significantly altered the stratification of tumor stage when compared with either CXR/MRI or CCT/MRI (χ 2 , P < 0.001 for both). Cancer stages based on PET/CT, but not CXR/MRI or CCT/MRI, were associated with significant differences in mortality risk on Kaplan-Meier analyses ( P ≤ 0.002 for all PET/CT-based comparisons). Furthermore, overall discriminative ability was significantly greater for PET/CT (C-index, 0.712) than for CXR/MRI (C-index, 0.675; P = 0.04) or CCT/MRI (C-index, 0.657; P = 0.02). Finally, PET/CT was significantly associated with a positive net reclassification improvement when compared with CXR/MRI (0.184, P = 0.03) but not CCT/MRI (0.094%, P = 0.31). Conclusion: Tumor stages determined by PET/CT were associated with more distinct prognostic properties in terms of survival than those determined by standard imaging strategies. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.
Fast fMRI can detect oscillatory neural activity in humans.

PubMed

Lewis, Laura D; Setsompop, Kawin; Rosen, Bruce R; Polimeni, Jonathan R

2016-10-25

Oscillatory neural dynamics play an important role in the coordination of large-scale brain networks. High-level cognitive processes depend on dynamics evolving over hundreds of milliseconds, so measuring neural activity in this frequency range is important for cognitive neuroscience. However, current noninvasive neuroimaging methods are not able to precisely localize oscillatory neural activity above 0.2 Hz. Electroencephalography and magnetoencephalography have limited spatial resolution, whereas fMRI has limited temporal resolution because it measures vascular responses rather than directly recording neural activity. We hypothesized that the recent development of fast fMRI techniques, combined with the extra sensitivity afforded by ultra-high-field systems, could enable precise localization of neural oscillations. We tested whether fMRI can detect neural oscillations using human visual cortex as a model system. We detected small oscillatory fMRI signals in response to stimuli oscillating at up to 0.75 Hz within single scan sessions, and these responses were an order of magnitude larger than predicted by canonical linear models. Simultaneous EEG-fMRI and simulations based on a biophysical model of the hemodynamic response to neuronal activity suggested that the blood oxygen level-dependent response becomes faster for rapidly varying stimuli, enabling the detection of higher frequencies than expected. Accounting for phase delays across voxels further improved detection, demonstrating that identifying vascular delays will be of increasing importance with higher-frequency activity. These results challenge the assumption that the hemodynamic response is slow, and demonstrate that fMRI has the potential to map neural oscillations directly throughout the brain.
Preliminary studies of a simultaneous PET/MRI scanner based on the RatCAP small animal tomograph

NASA Astrophysics Data System (ADS)

Woody, C.; Schlyer, D.; Vaska, P.; Tomasi, D.; Solis-Najera, S.; Rooney, W.; Pratte, J.-F.; Junnarkar, S.; Stoll, S.; Master, Z.; Purschke, M.; Park, S.-J.; Southekal, S.; Kriplani, A.; Krishnamoorthy, S.; Maramraju, S.; O'Connor, P.; Radeka, V.

2007-02-01

We are developing a scanner that will allow simultaneous acquisition of high resolution anatomical data using magnetic resonance imaging (MRI) and quantitative physiological data using positron emission tomography (PET). The approach is based on the technology used for the RatCAP conscious small animal PET tomograph which utilizes block detectors consisting of pixelated arrays of LSO crystals read out with matching arrays of avalanche photodiodes and a custom-designed ASIC. The version of this detector used for simultaneous PET/MRI imaging will be constructed out of all nonmagnetic materials and will be situated inside the MRI field. We have demonstrated that the PET detector and its electronics can be operated inside the MRI, and have obtained MRI images with various detector components located inside the MRI field. The MRI images show minimal distortion in this configuration even where some components still contain traces of certain magnetic materials. We plan to improve on the image quality in the future using completely non-magnetic components and by tuning the MRI pulse sequences. The combined result will be a highly compact, low mass PET scanner that can operate inside an MRI magnet without distorting the MRI image, and can be retrofitted into existing MRI instruments.
A diffusion model-free framework with echo time dependence for free-water elimination and brain tissue microstructure characterization.

PubMed

Molina-Romero, Miguel; Gómez, Pedro A; Sperl, Jonathan I; Czisch, Michael; Sämann, Philipp G; Jones, Derek K; Menzel, Marion I; Menze, Bjoern H

2018-03-23

The compartmental nature of brain tissue microstructure is typically studied by diffusion MRI, MR relaxometry or their correlation. Diffusion MRI relies on signal representations or biophysical models, while MR relaxometry and correlation studies are based on regularized inverse Laplace transforms (ILTs). Here we introduce a general framework for characterizing microstructure that does not depend on diffusion modeling and replaces ill-posed ILTs with blind source separation (BSS). This framework yields proton density, relaxation times, volume fractions, and signal disentanglement, allowing for separation of the free-water component. Diffusion experiments repeated for several different echo times, contain entangled diffusion and relaxation compartmental information. These can be disentangled by BSS using a physically constrained nonnegative matrix factorization. Computer simulations, phantom studies, together with repeatability and reproducibility experiments demonstrated that BSS is capable of estimating proton density, compartmental volume fractions and transversal relaxations. In vivo results proved its potential to correct for free-water contamination and to estimate tissue parameters. Formulation of the diffusion-relaxation dependence as a BSS problem introduces a new framework for studying microstructure compartmentalization, and a novel tool for free-water elimination. © 2018 International Society for Magnetic Resonance in Medicine.
Pilot study for supervised target detection applied to spatially registered multiparametric MRI in order to non-invasively score prostate cancer.

PubMed

Mayer, Rulon; Simone, Charles B; Skinner, William; Turkbey, Baris; Choykey, Peter

2018-03-01

Gleason Score (GS) is a validated predictor of prostate cancer (PCa) disease progression and outcomes. GS from invasive needle biopsies suffers from significant inter-observer variability and possible sampling error, leading to underestimating disease severity ("underscoring") and can result in possible complications. A robust non-invasive image-based approach is, therefore, needed. Use spatially registered multi-parametric MRI (MP-MRI), signatures, and supervised target detection algorithms (STDA) to non-invasively GS PCa at the voxel level. This study retrospectively analyzed 26 MP-MRI from The Cancer Imaging Archive. The MP-MRI (T2, Diffusion Weighted, Dynamic Contrast Enhanced) were spatially registered to each other, combined into stacks, and stitched together to form hypercubes. Multi-parametric (or multi-spectral) signatures derived from a training set of registered MP-MRI were transformed using statistics-based Whitening-Dewhitening (WD). Transformed signatures were inserted into STDA (having conical decision surfaces) applied to registered MP-MRI determined the tumor GS. The MRI-derived GS was quantitatively compared to the pathologist's assessment of the histology of sectioned whole mount prostates from patients who underwent radical prostatectomy. In addition, a meta-analysis of 17 studies of needle biopsy determined GS with confusion matrices and was compared to the MRI-determined GS. STDA and histology determined GS are highly correlated (R = 0.86, p < 0.02). STDA more accurately determined GS and reduced GS underscoring of PCa relative to needle biopsy as summarized by meta-analysis (p < 0.05). This pilot study found registered MP-MRI, STDA, and WD transforms of signatures shows promise in non-invasively GS PCa and reducing underscoring with high spatial resolution. Copyright © 2018 Elsevier Ltd. All rights reserved.
A Selective Review of Simulated Driving Studies: Combining Naturalistic and Hybrid Paradigms, Analysis Approaches, and Future Directions

PubMed Central

Calhoun, V. D.; Pearlson, G. D.

2011-01-01

Naturalistic paradigms such as movie watching or simulated driving that mimic closely real-world complex activities are becoming more widely used in functional magnetic resonance imaging (fMRI) studies both because of their ability to robustly stimulate brain connectivity and the availability of analysis methods which are able to capitalize on connectivity within and among intrinsic brain networks identified both during a task and in resting fMRI data. In this paper we review over a decade of work from our group and others on the use of simulated driving paradigms to study both the healthy brain as well as the effects of acute alcohol administration on functional connectivity during such paradigms. We briefly review our initial work focused on the configuration of the driving simulator and the analysis strategies. We then describe in more detail several recent studies from our group including a hybrid study examining distracted driving and compare resulting data with those from a separate visual oddball task. The analysis of these data were performed primarily using a combination of group independent component analysis (ICA) and the general linear model (GLM) and in the various studies we highlight novel findings which result from an analysis of either 1) within-network connectivity, 2) inter-network connectivity, also called functional network connectivity, or 3) the degree to which the modulation of the various intrinsic networks were associated with the alcohol administration and the task context. Despite the fact that the behavioral effects of alcohol intoxication are relatively well known, there is still much to discover on how acute alcohol exposure modulates brain function in a selective manner, associated with behavioral alterations. Through the above studies, we have learned more regarding the impact of acute alcohol intoxication on organization of the brain’s intrinsic connectivity networks during performance of a complex, real-world cognitive operation. Lessons learned from the above studies have broader applicability to designing ecologically valid, complex, functional MRI cognitive paradigms and incorporating pharmacologic challenges into such studies. Overall, the use of hybrid driving studies is a particularly promising area of neuroscience investigation. PMID:21718791
Magnetic susceptibility induced echo time shifts: Is there a bias in age-related fMRI studies?

PubMed Central

Ngo, Giang-Chau; Wong, Chelsea N.; Guo, Steve; Paine, Thomas; Kramer, Arthur F.; Sutton, Bradley P.

2016-01-01

Purpose To evaluate the potential for bias in functional MRI (fMRI) aging studies resulting from age-related differences in magnetic field distributions which can impact echo time and functional contrast. Materials and Methods Magnetic field maps were taken on 31 younger adults (age: 22 ± 2.9 years) and 46 older adults (age: 66 ± 4.5 years) on a 3 T scanner. Using the spatial gradients of the magnetic field map for each participant, an echo planar imaging (EPI) trajectory was simulated. The effective echo time, time at which the k-space trajectory is the closest to the center of k-space, was calculated. This was used to examine both within-subject and across-age-group differences in the effective echo time maps. The Blood Oxygenation Level Dependent (BOLD) percent signal change resulting from those echo time shifts was also calculated to determine their impact on fMRI aging studies. Result For a single subject, the effective echo time varied as much as ± 5 ms across the brain. An unpaired t-test between the effective echo time across age group resulted in significant differences in several regions of the brain (p<0.01). The difference in echo time was only approximately 1 ms, however which is not expected to have an important impact on BOLD fMRI percent signal change (< 4%). Conclusion Susceptibility-induced magnetic field gradients induce local echo time shifts in gradient echo fMRI images, which can cause variable BOLD sensitivity across the brain. However, the age-related differences in BOLD signal are expected to be small for an fMRI study at 3 T. PMID:27299727
An update on risk factors for cartilage loss in knee osteoarthritis assessed using MRI-based semiquantitative grading methods.

PubMed

Alizai, Hamza; Roemer, Frank W; Hayashi, Daichi; Crema, Michel D; Felson, David T; Guermazi, Ali

2015-03-01

Arthroscopy-based semiquantitative scoring systems such as Outerbridge and Noyes' scores were the first to be developed for the purpose of grading cartilage defects. As magnetic resonance imaging (MRI) became available for evaluation of the osteoarthritic knee joint, these systems were adapted for use with MRI. Later on, grading methods such as the Whole Organ Magnetic Resonance Score, the Boston-Leeds Osteoarthritis Knee Score and the MRI Osteoarthritis Knee Score were designed specifically for performing whole-organ assessment of the knee joint structures, including cartilage. Cartilage grades on MRI obtained with these scoring systems represent optimal outcome measures for longitudinal studies, and are designed to enhance understanding of the knee osteoarthritis disease process. The purpose of this narrative review is to describe cartilage assessment in knee osteoarthritis using currently available MRI-based semiquantitative whole-organ scoring systems, and to provide an update on the risk factors for cartilage loss in knee osteoarthritis as assessed with these scoring systems.
Combining anatomical, diffusion, and resting state functional magnetic resonance imaging for individual classification of mild and moderate Alzheimer's disease.

PubMed

Schouten, Tijn M; Koini, Marisa; de Vos, Frank; Seiler, Stephan; van der Grond, Jeroen; Lechner, Anita; Hafkemeijer, Anne; Möller, Christiane; Schmidt, Reinhold; de Rooij, Mark; Rombouts, Serge A R B

2016-01-01

Magnetic resonance imaging (MRI) is sensitive to structural and functional changes in the brain caused by Alzheimer's disease (AD), and can therefore be used to help in diagnosing the disease. Improving classification of AD patients based on MRI scans might help to identify AD earlier in the disease's progress, which may be key in developing treatments for AD. In this study we used an elastic net classifier based on several measures derived from the MRI scans of mild to moderate AD patients (N = 77) from the prospective registry on dementia study and controls (N = 173) from the Austrian Stroke Prevention Family Study. We based our classification on measures from anatomical MRI, diffusion weighted MRI and resting state functional MRI. Our unimodal classification performance ranged from an area under the curve (AUC) of 0.760 (full correlations between functional networks) to 0.909 (grey matter density). When combining measures from multiple modalities in a stepwise manner, the classification performance improved to an AUC of 0.952. This optimal combination consisted of grey matter density, white matter density, fractional anisotropy, mean diffusivity, and sparse partial correlations between functional networks. Classification performance for mild AD as well as moderate AD also improved when using this multimodal combination. We conclude that different MRI modalities provide complementary information for classifying AD. Moreover, combining multiple modalities can substantially improve classification performance over unimodal classification.
Measuring and modeling of a three-dimensional tracer transport in a planted soil column

NASA Astrophysics Data System (ADS)

Schroeder, N.; Javaux, M.; Haber-Pohlmeier, S.; Pohlmeier, A. J.; Huber, K.; Vereecken, H.; Vanderborght, J.

2013-12-01

Water flow from soil to root is driven by the plant transpiration and an important component of the hydrological cycle. The model R-SWMS combines three-dimensional (3D) water flow and solute transport in soil with a detailed description of root structure in three dimensions [1,2]. This model offers the possibility to calculate root water and solute uptake and flow within the roots, which enables explicit studies with respect to the distribution of water and solutes around the roots as well as local processes at the root-soil interface. In this study, we compared measured data from a tracer experiment using Magnetic Resonance Imaging (MRI) with simulations in order to assess the distribution and magnitude of the water uptake of a young lupine plant. An aqueous solution of the Gadolinium-complex (Gd-DTPA2-) was chosen as a tracer, as it behaves conservatively and is ideally suited for MRI. Water flow in the soil towards the roots can thus be visualized by following the change in tracer concentrations over time. The data were obtained by MRI, providing high resolution 3D images of the tracer distribution and root architecture structures by using a spin echo pulse sequence, which is strongly T1- weighted to be tracer sensitive [3], and T2 -weighted for root imaging [4]. This experimental setup was simulated using the 3D high-resolution numerical model R-SWMS. The comparison between MRI data and the simulations showed extensive effects of root architecture parameters on solute spreading. Although the results of our study showed the strength of combining non-invasive measurements and 3D modeling of solute and water flow in soil-root systems, where the derivation of plant hydraulic parameters such as axial and radial root conductivities is possible, current limitations were found with respect to MRI measurements and process description. [1] Javaux, M., T. Schröder, J. Vanderborght, and H. Vereecken (2008), Use of a Three-Dimensional Detailed Modeling Approach for Predicting Root Water Uptake, Vadose Zone Journal, 7(3), 1079-1079. [2] Schröder, N., M. Javaux, J. Vanderborght, B. Steffen, and H. Vereecken (2012), Effect of Root Water and Solute Uptake on Apparent Soil Dispersivity: A Simulation Study, Vadose Zone Journal, 11(3). [3 ]Haber-Pohlmeier, S., Bechtold, M., Stapf, S., and Pohlmeier, A. (2010). Water Flow Monitored by Tracer Transport in Natural Porous Media Using Magnetic Resonance Imaging. Vadose Zone Journal (9),835-845. [4] Stingaciu, L. R., Schulz, H., Pohlmeier, A., Behnke, S., Zilken, H., Vereecken, H., and Javaux, M. (2013). In Situ Root System Architecture Extraction from Magnetic Resonance Imaging for Application to Water Uptake Modeling. Vadose Zone Journal.
3D source localization of interictal spikes in epilepsy patients with MRI lesions

NASA Astrophysics Data System (ADS)

Ding, Lei; Worrell, Gregory A.; Lagerlund, Terrence D.; He, Bin

2006-08-01

The present study aims to accurately localize epileptogenic regions which are responsible for epileptic activities in epilepsy patients by means of a new subspace source localization approach, i.e. first principle vectors (FINE), using scalp EEG recordings. Computer simulations were first performed to assess source localization accuracy of FINE in the clinical electrode set-up. The source localization results from FINE were compared with the results from a classic subspace source localization approach, i.e. MUSIC, and their differences were tested statistically using the paired t-test. Other factors influencing the source localization accuracy were assessed statistically by ANOVA. The interictal epileptiform spike data from three adult epilepsy patients with medically intractable partial epilepsy and well-defined symptomatic MRI lesions were then studied using both FINE and MUSIC. The comparison between the electrical sources estimated by the subspace source localization approaches and MRI lesions was made through the coregistration between the EEG recordings and MRI scans. The accuracy of estimations made by FINE and MUSIC was also evaluated and compared by R2 statistic, which was used to indicate the goodness-of-fit of the estimated sources to the scalp EEG recordings. The three-concentric-spheres head volume conductor model was built for each patient with three spheres of different radii which takes the individual head size and skull thickness into consideration. The results from computer simulations indicate that the improvement of source spatial resolvability and localization accuracy of FINE as compared with MUSIC is significant when simulated sources are closely spaced, deep, or signal-to-noise ratio is low in a clinical electrode set-up. The interictal electrical generators estimated by FINE and MUSIC are in concordance with the patients' structural abnormality, i.e. MRI lesions, in all three patients. The higher R2 values achieved by FINE than MUSIC indicate that FINE provides a more satisfactory fitting of the scalp potential measurements than MUSIC in all patients. The present results suggest that FINE provides a useful brain source imaging technique, from clinical EEG recordings, for identifying and localizing epileptogenic regions in epilepsy patients with focal partial seizures. The present study may lead to the establishment of a high-resolution source localization technique from scalp-recorded EEGs for aiding presurgical planning in epilepsy patients.
Diffusion MRI noise mapping using random matrix theory

PubMed Central

Veraart, Jelle; Fieremans, Els; Novikov, Dmitry S.

2016-01-01

Purpose To estimate the spatially varying noise map using a redundant magnitude MR series. Methods We exploit redundancy in non-Gaussian multi-directional diffusion MRI data by identifying its noise-only principal components, based on the theory of noisy covariance matrices. The bulk of PCA eigenvalues, arising due to noise, is described by the universal Marchenko-Pastur distribution, parameterized by the noise level. This allows us to estimate noise level in a local neighborhood based on the singular value decomposition of a matrix combining neighborhood voxels and diffusion directions. Results We present a model-independent local noise mapping method capable of estimating noise level down to about 1% error. In contrast to current state-of-the art techniques, the resultant noise maps do not show artifactual anatomical features that often reflect physiological noise, the presence of sharp edges, or a lack of adequate a priori knowledge of the expected form of MR signal. Conclusions Simulations and experiments show that typical diffusion MRI data exhibit sufficient redundancy that enables accurate, precise, and robust estimation of the local noise level by interpreting the PCA eigenspectrum in terms of the Marchenko-Pastur distribution. PMID:26599599
Dissipative structures in magnetorotational turbulence

NASA Astrophysics Data System (ADS)

Ross, Johnathan; Latter, Henrik N.

2018-07-01

Via the process of accretion, magnetorotational turbulence removes energy from a disc's orbital motion and transforms it into heat. Turbulent heating is far from uniform and is usually concentrated in small regions of intense dissipation, characterized by abrupt magnetic reconnection and higher temperatures. These regions are of interest because they might generate non-thermal emission, in the form of flares and energetic particles, or thermally process solids in protoplanetary discs. Moreover, the nature of the dissipation bears on the fundamental dynamics of the magnetorotational instability (MRI) itself: local simulations indicate that the large-scale properties of the turbulence (e.g. saturation levels and the stress-pressure relationship) depend on the short dissipative scales. In this paper we undertake a numerical study of how the MRI dissipates and the small-scale dissipative structures it employs to do so. We use the Godunov code RAMSES and unstratified compressible shearing boxes. Our simulations reveal that dissipation is concentrated in ribbons of strong magnetic reconnection that are significantly elongated in azimuth, up to a scale height. Dissipative structures are hence meso-scale objects, and potentially provide a route by which large scales and small scales interact. We go on to show how these ribbons evolve over time - forming, merging, breaking apart, and disappearing. Finally, we reveal important couplings between the large-scale density waves generated by the MRI and the small-scale structures, which may illuminate the stress-pressure relationship in MRI turbulence.
MR image reconstruction via guided filter.

PubMed

Huang, Heyan; Yang, Hang; Wang, Kang

2018-04-01

Magnetic resonance imaging (MRI) reconstruction from the smallest possible set of Fourier samples has been a difficult problem in medical imaging field. In our paper, we present a new approach based on a guided filter for efficient MRI recovery algorithm. The guided filter is an edge-preserving smoothing operator and has better behaviors near edges than the bilateral filter. Our reconstruction method is consist of two steps. First, we propose two cost functions which could be computed efficiently and thus obtain two different images. Second, the guided filter is used with these two obtained images for efficient edge-preserving filtering, and one image is used as the guidance image, the other one is used as a filtered image in the guided filter. In our reconstruction algorithm, we can obtain more details by introducing guided filter. We compare our reconstruction algorithm with some competitive MRI reconstruction techniques in terms of PSNR and visual quality. Simulation results are given to show the performance of our new method.
Iterative image reconstruction for PROPELLER-MRI using the nonuniform fast fourier transform.

PubMed

Tamhane, Ashish A; Anastasio, Mark A; Gui, Minzhi; Arfanakis, Konstantinos

2010-07-01

To investigate an iterative image reconstruction algorithm using the nonuniform fast Fourier transform (NUFFT) for PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction) MRI. Numerical simulations, as well as experiments on a phantom and a healthy human subject were used to evaluate the performance of the iterative image reconstruction algorithm for PROPELLER, and compare it with that of conventional gridding. The trade-off between spatial resolution, signal to noise ratio, and image artifacts, was investigated for different values of the regularization parameter. The performance of the iterative image reconstruction algorithm in the presence of motion was also evaluated. It was demonstrated that, for a certain range of values of the regularization parameter, iterative reconstruction produced images with significantly increased signal to noise ratio, reduced artifacts, for similar spatial resolution, compared with gridding. Furthermore, the ability to reduce the effects of motion in PROPELLER-MRI was maintained when using the iterative reconstruction approach. An iterative image reconstruction technique based on the NUFFT was investigated for PROPELLER MRI. For a certain range of values of the regularization parameter, the new reconstruction technique may provide PROPELLER images with improved image quality compared with conventional gridding. (c) 2010 Wiley-Liss, Inc.

Iterative Image Reconstruction for PROPELLER-MRI using the NonUniform Fast Fourier Transform

PubMed Central

Tamhane, Ashish A.; Anastasio, Mark A.; Gui, Minzhi; Arfanakis, Konstantinos

2013-01-01

Purpose To investigate an iterative image reconstruction algorithm using the non-uniform fast Fourier transform (NUFFT) for PROPELLER (Periodically Rotated Overlapping parallEL Lines with Enhanced Reconstruction) MRI. Materials and Methods Numerical simulations, as well as experiments on a phantom and a healthy human subject were used to evaluate the performance of the iterative image reconstruction algorithm for PROPELLER, and compare it to that of conventional gridding. The trade-off between spatial resolution, signal to noise ratio, and image artifacts, was investigated for different values of the regularization parameter. The performance of the iterative image reconstruction algorithm in the presence of motion was also evaluated. Results It was demonstrated that, for a certain range of values of the regularization parameter, iterative reconstruction produced images with significantly increased SNR, reduced artifacts, for similar spatial resolution, compared to gridding. Furthermore, the ability to reduce the effects of motion in PROPELLER-MRI was maintained when using the iterative reconstruction approach. Conclusion An iterative image reconstruction technique based on the NUFFT was investigated for PROPELLER MRI. For a certain range of values of the regularization parameter the new reconstruction technique may provide PROPELLER images with improved image quality compared to conventional gridding. PMID:20578028
Imaging tooth enamel using zero echo time (ZTE) magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Rychert, Kevin M.; Zhu, Gang; Kmiec, Maciej M.; Nemani, Venkata K.; Williams, Benjamin B.; Flood, Ann B.; Swartz, Harold M.; Gimi, Barjor

2015-03-01

In an event where many thousands of people may have been exposed to levels of radiation that are sufficient to cause the acute radiation syndrome, we need technology that can estimate the absorbed dose on an individual basis for triage and meaningful medical decision making. Such dose estimates may be achieved using in vivo electron paramagnetic resonance (EPR) tooth biodosimetry, which measures the number of persistent free radicals that are generated in tooth enamel following irradiation. However, the accuracy of dose estimates may be impacted by individual variations in teeth, especially the amount and distribution of enamel in the inhomogeneous sensitive volume of the resonator used to detect the radicals. In order to study the relationship between interpersonal variations in enamel and EPR-based dose estimates, it is desirable to estimate these parameters nondestructively and without adding radiation to the teeth. Magnetic Resonance Imaging (MRI) is capable of acquiring structural and biochemical information without imparting additional radiation, which may be beneficial for many EPR dosimetry studies. However, the extremely short T2 relaxation time in tooth structures precludes tooth imaging using conventional MRI methods. Therefore, we used zero echo time (ZTE) MRI to image teeth ex vivo to assess enamel volumes and spatial distributions. Using these data in combination with the data on the distribution of the transverse radio frequency magnetic field from electromagnetic simulations, we then can identify possible sources of variations in radiation-induced signals detectable by EPR. Unlike conventional MRI, ZTE applies spatial encoding gradients during the RF excitation pulse, thereby facilitating signal acquisition almost immediately after excitation, minimizing signal loss from short T2 relaxation times. ZTE successfully provided volumetric measures of tooth enamel that may be related to variations that impact EPR dosimetry and facilitate the development of analytical procedures for individual dose estimates.
3D-Printed masks as a new approach for immobilization in radiotherapy – a study of positioning accuracy

PubMed Central

Haefner, Matthias Felix; Giesel, Frederik Lars; Mattke, Matthias; Rath, Daniel; Wade, Moritz; Kuypers, Jacob; Preuss, Alan; Kauczor, Hans-Ulrich; Schenk, Jens-Peter; Debus, Juergen; Sterzing, Florian; Unterhinninghofen, Roland

2018-01-01

We developed a new approach to produce individual immobilization devices for the head based on MRI data and 3D printing technologies. The purpose of this study was to determine positioning accuracy with healthy volunteers. 3D MRI data of the head were acquired for 8 volunteers. In-house developed software processed the image data to generate a surface mesh model of the immobilization mask. After adding an interface for the couch, the fixation setup was materialized using a 3D printer with acrylonitrile butadiene styrene (ABS). Repeated MRI datasets (n=10) were acquired for all volunteers wearing their masks thus simulating a setup for multiple fractions. Using automatic image-to-image registration, displacements of the head were calculated relative to the first dataset (6 degrees of freedom). The production process has been described in detail. The absolute lateral (x), vertical (y) and longitudinal (z) translations ranged between −0.7 and 0.5 mm, −1.8 and 1.4 mm, and −1.6 and 2.4 mm, respectively. The absolute rotations for pitch (x), yaw (y) and roll (z) ranged between −0.9 and 0.8°, −0.5 and 1.1°, and −0.6 and 0.8°, respectively. The mean 3D displacement was 0.9 mm with a standard deviation (SD) of the systematic and random error of 0.2 mm and 0.5 mm, respectively. In conclusion, an almost entirely automated production process of 3D printed immobilization masks for the head derived from MRI data was established. A high level of setup accuracy was demonstrated in a volunteer cohort. Future research will have to focus on workflow optimization and clinical evaluation. PMID:29464087
3D-Printed masks as a new approach for immobilization in radiotherapy - a study of positioning accuracy.

PubMed

Haefner, Matthias Felix; Giesel, Frederik Lars; Mattke, Matthias; Rath, Daniel; Wade, Moritz; Kuypers, Jacob; Preuss, Alan; Kauczor, Hans-Ulrich; Schenk, Jens-Peter; Debus, Juergen; Sterzing, Florian; Unterhinninghofen, Roland

2018-01-19

We developed a new approach to produce individual immobilization devices for the head based on MRI data and 3D printing technologies. The purpose of this study was to determine positioning accuracy with healthy volunteers. 3D MRI data of the head were acquired for 8 volunteers. In-house developed software processed the image data to generate a surface mesh model of the immobilization mask. After adding an interface for the couch, the fixation setup was materialized using a 3D printer with acrylonitrile butadiene styrene (ABS). Repeated MRI datasets (n=10) were acquired for all volunteers wearing their masks thus simulating a setup for multiple fractions. Using automatic image-to-image registration, displacements of the head were calculated relative to the first dataset (6 degrees of freedom). The production process has been described in detail. The absolute lateral (x), vertical (y) and longitudinal (z) translations ranged between -0.7 and 0.5 mm, -1.8 and 1.4 mm, and -1.6 and 2.4 mm, respectively. The absolute rotations for pitch (x), yaw (y) and roll (z) ranged between -0.9 and 0.8°, -0.5 and 1.1°, and -0.6 and 0.8°, respectively. The mean 3D displacement was 0.9 mm with a standard deviation (SD) of the systematic and random error of 0.2 mm and 0.5 mm, respectively. In conclusion, an almost entirely automated production process of 3D printed immobilization masks for the head derived from MRI data was established. A high level of setup accuracy was demonstrated in a volunteer cohort. Future research will have to focus on workflow optimization and clinical evaluation.
Multicenter prospective study of magnetic resonance imaging prior to breast-conserving surgery for breast cancer.

PubMed

Liu, Qian; Liu, Yinhua; Xu, Ling; Duan, Xuening; Li, Ting; Qin, Naishan; Kang, Hua; Jiang, Hongchuan; Yang, Deqi; Qu, Xiang; Jiang, Zefei; Yu, Chengze

2014-01-01

This multicenter prospective study aimed to assess the utility of dynamic enhanced magnetic resonance imaging (MRI) prior to breast-conserving surgery for breast cancer. The research subjects were drawn from patients with primary early resectable breast cancer treated in the breast disease centers of six three-level hospitals in Beijing from 1 January 2010 to 31 December 2012. The participants were allocated to a breast-conserving surgery group (breast-conserving group) or a total mastectomy group (total mastectomy group). Enhanced MRI was used to measure breast volume, longest diameter of tumor and tumor volume. The correlations between these measurements and those derived from histopathologic findings were assessed. The relationships between the success rate of breast-conserving surgery and MRI- and pathology-based measurement results were statistically analyzed in the breast-conserving group. The study included 461 cases in the total mastectomy group and 195 in the breast-conserving group. Allocation to these groups was based on clinical indications and patient preferences. The cut-off for concurrence between MRI- and pathology-based measurements of the longest diameter of tumor was set at 0.3 cm. In the total mastectomy group, the confidence interval for 95% concurrence of these measurements was 35.41%-44.63%. Correlation coefficients for MRI and histopathology-based measurements of breast volume, tumor volume and tumor volume/breast volume ratio were r = 0.861, 0.569, and 0.600, respectively (all P < 0.001). In the breast-conserving group, with 0.30 cm taken as the cut-off for concurrence, the 95% confidence interval for MRI and pathology-based measurements of the longest diameter of tumor was 29.98%-44.01%. The subjective and objective success rates for breast-conserving surgery were 100% and 88.54%, respectively. There were significant correlations between dynamic enhanced MRI- and histopathology-based measurements of the longest diameter of breast lesions, breast and tumor volumes, and breast volume/tumor volume ratios. Preoperative MRI examination improves the success rate of breast-conserving surgery.
Compact Intraoperative MRI: Stereotactic Accuracy and Future Directions.

PubMed

Markowitz, Daniel; Lin, Dishen; Salas, Sussan; Kohn, Nina; Schulder, Michael

2017-01-01

Intraoperative imaging must supply data that can be used for accurate stereotactic navigation. This information should be at least as accurate as that acquired from diagnostic imagers. The aim of this study was to compare the stereotactic accuracy of an updated compact intraoperative MRI (iMRI) device based on a 0.15-T magnet to standard surgical navigation on a 1.5-T diagnostic scan MRI and to navigation with an earlier model of the same system. The accuracy of each system was assessed using a water-filled phantom model of the brain. Data collected with the new system were compared to those obtained in a previous study assessing the older system. The accuracy of the new iMRI was measured against standard surgical navigation on a 1.5-T MRI using T1-weighted (W) images. The mean error with the iMRI using T1W images was lower than that based on images from the 1.5-T scan (1.24 vs. 2.43 mm). T2W images from the newer iMRI yielded a lower navigation error than those acquired with the prior model (1.28 vs. 3.15 mm). Improvements in magnet design can yield progressive increases in accuracy, validating the concept of compact, low-field iMRI. Avoiding the need for registration between image and surgical space increases navigation accuracy. © 2017 S. Karger AG, Basel.
Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture

PubMed Central

Meszlényi, Regina J.; Buza, Krisztian; Vidnyánszky, Zoltán

2017-01-01

Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network. PMID:29089883
Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture.

PubMed

Meszlényi, Regina J; Buza, Krisztian; Vidnyánszky, Zoltán

2017-01-01

Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network.
MRI with and without a high-density EEG cap--what makes the difference?

PubMed

Klein, Carina; Hänggi, Jürgen; Luechinger, Roger; Jäncke, Lutz

2015-02-01

Besides the benefit of combining electroencephalography (EEG) and magnetic resonance imaging (MRI), much effort has been spent to develop algorithms aimed at successfully cleaning the EEG data from MRI-related gradient and ballistocardiological artifacts. However, there are also studies showing a negative influence of the EEG on MRI data quality. Therefore, in the present study, we focused for the first time on the influence of the EEG on morphometric measurements of T1-weighted MRI data (voxel- and surfaced-based morphometry). Here, we demonstrate a strong influence of the EEG on cortical thickness, surface area, and volume as well as subcortical volumes due to local EEG-related inhomogeneities of the static magnetic (B0) and the gradient field (B1). In a second step, we analyzed the signal-to-noise ratios for both the anatomical and the functional data when recorded simultaneously with EEG and MRI and compared them to the ratios of the MRI data without simultaneous EEG measurements. These analyses revealed consistently lower signal-to-noise ratios for anatomical as well as functional MRI data during simultaneous EEG registration. In contrast, further analyses of T2*-weighted images provided reliable results independent of whether including the individuals' T1-weighted image with or without the EEG cap in the fMRI preprocessing stream. Based on our findings, we strongly recommend against using the structural images obtained during simultaneous EEG-MRI recordings for further anatomical data analysis. Copyright © 2014 Elsevier Inc. All rights reserved.
A Novel Feature-Map Based ICA Model for Identifying the Individual, Intra/Inter-Group Brain Networks across Multiple fMRI Datasets.

PubMed

Wang, Nizhuan; Chang, Chunqi; Zeng, Weiming; Shi, Yuhu; Yan, Hongjie

2017-01-01

Independent component analysis (ICA) has been widely used in functional magnetic resonance imaging (fMRI) data analysis to evaluate functional connectivity of the brain; however, there are still some limitations on ICA simultaneously handling neuroimaging datasets with diverse acquisition parameters, e.g., different repetition time, different scanner, etc. Therefore, it is difficult for the traditional ICA framework to effectively handle ever-increasingly big neuroimaging datasets. In this research, a novel feature-map based ICA framework (FMICA) was proposed to address the aforementioned deficiencies, which aimed at exploring brain functional networks (BFNs) at different scales, e.g., the first level (individual subject level), second level (intragroup level of subjects within a certain dataset) and third level (intergroup level of subjects across different datasets), based only on the feature maps extracted from the fMRI datasets. The FMICA was presented as a hierarchical framework, which effectively made ICA and constrained ICA as a whole to identify the BFNs from the feature maps. The simulated and real experimental results demonstrated that FMICA had the excellent ability to identify the intergroup BFNs and to characterize subject-specific and group-specific difference of BFNs from the independent component feature maps, which sharply reduced the size of fMRI datasets. Compared with traditional ICAs, FMICA as a more generalized framework could efficiently and simultaneously identify the variant BFNs at the subject-specific, intragroup, intragroup-specific and intergroup levels, implying that FMICA was able to handle big neuroimaging datasets in neuroscience research.
Feasibility of conductivity imaging using subject eddy currents induced by switching of MRI gradients.

PubMed

Oran, Omer Faruk; Ider, Yusuf Ziya

2017-05-01

To investigate the feasibility of low-frequency conductivity imaging based on measuring the magnetic field due to subject eddy currents induced by switching of MRI z-gradients. We developed a simulation model for calculating subject eddy currents and the magnetic fields they generate (subject eddy fields). The inverse problem of obtaining conductivity distribution from subject eddy fields was formulated as a convection-reaction partial differential equation. For measuring subject eddy fields, a modified spin-echo pulse sequence was used to determine the contribution of subject eddy fields to MR phase images. In the simulations, successful conductivity reconstructions were obtained by solving the derived convection-reaction equation, suggesting that the proposed reconstruction algorithm performs well under ideal conditions. However, the level of the calculated phase due to the subject eddy field in a representative object indicates that this phase is below the noise level and cannot be measured with an uncertainty sufficiently low for accurate conductivity reconstruction. Furthermore, some artifacts other than random noise were observed in the measured phases, which are discussed in relation to the effects of system imperfections during readout. Low-frequency conductivity imaging does not seem feasible using basic pulse sequences such as spin-echo on a clinical MRI scanner. Magn Reson Med 77:1926-1937, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.
Diagnostic Pathway with Multiparametric Magnetic Resonance Imaging Versus Standard Pathway: Results from a Randomized Prospective Study in Biopsy-naïve Patients with Suspected Prostate Cancer.

PubMed

Porpiglia, Francesco; Manfredi, Matteo; Mele, Fabrizio; Cossu, Marco; Bollito, Enrico; Veltri, Andrea; Cirillo, Stefano; Regge, Daniele; Faletti, Riccardo; Passera, Roberto; Fiori, Cristian; De Luca, Stefano

2017-08-01

An approach based on multiparametric magnetic resonance imaging (mpMRI) might increase the detection rate (DR) of clinically significant prostate cancer (csPCa). To compare an mpMRI-based pathway with the standard approach for the detection of prostate cancer (PCa) and csPCa. Between November 2014 and April 2016, 212 biopsy-naïve patients with suspected PCa (prostate specific antigen level ≤15 ng/ml and negative digital rectal examination results) were included in this randomized clinical trial. Patients were randomized into a prebiopsy mpMRI group (arm A, n=107) or a standard biopsy (SB) group (arm B, n=105). In arm A, patients with mpMRI evidence of lesions suspected for PCa underwent mpMRI/transrectal ultrasound fusion software-guided targeted biopsy (TB) (n=81). The remaining patients in arm A (n=26) with negative mpMRI results and patients in arm B underwent 12-core SB. The primary end point was comparison of the DR of PCa and csPCa between the two arms of the study; the secondary end point was comparison of the DR between TB and SB. The overall DRs were higher in arm A versus arm B for PCa (50.5% vs 29.5%, respectively; p=0.002) and csPCa (43.9% vs 18.1%, respectively; p<0.001). Concerning the biopsy approach, that is, TB in arm A, SB in arm A, and SB in arm B, the overall DRs were significantly different for PCa (60.5% vs 19.2% vs 29.5%, respectively; p<0.001) and for csPCa (56.8% vs 3.8% vs 18.1%, respectively; p<0.001). The reproducibility of the study could have been affected by the single-center nature. A diagnostic pathway based on mpMRI had a higher DR than the standard pathway in both PCa and csPCa. In this randomized trial, a pathway for the diagnosis of prostate cancer based on multiparametric magnetic resonance imaging (mpMRI) was compared with the standard pathway based on random biopsy. The mpMRI-based pathway had better performance than the standard pathway. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.
A Prospective Study of the Utility of Magnetic Resonance Imaging in Determining Candidacy for Partial Breast Irradiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dorn, Paige L.; Al-Hallaq, Hania A.; Haq, Farah

2013-03-01

Purpose: Retrospective data have demonstrated that breast magnetic resonance imaging (MRI) may change a patient's eligibility for partial breast irradiation (PBI) by identifying multicentric, multifocal, or contralateral disease. The objective of the current study was to prospectively determine the frequency with which MRI identifies occult disease and to establish clinical factors associated with a higher likelihood of MRI prompting changes in PBI eligibility. Methods and Materials: At The University of Chicago, women with breast cancer uniformly undergo MRI in addition to mammography and ultrasonography. From June 2009 through May 2011, all patients were screened prospectively in a multidisciplinary conference formore » PBI eligibility based on standard imaging, and the impact of MRI on PBI eligibility according to National Surgical Adjuvant Breast and Bowel Project protocol B-39/Radiation Therapy Oncology Group protocol 0413 entry criteria was recorded. Univariable analysis was performed using clinical characteristics in both the prospective cohort and in a separate cohort of retrospectively identified patients. Pooled analysis was used to derive a scoring index predictive of the risk that MRI would identify additional disease. Results: A total of 521 patients were screened for PBI eligibility, and 124 (23.8%) patients were deemed eligible for PBI based on standard imaging. MRI findings changed PBI eligibility in 12.9% of patients. In the pooled univariable analysis, tumor size ≥2 cm on mammography or ultrasonography (P=.02), age <50 years (P=.01), invasive lobular histology (P=.01), and HER-2/neu amplification (P=.01) were associated with a higher likelihood of MRI changing PBI eligibility. A predictive score was generated by summing the number of significant risk factors. Patients with a score of 0, 1, 2, and 3 had changes to eligibility based on MRI findings in 2.8%, 13.2%, 38.1%, and 100%, respectively (P<.0001). Conclusions: MRI identified additional disease in a significant number of patients eligible for PBI, based on standard imaging. Clinical characteristics may be useful in directing implementation of MRI in the staging of PBI candidates.« less
Magnetic resonance imaging in experimental stroke and comparison with histology: systematic review and meta-analysis.

PubMed

Milidonis, Xenios; Marshall, Ian; Macleod, Malcolm R; Sena, Emily S

2015-03-01

Because the new era of preclinical stroke research demands improvements in validity and generalizability of findings, moving from single site to multicenter studies could be pivotal. However, the conduct of magnetic resonance imaging (MRI) in stroke remains ill-defined. We sought to assess the variability in the use of MRI for evaluating lesions post stroke and to examine the possibility as an alternative to gold standard histology for measuring the infarct size. We identified animal studies of ischemic stroke reporting lesion sizes using MRI. We assessed the degree of heterogeneity and reporting of scanning protocols, postprocessing methods, study design characteristics, and study quality. Studies performing histological evaluation of infarct size were further selected to compare with corresponding MRI using meta-regression. Fifty-four articles undertaking a total of 78 different MRI scanning protocols met the inclusion criteria. T2-weighted imaging was most frequently used (83% of the studies), followed by diffusion-weighted imaging (43%). Reporting of the imaging parameters was adequate, but heterogeneity between studies was high. Twelve studies assessed the infarct size using both MRI and histology at corresponding time points, with T2-weighted imaging-based treatment effect having a significant positive correlation with histology (; P<0.001). Guidelines for standardized use and reporting of MRI in preclinical stroke are urgently needed. T2-weighted imaging could be used as an effective in vivo alternative to histology for estimating treatment effects based on the extent of infarction; however, additional studies are needed to explore the effect of individual parameters. © 2015 American Heart Association, Inc.
MR-assisted PET motion correction in simultaneous PET/MRI studies of dementia subjects.

PubMed

Chen, Kevin T; Salcedo, Stephanie; Chonde, Daniel B; Izquierdo-Garcia, David; Levine, Michael A; Price, Julie C; Dickerson, Bradford C; Catana, Ciprian

2018-03-08

Subject motion in positron emission tomography (PET) studies leads to image blurring and artifacts; simultaneously acquired magnetic resonance imaging (MRI) data provides a means for motion correction (MC) in integrated PET/MRI scanners. To assess the effect of realistic head motion and MR-based MC on static [ 18 F]-fluorodeoxyglucose (FDG) PET images in dementia patients. Observational study. Thirty dementia subjects were recruited. 3T hybrid PET/MR scanner where EPI-based and T 1 -weighted sequences were acquired simultaneously with the PET data. Head motion parameters estimated from high temporal resolution MR volumes were used for PET MC. The MR-based MC method was compared to PET frame-based MC methods in which motion parameters were estimated by coregistering 5-minute frames before and after accounting for the attenuation-emission mismatch. The relative changes in standardized uptake value ratios (SUVRs) between the PET volumes processed with the various MC methods, without MC, and the PET volumes with simulated motion were compared in relevant brain regions. The absolute value of the regional SUVR relative change was assessed with pairwise paired t-tests testing at the P = 0.05 level, comparing the values obtained through different MR-based MC processing methods as well as across different motion groups. The intraregion voxelwise variability of regional SUVRs obtained through different MR-based MC processing methods was also assessed with pairwise paired t-tests testing at the P = 0.05 level. MC had a greater impact on PET data quantification in subjects with larger amplitude motion (higher than 18% in the medial orbitofrontal cortex) and greater changes were generally observed for the MR-based MC method compared to the frame-based methods. Furthermore, a mean relative change of ∼4% was observed after MC even at the group level, suggesting the importance of routinely applying this correction. The intraregion voxelwise variability of regional SUVRs was also decreased using MR-based MC. All comparisons were significant at the P = 0.05 level. Incorporating temporally correlated MR data to account for intraframe motion has a positive impact on the FDG PET image quality and data quantification in dementia patients. 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.
Magnetorotational instability and dynamo action in gravito-turbulent astrophysical discs

NASA Astrophysics Data System (ADS)

Riols, A.; Latter, H.

2018-02-01

Though usually treated in isolation, the magnetorotational and gravitational instabilities (MRI and GI) may coincide at certain radii and evolutionary stages of protoplanetary discs and active galactic nuclei. Their mutual interactions could profoundly influence several important processes, such as accretion variability and outbursts, fragmentation and disc truncation, or large-scale magnetic field production. Direct numerical simulations of both instabilities are computationally challenging and remain relatively unexplored. In this paper, we aim to redress this neglect via a set of 3D vertically stratified shearing-box simulations, combining self-gravity and magnetic fields. We show that gravito-turbulence greatly weakens the zero-net-flux MRI. In the limit of efficient cooling (and thus enhanced GI), the MRI is completely suppressed, and yet strong magnetic fields are sustained by the gravito-turbulence. This turbulent `spiral wave' dynamo may have widespread application, especially in galactic discs. Finally, we present preliminary work showing that a strong net-vertical-flux revives the MRI and supports a magnetically dominated state in which the GI is secondary.
Selection of optimal multispectral imaging system parameters for small joint arthritis detection

NASA Astrophysics Data System (ADS)

Dolenec, Rok; Laistler, Elmar; Stergar, Jost; Milanic, Matija

2018-02-01

Early detection and treatment of arthritis is essential for a successful outcome of the treatment, but it has proven to be very challenging with existing diagnostic methods. Novel methods based on the optical imaging of the affected joints are becoming an attractive alternative. A non-contact multispectral imaging (MSI) system for imaging of small joints of human hands and feet is being developed. In this work, a numerical simulation of the MSI system is presented. The purpose of the simulation is to determine the optimal design parameters. Inflamed and unaffected human joint models were constructed with a realistic geometry and tissue distributions, based on a MRI scan of a human finger with a spatial resolution of 0.2 mm. The light transport simulation is based on a weighted-photon 3D Monte Carlo method utilizing CUDA GPU acceleration. An uniform illumination of the finger within the 400-1100 nm spectral range was simulated and the photons exiting the joint were recorded using different acceptance angles. From the obtained reflectance and transmittance images the spectral and spatial features most indicative of inflammation were identified. Optimal acceptance angle and spectral bands were determined. This study demonstrates that proper selection of MSI system parameters critically affects ability of a MSI system to discriminate the unaffected and inflamed joints. The presented system design optimization approach could be applied to other pathologies.
Income generated by women treated with magnetic resonance imaging-based brachytherapy: A simulation study evaluating the macroeconomic benefits of implementing a high-end technology in a public sector healthcare setting.

PubMed

Chakraborty, Santam; Mahantshetty, Umesh; Chopra, Supriya; Lewis, Shirley; Hande, Vinod; Gudi, Shivakumar; Krishnatry, Rahul; Engineer, Reena; Shrivastava, Shyam Kishore

To estimate the difference in income generated if all women presenting in our institute over a 5-year period were treated with MRI-based image-guided brachytherapy (MR-IGBT) instead of conventional radiograph-based brachytherapy (CR-BT). Outcome data from 463 patients (94 treated with MR-IGBT) treated in our institute was used to simulate cumulative women-days of work and cumulative income over 5 years for 5526 patients expected to be treated in this period. The average daily income for a woman was derived from the National Sample Survey Organization (NSSO) survey data. Outcomes from both unmatched and propensity score-matched data sets were simulated. The cumulative income in 5 years ranged between Rs 101-168 million if all patients presenting at our institute underwent MR-IGBT. The simulated excess income ranged from Rs 4-45 million after 5 years, which represented 6-66% of the expenditure incurred for acquiring the required equipment and manpower for practicing exclusive MR-IGBT. Using outcome data from a prospective cohort of patients treated with MR-IGBT in our institute, we demonstrated that significant economic gains may be realized if MR-IGBT was used instead of CR-BT. Copyright © 2017 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.
A variational Bayes spatiotemporal model for electromagnetic brain mapping.

PubMed

Nathoo, F S; Babul, A; Moiseev, A; Virji-Babul, N; Beg, M F

2014-03-01

In this article, we present a new variational Bayes approach for solving the neuroelectromagnetic inverse problem arising in studies involving electroencephalography (EEG) and magnetoencephalography (MEG). This high-dimensional spatiotemporal estimation problem involves the recovery of time-varying neural activity at a large number of locations within the brain, from electromagnetic signals recorded at a relatively small number of external locations on or near the scalp. Framing this problem within the context of spatial variable selection for an underdetermined functional linear model, we propose a spatial mixture formulation where the profile of electrical activity within the brain is represented through location-specific spike-and-slab priors based on a spatial logistic specification. The prior specification accommodates spatial clustering in brain activation, while also allowing for the inclusion of auxiliary information derived from alternative imaging modalities, such as functional magnetic resonance imaging (fMRI). We develop a variational Bayes approach for computing estimates of neural source activity, and incorporate a nonparametric bootstrap for interval estimation. The proposed methodology is compared with several alternative approaches through simulation studies, and is applied to the analysis of a multimodal neuroimaging study examining the neural response to face perception using EEG, MEG, and fMRI. © 2013, The International Biometric Society.
Cluster mass inference via random field theory.

PubMed

Zhang, Hui; Nichols, Thomas E; Johnson, Timothy D

2009-01-01

Cluster extent and voxel intensity are two widely used statistics in neuroimaging inference. Cluster extent is sensitive to spatially extended signals while voxel intensity is better for intense but focal signals. In order to leverage strength from both statistics, several nonparametric permutation methods have been proposed to combine the two methods. Simulation studies have shown that of the different cluster permutation methods, the cluster mass statistic is generally the best. However, to date, there is no parametric cluster mass inference available. In this paper, we propose a cluster mass inference method based on random field theory (RFT). We develop this method for Gaussian images, evaluate it on Gaussian and Gaussianized t-statistic images and investigate its statistical properties via simulation studies and real data. Simulation results show that the method is valid under the null hypothesis and demonstrate that it can be more powerful than the cluster extent inference method. Further, analyses with a single subject and a group fMRI dataset demonstrate better power than traditional cluster size inference, and good accuracy relative to a gold-standard permutation test.

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