[Magnetic resonance imaging in facial injuries and digital fusion CT/MRI].

PubMed

Kozakiewicz, Marcin; Olszycki, Marek; Arkuszewski, Piotr; Stefańczyk, Ludomir

2006-01-01

Magnetic resonance images [MRI] and their digital fusion with computed tomography [CT] data, observed in patients affected with facial injuries, are presented in this study. The MR imaging of 12 posttraumatic patients was performed in the same plains as their previous CT scans. Evaluation focused on quality of the facial soft tissues depicting, which was unsatisfactory in CT. Using the own "Dental Studio" programme the digital fusion of the both modalities was performed. Pathologic dislocations and injures of facial soft tissues are visualized better in MRI than in CT examination. Especially MRI properly reveals disturbances in intraorbital soft structures. MRI-based assessment is valuable in patients affected with facial soft tissues injuries, especially in case of orbita/sinuses hernia. Fusion CT/MRI scans allows to evaluate simultaneously bone structure and soft tissues of the same region.

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.

Improved volumetric measurement of brain structure with a distortion correction procedure using an ADNI phantom.

PubMed

Maikusa, Norihide; Yamashita, Fumio; Tanaka, Kenichiro; Abe, Osamu; Kawaguchi, Atsushi; Kabasawa, Hiroyuki; Chiba, Shoma; Kasahara, Akihiro; Kobayashi, Nobuhisa; Yuasa, Tetsuya; Sato, Noriko; Matsuda, Hiroshi; Iwatsubo, Takeshi

2013-06-01

Serial magnetic resonance imaging (MRI) images acquired from multisite and multivendor MRI scanners are widely used in measuring longitudinal structural changes in the brain. Precise and accurate measurements are important in understanding the natural progression of neurodegenerative disorders such as Alzheimer's disease. However, geometric distortions in MRI images decrease the accuracy and precision of volumetric or morphometric measurements. To solve this problem, the authors suggest a commercially available phantom-based distortion correction method that accommodates the variation in geometric distortion within MRI images obtained with multivendor MRI scanners. The authors' method is based on image warping using a polynomial function. The method detects fiducial points within a phantom image using phantom analysis software developed by the Mayo Clinic and calculates warping functions for distortion correction. To quantify the effectiveness of the authors' method, the authors corrected phantom images obtained from multivendor MRI scanners and calculated the root-mean-square (RMS) of fiducial errors and the circularity ratio as evaluation values. The authors also compared the performance of the authors' method with that of a distortion correction method based on a spherical harmonics description of the generic gradient design parameters. Moreover, the authors evaluated whether this correction improves the test-retest reproducibility of voxel-based morphometry in human studies. A Wilcoxon signed-rank test with uncorrected and corrected images was performed. The root-mean-square errors and circularity ratios for all slices significantly improved (p < 0.0001) after the authors' distortion correction. Additionally, the authors' method was significantly better than a distortion correction method based on a description of spherical harmonics in improving the distortion of root-mean-square errors (p < 0.001 and 0.0337, respectively). Moreover, the authors' method reduced the RMS error arising from gradient nonlinearity more than gradwarp methods. In human studies, the coefficient of variation of voxel-based morphometry analysis of the whole brain improved significantly from 3.46% to 2.70% after distortion correction of the whole gray matter using the authors' method (Wilcoxon signed-rank test, p < 0.05). The authors proposed a phantom-based distortion correction method to improve reproducibility in longitudinal structural brain analysis using multivendor MRI. The authors evaluated the authors' method for phantom images in terms of two geometrical values and for human images in terms of test-retest reproducibility. The results showed that distortion was corrected significantly using the authors' method. In human studies, the reproducibility of voxel-based morphometry analysis for the whole gray matter significantly improved after distortion correction using the authors' method.

Integrating histology and MRI in the first digital brain of common squirrel monkey, Saimiri sciureus

NASA Astrophysics Data System (ADS)

Sun, Peizhen; Parvathaneni, Prasanna; Schilling, Kurt G.; Gao, Yurui; Janve, Vaibhav; Anderson, Adam; Landman, Bennett A.

2015-03-01

This effort is a continuation of development of a digital brain atlas of the common squirrel monkey, Saimiri sciureus, a New World monkey with functional and microstructural organization of central nervous system similar to that of humans. Here, we present the integration of histology with multi-modal magnetic resonance imaging (MRI) atlas constructed from the brain of an adult female squirrel monkey. The central concept of this work is to use block face photography to establish an intermediate common space in coordinate system which preserves the high resolution in-plane resolution of histology while enabling 3-D correspondence with MRI. In vivo MRI acquisitions include high resolution T2 structural imaging (300 μm isotropic) and low resolution diffusion tensor imaging (600 um isotropic). Ex vivo MRI acquisitions include high resolution T2 structural imaging and high resolution diffusion tensor imaging (both 300 μm isotropic). Cortical regions were manually annotated on the co-registered volumes based on published histological sections in-plane. We describe mapping of histology and MRI based data of the common squirrel monkey and construction of a viewing tool that enable online viewing of these datasets. The previously descried atlas MRI is used for its deformation to provide accurate conformation to the MRI, thus adding information at the histological level to the MRI volume. This paper presents the mapping of single 2D image slice in block face as a proof of concept and this can be extended to map the atlas space in 3D coordinate system as part of the future work and can be loaded to an XNAT system for further use.

Individual Differences in the Alignment of Structural and Functional Markers of the V5/MT Complex in Primates

PubMed Central

Large, I.; Bridge, H.; Ahmed, B.; Clare, S.; Kolasinski, J.; Lam, W. W.; Miller, K. L.; Dyrby, T. B.; Parker, A. J.; Smith, J. E. T.; Daubney, G.; Sallet, J.; Bell, A. H.; Krug, K.

2016-01-01

Extrastriate visual area V5/MT in primates is defined both structurally by myeloarchitecture and functionally by distinct responses to visual motion. Myelination is directly identifiable from postmortem histology but also indirectly by image contrast with structural magnetic resonance imaging (sMRI). First, we compared the identification of V5/MT using both sMRI and histology in Rhesus macaques. A section-by-section comparison of histological slices with in vivo and postmortem sMRI for the same block of cortical tissue showed precise correspondence in localizing heavy myelination for V5/MT and neighboring MST. Thus, sMRI in macaques accurately locates histologically defined myelin within areas known to be motion selective. Second, we investigated the functionally homologous human motion complex (hMT+) using high-resolution in vivo imaging. Humans showed considerable intersubject variability in hMT+ location, when defined with myelin-weighted sMRI signals to reveal structure. When comparing sMRI markers to functional MRI in response to moving stimuli, a region of high myelin signal was generally located within the hMT+ complex. However, there were considerable differences in the alignment of structural and functional markers between individuals. Our results suggest that variation in area identification for hMT+ based on structural and functional markers reflects individual differences in human regional brain architecture. PMID:27371764

A phenome-wide examination of neural and cognitive function.

PubMed

Poldrack, R A; Congdon, E; Triplett, W; Gorgolewski, K J; Karlsgodt, K H; Mumford, J A; Sabb, F W; Freimer, N B; London, E D; Cannon, T D; Bilder, R M

2016-12-06

This data descriptor outlines a shared neuroimaging dataset from the UCLA Consortium for Neuropsychiatric Phenomics, which focused on understanding the dimensional structure of memory and cognitive control (response inhibition) functions in both healthy individuals (130 subjects) and individuals with neuropsychiatric disorders including schizophrenia (50 subjects), bipolar disorder (49 subjects), and attention deficit/hyperactivity disorder (43 subjects). The dataset includes an extensive set of task-based fMRI assessments, resting fMRI, structural MRI, and high angular resolution diffusion MRI. The dataset is shared through the OpenfMRI project, and is formatted according to the Brain Imaging Data Structure (BIDS) standard.

Complementary aspects of diffusion imaging and fMRI; I: structure and function.

PubMed

Mulkern, Robert V; Davis, Peter E; Haker, Steven J; Estepar, Raul San Jose; Panych, Lawrence P; Maier, Stephan E; Rivkin, Michael J

2006-05-01

Studying the intersection of brain structure and function is an important aspect of modern neuroscience. The development of magnetic resonance imaging (MRI) over the last 25 years has provided new and powerful tools for the study of brain structure and function. Two tools in particular, diffusion imaging and functional MRI (fMRI), are playing increasingly important roles in elucidating the complementary aspects of brain structure and function. In this work, we review basic technical features of diffusion imaging and fMRI for studying the integrity of white matter structural components and for determining the location and extent of cortical activation in gray matter, respectively. We then review a growing body of literature in which the complementary aspects of diffusion imaging and fMRI, applied as separate examinations but analyzed in tandem, have been exploited to enhance our knowledge of brain structure and function.

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.

Development and application of pulmonary structure-function registration methods: towards pulmonary image-guidance tools for improved airway targeted therapies and outcomes

NASA Astrophysics Data System (ADS)

Guo, Fumin; Pike, Damien; Svenningsen, Sarah; Coxson, Harvey O.; Drozd, John J.; Yuan, Jing; Fenster, Aaron; Parraga, Grace

2014-03-01

Objectives: We aimed to develop a way to rapidly generate multi-modality (MRI-CT) pulmonary imaging structurefunction maps using novel non-rigid image registration methods. This objective is part of our overarching goal to provide an image processing pipeline to generate pulmonary structure-function maps and guide airway-targeted therapies. Methods: Anatomical 1H and functional 3He MRI were acquired in 5 healthy asymptomatic ex-smokers and 7 ex-smokers with chronic obstructive pulmonary disease (COPD) at inspiration breath-hold. Thoracic CT was performed within ten minutes of MRI using the same breath-hold volume. Landmark-based affine registration methods previously validated for imaging of COPD, was based on corresponding fiducial markers located in both CT and 1H MRI coronal slices and compared with shape-based CT-MRI non-rigid registration. Shape-based CT-MRI registration was developed by first identifying the shapes of the lung cavities manually, and then registering the two shapes using affine and thin-plate spline algorithms. We compared registration accuracy using the fiducial localization error (FLE) and target registration error (TRE). Results: For landmark-based registration, the TRE was 8.4±5.3 mm for whole lung and 7.8±4.6 mm for the R and L lungs registered independently (p=0.4). For shape-based registration, the TRE was 8.0±4.6 mm for whole lung as compared to 6.9±4.4 mm for the R and L lung registered independently and this difference was significant (p=0.01). The difference for shape-based (6.9±4.4 mm) and landmark-based R and L lung registration (7.8±4.6 mm) was also significant (p=.04) Conclusion: Shape-based registration TRE was significantly improved compared to landmark-based registration when considering L and R lungs independently.

Joint multi-object registration and segmentation of left and right cardiac ventricles in 4D cine MRI

NASA Astrophysics Data System (ADS)

Ehrhardt, Jan; Kepp, Timo; Schmidt-Richberg, Alexander; Handels, Heinz

2014-03-01

The diagnosis of cardiac function based on cine MRI requires the segmentation of cardiac structures in the images, but the problem of automatic cardiac segmentation is still open, due to the imaging characteristics of cardiac MR images and the anatomical variability of the heart. In this paper, we present a variational framework for joint segmentation and registration of multiple structures of the heart. To enable the simultaneous segmentation and registration of multiple objects, a shape prior term is introduced into a region competition approach for multi-object level set segmentation. The proposed algorithm is applied for simultaneous segmentation of the myocardium as well as the left and right ventricular blood pool in short axis cine MRI images. Two experiments are performed: first, intra-patient 4D segmentation with a given initial segmentation for one time-point in a 4D sequence, and second, a multi-atlas segmentation strategy is applied to unseen patient data. Evaluation of segmentation accuracy is done by overlap coefficients and surface distances. An evaluation based on clinical 4D cine MRI images of 25 patients shows the benefit of the combined approach compared to sole registration and sole segmentation.

Segmentation of knee MRI using structure enhanced local phase filtering

NASA Astrophysics Data System (ADS)

Lim, Mikhiel; Hacihaliloglu, Ilker

2016-03-01

The segmentation of bone surfaces from magnetic resonance imaging (MRI) data has applications in the quanti- tative measurement of knee osteoarthritis, surgery planning for patient specific total knee arthroplasty and its subsequent fabrication of artificial implants. However, due to the problems associated with MRI imaging such as low contrast between bone and surrounding tissues, noise, bias fields, and the partial volume effect, segmentation of bone surfaces continues to be a challenging operation. In this paper, a new framework is presented for the enhancement of knee MRI scans prior to segmentation in order to obtain high contrast bone images. During the first stage, a new contrast enhanced relative total variation (RTV) regularization method is used in order to remove textural noise from the bone structures and surrounding soft tissue interface. This salient bone edge information is further enhanced using a sparse gradient counting method based on L0 gradient minimization, which globally controls how many non-zero gradients are resulted in order to approximate prominent bone structures in a structure-sparsity-management manner. The last stage of the framework involves incorporation of local phase bone boundary information in order to provide an intensity invariant enhancement of contrast between the bone and surrounding soft tissue. The enhanced images are segmented using a fast random walker algorithm. Validation against expert segmentation was performed on 10 clinical knee MRI images, and achieved a mean dice similarity coefficient (DSC) of 0.975.

Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging☆

PubMed Central

Oishi, Kenichi; Faria, Andreia V.; Yoshida, Shoko; Chang, Linda; Mori, Susumu

2013-01-01

The development of the brain is structure-specific, and the growth rate of each structure differs depending on the age of the subject. Magnetic resonance imaging (MRI) is often used to evaluate brain development because of the high spatial resolution and contrast that enable the observation of structure-specific developmental status. Currently, most clinical MRIs are evaluated qualitatively to assist in the clinical decision-making and diagnosis. The clinical MRI report usually does not provide quantitative values that can be used to monitor developmental status. Recently, the importance of image quantification to detect and evaluate mild-to-moderate anatomical abnormalities has been emphasized because these alterations are possibly related to several psychiatric disorders and learning disabilities. In the research arena, structural MRI and diffusion tensor imaging (DTI) have been widely applied to quantify brain development of the pediatric population. To interpret the values from these MR modalities, a “growth percentile chart,” which describes the mean and standard deviation of the normal developmental curve for each anatomical structure, is required. Although efforts have been made to create such a growth percentile chart based on MRI and DTI, one of the greatest challenges is to standardize the anatomical boundaries of the measured anatomical structures. To avoid inter- and intra-reader variability about the anatomical boundary definition, and hence, to increase the precision of quantitative measurements, an automated structure parcellation method, customized for the neonatal and pediatric population, has been developed. This method enables quantification of multiple MR modalities using a common analytic framework. In this paper, the attempt to create an MRI- and a DTI-based growth percentile chart, followed by an application to investigate developmental abnormalities related to cerebral palsy, Williams syndrome, and Rett syndrome, have been introduced. Future directions include multimodal image analysis and personalization for clinical application. PMID:23796902

MRI and PET Compatible Bed for Direct Co-Registration in Small Animals

NASA Astrophysics Data System (ADS)

Bartoli, Antonietta; Esposito, Giovanna; D'Angeli, Luca; Chaabane, Linda; Terreno, Enzo

2013-06-01

To obtain an accurate co-registration with stand-alone PET and MRI scanners, we developed a compatible bed system for mice and rats that enables both images to be acquired without repositioning the animals. MRI acquisitions were performed on a preclinical 7T scanner (Pharmascan, Bruker), whereas PET scans were acquired on a YAP-(S)PET (ISE s.r.l.). The bed performance was tested both on a phantom (NEMA Image Quality phantom) and in vivo (healthy rats and mice brain). Fiducial markers filled up with a drop of 18 F were visible in both modalities. Co-registration process was performed using the point-based registration technique. The reproducibility and accuracy of the co-registration were assessed using the phantom. The reproducibility of the translation distances was 0.2 mm along the z axis. On the other hand, the accuracy depended on the physical size of the phantom structures under investigation but was always lower than 4%. Regions of Interest (ROIs) drawn on the fused images were used for quantification purposes. PET and MRI intensity profiles on small structures of the phantom showed that the underestimation in activity concentration reached 90% in regions that were smaller than the PET spatial resolution, while the MRI allowed a good visualization of the 1 mm 0 rod. PET/MRI images of healthy mice and rats highlighted the expected superior capability of MRI to define brain structures. The simplicity of our developed MRI/PET compatible bed and the quality of the fused images obtained offers a promising opportunity for a future preclinical translation, particularly for neuroimaging studies.

Magnetic resonance imaging based clinical research in Alzheimer's disease.

PubMed

Fayed, Nicolás; Modrego, Pedro J; Salinas, Gulillermo Rojas; Gazulla, José

2012-01-01

Alzheimer's disease (AD) is the most common cause of dementia in elderly people in western countries. However important goals are unmet in the issue of early diagnosis and the development of new drugs for treatment. Magnetic resonance imaging (MRI) and volumetry of the medial temporal lobe structures are useful tools for diagnosis. Positron emission tomography is one of the most sensitive tests for making an early diagnosis of AD but the cost and limited availability are important caveats for its utilization. The importance of magnetic resonance techniques has increased gradually to the extent that most clinical works based on AD use these techniques as the main aid to diagnosis. However, the accuracy of structural MRI as biomarker of early AD generally reaches an accuracy of 80%, so additional biomarkers should be used to improve predictions. Other structural MRI (diffusion weighted, diffusion-tensor MRI) and functional MRI have also added interesting contribution to the understanding of the pathophysiology of AD. Magnetic resonance spectroscopy has proven useful to monitor progression and response to treatment in AD, as well as a biomarker of early AD in mild cognitive impairment.

[Imaging anatomy of cranial nerves].

PubMed

Hermier, M; Leal, P R L; Salaris, S F; Froment, J-C; Sindou, M

2009-04-01

Knowledge of the anatomy of the cranial nerves is mandatory for optimal radiological exploration and interpretation of the images in normal and pathological conditions. CT is the method of choice for the study of the skull base and its foramina. MRI explores the cranial nerves and their vascular relationships precisely. Because of their small size, it is essential to obtain images with high spatial resolution. The MRI sequences optimize contrast between nerves and surrounding structures (cerebrospinal fluid, fat, bone structures and vessels). This chapter discusses the radiological anatomy of the cranial nerves.

Advances in Monitoring Cell-Based Therapies with Magnetic Resonance Imaging: Future Perspectives

PubMed Central

Ngen, Ethel J.; Artemov, Dmitri

2017-01-01

Cell-based therapies are currently being developed for applications in both regenerative medicine and in oncology. Preclinical, translational, and clinical research on cell-based therapies will benefit tremendously from novel imaging approaches that enable the effective monitoring of the delivery, survival, migration, biodistribution, and integration of transplanted cells. Magnetic resonance imaging (MRI) offers several advantages over other imaging modalities for elucidating the fate of transplanted cells both preclinically and clinically. These advantages include the ability to image transplanted cells longitudinally at high spatial resolution without exposure to ionizing radiation, and the possibility to co-register anatomical structures with molecular processes and functional changes. However, since cellular MRI is still in its infancy, it currently faces a number of challenges, which provide avenues for future research and development. In this review, we describe the basic principle of cell-tracking with MRI; explain the different approaches currently used to monitor cell-based therapies; describe currently available MRI contrast generation mechanisms and strategies for monitoring transplanted cells; discuss some of the challenges in tracking transplanted cells; and suggest future research directions. PMID:28106829

Structural brain changes versus self-report: machine-learning classification of chronic fatigue syndrome patients.

PubMed

Sevel, Landrew S; Boissoneault, Jeff; Letzen, Janelle E; Robinson, Michael E; Staud, Roland

2018-05-30

Chronic fatigue syndrome (CFS) is a disorder associated with fatigue, pain, and structural/functional abnormalities seen during magnetic resonance brain imaging (MRI). Therefore, we evaluated the performance of structural MRI (sMRI) abnormalities in the classification of CFS patients versus healthy controls and compared it to machine learning (ML) classification based upon self-report (SR). Participants included 18 CFS patients and 15 healthy controls (HC). All subjects underwent T1-weighted sMRI and provided visual analogue-scale ratings of fatigue, pain intensity, anxiety, depression, anger, and sleep quality. sMRI data were segmented using FreeSurfer and 61 regions based on functional and structural abnormalities previously reported in patients with CFS. Classification was performed in RapidMiner using a linear support vector machine and bootstrap optimism correction. We compared ML classifiers based on (1) 61 a priori sMRI regional estimates and (2) SR ratings. The sMRI model achieved 79.58% classification accuracy. The SR (accuracy = 95.95%) outperformed both sMRI models. Estimates from multiple brain areas related to cognition, emotion, and memory contributed strongly to group classification. This is the first ML-based group classification of CFS. Our findings suggest that sMRI abnormalities are useful for discriminating CFS patients from HC, but SR ratings remain most effective in classification tasks.

A spatiotemporal-based scheme for efficient registration-based segmentation of thoracic 4-D MRI.

PubMed

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

2014-05-01

Dynamic three-dimensional (3-D) (four-dimensional, 4-D) magnetic resonance (MR) imaging is gaining importance in the study of pulmonary motion for respiratory diseases and pulmonary tumor motion for radiotherapy. To perform quantitative analysis using 4-D MR images, segmentation of anatomical structures such as the lung and pulmonary tumor is required. Manual segmentation of entire thoracic 4-D MRI data that typically contains many 3-D volumes acquired over several breathing cycles is extremely tedious, time consuming, and suffers high user variability. This requires the development of new automated segmentation schemes for 4-D MRI data segmentation. Registration-based segmentation technique that uses automatic registration methods for segmentation has been shown to be an accurate method to segment structures for 4-D data series. However, directly applying registration-based segmentation to segment 4-D MRI series lacks efficiency. Here we propose an automated 4-D registration-based segmentation scheme that is based on spatiotemporal information for the segmentation of thoracic 4-D MR lung images. The proposed scheme saved up to 95% of computation amount while achieving comparable accurate segmentations compared to directly applying registration-based segmentation to 4-D dataset. The scheme facilitates rapid 3-D/4-D visualization of the lung and tumor motion and potentially the tracking of tumor during radiation delivery.

More IMPATIENT: A Gridding-Accelerated Toeplitz-based Strategy for Non-Cartesian High-Resolution 3D MRI on GPUs

PubMed Central

Gai, Jiading; Obeid, Nady; Holtrop, Joseph L.; Wu, Xiao-Long; Lam, Fan; Fu, Maojing; Haldar, Justin P.; Hwu, Wen-mei W.; Liang, Zhi-Pei; Sutton, Bradley P.

2013-01-01

Several recent methods have been proposed to obtain significant speed-ups in MRI image reconstruction by leveraging the computational power of GPUs. Previously, we implemented a GPU-based image reconstruction technique called the Illinois Massively Parallel Acquisition Toolkit for Image reconstruction with ENhanced Throughput in MRI (IMPATIENT MRI) for reconstructing data collected along arbitrary 3D trajectories. In this paper, we improve IMPATIENT by removing computational bottlenecks by using a gridding approach to accelerate the computation of various data structures needed by the previous routine. Further, we enhance the routine with capabilities for off-resonance correction and multi-sensor parallel imaging reconstruction. Through implementation of optimized gridding into our iterative reconstruction scheme, speed-ups of more than a factor of 200 are provided in the improved GPU implementation compared to the previous accelerated GPU code. PMID:23682203

Automated Quality Assessment of Structural Magnetic Resonance Brain Images Based on a Supervised Machine Learning Algorithm.

PubMed

Pizarro, Ricardo A; Cheng, Xi; Barnett, Alan; Lemaitre, Herve; Verchinski, Beth A; Goldman, Aaron L; Xiao, Ena; Luo, Qian; Berman, Karen F; Callicott, Joseph H; Weinberger, Daniel R; Mattay, Venkata S

2016-01-01

High-resolution three-dimensional magnetic resonance imaging (3D-MRI) is being increasingly used to delineate morphological changes underlying neuropsychiatric disorders. Unfortunately, artifacts frequently compromise the utility of 3D-MRI yielding irreproducible results, from both type I and type II errors. It is therefore critical to screen 3D-MRIs for artifacts before use. Currently, quality assessment involves slice-wise visual inspection of 3D-MRI volumes, a procedure that is both subjective and time consuming. Automating the quality rating of 3D-MRI could improve the efficiency and reproducibility of the procedure. The present study is one of the first efforts to apply a support vector machine (SVM) algorithm in the quality assessment of structural brain images, using global and region of interest (ROI) automated image quality features developed in-house. SVM is a supervised machine-learning algorithm that can predict the category of test datasets based on the knowledge acquired from a learning dataset. The performance (accuracy) of the automated SVM approach was assessed, by comparing the SVM-predicted quality labels to investigator-determined quality labels. The accuracy for classifying 1457 3D-MRI volumes from our database using the SVM approach is around 80%. These results are promising and illustrate the possibility of using SVM as an automated quality assessment tool for 3D-MRI.

Tensor-product kernel-based representation encoding joint MRI view similarity.

PubMed

Alvarez-Meza, A; Cardenas-Pena, D; Castro-Ospina, A E; Alvarez, M; Castellanos-Dominguez, G

2014-01-01

To support 3D magnetic resonance image (MRI) analysis, a marginal image similarity (MIS) matrix holding MR inter-slice relationship along every axis view (Axial, Coronal, and Sagittal) can be estimated. However, mutual inference from MIS view information poses a difficult task since relationships between axes are nonlinear. To overcome this issue, we introduce a Tensor-Product Kernel-based Representation (TKR) that allows encoding brain structure patterns due to patient differences, gathering all MIS matrices into a single joint image similarity framework. The TKR training strategy is carried out into a low dimensional projected space to get less influence of voxel-derived noise. Obtained results for classifying the considered patient categories (gender and age) on real MRI database shows that the proposed TKR training approach outperforms the conventional voxel-wise sum of squared differences. The proposed approach may be useful to support MRI clustering and similarity inference tasks, which are required on template-based image segmentation and atlas construction.

Magnetic resonance imaging. Application to family practice.

PubMed

Goh, R H; Somers, S; Jurriaans, E; Yu, J

1999-09-01

To review indications, contraindications, and risks of using magnetic resonance imaging (MRI) in order to help primary care physicians refer patients appropriately for MRI, screen for contraindications to using MRI, and educate patients about MRI. Recommendations are based on classic textbooks, the policies of our MRI group, and a literature search using MEDLINE with the MeSH headings magnetic resonance imaging, brain, musculoskeletal, and spine. The search was limited to human, English-language, and review articles. Evidence in favour of using MRI for imaging the head, spine, and joints is well established. For cardiac, abdominal, and pelvic conditions, MRI has been shown useful for certain indications, usually to complement other modalities. For demonstrating soft tissue conditions, MRI is better than computed tomography (CT), but CT shows bone and acute bleeding better. Therefore, patients with trauma or suspected intracranial bleeding should have CT. Tumours, congenital abnormalities, vascular structures, and the cervical or thoracic spine show better on MRI. Either modality can be used for lower back pain. Cardiac, abdominal, and pelvic abnormalities should be imaged with ultrasound or CT before MRI. Contraindications for MRI are mainly metallic implants or shrapnel, severe claustrophobia, or obesity. With the increasing availability of MRI scanners in Canada, better understanding of the indications, contraindications, and risks will be helpful for family physicians and their patients.

The Utility of Magnetic Resonance Imaging in Assessing Patients With Pituitary Tumors Compressing the Anterior Visual Pathway.

PubMed

Ryu, Won Hyung A; Starreveld, Yves; Burton, Jodie M; Liu, Junjie; Costello, Fiona

2017-09-01

Pituitary tumors are one of the most common types of intracranial neoplasms, and can cause progressive visual loss. An ongoing challenge in the management of patients with pituitary tumors is the cost, availability, and reliability of current magnetic resonance imaging (MRI) techniques to capture clinically significant incremental tumor growth. The purpose of this study was to evaluate the various MRI-based structural analyses and to explore the relationship between measures of structure and function in the afferent visual pathway of patients with pituitary tumors. We performed a critical review of literature on MRI-based structural analyses of pituitary adenomas using PubMed, Embase, Cochrane Library, and Google Scholar. In addition, preoperative structural characteristics of the optic apparatus, optic nerve compression, and optic chiasm elevation identified as important in the literature review, were examined in 18 of our patients from October 2010 to January 2014. In our review of literature, a total of 443 citations were obtained from our search strategy and review of bibliographies. Eight of these studies met inclusion/exclusion criteria and were retrieved for critical review. Of the 8 included studies, only 2 studies examined the relationship between MRI-based structural measurements and postoperative visual recovery. In our small case-series, MRI analysis of chiasm elevation, severity of optic nerve compression, chiasm position, height of chiasm, tumor height, and tumor volume failed to differentiate patients with postoperative visual dysfunction vs those with visual recovery (P > 0.05). Although MRI-based structural analysis is an important and useful tool for managing patients with pituitary tumors, there are limited objective measures shown to be predictive of postoperative visual recovery.

Magnetic resonance imaging of the inner ear by using a hybrid radiofrequency coil at 7 T

NASA Astrophysics Data System (ADS)

Kim, Kyoung-Nam; Heo, Phil; Kim, Young-Bo; Han, Gyu-Cheol

2015-01-01

Visualization of the membranous structures of the inner ear has been limited to the detection of the normal fluid signal intensity within the bony labyrinth by using magnetic resonance imaging (MRI) equipped with a 1.5 Tesla (T) magnet. High-field (HF) MRI has been available for more than a decade, and numerous studies have documented its significant advantages over conventional MRI with regards to its use in basic scientific research and routine clinical assessments. No previous studies of the inner ear by using HF MRI have been reported, in part because high-quality resolution of mastoid pneumatization is challenging due to artifacts generated in the HF environment and insufficient performance of radiofrequency (RF) coils. Therefore, a hybrid RF coil with integrated circuitry was developed at 7 T and was targeted for anatomical imaging to achieve a high resolution image of the structure of the human inner ear, excluding the bony portion. The inner-ear's structure is composed of soft tissues containing hydrogen ions and includes the membranous labyrinth, endolymphatic space, perilymphatic space, and cochlear-vestibular nerves. Visualization of the inner-ear's anatomy was performed in-vivo with a custom-designed hybrid RF coil and a specific imaging protocol based on an interpolated breath-held examination sequence. The comparative signal intensity value at 30-mm away from the phantom side was 88% higher for the hybrid RF coil and 24% higher for the 8-channel transmit/receive (Tx/Rx) coil than for the commercial birdcage coil. The optimized MRI protocol employed a hybrid RF coil because it enabled high-resolution imaging of the inner-ear's anatomy and accurate mapping of structures including the cochlea and the semicircular canals. These results indicate that 7 T MRI achieves high spatial resolution visualization of the inner-ear's anatomy. Therefore, MRI imaging using a hybrid RF coil at 7 T could provide a powerful tool for clinical investigations of petrous pathologies of the inner ear.

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.

Pushing the sensitivity envelope of lanthanide-based magnetic resonance imaging (MRI) contrast agents for molecular imaging applications.

PubMed

Aime, Silvio; Castelli, Daniela Delli; Crich, Simonetta Geninatti; Gianolio, Eliana; Terreno, Enzo

2009-07-21

Contrast in magnetic resonance imaging (MRI) arises from changes in the intensity of the proton signal of water between voxels (essentially, the 3D counterpart of pixels). Differences in intervoxel intensity can be significantly enhanced with chemicals that alter the nuclear magnetic resonance (NMR) intensity of the imaged spins; this alteration can occur by various mechanisms. Paramagnetic lanthanide(III) complexes are used in two major classes of MRI contrast agent: the well-established class of Gd-based agents and the emerging class of chemical exchange saturation transfer (CEST) agents. A Gd-based complex increases water signal by enhancing the longitudinal relaxation rate of water protons, whereas CEST agents decrease water signal as a consequence of the transfer of saturated magnetization from the exchangeable protons of the agent. In this Account, we survey recent progress in both areas, focusing on how MRI is becoming a more competitive choice among the various molecular imaging methods. Compared with other imaging modalities, MRI is set apart by its superb anatomical resolution; however, its success in molecular imaging suffers because of its intrinsic insensitivity. A relatively high concentration of molecular agents (0.01-0.1 mM) is necessary to produce a local alteration in the water signal intensity. Unfortunately, the most desirable molecules for visualization in molecular imaging are present at much lower concentrations, in the nano- or picomolar range. Therefore, augmenting the sensitivity of MRI agents is key to the development of MR-based molecular imaging applications. In principle, this task can be tackled either by increasing the sensitivity of the reporting units, through the optimization of their structural and dynamic properties, or by setting up proper amplification strategies that allow the accumulation of a huge number of imaging reporters at the site of interest. For Gd-based agents, high sensitivities can be attained by exploiting a range of nanosized carriers (micelles, liposomes, microemulsions, and the like, as well as biological structures such as apoferritin and lipoproteins) properly loaded with Gd-based chelates. Furthermore, the sensitivity of Gd-based agents can be markedly affected either by their interactions with biological structures or by their cellular localization. For CEST agents, a huge sensitivity enhancement has been obtained by using the water molecules contained in the inner cavity of liposomes as the exchangeable source of protons for magnetization transfer. Several "tricks" (for example, the use of multimeric lanthanide(III) shift reagents, changes in the shape of the liposome container, and so forth) have been devised to improve the chemical shift separation between the intraliposomal water and the "bulk" water resonances. Overall, excellent sensitivity enhancements have been obtained for both classes of agents, enabling their use in MR molecular imaging applications.

Magnetic resonance imaging and image analysis for assessment of HPMC matrix tablets structural evolution in USP Apparatus 4.

PubMed

Kulinowski, Piotr; Dorożyński, Przemysław; Młynarczyk, Anna; Węglarz, Władysław P

2011-05-01

The purpose of the study was to present a methodology for the processing of Magnetic Resonance Imaging (MRI) data for the quantification of the dosage form matrix evolution during drug dissolution. The results of the study were verified by comparison with other approaches presented in literature. A commercially available, HPMC-based quetiapine fumarate tablet was studied with a 4.7T MR system. Imaging was performed inside an MRI probe-head coupled with a flow-through cell for 12 h in circulating water. The images were segmented into three regions using threshold-based segmentation algorithms due to trimodal structure of the image intensity histograms. Temporal evolution of dry glassy, swollen glassy and gel regions was monitored. The characteristic features were observed: initial high expansion rate of the swollen glassy and gel layers due to initial water uptake, dry glassy core disappearance and maximum area of swollen glassy region at 4 h, and subsequent gel layer thickness increase at the expense of swollen glassy layer. The temporal evolution of an HPMC-based tablet by means of noninvasive MRI integrated with USP Apparatus 4 was found to be consistent with both the theoretical model based on polymer disentanglement concentration and experimental VIS/FTIR studies.

Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation

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

Akhbardeh, Alireza; Jacobs, Michael A.; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205

2012-04-15

Purpose: Visualization of anatomical structures using radiological imaging methods is an important tool in medicine to differentiate normal from pathological tissue and can generate large amounts of data for a radiologist to read. Integrating these large data sets is difficult and time-consuming. A new approach uses both supervised and unsupervised advanced machine learning techniques to visualize and segment radiological data. This study describes the application of a novel hybrid scheme, based on combining wavelet transform and nonlinear dimensionality reduction (NLDR) methods, to breast magnetic resonance imaging (MRI) data using three well-established NLDR techniques, namely, ISOMAP, local linear embedding (LLE), andmore » diffusion maps (DfM), to perform a comparative performance analysis. Methods: Twenty-five breast lesion subjects were scanned using a 3T scanner. MRI sequences used were T1-weighted, T2-weighted, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging. The hybrid scheme consisted of two steps: preprocessing and postprocessing of the data. The preprocessing step was applied for B{sub 1} inhomogeneity correction, image registration, and wavelet-based image compression to match and denoise the data. In the postprocessing step, MRI parameters were considered data dimensions and the NLDR-based hybrid approach was applied to integrate the MRI parameters into a single image, termed the embedded image. This was achieved by mapping all pixel intensities from the higher dimension to a lower dimensional (embedded) space. For validation, the authors compared the hybrid NLDR with linear methods of principal component analysis (PCA) and multidimensional scaling (MDS) using synthetic data. For the clinical application, the authors used breast MRI data, comparison was performed using the postcontrast DCE MRI image and evaluating the congruence of the segmented lesions. Results: The NLDR-based hybrid approach was able to define and segment both synthetic and clinical data. In the synthetic data, the authors demonstrated the performance of the NLDR method compared with conventional linear DR methods. The NLDR approach enabled successful segmentation of the structures, whereas, in most cases, PCA and MDS failed. The NLDR approach was able to segment different breast tissue types with a high accuracy and the embedded image of the breast MRI data demonstrated fuzzy boundaries between the different types of breast tissue, i.e., fatty, glandular, and tissue with lesions (>86%). Conclusions: The proposed hybrid NLDR methods were able to segment clinical breast data with a high accuracy and construct an embedded image that visualized the contribution of different radiological parameters.« less

Multi-atlas-based CT synthesis from conventional MRI with patch-based refinement for MRI-based radiotherapy planning

NASA Astrophysics Data System (ADS)

Lee, Junghoon; Carass, Aaron; Jog, Amod; Zhao, Can; Prince, Jerry L.

2017-02-01

Accurate CT synthesis, sometimes called electron density estimation, from MRI is crucial for successful MRI-based radiotherapy planning and dose computation. Existing CT synthesis methods are able to synthesize normal tissues but are unable to accurately synthesize abnormal tissues (i.e., tumor), thus providing a suboptimal solution. We propose a multiatlas- based hybrid synthesis approach that combines multi-atlas registration and patch-based synthesis to accurately synthesize both normal and abnormal tissues. Multi-parametric atlas MR images are registered to the target MR images by multi-channel deformable registration, from which the atlas CT images are deformed and fused by locally-weighted averaging using a structural similarity measure (SSIM). Synthetic MR images are also computed from the registered atlas MRIs by using the same weights used for the CT synthesis; these are compared to the target patient MRIs allowing for the assessment of the CT synthesis fidelity. Poor synthesis regions are automatically detected based on the fidelity measure and refined by a patch-based synthesis. The proposed approach was tested on brain cancer patient data, and showed a noticeable improvement for the tumor region.

Multi-atlas-based CT synthesis from conventional MRI with patch-based refinement for MRI-based radiotherapy planning.

PubMed

Lee, Junghoon; Carass, Aaron; Jog, Amod; Zhao, Can; Prince, Jerry L

2017-02-01

Accurate CT synthesis, sometimes called electron density estimation, from MRI is crucial for successful MRI-based radiotherapy planning and dose computation. Existing CT synthesis methods are able to synthesize normal tissues but are unable to accurately synthesize abnormal tissues (i.e., tumor), thus providing a suboptimal solution. We propose a multi-atlas-based hybrid synthesis approach that combines multi-atlas registration and patch-based synthesis to accurately synthesize both normal and abnormal tissues. Multi-parametric atlas MR images are registered to the target MR images by multi-channel deformable registration, from which the atlas CT images are deformed and fused by locally-weighted averaging using a structural similarity measure (SSIM). Synthetic MR images are also computed from the registered atlas MRIs by using the same weights used for the CT synthesis; these are compared to the target patient MRIs allowing for the assessment of the CT synthesis fidelity. Poor synthesis regions are automatically detected based on the fidelity measure and refined by a patch-based synthesis. The proposed approach was tested on brain cancer patient data, and showed a noticeable improvement for the tumor region.

PCA-based groupwise image registration for quantitative MRI.

PubMed

Huizinga, W; Poot, D H J; Guyader, J-M; Klaassen, R; Coolen, B F; van Kranenburg, M; van Geuns, R J M; Uitterdijk, A; Polfliet, M; Vandemeulebroucke, J; Leemans, A; Niessen, W J; Klein, S

2016-04-01

Quantitative magnetic resonance imaging (qMRI) is a technique for estimating quantitative tissue properties, such as the T1 and T2 relaxation times, apparent diffusion coefficient (ADC), and various perfusion measures. This estimation is achieved by acquiring multiple images with different acquisition parameters (or at multiple time points after injection of a contrast agent) and by fitting a qMRI signal model to the image intensities. Image registration is often necessary to compensate for misalignments due to subject motion and/or geometric distortions caused by the acquisition. However, large differences in image appearance make accurate image registration challenging. In this work, we propose a groupwise image registration method for compensating misalignment in qMRI. The groupwise formulation of the method eliminates the requirement of choosing a reference image, thus avoiding a registration bias. The method minimizes a cost function that is based on principal component analysis (PCA), exploiting the fact that intensity changes in qMRI can be described by a low-dimensional signal model, but not requiring knowledge on the specific acquisition model. The method was evaluated on 4D CT data of the lungs, and both real and synthetic images of five different qMRI applications: T1 mapping in a porcine heart, combined T1 and T2 mapping in carotid arteries, ADC mapping in the abdomen, diffusion tensor mapping in the brain, and dynamic contrast-enhanced mapping in the abdomen. Each application is based on a different acquisition model. The method is compared to a mutual information-based pairwise registration method and four other state-of-the-art groupwise registration methods. Registration accuracy is evaluated in terms of the precision of the estimated qMRI parameters, overlap of segmented structures, distance between corresponding landmarks, and smoothness of the deformation. In all qMRI applications the proposed method performed better than or equally well as competing methods, while avoiding the need to choose a reference image. It is also shown that the results of the conventional pairwise approach do depend on the choice of this reference image. We therefore conclude that our groupwise registration method with a similarity measure based on PCA is the preferred technique for compensating misalignments in qMRI. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Magnetic resonance imaging of mass transport and structure inside a phototrophic biofilm.

PubMed

Ramanan, Baheerathan; Holmes, William M; Sloan, William T; Phoenix, Vernon R

2013-05-01

The aim of this study was to utilize magnetic resonance imaging (MRI) to image structural heterogeneity and mass transport inside a biofilm which was too thick for photon based imaging. MRI was used to map water diffusion and image the transport of the paramagnetically tagged macromolecule, Gd-DTPA, inside a 2.5 mm thick cyanobacterial biofilm. The structural heterogeneity of the biofilm was imaged at resolutions down to 22 × 22 μm, enabling the impact of biofilm architecture on the mass transport of both water and Gd-DTPA to be investigated. Higher density areas of the biofilm correlated with areas exhibiting lower relative water diffusion coefficients and slower transport of Gd-DTPA, highlighting the impact of biofilm structure on mass transport phenomena. This approach has potential for shedding light on heterogeneous mass transport of a range of molecular mass molecules in biofilms.

Advances in the application of MRI to amyotrophic lateral sclerosis

PubMed Central

Turner, Martin R; Modo, Michel

2011-01-01

Importance of the field With the emergence of therapeutic candidates for the incurable and rapidly progressive neurodegenerative condition of amyotrophic lateral sclerosis (ALS), it will be essential to develop easily obtainable biomarkers for diagnosis, as well as monitoring, in a disease where clinical examination remains the predominant diagnostic tool. Magnetic resonance imaging (MRI) has greatly developed over the past thirty years since its initial introduction to neuroscience. With multi-modal applications, MRI is now offering exciting opportunities to develop practical biomarkers in ALS. Areas covered in this review The historical application of MRI to the field of ALS, its state-of-the-art and future aspirations will be reviewed. Specifically, the significance and limitations of structural MRI to detect gross morphological tissue changes in relation to clinical presentation will be discussed. The more recent application of diffusion tensor imaging (DTI), magnetic resonance spectroscopy (MRS), functional and resting-state MRI (fMRI & R-fMRI) will be contrasted in relation to these more conventional MRI assessments. Finally, future aspirations will be sketched out in providing a more disease mechanism-based molecular MRI. What the reader will gain This review will equip the reader with an overview of the application of MRI to ALS and illustrate its potential to develop biomarkers. This discussion is exemplified by key studies, demonstrating the strengths and limitations of each modality. The reader will gain an expert opinion on both the current and future developments of MR imaging in ALS. Take home message MR imaging generates potential diagnostic, prognostic and therapeutic monitoring biomarkers of ALS. The emerging fusion of structural, functional and potentially molecular imaging will improve our understanding of wider cerebral connectivity and holds the promise of biomarkers sensitive to the earliest changes. PMID:21516259

Metamaterial Combining Electric- and Magnetic-Dipole-Based Configurations for Unique Dual-Band Signal Enhancement in Ultrahigh-Field Magnetic Resonance Imaging

PubMed Central

2017-01-01

Magnetic resonance imaging and spectroscopy (MRI and MRS) are both widely used techniques in medical diagnostics and research. One of the major thrusts in recent years has been the introduction of ultrahigh-field magnets in order to boost the sensitivity. Several MRI studies have examined further potential improvements in sensitivity using metamaterials, focusing on single frequency applications. However, metamaterials have yet to reach a level that is practical for routine MRI use. In this work, we explore a new metamaterial implementation for MRI, a dual-nuclei resonant structure, which can be used for both proton and heteronuclear magnetic resonance. Our approach combines two configurations, one based on a set of electric dipoles for the low frequency band, and the second based on a set of magnetic dipoles for the high frequency band. We focus on the implementation of a dual-nuclei metamaterial for phosphorus and proton imaging and spectroscopy at an ultrahigh-field strength of 7 T. In vivo scans using this flexible and compact structure show that it locally enhances both the phosphorus and proton transmit and receive sensitivities. PMID:28901137

Metamaterial Combining Electric- and Magnetic-Dipole-Based Configurations for Unique Dual-Band Signal Enhancement in Ultrahigh-Field Magnetic Resonance Imaging.

PubMed

Schmidt, Rita; Webb, Andrew

2017-10-11

Magnetic resonance imaging and spectroscopy (MRI and MRS) are both widely used techniques in medical diagnostics and research. One of the major thrusts in recent years has been the introduction of ultrahigh-field magnets in order to boost the sensitivity. Several MRI studies have examined further potential improvements in sensitivity using metamaterials, focusing on single frequency applications. However, metamaterials have yet to reach a level that is practical for routine MRI use. In this work, we explore a new metamaterial implementation for MRI, a dual-nuclei resonant structure, which can be used for both proton and heteronuclear magnetic resonance. Our approach combines two configurations, one based on a set of electric dipoles for the low frequency band, and the second based on a set of magnetic dipoles for the high frequency band. We focus on the implementation of a dual-nuclei metamaterial for phosphorus and proton imaging and spectroscopy at an ultrahigh-field strength of 7 T. In vivo scans using this flexible and compact structure show that it locally enhances both the phosphorus and proton transmit and receive sensitivities.

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.

Coregistration of Preoperative MRI with Ex Vivo Mesorectal Pathology Specimens to Spatially Map Post-treatment Changes in Rectal Cancer Onto In Vivo Imaging: Preliminary Findings.

PubMed

Antunes, Jacob; Viswanath, Satish; Brady, Justin T; Crawshaw, Benjamin; Ros, Pablo; Steele, Scott; Delaney, Conor P; Paspulati, Raj; Willis, Joseph; Madabhushi, Anant

2018-07-01

The objective of this study was to develop and quantitatively evaluate a radiology-pathology fusion method for spatially mapping tissue regions corresponding to different chemoradiation therapy-related effects from surgically excised whole-mount rectal cancer histopathology onto preoperative magnetic resonance imaging (MRI). This study included six subjects with rectal cancer treated with chemoradiation therapy who were then imaged with a 3-T T2-weighted MRI sequence, before undergoing mesorectal excision surgery. Excised rectal specimens were sectioned, stained, and digitized as two-dimensional (2D) whole-mount slides. Annotations of residual disease, ulceration, fibrosis, muscularis propria, mucosa, fat, inflammation, and pools of mucin were made by an expert pathologist on digitized slide images. An expert radiologist and pathologist jointly established corresponding 2D sections between MRI and pathology images, as well as identified a total of 10 corresponding landmarks per case (based on visually similar structures) on both modalities (five for driving registration and five for evaluating alignment). We spatially fused the in vivo MRI and ex vivo pathology images using landmark-based registration. This allowed us to spatially map detailed annotations from 2D pathology slides onto corresponding 2D MRI sections. Quantitative assessment of coregistered pathology and MRI sections revealed excellent structural alignment, with an overall deviation of 1.50 ± 0.63 mm across five expert-selected anatomic landmarks (in-plane misalignment of two to three pixels at 0.67- to 1.00-mm spatial resolution). Moreover, the T2-weighted intensity distributions were distinctly different when comparing fibrotic tissue to perirectal fat (as expected), but showed a marked overlap when comparing fibrotic tissue and residual rectal cancer. Our fusion methodology enabled successful and accurate localization of post-treatment effects on in vivo MRI. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Skin age testing criteria: characterization of human skin structures by 500 MHz MRI multiple contrast and image processing.

PubMed

Sharma, Rakesh

2010-07-21

Ex vivo magnetic resonance microimaging (MRM) image characteristics are reported in human skin samples in different age groups. Human excised skin samples were imaged using a custom coil placed inside a 500 MHz NMR imager for high-resolution microimaging. Skin MRI images were processed for characterization of different skin structures. Contiguous cross-sectional T1-weighted 3D spin echo MRI, T2-weighted 3D spin echo MRI and proton density images were compared with skin histopathology and NMR peaks. In all skin specimens, epidermis and dermis thickening and hair follicle size were measured using MRM. Optimized parameters TE and TR and multicontrast enhancement generated better MRI visibility of different skin components. Within high MR signal regions near to the custom coil, MRI images with short echo time were comparable with digitized histological sections for skin structures of the epidermis, dermis and hair follicles in 6 (67%) of the nine specimens. Skin % tissue composition, measurement of the epidermis, dermis, sebaceous gland and hair follicle size, and skin NMR peaks were signatures of skin type. The image processing determined the dimensionality of skin tissue components and skin typing. The ex vivo MRI images and histopathology of the skin may be used to measure the skin structure and skin NMR peaks with image processing may be a tool for determining skin typing and skin composition.

Skin age testing criteria: characterization of human skin structures by 500 MHz MRI multiple contrast and image processing

NASA Astrophysics Data System (ADS)

Sharma, Rakesh

2010-07-01

Ex vivo magnetic resonance microimaging (MRM) image characteristics are reported in human skin samples in different age groups. Human excised skin samples were imaged using a custom coil placed inside a 500 MHz NMR imager for high-resolution microimaging. Skin MRI images were processed for characterization of different skin structures. Contiguous cross-sectional T1-weighted 3D spin echo MRI, T2-weighted 3D spin echo MRI and proton density images were compared with skin histopathology and NMR peaks. In all skin specimens, epidermis and dermis thickening and hair follicle size were measured using MRM. Optimized parameters TE and TR and multicontrast enhancement generated better MRI visibility of different skin components. Within high MR signal regions near to the custom coil, MRI images with short echo time were comparable with digitized histological sections for skin structures of the epidermis, dermis and hair follicles in 6 (67%) of the nine specimens. Skin % tissue composition, measurement of the epidermis, dermis, sebaceous gland and hair follicle size, and skin NMR peaks were signatures of skin type. The image processing determined the dimensionality of skin tissue components and skin typing. The ex vivo MRI images and histopathology of the skin may be used to measure the skin structure and skin NMR peaks with image processing may be a tool for determining skin typing and skin composition.

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.,

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.

MR to CT registration of brains using image synthesis

NASA Astrophysics Data System (ADS)

Roy, Snehashis; Carass, Aaron; Jog, Amod; Prince, Jerry L.; Lee, Junghoon

2014-03-01

Computed tomography (CT) is the preferred imaging modality for patient dose calculation for radiation therapy. Magnetic resonance (MR) imaging (MRI) is used along with CT to identify brain structures due to its superior soft tissue contrast. Registration of MR and CT is necessary for accurate delineation of the tumor and other structures, and is critical in radiotherapy planning. Mutual information (MI) or its variants are typically used as a similarity metric to register MRI to CT. However, unlike CT, MRI intensity does not have an accepted calibrated intensity scale. Therefore, MI-based MR-CT registration may vary from scan to scan as MI depends on the joint histogram of the images. In this paper, we propose a fully automatic framework for MR-CT registration by synthesizing a synthetic CT image from MRI using a co-registered pair of MR and CT images as an atlas. Patches of the subject MRI are matched to the atlas and the synthetic CT patches are estimated in a probabilistic framework. The synthetic CT is registered to the original CT using a deformable registration and the computed deformation is applied to the MRI. In contrast to most existing methods, we do not need any manual intervention such as picking landmarks or regions of interests. The proposed method was validated on ten brain cancer patient cases, showing 25% improvement in MI and correlation between MR and CT images after registration compared to state-of-the-art registration methods.

High Resolution Three-Dimensional MR Imaging of the Skull Base: Compartments, Boundaries, and Critical Structures.

PubMed

Blitz, Ari Meir; Aygun, Nafi; Herzka, Daniel A; Ishii, Masaru; Gallia, Gary L

2017-01-01

High-resolution 3D MRI of the skull base allows for a more detailed and accurate assessment of normal anatomic structures as well as the location and extent of skull base pathologies than has previously been possible. This article describes the techniques employed for high-resolution skull base MRI including pre- and post-contrast constructive interference in the steady state (CISS) imaging and their utility for evaluation of the many small structures of the skull base, focusing on those regions and concepts most pertinent to localization of cranial nerve palsies and in providing pre-operative guidance and post-operative assessment. The concept of skull base compartments as a means of conceptualizing the various layers of the skull base and their importance in assessment of masses of the skull base is discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

Magnetic resonance imaging of the normal bovine digit.

PubMed

Raji, A R; Sardari, K; Mirmahmoob, P

2009-08-01

The purpose of this study was defining the normal structures of the digits and hoof in Holstein dairy cattle using Magnetic Resonance Image (MRI). Transverse, Sagital and Dorsoplantar MRI images of three isolated cattle cadaver digits were obtained using Gyroscan T5-NT a magnet of 0.5 Tesla and T1 Weighted sequence. The MRI images were compared to corresponding frozen cross-sections and dissect specimens of the cadaver digits. Relevant anatomical structures were identified and labeled at each level. The MRI images provided anatomical detail of the digits and hoof in Holstein dairy cattle. Transversal images provided excellent depiction of anatomical structures when compared to corresponding frozen cross-sections. The information presented in this paper would serve as an initial reference to the evaluation of MRI images of the digits and hoof in Holstein dairy cattle, that can be used by radiologist, clinicians, surgeon or for research propose in bovine lameness.

Automatic Segmenting Structures in MRI's Based on Texture Analysis and Fuzzy Logic

NASA Astrophysics Data System (ADS)

Kaur, Mandeep; Rattan, Munish; Singh, Pushpinder

2017-12-01

The purpose of this paper is to present the variational method for geometric contours which helps the level set function remain close to the sign distance function, therefor it remove the need of expensive re-initialization procedure and thus, level set method is applied on magnetic resonance images (MRI) to track the irregularities in them as medical imaging plays a substantial part in the treatment, therapy and diagnosis of various organs, tumors and various abnormalities. It favors the patient with more speedy and decisive disease controlling with lesser side effects. The geometrical shape, the tumor's size and tissue's abnormal growth can be calculated by the segmentation of that particular image. It is still a great challenge for the researchers to tackle with an automatic segmentation in the medical imaging. Based on the texture analysis, different images are processed by optimization of level set segmentation. Traditionally, optimization was manual for every image where each parameter is selected one after another. By applying fuzzy logic, the segmentation of image is correlated based on texture features, to make it automatic and more effective. There is no initialization of parameters and it works like an intelligent system. It segments the different MRI images without tuning the level set parameters and give optimized results for all MRI's.

Dynamic Imaging of the Eye, Optic Nerve, and Extraocular Muscles With Golden Angle Radial MRI

PubMed Central

Smith, David S.; Smith, Alex K.; Welch, E. Brian; Smith, Seth A.

2017-01-01

Purpose The eye and its accessory structures, the optic nerve and the extraocular muscles, form a complex dynamic system. In vivo magnetic resonance imaging (MRI) of this system in motion can have substantial benefits in understanding oculomotor functioning in health and disease, but has been restricted to date to imaging of static gazes only. The purpose of this work was to develop a technique to image the eye and its accessory visual structures in motion. Methods Dynamic imaging of the eye was developed on a 3-Tesla MRI scanner, based on a golden angle radial sequence that allows freely selectable frame-rate and temporal-span image reconstructions from the same acquired data set. Retrospective image reconstructions at a chosen frame rate of 57 ms per image yielded high-quality in vivo movies of various eye motion tasks performed in the scanner. Motion analysis was performed for a left–right version task where motion paths, lengths, and strains/globe angle of the medial and lateral extraocular muscles and the optic nerves were estimated. Results Offline image reconstructions resulted in dynamic images of bilateral visual structures of healthy adults in only ∼15-s imaging time. Qualitative and quantitative analyses of the motion enabled estimation of trajectories, lengths, and strains on the optic nerves and extraocular muscles at very high frame rates of ∼18 frames/s. Conclusions This work presents an MRI technique that enables high-frame-rate dynamic imaging of the eyes and orbital structures. The presented sequence has the potential to be used in furthering the understanding of oculomotor mechanics in vivo, both in health and disease. PMID:28813574

Supervised learning based multimodal MRI brain tumour segmentation using texture features from supervoxels.

PubMed

Soltaninejad, Mohammadreza; Yang, Guang; Lambrou, Tryphon; Allinson, Nigel; Jones, Timothy L; Barrick, Thomas R; Howe, Franklyn A; Ye, Xujiong

2018-04-01

Accurate segmentation of brain tumour in magnetic resonance images (MRI) is a difficult task due to various tumour types. Using information and features from multimodal MRI including structural MRI and isotropic (p) and anisotropic (q) components derived from the diffusion tensor imaging (DTI) may result in a more accurate analysis of brain images. We propose a novel 3D supervoxel based learning method for segmentation of tumour in multimodal MRI brain images (conventional MRI and DTI). Supervoxels are generated using the information across the multimodal MRI dataset. For each supervoxel, a variety of features including histograms of texton descriptor, calculated using a set of Gabor filters with different sizes and orientations, and first order intensity statistical features are extracted. Those features are fed into a random forests (RF) classifier to classify each supervoxel into tumour core, oedema or healthy brain tissue. The method is evaluated on two datasets: 1) Our clinical dataset: 11 multimodal images of patients and 2) BRATS 2013 clinical dataset: 30 multimodal images. For our clinical dataset, the average detection sensitivity of tumour (including tumour core and oedema) using multimodal MRI is 86% with balanced error rate (BER) 7%; while the Dice score for automatic tumour segmentation against ground truth is 0.84. The corresponding results of the BRATS 2013 dataset are 96%, 2% and 0.89, respectively. The method demonstrates promising results in the segmentation of brain tumour. Adding features from multimodal MRI images can largely increase the segmentation accuracy. The method provides a close match to expert delineation across all tumour grades, leading to a faster and more reproducible method of brain tumour detection and delineation to aid patient management. Copyright © 2018 Elsevier B.V. All rights reserved.

Amygdala Volumetry in Patients with Temporal Lobe Epilepsy and Normal Magnetic Resonance Imaging

PubMed Central

Singh, Paramdeep; Kaur, Rupinderjeet; Saggar, Kavita; Singh, Gagandeep; Aggarwal, Simmi

2016-01-01

Summary Background It has been suggested that the pathophysiology of temporal lobe epilepsy may relate to abnormalities in various brain structures, including the amygdala. Patients with mesial temporal lobe epilepsy (MTLE) without MRI abnormalities (MTLE-NMRI) represent a challenge for diagnosis of the underlying abnormality and for presurgical evaluation. To date, however, only few studies have used quantitative structural Magnetic Resonance Imaging-based techniques to examine amygdalar pathology in these patients. Material/Methods Based on clinical examination, 24-hour video EEG recordings and MRI findings, 50 patients with EEG lateralized TLE and normal structural Magnetic Resonance Imaging results were included in this study. Volumetric magnetic resonance imaging (MRI) studies of the amygdalas and hippocampi were conducted in 50 non-epileptic controls (age 7–79 years) and 50 patients with MTLE with normal MRI on a 1.5-Tesla scanner. Visual assessment and amygdalar volumetry were performed on oblique coronal T2W and T1W MP-RAGE images respectively. The T2 relaxation times were measured using the 16-echo Carr-Purcell-Meiboom-Gill sequence (TE, 22–352). Volumetric data were normalized for variation in head size between individuals. Results were assessed by SSPS statistic program. Results Individual manual volumetric analysis confirmed statistically significant amygdala enlargement (AE) in eight (16%) patients. Overall, among all patients with AE and a defined epileptic focus, 7 had predominant increased volume ipsilateral to the epileptic focus. The T2 relaxometry demonstrated no hyperintense signal of the amygdala in any patient with significant AE. Conclusions This paper presented AE in a few patients with TLE and normal MRI. These findings support the hypothesis that there might be a subgroup of patients with MTLE-NMRI in which the enlarged amygdala could be related to the epileptogenic process. PMID:27231493

Interactive local super-resolution reconstruction of whole-body MRI mouse data: a pilot study with applications to bone and kidney metastases.

PubMed

Dzyubachyk, Oleh; Khmelinskii, Artem; Plenge, Esben; Kok, Peter; Snoeks, Thomas J A; Poot, Dirk H J; Löwik, Clemens W G M; Botha, Charl P; Niessen, Wiro J; van der Weerd, Louise; Meijering, Erik; Lelieveldt, Boudewijn P F

2014-01-01

In small animal imaging studies, when the locations of the micro-structures of interest are unknown a priori, there is a simultaneous need for full-body coverage and high resolution. In MRI, additional requirements to image contrast and acquisition time will often make it impossible to acquire such images directly. Recently, a resolution enhancing post-processing technique called super-resolution reconstruction (SRR) has been demonstrated to improve visualization and localization of micro-structures in small animal MRI by combining multiple low-resolution acquisitions. However, when the field-of-view is large relative to the desired voxel size, solving the SRR problem becomes very expensive, in terms of both memory requirements and computation time. In this paper we introduce a novel local approach to SRR that aims to overcome the computational problems and allow researchers to efficiently explore both global and local characteristics in whole-body small animal MRI. The method integrates state-of-the-art image processing techniques from the areas of articulated atlas-based segmentation, planar reformation, and SRR. A proof-of-concept is provided with two case studies involving CT, BLI, and MRI data of bone and kidney tumors in a mouse model. We show that local SRR-MRI is a computationally efficient complementary imaging modality for the precise characterization of tumor metastases, and that the method provides a feasible high-resolution alternative to conventional MRI.

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.

Promise of new imaging technologies for assessing ovarian function.

PubMed

Singh, Jaswant; Adams, Gregg P; Pierson, Roger A

2003-10-15

Advancements in imaging technologies over the last two decades have ushered a quiet revolution in research approaches to the study of ovarian structure and function. The most significant changes in our understanding of the ovary have resulted from the use of ultrasonography which has enabled sequential analyses in live animals. Computer-assisted image analysis and mathematical modeling of the dynamic changes within the ovary has permitted exciting new avenues of research with readily quantifiable endpoints. Spectral, color-flow and power Doppler imaging now facilitate physiologic interpretations of vascular dynamics over time. Similarly, magnetic resonance imaging (MRI) is emerging as a research tool in ovarian imaging. New technologies, such as three-dimensional ultrasonography and MRI, ultrasound-based biomicroscopy and synchrotron-based techniques each have the potential to enhance our real-time picture of ovarian function to the near-cellular level. Collectively, information available in ultrasonography, MRI, computer-assisted image analysis and mathematical modeling heralds a new era in our understanding of the basic processes of female and male reproduction.

Delineation of early brain development from fetuses to infants with diffusion MRI and beyond.

PubMed

Ouyang, Minhui; Dubois, Jessica; Yu, Qinlin; Mukherjee, Pratik; Huang, Hao

2018-04-12

Dynamic macrostructural and microstructural changes take place from the mid-fetal stage to 2 years after birth. Delineating structural changes of the brain during early development provides new insights into the complicated processes of both typical development and the pathological mechanisms underlying various psychiatric and neurological disorders including autism, attention deficit hyperactivity disorder and schizophrenia. Decades of histological studies have identified strong spatial and functional maturation gradients in human brain gray and white matter. The recent improvements in magnetic resonance imaging (MRI) techniques, especially diffusion MRI (dMRI), relaxometry imaging, and magnetization transfer imaging (MTI) have provided unprecedented opportunities to non-invasively quantify and map the early developmental changes at whole brain and regional levels. Here, we review the recent advances in understanding early brain structural development during the second half of gestation and the first two postnatal years using modern MR techniques. Specifically, we review studies that delineate the emergence and microstructural maturation of white matter tracts, as well as dynamic mapping of inhomogeneous cortical microstructural organization unique to fetuses and infants. These imaging studies converge into maturational curves of MRI measurements that are distinctive across different white matter tracts and cortical regions. Furthermore, contemporary models offering biophysical interpretations of the dMRI-derived measurements are illustrated to infer the underlying microstructural changes. Collectively, this review summarizes findings that contribute to charting spatiotemporally heterogeneous gray and white matter structural development, offering MRI-based biomarkers of typical brain development and setting the stage for understanding aberrant brain development in neurodevelopmental disorders. Copyright © 2018 Elsevier Inc. All rights reserved.

Lung parenchymal analysis on dynamic MRI in thoracic insufficiency syndrome to assess changes following surgical intervention

NASA Astrophysics Data System (ADS)

Jagadale, Basavaraj N.; Udupa, Jayaram K.; Tong, Yubing; Wu, Caiyun; McDonough, Joseph; Torigian, Drew A.; Campbell, Robert M.

2018-02-01

General surgeons, orthopedists, and pulmonologists individually treat patients with thoracic insufficiency syndrome (TIS). The benefits of growth-sparing procedures such as Vertical Expandable Prosthetic Titanium Rib (VEPTR)insertionfor treating patients with TIS have been demonstrated. However, at present there is no objective assessment metricto examine different thoracic structural components individually as to their roles in the syndrome, in contributing to dynamics and function, and in influencing treatment outcome. Using thoracic dynamic MRI (dMRI), we have been developing a methodology to overcome this problem. In this paper, we extend this methodology from our previous structural analysis approaches to examining lung tissue properties. We process the T2-weighted dMRI images through a series of steps involving 4D image construction of the acquired dMRI images, intensity non-uniformity correction and standardization of the 4D image, lung segmentation, and estimation of the parameters describing lung tissue intensity distributions in the 4D image. Based on pre- and post-operative dMRI data sets from 25 TIS patients (predominantly neuromuscular and congenital conditions), we demonstrate how lung tissue can be characterized by the estimated distribution parameters. Our results show that standardized T2-weighted image intensity values decrease from the pre- to post-operative condition, likely reflecting improved lung aeration post-operatively. In both pre- and post-operative conditions, the intensity values decrease also from end-expiration to end-inspiration, supporting the basic premise of our results.

An in vivo MRI Template Set for Morphometry, Tissue Segmentation, and fMRI Localization in Rats

PubMed Central

Valdés-Hernández, Pedro Antonio; Sumiyoshi, Akira; Nonaka, Hiroi; Haga, Risa; Aubert-Vásquez, Eduardo; Ogawa, Takeshi; Iturria-Medina, Yasser; Riera, Jorge J.; Kawashima, Ryuta

2011-01-01

Over the last decade, several papers have focused on the construction of highly detailed mouse high field magnetic resonance image (MRI) templates via non-linear registration to unbiased reference spaces, allowing for a variety of neuroimaging applications such as robust morphometric analyses. However, work in rats has only provided medium field MRI averages based on linear registration to biased spaces with the sole purpose of approximate functional MRI (fMRI) localization. This precludes any morphometric analysis in spite of the need of exploring in detail the neuroanatomical substrates of diseases in a recent advent of rat models. In this paper we present a new in vivo rat T2 MRI template set, comprising average images of both intensity and shape, obtained via non-linear registration. Also, unlike previous rat template sets, we include white and gray matter probabilistic segmentations, expanding its use to those applications demanding prior-based tissue segmentation, e.g., statistical parametric mapping (SPM) voxel-based morphometry. We also provide a preliminary digitalization of latest Paxinos and Watson atlas for anatomical and functional interpretations within the cerebral cortex. We confirmed that, like with previous templates, forepaw and hindpaw fMRI activations can be correctly localized in the expected atlas structure. To exemplify the use of our new MRI template set, were reported the volumes of brain tissues and cortical structures and probed their relationships with ontogenetic development. Other in vivo applications in the near future can be tensor-, deformation-, or voxel-based morphometry, morphological connectivity, and diffusion tensor-based anatomical connectivity. Our template set, freely available through the SPM extension website, could be an important tool for future longitudinal and/or functional extensive preclinical studies. PMID:22275894

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.

Development of Ferrite-Based Temperature Sensors for Magnetic Resonance Imaging: A Study of Cu1 -xZnxFe2O4

NASA Astrophysics Data System (ADS)

Alghamdi, N. A.; Hankiewicz, J. H.; Anderson, N. R.; Stupic, K. F.; Camley, R. E.; Przybylski, M.; Żukrowski, J.; Celinski, Z.

2018-05-01

We investigate the use of Cu1 -xZnxFe2O4 ferrites (0.60

Individual classification of Alzheimer's disease with diffusion magnetic resonance imaging.

PubMed

Schouten, Tijn M; Koini, Marisa; Vos, Frank de; Seiler, Stephan; Rooij, Mark de; Lechner, Anita; Schmidt, Reinhold; Heuvel, Martijn van den; Grond, Jeroen van der; Rombouts, Serge A R B

2017-05-15

Diffusion magnetic resonance imaging (MRI) is a powerful non-invasive method to study white matter integrity, and is sensitive to detect differences in Alzheimer's disease (AD) patients. Diffusion MRI may be able to contribute towards reliable diagnosis of AD. We used diffusion MRI to classify AD patients (N=77), and controls (N=173). We use different methods to extract information from the diffusion MRI data. First, we use the voxel-wise diffusion tensor measures that have been skeletonised using tract based spatial statistics. Second, we clustered the voxel-wise diffusion measures with independent component analysis (ICA), and extracted the mixing weights. Third, we determined structural connectivity between Harvard Oxford atlas regions with probabilistic tractography, as well as graph measures based on these structural connectivity graphs. Classification performance for voxel-wise measures ranged between an AUC of 0.888, and 0.902. The ICA-clustered measures ranged between an AUC of 0.893, and 0.920. The AUC for the structural connectivity graph was 0.900, while graph measures based upon this graph ranged between an AUC of 0.531, and 0.840. All measures combined with a sparse group lasso resulted in an AUC of 0.896. Overall, fractional anisotropy clustered into ICA components was the best performing measure. These findings may be useful for future incorporation of diffusion MRI into protocols for AD classification, or as a starting point for early detection of AD using diffusion MRI. Copyright © 2017 Elsevier Inc. All rights reserved.

A general prediction model for the detection of ADHD and Autism using structural and functional MRI.

PubMed

Sen, Bhaskar; Borle, Neil C; Greiner, Russell; Brown, Matthew R G

2018-01-01

This work presents a novel method for learning a model that can diagnose Attention Deficit Hyperactivity Disorder (ADHD), as well as Autism, using structural texture and functional connectivity features obtained from 3-dimensional structural magnetic resonance imaging (MRI) and 4-dimensional resting-state functional magnetic resonance imaging (fMRI) scans of subjects. We explore a series of three learners: (1) The LeFMS learner first extracts features from the structural MRI images using the texture-based filters produced by a sparse autoencoder. These filters are then convolved with the original MRI image using an unsupervised convolutional network. The resulting features are used as input to a linear support vector machine (SVM) classifier. (2) The LeFMF learner produces a diagnostic model by first computing spatial non-stationary independent components of the fMRI scans, which it uses to decompose each subject's fMRI scan into the time courses of these common spatial components. These features can then be used with a learner by themselves or in combination with other features to produce the model. Regardless of which approach is used, the final set of features are input to a linear support vector machine (SVM) classifier. (3) Finally, the overall LeFMSF learner uses the combined features obtained from the two feature extraction processes in (1) and (2) above as input to an SVM classifier, achieving an accuracy of 0.673 on the ADHD-200 holdout data and 0.643 on the ABIDE holdout data. Both of these results, obtained with the same LeFMSF framework, are the best known, over all hold-out accuracies on these datasets when only using imaging data-exceeding previously-published results by 0.012 for ADHD and 0.042 for Autism. Our results show that combining multi-modal features can yield good classification accuracy for diagnosis of ADHD and Autism, which is an important step towards computer-aided diagnosis of these psychiatric diseases and perhaps others as well.

Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project

PubMed Central

Uğurbil, Kamil; Xu, Junqian; Auerbach, Edward J.; Moeller, Steen; Vu, An; Duarte-Carvajalino, Julio M.; Lenglet, Christophe; Wu, Xiaoping; Schmitter, Sebastian; Van de Moortele, Pierre Francois; Strupp, John; Sapiro, Guillermo; De Martino, Federico; Wang, Dingxin; Harel, Noam; Garwood, Michael; Chen, Liyong; Feinberg, David A.; Smith, Stephen M.; Miller, Karla L.; Sotiropoulos, Stamatios N; Jbabdi, Saad; Andersson, Jesper L; Behrens, Timothy EJ; Glasser, Matthew F.; Van Essen, David; Yacoub, Essa

2013-01-01

The human connectome project (HCP) relies primarily on three complementary magnetic resonance (MR) methods. These are: 1) resting state functional MR imaging (rfMRI) which uses correlations in the temporal fluctuations in an fMRI time series to deduce ‘functional connectivity’; 2) diffusion imaging (dMRI), which provides the input for tractography algorithms used for the reconstruction of the complex axonal fiber architecture; and 3) task based fMRI (tfMRI), which is employed to identify functional parcellation in the human brain in order to assist analyses of data obtained with the first two methods. We describe technical improvements and optimization of these methods as well as instrumental choices that impact speed of acquisition of fMRI and dMRI images at 3 Tesla, leading to whole brain coverage with 2 mm isotropic resolution in 0.7 second for fMRI, and 1.25 mm isotropic resolution dMRI data for tractography analysis with three-fold reduction in total data acquisition time. Ongoing technical developments and optimization for acquisition of similar data at 7 Tesla magnetic field are also presented, targeting higher resolution, specificity of functional imaging signals, mitigation of the inhomogeneous radio frequency (RF) fields and power deposition. Results demonstrate that overall, these approaches represent a significant advance in MR imaging of the human brain to investigate brain function and structure. PMID:23702417

Topical Review: Unique Contributions of Magnetic Resonance Imaging to Pediatric Psychology Research

PubMed Central

Duraccio, Kara M.; Carbine, Kaylie M.; Kirwan, C. Brock

2016-01-01

Objective This review aims to provide a brief introduction of the utility of magnetic resonance imaging (MRI) methods in pediatric psychology research, describe several exemplar studies that highlight the unique benefits of MRI techniques for pediatric psychology research, and detail methods for addressing several challenges inherent to pediatric MRI research. Methods Literature review. Results Numerous useful applications of MRI research in pediatric psychology have been illustrated in published research. MRI methods yield information that cannot be obtained using neuropsychological or behavioral measures. Conclusions Using MRI in pediatric psychology research may facilitate examination of neural structures and processes that underlie health behaviors. Challenges inherent to conducting MRI research with pediatric research participants (e.g., head movement) may be addressed using evidence-based strategies. We encourage pediatric psychology researchers to consider adopting MRI techniques to answer research questions relevant to pediatric health and illness. PMID:26141118

Association between pathology and texture features of multi parametric MRI of the prostate

NASA Astrophysics Data System (ADS)

Kuess, Peter; Andrzejewski, Piotr; Nilsson, David; Georg, Petra; Knoth, Johannes; Susani, Martin; Trygg, Johan; Helbich, Thomas H.; Polanec, Stephan H.; Georg, Dietmar; Nyholm, Tufve

2017-10-01

The role of multi-parametric (mp)MRI in the diagnosis and treatment of prostate cancer has increased considerably. An alternative to visual inspection of mpMRI is the evaluation using histogram-based (first order statistics) parameters and textural features (second order statistics). The aims of the present work were to investigate the relationship between benign and malignant sub-volumes of the prostate and textures obtained from mpMR images. The performance of tumor prediction was investigated based on the combination of histogram-based and textural parameters. Subsequently, the relative importance of mpMR images was assessed and the benefit of additional imaging analyzed. Finally, sub-structures based on the PI-RADS classification were investigated as potential regions to automatically detect maligned lesions. Twenty-five patients who received mpMRI prior to radical prostatectomy were included in the study. The imaging protocol included T2, DWI, and DCE. Delineation of tumor regions was performed based on pathological information. First and second order statistics were derived from each structure and for all image modalities. The resulting data were processed with multivariate analysis, using PCA (principal component analysis) and OPLS-DA (orthogonal partial least squares discriminant analysis) for separation of malignant and healthy tissue. PCA showed a clear difference between tumor and healthy regions in the peripheral zone for all investigated images. The predictive ability of the OPLS-DA models increased for all image modalities when first and second order statistics were combined. The predictive value reached a plateau after adding ADC and T2, and did not increase further with the addition of other image information. The present study indicates a distinct difference in the signatures between malign and benign prostate tissue. This is an absolute prerequisite for automatic tumor segmentation, but only the first step in that direction. For the specific identified signature, DCE did not add complementary information to T2 and ADC maps.

Quantifying the ultrastructure of carotid arteries using high-resolution micro-diffusion tensor imaging—comparison of intact versus open cut tissue

NASA Astrophysics Data System (ADS)

Salman Shahid, Syed; Gaul, Robert T.; Kerskens, Christian; Flamini, Vittoria; Lally, Caitríona

2017-12-01

Diffusion magnetic resonance imaging (dMRI) can provide insights into the microstructure of intact arterial tissue. The current study employed high magnetic field MRI to obtain ultra-high resolution dMRI at an isotropic voxel resolution of 117 µm3 in less than 2 h of scan time. A parameter selective single shell (128 directions) diffusion-encoding scheme based on Stejskel-Tanner sequence with echo-planar imaging (EPI) readout was used. EPI segmentation was used to reduce the echo time (TE) and to minimise the susceptibility-induced artefacts. The study utilised the dMRI analysis with diffusion tensor imaging (DTI) framework to investigate structural heterogeneity in intact arterial tissue and to quantify variations in tissue composition when the tissue is cut open and flattened. For intact arterial samples, the region of interest base comparison showed significant differences in fractional anisotropy and mean diffusivity across the media layer (p  <  0.05). For open cut flat samples, DTI based directionally invariant indices did not show significant differences across the media layer. For intact samples, fibre tractography based indices such as calculated helical angle and fibre dispersion showed near circumferential alignment and a high degree of fibre dispersion, respectively. This study demonstrates the feasibility of fast dMRI acquisition with ultra-high spatial and angular resolution at 7 T. Using the optimised sequence parameters, this study shows that DTI based markers are sensitive to local structural changes in intact arterial tissue samples and these markers may have clinical relevance in the diagnosis of atherosclerosis and aneurysm.

Sparse magnetic resonance imaging reconstruction using the bregman iteration

NASA Astrophysics Data System (ADS)

Lee, Dong-Hoon; Hong, Cheol-Pyo; Lee, Man-Woo

2013-01-01

Magnetic resonance imaging (MRI) reconstruction needs many samples that are sequentially sampled by using phase encoding gradients in a MRI system. It is directly connected to the scan time for the MRI system and takes a long time. Therefore, many researchers have studied ways to reduce the scan time, especially, compressed sensing (CS), which is used for sparse images and reconstruction for fewer sampling datasets when the k-space is not fully sampled. Recently, an iterative technique based on the bregman method was developed for denoising. The bregman iteration method improves on total variation (TV) regularization by gradually recovering the fine-scale structures that are usually lost in TV regularization. In this study, we studied sparse sampling image reconstruction using the bregman iteration for a low-field MRI system to improve its temporal resolution and to validate its usefulness. The image was obtained with a 0.32 T MRI scanner (Magfinder II, SCIMEDIX, Korea) with a phantom and an in-vivo human brain in a head coil. We applied random k-space sampling, and we determined the sampling ratios by using half the fully sampled k-space. The bregman iteration was used to generate the final images based on the reduced data. We also calculated the root-mean-square-error (RMSE) values from error images that were obtained using various numbers of bregman iterations. Our reconstructed images using the bregman iteration for sparse sampling images showed good results compared with the original images. Moreover, the RMSE values showed that the sparse reconstructed phantom and the human images converged to the original images. We confirmed the feasibility of sparse sampling image reconstruction methods using the bregman iteration with a low-field MRI system and obtained good results. Although our results used half the sampling ratio, this method will be helpful in increasing the temporal resolution at low-field MRI systems.

A distributed computing system for magnetic resonance imaging: Java-based processing and binding of XML.

PubMed

de Beer, R; Graveron-Demilly, D; Nastase, S; van Ormondt, D

2004-03-01

Recently we have developed a Java-based heterogeneous distributed computing system for the field of magnetic resonance imaging (MRI). It is a software system for embedding the various image reconstruction algorithms that we have created for handling MRI data sets with sparse sampling distributions. Since these data sets may result from multi-dimensional MRI measurements our system has to control the storage and manipulation of large amounts of data. In this paper we describe how we have employed the extensible markup language (XML) to realize this data handling in a highly structured way. To that end we have used Java packages, recently released by Sun Microsystems, to process XML documents and to compile pieces of XML code into Java classes. We have effectuated a flexible storage and manipulation approach for all kinds of data within the MRI system, such as data describing and containing multi-dimensional MRI measurements, data configuring image reconstruction methods and data representing and visualizing the various services of the system. We have found that the object-oriented approach, possible with the Java programming environment, combined with the XML technology is a convenient way of describing and handling various data streams in heterogeneous distributed computing systems.

Fast magnetic resonance imaging based on high degree total variation

NASA Astrophysics Data System (ADS)

Wang, Sujie; Lu, Liangliang; Zheng, Junbao; Jiang, Mingfeng

2018-04-01

In order to eliminating the artifacts and "staircase effect" of total variation in Compressive Sensing MRI, high degree total variation model is proposed for dynamic MRI reconstruction. the high degree total variation regularization term is used as a constraint to reconstruct the magnetic resonance image, and the iterative weighted MM algorithm is proposed to solve the convex optimization problem of the reconstructed MR image model, In addtion, one set of cardiac magnetic resonance data is used to verify the proposed algorithm for MRI. The results show that the high degree total variation method has a better reconstruction effect than the total variation and the total generalized variation, which can obtain higher reconstruction SNR and better structural similarity.

Photo-multiplier Tube Based Hybrid MRI and Frequency Domain Fluorescence Tomography System for Small Animal Imaging

PubMed Central

Lin, Y; Ghijsen, M T; Gao, H; Liu, N; Nalcioglu, O; Gulsen, G

2014-01-01

Fluorescence tomography (FT) is a promising molecular imaging technique that can spatially resolve both fluorophore concentration and lifetime parameters. However, recovered fluorophore parameters highly depend on the size and depth of the object due to the ill-posedness of the FT inverse problem. Structural a priori information from another high spatial resolution imaging modality has been demonstrated to significantly improve FT reconstruction accuracy. In this study, we have constructed a combined magnetic resonance imaging (MRI) and FT system for small animal imaging. A photo-multiplier tube (PMT) is used as the detector to acquire frequency domain FT measurements. This is the first MR-compatible time-resolved FT system that can reconstruct both fluorescence concentration and lifetime maps simultaneously. The performance of the hybrid system is evaluated with phantom studies. Two different fluorophores, Indocyanine Green (ICG) and 3-3′ Diethylthiatricarbocyanine Iodide (DTTCI), which have similar excitation and emission spectra but different lifetimes, are utilized. The fluorescence concentration and lifetime maps are both reconstructed with and without the structural a priori information obtained from MRI for comparison. We show that the hybrid system can accurately recover both fluorescence intensity and lifetime within 10% error for two 4.2 mm-diameter cylindrical objects embedded in a 38 mm-diameter cylindrical phantom when MRI structural a priori information is utilized. PMID:21753235

Towards radiological diagnosis of abdominal adhesions based on motion signatures derived from sequences of cine-MRI images.

PubMed

Fenner, John; Wright, Benjamin; Emberey, Jonathan; Spencer, Paul; Gillott, Richard; Summers, Angela; Hutchinson, Charles; Lawford, Pat; Brenchley, Paul; Bardhan, Karna Dev

2014-06-01

This paper reports novel development and preliminary application of an image registration technique for diagnosis of abdominal adhesions imaged with cine-MRI (cMRI). Adhesions can severely compromise the movement and physiological function of the abdominal contents, and their presence is difficult to detect. The image registration approach presented here is designed to expose anomalies in movement of the abdominal organs, providing a movement signature that is indicative of underlying structural abnormalities. Validation of the technique was performed using structurally based in vitro and in silico models, supported with Receiver Operating Characteristic (ROC) methods. For the more challenging cases presented to the small cohort of 4 observers, the AUC (area under curve) improved from a mean value of 0.67 ± 0.02 (without image registration assistance) to a value of 0.87 ± 0.02 when image registration support was included. Also, in these cases, a reduction in time to diagnosis was observed, decreasing by between 20% and 50%. These results provided sufficient confidence to apply the image registration diagnostic protocol to sample magnetic resonance imaging data from healthy volunteers as well as a patient suffering from encapsulating peritoneal sclerosis (an extreme form of adhesions) where immobilization of the gut by cocooning of the small bowel is observed. The results as a whole support the hypothesis that movement analysis using image registration offers a possible method for detecting underlying structural anomalies and encourages further investigation. Copyright © 2014 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Comparison of onboard low-field magnetic resonance imaging versus onboard computed tomography for anatomy visualization in radiotherapy.

PubMed

Noel, Camille E; Parikh, Parag J; Spencer, Christopher R; Green, Olga L; Hu, Yanle; Mutic, Sasa; Olsen, Jeffrey R

2015-01-01

Onboard magnetic resonance imaging (OB-MRI) for daily localization and adaptive radiotherapy has been under development by several groups. However, no clinical studies have evaluated whether OB-MRI improves visualization of the target and organs at risk (OARs) compared to standard onboard computed tomography (OB-CT). This study compared visualization of patient anatomy on images acquired on the MRI-(60)Co ViewRay system to those acquired with OB-CT. Fourteen patients enrolled on a protocol approved by the Institutional Review Board (IRB) and undergoing image-guided radiotherapy for cancer in the thorax (n = 2), pelvis (n = 6), abdomen (n = 3) or head and neck (n = 3) were imaged with OB-MRI and OB-CT. For each of the 14 patients, the OB-MRI and OB-CT datasets were displayed side-by-side and independently reviewed by three radiation oncologists. Each physician was asked to evaluate which dataset offered better visualization of the target and OARs. A quantitative contouring study was performed on two abdominal patients to assess if OB-MRI could offer improved inter-observer segmentation agreement for adaptive planning. In total 221 OARs and 10 targets were compared for visualization on OB-MRI and OB-CT by each of the three physicians. The majority of physicians (two or more) evaluated visualization on MRI as better for 71% of structures, worse for 10% of structures, and equivalent for 14% of structures. 5% of structures were not visible on either. Physicians agreed unanimously for 74% and in majority for > 99% of structures. Targets were better visualized on MRI in 4/10 cases, and never on OB-CT. Low-field MR provides better anatomic visualization of many radiotherapy targets and most OARs as compared to OB-CT. Further studies with OB-MRI should be pursued.

Magnetic Transfer Contrast Accurately Localizes Substantia Nigra Confirmed by Histology

PubMed Central

Bolding, Mark S.; Reid, Meredith A.; Avsar, Kathy B.; Roberts, Rosalinda C.; Gamlin, Paul D.; Gawne, Timothy J.; White, David M.; den Hollander, Jan A.; Lahti, Adrienne C.

2012-01-01

Background Magnetic Resonance Imaging (MRI) has multiple contrast mechanisms. Like various staining techniques in histology, each contrast type reveals different information about the structure of the brain. However, it is not always clear how structures visible in MRI correspond to structures previously identified by histology. The purpose of this study was to determine if magnetic transfer contrast (MTC) or T2 contrast MRI was better at delineating the substantia nigra. Methods MRI scans were acquired in-vivo from two non-human primates (NHPs). The NHPs were subsequently euthanized, perfused, and their brains sectioned for histological analyses. Each slice was photographed prior to sectioning. Each brain was sectioned into approximately 500, 40-micron sections, encompassing most of the cortex, midbrain, and dorsal parts of the hindbrain. Levels corresponding to anatomical MRI images were selected. From these, adjacent sections were stained using Kluver Barrera (myelin and cell bodies) or tyrosine hydroxylase (TH) (dopaminergic neurons) immunohistochemistry. The resulting images were coregistered to the block-face images using a moving least squares algorithm with similarity transformations. MR images were similarly coregistered to the block-face images, allowing the structures in the MRI to be identified with structures in the histological images. Results We found that hyperintense (light) areas in MTC images were coextensive with the SN as delineated histologically. The hypointense (dark) areas in T2-weighted images were not coextensive with the SN, but extended partially into the SN and partially into the cerebral peduncles. Conclusions MTC is a more accurate contrast mechanism than T2-weighting for localizing the SN in vivo. PMID:22981657

Structural and functional brain changes in early- and mid-stage primary open-angle glaucoma using voxel-based morphometry and functional magnetic resonance imaging.

PubMed

Jiang, Ming-Ming; Zhou, Qing; Liu, Xiao-Yong; Shi, Chang-Zheng; Chen, Jian; Huang, Xiang-He

2017-03-01

To investigate structural and functional brain changes in patients with primary open-angle glaucoma (POAG) by using voxel-based morphometry based on diffeomorphic anatomical registration through exponentiated Lie algebra (VBM-DARTEL) and blood oxygenation level dependent functional magnetic resonance imaging (BOLD-fMRI), respectively.Thirteen patients diagnosed with POAG and 13 age- and sex-matched healthy controls were enrolled in the study. For each participant, high-resolution structural brain imaging and blood flow imaging were acquired on a 3.0-Tesla magnetic resonance imaging (MRI) scanner. Structural and functional changes between the POAG and control groups were analyzed. An analysis was carried out to identify correlations between structural and functional changes acquired in the previous analysis and the retinal nerve fiber layer (RNFL).Patients in the POAG group showed a significant (P < 0.001) volume increase in the midbrain, left brainstem, frontal gyrus, cerebellar vermis, left inferior parietal lobule, caudate nucleus, thalamus, precuneus, and Brodmann areas 7, 18, and 46. Moreover, significant (P < 0.001) BOLD signal changes were observed in the right supramarginal gyrus, frontal gyrus, superior frontal gyrus, left inferior parietal lobule, left cuneus, and left midcingulate area; many of these regions had high correlations with the RNFL.Patients with POAG undergo widespread and complex changes in cortical brain structure and blood flow. (ClinicalTrials.gov number: NCT02570867).

Multivariate data analysis and machine learning in Alzheimer's disease with a focus on structural magnetic resonance imaging.

PubMed

Falahati, Farshad; Westman, Eric; Simmons, Andrew

2014-01-01

Machine learning algorithms and multivariate data analysis methods have been widely utilized in the field of Alzheimer's disease (AD) research in recent years. Advances in medical imaging and medical image analysis have provided a means to generate and extract valuable neuroimaging information. Automatic classification techniques provide tools to analyze this information and observe inherent disease-related patterns in the data. In particular, these classifiers have been used to discriminate AD patients from healthy control subjects and to predict conversion from mild cognitive impairment to AD. In this paper, recent studies are reviewed that have used machine learning and multivariate analysis in the field of AD research. The main focus is on studies that used structural magnetic resonance imaging (MRI), but studies that included positron emission tomography and cerebrospinal fluid biomarkers in addition to MRI are also considered. A wide variety of materials and methods has been employed in different studies, resulting in a range of different outcomes. Influential factors such as classifiers, feature extraction algorithms, feature selection methods, validation approaches, and cohort properties are reviewed, as well as key MRI-based and multi-modal based studies. Current and future trends are discussed.

Image fusion pitfalls for cranial radiosurgery.

PubMed

Jonker, Benjamin P

2013-01-01

Stereotactic radiosurgery requires imaging to define both the stereotactic space in which the treatment is delivered and the target itself. Image fusion is the process of using rotation and translation to bring a second image set into alignment with the first image set. This allows the potential concurrent use of multiple image sets to define the target and stereotactic space. While a single magnetic resonance imaging (MRI) sequence alone can be used for delineation of the target and fiducials, there may be significant advantages to using additional imaging sets including other MRI sequences, computed tomography (CT) scans, and advanced imaging sets such as catheter-based angiography, diffusor tension imaging-based fiber tracking and positon emission tomography in order to more accurately define the target and surrounding critical structures. Stereotactic space is usually defined by detection of fiducials on the stereotactic head frame or mask system. Unfortunately MRI sequences are susceptible to geometric distortion, whereas CT scans do not face this problem (although they have poorer resolution of the target in most cases). Thus image fusion can allow the definition of stereotactic space to proceed from the geometrically accurate CT images at the same time as using MRI to define the target. The use of image fusion is associated with risk of error introduced by inaccuracies of the fusion process, as well as workflow changes that if not properly accounted for can mislead the treating clinician. The purpose of this review is to describe the uses of image fusion in stereotactic radiosurgery as well as its potential pitfalls.

Usefulness of the advanced neuroimaging protocol based on plain and gadolinium-enhanced constructive interference in steady state images for gamma knife radiosurgery and planning microsurgical procedures for skull base tumors.

PubMed

Hayashi, Motohiro; Chernov, Mikhail F; Tamura, Noriko; Yomo, Shoji; Tamura, Manabu; Horiba, Ayako; Izawa, Masahiro; Muragaki, Yoshihiro; Iseki, Hiroshi; Okada, Yoshikazu; Ivanov, Pavel; Régis, Jean; Takakura, Kintomo

2013-01-01

Gamma Knife radiosurgery (GKS) is currently performed with 0.1 mm preciseness, which can be designated microradiosurgery. It requires advanced methods for visualizing the target, which can be effectively attained by a neuroimaging protocol based on plain and gadolinium-enhanced constructive interference in steady state (CISS) images. Since 2003, the following thin-sliced images are routinely obtained before GKS of skull base lesions in our practice: axial CISS, gadolinium-enhanced axial CISS, gadolinium-enhanced axial modified time-of-flight (TOF), and axial computed tomography (CT). Fusion of "bone window" CT and magnetic resonance imaging (MRI), and detailed three-dimensional (3D) delineation of the anatomical structures are performed with the Leksell GammaPlan (Elekta Instruments AB). Recently, a similar technique has been also applied to evaluate neuroanatomy before open microsurgical procedures. Plain CISS images permit clear visualization of the cranial nerves in the subarachnoid space. Gadolinium-enhanced CISS images make the tumor "lucid" but do not affect the signal intensity of the cranial nerves, so they can be clearly delineated in the vicinity to the lesion. Gadolinium-enhanced TOF images are useful for 3D evaluation of the interrelations between the neoplasm and adjacent vessels. Fusion of "bone window" CT and MRI scans permits simultaneous assessment of both soft tissue and bone structures and allows 3D estimation and correction of MRI distortion artifacts. Detailed understanding of the neuroanatomy based on application of the advanced neuroimaging protocol permits performance of highly conformal and selective radiosurgical treatment. It also allows precise planning of the microsurgical procedures for skull base tumors.

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.

Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning.

PubMed

Arabi, Hossein; Koutsouvelis, Nikolaos; Rouzaud, Michel; Miralbell, Raymond; Zaidi, Habib

2016-09-07

Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of  -1.5  ±  5.0% (mean  ±  SD) in bony structures compared to  -19.9  ±  11.8% and  -8.1  ±  8.2% achieved by MRI segmentation-based (water-only) and atlas-guided AC. Dosimetric evaluation using dose volume histograms and the average difference between minimum/maximum absorbed doses revealed a mean error of less than 1% for the both target volumes and organs at risk. Two-dimensional (2D) gamma analysis of the isocenter dose distributions at 1%/1 mm criterion revealed pass rates of 91.40  ±  7.56%, 96.00  ±  4.11% and 97.67  ±  3.6% for MRI segmentation, atlas-guided and the proposed methods, respectively. The proposed method generates accurate pseudo-CT images from conventional Dixon MRI sequences with improved bone extraction accuracy. The approach is promising for potential use in PET AC and MRI-only or hybrid PET/MRI-guided RT treatment planning.

Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning

NASA Astrophysics Data System (ADS)

Arabi, Hossein; Koutsouvelis, Nikolaos; Rouzaud, Michel; Miralbell, Raymond; Zaidi, Habib

2016-09-01

Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of  -1.5  ±  5.0% (mean  ±  SD) in bony structures compared to  -19.9  ±  11.8% and  -8.1  ±  8.2% achieved by MRI segmentation-based (water-only) and atlas-guided AC. Dosimetric evaluation using dose volume histograms and the average difference between minimum/maximum absorbed doses revealed a mean error of less than 1% for the both target volumes and organs at risk. Two-dimensional (2D) gamma analysis of the isocenter dose distributions at 1%/1 mm criterion revealed pass rates of 91.40  ±  7.56%, 96.00  ±  4.11% and 97.67  ±  3.6% for MRI segmentation, atlas-guided and the proposed methods, respectively. The proposed method generates accurate pseudo-CT images from conventional Dixon MRI sequences with improved bone extraction accuracy. The approach is promising for potential use in PET AC and MRI-only or hybrid PET/MRI-guided RT treatment planning.

Structural and functional changes during epileptogenesis in the mouse model of medial temporal lobe epilepsy.

PubMed

Dietrich, Yvan; Eliat, Pierre-Antoine; Dieuset, Gabriel; Saint-Jalmes, Herve; Pineau, Charles; Wendling, Fabrice; Martin, Benoit

2016-08-01

An important issue in epilepsy research is to understand the structural and functional modifications leading to chronic epilepsy, characterized by spontaneous recurrent seizures, after initial brain insult. To address this issue, we recorded and analyzed electroencephalography (EEG) and quantitative magnetic resonance imaging (MRI) data during epileptogenesis in the in vivo mouse model of Medial Temporal Lobe Epilepsy (MTLE, kainate). Besides, this model of epilepsy is a particular form of drug-resistant epilepsy. The results indicate that high-field (4.7T) MRI parameters (T2-weighted; T2-quantitative) allow to detect the gradual neuro-anatomical changes that occur during epileptogenesis while electrophysiological parameters (number and duration of Hippocampal Paroxysmal Discharges) allow to assess the dysfunctional changes through the quantification of epileptiform activity. We found a strong correlation between EEG-based markers (invasive recording) and MRI-based parameters (non-invasive) periodically computed over the `latent period' that spans over two weeks, on average. These results indicated that both structural and functional changes occur in the considered epilepsy model and are considered as biomarkers of the installation of epilepsy. Additionally, such structural and functional changes can also be observed in human temporal lobe epilepsy. Interestingly, MRI imaging parameters could be used to track early (day-7) structural changes (gliosis, cell loss) in the lesioned brain and to quantify the evolution of epileptogenesis after traumatic brain injury.

Three-dimensional liver motion tracking using real-time two-dimensional MRI

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

Brix, Lau, E-mail: lau.brix@stab.rm.dk; Ringgaard, Steffen; Sørensen, Thomas Sangild

2014-04-15

Purpose: Combined magnetic resonance imaging (MRI) systems and linear accelerators for radiotherapy (MR-Linacs) are currently under development. MRI is noninvasive and nonionizing and can produce images with high soft tissue contrast. However, new tracking methods are required to obtain fast real-time spatial target localization. This study develops and evaluates a method for tracking three-dimensional (3D) respiratory liver motion in two-dimensional (2D) real-time MRI image series with high temporal and spatial resolution. Methods: The proposed method for 3D tracking in 2D real-time MRI series has three steps: (1) Recording of a 3D MRI scan and selection of a blood vessel (ormore » tumor) structure to be tracked in subsequent 2D MRI series. (2) Generation of a library of 2D image templates oriented parallel to the 2D MRI image series by reslicing and resampling the 3D MRI scan. (3) 3D tracking of the selected structure in each real-time 2D image by finding the template and template position that yield the highest normalized cross correlation coefficient with the image. Since the tracked structure has a known 3D position relative to each template, the selection and 2D localization of a specific template translates into quantification of both the through-plane and in-plane position of the structure. As a proof of principle, 3D tracking of liver blood vessel structures was performed in five healthy volunteers in two 5.4 Hz axial, sagittal, and coronal real-time 2D MRI series of 30 s duration. In each 2D MRI series, the 3D localization was carried out twice, using nonoverlapping template libraries, which resulted in a total of 12 estimated 3D trajectories per volunteer. Validation tests carried out to support the tracking algorithm included quantification of the breathing induced 3D liver motion and liver motion directionality for the volunteers, and comparison of 2D MRI estimated positions of a structure in a watermelon with the actual positions. Results: Axial, sagittal, and coronal 2D MRI series yielded 3D respiratory motion curves for all volunteers. The motion directionality and amplitude were very similar when measured directly as in-plane motion or estimated indirectly as through-plane motion. The mean peak-to-peak breathing amplitude was 1.6 mm (left-right), 11.0 mm (craniocaudal), and 2.5 mm (anterior-posterior). The position of the watermelon structure was estimated in 2D MRI images with a root-mean-square error of 0.52 mm (in-plane) and 0.87 mm (through-plane). Conclusions: A method for 3D tracking in 2D MRI series was developed and demonstrated for liver tracking in volunteers. The method would allow real-time 3D localization with integrated MR-Linac systems.« less

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.

Detailed Magnetic Resonance Imaging (MRI) Analysis in Infantile Spasms.

PubMed

Harini, Chellamani; Sharda, Sonal; Bergin, Ann Marie; Poduri, Annapurna; Yuskaitis, Christopher J; Peters, Jurriaan M; Rakesh, Kshitiz; Kapur, Kush; Pearl, Phillip L; Prabhu, Sanjay P

2018-05-01

To evaluate initial magnetic resonance imaging (MRI) abnormalities in infantile spasms, correlate them to clinical characteristics, and describe repeat imaging findings. A retrospective review of infantile spasm patients was conducted, classifying abnormal MRI into developmental, acquired, and nonspecific subgroups. MRIs were abnormal in 52 of 71 infantile spasm patients (23 developmental, 23 acquired, and 6 nonspecific) with no correlation to the clinical infantile spasm characteristics. Both developmental and acquired subgroups exhibited cortical gray and/or white matter abnormalities. Additional abnormalities of deep gray structures, brain stem, callosum, and volume loss occurred in the structural acquired subgroup. Repeat MRI showed better definition of the extent of existing malformations. In structural infantile spasms, developmental/acquired subgroups showed differences in pattern of MRI abnormalities but did not correlate with clinical characteristics.

Examining multi-component DNA-templated nanostructures as imaging agents

NASA Astrophysics Data System (ADS)

Jaganathan, Hamsa

2011-12-01

Magnetic resonance imaging (MRI) is the leading non-invasive tool for disease imaging and diagnosis. Although MRI exhibits high spatial resolution for anatomical features, the contrast resolution is low. Imaging agents serve as an aid to distinguish different types of tissues within images. Gadolinium chelates, which are considered first generation designs, can be toxic to health, while ultra-small, superparamagnetic nanoparticles (NPs) have low tissue-targeting efficiency and rapid bio-distribution, resulting to an inadequate detection of the MRI signal and enhancement of image contrast. In order to improve the utility of MRI agents, the challenge in composition and structure needs to be addressed. One-dimensional (1D), superparamagnetic nanostructures have been reported to enhance magnetic and in vivo properties and therefore has a potential to improve contrast enhancement in MRI images. In this dissertation, the structure of 1D, multi-component NP chains, scaffolded on DNA, were pre-clinically examined as potential MRI agents. First, research was focused on characterizing and understanding the mechanism of proton relaxation for DNA-templated NP chains using nuclear magnetic resonance (NMR) spectrometry. Proton relaxation and transverse relaxivity were higher in multi-component NP chains compared to disperse NPs, indicating the arrangement of NPs on a 1D structure improved proton relaxation sensitivity. Second, in vitro evaluation for potential issues in toxicity and contrast efficiency in tissue environments using a 3 Tesla clinical MRI scanner was performed. Cell uptake of DNA-templated NP chains was enhanced after encapsulating the nanostructure with layers of polyelectrolytes and targeting ligands. Compared to dispersed NPs, DNA-templated NP chains improved MRI contrast in both the epithelial basement membrane and colon cancer tumors scaffolds. The last part of the project was focused on developing a novel MRI agent that detects changes in DNA methylation levels. The findings from this dissertation suggest that the structural arrangement of NPs on DNA significantly influenced their function and utility as MRI agents.

Technological challenges in Magnetic Resonance Imaging: enhancing sensitivity, moving to quantitative imaging and searching for disease biomarkers

NASA Astrophysics Data System (ADS)

Retico, A.

2018-02-01

Diagnostic imaging based on the Nuclear Magnetic Resonance phenomenon has increasingly spread in the recent few decades, mainly owing to its exquisite capability in depicting a contrast between soft tissues, to its generally non-invasive nature, and to the priceless advantage of using non-ionizing radiation. Magnetic Resonance (MR)-based acquisition techniques allow gathering information on the structure (through Magnetic Resonance Imaging— MRI), the metabolic composition (through Magnetic Resonance Spectroscopy—MRS), and the functioning (through functional MRI —fMRI) of the human body. MR investigations are the methods of choice for studying the brain in vivo, including anatomy, structural wiring and functional connectivity, in healthy and pathological conditions. Alongside the efforts of the clinical research community in extending the acquisition protocols to allow the exploration of a large variety of pathologies affecting diverse body regions, some relevant technological improvements are on the way to maximize the impact of MR in medical diagnostic. The development of MR scanners operating at ultra-high magnetic field (UHF) strength (>= 7 tesla), is pushing forward the spatial resolution of MRI and the spectral resolution of MRS, and it is increasing the specificity of fMRI to grey matter signal. UHF MR systems are currently in use for research purposes only; nevertheless, UHF technological advances are positively affecting MR investigations at clinical field strengths. To overcome the current major limitation of MRI, which is mostly based on contrast between tissues rather than on absolute measurements of physical quantities, a new acquisition modality is under development, which is referred as Magnetic Resonance Fingerprinting technique. Finally, as neuroimaging data acquired worldwide are reaching the typical size of Big Data, dedicated technical solutions are required to mine large amount of information and to identify specific biomarkers of pathological conditions.

The Appropriate Use of Neuroimaging in the Diagnostic Work-Up of Dementia

PubMed Central

Bermingham, SL

2014-01-01

Background Structural brain imaging is often performed to establish the underlying causes of dementia. However, recommendations differ as to who should receive neuroimaging and whether computed tomography (CT) or magnetic resonance imaging (MRI) should be used. Objectives This study aimed to determine the cost-effectiveness in Ontario of offering structural imaging to all patients with mild to moderate dementia compared with offering it selectively according to guidelines from the Canadian Consensus Conference on the Diagnosis and Treatment of Dementia (CCC). We compared the cost-effectiveness of CT and MRI as first-line strategies. Methods We performed a systematic literature search (2000 to 2013) to identify cost-effectiveness studies of clinical prediction rules and structural imaging modalities. Studies were assessed for quality and applicability to Ontario. We also developed a model to evaluate the cost-effectiveness of clinical guidelines (image all versus according to CCC) and modalities (CT versus MRI). Transition probabilities, utilities, and costs were obtained from published literature or expert opinion. Results were expressed in terms of costs and quality adjusted life years (QALYs). Results No relevant cost-effectiveness analyses were identified in the published literature. According to the base-case results of our model, the most effective and cost-effective strategy is to image patients who meet CCC criteria with CT and to follow-up with MRI for suspected cases of space-occupying lesions (SOL). However, the results were sensitive to the specificity of MRI for detecting vascular causes of dementia. At a specificity of 64%, the most cost-effective strategy is CCC followed by MRI. Limitations Studies used to estimate diagnostic accuracy were limited by a lack of a gold standard test for establishing the cause of dementia. The model does not include costs to patients and their families, nor does it account for patient preferences about diagnostic information. Conclusions Given the relative prevalence of vascular dementia and SOLs, and the improvement in QALYs associated with treatment, the strategy with the greatest combined sensitivity (CCC with CT followed by MRI for patients with SOLs) results in the greatest number of QALYs and is the least costly. Due to limitations in the clinical data and challenges in the interpretation of this evidence, the model should be considered a framework for assessing uncertainty in the evidence base rather than providing definitive answers to the research questions. Plain Language Summary There is wide debate about whether or not brain scans should routinely be used to assess patients with mild to moderate dementia. Proponents say that imaging is important to detect or rule out possible underlying causes of dementia, such as silent strokes and tumours. Opponents call for a more selective approach, considering the need for clinical judgement and the cost of the technology. Using data from published research, a model was developed to study the cost-effectiveness of different approaches to brain imaging for a hypothetical group of patients with dementia. The model compared 2 strategies: imaging all patients and imaging selectively based on clinical practice guidelines from the Canadian Consensus Conference on the Diagnosis and Treatment of Dementia (CCC). It also compared 2 types of technology: computed tomography (CT) and magnetic resonance imaging (MRI). The results of the model depended on the accuracy of CT and MRI in diagnosing dementia caused by vascular disease. Unfortunately, because there is no “gold standard” approach to diagnosing dementia, interpreting the published research is challenging. Based on current evidence, in which diagnostic strategies are assessed using a mix of methods, the model showed that the most effective and least costly strategy is to image selectively according to the CCC guidelines, using CT first and then MRI as a follow-up for patients suspected of having space-occupying lesions such as tumours. However, if we assumed that MRI plus clinical assessment is the gold standard, then imaging all patients with MRI is the most cost-effective strategy, despite the higher cost of this technology. The model did not take into account the value that physicians, patients, and families place on having diagnostic information, even if effective treatment does not yet exist. The model was not able to answer the specific research questions with confidence, but it provides a framework for identifying areas where more research is needed to support decision-making in the diagnosis of dementia. PMID:24592297

Topical Review: Unique Contributions of Magnetic Resonance Imaging to Pediatric Psychology Research.

PubMed

Jensen, Chad D; Duraccio, Kara M; Carbine, Kaylie M; Kirwan, C Brock

2016-03-01

This review aims to provide a brief introduction of the utility of magnetic resonance imaging (MRI) methods in pediatric psychology research, describe several exemplar studies that highlight the unique benefits of MRI techniques for pediatric psychology research, and detail methods for addressing several challenges inherent to pediatric MRI research. Literature review. Numerous useful applications of MRI research in pediatric psychology have been illustrated in published research. MRI methods yield information that cannot be obtained using neuropsychological or behavioral measures. Using MRI in pediatric psychology research may facilitate examination of neural structures and processes that underlie health behaviors. Challenges inherent to conducting MRI research with pediatric research participants (e.g., head movement) may be addressed using evidence-based strategies. We encourage pediatric psychology researchers to consider adopting MRI techniques to answer research questions relevant to pediatric health and illness. © The Author 2015. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

[Possibilities of modern imaging technologies in early diagnosis of Alzheimer disease].

PubMed

Unschuld, Paul G

2015-04-01

Recent advances in neuroimaging technology and image analysis algorithms have significantly contributed to a better understanding of spatial and temporal aspects of brain change associated with Alzheimer Disease. The current review will demonstrate how functional (fMRI) and structural magnetic resonance imaging (MRI) techniques may be used to identify distinct patterns of brain change associated with disease progression and also increased risk for Alzheimer Disease. Moreover, Positron Emission Tomography (PET) based measures of glucosemetabolism (Fluorodeoxyglucose, FDG) and Amyloid-beta plaque density (11-C-Pittsburgh Compound B, PiB and 18-F) will be reviewed regarding their diagnostic value for assessing the individual degree of Alzheimer -pathology and thus complement the information provided by MRI and other clinical measures.

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.

Integrin Targeted MR Imaging

PubMed Central

Tan, Mingqian; Lu, Zheng-Rong

2011-01-01

Magnetic resonance imaging (MRI) is a powerful medical diagnostic imaging modality for integrin targeted imaging, which uses the magnetic resonance of tissue water protons to display tissue anatomic structures with high spatial resolution. Contrast agents are often used in MRI to highlight specific regions of the body and make them easier to visualize. There are four main classes of MRI contrast agents based on their different contrast mechanisms, including T1, T2, chemical exchange saturation transfer (CEST) agents, and heteronuclear contrast agents. Integrins are an important family of heterodimeric transmembrane glycoproteins that function as mediators of cell-cell and cell-extracellular matrix interactions. The overexpressed integrins can be used as the molecular targets for designing suitable integrin targeted contrast agents for MR molecular imaging. Integrin targeted contrast agent includes a targeting agent specific to a target integrin, a paramagnetic agent and a linker connecting the targeting agent with the paramagnetic agent. Proper selection of targeting agents is critical for targeted MRI contrast agents to effectively bind to integrins for in vivo imaging. An ideal integrin targeted MR contrast agent should be non-toxic, provide strong contrast enhancement at the target sites and can be completely excreted from the body after MR imaging. An overview of integrin targeted MR contrast agents based on small molecular and macromolecular Gd(III) complexes, lipid nanoparticles and superparamagnetic nanoparticles is provided for MR molecular imaging. By using proper delivery systems for loading sufficient Gd(III) chelates or superparamagnetic nanoparticles, effective molecular imaging of integrins with MRI has been demonstrated in animal models. PMID:21547154

Brain Abnormalities in Congenital Fibrosis of the Extraocular Muscles Type 1: A Multimodal MRI Imaging Study.

PubMed

Miao, Wen; Man, Fengyuan; Wu, Shaoqin; Lv, Bin; Wang, Zhenchang; Xian, Junfang; Sabel, Bernhard A; He, Huiguang; Jiao, Yonghong

2015-01-01

To explore the possible brain structural and functional alterations in congenital fibrosis of extraocular muscles type 1 (CFEOM1) patients using multimodal MRI imaging. T1-weighted, diffusion tensor images and functional MRI data were obtained from 9 KIF21A positive patients and 19 age- and gender-matched healthy controls. Voxel based morphometry and tract based spatial statistics were applied to the T1-weighted and diffusion tensor images, respectively. Amplitude of low frequency fluctuations and regional homogeneity were used to process the functional MRI data. We then compared these multimodal characteristics between CFEOM1 patients and healthy controls. Compared with healthy controls, CFEOM1 patients demonstrated increased grey matter volume in bilateral frontal orbital cortex and in the right temporal pole. No diffusion indices changes were detected, indicating unaffected white matter microstructure. In addition, from resting state functional MRI data, trend of amplitude of low-frequency fluctuations increases were noted in the right inferior parietal lobe and in the right frontal cortex, and a trend of ReHo increase (p<0.001 uncorrected) in the left precentral gyrus, left orbital frontal cortex, temporal pole and cingulate gyrus. CFEOM1 patients had structural and functional changes in grey matter, but the white matter was unaffected. These alterations in the brain may be due to the abnormality of extraocular muscles and their innervating nerves. Future studies should consider the possible correlations between brain morphological/functional findings and clinical data, especially pertaining to eye movements, to obtain more precise answers about the role of brain area changes and their functional consequence in CFEOM1.

Tensor Based Representation and Analysis of Diffusion-Weighted Magnetic Resonance Images

ERIC Educational Resources Information Center

Barmpoutis, Angelos

2009-01-01

Cartesian tensor bases have been widely used to model spherical functions. In medical imaging, tensors of various orders can approximate the diffusivity function at each voxel of a diffusion-weighted MRI data set. This approximation produces tensor-valued datasets that contain information about the underlying local structure of the scanned tissue.…

The use of high resolution magnetic resonance on 3.0-T system in the diagnosis and surgical planning of intraosseous lesions of the jaws: preliminary results of a retrospective study.

PubMed

Cassetta, M; Di Carlo, S; Pranno, N; Stagnitti, A; Pompa, V; Pompa, G

2012-12-01

The pre-operative evaluation in oral and maxillofacial surgery is currently performed by computerized tomography (CT). However in some case the information of the traditional imaging methods are not enough in the diagnosis and surgical planning. The efficacy of these imaging methods in the evaluation of soft tissues is lower than magnetic resonance imaging (MRI). The aim of the study was to show the use of MRI in the evaluation of relation between intraosseous lesions of the jaws and anatomical structures, when it was difficult using the traditional radiographic methods, and to evaluate the usefulness of MRI to depict the morphostructural characterization of the lesions and infiltration of the soft tissues. 10 patients with a lesion of jaw were selected. All the patients underwent panoramic radiography (OPT), CT and MRI. The images were examined by dental and maxillofacial radiology who compared the different imaging methods to analyze the morphological and structural characteristics of the lesion and assessed the relationship between the lesion and the anatomical structures. Magnetic resonance imaging provided more detailed spatial and structural information than other imaging methods. MRI allowed us to characterize the intraosseous lesions of the jaws and to plan the surgery, resulting in a lower risk of anatomic structures surgical injury.

Atlas-Guided Segmentation of Vervet Monkey Brain MRI

PubMed Central

Fedorov, Andriy; Li, Xiaoxing; Pohl, Kilian M; Bouix, Sylvain; Styner, Martin; Addicott, Merideth; Wyatt, Chris; Daunais, James B; Wells, William M; Kikinis, Ron

2011-01-01

The vervet monkey is an important nonhuman primate model that allows the study of isolated environmental factors in a controlled environment. Analysis of monkey MRI often suffers from lower quality images compared with human MRI because clinical equipment is typically used to image the smaller monkey brain and higher spatial resolution is required. This, together with the anatomical differences of the monkey brains, complicates the use of neuroimage analysis pipelines tuned for human MRI analysis. In this paper we developed an open source image analysis framework based on the tools available within the 3D Slicer software to support a biological study that investigates the effect of chronic ethanol exposure on brain morphometry in a longitudinally followed population of male vervets. We first developed a computerized atlas of vervet monkey brain MRI, which was used to encode the typical appearance of the individual brain structures in MRI and their spatial distribution. The atlas was then used as a spatial prior during automatic segmentation to process two longitudinal scans per subject. Our evaluation confirms the consistency and reliability of the automatic segmentation. The comparison of atlas construction strategies reveals that the use of a population-specific atlas leads to improved accuracy of the segmentation for subcortical brain structures. The contribution of this work is twofold. First, we describe an image processing workflow specifically tuned towards the analysis of vervet MRI that consists solely of the open source software tools. Second, we develop a digital atlas of vervet monkey brain MRIs to enable similar studies that rely on the vervet model. PMID:22253661

Functional and structural abnormalities associated with empathy in patients with schizophrenia: An fMRI and VBM study

PubMed Central

Singh, Sadhana; Modi, Shilpi; Goyal, Satnam; Kaur, Prabhjot; Singh, Namita; Bhatia, Triptish; Deshpande, Smita N; Khushu, Subash

2016-01-01

Empathy deficit is a core feature of schizophrenia which may lead to social dysfunction. The present study was carried out to investigate functional and structural abnormalities associated with empathy in patients with schizophrenia using functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM). A sample of 14 schizophrenia patients and 14 healthy control subjects matched for age, sex and education were examined with structural high-resolution T1-weighted MRI; fMRI images were obtained during empathy task in the same session. The analysis was carried out using SPM8 software. On behavioural assessment, schizophrenic patients (83.00±29.04) showed less scores for sadness compared to healthy controls (128.70±22.26) (p<0.001). fMRI results also showed reduced clusters of activation in the bilateral fusiform gyrus, left lingual gyrus, left middle and inferior occipital gyrus in schizophrenic subjects as compared to controls during empathy task. In the same brain areas, VBM results also showed reduced grey and white matter volumes. The present study provides an evidence for an association between structural alterations and disturbed functional brain activation during empathy task in persons affected with schizophrenia. These findings suggest a biological basis for social cognition deficits in schizophrenics. PMID:25963262

Functional and structural abnormalities associated with empathy in patients with schizophrenia: An fMRI and VBM study.

PubMed

Singh, Sadhana; Modi, Shilpi; Goyal, Satnam; Kaur, Prabhjot; Singh, Namita; Bhatia, Triptish; Deshpande, Smita N; Khushu, Subash

2015-06-01

Empathy deficit is a core feature of schizophrenia which may lead to social dysfunction. The present study was carried out to investigate functional and structural abnormalities associated with empathy in patients with schizophrenia using functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM). A sample of 14 schizophrenia patients and 14 healthy control subjects matched for age, sex and education were examined with structural highresolution T1-weighted MRI; fMRI images were obtained during empathy task in the same session. The analysis was carried out using SPM8 software. On behavioural assessment, schizophrenic patients (83.00+-29.04) showed less scores for sadness compared to healthy controls (128.70+-22.26) (p less than 0.001). fMRI results also showed reduced clusters of activation in the bilateral fusiform gyrus, left lingual gyrus, left middle and inferior occipital gyrus in schizophrenic subjects as compared to controls during empathy task. In the same brain areas, VBM results also showed reduced grey and white matter volumes. The present study provides an evidence for an association between structural alterations and disturbed functional brain activation during empathy task in persons affected with schizophrenia. These findings suggest a biological basis for social cognition deficits in schizophrenics.

A narrative overview of the current status of MRI of the hip and its relevance for osteoarthritis research - what we know, what has changed and where are we going?

PubMed

Crema, M D; Watts, G J; Guermazi, A; Kim, Y-J; Kijowski, R; Roemer, F W

2017-01-01

To review and discuss the role of magnetic resonance imaging (MRI) in the context of hip osteoarthritis (OA) research. The content of this narrative review, based on an extensive PubMed database research including English literature only, describes the advances in MRI of the hip joint and its potential usefulness in hip OA research, reviews the relevance of different MRI features in regard to symptomatic and structural progression in hip OA, and gives an outlook regarding future use of MRI in hip OA research endeavors. Recent technical advances have helped to overcome many of the past difficulties related to MRI assessment of hip OA. MRI-based morphologic scoring systems allow for detailed assessment of several hip joint tissues and, in combination with the recent advances in MRI, may increase reproducibility and sensitivity to change. Compositional MRI techniques may add to our understanding of disease onset and progression. Knowledge about imaging pitfalls and anatomical variants is crucial to avoid misinterpretation. In comparison to research on knee OA, the associations between MRI features and the incidence and progression of disease as well as with clinical symptoms have been little explored. Anatomic alterations of the hip joint as seen in femoro-acetabular impingement (FAI) seem to play a role in the onset and progression of structural damage. With the technical advances occurring in recent years, MRI may play a major role in investigating the natural history of hip OA and provide an improved method for assessment of the efficacy of new therapeutic approaches. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

RAPID COMMUNICATION: Magnetic resonance imaging inside metallic vessels

NASA Astrophysics Data System (ADS)

Han, Hui; Balcom, Bruce J.

2010-10-01

We introduce magnetic resonance imaging (MRI) measurements inside metallic vessels. Until now, MRI has been unusable inside metallic vessels because of eddy currents in the walls. We have solved the problem and generated high quality images by employing a magnetic field gradient monitoring method. The ability to image within metal enclosures and structures means many new samples and systems are now amenable to MRI. Most importantly this study will form the basis of new MRI-compatible metallic pressure vessels, which will permit MRI of macroscopic systems at high pressure.

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.

A guide for effective anatomical vascularization studies: useful ex vivo methods for both CT and MRI imaging before dissection.

PubMed

Renard, Yohann; Hossu, Gabriela; Chen, Bailiang; Krebs, Marine; Labrousse, Marc; Perez, Manuela

2018-01-01

The objective of this study was to develop a simple and useful injection protocol for imaging cadaveric vascularization and dissection. Mixtures of contrast agent and cast product should provide adequate contrast for two types of ex vivo imaging (MRI and CT) and should harden to allow gross dissection of the injected structures. We tested the most popular contrast agents and cast products, and selected the optimal mixture composition based on their availability and ease of use. All mixtures were first tested in vitro to adjust dilution parameters of each contrast agent and to fine-tune MR imaging acquisition sequences. Mixtures were then injected in 24 pig livers and one human pancreas for MR and computed tomography (CT) imaging before anatomical dissection. Colorized latex, gadobutrol and barite mixture met the above objective. Mixtures composed of copper sulfate (CuSO 4 ) gadoxetic acid (for MRI) and iodine (for CT) gave an inhomogeneous signal or extravasation of the contrast agent. Agar did not harden sufficiently for gross dissection but appears useful for CT and magnetic resonance imaging (MRI) studies without dissection. Silicone was very hard to inject but achieved the goals of the study. Resin is particularly difficult to use but could replace latex as an alternative for corrosion instead of dissection. This injection protocol allows CT and MRI images to be obtained of cadaveric vascularization and anatomical casts in the same anatomic specimen. Post-imaging processing software allow easy 3D reconstruction of complex anatomical structures using this technique. Applications are numerous, e.g. surgical training, teaching methods, postmortem anatomic studies, pathologic studies, and forensic diagnoses. © 2017 Anatomical Society.

Improving Brain Magnetic Resonance Image (MRI) Segmentation via a Novel Algorithm based on Genetic and Regional Growth

PubMed Central

A., Javadpour; A., Mohammadi

2016-01-01

Background Regarding the importance of right diagnosis in medical applications, various methods have been exploited for processing medical images solar. The method of segmentation is used to analyze anal to miscall structures in medical imaging. Objective This study describes a new method for brain Magnetic Resonance Image (MRI) segmentation via a novel algorithm based on genetic and regional growth. Methods Among medical imaging methods, brains MRI segmentation is important due to high contrast of non-intrusive soft tissue and high spatial resolution. Size variations of brain tissues are often accompanied by various diseases such as Alzheimer’s disease. As our knowledge about the relation between various brain diseases and deviation of brain anatomy increases, MRI segmentation is exploited as the first step in early diagnosis. In this paper, regional growth method and auto-mate selection of initial points by genetic algorithm is used to introduce a new method for MRI segmentation. Primary pixels and similarity criterion are automatically by genetic algorithms to maximize the accuracy and validity in image segmentation. Results By using genetic algorithms and defining the fixed function of image segmentation, the initial points for the algorithm were found. The proposed algorithms are applied to the images and results are manually selected by regional growth in which the initial points were compared. The results showed that the proposed algorithm could reduce segmentation error effectively. Conclusion The study concluded that the proposed algorithm could reduce segmentation error effectively and help us to diagnose brain diseases. PMID:27672629

Three-Dimensional Magnetic Resonance Imaging of Velopharyngeal Structures

ERIC Educational Resources Information Center

Bae, Youkyung; Kuehn, David P.; Sutton, Bradley P.; Conway, Charles A.; Perry, Jamie L.

2011-01-01

Purpose: To report the feasibility of using a 3-dimensional (3D) magnetic resonance imaging (MRI) protocol for examining velopharyngeal structures. Using collected 3D MRI data, the authors investigated the effect of sex on the midsagittal velopharyngeal structures and the levator veli palatini (levator) muscle configurations. Method: Ten Caucasian…

The usefulness of (18)F-FDG PET/MRI fusion image in diagnosing pancreatic tumor: comparison with (18)F-FDG PET/CT.

PubMed

Nagamachi, Shigeki; Nishii, Ryuichi; Wakamatsu, Hideyuki; Mizutani, Youichi; Kiyohara, Shogo; Fujita, Seigo; Futami, Shigemi; Sakae, Tatefumi; Furukoji, Eiji; Tamura, Shozo; Arita, Hideo; Chijiiwa, Kazuo; Kawai, Keiichi

2013-07-01

This study aimed at demonstrating the feasibility of retrospectively fused (18)F FDG-PET and MRI (PET/MRI fusion image) in diagnosing pancreatic tumor, in particular differentiating malignant tumor from benign lesions. In addition, we evaluated additional findings characterizing pancreatic lesions by FDG-PET/MRI fusion image. We analyzed retrospectively 119 patients: 96 cancers and 23 benign lesions. FDG-PET/MRI fusion images (PET/T1 WI or PET/T2WI) were made by dedicated software using 1.5 Tesla (T) MRI image and FDG-PET images. These images were interpreted by two well-trained radiologists without knowledge of clinical information and compared with FDG-PET/CT images. We compared the differential diagnostic capability between PET/CT and FDG-PET/MRI fusion image. In addition, we evaluated additional findings such as tumor structure and tumor invasion. FDG-PET/MRI fusion image significantly improved accuracy compared with that of PET/CT (96.6 vs. 86.6 %). As additional finding, dilatation of main pancreatic duct was noted in 65.9 % of solid types and in 22.6 % of cystic types, on PET/MRI-T2 fusion image. Similarly, encasement of adjacent vessels was noted in 43.1 % of solid types and in 6.5 % of cystic types. Particularly in cystic types, intra-tumor structures such as mural nodule (35.4 %) or intra-cystic septum (74.2 %) were detected additionally. Besides, PET/MRI-T2 fusion image could detect extra benign cystic lesions (9.1 % in solid type and 9.7 % in cystic type) that were not noted by PET/CT. In diagnosing pancreatic lesions, FDG-PET/MRI fusion image was useful in differentiating pancreatic cancer from benign lesions. Furthermore, it was helpful in evaluating relationship between lesions and surrounding tissues as well as in detecting extra benign cysts.

Use of Brain MRI Atlases to Determine Boundaries of Age-Related Pathology: The Importance of Statistical Method

PubMed Central

Dickie, David Alexander; Job, Dominic E.; Gonzalez, David Rodriguez; Shenkin, Susan D.; Wardlaw, Joanna M.

2015-01-01

Introduction Neurodegenerative disease diagnoses may be supported by the comparison of an individual patient’s brain magnetic resonance image (MRI) with a voxel-based atlas of normal brain MRI. Most current brain MRI atlases are of young to middle-aged adults and parametric, e.g., mean ±standard deviation (SD); these atlases require data to be Gaussian. Brain MRI data, e.g., grey matter (GM) proportion images, from normal older subjects are apparently not Gaussian. We created a nonparametric and a parametric atlas of the normal limits of GM proportions in older subjects and compared their classifications of GM proportions in Alzheimer’s disease (AD) patients. Methods Using publicly available brain MRI from 138 normal subjects and 138 subjects diagnosed with AD (all 55–90 years), we created: a mean ±SD atlas to estimate parametrically the percentile ranks and limits of normal ageing GM; and, separately, a nonparametric, rank order-based GM atlas from the same normal ageing subjects. GM images from AD patients were then classified with respect to each atlas to determine the effect statistical distributions had on classifications of proportions of GM in AD patients. Results The parametric atlas often defined the lower normal limit of the proportion of GM to be negative (which does not make sense physiologically as the lowest possible proportion is zero). Because of this, for approximately half of the AD subjects, 25–45% of voxels were classified as normal when compared to the parametric atlas; but were classified as abnormal when compared to the nonparametric atlas. These voxels were mainly concentrated in the frontal and occipital lobes. Discussion To our knowledge, we have presented the first nonparametric brain MRI atlas. In conditions where there is increasing variability in brain structure, such as in old age, nonparametric brain MRI atlases may represent the limits of normal brain structure more accurately than parametric approaches. Therefore, we conclude that the statistical method used for construction of brain MRI atlases should be selected taking into account the population and aim under study. Parametric methods are generally robust for defining central tendencies, e.g., means, of brain structure. Nonparametric methods are advisable when studying the limits of brain structure in ageing and neurodegenerative disease. PMID:26023913

Neuroimaging in epilepsy.

PubMed

Sidhu, Meneka Kaur; Duncan, John S; Sander, Josemir W

2018-05-17

Epilepsy neuroimaging is important for detecting the seizure onset zone, predicting and preventing deficits from surgery and illuminating mechanisms of epileptogenesis. An aspiration is to integrate imaging and genetic biomarkers to enable personalized epilepsy treatments. The ability to detect lesions, particularly focal cortical dysplasia and hippocampal sclerosis, is increased using ultra high-field imaging and postprocessing techniques such as automated volumetry, T2 relaxometry, voxel-based morphometry and surface-based techniques. Statistical analysis of PET and single photon emission computer tomography (STATISCOM) are superior to qualitative analysis alone in identifying focal abnormalities in MRI-negative patients. These methods have also been used to study mechanisms of epileptogenesis and pharmacoresistance.Recent language fMRI studies aim to localize, and also lateralize language functions. Memory fMRI has been recommended to lateralize mnemonic function and predict outcome after surgery in temporal lobe epilepsy. Combinations of structural, functional and post-processing methods have been used in multimodal and machine learning models to improve the identification of the seizure onset zone and increase understanding of mechanisms underlying structural and functional aberrations in epilepsy.

Bold-Independent Computational Entropy Assesses Functional Donut-Like Structures in Brain fMRI Images

PubMed Central

Peters, James F.; Ramanna, Sheela; Tozzi, Arturo; İnan, Ebubekir

2017-01-01

We introduce a novel method for the measurement of information level in fMRI (functional Magnetic Resonance Imaging) neural data sets, based on image subdivision in small polygons equipped with different entropic content. We show how this method, called maximal nucleus clustering (MNC), is a novel, fast and inexpensive image-analysis technique, independent from the standard blood-oxygen-level dependent signals. MNC facilitates the objective detection of hidden temporal patterns of entropy/information in zones of fMRI images generally not taken into account by the subjective standpoint of the observer. This approach befits the geometric character of fMRIs. The main purpose of this study is to provide a computable framework for fMRI that not only facilitates analyses, but also provides an easily decipherable visualization of structures. This framework commands attention because it is easily implemented using conventional software systems. In order to evaluate the potential applications of MNC, we looked for the presence of a fourth dimension's distinctive hallmarks in a temporal sequence of 2D images taken during spontaneous brain activity. Indeed, recent findings suggest that several brain activities, such as mind-wandering and memory retrieval, might take place in the functional space of a four dimensional hypersphere, which is a double donut-like structure undetectable in the usual three dimensions. We found that the Rényi entropy is higher in MNC areas than in the surrounding ones, and that these temporal patterns closely resemble the trajectories predicted by the possible presence of a hypersphere in the brain. PMID:28203153

Bold-Independent Computational Entropy Assesses Functional Donut-Like Structures in Brain fMRI Images.

PubMed

Peters, James F; Ramanna, Sheela; Tozzi, Arturo; İnan, Ebubekir

2017-01-01

We introduce a novel method for the measurement of information level in fMRI (functional Magnetic Resonance Imaging) neural data sets, based on image subdivision in small polygons equipped with different entropic content. We show how this method, called maximal nucleus clustering (MNC), is a novel, fast and inexpensive image-analysis technique, independent from the standard blood-oxygen-level dependent signals. MNC facilitates the objective detection of hidden temporal patterns of entropy/information in zones of fMRI images generally not taken into account by the subjective standpoint of the observer. This approach befits the geometric character of fMRIs. The main purpose of this study is to provide a computable framework for fMRI that not only facilitates analyses, but also provides an easily decipherable visualization of structures. This framework commands attention because it is easily implemented using conventional software systems. In order to evaluate the potential applications of MNC, we looked for the presence of a fourth dimension's distinctive hallmarks in a temporal sequence of 2D images taken during spontaneous brain activity. Indeed, recent findings suggest that several brain activities, such as mind-wandering and memory retrieval, might take place in the functional space of a four dimensional hypersphere, which is a double donut-like structure undetectable in the usual three dimensions. We found that the Rényi entropy is higher in MNC areas than in the surrounding ones, and that these temporal patterns closely resemble the trajectories predicted by the possible presence of a hypersphere in the brain.

Automatic segmentation of left ventricle in cardiac cine MRI images based on deep learning

NASA Astrophysics Data System (ADS)

Zhou, Tian; Icke, Ilknur; Dogdas, Belma; Parimal, Sarayu; Sampath, Smita; Forbes, Joseph; Bagchi, Ansuman; Chin, Chih-Liang; Chen, Antong

2017-02-01

In developing treatment of cardiovascular diseases, short axis cine MRI has been used as a standard technique for understanding the global structural and functional characteristics of the heart, e.g. ventricle dimensions, stroke volume and ejection fraction. To conduct an accurate assessment, heart structures need to be segmented from the cine MRI images with high precision, which could be a laborious task when performed manually. Herein a fully automatic framework is proposed for the segmentation of the left ventricle from the slices of short axis cine MRI scans of porcine subjects using a deep learning approach. For training the deep learning models, which generally requires a large set of data, a public database of human cine MRI scans is used. Experiments on the 3150 cine slices of 7 porcine subjects have shown that when comparing the automatic and manual segmentations the mean slice-wise Dice coefficient is about 0.930, the point-to-curve error is 1.07 mm, and the mean slice-wise Hausdorff distance is around 3.70 mm, which demonstrates the accuracy and robustness of the proposed inter-species translational approach.

Visualisation of the Bonebridge by means of CT and CBCT

PubMed Central

2013-01-01

Background With the Bonebridge, a new bone-anchored hearing aid has been available since March 2012. The objective of the study was to analyse the visualisation of the implant itself as well as its impact on the representation of the bony structures of the petrosal bone in CT, MRI and cone beam CT (CBCT). Methods The Bonebridge was implanted unilaterally in two completely prepared human heads. The radiological imaging by means of CBCT, 64-slice CT, 1.5-T and 3.0-T MRI was conducted both preoperatively and postoperatively. The images were subsequently evaluated from both the ENT medical and nd radiological perspectives. Results As anticipated, no visualisation of the implant or of the petrosal bones could be realised on MRI because of the interactive technology and the magnet artefact. In contrast, an excellent evaluability of the implant itself as well as of the surrounding neurovascular structures (sinus sigmoideus, skull base, middle ear, inner ear, inner auditory canal) was exhibited in both the CT and in the CBCT. Conclusion The Bonebridge can be excellently imaged with the radiological imaging technologies of CT and CBCT. In the process, CBCT shows discrete advantages in comparison with CT. No relevant restrictions in image quality in the evaluation of the bony structures of the petrosal bones could be seen. PMID:24004903

The role of magnetic resonance imaging techniques in evaluation and management of the idiopathic inflammatory myopathies.

PubMed

Day, Jessica; Patel, Sandy; Limaye, Vidya

2017-04-01

Magnetic resonance imaging (MRI) is an important tool in the evaluation of neuromuscular disorders. MRI accurately demonstrates muscle oedema, atrophy, subcutaneous pathology and fatty infiltration and also highlights the distribution of muscle involvement. This review examines the role of MRI in evaluation of the idiopathic inflammatory myopathies (IIMs), a heterogeneous group of autoimmune conditions characterised by muscle inflammation and a variety of extra-muscular manifestations. MRI has a clear role in aiding diagnosis of these conditions, guiding muscle biopsy, differentiating subtypes of IIM using a pattern-based approach, and monitoring disease activity in a longitudinal fashion. Whole body MRI is an emerging technique that offers several advantages over regional MRI, but is not currently widely available. We will also consider newer MRI techniques which provide detailed information regarding the metabolism, function and structure of muscle, although their use is restricted to research purposes at present. Copyright © 2017 Elsevier Inc. All rights reserved.

Diagnosis of pulmonary hypertension from magnetic resonance imaging-based computational models and decision tree analysis.

PubMed

Lungu, Angela; Swift, Andrew J; Capener, David; Kiely, David; Hose, Rod; Wild, Jim M

2016-06-01

Accurately identifying patients with pulmonary hypertension (PH) using noninvasive methods is challenging, and right heart catheterization (RHC) is the gold standard. Magnetic resonance imaging (MRI) has been proposed as an alternative to echocardiography and RHC in the assessment of cardiac function and pulmonary hemodynamics in patients with suspected PH. The aim of this study was to assess whether machine learning using computational modeling techniques and image-based metrics of PH can improve the diagnostic accuracy of MRI in PH. Seventy-two patients with suspected PH attending a referral center underwent RHC and MRI within 48 hours. Fifty-seven patients were diagnosed with PH, and 15 had no PH. A number of functional and structural cardiac and cardiovascular markers derived from 2 mathematical models and also solely from MRI of the main pulmonary artery and heart were integrated into a classification algorithm to investigate the diagnostic utility of the combination of the individual markers. A physiological marker based on the quantification of wave reflection in the pulmonary artery was shown to perform best individually, but optimal diagnostic performance was found by the combination of several image-based markers. Classifier results, validated using leave-one-out cross validation, demonstrated that combining computation-derived metrics reflecting hemodynamic changes in the pulmonary vasculature with measurement of right ventricular morphology and function, in a decision support algorithm, provides a method to noninvasively diagnose PH with high accuracy (92%). The high diagnostic accuracy of these MRI-based model parameters may reduce the need for RHC in patients with suspected PH.

Image fusion pitfalls for cranial radiosurgery

PubMed Central

Jonker, Benjamin P.

2013-01-01

Stereotactic radiosurgery requires imaging to define both the stereotactic space in which the treatment is delivered and the target itself. Image fusion is the process of using rotation and translation to bring a second image set into alignment with the first image set. This allows the potential concurrent use of multiple image sets to define the target and stereotactic space. While a single magnetic resonance imaging (MRI) sequence alone can be used for delineation of the target and fiducials, there may be significant advantages to using additional imaging sets including other MRI sequences, computed tomography (CT) scans, and advanced imaging sets such as catheter-based angiography, diffusor tension imaging-based fiber tracking and positon emission tomography in order to more accurately define the target and surrounding critical structures. Stereotactic space is usually defined by detection of fiducials on the stereotactic head frame or mask system. Unfortunately MRI sequences are susceptible to geometric distortion, whereas CT scans do not face this problem (although they have poorer resolution of the target in most cases). Thus image fusion can allow the definition of stereotactic space to proceed from the geometrically accurate CT images at the same time as using MRI to define the target. The use of image fusion is associated with risk of error introduced by inaccuracies of the fusion process, as well as workflow changes that if not properly accounted for can mislead the treating clinician. The purpose of this review is to describe the uses of image fusion in stereotactic radiosurgery as well as its potential pitfalls. PMID:23682338

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.

A wavelet-based statistical analysis of FMRI data: I. motivation and data distribution modeling.

PubMed

Dinov, Ivo D; Boscardin, John W; Mega, Michael S; Sowell, Elizabeth L; Toga, Arthur W

2005-01-01

We propose a new method for statistical analysis of functional magnetic resonance imaging (fMRI) data. The discrete wavelet transformation is employed as a tool for efficient and robust signal representation. We use structural magnetic resonance imaging (MRI) and fMRI to empirically estimate the distribution of the wavelet coefficients of the data both across individuals and spatial locations. An anatomical subvolume probabilistic atlas is used to tessellate the structural and functional signals into smaller regions each of which is processed separately. A frequency-adaptive wavelet shrinkage scheme is employed to obtain essentially optimal estimations of the signals in the wavelet space. The empirical distributions of the signals on all the regions are computed in a compressed wavelet space. These are modeled by heavy-tail distributions because their histograms exhibit slower tail decay than the Gaussian. We discovered that the Cauchy, Bessel K Forms, and Pareto distributions provide the most accurate asymptotic models for the distribution of the wavelet coefficients of the data. Finally, we propose a new model for statistical analysis of functional MRI data using this atlas-based wavelet space representation. In the second part of our investigation, we will apply this technique to analyze a large fMRI dataset involving repeated presentation of sensory-motor response stimuli in young, elderly, and demented subjects.

Decision forests for learning prostate cancer probability maps from multiparametric MRI

NASA Astrophysics Data System (ADS)

Ehrenberg, Henry R.; Cornfeld, Daniel; Nawaf, Cayce B.; Sprenkle, Preston C.; Duncan, James S.

2016-03-01

Objectives: Advances in multiparametric magnetic resonance imaging (mpMRI) and ultrasound/MRI fusion imaging offer a powerful alternative to the typical undirected approach to diagnosing prostate cancer. However, these methods require the time and expertise needed to interpret mpMRI image scenes. In this paper, a machine learning framework for automatically detecting and localizing cancerous lesions within the prostate is developed and evaluated. Methods: Two studies were performed to gather MRI and pathology data. The 12 patients in the first study underwent an MRI session to obtain structural, diffusion-weighted, and dynamic contrast enhanced image vol- umes of the prostate, and regions suspected of being cancerous from the MRI data were manually contoured by radiologists. Whole-mount slices of the prostate were obtained for the patients in the second study, in addition to structural and diffusion-weighted MRI data, for pathology verification. A 3-D feature set for voxel-wise appear- ance description combining intensity data, textural operators, and zonal approximations was generated. Voxels in a test set were classified as normal or cancer using a decision forest-based model initialized using Gaussian discriminant analysis. A leave-one-patient-out cross-validation scheme was used to assess the predictions against the expert manual segmentations confirmed as cancer by biopsy. Results: We achieved an area under the average receiver-operator characteristic curve of 0.923 for the first study, and visual assessment of the probability maps showed 21 out of 22 tumors were identified while a high level of specificity was maintained. In addition to evaluating the model against related approaches, the effects of the individual MRI parameter types were explored, and pathological verification using whole-mount slices from the second study was performed. Conclusions: The results of this paper show that the combination of mpMRI and machine learning is a powerful tool for quantitatively diagnosing prostate cancer.

Comparison of SPECT/CT, MRI and CT in diagnosis of skull base bone invasion in nasopharyngeal carcinoma.

PubMed

Zhang, Shu-xu; Han, Peng-hui; Zhang, Guo-qian; Wang, Rui-hao; Ge, Yong-bin; Ren, Zhi-gang; Li, Jian-sheng; Fu, Wen-hai

2014-01-01

Early detection of skull base invasion in nasopharyngeal carcinoma (NPC) is crucial for correct staging, assessing treatment response and contouring the tumor target in radiotherapy planning, as well as improving the patient's prognosis. To compare the diagnostic efficacy of single photon emission computed tomography/computed tomography (SPECT/CT) imaging, magnetic resonance imaging (MRI) and computed tomography (CT) for the detection of skull base invasion in NPC. Sixty untreated patients with histologically proven NPC underwent SPECT/CT imaging, contrast-enhanced MRI and CT. Of the 60 patients, 30 had skull base invasion confirmed by the final results of contrast-enhanced MRI, CT and six-month follow-up imaging (MRI and CT). The diagnostic efficacy of the three imaging modalities in detecting skull base invasion was evaluated. The rates of positive findings of skull base invasion for SPECT/CT, MRI and CT were 53.3%, 48.3% and 33.3%, respectively. The sensitivity, specificity and accuracy were 93.3%, 86.7% and 90.0% for SPECT/CT fusion imaging, 96.7%, 100.0% and 98.3% for contrast-enhanced MRI, and 66.7%, 100.0% and 83.3% for contrast-enhanced CT. MRI showed the best performance for the diagnosis of skull base invasion in nasopharyngeal carcinoma, followed closely by SPECT/CT. SPECT/CT had poorer specificity than that of both MRI and CT, while CT had the lowest sensitivity.

Recognition of upper airway and surrounding structures at MRI in pediatric PCOS and OSAS

NASA Astrophysics Data System (ADS)

Tong, Yubing; Udupa, J. K.; Odhner, D.; Sin, Sanghun; Arens, Raanan

2013-03-01

Obstructive Sleep Apnea Syndrome (OSAS) is common in obese children with risk being 4.5 fold compared to normal control subjects. Polycystic Ovary Syndrome (PCOS) has recently been shown to be associated with OSAS that may further lead to significant cardiovascular and neuro-cognitive deficits. We are investigating image-based biomarkers to understand the architectural and dynamic changes in the upper airway and the surrounding hard and soft tissue structures via MRI in obese teenage children to study OSAS. At the previous SPIE conferences, we presented methods underlying Fuzzy Object Models (FOMs) for Automatic Anatomy Recognition (AAR) based on CT images of the thorax and the abdomen. The purpose of this paper is to demonstrate that the AAR approach is applicable to a different body region and image modality combination, namely in the study of upper airway structures via MRI. FOMs were built hierarchically, the smaller sub-objects forming the offspring of larger parent objects. FOMs encode the uncertainty and variability present in the form and relationships among the objects over a study population. Totally 11 basic objects (17 including composite) were modeled. Automatic recognition for the best pose of FOMs in a given image was implemented by using four methods - a one-shot method that does not require search, another three searching methods that include Fisher Linear Discriminate (FLD), a b-scale energy optimization strategy, and optimum threshold recognition method. In all, 30 multi-fold cross validation experiments based on 15 patient MRI data sets were carried out to assess the accuracy of recognition. The results indicate that the objects can be recognized with an average location error of less than 5 mm or 2-3 voxels. Then the iterative relative fuzzy connectedness (IRFC) algorithm was adopted for delineation of the target organs based on the recognized results. The delineation results showed an overall FP and TP volume fraction of 0.02 and 0.93.

The Relationship Between the Evolution of an Internal Structure and Drug Dissolution from Controlled-Release Matrix Tablets.

PubMed

Kulinowski, Piotr; Hudy, Wiktor; Mendyk, Aleksander; Juszczyk, Ewelina; Węglarz, Władysław P; Jachowicz, Renata; Dorożyński, Przemysław

2016-06-01

In the last decade, imaging has been introduced as a supplementary method to the dissolution tests, but a direct relationship of dissolution and imaging data has been almost completely overlooked. The purpose of this study was to assess the feasibility of relating magnetic resonance imaging (MRI) and dissolution data to elucidate dissolution profile features (i.e., kinetics, kinetics changes, and variability). Commercial, hydroxypropylmethyl cellulose-based quetiapine fumarate controlled-release matrix tablets were studied using the following two methods: (i) MRI inside the USP4 apparatus with subsequent machine learning-based image segmentation and (ii) dissolution testing with piecewise dissolution modeling. Obtained data were analyzed together using statistical data processing methods, including multiple linear regression. As a result, in this case, zeroth order release was found to be a consequence of internal structure evolution (interplay between region's areas-e.g., linear relationship between interface and core), which eventually resulted in core disappearance. Dry core disappearance had an impact on (i) changes in dissolution kinetics (from zeroth order to nonlinear) and (ii) an increase in variability of drug dissolution results. It can be concluded that it is feasible to parameterize changes in micro/meso morphology of hydrated, controlled release, swellable matrices using MRI to establish a causal relationship between the changes in morphology and drug dissolution. Presented results open new perspectives in practical application of combined MRI/dissolution to controlled-release drug products.

Diffusion MRI and its role in neuropsychology

PubMed Central

Mueller, Bryon A; Lim, Kelvin O; Hemmy, Laura; Camchong, Jazmin

2015-01-01

Diffusion Magnetic Resonance Imaging (dMRI) is a popular method used by neuroscientists to uncover unique information about the structural connections within the brain. dMRI is a non-invasive imaging methodology in which image contrast is based on the diffusion of water molecules in tissue. While applicable to many tissues in the body, this review focuses exclusively on the use of dMRI to examine white matter in the brain. In this review, we begin with a definition of diffusion and how diffusion is measured with MRI. Next we introduce the diffusion tensor model, the predominant model used in dMRI. We then describe acquisition issues related to acquisition parameters and scanner hardware and software. Sources of artifacts are then discussed, followed by a brief review of analysis approaches. We provide an overview of the limitations of the traditional diffusion tensor model, and highlight several more sophisticated non-tensor models that better describe the complex architecture of the brain’s white matter. We then touch on reliability and validity issues of diffusion measurements. Finally, we describe examples of ways in which dMRI has been applied to studies of brain disorders and how identified alterations relate to symptomatology and cognition. PMID:26255305

Implementation of compressive sensing for preclinical cine-MRI

NASA Astrophysics Data System (ADS)

Tan, Elliot; Yang, Ming; Ma, Lixin; Zheng, Yahong Rosa

2014-03-01

This paper presents a practical implementation of Compressive Sensing (CS) for a preclinical MRI machine to acquire randomly undersampled k-space data in cardiac function imaging applications. First, random undersampling masks were generated based on Gaussian, Cauchy, wrapped Cauchy and von Mises probability distribution functions by the inverse transform method. The best masks for undersampling ratios of 0.3, 0.4 and 0.5 were chosen for animal experimentation, and were programmed into a Bruker Avance III BioSpec 7.0T MRI system through method programming in ParaVision. Three undersampled mouse heart datasets were obtained using a fast low angle shot (FLASH) sequence, along with a control undersampled phantom dataset. ECG and respiratory gating was used to obtain high quality images. After CS reconstructions were applied to all acquired data, resulting images were quantitatively analyzed using the performance metrics of reconstruction error and Structural Similarity Index (SSIM). The comparative analysis indicated that CS reconstructed images from MRI machine undersampled data were indeed comparable to CS reconstructed images from retrospective undersampled data, and that CS techniques are practical in a preclinical setting. The implementation achieved 2 to 4 times acceleration for image acquisition and satisfactory quality of image reconstruction.

Image Restoration Using Functional and Anatomical Information Fusion with Application to SPECT-MRI Images

PubMed Central

Benameur, S.; Mignotte, M.; Meunier, J.; Soucy, J. -P.

2009-01-01

Image restoration is usually viewed as an ill-posed problem in image processing, since there is no unique solution associated with it. The quality of restored image closely depends on the constraints imposed of the characteristics of the solution. In this paper, we propose an original extension of the NAS-RIF restoration technique by using information fusion as prior information with application in SPECT medical imaging. That extension allows the restoration process to be constrained by efficiently incorporating, within the NAS-RIF method, a regularization term which stabilizes the inverse solution. Our restoration method is constrained by anatomical information extracted from a high resolution anatomical procedure such as magnetic resonance imaging (MRI). This structural anatomy-based regularization term uses the result of an unsupervised Markovian segmentation obtained after a preliminary registration step between the MRI and SPECT data volumes from each patient. This method was successfully tested on 30 pairs of brain MRI and SPECT acquisitions from different subjects and on Hoffman and Jaszczak SPECT phantoms. The experiments demonstrated that the method performs better, in terms of signal-to-noise ratio, than a classical supervised restoration approach using a Metz filter. PMID:19812704

Multiresolution texture models for brain tumor segmentation in MRI.

PubMed

Iftekharuddin, Khan M; Ahmed, Shaheen; Hossen, Jakir

2011-01-01

In this study we discuss different types of texture features such as Fractal Dimension (FD) and Multifractional Brownian Motion (mBm) for estimating random structures and varying appearance of brain tissues and tumors in magnetic resonance images (MRI). We use different selection techniques including KullBack - Leibler Divergence (KLD) for ranking different texture and intensity features. We then exploit graph cut, self organizing maps (SOM) and expectation maximization (EM) techniques to fuse selected features for brain tumors segmentation in multimodality T1, T2, and FLAIR MRI. We use different similarity metrics to evaluate quality and robustness of these selected features for tumor segmentation in MRI for real pediatric patients. We also demonstrate a non-patient-specific automated tumor prediction scheme by using improved AdaBoost classification based on these image features.

Ameliorating slice gaps in multislice magnetic resonance images: an interpolation scheme.

PubMed

Kashou, Nasser H; Smith, Mark A; Roberts, Cynthia J

2015-01-01

Standard two-dimension (2D) magnetic resonance imaging (MRI) clinical acquisition protocols utilize orthogonal plane images which contain slice gaps (SG). The purpose of this work is to introduce a novel interpolation method for these orthogonal plane MRI 2D datasets. Three goals can be achieved: (1) increasing the resolution based on a priori knowledge of scanning protocol, (2) ameliorating the loss of data as a result of SG and (3) reconstructing a three-dimension (3D) dataset from 2D images. MRI data was collected using a 3T GE scanner and simulated using Matlab. The procedure for validating the MRI data combination algorithm was performed using a Shepp-Logan and a Gaussian phantom in both 2D and 3D of varying matrix sizes (64-512), as well as on one MRI dataset of a human brain and on an American College of Radiology magnetic resonance accreditation phantom. The squared error and mean squared error were computed in comparing this scheme to common interpolating functions employed in MR consoles and workstations. The mean structure similarity matrix was computed in 2D as a means of qualitative image assessment. Additionally, MRI scans were used for qualitative assessment of the method. This new scheme was consistently more accurate than upsampling each orientation separately and averaging the upsampled data. An efficient new interpolation approach to resolve SG was developed. This scheme effectively fills in the missing data points by using orthogonal plane images. To date, there have been few attempts to combine the information of three MRI plane orientations using brain images. This has specific applications for clinical MRI, functional MRI, diffusion-weighted imaging/diffusion tensor imaging and MR angiography where 2D slice acquisition are used. In these cases, the 2D data can be combined using our method in order to obtain 3D volume.

Normal feline brain: clinical anatomy using magnetic resonance imaging.

PubMed

Mogicato, G; Conchou, F; Layssol-Lamour, C; Raharison, F; Sautet, J

2012-04-01

The purpose of this study was to provide a clinical anatomy atlas of the feline brain using magnetic resonance imaging (MRI). Brains of twelve normal cats were imaged using a 1.5 T magnetic resonance unit and an inversion/recovery sequence (T1). Fourteen relevant MRI sections were chosen in transverse, dorsal, median and sagittal planes. Anatomic structures were identified and labelled using anatomical texts and Nomina Anatomica Veterinaria, sectioned specimen heads, and previously published articles. The MRI sections were stained according to the major embryological and anatomical subdivisions of the brain. The relevant anatomical structures seen on MRI will assist clinicians to better understand MR images and to relate this neuro-anatomy to clinical signs. © 2011 Blackwell Verlag GmbH.

Cross-sectional anatomy, computed tomography and magnetic resonance imaging of the head of common dolphin (Delphinus delphis) and striped dolphin (Stenella coeruleoalba).

PubMed

Alonso-Farré, J M; Gonzalo-Orden, M; Barreiro-Vázquez, J D; Barreiro-Lois, A; André, M; Morell, M; Llarena-Reino, M; Monreal-Pawlowsky, T; Degollada, E

2015-02-01

Computed tomography (CT) and low-field magnetic resonance imaging (MRI) were used to scan seven by-caught dolphin cadavers, belonging to two species: four common dolphins (Delphinus delphis) and three striped dolphins (Stenella coeruleoalba). CT and MRI were obtained with the animals in ventral recumbency. After the imaging procedures, six dolphins were frozen at -20°C and sliced in the same position they were examined. Not only CT and MRI scans, but also cross sections of the heads were obtained in three body planes: transverse (slices of 1 cm thickness) in three dolphins, sagittal (5 cm thickness) in two dolphins and dorsal (5 cm thickness) in two dolphins. Relevant anatomical structures were identified and labelled on each cross section, obtaining a comprehensive bi-dimensional topographical anatomy guide of the main features of the common and the striped dolphin head. Furthermore, the anatomical cross sections were compared with their corresponding CT and MRI images, allowing an imaging identification of most of the anatomical features. CT scans produced an excellent definition of the bony and air-filled structures, while MRI allowed us to successfully identify most of the soft tissue structures in the dolphin's head. This paper provides a detailed anatomical description of the head structures of common and striped dolphins and compares anatomical cross sections with CT and MRI scans, becoming a reference guide for the interpretation of imaging studies. © 2014 Blackwell Verlag GmbH.

Magnetization transfer and adiabatic R 1ρ MRI in the brainstem of Parkinson's disease.

PubMed

Tuite, Paul J; Mangia, Silvia; Tyan, Andrew E; Lee, Michael K; Garwood, Michael; Michaeli, Shalom

2012-06-01

In addition to classic midbrain pathology, Parkinson's disease (PD) is accompanied by changes in pontine and medullary brainstem structures. These additional abnormalities may underlie non-motor features as well as play a role in motor disability. Using novel magnetic resonance imaging (MRI) methods based on rotating frame adiabatic R(1ρ) (i.e., measurements of longitudinal relaxation during adiabatic full passage pulses) and modified magnetization transfer (MT) MRI mapping, we sought to identify brainstem alterations in nine individuals with mild-moderate PD (off medication) and ten age-matched controls at 4 T. We discovered significant differences in MRI parameters between midbrain and medullary brainstem structures in control subjects as compared to PD patients. These findings support the presence of underlying functional/structural brainstem changes in mild-moderate PD. Copyright © 2012 Elsevier Ltd. All rights reserved.

Brain Abnormalities in Congenital Fibrosis of the Extraocular Muscles Type 1: A Multimodal MRI Imaging Study

PubMed Central

Wu, Shaoqin; Lv, Bin; Wang, Zhenchang; Xian, Junfang; Sabel, Bernhard A.; He, Huiguang; Jiao, Yonghong

2015-01-01

Purpose To explore the possible brain structural and functional alterations in congenital fibrosis of extraocular muscles type 1 (CFEOM1) patients using multimodal MRI imaging. Methods T1-weighted, diffusion tensor images and functional MRI data were obtained from 9 KIF21A positive patients and 19 age- and gender- matched healthy controls. Voxel based morphometry and tract based spatial statistics were applied to the T1-weighted and diffusion tensor images, respectively. Amplitude of low frequency fluctuations and regional homogeneity were used to process the functional MRI data. We then compared these multimodal characteristics between CFEOM1 patients and healthy controls. Results Compared with healthy controls, CFEOM1 patients demonstrated increased grey matter volume in bilateral frontal orbital cortex and in the right temporal pole. No diffusion indices changes were detected, indicating unaffected white matter microstructure. In addition, from resting state functional MRI data, trend of amplitude of low-frequency fluctuations increases were noted in the right inferior parietal lobe and in the right frontal cortex, and a trend of ReHo increase (p<0.001 uncorrected) in the left precentral gyrus, left orbital frontal cortex, temporal pole and cingulate gyrus. Conclusions CFEOM1 patients had structural and functional changes in grey matter, but the white matter was unaffected. These alterations in the brain may be due to the abnormality of extraocular muscles and their innervating nerves. Future studies should consider the possible correlations between brain morphological/functional findings and clinical data, especially pertaining to eye movements, to obtain more precise answers about the role of brain area changes and their functional consequence in CFEOM1. PMID:26186732

Quantitative structure-property relationship (correlation analysis) of phosphonic acid-based chelates in design of MRI contrast agent.

PubMed

Tiwari, Anjani K; Ojha, Himanshu; Kaul, Ankur; Dutta, Anupama; Srivastava, Pooja; Shukla, Gauri; Srivastava, Rakesh; Mishra, Anil K

2009-07-01

Nuclear magnetic resonance imaging is a very useful tool in modern medical diagnostics, especially when gadolinium (III)-based contrast agents are administered to the patient with the aim of increasing the image contrast between normal and diseased tissues. With the use of soft modelling techniques such as quantitative structure-activity relationship/quantitative structure-property relationship after a suitable description of their molecular structure, we have studied a series of phosphonic acid for designing new MRI contrast agent. Quantitative structure-property relationship studies with multiple linear regression analysis were applied to find correlation between different calculated molecular descriptors of the phosphonic acid-based chelating agent and their stability constants. The final quantitative structure-property relationship mathematical models were found as--quantitative structure-property relationship Model for phosphonic acid series (Model 1)--log K(ML) = {5.00243(+/-0.7102)}- MR {0.0263(+/-0.540)}n = 12 l r l = 0.942 s = 0.183 F = 99.165 quantitative structure-property relationship Model for phosphonic acid series (Model 2)--log K(ML) = {5.06280(+/-0.3418)}- MR {0.0252(+/- .198)}n = 12 l r l = 0.956 s = 0.186 F = 99.256.

Structural Image Analysis of the Brain in Neuropsychology Using Magnetic Resonance Imaging (MRI) Techniques.

PubMed

Bigler, Erin D

2015-09-01

Magnetic resonance imaging (MRI) of the brain provides exceptional image quality for visualization and neuroanatomical classification of brain structure. A variety of image analysis techniques provide both qualitative as well as quantitative methods to relate brain structure with neuropsychological outcome and are reviewed herein. Of particular importance are more automated methods that permit analysis of a broad spectrum of anatomical measures including volume, thickness and shape. The challenge for neuropsychology is which metric to use, for which disorder and the timing of when image analysis methods are applied to assess brain structure and pathology. A basic overview is provided as to the anatomical and pathoanatomical relations of different MRI sequences in assessing normal and abnormal findings. Some interpretive guidelines are offered including factors related to similarity and symmetry of typical brain development along with size-normalcy features of brain anatomy related to function. The review concludes with a detailed example of various quantitative techniques applied to analyzing brain structure for neuropsychological outcome studies in traumatic brain injury.

Structural Brain Atlases: Design, Rationale, and Applications in Normal and Pathological Cohorts

PubMed Central

Mandal, Pravat K.; Mahajan, Rashima; Dinov, Ivo D.

2015-01-01

Structural magnetic resonance imaging (MRI) provides anatomical information about the brain in healthy as well as in diseased conditions. On the other hand, functional MRI (fMRI) provides information on the brain activity during performance of a specific task. Analysis of fMRI data requires the registration of the data to a reference brain template in order to identify the activated brain regions. Brain templates also find application in other neuroimaging modalities, such as diffusion tensor imaging and multi-voxel spectroscopy. Further, there are certain differences (e.g., brain shape and size) in the brains of populations of different origin and during diseased conditions like in Alzheimer’s disease (AD), population and disease-specific brain templates may be considered crucial for accurate registration and subsequent analysis of fMRI as well as other neuroimaging data. This manuscript provides a comprehensive review of the history, construction and application of brain atlases. A chronological outline of the development of brain template design, starting from the Talairach and Tournoux atlas to the Chinese brain template (to date), along with their respective detailed construction protocols provides the backdrop to this manuscript. The manuscript also provides the automated workflow-based protocol for designing a population-specific brain atlas from structural MRI data using LONI Pipeline graphical workflow environment. We conclude by discussing the scope of brain templates as a research tool and their application in various neuroimaging modalities. PMID:22647262

A Comparison of Hyperelastic Warping of PET Images with Tagged MRI for the Analysis of Cardiac Deformation

DOE PAGES

Veress, Alexander I.; Klein, Gregory; Gullberg, Grant T.

2013-01-01

Tmore » he objectives of the following research were to evaluate the utility of a deformable image registration technique known as hyperelastic warping for the measurement of local strains in the left ventricle through the analysis of clinical, gated PE image datasets. wo normal human male subjects were sequentially imaged with PE and tagged MRI imaging. Strain predictions were made for systolic contraction using warping analyses of the PE images and HARP based strain analyses of the MRI images. Coefficient of determination R 2 values were computed for the comparison of circumferential and radial strain predictions produced by each methodology. here was good correspondence between the methodologies, with R 2 values of 0.78 for the radial strains of both hearts and from an R 2 = 0.81 and R 2 = 0.83 for the circumferential strains. he strain predictions were not statistically different ( P ≤ 0.01 ) . A series of sensitivity results indicated that the methodology was relatively insensitive to alterations in image intensity, random image noise, and alterations in fiber structure. his study demonstrated that warping was able to provide strain predictions of systolic contraction of the LV consistent with those provided by tagged MRI Warping.« less

Imaging Modalities Relevant to Intracranial Pressure Assessment in Astronauts: A Case-Based Discussion

NASA Technical Reports Server (NTRS)

Sargsyan, Ashot E.; Kramer, Larry A.; Hamilton, Douglas R.; Hamilton, Douglas R.; Fogarty, Jennifer; Polk, J. D.

2010-01-01

Introduction: Intracranial pressure (ICP) elevation has been inferred or documented in a number of space crewmembers. Recent advances in noninvasive imaging technology offer new possibilities for ICP assessment. Most International Space Station (ISS) partner agencies have adopted a battery of occupational health monitoring tests including magnetic resonance imaging (MRI) pre- and postflight, and high-resolution sonography of the orbital structures in all mission phases including during flight. We hypothesize that joint consideration of data from the two techniques has the potential to improve quality and continuity of crewmember monitoring and care. Methods: Specially designed MRI and sonographic protocols were used to image eyes and optic nerves (ON) including the meningeal sheaths. Specific crewmembers multi-modality imaging data were analyzed to identify points of mutual validation as well as unique features of complementary nature. Results and Conclusion: Magnetic resonance imaging (MRI) and high-resolution sonography are both tomographic methods, however images obtained by the two modalities are based on different physical phenomena and use different acquisition principles. Consideration of the images acquired by these two modalities allows cross-validating findings related to the volume and fluid content of the ON subarachnoid space, shape of the globe, and other anatomical features of the orbit. Each of the imaging modalities also has unique advantages, making them complementary techniques.

Simultaneous MRI and PET imaging of a rat brain

NASA Astrophysics Data System (ADS)

Raylman, Raymond R.; Majewski, Stan; Lemieux, Susan K.; Sendhil Velan, S.; Kross, Brian; Popov, Vladimir; Smith, Mark F.; Weisenberger, Andrew G.; Zorn, Carl; Marano, Gary D.

2006-12-01

Multi-modality imaging is rapidly becoming a valuable tool in the diagnosis of disease and in the development of new drugs. Functional images produced with PET fused with anatomical structure images created by MRI will allow the correlation of form with function. Our group is developing a system to acquire MRI and PET images contemporaneously. The prototype device consists of two opposed detector heads, operating in coincidence mode. Each MRI-PET detector module consists of an array of LSO detector elements coupled through a long fibre optic light guide to a single Hamamatsu flat panel position-sensitive photomultiplier tube (PSPMT). The use of light guides allows the PSPMTs to be positioned outside the bore of a 3T MRI scanner where the magnetic field is relatively small. To test the device, simultaneous MRI and PET images of the brain of a male Sprague Dawley rat injected with FDG were successfully obtained. The images revealed no noticeable artefacts in either image set. Future work includes the construction of a full ring PET scanner, improved light guides and construction of a specialized MRI coil to permit higher quality MRI imaging.

Sagittal MRI often overestimates the degree of cerebellar tonsillar ectopia: a potential for misdiagnosis of the Chiari I malformation.

PubMed

Tubbs, R Shane; Yan, Huang; Demerdash, Amin; Chern, Joshua J; Fries, Fabian N; Oskouian, Rod J; Oakes, W Jerry

2016-07-01

We hypothesized that by using coronal MRI, Chiari I malformation could be more precisely diagnosed, would provide simple anatomic landmarks, would provide information regarding asymmetry of hindbrain herniation, and would be a better method for analyzing the tonsillar herniation postoperatively when the opisthion has been removed. Fifty consecutive pediatric patients diagnosed with Chiari I malformation had comparison between the measurements of their caudally descended cerebellar tonsils on midsagittal and coronal MRI images. On MRI coronal imaging, tonsillar asymmetry was found in 48 patients. Maximal left tonsillar descent was 20.9 mm, and maximal right tonsillar descent was 17.4 mm. On MRI sagittal imaging, tonsillar descent ranged from 5 to 27.4 mm. Fifty-eight % of patients had syringomyelia. Five patients (10 %) on coronal MRI were found to have both cerebellar tonsils that were less than 3 mm below the foramen magnum. However, all of these patients had greater than 3 mm of tonsillar ectopia on sagittal imaging. Nineteen patients (38 %) on coronal MRI were found to have one of the cerebellar tonsils that were less than 3 mm below the foramen magnum. Similarly, each of these had greater than 3 mm of tonsillar ecotpia as measured on midsagittal MRI. Also, based on these findings, Chiari I malformation is almost always an asymmetrical tonsillar ectopia. Sagittal MRI overestimates the degree of tonsillar ectopia in patients with Chiari I malformation. Misdiagnosis may occur if sagittal imaging alone is used. The cerebellar tonsils are paramedian structures, and this should be kept in mind when interpreting midline sagittal MRI.

Impact of Virtual and Augmented Reality Based on Intraoperative Magnetic Resonance Imaging and Functional Neuronavigation in Glioma Surgery Involving Eloquent Areas.

PubMed

Sun, Guo-Chen; Wang, Fei; Chen, Xiao-Lei; Yu, Xin-Guang; Ma, Xiao-Dong; Zhou, Ding-Biao; Zhu, Ru-Yuan; Xu, Bai-Nan

2016-12-01

The utility of virtual and augmented reality based on functional neuronavigation and intraoperative magnetic resonance imaging (MRI) for glioma surgery has not been previously investigated. The study population consisted of 79 glioma patients and 55 control subjects. Preoperatively, the lesion and related eloquent structures were visualized by diffusion tensor tractography and blood oxygen level-dependent functional MRI. Intraoperatively, microscope-based functional neuronavigation was used to integrate the reconstructed eloquent structure and the real head and brain, which enabled safe resection of the lesion. Intraoperative MRI was used to verify brain shift during the surgical process and provided quality control during surgery. The control group underwent surgery guided by anatomic neuronavigation. Virtual and augmented reality protocols based on functional neuronavigation and intraoperative MRI provided useful information for performing tailored and optimized surgery. Complete resection was achieved in 55 of 79 (69.6%) glioma patients and 20 of 55 (36.4%) control subjects, with average resection rates of 95.2% ± 8.5% and 84.9% ± 15.7%, respectively. Both the complete resection rate and average extent of resection differed significantly between the 2 groups (P < 0.01). Postoperatively, the rate of preservation of neural functions (motor, visual field, and language) was lower in controls than in glioma patients at 2 weeks and 3 months (P < 0.01). Combining virtual and augmented reality based on functional neuronavigation and intraoperative MRI can facilitate resection of gliomas involving eloquent areas. Copyright © 2016 Elsevier Inc. All rights reserved.

Fractal analysis and its impact factors on pore structure of artificial cores based on the images obtained using magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Wang, Heming; Liu, Yu; Song, Yongchen; Zhao, Yuechao; Zhao, Jiafei; Wang, Dayong

2012-11-01

Pore structure is one of important factors affecting the properties of porous media, but it is difficult to describe the complexity of pore structure exactly. Fractal theory is an effective and available method for quantifying the complex and irregular pore structure. In this paper, the fractal dimension calculated by box-counting method based on fractal theory was applied to characterize the pore structure of artificial cores. The microstructure or pore distribution in the porous material was obtained using the nuclear magnetic resonance imaging (MRI). Three classical fractals and one sand packed bed model were selected as the experimental material to investigate the influence of box sizes, threshold value, and the image resolution when performing fractal analysis. To avoid the influence of box sizes, a sequence of divisors of the image was proposed and compared with other two algorithms (geometric sequence and arithmetic sequence) with its performance of partitioning the image completely and bringing the least fitted error. Threshold value selected manually and automatically showed that it plays an important role during the image binary processing and the minimum-error method can be used to obtain an appropriate or reasonable one. Images obtained under different pixel matrices in MRI were used to analyze the influence of image resolution. Higher image resolution can detect more quantity of pore structure and increase its irregularity. With benefits of those influence factors, fractal analysis on four kinds of artificial cores showed the fractal dimension can be used to distinguish the different kinds of artificial cores and the relationship between fractal dimension and porosity or permeability can be expressed by the model of D = a - bln(x + c).

Studying Autism Spectrum Disorder with Structural and Diffusion Magnetic Resonance Imaging: A Survey

PubMed Central

Ismail, Marwa M. T.; Keynton, Robert S.; Mostapha, Mahmoud M. M. O.; ElTanboly, Ahmed H.; Casanova, Manuel F.; Gimel'farb, Georgy L.; El-Baz, Ayman

2016-01-01

Magnetic resonance imaging (MRI) modalities have emerged as powerful means that facilitate non-invasive clinical diagnostics of various diseases and abnormalities since their inception in the 1980s. Multiple MRI modalities, such as different types of the sMRI and DTI, have been employed to investigate facets of ASD in order to better understand this complex syndrome. This paper reviews recent applications of structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI), to study autism spectrum disorder (ASD). Main reported findings are sometimes contradictory due to different age ranges, hardware protocols, population types, numbers of participants, and image analysis parameters. The primary anatomical structures, such as amygdalae, cerebrum, and cerebellum, associated with clinical-pathological correlates of ASD are highlighted through successive life stages, from infancy to adulthood. This survey demonstrates the absence of consistent pathology in the brains of autistic children and lack of research investigations in patients under 2 years of age in the literature. The known publications also emphasize advances in data acquisition and analysis, as well as significance of multimodal approaches that combine resting-state, task-evoked, and sMRI measures. Initial results obtained with the sMRI and DTI show good promise toward the early and non-invasive ASD diagnostics. PMID:27242476

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 anatomy of the prostate: implications for treatment planning.

PubMed

McLaughlin, Patrick W; Troyer, Sara; Berri, Sally; Narayana, Vrinda; Meirowitz, Amichay; Roberson, Peter L; Montie, James

2005-10-01

To summarize the functional anatomy relevant to prostate cancer treatment planning. Coronal, axial, and sagittal T2 magnetic resonance imaging (MRI) and MRI angiography were fused by mutual information and registered with computed tomography (CT) scan data sets to improve definition of zonal anatomy of the prostate and critical adjacent structures. The three major prostate zones (inner, outer, and anterior fibromuscular) are visible by T2 MRI imaging. The bladder, bladder neck, and internal (preprostatic) sphincter are a continuous muscular structure and clear definition of the preprostatic sphincter is difficult by MRI. Transition zone hypertrophy may efface the bladder neck and internal sphincter. The external "lower" sphincter is clearly visible by T2 MRI with wide variations in length. The critical erectile structures are the internal pudendal artery (defined by MRI angiogram or T2 MRI), corpus cavernosum, and neurovascular bundle. The neurovascular bundle is visible along the posterior lateral surface of the prostate on CT and MRI, but its terminal branches (cavernosal nerves) are not visible and must be defined by their relationship to the urethra within the genitourinary diaphragm. Visualization of the ejaculatory ducts within the prostate is possible on sagittal MRI. The anatomy of the prostate-rectum interface is clarified by MRI, as is the potentially important distinction of rectal muscle and rectal mucosa. Improved understanding of functional anatomy and imaging of the prostate and critical adjacent structures will improve prostate radiation therapy by improvement of dose and toxicity correlation, limitation of dose to critical structures, and potential improvement in post therapy quality of life.

Fast 3D registration of multimodality tibial images with significant structural mismatch

NASA Astrophysics Data System (ADS)

Rajapakse, C. S.; Wald, M. J.; Magland, J.; Zhang, X. H.; Liu, X. S.; Guo, X. E.; Wehrli, F. W.

2009-02-01

Recently, micro-magnetic resonance imaging (μMRI) in conjunction with micro-finite element analysis has shown great potential in estimating mechanical properties - stiffness and elastic moduli - of bone in patients at risk of osteoporosis. Due to limited spatial resolution and signal-to-noise ratio achievable in vivo, the validity of estimated properties is often established by comparison to those derived from high-resolution micro-CT (μCT) images of cadaveric specimens. For accurate comparison of mechanical parameters derived from μMR and μCT images, analyzed 3D volumes have to be closely matched. The alignment of the micro structure (and the cortex) is often hampered by the fundamental differences of μMR and μCT images and variations in marrow content and cortical bone thickness. Here we present an intensity cross-correlation based registration algorithm coupled with segmentation for registering 3D tibial specimen images acquired by μMRI and μCT in the context of finite-element modeling to assess the bone's mechanical constants. The algorithm first generates three translational and three rotational parameters required to align segmented μMR and CT images from sub regions with high micro-structural similarities. These transformation parameters are then used to register the grayscale μMR and μCT images, which include both the cortex and trabecular bone. The intensity crosscorrelation maximization based registration algorithm described here is suitable for 3D rigid-body image registration applications where through-plane rotations are known to be relatively small. The close alignment of the resulting images is demonstrated quantitatively based on a voxel-overlap measure and qualitatively using visual inspection of the micro structure.

Coregistration of Magnetic Resonance and Single Photon Emission Computed Tomography Images for Noninvasive Localization of Stem Cells Grafted in the Infarcted Rat Myocardium

PubMed Central

Shen, Dinggang; Liu, Dengfeng; Cao, Zixiong; Acton, Paul D.; Zhou, Rong

2008-01-01

This paper demonstrates the application of mutual information based coregistration of radionuclide and magnetic resonance imaging (MRI) in an effort to use multimodality imaging for noninvasive localization of stem cells grafted in the infarcted myocardium in rats. Radionuclide imaging such as single photon emission computed tomography (SPECT) or positron emission tomography (PET) inherently has high sensitivity and is suitable for tracking of labeled stem cells, while high-resolution MRI is able to provide detailed anatomical and functional information of myocardium. Thus, coregistration of PET or SPECT images with MRI will map the location and distribution of stem cells on detailed myocardium structures. To validate this coregistration method, SPECT data were simulated by using a Monte Carlo-based projector that modeled the pinhole-imaging physics assuming nonzero diameter and photon penetration at the edge. Translational and rotational errors of the coregistration were examined with respect to various SPECT activities, and they are on average about 0.50 mm and 0.82°, respectively. Only the rotational error is dependent on activity of SPECT data. Stem cells were labeled with 111 Indium oxyquinoline and grafted in the ischemic myocardium of a rat model. Dual-tracer small-animal SPECT images were acquired, which allowed simultaneous detection of 111In-labeled stem cells and of [99mTc]sestamibi to assess myocardial perfusion deficit. The same animals were subjected to cardiac MRI. A mutual-information-based coregistration method was then applied to the SPECT and MRIs. By coregistration, the 111 In signal from labeled cells was mapped into the akinetic region identified on cine MRIs; the regional perfusion deficit on the SPECT images also coincided with the akinetic region on the MR image. PMID:17053860

Neurological soft signs are not "soft" in brain structure and functional networks: evidence from ALE meta-analysis.

PubMed

Zhao, Qing; Li, Zhi; Huang, Jia; Yan, Chao; Dazzan, Paola; Pantelis, Christos; Cheung, Eric F C; Lui, Simon S Y; Chan, Raymond C K

2014-05-01

Neurological soft signs (NSS) are associated with schizophrenia and related psychotic disorders. NSS have been conventionally considered as clinical neurological signs without localized brain regions. However, recent brain imaging studies suggest that NSS are partly localizable and may be associated with deficits in specific brain areas. We conducted an activation likelihood estimation meta-analysis to quantitatively review structural and functional imaging studies that evaluated the brain correlates of NSS in patients with schizophrenia and other psychotic disorders. Six structural magnetic resonance imaging (sMRI) and 15 functional magnetic resonance imaging (fMRI) studies were included. The results from meta-analysis of the sMRI studies indicated that NSS were associated with atrophy of the precentral gyrus, the cerebellum, the inferior frontal gyrus, and the thalamus. The results from meta-analysis of the fMRI studies demonstrated that the NSS-related task was significantly associated with altered brain activation in the inferior frontal gyrus, bilateral putamen, the cerebellum, and the superior temporal gyrus. Our findings from both sMRI and fMRI meta-analyses further support the conceptualization of NSS as a manifestation of the "cerebello-thalamo-prefrontal" brain network model of schizophrenia and related psychotic disorders.

Examining a New Method to Studying Velopharyngeal Structures in a Child With 22q11.2 Deletion Syndrome.

PubMed

Kollara, Lakshmi; Schenck, Graham; Jaskolka, Michael; Perry, Jamie L

2017-04-14

To date, no studies have imaged the velopharynx in children with 22q11.2 deletion syndrome (22q11.2 DS) without the use of sedation. Dysmorphology in velopharyngeal structures has been shown to have significant negative implications on speech among these individuals. This single case study was designed to assess the feasibility of a child-friendly magnetic resonance imaging (MRI) scanning protocol in this clinically challenging population and to determine the utility of this MRI protocol for future work in this area. One 6-year-old White girl diagnosed with 22q11.2 DS was imaged using a child-friendly, nonsedated MRI protocol. Quantitative and qualitative measures of the velopharyngeal area and associated structures were evaluated, and comparisons were made to age-matched control subjects with normal velopharyngeal anatomy. MRI data were successfully obtained using the child-friendly scanning protocol in the subject in the present study. Quantitative and qualitative differences of the levator muscle and associated velopharyngeal structures were noted. Using these MRI and structural analyses methods, insights related to muscle morphology can be obtained and considered as part of the research and clinical examination of children with 22q11.2 DS. The imaging protocol described in this study presents an effective means to counteract difficulties in imaging young children.

Altered small-world topology of structural brain networks in infants with intrauterine growth restriction and its association with later neurodevelopmental outcome.

PubMed

Batalle, Dafnis; Eixarch, Elisenda; Figueras, Francesc; Muñoz-Moreno, Emma; Bargallo, Nuria; Illa, Miriam; Acosta-Rojas, Ruthy; Amat-Roldan, Ivan; Gratacos, Eduard

2012-04-02

Intrauterine growth restriction (IUGR) due to placental insufficiency affects 5-10% of all pregnancies and it is associated with a wide range of short- and long-term neurodevelopmental disorders. Prediction of neurodevelopmental outcomes in IUGR is among the clinical challenges of modern fetal medicine and pediatrics. In recent years several studies have used magnetic resonance imaging (MRI) to demonstrate differences in brain structure in IUGR subjects, but the ability to use MRI for individual predictive purposes in IUGR is limited. Recent research suggests that MRI in vivo access to brain connectivity might have the potential to help understanding cognitive and neurodevelopment processes. Specifically, MRI based connectomics is an emerging approach to extract information from MRI data that exhaustively maps inter-regional connectivity within the brain to build a graph model of its neural circuitry known as brain network. In the present study we used diffusion MRI based connectomics to obtain structural brain networks of a prospective cohort of one year old infants (32 controls and 24 IUGR) and analyze the existence of quantifiable brain reorganization of white matter circuitry in IUGR group by means of global and regional graph theory features of brain networks. Based on global and regional analyses of the brain network topology we demonstrated brain reorganization in IUGR infants at one year of age. Specifically, IUGR infants presented decreased global and local weighted efficiency, and a pattern of altered regional graph theory features. By means of binomial logistic regression, we also demonstrated that connectivity measures were associated with abnormal performance in later neurodevelopmental outcome as measured by Bayley Scale for Infant and Toddler Development, Third edition (BSID-III) at two years of age. These findings show the potential of diffusion MRI based connectomics and graph theory based network characteristics for estimating differences in the architecture of neural circuitry and developing imaging biomarkers of poor neurodevelopment outcome in infants with prenatal diseases. Copyright © 2012 Elsevier Inc. All rights reserved.

Unsupervised nonlinear dimensionality reduction machine learning methods applied to multiparametric MRI in cerebral ischemia: preliminary results

NASA Astrophysics Data System (ADS)

Parekh, Vishwa S.; Jacobs, Jeremy R.; Jacobs, Michael A.

2014-03-01

The evaluation and treatment of acute cerebral ischemia requires a technique that can determine the total area of tissue at risk for infarction using diagnostic magnetic resonance imaging (MRI) sequences. Typical MRI data sets consist of T1- and T2-weighted imaging (T1WI, T2WI) along with advanced MRI parameters of diffusion-weighted imaging (DWI) and perfusion weighted imaging (PWI) methods. Each of these parameters has distinct radiological-pathological meaning. For example, DWI interrogates the movement of water in the tissue and PWI gives an estimate of the blood flow, both are critical measures during the evolution of stroke. In order to integrate these data and give an estimate of the tissue at risk or damaged; we have developed advanced machine learning methods based on unsupervised non-linear dimensionality reduction (NLDR) techniques. NLDR methods are a class of algorithms that uses mathematically defined manifolds for statistical sampling of multidimensional classes to generate a discrimination rule of guaranteed statistical accuracy and they can generate a two- or three-dimensional map, which represents the prominent structures of the data and provides an embedded image of meaningful low-dimensional structures hidden in their high-dimensional observations. In this manuscript, we develop NLDR methods on high dimensional MRI data sets of preclinical animals and clinical patients with stroke. On analyzing the performance of these methods, we observed that there was a high of similarity between multiparametric embedded images from NLDR methods and the ADC map and perfusion map. It was also observed that embedded scattergram of abnormal (infarcted or at risk) tissue can be visualized and provides a mechanism for automatic methods to delineate potential stroke volumes and early tissue at risk.

A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI.

PubMed

Iglesias, Juan Eugenio; Augustinack, Jean C; Nguyen, Khoa; Player, Christopher M; Player, Allison; Wright, Michelle; Roy, Nicole; Frosch, Matthew P; McKee, Ann C; Wald, Lawrence L; Fischl, Bruce; Van Leemput, Koen

2015-07-15

Automated analysis of MRI data of the subregions of the hippocampus requires computational atlases built at a higher resolution than those that are typically used in current neuroimaging studies. Here we describe the construction of a statistical atlas of the hippocampal formation at the subregion level using ultra-high resolution, ex vivo MRI. Fifteen autopsy samples were scanned at 0.13 mm isotropic resolution (on average) using customized hardware. The images were manually segmented into 13 different hippocampal substructures using a protocol specifically designed for this study; precise delineations were made possible by the extraordinary resolution of the scans. In addition to the subregions, manual annotations for neighboring structures (e.g., amygdala, cortex) were obtained from a separate dataset of in vivo, T1-weighted MRI scans of the whole brain (1mm resolution). The manual labels from the in vivo and ex vivo data were combined into a single computational atlas of the hippocampal formation with a novel atlas building algorithm based on Bayesian inference. The resulting atlas can be used to automatically segment the hippocampal subregions in structural MRI images, using an algorithm that can analyze multimodal data and adapt to variations in MRI contrast due to differences in acquisition hardware or pulse sequences. The applicability of the atlas, which we are releasing as part of FreeSurfer (version 6.0), is demonstrated with experiments on three different publicly available datasets with different types of MRI contrast. The results show that the atlas and companion segmentation method: 1) can segment T1 and T2 images, as well as their combination, 2) replicate findings on mild cognitive impairment based on high-resolution T2 data, and 3) can discriminate between Alzheimer's disease subjects and elderly controls with 88% accuracy in standard resolution (1mm) T1 data, significantly outperforming the atlas in FreeSurfer version 5.3 (86% accuracy) and classification based on whole hippocampal volume (82% accuracy). Copyright © 2015. Published by Elsevier Inc.

Structure-borne sound from magnetic resonance imaging systems

NASA Astrophysics Data System (ADS)

Ungar, Eric E.; Zapfe, Jeffrey A.

2003-10-01

Magnetic resonance imaging (MRI) systems are known to produce a considerable amount of audible noise. The recent tendency to install such systems on above-grade floors has led to increasing concerns about structure-borne noise transmission from the MRI to adjacent occupied areas. This paper presents the results of a study in which structure-borne noise forces produced by two operational MRI systems were determined via measurement of the floor vibrations induced by the systems and of the impedance of their supporting floors. Forces with known spectra were applied to the floors of planned MRI suites in a hospital extension and the corresponding noise in adjacent areas was measured. Similarly, airborne noise was introduced in the planned suites and the related noise in adjacent areas was measured. The results then were scaled to correspond to the measured MRI forces and airborne noise. It was found that in areas below the planned MRI installations structure-borne noise would predominate, unless it is mitigated. Structure-borne noise isolation of MRI systems, whose environments must meet stringent vibration criteria, is discussed briefly.

Automatic MRI 2D brain segmentation using graph searching technique.

PubMed

Pedoia, Valentina; Binaghi, Elisabetta

2013-09-01

Accurate and efficient segmentation of the whole brain in magnetic resonance (MR) images is a key task in many neuroscience and medical studies either because the whole brain is the final anatomical structure of interest or because the automatic extraction facilitates further analysis. The problem of segmenting brain MRI images has been extensively addressed by many researchers. Despite the relevant achievements obtained, automated segmentation of brain MRI imagery is still a challenging problem whose solution has to cope with critical aspects such as anatomical variability and pathological deformation. In the present paper, we describe and experimentally evaluate a method for segmenting brain from MRI images basing on two-dimensional graph searching principles for border detection. The segmentation of the whole brain over the entire volume is accomplished slice by slice, automatically detecting frames including eyes. The method is fully automatic and easily reproducible by computing the internal main parameters directly from the image data. The segmentation procedure is conceived as a tool of general applicability, although design requirements are especially commensurate with the accuracy required in clinical tasks such as surgical planning and post-surgical assessment. Several experiments were performed to assess the performance of the algorithm on a varied set of MRI images obtaining good results in terms of accuracy and stability. Copyright © 2012 John Wiley & Sons, Ltd.

Spine labeling in MRI via regularized distribution matching.

PubMed

Hojjat, Seyed-Parsa; Ayed, Ismail; Garvin, Gregory J; Punithakumar, Kumaradevan

2017-11-01

This study investigates an efficient (nearly real-time) two-stage spine labeling algorithm that removes the need for an external training while being applicable to different types of MRI data and acquisition protocols. Based solely on the image being labeled (i.e., we do not use training data), the first stage aims at detecting potential vertebra candidates following the optimization of a functional containing two terms: (i) a distribution-matching term that encodes contextual information about the vertebrae via a density model learned from a very simple user input, which amounts to a point (mouse click) on a predefined vertebra; and (ii) a regularization constraint, which penalizes isolated candidates in the solution. The second stage removes false positives and identifies all vertebrae and discs by optimizing a geometric constraint, which embeds generic anatomical information on the interconnections between neighboring structures. Based on generic knowledge, our geometric constraint does not require external training. We performed quantitative evaluations of the algorithm over a data set of 90 mid-sagittal MRI images of the lumbar spine acquired from 45 different subjects. To assess the flexibility of the algorithm, we used both T1- and T2-weighted images for each subject. A total of 990 structures were automatically detected/labeled and compared to ground-truth annotations by an expert. On the T2-weighted data, we obtained an accuracy of 91.6% for the vertebrae and 89.2% for the discs. On the T1-weighted data, we obtained an accuracy of 90.7% for the vertebrae and 88.1% for the discs. Our algorithm removes the need for external training while being applicable to different types of MRI data and acquisition protocols. Based on the current testing data, a subject-specific model density and generic anatomical information, our method can achieve competitive performances when applied to T1- and T2-weighted MRI images.

A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity.

PubMed

Huang, Lijie; Huang, Taicheng; Zhen, Zonglei; Liu, Jia

2016-03-15

We present a test-retest dataset for evaluation of long-term reliability of measures from structural and resting-state functional magnetic resonance imaging (sMRI and rfMRI) scans. The repeated scan dataset was collected from 61 healthy adults in two sessions using highly similar imaging parameters at an interval of 103-189 days. However, as the imaging parameters were not completely identical, the reliability estimated from this dataset shall reflect the lower bounds of the true reliability of sMRI/rfMRI measures. Furthermore, in conjunction with other test-retest datasets, our dataset may help explore the impact of different imaging parameters on reliability of sMRI/rfMRI measures, which is especially critical for assessing datasets collected from multiple centers. In addition, intelligence quotient (IQ) was measured for each participant using Raven's Advanced Progressive Matrices. The data can thus be used for purposes other than assessing reliability of sMRI/rfMRI alone. For example, data from each single session could be used to associate structural and functional measures of the brain with the IQ metrics to explore brain-IQ association.

Heritability estimates on resting state fMRI data using ENIGMA analysis pipeline.

PubMed

Adhikari, Bhim M; Jahanshad, Neda; Shukla, Dinesh; Glahn, David C; Blangero, John; Reynolds, Richard C; Cox, Robert W; Fieremans, Els; Veraart, Jelle; Novikov, Dmitry S; Nichols, Thomas E; Hong, L Elliot; Thompson, Paul M; Kochunov, Peter

2018-01-01

Big data initiatives such as the Enhancing NeuroImaging Genetics through Meta-Analysis consortium (ENIGMA), combine data collected by independent studies worldwide to achieve more generalizable estimates of effect sizes and more reliable and reproducible outcomes. Such efforts require harmonized image analyses protocols to extract phenotypes consistently. This harmonization is particularly challenging for resting state fMRI due to the wide variability of acquisition protocols and scanner platforms; this leads to site-to-site variance in quality, resolution and temporal signal-to-noise ratio (tSNR). An effective harmonization should provide optimal measures for data of different qualities. We developed a multi-site rsfMRI analysis pipeline to allow research groups around the world to process rsfMRI scans in a harmonized way, to extract consistent and quantitative measurements of connectivity and to perform coordinated statistical tests. We used the single-modality ENIGMA rsfMRI preprocessing pipeline based on modelfree Marchenko-Pastur PCA based denoising to verify and replicate resting state network heritability estimates. We analyzed two independent cohorts, GOBS (Genetics of Brain Structure) and HCP (the Human Connectome Project), which collected data using conventional and connectomics oriented fMRI protocols, respectively. We used seed-based connectivity and dual-regression approaches to show that the rsfMRI signal is consistently heritable across twenty major functional network measures. Heritability values of 20-40% were observed across both cohorts.

Structural and functional network connectivity breakdown in Alzheimer’s disease studied with magnetic resonance imaging techniques.

PubMed

Filippi, Massimo; Agosta, Federica

2011-01-01

Patients with Alzheimer’s disease (AD) experience a brain network breakdown, reflecting disconnection at both the structural and functional system level. Resting-state (RS) functional MRI (fMRI) studies demonstrated that the regional coherence of the fMRI signal is significantly altered in patients with AD and amnestic mild cognitive impairment. Diffusion tensor (DT) MRI has made it possible to track fiber bundle projections across the brain, revealing a substantially abnormal interplay of “critical” white matter tracts in these conditions. The observed agreement between the results of RS fMRI and DT MRI tractography studies in healthy individuals is encouraging and offers interesting hypotheses to be tested in patients with AD, a MCI, and other dementias in order to improve our understanding of their pathobiology in vivo. In this review,we describe the major findings obtained in AD using RS fMRI and DT MRI tractography, and discuss how the relationship between structure and function of the brain networks in AD may be better understood through the application of MR-based technology. This research endeavor holds a great promise in clarifying the mechanisms of cognitive decline in complex chronic neurodegenerative disorders.

Adaptation of brain functional and structural networks in aging.

PubMed

Lee, Annie; Ratnarajah, Nagulan; Tuan, Ta Anh; Chen, Shen-Hsing Annabel; Qiu, Anqi

2015-01-01

The human brain, especially the prefrontal cortex (PFC), is functionally and anatomically reorganized in order to adapt to neuronal challenges in aging. This study employed structural MRI, resting-state fMRI (rs-fMRI), and high angular resolution diffusion imaging (HARDI), and examined the functional and structural reorganization of the PFC in aging using a Chinese sample of 173 subjects aged from 21 years and above. We found age-related increases in the structural connectivity between the PFC and posterior brain regions. Such findings were partially mediated by age-related increases in the structural connectivity of the occipital lobe within the posterior brain. Based on our findings, it is thought that the PFC reorganization in aging could be partly due to the adaptation to age-related changes in the structural reorganization of the posterior brain. This thus supports the idea derived from task-based fMRI that the PFC reorganization in aging may be adapted to the need of compensation for resolving less distinctive stimulus information from the posterior brain regions. In addition, we found that the structural connectivity of the PFC with the temporal lobe was fully mediated by the temporal cortical thickness, suggesting that the brain morphology plays an important role in the functional and structural reorganization with aging.

A voxel based comparative analysis using magnetization transfer imaging and T1-weighted magnetic resonance imaging in progressive supranuclear palsy

PubMed Central

Sandhya, Mangalore; Saini, Jitender; Pasha, Shaik Afsar; Yadav, Ravi; Pal, Pramod Kumar

2014-01-01

Aims: In progressive supranuclear palsy (PSP) tissue damage occurs in specific cortical and subcortical regions. Voxel based analysis using T1-weighted images depict quantitative gray matter (GM) atrophy changes. Magnetization transfer (MT) imaging depicts qualitative changes in the brain parenchyma. The purpose of our study was to investigate whether MT imaging could indicate abnormalities in PSP. Settings and Design: A total of 10 patients with PSP (9 men and 1 woman) and 8 controls (5 men and 3 women) were studied with T1-weighted magnetic resonance imaging (MRI) and 3DMT imaging. Voxel based analysis of T1-weighted MRI was performed to investigate brain atrophy while MT was used to study qualitative abnormalities in the brain tissue. We used SPM8 to investigate group differences (with two sample t-test) using the GM and white matter (WM) segmented data. Results: T1-weighted imaging and MT are equally sensitive to detect changes in GM and WM in PSP. Magnetization transfer ratio images and magnetization-prepared rapid acquisition of gradient echo revealed extensive bilateral volume and qualitative changes in the orbitofrontal, prefrontal cortex and limbic lobe and sub cortical GM. The prefrontal structures involved were the rectal gyrus, medial, inferior frontal gyrus (IFG) and middle frontal gyrus (MFG). The anterior cingulate, cingulate gyrus and lingual gyrus of limbic lobe and subcortical structures such as caudate, thalamus, insula and claustrum were also involved. Cerebellar involvement mainly of anterior lobe was also noted. Conclusions: The findings suggest that voxel based MT imaging permits a whole brain unbiased investigation of central nervous system structural integrity in PSP. PMID:25024571

MRI (Magnetic Resonance Imaging)

MedlinePlus

... IV in the arm. MRI Research Programs at FDA Magnetic Resonance Imaging (MRI) Safety Electromagnetic Modeling Related ... Resonance Imaging Equipment in Clinical Use (March 2015) FDA/CDER: Information on Gadolinium-Based Contrast Agents Safety ...

[Vertical retraction syndrome caused by anomalous orbital structures].

PubMed

Yang, Qiong; Jiao, Yong-hong; Man, Feng-yuan; Wang, Zhen-chang; Chang, Qing-lin; Lu, Wei; Wang, Jing-hui; Zhao, Kan-xing

2011-11-01

To described the clinical feature and MRI imaging of six children with vertical retraction syndrome. Six children with unilateral vertical retraction syndrome between 15 months and 8 years of age, mean age was (5.01 ± 1.27) years old. Strabismus examination included diopter, prism diopters, eye movement examination, binocular vision and fundus examination. Imaging of the ocular motor nerves at the brainstem was performed in 0.8 mm thickness image planes using 3D-FIESTA sequence, the orbits were imaged with FSE T1, T2WI using surface coils, and within 2.0 mm thick planes. Four children showed hypertropia, characterized by limited depression, a light retraction of the globe during downward gaze and eyelid lag. The MRI imaging showed anomalous orbital structure in the superonasal quadrant that between medial rectus and superior rectus or adjacent to the superior rectus. Two children showed intermittent exotropia, characterized by limited elevation, retraction of the globe and narrowing of the palpebral fissure during upward gaze. The MRI imaging showed anomalous orbital structure was present in the inferotemporal quadrant, one originate in inferior rectus and another close to the lateral rectus. Anomalous orbital structures are a main cause of vertical retraction syndrome. The presence of specific unusual eye movement and MRI imaging may assist in diagnosis. When the eyelid lag was found since the early age, anomalous orbital structures were implied.

Functional Connectivity Mapping in the Animal Model: Principles and Applications of Resting-State fMRI

PubMed Central

Gorges, Martin; Roselli, Francesco; Müller, Hans-Peter; Ludolph, Albert C.; Rasche, Volker; Kassubek, Jan

2017-01-01

“Resting-state” fMRI has substantially contributed to the understanding of human and non-human functional brain organization by the analysis of correlated patterns in spontaneous activity within dedicated brain systems. Spontaneous neural activity is indirectly measured from the blood oxygenation level-dependent signal as acquired by echo planar imaging, when subjects quietly “resting” in the scanner. Animal models including disease or knockout models allow a broad spectrum of experimental manipulations not applicable in humans. The non-invasive fMRI approach provides a promising tool for cross-species comparative investigations. This review focuses on the principles of “resting-state” functional connectivity analysis and its applications to living animals. The translational aspect from in vivo animal models toward clinical applications in humans is emphasized. We introduce the fMRI-based investigation of the non-human brain’s hemodynamics, the methodological issues in the data postprocessing, and the functional data interpretation from different abstraction levels. The longer term goal of integrating fMRI connectivity data with structural connectomes obtained with tracing and optical imaging approaches is presented and will allow the interrogation of fMRI data in terms of directional flow of information and may identify the structural underpinnings of observed functional connectivity patterns. PMID:28539914

The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments.

PubMed

Gorgolewski, Krzysztof J; Auer, Tibor; Calhoun, Vince D; Craddock, R Cameron; Das, Samir; Duff, Eugene P; Flandin, Guillaume; Ghosh, Satrajit S; Glatard, Tristan; Halchenko, Yaroslav O; Handwerker, Daniel A; Hanke, Michael; Keator, David; Li, Xiangrui; Michael, Zachary; Maumet, Camille; Nichols, B Nolan; Nichols, Thomas E; Pellman, John; Poline, Jean-Baptiste; Rokem, Ariel; Schaefer, Gunnar; Sochat, Vanessa; Triplett, William; Turner, Jessica A; Varoquaux, Gaël; Poldrack, Russell A

2016-06-21

The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations.

The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments

PubMed Central

Gorgolewski, Krzysztof J.; Auer, Tibor; Calhoun, Vince D.; Craddock, R. Cameron; Das, Samir; Duff, Eugene P.; Flandin, Guillaume; Ghosh, Satrajit S.; Glatard, Tristan; Halchenko, Yaroslav O.; Handwerker, Daniel A.; Hanke, Michael; Keator, David; Li, Xiangrui; Michael, Zachary; Maumet, Camille; Nichols, B. Nolan; Nichols, Thomas E.; Pellman, John; Poline, Jean-Baptiste; Rokem, Ariel; Schaefer, Gunnar; Sochat, Vanessa; Triplett, William; Turner, Jessica A.; Varoquaux, Gaël; Poldrack, Russell A.

2016-01-01

The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations. PMID:27326542

A Tool for Interactive Data Visualization: Application to Over 10,000 Brain Imaging and Phantom MRI Data Sets.

PubMed

Panta, Sandeep R; Wang, Runtang; Fries, Jill; Kalyanam, Ravi; Speer, Nicole; Banich, Marie; Kiehl, Kent; King, Margaret; Milham, Michael; Wager, Tor D; Turner, Jessica A; Plis, Sergey M; Calhoun, Vince D

2016-01-01

In this paper we propose a web-based approach for quick visualization of big data from brain magnetic resonance imaging (MRI) scans using a combination of an automated image capture and processing system, nonlinear embedding, and interactive data visualization tools. We draw upon thousands of MRI scans captured via the COllaborative Imaging and Neuroinformatics Suite (COINS). We then interface the output of several analysis pipelines based on structural and functional data to a t-distributed stochastic neighbor embedding (t-SNE) algorithm which reduces the number of dimensions for each scan in the input data set to two dimensions while preserving the local structure of data sets. Finally, we interactively display the output of this approach via a web-page, based on data driven documents (D3) JavaScript library. Two distinct approaches were used to visualize the data. In the first approach, we computed multiple quality control (QC) values from pre-processed data, which were used as inputs to the t-SNE algorithm. This approach helps in assessing the quality of each data set relative to others. In the second case, computed variables of interest (e.g., brain volume or voxel values from segmented gray matter images) were used as inputs to the t-SNE algorithm. This approach helps in identifying interesting patterns in the data sets. We demonstrate these approaches using multiple examples from over 10,000 data sets including (1) quality control measures calculated from phantom data over time, (2) quality control data from human functional MRI data across various studies, scanners, sites, (3) volumetric and density measures from human structural MRI data across various studies, scanners and sites. Results from (1) and (2) show the potential of our approach to combine t-SNE data reduction with interactive color coding of variables of interest to quickly identify visually unique clusters of data (i.e., data sets with poor QC, clustering of data by site) quickly. Results from (3) demonstrate interesting patterns of gray matter and volume, and evaluate how they map onto variables including scanners, age, and gender. In sum, the proposed approach allows researchers to rapidly identify and extract meaningful information from big data sets. Such tools are becoming increasingly important as datasets grow larger.

Ventricular Geometry From Non-contrast Non-ECG-gated CT Scans: An Imaging Marker of Cardiopulmonary Disease in Smokers.

PubMed

Rahaghi, Farbod N; Vegas-Sanchez-Ferrero, Gonzalo; Minhas, Jasleen K; Come, Carolyn E; De La Bruere, Isaac; Wells, James M; González, Germán; Bhatt, Surya P; Fenster, Brett E; Diaz, Alejandro A; Kohli, Puja; Ross, James C; Lynch, David A; Dransfield, Mark T; Bowler, Russel P; Ledesma-Carbayo, Maria J; San José Estépar, Raúl; Washko, George R

2017-05-01

Imaging-based assessment of cardiovascular structure and function provides clinically relevant information in smokers. Non-cardiac-gated thoracic computed tomographic (CT) scanning is increasingly leveraged for clinical care and lung cancer screening. We sought to determine if more comprehensive measures of ventricular geometry could be obtained from CT using an atlas-based surface model of the heart. Subcohorts of 24 subjects with cardiac magnetic resonance imaging (MRI) and 262 subjects with echocardiography were identified from COPDGene, a longitudinal observational study of smokers. A surface model of the heart was manually initialized, and then automatically optimized to fit the epicardium for each CT. Estimates of right and left ventricular (RV and LV) volume and free-wall curvature were then calculated and compared to structural and functional metrics obtained from MRI and echocardiograms. CT measures of RV dimension and curvature correlated with similar measures obtained using MRI. RV and LV volume obtained from CT inversely correlated with echocardiogram-based estimates of RV systolic pressure using tricuspid regurgitation jet velocity and LV ejection fraction respectively. Patients with evidence of RV or LV dysfunction on echocardiogram had larger RV and LV dimensions on CT. Logistic regression models based on demographics and ventricular measures from CT had an area under the curve of >0.7 for the prediction of elevated right ventricular systolic pressure and ventricular failure. These data suggest that non-cardiac-gated, non-contrast-enhanced thoracic CT scanning may provide insight into cardiac structure and function in smokers. Copyright © 2017. Published by Elsevier Inc.

ProstateAnalyzer: Web-based medical application for the management of prostate cancer using multiparametric MR imaging.

PubMed

Mata, Christian; Walker, Paul M; Oliver, Arnau; Brunotte, François; Martí, Joan; Lalande, Alain

2016-01-01

In this paper, we present ProstateAnalyzer, a new web-based medical tool for prostate cancer diagnosis. ProstateAnalyzer allows the visualization and analysis of magnetic resonance images (MRI) in a single framework. ProstateAnalyzer recovers the data from a PACS server and displays all the associated MRI images in the same framework, usually consisting of 3D T2-weighted imaging for anatomy, dynamic contrast-enhanced MRI for perfusion, diffusion-weighted imaging in the form of an apparent diffusion coefficient (ADC) map and MR Spectroscopy. ProstateAnalyzer allows annotating regions of interest in a sequence and propagates them to the others. From a representative case, the results using the four visualization platforms are fully detailed, showing the interaction among them. The tool has been implemented as a Java-based applet application to facilitate the portability of the tool to the different computer architectures and software and allowing the possibility to work remotely via the web. ProstateAnalyzer enables experts to manage prostate cancer patient data set more efficiently. The tool allows delineating annotations by experts and displays all the required information for use in diagnosis. According to the current European Society of Urogenital Radiology guidelines, it also includes the PI-RADS structured reporting scheme.

Multifunctional gadolinium-based dendritic macromolecules as liver targeting imaging probes.

PubMed

Luo, Kui; Liu, Gang; He, Bin; Wu, Yao; Gong, Qingyong; Song, Bin; Ai, Hua; Gu, Zhongwei

2011-04-01

The quest for highly efficient and safe contrast agents has become the key factor for successful application of magnetic resonance imaging (MRI). The gadolinium (Gd) based dendritic macromolecules, with precise and tunable nanoscopic sizes, are excellent candidates as multivalent MRI probes. In this paper, a novel series of Gd-based multifunctional peptide dendritic probes (generation 2, 3, and 4) possessing highly controlled structures and single molecular weight were designed and prepared as liver MRI probes. These macromolecular Gd-ligand agents exhibited up to 3-fold increase in T(1) relaxivity comparing to Gd-DTPA complexes. No obvious in vitro cytotoxicity was observed from the measured concentrations. These dendritic probes were further functionalized with multiple galactosyl moieties and led to much higher cell uptake in vitro as demonstrated in T(1)-weighted scans. During in vivo animal studies, the probes provided better signal intensity (SI) enhancement in mouse liver, especially at 60 min post-injection, with the most efficient enhancement from the galactosyl moiety decorated third generation dendrimer. The imaging results were verified with analysis of Gd content in liver tissues. The design strategy of multifunctional Gd-ligand peptide dendritic macromolecules in this study may be used for developing other sensitive MRI probes with targeting capability. Copyright © 2011 Elsevier Ltd. All rights reserved.

Connectivity changes after laser ablation: Resting-state fMRI.

PubMed

Boerwinkle, Varina L; Vedantam, Aditya; Lam, Sandi; Wilfong, Angus A; Curry, Daniel J

2018-05-01

Resting-state functional magnetic resonance imaging (rsfMRI) is emerging as a useful tool in the multimodal assessment of patients with epilepsy. In pediatric patients who cannot perform task-based fMRI, rsfMRI may present an adjunct and alternative. Although changes in brain activation during task-based fMRI have been described after surgery for epilepsy, there is limited data on the role of postoperative rsfMRI. In this short review, we discuss the role of postoperative rsfMRI after laser ablation of seizure foci. By establishing standardized anesthesia protocols and imaging parameters, we have been able to perform serial rsfMRI at postoperative follow-up. The development of in-house software that can merge rsfMRI images to surgical navigation systems has allowed us to enhance the clinical applications of this technique. Resting-state fMRI after laser ablation has the potential to identify changes in connectivity, localize new seizure foci, and guide antiepileptic therapy. In our experience, rsfMRI complements conventional MR imaging and task-based fMRI for the evaluation of patients with seizure recurrence after laser ablation, and represents a potential noninvasive biomarker for functional connectivity. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Lumbar spinal stenosis CAD from clinical MRM and MRI based on inter- and intra-context features with a two-level classifier

NASA Astrophysics Data System (ADS)

Koh, Jaehan; Alomari, Raja S.; Chaudhary, Vipin; Dhillon, Gurmeet

2011-03-01

An imaging test has an important role in the diagnosis of lumbar abnormalities since it allows to examine the internal structure of soft tissues and bony elements without the need of an unnecessary surgery and recovery time. For the past decade, among various imaging modalities, magnetic resonance imaging (MRI) has taken the significant part of the clinical evaluation of the lumbar spine. This is mainly due to technological advancements that lead to the improvement of imaging devices in spatial resolution, contrast resolution, and multi-planar capabilities. In addition, noninvasive nature of MRI makes it easy to diagnose many common causes of low back pain such as disc herniation, spinal stenosis, and degenerative disc diseases. In this paper, we propose a method to diagnose lumbar spinal stenosis (LSS), a narrowing of the spinal canal, from magnetic resonance myelography (MRM) images. Our method segments the thecal sac in the preprocessing stage, generates the features based on inter- and intra-context information, and diagnoses lumbar disc stenosis. Experiments with 55 subjects show that our method achieves 91.3% diagnostic accuracy. In the future, we plan to test our method on more subjects.

Imaging techniques in the management of chronic kidney disease: current developments and future perspectives.

PubMed

Herget-Rosenthal, Stefan

2011-05-01

The measurement of both renal function and structure is critical in clinical nephrology to detect, stage, and monitor chronic kidney disease (CKD). Current imaging modalities especially ultrasound (US), computed tomography, and magnetic resonance imaging (MRI) provide adequate information on structural changes but little on functional impairment in CKD. Although not yet considered first-line procedures for evaluating patients with renal disease, new US and MR imaging techniques may permit the assessment of renal function in the near future. Combined with established imaging techniques, contrast-enhanced US, dynamic contrast-enhanced MRI, blood oxygen level dependency MRI, or diffusion-weighted imaging may provide rapid, accurate, simultaneous, and noninvasive imaging of the structure of kidneys, macrovascular and microvascular renal perfusion, oxygenation, and glomerular filtration rate. Recent developments in molecular imaging indicate that pathophysiological pathways of renal diseases such as apoptosis, coagulation, fibrosis, and ischemia will be visualized at the tissue level. These major advances in imaging and developments in hardware and software could enable comprehensive imaging of renal structure and function in four dimensions (three dimensions plus time), and imaging is expected to play an increasing role in the management of CKD. Copyright © 2011 Elsevier Inc. All rights reserved.

Anatomically Realistic Three-Dimensional Meshes of the Pelvic Floor & Anal Canal for Finite Element Analysis

PubMed Central

Noakes, Kimberley F.; Bissett, Ian P.; Pullan, Andrew J.; Cheng, Leo K.

2014-01-01

Three anatomically realistic meshes, suitable for finite element analysis, of the pelvic floor and anal canal regions have been developed to provide a framework with which to examine the mechanics, via finite element analysis of normal function within the pelvic floor. Two cadaver-based meshes were produced using the Visible Human Project (male and female) cryosection data sets, and a third mesh was produced based on MR image data from a live subject. The Visible Man (VM) mesh included 10 different pelvic structures while the Visible Woman and MRI meshes contained 14 and 13 structures respectively. Each image set was digitized and then finite element meshes were created using an iterative fitting procedure with smoothing constraints calculated from ‘L’-curves. These weights produced accurate geometric meshes of each pelvic structure with average Root Mean Square (RMS) fitting errors of less than 1.15 mm. The Visible Human cadaveric data provided high resolution images, however, the cadaveric meshes lacked the normal dynamic form of living tissue and suffered from artifacts related to postmortem changes. The lower resolution MRI mesh was able to accurately portray structure of the living subject and paves the way for dynamic, functional modeling. PMID:18317929

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

Automatic tissue image segmentation based on image processing and deep learning

NASA Astrophysics Data System (ADS)

Kong, Zhenglun; Luo, Junyi; Xu, Shengpu; Li, Ting

2018-02-01

Image segmentation plays an important role in multimodality imaging, especially in fusion structural images offered by CT, MRI with functional images collected by optical technologies or other novel imaging technologies. Plus, image segmentation also provides detailed structure description for quantitative visualization of treating light distribution in the human body when incorporated with 3D light transport simulation method. Here we used image enhancement, operators, and morphometry methods to extract the accurate contours of different tissues such as skull, cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) on 5 fMRI head image datasets. Then we utilized convolutional neural network to realize automatic segmentation of images in a deep learning way. We also introduced parallel computing. Such approaches greatly reduced the processing time compared to manual and semi-automatic segmentation and is of great importance in improving speed and accuracy as more and more samples being learned. Our results can be used as a criteria when diagnosing diseases such as cerebral atrophy, which is caused by pathological changes in gray matter or white matter. We demonstrated the great potential of such image processing and deep leaning combined automatic tissue image segmentation in personalized medicine, especially in monitoring, and treatments.

Impact of a Structured Reporting Template on Adherence to Prostate Imaging Reporting and Data System Version 2 and on the Diagnostic Performance of Prostate MRI for Clinically Significant Prostate Cancer.

PubMed

Shaish, Hiram; Feltus, Whitney; Steinman, Jonathan; Hecht, Elizabeth; Wenske, Sven; Ahmed, Firas

2018-05-01

The aim of this study was to assess the impact of a structured reporting template on adherence to the Prostate Imaging Reporting and Data System (PI-RADS) version 2 lexicon and on the diagnostic performance of prostate MRI to detect clinically significant prostate cancer (CS-PCa). An imaging database was searched for consecutive patients who underwent prostate MRI followed by MRI-ultrasound fusion biopsy from October 2015 through October 2017. The initial MRI reporting template used included only subheadings. In July 2016, the template was changed to a standardized PI-RADS-compliant structured template incorporating dropdown menus. Lesion, patient characteristics, pathology, and adherence to the PI-RADS lexicon were extracted from MRI reports and patient charts. Diagnostic performance of prostate MRI to detect CS-PCa using combined ultrasound-MRI fusion and systematic biopsy as a reference standard was assessed. Three hundred twenty-four lesions in 202 patients (average age, 67 years; average prostate-specific antigen level, 5.9 ng/mL) were analyzed, including 217 MRI peripheral zone (PZ) lesions, 84 MRI non-PZ lesions, and 23 additional PZ lesions found on systematic biopsy but missed on MRI. Thirty-three percent (106 of 324) were CS-PCa. Adherence to the PI-RADS lexicon improved from 32.9% (50 of 152) to 88.4% (152 of 172) (P < .0001) after introduction of the structured template. The sensitivity of prostate MRI for CS-PCa in the PZ increased from 53% to 70% (P = .011). There was no significant change in specificity (60% versus 55%, P = .458). A structured template with dropdown menus incorporating the PI-RADS lexicon and classification rules improves adherence to PI-RADS and may increase the diagnostic performance of prostate MRI for CS-PCa. Copyright © 2018 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Automatic Atlas Based Electron Density and Structure Contouring for MRI-based Prostate Radiation Therapy on the Cloud

NASA Astrophysics Data System (ADS)

Dowling, J. A.; Burdett, N.; Greer, P. B.; Sun, J.; Parker, J.; Pichler, P.; Stanwell, P.; Chandra, S.; Rivest-Hénault, D.; Ghose, S.; Salvado, O.; Fripp, J.

2014-03-01

Our group have been developing methods for MRI-alone prostate cancer radiation therapy treatment planning. To assist with clinical validation of the workflow we are investigating a cloud platform solution for research purposes. Benefits of cloud computing can include increased scalability, performance and extensibility while reducing total cost of ownership. In this paper we demonstrate the generation of DICOM-RT directories containing an automatic average atlas based electron density image and fast pelvic organ contouring from whole pelvis MR scans.

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.

DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction.

PubMed

Yang, Guang; Yu, Simiao; Dong, Hao; Slabaugh, Greg; Dragotti, Pier Luigi; Ye, Xujiong; Liu, Fangde; Arridge, Simon; Keegan, Jennifer; Guo, Yike; Firmin, David; Keegan, Jennifer; Slabaugh, Greg; Arridge, Simon; Ye, Xujiong; Guo, Yike; Yu, Simiao; Liu, Fangde; Firmin, David; Dragotti, Pier Luigi; Yang, Guang; Dong, Hao

2018-06-01

Compressed sensing magnetic resonance imaging (CS-MRI) enables fast acquisition, which is highly desirable for numerous clinical applications. This can not only reduce the scanning cost and ease patient burden, but also potentially reduce motion artefacts and the effect of contrast washout, thus yielding better image quality. Different from parallel imaging-based fast MRI, which utilizes multiple coils to simultaneously receive MR signals, CS-MRI breaks the Nyquist-Shannon sampling barrier to reconstruct MRI images with much less required raw data. This paper provides a deep learning-based strategy for reconstruction of CS-MRI, and bridges a substantial gap between conventional non-learning methods working only on data from a single image, and prior knowledge from large training data sets. In particular, a novel conditional Generative Adversarial Networks-based model (DAGAN)-based model is proposed to reconstruct CS-MRI. In our DAGAN architecture, we have designed a refinement learning method to stabilize our U-Net based generator, which provides an end-to-end network to reduce aliasing artefacts. To better preserve texture and edges in the reconstruction, we have coupled the adversarial loss with an innovative content loss. In addition, we incorporate frequency-domain information to enforce similarity in both the image and frequency domains. We have performed comprehensive comparison studies with both conventional CS-MRI reconstruction methods and newly investigated deep learning approaches. Compared with these methods, our DAGAN method provides superior reconstruction with preserved perceptual image details. Furthermore, each image is reconstructed in about 5 ms, which is suitable for real-time processing.

Local contrast-enhanced MR images via high dynamic range processing.

PubMed

Chandra, Shekhar S; Engstrom, Craig; Fripp, Jurgen; Neubert, Ales; Jin, Jin; Walker, Duncan; Salvado, Olivier; Ho, Charles; Crozier, Stuart

2018-09-01

To develop a local contrast-enhancing and feature-preserving high dynamic range (HDR) image processing algorithm for multichannel and multisequence MR images of multiple body regions and tissues, and to evaluate its performance for structure visualization, bias field (correction) mitigation, and automated tissue segmentation. A multiscale-shape and detail-enhancement HDR-MRI algorithm is applied to data sets of multichannel and multisequence MR images of the brain, knee, breast, and hip. In multisequence 3T hip images, agreement between automatic cartilage segmentations and corresponding synthesized HDR-MRI series were computed for mean voxel overlap established from manual segmentations for a series of cases. Qualitative comparisons between the developed HDR-MRI and standard synthesis methods were performed on multichannel 7T brain and knee data, and multisequence 3T breast and knee data. The synthesized HDR-MRI series provided excellent enhancement of fine-scale structure from multiple scales and contrasts, while substantially reducing bias field effects in 7T brain gradient echo, T 1 and T 2 breast images and 7T knee multichannel images. Evaluation of the HDR-MRI approach on 3T hip multisequence images showed superior outcomes for automatic cartilage segmentations with respect to manual segmentation, particularly around regions with hyperintense synovial fluid, across a set of 3D sequences. The successful combination of multichannel/sequence MR images into a single-fused HDR-MR image format provided consolidated visualization of tissues within 1 omnibus image, enhanced definition of thin, complex anatomical structures in the presence of variable or hyperintense signals, and improved tissue (cartilage) segmentation outcomes. © 2018 International Society for Magnetic Resonance in Medicine.

MRI Segmentation of the Human Brain: Challenges, Methods, and Applications

PubMed Central

Despotović, Ivana

2015-01-01

Image segmentation is one of the most important tasks in medical image analysis and is often the first and the most critical step in many clinical applications. In brain MRI analysis, image segmentation is commonly used for measuring and visualizing the brain's anatomical structures, for analyzing brain changes, for delineating pathological regions, and for surgical planning and image-guided interventions. In the last few decades, various segmentation techniques of different accuracy and degree of complexity have been developed and reported in the literature. In this paper we review the most popular methods commonly used for brain MRI segmentation. We highlight differences between them and discuss their capabilities, advantages, and limitations. To address the complexity and challenges of the brain MRI segmentation problem, we first introduce the basic concepts of image segmentation. Then, we explain different MRI preprocessing steps including image registration, bias field correction, and removal of nonbrain tissue. Finally, after reviewing different brain MRI segmentation methods, we discuss the validation problem in brain MRI segmentation. PMID:25945121

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.

Structural and functional differences in the cingulate cortex relate to disease severity in anorexia nervosa

PubMed Central

Bär, Karl-Jürgen; de la Cruz, Feliberto; Berger, Sandy; Schultz, Carl Christoph; Wagner, Gerd

2015-01-01

Background The dysfunction of specific brain areas might account for the distortion of body image in patients with anorexia nervosa. The present study was designed to reveal brain regions that are abnormal in structure and function in patients with this disorder. We hypothesized, based on brain areas of altered activity in patients with anorexia nervosa and regions involved in pain processing, an interrelation of structural aberrations in the frontoparietal–cingulate network and aberrant functional activation during thermal pain processing in patients with the disorder. Methods We determined pain thresholds outside the MRI scanner in patients with anorexia nervosa and matched healthy controls. Thereafter, thermal pain stimuli were applied during fMRI imaging. Structural analyses with high-resolution structural T1-weighted volumes were performed using voxel-based morphometry and a surface-based approach. Results Twenty-six patients and 26 controls participated in our study, and owing to technical difficulties, 15 participants in each group were included in our fMRI analysis. Structural analyses revealed significantly decreased grey matter volume and cortical thickness in the frontoparietal–cingulate network in patients with anorexia nervosa. We detected an increased blood oxygen level–dependent signal in patients during the painful 45°C condition in the midcingulate and posterior cingulate cortex, which positively correlated with increased pain thresholds. Decreased grey matter and cortical thickness correlated negatively with pain thresholds, symptom severity and illness duration, but not with body mass index. Limitations The lack of a specific quantification of body image distortion is a limitation of our study. Conclusion This study provides further evidence for confined structural and functional brain abnormalities in patients with anorexia nervosa in brain regions that are involved in perception and integration of bodily stimuli. The association of structural and functional deviations with thermal thresholds as well as with clinical characteristics might indicate a common neuronal origin. PMID:25825813

Structural brain alterations in primary open angle glaucoma: a 3T MRI study

PubMed Central

Wang, Jieqiong; Li, Ting; Sabel, Bernhard A.; Chen, Zhiqiang; Wen, Hongwei; Li, Jianhong; Xie, Xiaobin; Yang, Diya; Chen, Weiwei; Wang, Ningli; Xian, Junfang; He, Huiguang

2016-01-01

Glaucoma is not only an eye disease but is also associated with degeneration of brain structures. We now investigated the pattern of visual and non-visual brain structural changes in 25 primary open angle glaucoma (POAG) patients and 25 age-gender-matched normal controls using T1-weighted imaging. MRI images were subjected to volume-based analysis (VBA) and surface-based analysis (SBA) in the whole brain as well as ROI-based analysis of the lateral geniculate nucleus (LGN), visual cortex (V1/2), amygdala and hippocampus. While VBA showed no significant differences in the gray matter volumes of patients, SBA revealed significantly reduced cortical thickness in the right frontal pole and ROI-based analysis volume shrinkage in LGN bilaterally, right V1 and left amygdala. Structural abnormalities were correlated with clinical parameters in a subset of the patients revealing that the left LGN volume was negatively correlated with bilateral cup-to-disk ratio (CDR), the right LGN volume was positively correlated with the mean deviation of the right visual hemifield, and the right V1 cortical thickness was negatively correlated with the right CDR in glaucoma. These results demonstrate that POAG affects both vision-related structures and non-visual cortical regions. Moreover, alterations of the brain visual structures reflect the clinical severity of glaucoma. PMID:26743811

PC software package to confront multimodality images and a stereotactic atlas in neurosurgery

NASA Astrophysics Data System (ADS)

Barillot, Christian; Lemoine, Didier; Gibaud, Bernard; Toulemont, P. J.; Scarabin, Jean-Marie

1990-07-01

The aim of this application is to interactively transfer information between CT, MRI or DSA data and a 3D stereotactic atlas digitized on a C. Based on a 3D organization of data, this system is devoted to assist a neurosurgeon in surgical planning by numerically cross-assigning information between heterogeneous data (in-vivo or atlas). All these images can be retrieved in digital form from the PACS central archive (SIRENE PACS system). The basic feature of this confrontation is the Talairach's proportional squaring which consists in dividing the 3D cerebral space in independently deformable sub-parts. This 3D model is based on anatomical structures such as the AC-PC line and its two associated vertical lines VAC and VPC. Based on this proportional squaring, the atlas has been digitized in order to get atlas plates along the three orthogonal directions of this geometrical reference (axial, coronal, sagittal). The registration of in-vivo data to the proportional squaring is done by extracting either external framework landmarks or anatomical reference structures (i.e. AC and PC structures on the MRI sagittal mid-plane image). Geometrical transformations and scaling are then recorded for each modality or acquisition according to the proportional squaring. These transformations make for instance possible the transfer of a 3D point of a MRI examination to its 3D location within the proportional squaring and furthermore to its 3D location within another data set (in-vivo or atlas). From that stage, the application gives the choice to the neurosurgeon to select any confrontation between input data (in-vivo images or atlas) and output data (id).

Framework for 2D-3D image fusion of infrared thermography with preoperative MRI.

PubMed

Hoffmann, Nico; Weidner, Florian; Urban, Peter; Meyer, Tobias; Schnabel, Christian; Radev, Yordan; Schackert, Gabriele; Petersohn, Uwe; Koch, Edmund; Gumhold, Stefan; Steiner, Gerald; Kirsch, Matthias

2017-11-27

Multimodal medical image fusion combines information of one or more images in order to improve the diagnostic value. While previous applications mainly focus on merging images from computed tomography, magnetic resonance imaging (MRI), ultrasonic and single-photon emission computed tomography, we propose a novel approach for the registration and fusion of preoperative 3D MRI with intraoperative 2D infrared thermography. Image-guided neurosurgeries are based on neuronavigation systems, which further allow us track the position and orientation of arbitrary cameras. Hereby, we are able to relate the 2D coordinate system of the infrared camera with the 3D MRI coordinate system. The registered image data are now combined by calibration-based image fusion in order to map our intraoperative 2D thermographic images onto the respective brain surface recovered from preoperative MRI. In extensive accuracy measurements, we found that the proposed framework achieves a mean accuracy of 2.46 mm.

Anatomic study of the canine stifle using low-field magnetic resonance imaging (MRI) and MRI arthrography.

PubMed

Pujol, Esteban; Van Bree, Henri; Cauzinille, Laurent; Poncet, Cyrill; Gielen, Ingrid; Bouvy, Bernard

2011-06-01

To investigate the use of low-field magnetic resonance imaging (MRI) and MR arthrography in normal canine stifles and to compare MRI images to gross dissection. Descriptive study. Adult canine pelvic limbs (n=17). Stifle joints from 12 dogs were examined by orthopedic and radiographic examination, synovial fluid analysis, and MRI performed using a 0.2 T system. Limbs 1 to 7 were used to develop the MR and MR arthrography imaging protocol. Limbs 8-17 were studied with the developed MR and MR arthrography protocol and by gross dissection. Three sequences were obtained: T1-weighted spin echo (SE) in sagittal, dorsal, and transverse plane; T2-weighted SE in sagittal plane and T1-gradient echo in sagittal plane. Specific bony and soft tissue structures were easily identifiable with the exception of articular cartilage. The cranial and caudal cruciate ligaments were identified. Medial and lateral menisci were seen as wedge-shaped hypointense areas. MR arthrography permitted further delineation of specific structures. MR images corresponded with gross dissection morphology. With the exception of poor delineation of articular cartilage, a low-field MRI and MR arthrography protocol provides images of adequate quality to assess the normal canine stifle joint. © Copyright 2011 by The American College of Veterinary Surgeons.

An illustrative overview of semi-quantitative MRI scoring of knee osteoarthritis: lessons learned from longitudinal observational studies.

PubMed

Roemer, F W; Hunter, D J; Crema, M D; Kwoh, C K; Ochoa-Albiztegui, E; Guermazi, A

2016-02-01

To introduce the most popular magnetic resonance imaging (MRI) osteoarthritis (OA) semi-quantitative (SQ) scoring systems to a broader audience with a focus on the most commonly applied scores, i.e., the MOAKS and WORMS system and illustrate similarities and differences. While the main structure and methodology of each scoring system are publicly available, the core of this overview will be an illustrative imaging atlas section including image examples from multiple OA studies applying MRI in regard to different features assessed, show specific examples of different grades and point out pitfalls and specifics of SQ assessment including artifacts, blinding to time point of acquisition and within-grade evaluation. Similarities and differences between different scoring systems are presented. Technical considerations are followed by a brief description of the most commonly utilized SQ scoring systems including their responsiveness and reliability. The second part is comprised of the atlas section presenting illustrative image examples. Evidence suggests that SQ assessment of OA by expert MRI readers is valid, reliable and responsive, which helps investigators to understand the natural history of this complex disease and to evaluate potential new drugs in OA clinical trials. Researchers have to be aware of the differences and specifics of the different systems to be able to engage in imaging assessment and interpretation of imaging-based data. SQ scoring has enabled us to explain associations of structural tissue damage with clinical manifestations of the disease and with morphological alterations thought to represent disease progression. Copyright © 2015 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

An illustrative overview of semi-quantitative MRI scoring of knee osteoarthritis: Lessons learned from longitudinal observational studies

PubMed Central

Roemer, Frank W.; Hunter, David J.; Crema, Michel D.; Kwoh, C. Kent; Ochoa-Albiztegui, Elena; Guermazi, Ali

2015-01-01

Objective To introduce the most popular magnetic resonance imaging (MRI) osteoarthritis (OA) semi-quantitative (SQ) scoring systems to a broader audience with a focus on the most commonly applied scores, i.e. the MOAKS and WORMS system and illustrate similarities and differences. Design While the main structure and methodology of each scoring system are publicly available, the core of this overview will be an illustrative imaging atlas section including image examples from multiple osteoarthritis studies applying MRI in regard to different features assessed, show specific examples of different grades and point out pitfalls and specifics of SQ assessment including artifacts, blinding to time point of acquisition and within-grade evaluation. Results Similarities and differences between different scoring systems are presented. Technical considerations are followed by a brief description of the most commonly utilized SQ scoring systems including their responsiveness and reliability. The second part is comprised of the atlas section presenting illustrative image examples. Conclusions Evidence suggests that SQ assessment of OA by expert MRI readers is valid, reliable and responsive, which helps investigators to understand the natural history of this complex disease and to evaluate potential new drugs in OA clinical trials. Researchers have to be aware of the differences and specifics of the different systems to be able to engage in imaging assessment and interpretation of imaging-based data. SQ scoring has enabled us to explain associations of structural tissue damage with clinical manifestations of the disease and with morphological alterations thought to represent disease progression. PMID:26318656

Reconstruction of 7T-Like Images From 3T MRI

PubMed Central

Bahrami, Khosro; Shi, Feng; Zong, Xiaopeng; Shin, Hae Won; An, Hongyu

2016-01-01

In the recent MRI scanning, ultra-high-field (7T) MR imaging provides higher resolution and better tissue contrast compared to routine 3T MRI, which may help in more accurate and early brain diseases diagnosis. However, currently, 7T MRI scanners are more expensive and less available at clinical and research centers. These motivate us to propose a method for the reconstruction of images close to the quality of 7T MRI, called 7T-like images, from 3T MRI, to improve the quality in terms of resolution and contrast. By doing so, the post-processing tasks, such as tissue segmentation, can be done more accurately and brain tissues details can be seen with higher resolution and contrast. To do this, we have acquired a unique dataset which includes paired 3T and 7T images scanned from same subjects, and then propose a hierarchical reconstruction based on group sparsity in a novel multi-level Canonical Correlation Analysis (CCA) space, to improve the quality of 3T MR image to be 7T-like MRI. First, overlapping patches are extracted from the input 3T MR image. Then, by extracting the most similar patches from all the aligned 3T and 7T images in the training set, the paired 3T and 7T dictionaries are constructed for each patch. It is worth noting that, for the training, we use pairs of 3T and 7T MR images from each training subject. Then, we propose multi-level CCA to map the paired 3T and 7T patch sets to a common space to increase their correlations. In such space, each input 3T MRI patch is sparsely represented by the 3T dictionary and then the obtained sparse coefficients are used together with the corresponding 7T dictionary to reconstruct the 7T-like patch. Also, to have the structural consistency between adjacent patches, the group sparsity is employed. This reconstruction is performed with changing patch sizes in a hierarchical framework. Experiments have been done using 13 subjects with both 3T and 7T MR images. The results show that our method outperforms previous methods and is able to recover better structural details. Also, to place our proposed method in a medical application context, we evaluated the influence of post-processing methods such as brain tissue segmentation on the reconstructed 7T-like MR images. Results show that our 7T-like images lead to higher accuracy in segmentation of white matter (WM), gray matter (GM), cerebrospinal fluid (CSF), and skull, compared to segmentation of 3T MR images. PMID:27046894

Classification of the venous architecture of the pineal gland by 7T MRI.

PubMed

Cho, Zang-Hee; Choi, Sang-Han; Chi, Je-Gun; Kim, Young-Bo

2011-10-01

Magnetic resonance imaging (MRI) at 7.0 Tesla (7T) can show many details of anatomical structures with unprecedented resolution and contrast. In this report, we describe for the first time the unexpected wide variation in pineal gland structure, as visualized by MR images obtained with 7T in a group of healthy young volunteers. A total of 34 volunteers (22 men and 12 women) were enrolled in the study. Their 7T MR images revealed such wide variations in pineal gland shape that it led us to attempt to classify the patterns seen in these pineal glands. Indeed, they were successfully correlated with a previous human cadaver study of venous structures by Tamaki et al., who classified the venous structures of the pineal gland into three categories. This is the first human in vivo pineal vein imaging study using 7T MRI. Pineal venous imaging may permit the early diagnosis of a pineal tumor. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

MRI in multiple sclerosis: current status and future prospects

PubMed Central

Bakshi, Rohit; Thompson, Alan J; Rocca, Maria A; Pelletier, Daniel; Dousset, Vincent; Barkhof, Frederik; Inglese, Matilde; Guttmann, Charles R G; Horsfield, Mark A; Filippi, Massimo

2008-01-01

Many promising MRI approaches for research or clinical management of multiple sclerosis (MS) have recently emerged, or are under development or refinement. Advanced MRI methods need to be assessed to determine whether they allow earlier diagnosis or better identification of phenotypes. Improved post-processing should allow more efficient and complete extraction of information from images. Magnetic resonance spectroscopy should improve in sensitivity and specificity with higher field strengths and should enable the detection of a wider array of metabolites. Diffusion imaging is moving closer to the goal of defining structural connectivity and, thereby, determining the functional significance of lesions at specific locations. Cell-specific imaging now seems feasible with new magnetic resonance contrast agents. The imaging of myelin water fraction brings the hope of providing a specific measure of myelin content. Ultra-high-field MRI increases sensitivity, but also presents new technical challenges. Here, we review these recent developments in MRI for MS, and also look forward to refinements in spinal-cord imaging, optic-nerve imaging, perfusion MRI, and functional MRI. Advances in MRI should improve our ability to diagnose, monitor, and understand the pathophysiology of MS. PMID:18565455

MRI-negative temporal lobe epilepsy-What do we know?

PubMed

Muhlhofer, Wolfgang; Tan, Yee-Leng; Mueller, Susanne G; Knowlton, Robert

2017-05-01

Temporal lobe epilepsy (TLE) is the most common focal epilepsy in adults. TLE has a high chance of becoming medically refractory, and as such, is frequently considered for further evaluation and surgical intervention. Up to 30% of TLE cases, however, can have normal ("nonlesional" or negative) magnetic resonance imaging (MRI) results, which complicates the presurgical workup and has been associated with worse surgical outcomes. Helped by contributions from advanced imaging techniques and electrical source localization, the number of surgeries performed on MRI-negative TLE has increased over the last decade. Thereby new epidemiologic, clinical, electrophysiologic, neuropathologic, and surgical data of MRI-negative TLE has emerged, showing characteristics that are distinct from those of lesional TLE. This review article summarizes what we know today about MRI-negative TLE, and discusses the comprehensive assessment of patients with MRI-negative TLE in a structured and systematic approach. It also includes a concise description of the most recent developments in structural and functional imaging, and highlights postprocessing imaging techniques that have been shown to add localization value in MRI-negative epilepsies. We evaluate surgical outcomes of MRI-negative TLE, identify prognostic makers of postoperative seizure freedom, and discuss strategies for optimizing the selection of surgical candidates in this group. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Carbon-Based Nanostructures as Advanced Contrast Agents for Magnetic Resonance Imaging

NASA Astrophysics Data System (ADS)

Ananta Narayanan, Jeyarama S.

2011-12-01

Superparamagnetic carbon-based nanostructures are presented as contrast agents (CAs) for advanced imaging applications such as cellular and molecular imaging using magnetic resonance imaging (MRI). Gadolinium-loaded, ultra-short single-walled carbon nanotubes (gadonanotubes; GNTs) are shown to have extremely high r1 relaxivities (contrast enhancement efficacy), especially at low-magnetic field strengths. The inherent lipophilicity of GNTs provides them the ability to image cells at low magnetic field strength. A carboxylated dextran-coated GNT (GadoDex) has been synthesized and proposed as a new biocompatible high-performance MRI CA. The r1 relaxivity is ca. 20 times greater than for other paramagnetic Gd-based CAs. This enhanced relaxivity for GadoDex is due to the synergistic effects of an increased molecular tumbling time (tauR) and a faster proton exchange rate (taum). GNTs also exhibit very large transverse relaxivities (r2) at high magnetic fields (≥ 3 T). The dependence of the transverse relaxation rates (especially R2*) of labeled cells on GNT concentration offers the possibility to quantify cell population in vivo using R2* mapping. The cell-labeling efficiency and high transverse relaxivities of GNTs has enabled the first non-iron oxide-based single-cell imaging using MRI. The residual metal catalyst particles of SWNT materials also have transverse relaxation properties. All of the SWNT materials exhibit superior transverse relaxation properties. However, purified SWNTs and US-tubes with less residual metal content exhibit better transverse relaxivities (r2), demonstrating the importance of the SWNT structure for enhanced MRI CA performance. A strategy to improve the r1 relaxivity of Gd-CAs by geometrically confining them within porous silicon particles (SiMPs) has been investigated. The enhancement in relaxivity is attributed to the slow diffusion of water molecules through the pores and the increase in the molecular tumbling time of the nanoconstruct. The universality of the strategy has been demonstrated for GNTs, gadofullerols and clinically-used MagnevistRTM. In summary, primary nanoscale confinement of Gd3+ ions in US-tubes has resulted in a new class of CAs which could revitalize low-field contrast-enhanced MRI, while extending and complementing current high-field MRI technology, as well. The observed boost in relaxivity upon a secondary nanoscale confinement of Gd-CAs within SiMPs suggests that additional unforeseen nanoscale effects may have the potential to further boost performance of MRI CAs.

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.

[The Application of Magnetic Resonance Imaging in Alzheimer's Disease].

PubMed

Matsuda, Hiroshi

2017-07-01

In Alzheimer's disease (AD), magnetic resonance imaging (MRI) is essential for early diagnosis, differential diagnosis, and evaluation of disease progression. In structural MRI, the automatic diagnosis of atrophy by computers, even when it is not visually noticeable, is possible in daily clinical practice. Furthermore, subfield volumetric measurements of the medial temporal structures, as well as longitudinal volume measurements with high accuracy, have been developed and are useful for calculating the needed sample size in clinical trials. In addition to detecting local atrophy, graph theory has been applied to structural MRI for evaluation of alterations of the brain networks potentially affected in AD.

Imaging of skull base lesions.

PubMed

Kelly, Hillary R; Curtin, Hugh D

2016-01-01

Skull base imaging requires a thorough knowledge of the complex anatomy of this region, including the numerous fissures and foramina and the major neurovascular structures that traverse them. Computed tomography (CT) and magnetic resonance imaging (MRI) play complementary roles in imaging of the skull base. MR is the preferred modality for evaluation of the soft tissues, the cranial nerves, and the medullary spaces of bone, while CT is preferred for demonstrating thin cortical bone structure. The anatomic location and origin of a lesion as well as the specific CT and MR findings can often narrow the differential diagnosis to a short list of possibilities. However, the primary role of the imaging specialist in evaluating the skull base is usually to define the extent of the lesion and determine its relationship to vital neurovascular structures. Technologic advances in imaging and radiation therapy, as well as surgical technique, have allowed for more aggressive approaches and improved outcomes, further emphasizing the importance of precise preoperative mapping of skull base lesions via imaging. Tumors arising from and affecting the cranial nerves at the skull base are considered here. © 2016 Elsevier B.V. All rights reserved.

MRI Scans

MedlinePlus

Magnetic resonance imaging (MRI) uses a large magnet and radio waves to look at organs and structures inside your body. Health care professionals use MRI scans to diagnose a variety of conditions, from torn ...

Macromolecular and Dendrimer Based Magnetic Resonance Contrast Agents

PubMed Central

Bumb, Ambika; Brechbiel, Martin W.; Choyke, Peter

2010-01-01

Magnetic resonance imaging (MRI) is a powerful imaging modality that can provide an assessment of function or molecular expression in tandem with anatomic detail. Over the last 20–25 years, a number of gadolinium based MR contrast agents have been developed to enhance signal by altering proton relaxation properties. This review explores a range of these agents from small molecule chelates, such as Gd-DTPA and Gd-DOTA, to macromolecular structures composed of albumin, polylysine, polysaccharides (dextran, inulin, starch), poly(ethylene glycol), copolymers of cystamine and cystine with GD-DTPA, and various dendritic structures based on polyamidoamine and polylysine (Gadomers). The synthesis, structure, biodistribution and targeting of dendrimer-based MR contrast agents are also discussed. PMID:20590365

GADOLINIUM(Gd)-BASED and Ion Oxide Nanoparticle Contrast Agents for Pre-Clinical and Clinical Magnetic Resonance Imaging (mri) Research

NASA Astrophysics Data System (ADS)

Ng, Thian C.

2012-06-01

It is known that one strength of MRI is its excellent soft tissue discrimination. It naturally provides sufficient contrast between the structural differences of normal and pathological tissues, their spatial extent and progression. However, to further extend its applications and enhance even more contrast for clinical studies, various Gadolinium (Gd)-based contrast agents have been developed for different organs (brain strokes, cancer, cardio-MRI, etc). These Gd-based contrast agents are paramagnetic compounds that have strong T1-effect for enhancing the contrast between tissue types. Gd-contrast can also enhance magnetic resonance angiography (CE-MRA) for studying stenosis and for measuring perfusion, vascular susceptibility, interstitial space, etc. Another class of contrast agents makes use of ferrite iron oxide nanoparticles (including Superparamagnetic Ion Oxide (SPIO) and Ultrasmall Superparamagnetic Iron Oxide (USPIO)). These nanoparticles have superior magnetic susceptibility effect and produce a drop in signal, namely in T2*-weighted images, useful for the determination of lymph nodes metastases, angiogenesis and arteriosclerosis plaques.

[Magnetic resonance imaging of the penis. Its normal anatomy].

PubMed

Banchik, E L; Mineev, N I; Mitusov, V V; Dombrovskiĭ, V I; Kogan, M I

2012-01-01

To estimate the capabilities of magnetic resonance imaging (MRI) to identify penile anatomic structures and their topographic relationships. Penile MRI results were analyzed in 52 men of different ages who had no history, clinical, laboratory, and radiological data in favor of diseases of this organ. Penile imaging technology and its algorithm, including patient preparation and posi-tioning and a list of impulse sequences and their parameters, are proposed. Penile MRI and anatomy are described in detail; magnetic resonance signal characteristics of the main structural elements of the organ and its adjacent tissues on T1- and T2-weighted images are specified. The MRI morphometry results of the cavernous and spongy bodies, urethra, and penis as a whole, which agree well with the similar known literature data, are given. The investigation has provided evidence for the high informative value of the technique in recognizing the relatively small anatomic structures of the penis, which is comparable with that of the morphological study of a gross specimen of this organ, which in turn predetermines a further investigation of the capabilities of MRI to diagnose penile diseases and to estimate the quality of their treatment.

Developing 3D microscopy with CLARITY on human brain tissue: Towards a tool for informing and validating MRI-based histology.

PubMed

Morawski, Markus; Kirilina, Evgeniya; Scherf, Nico; Jäger, Carsten; Reimann, Katja; Trampel, Robert; Gavriilidis, Filippos; Geyer, Stefan; Biedermann, Bernd; Arendt, Thomas; Weiskopf, Nikolaus

2017-11-28

Recent breakthroughs in magnetic resonance imaging (MRI) enabled quantitative relaxometry and diffusion-weighted imaging with sub-millimeter resolution. Combined with biophysical models of MR contrast the emerging methods promise in vivo mapping of cyto- and myelo-architectonics, i.e., in vivo histology using MRI (hMRI) in humans. The hMRI methods require histological reference data for model building and validation. This is currently provided by MRI on post mortem human brain tissue in combination with classical histology on sections. However, this well established approach is limited to qualitative 2D information, while a systematic validation of hMRI requires quantitative 3D information on macroscopic voxels. We present a promising histological method based on optical 3D imaging combined with a tissue clearing method, Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging compatible Tissue hYdrogel (CLARITY), adapted for hMRI validation. Adapting CLARITY to the needs of hMRI is challenging due to poor antibody penetration into large sample volumes and high opacity of aged post mortem human brain tissue. In a pilot experiment we achieved transparency of up to 8 mm-thick and immunohistochemical staining of up to 5 mm-thick post mortem brain tissue by a combination of active and passive clearing, prolonged clearing and staining times. We combined 3D optical imaging of the cleared samples with tailored image processing methods. We demonstrated the feasibility for quantification of neuron density, fiber orientation distribution and cell type classification within a volume with size similar to a typical MRI voxel. The presented combination of MRI, 3D optical microscopy and image processing is a promising tool for validation of MRI-based microstructure estimates. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A dual model HU conversion from MRI intensity values within and outside of bone segment for MRI-based radiotherapy treatment planning of prostate cancer

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

Korhonen, Juha, E-mail: juha.p.korhonen@hus.fi; Department of Oncology, Helsinki University Central Hospital, POB-180, 00029 HUS; Kapanen, Mika

2014-01-15

Purpose: The lack of electron density information in magnetic resonance images (MRI) poses a major challenge for MRI-based radiotherapy treatment planning (RTP). In this study the authors convert MRI intensity values into Hounsfield units (HUs) in the male pelvis and thus enable accurate MRI-based RTP for prostate cancer patients with varying tissue anatomy and body fat contents. Methods: T{sub 1}/T{sub 2}*-weighted MRI intensity values and standard computed tomography (CT) image HUs in the male pelvis were analyzed using image data of 10 prostate cancer patients. The collected data were utilized to generate a dual model HU conversion technique from MRImore » intensity values of the single image set separately within and outside of contoured pelvic bones. Within the bone segment local MRI intensity values were converted to HUs by applying a second-order polynomial model. This model was tuned for each patient by two patient-specific adjustments: MR signal normalization to correct shifts in absolute intensity level and application of a cutoff value to accurately represent low density bony tissue HUs. For soft tissues, such as fat and muscle, located outside of the bone contours, a threshold-based segmentation method without requirements for any patient-specific adjustments was introduced to convert MRI intensity values into HUs. The dual model HU conversion technique was implemented by constructing pseudo-CT images for 10 other prostate cancer patients. The feasibility of these images for RTP was evaluated by comparing HUs in the generated pseudo-CT images with those in standard CT images, and by determining deviations in MRI-based dose distributions compared to those in CT images with 7-field intensity modulated radiation therapy (IMRT) with the anisotropic analytical algorithm and 360° volumetric-modulated arc therapy (VMAT) with the Voxel Monte Carlo algorithm. Results: The average HU differences between the constructed pseudo-CT images and standard CT images of each test patient ranged from −2 to 5 HUs and from 22 to 78 HUs in soft and bony tissues, respectively. The average local absolute value differences were 11 HUs in soft tissues and 99 HUs in bones. The planning target volume doses (volumes 95%, 50%, 5%) in the pseudo-CT images were within 0.8% compared to those in CT images in all of the 20 treatment plans. The average deviation was 0.3%. With all the test patients over 94% (IMRT) and 92% (VMAT) of dose points within body (lower than 10% of maximum dose suppressed) passed the 1 mm and 1% 2D gamma index criterion. The statistical tests (t- and F-tests) showed significantly improved (p ≤ 0.05) HU and dose calculation accuracies with the soft tissue conversion method instead of homogeneous representation of these tissues in MRI-based RTP images. Conclusions: This study indicates that it is possible to construct high quality pseudo-CT images by converting the intensity values of a single MRI series into HUs in the male pelvis, and to use these images for accurate MRI-based prostate RTP dose calculations.« less

Multi-modal image registration: matching MRI with histology

NASA Astrophysics Data System (ADS)

Alic, Lejla; Haeck, Joost C.; Klein, Stefan; Bol, Karin; van Tiel, Sandra T.; Wielopolski, Piotr A.; Bijster, Magda; Niessen, Wiro J.; Bernsen, Monique; Veenland, Jifke F.; de Jong, Marion

2010-03-01

Spatial correspondence between histology and multi sequence MRI can provide information about the capabilities of non-invasive imaging to characterize cancerous tissue. However, shrinkage and deformation occurring during the excision of the tumor and the histological processing complicate the co registration of MR images with histological sections. This work proposes a methodology to establish a detailed 3D relation between histology sections and in vivo MRI tumor data. The key features of the methodology are a very dense histological sampling (up to 100 histology slices per tumor), mutual information based non-rigid B-spline registration, the utilization of the whole 3D data sets, and the exploitation of an intermediate ex vivo MRI. In this proof of concept paper, the methodology was applied to one tumor. We found that, after registration, the visual alignment of tumor borders and internal structures was fairly accurate. Utilizing the intermediate ex vivo MRI, it was possible to account for changes caused by the excision of the tumor: we observed a tumor expansion of 20%. Also the effects of fixation, dehydration and histological sectioning could be determined: 26% shrinkage of the tumor was found. The annotation of viable tissue, performed in histology and transformed to the in vivo MRI, matched clearly with high intensity regions in MRI. With this methodology, histological annotation can be directly related to the corresponding in vivo MRI. This is a vital step for the evaluation of the feasibility of multi-spectral MRI to depict histological groundtruth.

Translating Neurocognitive Models of Auditory-Verbal Hallucinations into Therapy: Using Real-time fMRI-Neurofeedback to Treat Voices

PubMed Central

Fovet, Thomas; Orlov, Natasza; Dyck, Miriam; Allen, Paul; Mathiak, Klaus; Jardri, Renaud

2016-01-01

Auditory-verbal hallucinations (AVHs) are frequent and disabling symptoms, which can be refractory to conventional psychopharmacological treatment in more than 25% of the cases. Recent advances in brain imaging allow for a better understanding of the neural underpinnings of AVHs. These findings strengthened transdiagnostic neurocognitive models that characterize these frequent and disabling experiences. At the same time, technical improvements in real-time functional magnetic resonance imaging (fMRI) enabled the development of innovative and non-invasive methods with the potential to relieve psychiatric symptoms, such as fMRI-based neurofeedback (fMRI-NF). During fMRI-NF, brain activity is measured and fed back in real time to the participant in order to help subjects to progressively achieve voluntary control over their own neural activity. Precisely defining the target brain area/network(s) appears critical in fMRI-NF protocols. After reviewing the available neurocognitive models for AVHs, we elaborate on how recent findings in the field may help to develop strong a priori strategies for fMRI-NF target localization. The first approach relies on imaging-based “trait markers” (i.e., persistent traits or vulnerability markers that can also be detected in the presymptomatic and remitted phases of AVHs). The goal of such strategies is to target areas that show aberrant activations during AVHs or are known to be involved in compensatory activation (or resilience processes). Brain regions, from which the NF signal is derived, can be based on structural MRI and neurocognitive knowledge, or functional MRI information collected during specific cognitive tasks. Because hallucinations are acute and intrusive symptoms, a second strategy focuses more on “state markers.” In this case, the signal of interest relies on fMRI capture of the neural networks exhibiting increased activity during AVHs occurrences, by means of multivariate pattern recognition methods. The fine-grained activity patterns concomitant to hallucinations can then be fed back to the patients for therapeutic purpose. Considering the potential cost necessary to implement fMRI-NF, proof-of-concept studies are urgently required to define the optimal strategy for application in patients with AVHs. This technique has the potential to establish a new brain imaging-guided psychotherapy for patients that do not respond to conventional treatments and take functional neuroimaging to therapeutic applications. PMID:27445865

A highly sensitive x-ray imaging modality for hepatocellular carcinoma detection in vitro

NASA Astrophysics Data System (ADS)

Rand, Danielle; Walsh, Edward G.; Derdak, Zoltan; Wands, Jack R.; Rose-Petruck, Christoph

2015-01-01

Innovations that improve sensitivity and reduce cost are of paramount importance in diagnostic imaging. The novel x-ray imaging modality called spatial frequency heterodyne imaging (SFHI) is based on a linear arrangement of x-ray source, tissue, and x-ray detector, much like that of a conventional x-ray imaging apparatus. However, SFHI rests on a complete paradigm reversal compared to conventional x-ray absorption-based radiology: while scattered x-rays are carefully rejected in absorption-based x-ray radiology to enhance the image contrast, SFHI forms images exclusively from x-rays scattered by the tissue. In this study we use numerical processing to produce x-ray scatter images of hepatocellular carcinoma labeled with a nanoparticle contrast agent. We subsequently compare the sensitivity of SFHI in this application to that of both conventional x-ray imaging and magnetic resonance imaging (MRI). Although SFHI is still in the early stages of its development, our results show that the sensitivity of SFHI is an order of magnitude greater than that of absorption-based x-ray imaging and approximately equal to that of MRI. As x-ray imaging modalities typically have lower installation and service costs compared to MRI, SFHI could become a cost effective alternative to MRI, particularly in areas of the world with inadequate availability of MRI facilities.

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.

Resting-state fMRI and social cognition: An opportunity to connect.

PubMed

Doruyter, Alex; Groenewold, Nynke A; Dupont, Patrick; Stein, Dan J; Warwick, James M

2017-09-01

Many psychiatric disorders are characterized by altered social cognition. The importance of social cognition has previously been recognized by the National Institute of Mental Health Research Domain Criteria project, in which it features as a core domain. Social task-based functional magnetic resonance imaging (fMRI) currently offers the most direct insight into how the brain processes social information; however, resting-state fMRI may be just as important in understanding the biology and network nature of social processing. Resting-state fMRI allows researchers to investigate the functional relationships between brain regions in a neutral state: so-called resting functional connectivity (RFC). There is evidence that RFC is predictive of how the brain processes information during social tasks. This is important because it shifts the focus from possibly context-dependent aberrations to context-independent aberrations in functional network architecture. Rather than being analysed in isolation, the study of resting-state brain networks shows promise in linking results of task-based fMRI results, structural connectivity, molecular imaging findings, and performance measures of social cognition-which may prove crucial in furthering our understanding of the social brain. Copyright © 2017 John Wiley & Sons, Ltd.

Wavelet-based de-noising algorithm for images acquired with parallel magnetic resonance imaging (MRI).

PubMed

Delakis, Ioannis; Hammad, Omer; Kitney, Richard I

2007-07-07

Wavelet-based de-noising has been shown to improve image signal-to-noise ratio in magnetic resonance imaging (MRI) while maintaining spatial resolution. Wavelet-based de-noising techniques typically implemented in MRI require that noise displays uniform spatial distribution. However, images acquired with parallel MRI have spatially varying noise levels. In this work, a new algorithm for filtering images with parallel MRI is presented. The proposed algorithm extracts the edges from the original image and then generates a noise map from the wavelet coefficients at finer scales. The noise map is zeroed at locations where edges have been detected and directional analysis is also used to calculate noise in regions of low-contrast edges that may not have been detected. The new methodology was applied on phantom and brain images and compared with other applicable de-noising techniques. The performance of the proposed algorithm was shown to be comparable with other techniques in central areas of the images, where noise levels are high. In addition, finer details and edges were maintained in peripheral areas, where noise levels are low. The proposed methodology is fully automated and can be applied on final reconstructed images without requiring sensitivity profiles or noise matrices of the receiver coils, therefore making it suitable for implementation in a clinical MRI setting.

Accelerated High-Dimensional MR Imaging with Sparse Sampling Using Low-Rank Tensors

PubMed Central

He, Jingfei; Liu, Qiegen; Christodoulou, Anthony G.; Ma, Chao; Lam, Fan

2017-01-01

High-dimensional MR imaging often requires long data acquisition time, thereby limiting its practical applications. This paper presents a low-rank tensor based method for accelerated high-dimensional MR imaging using sparse sampling. This method represents high-dimensional images as low-rank tensors (or partially separable functions) and uses this mathematical structure for sparse sampling of the data space and for image reconstruction from highly undersampled data. More specifically, the proposed method acquires two datasets with complementary sampling patterns, one for subspace estimation and the other for image reconstruction; image reconstruction from highly undersampled data is accomplished by fitting the measured data with a sparsity constraint on the core tensor and a group sparsity constraint on the spatial coefficients jointly using the alternating direction method of multipliers. The usefulness of the proposed method is demonstrated in MRI applications; it may also have applications beyond MRI. PMID:27093543

Tractography-Based Score for Learning Effective Connectivity From Multimodal Imaging Data Using Dynamic Bayesian Networks.

PubMed

Dang, Shilpa; Chaudhury, Santanu; Lall, Brejesh; Roy, Prasun K

2018-05-01

Effective connectivity (EC) is the methodology for determining functional-integration among the functionally active segregated regions of the brain. By definition EC is "the causal influence exerted by one neuronal group on another" which is constrained by anatomical connectivity (AC) (axonal connections). AC is necessary for EC but does not fully determine it, because synaptic communication occurs dynamically in a context-dependent fashion. Although there is a vast emerging evidence of structure-function relationship using multimodal imaging studies, till date only a few studies have done joint modeling of the two modalities: functional MRI (fMRI) and diffusion tensor imaging (DTI). We aim to propose a unified probabilistic framework that combines information from both sources to learn EC using dynamic Bayesian networks (DBNs). DBNs are probabilistic graphical temporal models that learn EC in an exploratory fashion. Specifically, we propose a novel anatomically informed (AI) score that evaluates fitness of a given connectivity structure to both DTI and fMRI data simultaneously. The AI score is employed in structure learning of DBN given the data. Experiments with synthetic-data demonstrate the face validity of structure learning with our AI score over anatomically uninformed counterpart. Moreover, real-data results are cross-validated by performing classification-experiments. EC inferred on real fMRI-DTI datasets is found to be consistent with previous literature and show promising results in light of the AC present as compared to other classically used techniques such as Granger-causality. Multimodal analyses provide a more reliable basis for differentiating brain under abnormal/diseased conditions than the single modality analysis.

Frequency, Prognosis and Surgical Treatment of Structural Abnormalities Seen with Magnetic Resonance Imaging in Childhood Epilepsy

ERIC Educational Resources Information Center

Berg, Anne T.; Mathern, Gary W.; Bronen, Richard A.; Fulbright, Robert K.; DiMario, Francis; Testa, Francine M.; Levy, Susan R.

2009-01-01

The epidemiology of lesions identified by magnetic resonance imaging (MRI), along with the use of pre-surgical evaluations and surgery in childhood-onset epilepsy patients has not previously been described. In a prospectively identified community-based cohort of children enrolled from 1993 to 1997, we examined (i) the frequency of lesions…

MEG-guided analysis of 7T-MRI in patients with epilepsy.

PubMed

Colon, A J; Osch, M J P van; Buijs, M; Grond, J V D; Hillebrand, A; Schijns, O; Wagner, G J; Ossenblok, P; Hofman, P; Buchem, M A V; Boon, P

2018-05-26

To study possible detection of structural abnormalities on 7T MRI that were not detected on 3T MRI and estimate the added value of MEG-guidance. For abnormalities found, analysis of convergence between clinical, MEG and 7T MRI localization of suspected epileptogenic foci. In adult patients with well-documented localization-related epilepsy in whom a previous 3T MRI did not demonstrate an epileptogenic lesion but MEG indicated a plausible epileptogenic focus, 7T MRI was performed. Based on semiologic data, visual analysis of the 7T images was performed as well as based on prior MEG results. Correlation with other data from the patient charts, for as far as these were available, was analysed. To establish the level of concordance between the three observers the generalized or Fleiss kappa was calculated. In 3/19 patients abnormalities that, based on semiology, could plausibly represent an epileptogenic lesion were detected using 7T MRI. In an additional 3/19 an abnormality was detected after MEG-guidance. However, in these later cases there was no concordance among the three observers with regard to the presence of a structural abnormality. In one of these three cases intracranial recording was performed, proving the possible abnormality on 7T MRI to be the epileptogenic focus. In 32% of patients 7T MRI showed abnormalities that could indicate an epileptogenic lesion whereas previous 3T MRI did not, especially when visual inspection was guided by the presence of focal interictal MEG abnormalities. Copyright © 2018 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Ultra-high field upper extremity peripheral nerve and non-contrast enhanced vascular imaging

PubMed Central

Raval, Shailesh B.; Britton, Cynthia A.; Zhao, Tiejun; Krishnamurthy, Narayanan; Santini, Tales; Gorantla, Vijay S.; Ibrahim, Tamer S.

2017-01-01

Objective The purpose of this study was to explore the efficacy of Ultra-high field [UHF] 7 Tesla [T] MRI as compared to 3T MRI in non-contrast enhanced [nCE] imaging of structural anatomy in the elbow, forearm, and hand [upper extremity]. Materials and method A wide range of sequences including T1 weighted [T1] volumetric interpolate breath-hold exam [VIBE], T2 weighted [T2] double-echo steady state [DESS], susceptibility weighted imaging [SWI], time-of-flight [TOF], diffusion tensor imaging [DTI], and diffusion spectrum imaging [DSI] were optimized and incorporated with a radiofrequency [RF] coil system composed of a transverse electromagnetic [TEM] transmit coil combined with an 8-channel receive-only array for 7T upper extremity [UE] imaging. In addition, Siemens optimized protocol/sequences were used on a 3T scanner and the resulting images from T1 VIBE and T2 DESS were compared to that obtained at 7T qualitatively and quantitatively [SWI was only qualitatively compared]. DSI studio was utilized to identify nerves based on analysis of diffusion weighted derived fractional anisotropy images. Images of forearm vasculature were extracted using a paint grow manual segmentation method based on MIPAV [Medical Image Processing, Analysis, and Visualization]. Results High resolution and high quality signal-to-noise ratio [SNR] and contrast-to-noise ratio [CNR]—images of the hand, forearm, and elbow were acquired with nearly homogeneous 7T excitation. Measured [performed on the T1 VIBE and T2 DESS sequences] SNR and CNR values were almost doubled at 7T vs. 3T. Cartilage, synovial fluid and tendon structures could be seen with higher clarity in the 7T T1 and T2 weighted images. SWI allowed high resolution and better quality imaging of large and medium sized arteries and veins, capillary networks and arteriovenous anastomoses at 7T when compared to 3T. 7T diffusion weighted sequence [not performed at 3T] demonstrates that the forearm nerves are clearly delineated by fiber tractography. The proper digital palmar arteries and superficial palmar arch could also be clearly visualized using TOF nCE 7T MRI. Conclusion Ultra-high resolution neurovascular imaging in upper extremities is possible at 7T without use of renal toxic intravenous contrast. 7T MRI can provide superior peripheral nerve [based on fiber anisotropy and diffusion coefficient parameters derived from diffusion tensor/spectrum imaging] and vascular [nCE MRA and vessel segmentation] imaging. PMID:28662061

Magnetic Resonance Imaging in Aneurysmal Subarachnoid Hemorrhage: Current Evidence and Future Directions.

PubMed

Nelson, Sarah E; Sair, Haris I; Stevens, Robert D

2018-04-09

Aneurysmal subarachnoid hemorrhage (aSAH) is associated with an unacceptably high mortality and chronic disability in survivors, underscoring a need to validate new approaches for treatment and prognosis. The use of advanced imaging, magnetic resonance imaging (MRI) in particular, could help address this gap given its versatile capacity to quantitatively evaluate and map changes in brain anatomy, physiology and functional activation. Yet there is uncertainty about the real value of brain MRI in the clinical setting of aSAH. In this review, we discuss current and emerging MRI research in aSAH. PubMed was searched from inception to June 2017, and additional studies were then chosen on the basis of relevance to the topics covered in this review. Available studies suggest that brain MRI is a feasible, safe, and valuable testing modality. MRI detects brain abnormalities associated with neurologic examination, outcomes, and aneurysm treatment and thus has the potential to increase knowledge of aSAH pathophysiology as well as to guide management and outcome prediction. Newer pulse sequences have the potential to reveal structural and physiological changes that could also improve management of aSAH. Research is needed to confirm the value of MRI-based biomarkers in clinical practice and as endpoints in clinical trials, with the goal of improving outcome for patients with aSAH.

The role of magnetic resonance imaging in the diagnosis of Parkinson's disease: a review.

PubMed

Al-Radaideh, Ali M; Rababah, Eman M

2016-01-01

Parkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's in elderly people. Different structural and functional neuroimaging methods play a great role in the early diagnosis of neurodegenerative diseases. This review discusses the role of magnetic resonance imaging (MRI) in the diagnosis of PD. MRI provides clinicians with structural and functional information of human brain noninvasively. Advanced quantitative MRI techniques have shown promise for detecting pathological changes related to different stages of PD. Collectively, advanced MRI techniques at high and ultrahigh magnetic fields aid in better understanding of the nature and progression of PD. Copyright © 2016 Elsevier Inc. All rights reserved.

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

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.

Magnetic resonance imaging assisted management in five cases of suspected quittor.

PubMed

Meehan, Lucinda J; Taylor, Sarah E; Labens, Raphael; Cillán-García, Eugenio

2016-01-01

Assessment of the usefulness of magnetic resonance imaging (MRI) in treatment planning in suspected cases of quittor in the horse. Five horses with chronic discharging tracts at the level of the foot underwent MRI for treatment planning. The MRI examination revealed variable involvement of soft tissue and osseous structures of the foot in addition to abnormalities of the ungular cartilages in all cases. In two cases, follow-up MRI examination was performed. Four of five horses had a successful outcome, with three of these undergoing only one surgical procedure and one being managed medically. We believe that the use of preoperative MRI facilitated accurate determination of the structures involved in cases of quittor, guiding the management, surgical approach and postoperative therapy.

Numerical study on simultaneous emission and transmission tomography in the MRI framework

NASA Astrophysics Data System (ADS)

Gjesteby, Lars; Cong, Wenxiang; Wang, Ge

2017-09-01

Multi-modality imaging methods are instrumental for advanced diagnosis and therapy. Specifically, a hybrid system that combines computed tomography (CT), nuclear imaging, and magnetic resonance imaging (MRI) will be a Holy Grail of medical imaging, delivering complementary structural/morphological, functional, and molecular information for precision medicine. A novel imaging method was recently demonstrated that takes advantage of radiotracer polarization to combine MRI principles with nuclear imaging. This approach allows the concentration of a polarized Υ-ray emitting radioisotope to be imaged with MRI resolution potentially outperforming the standard nuclear imaging mode at a sensitivity significantly higher than that of MRI. In our work, we propose to acquire MRI-modulated nuclear data for simultaneous image reconstruction of both emission and transmission parameters, suggesting the potential for simultaneous CT-SPECT-MRI. The synchronized diverse datasets allow excellent spatiotemporal registration and unique insight into physiological and pathological features. Here we describe the methodology involving the system design with emphasis on the formulation for tomographic images, even when significant radiotracer signals are limited to a region of interest (ROI). Initial numerical results demonstrate the feasibility of our approach for reconstructing concentration and attenuation images through a head phantom with various radio-labeled ROIs. Additional considerations regarding the radioisotope characteristics are also discussed.

Brain medical image diagnosis based on corners with importance-values.

PubMed

Gao, Linlin; Pan, Haiwei; Li, Qing; Xie, Xiaoqin; Zhang, Zhiqiang; Han, Jinming; Zhai, Xiao

2017-11-21

Brain disorders are one of the top causes of human death. Generally, neurologists analyze brain medical images for diagnosis. In the image analysis field, corners are one of the most important features, which makes corner detection and matching studies essential. However, existing corner detection studies do not consider the domain information of brain. This leads to many useless corners and the loss of significant information. Regarding corner matching, the uncertainty and structure of brain are not employed in existing methods. Moreover, most corner matching studies are used for 3D image registration. They are inapplicable for 2D brain image diagnosis because of the different mechanisms. To address these problems, we propose a novel corner-based brain medical image classification method. Specifically, we automatically extract multilayer texture images (MTIs) which embody diagnostic information from neurologists. Moreover, we present a corner matching method utilizing the uncertainty and structure of brain medical images and a bipartite graph model. Finally, we propose a similarity calculation method for diagnosis. Brain CT and MRI image sets are utilized to evaluate the proposed method. First, classifiers are trained in N-fold cross-validation analysis to produce the best θ and K. Then independent brain image sets are tested to evaluate the classifiers. Moreover, the classifiers are also compared with advanced brain image classification studies. For the brain CT image set, the proposed classifier outperforms the comparison methods by at least 8% on accuracy and 2.4% on F1-score. Regarding the brain MRI image set, the proposed classifier is superior to the comparison methods by more than 7.3% on accuracy and 4.9% on F1-score. Results also demonstrate that the proposed method is robust to different intensity ranges of brain medical image. In this study, we develop a robust corner-based brain medical image classifier. Specifically, we propose a corner detection method utilizing the diagnostic information from neurologists and a corner matching method based on the uncertainty and structure of brain medical images. Additionally, we present a similarity calculation method for brain image classification. Experimental results on two brain image sets show the proposed corner-based brain medical image classifier outperforms the state-of-the-art studies.

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.

Accuracy of magnetic resonance based susceptibility measurements

NASA Astrophysics Data System (ADS)

Erdevig, Hannah E.; Russek, Stephen E.; Carnicka, Slavka; Stupic, Karl F.; Keenan, Kathryn E.

2017-05-01

Magnetic Resonance Imaging (MRI) is increasingly used to map the magnetic susceptibility of tissue to identify cerebral microbleeds associated with traumatic brain injury and pathological iron deposits associated with neurodegenerative diseases such as Parkinson's and Alzheimer's disease. Accurate measurements of susceptibility are important for determining oxygen and iron content in blood vessels and brain tissue for use in noninvasive clinical diagnosis and treatment assessments. Induced magnetic fields with amplitude on the order of 100 nT, can be detected using MRI phase images. The induced field distributions can then be inverted to obtain quantitative susceptibility maps. The focus of this research was to determine the accuracy of MRI-based susceptibility measurements using simple phantom geometries and to compare the susceptibility measurements with magnetometry measurements where SI-traceable standards are available. The susceptibilities of paramagnetic salt solutions in cylindrical containers were measured as a function of orientation relative to the static MRI field. The observed induced fields as a function of orientation of the cylinder were in good agreement with simple models. The MRI susceptibility measurements were compared with SQUID magnetometry using NIST-traceable standards. MRI can accurately measure relative magnetic susceptibilities while SQUID magnetometry measures absolute magnetic susceptibility. Given the accuracy of moment measurements of tissue mimicking samples, and the need to look at small differences in tissue properties, the use of existing NIST standard reference materials to calibrate MRI reference structures is problematic and better reference materials are required.

The cerebellar development in chinese children-a study by voxel-based volume measurement of reconstructed 3D MRI scan.

PubMed

Wu, Kuan-Hsun; Chen, Chia-Yuan; Shen, Ein-Yiao

2011-01-01

Cerebellar disorder was frequently reported to have relation with structural brain volume alteration and/or morphology change. In dealing with such clinical situations, we need a convenient and noninvasive imaging tool to provide clinicians with a means of tracing developmental changes in the cerebellum. Herein, we present a new daily practice method for cerebellum imaging that uses a work station and a software program to process reconstructed 3D neuroimages after MRI scanning. In a 3-y period, 3D neuroimages reconstructed from MRI scans of 50 children aged 0.2-12.7 y were taken. The resulting images were then statistically analyzed against a growth curve. We observed a remarkable increase in the size of the cerebellum in the first 2 y of life. Furthermore, the unmyelinated cerebellum grew mainly between birth and 2 y of age in the postnatal stage. In contrast, the postnatal development of the brain mainly depended on the growth of myelinated cerebellum from birth through adolescence. This study presents basic data from a study of ethnic Chinese children's cerebellums using reconstructed 3D brain images. Based on the technique we introduce here, clinicians can evaluate the growth of the brain.

Alteration of diffusion-tensor MRI measures in brain regions involved in early stages of Parkinson's disease.

PubMed

Chen, Nan-Kuei; Chou, Ying-Hui; Sundman, Mark; Hickey, Patrick; Kasoff, Willard S; Bernstein, Adam; Trouard, Theodore P; Lin, Tanya; Rapcsak, Steven Z; Sherman, Scott J; Weingarten, Carol

2018-06-07

Many non-motor symptoms (e.g., hyposmia) appear years before the cardinal motor features of Parkinson's disease (PD). It is thus desirable to be able to use noninvasive brain imaging methods, such as magnetic resonance imaging (MRI), to detect brain abnormalities in early PD stages. Among the MRI modalities, diffusion tensor imaging (DTI) is suitable for detecting changes of brain tissue structure due to neurological diseases. The main purpose of this study was to investigate whether DTI signals measured from brain regions involved in early stages of PD differ from those of healthy controls. To answer this question, we analyzed whole-brain DTI data of 30 early-stage PD patients and 30 controls using improved ROI based analysis methods. Results showed that 1) the fractional anisotropy (FA) values in the olfactory tract (connected with the olfactory bulb: one of the first structures affected by PD) are lower in PD patients than healthy controls; 2) FA values are higher in PD patients than healthy controls in the following brain regions: corticospinal tract, cingulum (near hippocampus), and superior longitudinal fasciculus (temporal part). Experimental results suggest that the tissue property, measured by FA, in olfactory regions is structurally modulated by PD with a mechanism that is different from other brain regions.

Multiscale multimodal fusion of histological and MRI volumes for characterization of lung inflammation

NASA Astrophysics Data System (ADS)

Rusu, Mirabela; Wang, Haibo; Golden, Thea; Gow, Andrew; Madabhushi, Anant

2013-03-01

Mouse lung models facilitate the investigation of conditions such as chronic inflammation which are associated with common lung diseases. The multi-scale manifestation of lung inflammation prompted us to use multi-scale imaging - both in vivo, ex vivo MRI along with ex vivo histology, for its study in a new quantitative way. Some imaging modalities, such as MRI, are non-invasive and capture macroscopic features of the pathology, while others, e.g. ex vivo histology, depict detailed structures. Registering such multi-modal data to the same spatial coordinates will allow the construction of a comprehensive 3D model to enable the multi-scale study of diseases. Moreover, it may facilitate the identification and definition of quantitative of in vivo imaging signatures for diseases and pathologic processes. We introduce a quantitative, image analytic framework to integrate in vivo MR images of the entire mouse with ex vivo histology of the lung alone, using lung ex vivo MRI as conduit to facilitate their co-registration. In our framework, we first align the MR images by registering the in vivo and ex vivo MRI of the lung using an interactive rigid registration approach. Then we reconstruct the 3D volume of the ex vivo histological specimen by efficient group wise registration of the 2D slices. The resulting 3D histologic volume is subsequently registered to the MRI volumes by interactive rigid registration, directly to the ex vivo MRI, and implicitly to in vivo MRI. Qualitative evaluation of the registration framework was performed by comparing airway tree structures in ex vivo MRI and ex vivo histology where airways are visible and may be annotated. We present a use case for evaluation of our co-registration framework in the context of studying chronic inammation in a diseased mouse.

Structural Correlates for Lexical Efficiency and Number of Languages in Non-Native Speakers of English

ERIC Educational Resources Information Center

Grogan, A.; Parker Jones, O.; Ali, N.; Crinion, J.; Orabona, S.; Mechias, M. L.; Ramsden, S.; Green, D. W.; Price, C. J.

2012-01-01

We used structural magnetic resonance imaging (MRI) and voxel based morphometry (VBM) to investigate whether the efficiency of word processing in the non-native language (lexical efficiency) and the number of non-native languages spoken (2+ versus 1) were related to local differences in the brain structure of bilingual and multilingual speakers.…

Spatially encoded phase-contrast MRI-3D MRI movies of 1D and 2D structures at millisecond resolution.

PubMed

Merboldt, Klaus-Dietmar; Uecker, Martin; Voit, Dirk; Frahm, Jens

2011-10-01

This work demonstrates that the principles underlying phase-contrast MRI may be used to encode spatial rather than flow information along a perpendicular dimension, if this dimension contains an MRI-visible object at only one spatial location. In particular, the situation applies to 3D mapping of curved 2D structures which requires only two projection images with different spatial phase-encoding gradients. These phase-contrast gradients define the field of view and mean spin-density positions of the object in the perpendicular dimension by respective phase differences. When combined with highly undersampled radial fast low angle shot (FLASH) and image reconstruction by regularized nonlinear inversion, spatial phase-contrast MRI allows for dynamic 3D mapping of 2D structures in real time. First examples include 3D MRI movies of the acting human hand at a temporal resolution of 50 ms. With an even simpler technique, 3D maps of curved 1D structures may be obtained from only three acquisitions of a frequency-encoded MRI signal with two perpendicular phase encodings. Here, 3D MRI movies of a rapidly rotating banana were obtained at 5 ms resolution or 200 frames per second. In conclusion, spatial phase-contrast 3D MRI of 2D or 1D structures is respective two or four orders of magnitude faster than conventional 3D MRI. Copyright © 2011 Wiley-Liss, Inc.

Mapping the order and pattern of brain structural MRI changes using change-point analysis in premanifest Huntington's disease.

PubMed

Wu, Dan; Faria, Andreia V; Younes, Laurent; Mori, Susumu; Brown, Timothy; Johnson, Hans; Paulsen, Jane S; Ross, Christopher A; Miller, Michael I

2017-10-01

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder that progressively affects motor, cognitive, and emotional functions. Structural MRI studies have demonstrated brain atrophy beginning many years prior to clinical onset ("premanifest" period), but the order and pattern of brain structural changes have not been fully characterized. In this study, we investigated brain regional volumes and diffusion tensor imaging (DTI) measurements in premanifest HD, and we aim to determine (1) the extent of MRI changes in a large number of structures across the brain by atlas-based analysis, and (2) the initiation points of structural MRI changes in these brain regions. We adopted a novel multivariate linear regression model to detect the inflection points at which the MRI changes begin (namely, "change-points"), with respect to the CAG-age product (CAP, an indicator of extent of exposure to the effects of CAG repeat expansion). We used approximately 300 T1-weighted and DTI data from premanifest HD and control subjects in the PREDICT-HD study, with atlas-based whole brain segmentation and change-point analysis. The results indicated a distinct topology of structural MRI changes: the change-points of the volumetric measurements suggested a central-to-peripheral pattern of atrophy from the striatum to the deep white matter; and the change points of DTI measurements indicated the earliest changes in mean diffusivity in the deep white matter and posterior white matter. While interpretation needs to be cautious given the cross-sectional nature of the data, these findings suggest a spatial and temporal pattern of spread of structural changes within the HD brain. Hum Brain Mapp 38:5035-5050, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Metastatic Renal Cell Carcinoma Masquerading as Jugular Foramen Paraganglioma: A Role for Novel Magnetic Resonance Imaging.

PubMed

Thomas, Andrew J; Wiggins, Richard H; Gurgel, Richard K

2017-08-01

To describe a case of metastatic renal cell carcinoma (RCC) masquerading as a jugular foramen paraganglioma (JP). To compare imaging findings between skull base metastatic RCC and histologically proven paraganglioma. A case of unexpected metastatic skull base RCC is reviewed. Computed tomography (CT) and magnetic resonance imaging (MRI) were compared between 3 confirmed cases of JP and our case of metastatic RCC. Diffusion-weighted MRI (DW-MRI) sequences and computed apparent diffusion coefficient (ADC) values were compared between these entities. A 55-year-old man presents with what appears clinically and radiographically to be JP. The tumor was resected, then discovered on postoperative pathology to be metastatic RCC. Imaging was retrospectively compared between 3 histologically confirmed cases of JP and our case of skull base RCC. The RCC metastasis was indistinguishable from JP on CT and traditional MRI but distinct by ADC values calculated from DW-MRI. Metastatic RCC at the skull base may mimic the clinical presentation and radiographic appearance of JP. The MRI finding of flow voids is seen in both paraganglioma and metastatic RCC. Diffusion-weighted MRI is able to distinguish these entities, highlighting its potential utility in distinguishing skull base lesions.

Integrating MRI-based geometry, composition and fiber architecture in a finite element model of the human intervertebral disc.

PubMed

Stadelmann, Marc A; Maquer, Ghislain; Voumard, Benjamin; Grant, Aaron; Hackney, David B; Vermathen, Peter; Alkalay, Ron N; Zysset, Philippe K

2018-05-17

Intervertebral disc degeneration is a common disease that is often related to impaired mechanical function, herniations and chronic back pain. The degenerative process induces alterations of the disc's shape, composition and structure that can be visualized in vivo using magnetic resonance imaging (MRI). Numerical tools such as finite element analysis (FEA) have the potential to relate MRI-based information to the altered mechanical behavior of the disc. However, in terms of geometry, composition and fiber architecture, current FE models rely on observations made on healthy discs and might therefore not be well suited to study the degeneration process. To address the issue, we propose a new, more realistic FE methodology based on diffusion tensor imaging (DTI). For this study, a human disc joint was imaged in a high-field MR scanner with proton-density weighted (PD) and DTI sequences. The PD image was segmented and an anatomy-specific mesh was generated. Assuming accordance between local principal diffusion direction and local mean collagen fiber alignment, corresponding fiber angles were assigned to each element. Those element-wise fiber directions and PD intensities allowed the homogenized model to smoothly account for composition and fibrous structure of the disc. The disc's in vitro mechanical behavior was quantified under tension, compression, flexion, extension, lateral bending and rotation. The six resulting load-displacement curves could be replicated by the FE model, which supports our approach as a first proof of concept towards patient-specific disc modeling. Copyright © 2018 Elsevier Ltd. All rights reserved.

Structural Magnetic Resonance Imaging Data Do Not Help Support DSM-5 Autism Spectrum Disorder Category

ERIC Educational Resources Information Center

Pina-Camacho, Laura; Villero, Sonia; Boada, Leticia; Fraguas, David; Janssen, Joost; Mayoral, Maria; Llorente, Cloe; Arango, Celso; Parellada, Mara

2013-01-01

This systematic review aims to determine whether or not structural magnetic resonance imaging (sMRI) data support the DSM-5 proposal of an autism spectrum disorder (ASD) diagnostic category, and whether or not classical DSM-IV autistic disorder (AD) and Asperger syndrome (AS) categories should be subsumed into it. The most replicated sMRI findings…

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.

Concurrent multiscale imaging with magnetic resonance imaging and optical coherence tomography

NASA Astrophysics Data System (ADS)

Liang, Chia-Pin; Yang, Bo; Kim, Il Kyoon; Makris, George; Desai, Jaydev P.; Gullapalli, Rao P.; Chen, Yu

2013-04-01

We develop a novel platform based on a tele-operated robot to perform high-resolution optical coherence tomography (OCT) imaging under continuous large field-of-view magnetic resonance imaging (MRI) guidance. Intra-operative MRI (iMRI) is a promising guidance tool for high-precision surgery, but it may not have sufficient resolution or contrast to visualize certain small targets. To address these limitations, we develop an MRI-compatible OCT needle probe, which is capable of providing microscale tissue architecture in conjunction with macroscale MRI tissue morphology in real time. Coregistered MRI/OCT images on ex vivo chicken breast and human brain tissues demonstrate that the complementary imaging scales and contrast mechanisms have great potential to improve the efficiency and the accuracy of iMRI procedure.

funcLAB/G-service-oriented architecture for standards-based analysis of functional magnetic resonance imaging in HealthGrids.

PubMed

Erberich, Stephan G; Bhandekar, Manasee; Chervenak, Ann; Kesselman, Carl; Nelson, Marvin D

2007-01-01

Functional MRI is successfully being used in clinical and research applications including preoperative planning, language mapping, and outcome monitoring. However, clinical use of fMRI is less widespread due to its complexity of imaging, image workflow, post-processing, and lack of algorithmic standards hindering result comparability. As a consequence, wide-spread adoption of fMRI as clinical tool is low contributing to the uncertainty of community physicians how to integrate fMRI into practice. In addition, training of physicians with fMRI is in its infancy and requires clinical and technical understanding. Therefore, many institutions which perform fMRI have a team of basic researchers and physicians to perform fMRI as a routine imaging tool. In order to provide fMRI as an advanced diagnostic tool to the benefit of a larger patient population, image acquisition and image post-processing must be streamlined, standardized, and available at any institution which does not have these resources available. Here we describe a software architecture, the functional imaging laboratory (funcLAB/G), which addresses (i) standardized image processing using Statistical Parametric Mapping and (ii) its extension to secure sharing and availability for the community using standards-based Grid technology (Globus Toolkit). funcLAB/G carries the potential to overcome the limitations of fMRI in clinical use and thus makes standardized fMRI available to the broader healthcare enterprise utilizing the Internet and HealthGrid Web Services technology.

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.

[Brain structure analysis for patients with antisocial personality disorder by MRI].

PubMed

Jiang, Weixiong; Liao, Jian; Liu, Huasheng; Huang, Renzhi; Li, Yongfan; Wang, Wei

2015-02-01

To investigate the structural abnormalities of brain in patients with antisocial personality disorder (ASPD) but without alcoholism and drug abuse. Volunteers from Hunan Reformatory (n=36) and the matched healthy subjects (n=26) were examined by high-spatial resolution magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). Voxel-based morphometry and fractional anisotropy (FA) maps were generated for each subject to reveal structural abnormalities in patients with ASPD. Compared with the healthy controls, ASPD patients showed significantly higher gray matter volumes in the inferior parietal lobule (P≤0.001, uncorrected), white matter volumes in the precuneus (P≤0.001, uncorrected), FA in the left lingual gyrus, bilateral precuneus, right superior frontal gyrus and right middle temporal gyrus (P≤0.01, uncorrected). Our results revealed the abnormal neuroanatomical features in ASPD patients, which might be related to the external behavioral traits in ASPD patients.

Puberty and structural brain development in humans.

PubMed

Herting, Megan M; Sowell, Elizabeth R

2017-01-01

Adolescence is a transitional period of physical and behavioral development between childhood and adulthood. Puberty is a distinct period of sexual maturation that occurs during adolescence. Since the advent of magnetic resonance imaging (MRI), human studies have largely examined neurodevelopment in the context of age. A breadth of animal findings suggest that sex hormones continue to influence the brain beyond the prenatal period, with both organizational and activational effects occurring during puberty. Given the animal evidence, human MRI research has also set out to determine how puberty may influence otherwise known patterns of age-related neurodevelopment. Here we review structural-based MRI studies and show that pubertal maturation is a key variable to consider in elucidating sex- and individual- based differences in patterns of human brain development. We also highlight the continuing challenges faced, as well as future considerations, for this vital avenue of research. Copyright © 2016. Published by Elsevier Inc.

Puberty and structural brain development in humans

PubMed Central

Herting, Megan M.; Sowell, Elizabeth R.

2017-01-01

Adolescence is a transitional period of physical and behavioral development between childhood and adulthood. Puberty is a distinct period of sexual maturation that occurs during adolescence. Since the advent of magnetic resonance imaging (MRI), human studies have largely examined neurodevelopment in the context of age. A breadth of animal findings suggest that sex hormones continue to influence the brain beyond the prenatal period, with both organizational and activational effects occurring during puberty. Given the animal evidence, human MRI research has also set out to determine how puberty may influence otherwise known patterns of age-related neurodevelopment. Here we review structural-based MRI studies and show that pubertal maturation is a key variable to consider in elucidating sex- and individual-based differences in patterns of human brain development. We also highlight the continuing challenges faced, as well as future considerations, for this vital avenue of research. PMID:28007528

A Bayesian Model for Highly Accelerated Phase-Contrast MRI

PubMed Central

Rich, Adam; Potter, Lee C.; Jin, Ning; Ash, Joshua; Simonetti, Orlando P.; Ahmad, Rizwan

2015-01-01

Purpose Phase-contrast magnetic resonance imaging (PC-MRI) is a noninvasive tool to assess cardiovascular disease by quantifying blood flow; however, low data acquisition efficiency limits the spatial and temporal resolutions, real-time application, and extensions to 4D flow imaging in clinical settings. We propose a new data processing approach called Reconstructing Velocity Encoded MRI with Approximate message passing aLgorithms (ReVEAL) that accelerates the acquisition by exploiting data structure unique to PC-MRI. Theory and Methods ReVEAL models physical correlations across space, time, and velocity encodings. The proposed Bayesian approach exploits the relationships in both magnitude and phase among velocity encodings. A fast iterative recovery algorithm is introduced based on message passing. For validation, prospectively undersampled data are processed from a pulsatile flow phantom and five healthy volunteers. Results ReVEAL is in good agreement, quantified by peak velocity and stroke volume (SV), with reference data for acceleration rates R ≤ 10. For SV, Pearson r ≥ 0.996 for phantom imaging (n = 24) and r ≥ 0.956 for prospectively accelerated in vivo imaging (n = 10) for R ≤ 10. Conclusion ReVEAL enables accurate quantification of blood flow from highly undersampled data. The technique is extensible to 4D flow imaging, where higher acceleration may be possible due to additional redundancy. PMID:26444911

Seeking Optimal Region-Of-Interest (ROI) Single-Value Summary Measures for fMRI Studies in Imaging Genetics

PubMed Central

Tong, Yunxia; Chen, Qiang; Nichols, Thomas E.; Rasetti, Roberta; Callicott, Joseph H.; Berman, Karen F.; Weinberger, Daniel R.; Mattay, Venkata S.

2016-01-01

A data-driven hypothesis-free genome-wide association (GWA) approach in imaging genetics studies allows screening the entire genome to discover novel genes that modulate brain structure, chemistry, and function. However, a whole brain voxel-wise analysis approach in such genome-wide based imaging genetic studies can be computationally intense and also likely has low statistical power since a stringent multiple comparisons correction is needed for searching over the entire genome and brain. In imaging genetics with functional magnetic resonance imaging (fMRI) phenotypes, since many experimental paradigms activate focal regions that can be pre-specified based on a priori knowledge, reducing the voxel-wise search to single-value summary measures within a priori ROIs could prove efficient and promising. The goal of this investigation is to evaluate the sensitivity and reliability of different single-value ROI summary measures and provide guidance in future work. Four different fMRI databases were tested and comparisons across different groups (patients with schizophrenia, their siblings, vs. normal control subjects; across genotype groups) were conducted. Our results show that four of these measures, particularly those that represent values from the top most-activated voxels within an ROI are more powerful at reliably detecting group differences and generating greater effect sizes than the others. PMID:26974435

TH-CD-206-09: Learning-Based MRI-CT Prostate Registration Using Spare Patch-Deformation Dictionary

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

Yang, X; Jani, A; Rossi, P

Purpose: To enable MRI-guided prostate radiotherapy, MRI-CT deformable registration is required to map the MRI-defined tumor and key organ contours onto the CT images. Due to the intrinsic differences in grey-level intensity characteristics between MRI and CT images, the integration of MRI into CT-based radiotherapy is very challenging. We are developing a learning-based registration approach to address this technical challenge. Methods: We propose to estimate the deformation between MRI and CT images in a patch-wise fashion by using the sparse representation technique. Specifically, we assume that two image patches should follow the same deformation if their patch-wise appearance patterns aremore » similar. We first extract a set of key points in the new CT image. Then, for each key point, we adaptively construct a coupled dictionary from the training MRI-CT images, where each coupled element includes both appearance and deformation of the same image patch. After calculating the sparse coefficients in representing the patch appearance of each key point based on the constructed dictionary, we can predict the deformation for this point by applying the same sparse coefficients to the respective deformations in the dictionary. Results: This registration technique was validated with 10 prostate-cancer patients’ data and its performance was compared with the commonly used free-form-deformation-based registration. Several landmarks in both images were identified to evaluate the accuracy of our approach. Overall, the averaged target registration error of the intensity-based registration and the proposed method was 3.8±0.4 mm and 1.9±0.3 mm, respectively. Conclusion: We have developed a novel prostate MR-CT registration approach based on patch-deformation dictionary, demonstrated its clinical feasibility, and validated its accuracy. This technique will either reduce or compensate for the effect of patient-specific treatment variation measured during the course of radiotherapy, is therefore well-suited for a number of MRI-guided adaptive radiotherapy, and potentially enhance prostate radiotherapy treatment outcome.« less

Comparison between cerebrospinal fluid and serum lactate concentrations in neurologic dogs with and without structural intracranial disease.

PubMed

Benedicenti, Leontine; Gianotti, Giacomo; Galban, Evelyn M

2018-04-01

The objectives of this study were to investigate the relationship between cerebrospinal fluid lactate and serum concentrations in dogs with clinical signs of central nervous system disease and to establish if cerebrospinal fluid lactate (CSF) concentrations are higher in dogs with structural intracranial disease (Group Pos-MRI) compared to dogs that have clinical signs of intracranial disease but no structural brain disease (Group Neg-MRI) based on magnetic resonance imaging (MRI) findings. Using a prospective study canine blood and cerebrospinal fluid were collected in 24 dogs with neurological signs after undergoing brain MRI. Dogs were divided in 2 groups. No significant difference between serum lactate (1.57 ± 0.9 mmol/L) and CSF lactate concentration (1.34 ± 0.3 mmol/L) was detected. There was a direct correlation between CSF and serum lactate concentration ( R = 0.731; P = 0.01). No significant difference was found in CSF lactate concentration between the 2 groups of dogs ( P = 0.13).

Methodologies for semiquantitative evaluation of hip osteoarthritis by magnetic resonance imaging: approaches based on the whole organ and focused on active lesions.

PubMed

Jaremko, Jacob L; Lambert, Robert G W; Zubler, Veronika; Weber, Ulrich; Loeuille, Damien; Roemer, Frank W; Cibere, Jolanda; Pianta, Marcus; Gracey, David; Conaghan, Philip; Ostergaard, Mikkel; Maksymowych, Walter P

2014-02-01

As a wider variety of therapeutic options for osteoarthritis (OA) becomes available, there is an increasing need to objectively evaluate disease severity on magnetic resonance imaging (MRI). This is more technically challenging at the hip than at the knee, and as a result, few systematic scoring systems exist. The OMERACT (Outcome Measures in Rheumatology) filter of truth, discrimination, and feasibility can be used to validate image-based scoring systems. Our objective was (1) to review the imaging features relevant to the assessment of severity and progression of hip OA; and (2) to review currently used methods to grade these features in existing hip OA scoring systems. A systematic literature review was conducted. MEDLINE keyword search was performed for features of arthropathy (such as hip + bone marrow edema or lesion, synovitis, cyst, effusion, cartilage, etc.) and scoring system (hip + OA + MRI + score or grade), with a secondary manual search for additional references in the retrieved publications. Findings relevant to the severity of hip OA include imaging markers associated with inflammation (bone marrow lesion, synovitis, effusion), structural damage (cartilage loss, osteophytes, subchondral cysts, labral tears), and predisposing geometric factors (hip dysplasia, femoral-acetabular impingement). Two approaches to the semiquantitative assessment of hip OA are represented by Hip OA MRI Scoring System (HOAMS), a comprehensive whole organ assessment of nearly all findings, and the Hip Inflammation MRI Scoring System (HIMRISS), which selectively scores only active lesions (bone marrow lesion, synovitis/effusion). Validation is presently confined to limited assessment of reliability. Two methods for semiquantitative assessment of hip OA on MRI have been described and validation according to the OMERACT Filter is limited to evaluation of reliability.

Differentiation of periapical granulomas and cysts by using dental MRI: a pilot study.

PubMed

Juerchott, Alexander; Pfefferle, Thorsten; Flechtenmacher, Christa; Mente, Johannes; Bendszus, Martin; Heiland, Sabine; Hilgenfeld, Tim

2018-05-17

The purpose of this pilot study was to evaluate whether periapical granulomas can be differentiated from periapical cysts in vivo by using dental magnetic resonance imaging (MRI). Prior to apicoectomy, 11 patients with radiographically confirmed periapical lesions underwent dental MRI, including fat-saturated T2-weighted (T2wFS) images, non-contrast-enhanced T1-weighted images with and without fat saturation (T1w/T1wFS), and contrast-enhanced fat-saturated T1-weighted (T1wFS+C) images. Two independent observers performed structured image analysis of MRI datasets twice. A total of 15 diagnostic MRI criteria were evaluated, and histopathological results (6 granulomas and 5 cysts) were compared with MRI characteristics. Statistical analysis was performed using intraclass correlation coefficient (ICC), Cohen's kappa (κ), Mann-Whitney U-test and Fisher's exact test. Lesion identification and consecutive structured image analysis was possible on T2wFS and T1wFS+C MRI images. A high reproducibility was shown for MRI measurements of the maximum lesion diameter (intraobserver ICC = 0.996/0.998; interobserver ICC = 0.997), for the "peripheral rim" thickness (intraobserver ICC = 0.988/0.984; interobserver ICC = 0.970), and for all non-quantitative MRI criteria (intraobserver-κ = 0.990/0.995; interobserver-κ = 0.988). In accordance with histopathological results, six MRI criteria allowed for a clear differentiation between cysts and granulomas: (1) outer margin of lesion, (2) texture of "peripheral rim" in T1wFS+C, (3) texture of "lesion center" in T2wFS, (4) surrounding tissue involvement in T2wFS, (5) surrounding tissue involvement in T1wFS+C and (6) maximum "peripheral rim" thickness (all: P < 0.05). In conclusion, this pilot study indicates that radiation-free dental MRI enables a reliable differentiation between periapical cysts and granulomas in vivo. Thus, MRI may substantially improve treatment strategies and help to avoid unnecessary surgery in apical periodontitis.

Statistical model of laminar structure for atlas-based segmentation of the fetal brain from in utero MR images

NASA Astrophysics Data System (ADS)

Habas, Piotr A.; Kim, Kio; Chandramohan, Dharshan; Rousseau, Francois; Glenn, Orit A.; Studholme, Colin

2009-02-01

Recent advances in MR and image analysis allow for reconstruction of high-resolution 3D images from clinical in utero scans of the human fetal brain. Automated segmentation of tissue types from MR images (MRI) is a key step in the quantitative analysis of brain development. Conventional atlas-based methods for adult brain segmentation are limited in their ability to accurately delineate complex structures of developing tissues from fetal MRI. In this paper, we formulate a novel geometric representation of the fetal brain aimed at capturing the laminar structure of developing anatomy. The proposed model uses a depth-based encoding of tissue occurrence within the fetal brain and provides an additional anatomical constraint in a form of a laminar prior that can be incorporated into conventional atlas-based EM segmentation. Validation experiments are performed using clinical in utero scans of 5 fetal subjects at gestational ages ranging from 20.5 to 22.5 weeks. Experimental results are evaluated against reference manual segmentations and quantified in terms of Dice similarity coefficient (DSC). The study demonstrates that the use of laminar depth-encoded tissue priors improves both the overall accuracy and precision of fetal brain segmentation. Particular refinement is observed in regions of the parietal and occipital lobes where the DSC index is improved from 0.81 to 0.82 for cortical grey matter, from 0.71 to 0.73 for the germinal matrix, and from 0.81 to 0.87 for white matter.

Tendon and ligament imaging

PubMed Central

Hodgson, R J; O'Connor, P J; Grainger, A J

2012-01-01

MRI and ultrasound are now widely used for the assessment of tendon and ligament abnormalities. Healthy tendons and ligaments contain high levels of collagen with a structured orientation, which gives rise to their characteristic normal imaging appearances as well as causing particular imaging artefacts. Changes to ligaments and tendons as a result of disease and injury can be demonstrated using both ultrasound and MRI. These have been validated against surgical and histological findings. Novel imaging techniques are being developed that may improve the ability of MRI and ultrasound to assess tendon and ligament disease. PMID:22553301

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

Transcranial magnetic stimulation assisted by neuronavigation of magnetic resonance images

NASA Astrophysics Data System (ADS)

Viesca, N. Angeline; Alcauter, S. Sarael; Barrios, A. Fernando; González, O. Jorge J.; Márquez, F. Jorge A.

2012-10-01

Technological advance has improved the way scientists and doctors can learn about the brain and treat different disorders. A non-invasive method used for this is Transcranial Magnetic Stimulation (TMS) based on neuron excitation by electromagnetic induction. Combining this method with functional Magnetic Resonance Images (fMRI), it is intended to improve the localization technique of cortical brain structures by designing an extracranial localization system, based on Alcauter et al. work.

Review: Magnetic resonance imaging techniques in ophthalmology

PubMed Central

Fagan, Andrew J.

2012-01-01

Imaging the eye with magnetic resonance imaging (MRI) has proved difficult due to the eye’s propensity to move involuntarily over typical imaging timescales, obscuring the fine structure in the eye due to the resulting motion artifacts. However, advances in MRI technology help to mitigate such drawbacks, enabling the acquisition of high spatiotemporal resolution images with a variety of contrast mechanisms. This review aims to classify the MRI techniques used to date in clinical and preclinical ophthalmologic studies, describing the qualitative and quantitative information that may be extracted and how this may inform on ocular pathophysiology. PMID:23112569

Structural MRI and Cognitive Correlates in Pest-control Personnel from Gulf War I

DTIC Science & Technology

2009-04-01

Medicine where they will be reconstructed for morphometric analyses by the study imaging expert, Dr. Killiany. All the images will be transferred to... geometric design; assess ability to organize and construct Raw Score...MRI and morphometric analysis of the images. The results of the current study will be able to compare whether brain imaging differences exist

Characterization of tumor microvascular structure and permeability: comparison between magnetic resonance imaging and intravital confocal imaging

NASA Astrophysics Data System (ADS)

Reitan, Nina Kristine; Thuen, Marte; Goa, Pa˚L. Erik; de Lange Davies, Catharina

2010-05-01

Solid tumors are characterized by abnormal blood vessel organization, structure, and function. These abnormalities give rise to enhanced vascular permeability and may predict therapeutic responses. The permeability and architecture of the microvasculature in human osteosarcoma tumors growing in dorsal window chambers in athymic mice were measured by confocal laser scanning microscopy (CLSM) and dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). Dextran (40 kDa) and Gadomer were used as molecular tracers for CLSM and DCE-MRI, respectively. A significant correlation was found between permeability indicators. The extravasation rate Ki as measured by CLSM correlated positively with DCE-MRI parameters, such as the volume transfer constant Ktrans and the initial slope of the contrast agent concentration-time curve. This demonstrates that these two techniques give complementary information. Extravasation was further related to microvascular structure and was found to correlate with the fractal dimension and vascular density. The structural parameter values that were obtained from CLSM images were higher for abnormal tumor vasculature than for normal vessels.

Breast MRI at 7 Tesla with a bilateral coil and T1-weighted acquisition with robust fat suppression: image evaluation and comparison with 3 Tesla.

PubMed

Brown, Ryan; Storey, Pippa; Geppert, Christian; McGorty, KellyAnne; Leite, Ana Paula Klautau; Babb, James; Sodickson, Daniel K; Wiggins, Graham C; Moy, Linda

2013-11-01

To evaluate the image quality of T1-weighted fat-suppressed breast MRI at 7 T and to compare 7-T and 3-T images. Seventeen subjects were imaged using a 7-T bilateral transmit-receive coil and 3D gradient echo sequence with adiabatic inversion-based fat suppression (FS). Images were graded on a five-point scale and quantitatively assessed through signal-to-noise ratio (SNR), fibroglandular/fat contrast and signal uniformity measurements. Image scores at 7 and 3 T were similar on standard-resolution images (1.1 × 1.1 × 1.1-1.6 mm(3)), indicating that high-quality breast imaging with clinical parameters can be performed at 7 T. The 7-T SNR advantage was underscored on 0.6-mm isotropic images, where image quality was significantly greater than at 3 T (4.2 versus 3.1, P ≤ 0.0001). Fibroglandular/fat contrast was more than two times higher at 7 T than at 3 T, owing to effective adiabatic inversion-based FS and the inherent 7-T signal advantage. Signal uniformity was comparable at 7 and 3 T (P < 0.05). Similar 7-T image quality was observed in all subjects, indicating robustness against anatomical variation. The 7-T bilateral transmit-receive coil and adiabatic inversion-based FS technique produce image quality that is as good as or better than at 3 T. • High image quality bilateral breast MRI is achievable with clinical parameters at 7 T. • 7-T high-resolution imaging improves delineation of subtle soft tissue structures. • Adiabatic-based fat suppression provides excellent fibroglandular/fat contrast at 7 T. • 7- and 3-T 3D T1-weighted gradient-echo images have similar signal uniformity. • The 7-T dual solenoid coil enables bilateral imaging without compromising uniformity.

A Highly Sensitive X-ray Imaging Modality for Hepatocellular Carcinoma Detection in Vitro

PubMed Central

Rand, Danielle; Walsh, Edward G.; Derdak, Zoltan; Wands, Jack R.; Rose-Petruck, Christoph

2015-01-01

Innovations that improve sensitivity and reduce cost are of paramount importance in diagnostic imaging. The novel x-ray imaging modality called Spatial Frequency Heterodyne Imaging (SFHI) is based on a linear arrangement of x-ray source, tissue, and x-ray detector, much like that of a conventional x-ray imaging apparatus. However, SFHI rests on a complete paradigm reversal compared to conventional x-ray absorption-based radiology: while scattered x-rays are carefully rejected in absorption-based x-ray radiology to enhance the image contrast, SFHI forms images exclusively from x-rays scattered by the tissue. In this study we use numerical processing to produce x-ray scatter images of Hepatocellular Carcinoma (HCC) labeled with a nanoparticle contrast agent. We subsequently compare the sensitivity of SFHI in this application to that of both conventional x-ray imaging and Magnetic Resonance Imaging (MRI). Although SFHI is still in the early stages of its development, our results show that the sensitivity of SFHI is an order of magnitude greater than that of absorption-based x-ray imaging and approximately equal to that of MRI. As x-ray imaging modalities typically have lower installation and service costs compared to MRI, SFHI could become a cost effective alternative to MRI, particularly in areas of the world with inadequate availability of MRI facilities. PMID:25559398

A highly sensitive x-ray imaging modality for hepatocellular carcinoma detection in vitro

DOE PAGES

Rand, Danielle; Walsh, Edward G.; Derdak, Zoltan; ...

2015-01-05

Innovations that improve sensitivity and reduce cost are of paramount importance in diagnostic imaging. The novel x-ray imaging modality called Spatial Frequency Heterodyne Imaging (SFHI) is based on a linear arrangement of x-ray source, tissue, and x-ray detector, much like that of a conventional x-ray imaging apparatus. However, SFHI rests on a complete paradigm reversal compared to conventional x-ray absorption-based radiology: while scattered x-rays are carefully rejected in absorption-based x-ray radiology to enhance the image contrast, SFHI forms images exclusively from x-rays scattered by the tissue. Here in this study we use numerical processing to produce x-ray scatter images ofmore » Hepatocellular Carcinoma (HCC) labeled with a nanoparticle contrast agent. We subsequently compare the sensitivity of SFHI in this application to that of both conventional x-ray imaging and Magnetic Resonance Imaging (MRI). Although SFHI is still in the early stages of its development, our results show that the sensitivity of SFHI is an order of magnitude greater than that of absorption-based x-ray imaging and approximately equal to that of MRI. Lastly, as x-ray imaging modalities typically have lower installation and service costs compared to MRI, SFHI could become a cost effective alternative to MRI, particularly in areas of the world with inadequate availability of MRI facilities.« less

Evaluation of MRI and cannabinoid type 1 receptor PET templates constructed using DARTEL for spatial normalization of rat brains

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

Kronfeld, Andrea; Müller-Forell, Wibke; Buchholz, Hans-Georg

Purpose: Image registration is one prerequisite for the analysis of brain regions in magnetic-resonance-imaging (MRI) or positron-emission-tomography (PET) studies. Diffeomorphic anatomical registration through exponentiated Lie algebra (DARTEL) is a nonlinear, diffeomorphic algorithm for image registration and construction of image templates. The goal of this small animal study was (1) the evaluation of a MRI and calculation of several cannabinoid type 1 (CB1) receptor PET templates constructed using DARTEL and (2) the analysis of the image registration accuracy of MR and PET images to their DARTEL templates with reference to analytical and iterative PET reconstruction algorithms. Methods: Five male Sprague Dawleymore » rats were investigated for template construction using MRI and [{sup 18}F]MK-9470 PET for CB1 receptor representation. PET images were reconstructed using the algorithms filtered back-projection, ordered subset expectation maximization in 2D, and maximum a posteriori in 3D. Landmarks were defined on each MR image, and templates were constructed under different settings, i.e., based on different tissue class images [gray matter (GM), white matter (WM), and GM + WM] and regularization forms (“linear elastic energy,” “membrane energy,” and “bending energy”). Registration accuracy for MRI and PET templates was evaluated by means of the distance between landmark coordinates. Results: The best MRI template was constructed based on gray and white matter images and the regularization form linear elastic energy. In this case, most distances between landmark coordinates were <1 mm. Accordingly, MRI-based spatial normalization was most accurate, but results of the PET-based spatial normalization were quite comparable. Conclusions: Image registration using DARTEL provides a standardized and automatic framework for small animal brain data analysis. The authors were able to show that this method works with high reliability and validity. Using DARTEL templates together with nonlinear registration algorithms allows for accurate spatial normalization of combined MRI/PET or PET-only studies.« less

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

MRI tools for assessment of microstructure and nephron function of the kidney.

PubMed

Xie, Luke; Bennett, Kevin M; Liu, Chunlei; Johnson, G Allan; Zhang, Jeff Lei; Lee, Vivian S

2016-12-01

MRI can provide excellent detail of renal structure and function. Recently, novel MR contrast mechanisms and imaging tools have been developed to evaluate microscopic kidney structures including the tubules and glomeruli. Quantitative MRI can assess local tubular function and is able to determine the concentrating mechanism of the kidney noninvasively in real time. Measuring single nephron function is now a near possibility. In parallel to advancing imaging techniques for kidney microstructure is a need to carefully understand the relationship between the local source of MRI contrast and the underlying physiological change. The development of these imaging markers can impact the accurate diagnosis and treatment of kidney disease. This study reviews the novel tools to examine kidney microstructure and local function and demonstrates the application of these methods in renal pathophysiology. Copyright © 2016 the American Physiological Society.

Combination of rs-fMRI and sMRI Data to Discriminate Autism Spectrum Disorders in Young Children Using Deep Belief Network.

PubMed

Akhavan Aghdam, Maryam; Sharifi, Arash; Pedram, Mir Mohsen

2018-05-07

In recent years, the use of advanced magnetic resonance (MR) imaging methods such as functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sMRI) has recorded a great increase in neuropsychiatric disorders. Deep learning is a branch of machine learning that is increasingly being used for applications of medical image analysis such as computer-aided diagnosis. In a bid to classify and represent learning tasks, this study utilized one of the most powerful deep learning algorithms (deep belief network (DBN)) for the combination of data from Autism Brain Imaging Data Exchange I and II (ABIDE I and ABIDE II) datasets. The DBN was employed so as to focus on the combination of resting-state fMRI (rs-fMRI), gray matter (GM), and white matter (WM) data. This was done based on the brain regions that were defined using the automated anatomical labeling (AAL), in order to classify autism spectrum disorders (ASDs) from typical controls (TCs). Since the diagnosis of ASD is much more effective at an early age, only 185 individuals (116 ASD and 69 TC) ranging in age from 5 to 10 years were included in this analysis. In contrast, the proposed method is used to exploit the latent or abstract high-level features inside rs-fMRI and sMRI data while the old methods consider only the simple low-level features extracted from neuroimages. Moreover, combining multiple data types and increasing the depth of DBN can improve classification accuracy. In this study, the best combination comprised rs-fMRI, GM, and WM for DBN of depth 3 with 65.56% accuracy (sensitivity = 84%, specificity = 32.96%, F1 score = 74.76%) obtained via 10-fold cross-validation. This result outperforms previously presented methods on ABIDE I dataset.

Using temporal ICA to selectively remove global noise while preserving global signal in functional MRI data.

PubMed

Glasser, Matthew F; Coalson, Timothy S; Bijsterbosch, Janine D; Harrison, Samuel J; Harms, Michael P; Anticevic, Alan; Van Essen, David C; Smith, Stephen M

2018-06-02

Temporal fluctuations in functional Magnetic Resonance Imaging (fMRI) have been profitably used to study brain activity and connectivity for over two decades. Unfortunately, fMRI data also contain structured temporal "noise" from a variety of sources, including subject motion, subject physiology, and the MRI equipment. Recently, methods have been developed to automatically and selectively remove spatially specific structured noise from fMRI data using spatial Independent Components Analysis (ICA) and machine learning classifiers. Spatial ICA is particularly effective at removing spatially specific structured noise from high temporal and spatial resolution fMRI data of the type acquired by the Human Connectome Project and similar studies. However, spatial ICA is mathematically, by design, unable to separate spatially widespread "global" structured noise from fMRI data (e.g., blood flow modulations from subject respiration). No methods currently exist to selectively and completely remove global structured noise while retaining the global signal from neural activity. This has left the field in a quandary-to do or not to do global signal regression-given that both choices have substantial downsides. Here we show that temporal ICA can selectively segregate and remove global structured noise while retaining global neural signal in both task-based and resting state fMRI data. We compare the results before and after temporal ICA cleanup to those from global signal regression and show that temporal ICA cleanup removes the global positive biases caused by global physiological noise without inducing the network-specific negative biases of global signal regression. We believe that temporal ICA cleanup provides a "best of both worlds" solution to the global signal and global noise dilemma and that temporal ICA itself unlocks interesting neurobiological insights from fMRI data. Copyright © 2018 Elsevier Inc. All rights reserved.

Functional and Structural Correlates of Motor Speed in the Cerebellar Anterior Lobe

PubMed Central

Wenzel, Uwe; Taubert, Marco; Ragert, Patrick; Krug, Jürgen; Villringer, Arno

2014-01-01

In athletics, motor performance is determined by different abilities such as technique, endurance, strength and speed. Based on animal studies, motor speed is thought to be encoded in the basal ganglia, sensorimotor cortex and the cerebellum. The question arises whether there is a unique structural feature in the human brain, which allows “power athletes” to perform a simple foot movement significantly faster than “endurance athletes”. We acquired structural and functional brain imaging data from 32 track-and-field athletes. The study comprised of 16 “power athletes” requiring high speed foot movements (sprinters, jumpers, throwers) and 16 endurance athletes (distance runners) which in contrast do not require as high speed foot movements. Functional magnetic resonance imaging (fMRI) was used to identify speed specific regions of interest in the brain during fast and slow foot movements. Anatomical MRI scans were performed to assess structural grey matter volume differences between athletes groups (voxel based morphometry). We tested maximum movement velocity of plantarflexion (PF-Vmax) and acquired electromyographical activity of the lateral and medial gastrocnemius muscle. Behaviourally, a significant difference between the two groups of athletes was noted in PF-Vmax and fMRI indicates that fast plantarflexions are accompanied by increased activity in the cerebellar anterior lobe. The same region indicates increased grey matter volume for the power athletes compared to the endurance counterparts. Our results suggest that speed-specific neuro-functional and -structural differences exist between power and endurance athletes in the peripheral and central nervous system. PMID:24800742

Whole-body MRI including diffusion-weighted MRI compared with 5-HTP PET/CT in the detection of neuroendocrine tumors

PubMed Central

Carlbom, Lina; Caballero-Corbalán, José; Granberg, Dan; Sörensen, Jens; Eriksson, Barbro; Ahlström, Håkan

2017-01-01

Aim We wanted to explore if whole-body magnetic resonance imaging (MRI) including diffusion-weighted (DW) and liver-specific contrast agent-enhanced imaging could be valuable in lesion detection of neuroendocrine tumors (NET). [11C]-5-Hydroxytryptophan positron emission tomography/computed tomography (5-HTP PET/CT) was used for comparison. Materials and methods Twenty-one patients with NET were investigated with whole-body MRI, including DW imaging (DWI) and contrast-enhanced imaging of the liver, and whole-body 5-HTP PET/CT. Seven additional patients underwent upper abdomen MRI including DWI, liver-specific contrast agent-enhanced imaging, and 5-HTP PET/CT. Results There was a patient-based concordance of 61% and a lesion-based concordance of 53% between the modalities. MRI showed good concordance with PET in detecting bone metastases but was less sensitive in detecting metastases in mediastinal lymph nodes. MRI detected more liver metastases than 5-HTP PET/CT. Conclusion Whole-body MRI with DWI did not detect all NET lesions found with whole-body 5-HTP PET/CT. Our findings indicate that MRI of the liver including liver-specific contrast agent-enhanced imaging and DWI could be a useful complement to whole-body 5-HTP PET/CT. PMID:27894208

Clinical and mutational spectrum in Korean patients with Rubinstein-Taybi syndrome: the spectrum of brain MRI abnormalities.

PubMed

Lee, Jin Sook; Byun, Christine K; Kim, Hunmin; Lim, Byung Chan; Hwang, Hee; Choi, Ji Eun; Hwang, Yong Seung; Seong, Moon-Woo; Park, Sung Sup; Kim, Ki Joong; Chae, Jong-Hee

2015-04-01

Rubinstein-Taybi syndrome (RSTS) is one of the neurodevelopmental disorders caused by mutations of epigenetic genes. The CREBBP gene is the most common causative gene, encoding the CREB-binding protein with histone acetyltransferase (HAT) activity, an epigenetic modulator. To date, there have been few reports on the structural abnormalities of the brain in RSTS patients. In addition, there are no reports on the analysis of CREBBP mutations in Korean RSTS patients. We performed mutational analyses on 16 unrelated patients with RSTS, with diagnosis based on the typical clinical features. Their medical records and brain MRI images were reviewed retrospectively. Ten of 16 patients (62.5%) had mutations in the CREBBP gene. The mutations included five frameshift mutations (31.2%), two nonsense mutations (12.5%), and three multiexon deletions (18.8%). There were no remarkable significant differences in the clinical features between those with and without a CREBBP mutation, although brain MRI abnormalities were more frequently observed in those with a CREBBP mutation. Seven of 10 patients in whom brain imaging was performed had structural abnormalities, including Chiari malformation type 1, thinning of the corpus callosum, and delayed myelination. There were no differences in delayed development or cognitive impairment between those with and without abnormal brain images, while epilepsy was involved in two patients who had abnormalities on brain MRI images. We investigated the spectrum of CREBBP mutations in Korean patients with RSTS for the first time. Eight novel mutations extended the genetic spectrum of CREBBP mutations in RSTS patients. This is also the first study showing the prevalence and spectrum of abnormalities on brain MRI in RSTS patients. Copyright © 2014 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Longer-Term Investigation of the Value of 18F-FDG-PET and Magnetic Resonance Imaging for Predicting the Conversion of Mild Cognitive Impairment to Alzheimer's Disease: A Multicenter Study.

PubMed

Inui, Yoshitaka; Ito, Kengo; Kato, Takashi

2017-01-01

The value of fluorine-18-fluorodeoxyglucose positron emission tomography (18F-FDG-PET) and magnetic resonance imaging (MRI) for predicting conversion of mild cognitive impairment (MCI) to Alzheimer's disease (AD) in longer-term is unclear. To evaluate longer-term prediction of MCI to AD conversion using 18F-FDG-PET and MRI in a multicenter study. One-hundred and fourteen patients with MCI were followed for 5 years. They underwent clinical and neuropsychological examinations, 18F-FDG-PET, and MRI at baseline. PET images were visually classified into predefined dementia patterns. PET scores were calculated as a semi quantitative index. For structural MRI, z-scores in medial temporal area were calculated by automated volume-based morphometry (VBM). Overall, 72% patients with amnestic MCI progressed to AD during the 5-year follow-up. The diagnostic accuracy of PET scores over 5 years was 60% with 53% sensitivity and 84% specificity. Visual interpretation of PET images predicted conversion to AD with an overall 82% diagnostic accuracy, 94% sensitivity, and 53% specificity. The accuracy of VBM analysis presented little fluctuation through 5 years and it was highest (73%) at the 5-year follow-up, with 79% sensitivity and 63% specificity. The best performance (87.9% diagnostic accuracy, 89.8% sensitivity, and 82.4% specificity) was with a combination identified using multivariate logistic regression analysis that included PET visual interpretation, educational level, and neuropsychological tests as predictors. 18F-FDG-PET visual assessment showed high performance for predicting conversion to AD from MCI, particularly in combination with neuropsychological tests. PET scores showed high diagnostic specificity. Structural MRI focused on the medial temporal area showed stable predictive value throughout the 5-year course.

Design of biomimetic vascular grafts with magnetic endothelial patterning.

PubMed

Fayol, Delphine; Le Visage, Catherine; Ino, Julia; Gazeau, Florence; Letourneur, Didier; Wilhelm, Claire

2013-01-01

The development of small diameter vascular grafts with a controlled pluricellular organization is still needed for effective vascular tissue engineering. Here, we describe a technological approach combining a tubular scaffold and magnetically labeled cells to create a pluricellular and organized vascular graft, the endothelialization of which could be monitored by MRI prior to transplantation. A novel type of scaffold was developed with a tubular geometry and a porous bulk structure enabling the seeding of cells in the scaffold pores. A homogeneous distribution of human mesenchymal stem cells in the macroporous structure was obtained by seeding the freeze-dried scaffold with the cell suspension. The efficient covering of the luminal surface of the tube was then made possible thanks to the implementation of a magnetic-based patterning technique. Human endothelial cells or endothelial progenitors were magnetically labeled with iron oxide nanoparticles and successfully attracted to the 2-mm lumen where they attached and formed a continuous endothelium. The combination of imaging modalities [fluorescence imaging, histology, and 3D magnetic resonance imaging (MRI)] evidenced the integrity of the vascular construct. In particular, the observation of different cell organizations in a vascular scaffold within the range of resolution of single cells by 4.7 T MRI is reported.

Improving Functional MRI Registration Using Whole-Brain Functional Correlation Tensors.

PubMed

Zhou, Yujia; Yap, Pew-Thian; Zhang, Han; Zhang, Lichi; Feng, Qianjin; Shen, Dinggang

2017-09-01

Population studies of brain function with resting-state functional magnetic resonance imaging (rs-fMRI) largely rely on the accurate inter-subject registration of functional areas. This is typically achieved through registration of the corresponding T1-weighted MR images with more structural details. However, accumulating evidence has suggested that such strategy cannot well-align functional regions which are not necessarily confined by the anatomical boundaries defined by the T1-weighted MR images. To mitigate this problem, various registration algorithms based directly on rs-fMRI data have been developed, most of which have utilized functional connectivity (FC) as features for registration. However, most of the FC-based registration methods usually extract the functional features only from the thin and highly curved cortical grey matter (GM), posing a great challenge in accurately estimating the whole-brain deformation field. In this paper, we demonstrate that the additional useful functional features can be extracted from brain regions beyond the GM, particularly, white-matter (WM) based on rs-fMRI, for improving the overall functional registration. Specifically, we quantify the local anisotropic correlation patterns of the blood oxygenation level-dependent (BOLD) signals, modeled by functional correlation tensors (FCTs), in both GM and WM. Functional registration is then performed based on multiple components of the whole-brain FCTs using a multichannel Large Deformation Diffeomorphic Metric Mapping (mLDDMM) algorithm. Experimental results show that our proposed method achieves superior functional registration performance, compared with other conventional registration methods.

Vision 20/20: Magnetic resonance imaging-guided attenuation correction in PET/MRI: Challenges, solutions, and opportunities

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

Mehranian, Abolfazl; Arabi, Hossein; Zaidi, Habib, E-mail: habib.zaidi@hcuge.ch

Attenuation correction is an essential component of the long chain of data correction techniques required to achieve the full potential of quantitative positron emission tomography (PET) imaging. The development of combined PET/magnetic resonance imaging (MRI) systems mandated the widespread interest in developing novel strategies for deriving accurate attenuation maps with the aim to improve the quantitative accuracy of these emerging hybrid imaging systems. The attenuation map in PET/MRI should ideally be derived from anatomical MR images; however, MRI intensities reflect proton density and relaxation time properties of biological tissues rather than their electron density and photon attenuation properties. Therefore, inmore » contrast to PET/computed tomography, there is a lack of standardized global mapping between the intensities of MRI signal and linear attenuation coefficients at 511 keV. Moreover, in standard MRI sequences, bones and lung tissues do not produce measurable signals owing to their low proton density and short transverse relaxation times. MR images are also inevitably subject to artifacts that degrade their quality, thus compromising their applicability for the task of attenuation correction in PET/MRI. MRI-guided attenuation correction strategies can be classified in three broad categories: (i) segmentation-based approaches, (ii) atlas-registration and machine learning methods, and (iii) emission/transmission-based approaches. This paper summarizes past and current state-of-the-art developments and latest advances in PET/MRI attenuation correction. The advantages and drawbacks of each approach for addressing the challenges of MR-based attenuation correction are comprehensively described. The opportunities brought by both MRI and PET imaging modalities for deriving accurate attenuation maps and improving PET quantification will be elaborated. Future prospects and potential clinical applications of these techniques and their integration in commercial systems will also be discussed.« less

Vision 20/20: Magnetic resonance imaging-guided attenuation correction in PET/MRI: Challenges, solutions, and opportunities.

PubMed

Mehranian, Abolfazl; Arabi, Hossein; Zaidi, Habib

2016-03-01

Attenuation correction is an essential component of the long chain of data correction techniques required to achieve the full potential of quantitative positron emission tomography (PET) imaging. The development of combined PET/magnetic resonance imaging (MRI) systems mandated the widespread interest in developing novel strategies for deriving accurate attenuation maps with the aim to improve the quantitative accuracy of these emerging hybrid imaging systems. The attenuation map in PET/MRI should ideally be derived from anatomical MR images; however, MRI intensities reflect proton density and relaxation time properties of biological tissues rather than their electron density and photon attenuation properties. Therefore, in contrast to PET/computed tomography, there is a lack of standardized global mapping between the intensities of MRI signal and linear attenuation coefficients at 511 keV. Moreover, in standard MRI sequences, bones and lung tissues do not produce measurable signals owing to their low proton density and short transverse relaxation times. MR images are also inevitably subject to artifacts that degrade their quality, thus compromising their applicability for the task of attenuation correction in PET/MRI. MRI-guided attenuation correction strategies can be classified in three broad categories: (i) segmentation-based approaches, (ii) atlas-registration and machine learning methods, and (iii) emission/transmission-based approaches. This paper summarizes past and current state-of-the-art developments and latest advances in PET/MRI attenuation correction. The advantages and drawbacks of each approach for addressing the challenges of MR-based attenuation correction are comprehensively described. The opportunities brought by both MRI and PET imaging modalities for deriving accurate attenuation maps and improving PET quantification will be elaborated. Future prospects and potential clinical applications of these techniques and their integration in commercial systems will also be discussed.

Monitoring Cartilage Tissue Engineering Using Magnetic Resonance Spectroscopy, Imaging, and Elastography

PubMed Central

Klatt, Dieter; Magin, Richard L.

2013-01-01

A key technical challenge in cartilage tissue engineering is the development of a noninvasive method for monitoring the composition, structure, and function of the tissue at different growth stages. Due to its noninvasive, three-dimensional imaging capabilities and the breadth of available contrast mechanisms, magnetic resonance imaging (MRI) techniques can be expected to play a leading role in assessing engineered cartilage. In this review, we describe the new MR-based tools (spectroscopy, imaging, and elastography) that can provide quantitative biomarkers for cartilage tissue development both in vitro and in vivo. Magnetic resonance spectroscopy can identify the changing molecular structure and alternations in the conformation of major macromolecules (collagen and proteoglycans) using parameters such as chemical shift, relaxation rates, and magnetic spin couplings. MRI provides high-resolution images whose contrast reflects developing tissue microstructure and porosity through changes in local relaxation times and the apparent diffusion coefficient. Magnetic resonance elastography uses low-frequency mechanical vibrations in conjunction with MRI to measure soft tissue mechanical properties (shear modulus and viscosity). When combined, these three techniques provide a noninvasive, multiscale window for characterizing cartilage tissue growth at all stages of tissue development, from the initial cell seeding of scaffolds to the development of the extracellular matrix during construct incubation, and finally, to the postimplantation assessment of tissue integration in animals and patients. PMID:23574498

The physical and biological basis of quantitative parameters derived from diffusion MRI

PubMed Central

2012-01-01

Diffusion magnetic resonance imaging is a quantitative imaging technique that measures the underlying molecular diffusion of protons. Diffusion-weighted imaging (DWI) quantifies the apparent diffusion coefficient (ADC) which was first used to detect early ischemic stroke. However this does not take account of the directional dependence of diffusion seen in biological systems (anisotropy). Diffusion tensor imaging (DTI) provides a mathematical model of diffusion anisotropy and is widely used. Parameters, including fractional anisotropy (FA), mean diffusivity (MD), parallel and perpendicular diffusivity can be derived to provide sensitive, but non-specific, measures of altered tissue structure. They are typically assessed in clinical studies by voxel-based or region-of-interest based analyses. The increasing recognition of the limitations of the diffusion tensor model has led to more complex multi-compartment models such as CHARMED, AxCaliber or NODDI being developed to estimate microstructural parameters including axonal diameter, axonal density and fiber orientations. However these are not yet in routine clinical use due to lengthy acquisition times. In this review, I discuss how molecular diffusion may be measured using diffusion MRI, the biological and physical bases for the parameters derived from DWI and DTI, how these are used in clinical studies and the prospect of more complex tissue models providing helpful micro-structural information. PMID:23289085

Studying neuroanatomy using MRI.

PubMed

Lerch, Jason P; van der Kouwe, André J W; Raznahan, Armin; Paus, Tomáš; Johansen-Berg, Heidi; Miller, Karla L; Smith, Stephen M; Fischl, Bruce; Sotiropoulos, Stamatios N

2017-02-23

The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging and disease. Developments in MRI acquisition, image processing and data modeling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and for inferring microstructural properties; we also describe key artifacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, although methods need to improve and caution is required in interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works.

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.

Magnetic resonance imaging using chemical exchange saturation transfer

NASA Astrophysics Data System (ADS)

Park, Jaeseok

2012-10-01

Magnetic resonance imaging (MRI) has been widely used as a valuable diagnostic imaging modality that exploits water content and water relaxation properties to provide both structural and functional information with high resolution. Chemical exchange saturation transfer (CEST) in MRI has been recently introduced as a new mechanism of image contrast, wherein exchangeable protons from mobile proteins and peptides are indirectly detected through saturation transfer and are not observable using conventional MRI. It has been demonstrated that CEST MRI can detect important tissue metabolites and byproducts such as glucose, glycogen, and lactate. Additionally, CEST MRI is sensitive to pH or temperature and can calibrate microenvironment dependent on pH or temperature. In this work, we provide an overview on recent trends in CEST MRI, introducing general principles of CEST mechanism, quantitative description of proton transfer process between water pool and exchangeable solute pool in the presence or absence of conventional magnetization transfer effect, and its applications

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.

Non-invasive imaging of transplanted human neural stem cells and ECM scaffold remodeling in the stroke-damaged rat brain by 19F- and diffusion-MRI

PubMed Central

Bible, Ellen; Dell’Acqua, Flavio; Solanky, Bhavana; Balducci, Anthony; Crapo, Peter; Badylak, Stephen F.; Ahrens, Eric T.; Modo, Michel

2012-01-01

Transplantation of human neural stem cells (hNSCs) is emerging as a viable treatment for stroke related brain injury. However, intraparenchymal grafts do not regenerate lost tissue, but rather integrate into the host parenchyma without significantly affecting the lesion cavity. Providing a structural support for the delivered cells appears important for cell based therapeutic approaches. The non-invasive monitoring of therapeutic methods would provide valuable information regarding therapeutic strategies but remains a challenge. Labeling transplanted cells with metal-based 1H-magnetic resonance imaging (MRI) contrast agents affects the visualization of the lesion cavity. Herein, we demonstrate that a 19F-MRI contrast agent can adequately monitor the distribution of transplanted cells, whilst allowing an evaluation of the lesion cavity and the formation of new tissue on 1H-MRI scans. Twenty percent of cells labeled with the 19F-agent were of host origin, potentially reflecting the re-uptake of label from dead transplanted cells. Both T2- and diffusion-weighted MRI scans indicated that transplantation of hNSCs suspended in a gel form of a xenogeneic extracellular matrix (ECM) bioscaffold resulted in uniformly distributed cells throughout the lesion cavity. However, diffusion MRI indicated that the injected materials did not yet establish diffusion barriers (i.e. cellular network, fiber tracts) normally found within striatal tissue. The ECM bioscaffold therefore provides an important support to hNSCs for the creation of de novo tissue and multi-nuclei MRI represents an adept method for the visualization of some aspects of this process. However, significant developments of both the transplantation paradigm, as well as regenerative imaging, are required to successfully create new tissue in the lesion cavity and to monitor this process non-invasively. PMID:22244696

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.

Multidimensionally encoded magnetic resonance imaging.

PubMed

Lin, Fa-Hsuan

2013-07-01

Magnetic resonance imaging (MRI) typically achieves spatial encoding by measuring the projection of a q-dimensional object over q-dimensional spatial bases created by linear spatial encoding magnetic fields (SEMs). Recently, imaging strategies using nonlinear SEMs have demonstrated potential advantages for reconstructing images with higher spatiotemporal resolution and reducing peripheral nerve stimulation. In practice, nonlinear SEMs and linear SEMs can be used jointly to further improve the image reconstruction performance. Here, we propose the multidimensionally encoded (MDE) MRI to map a q-dimensional object onto a p-dimensional encoding space where p > q. MDE MRI is a theoretical framework linking imaging strategies using linear and nonlinear SEMs. Using a system of eight surface SEM coils with an eight-channel radiofrequency coil array, we demonstrate the five-dimensional MDE MRI for a two-dimensional object as a further generalization of PatLoc imaging and O-space imaging. We also present a method of optimizing spatial bases in MDE MRI. Results show that MDE MRI with a higher dimensional encoding space can reconstruct images more efficiently and with a smaller reconstruction error when the k-space sampling distribution and the number of samples are controlled. Copyright © 2012 Wiley Periodicals, Inc.

Comparison of In Vivo and Ex Vivo MRI for the Detection of Structural Abnormalities in a Mouse Model of Tauopathy

PubMed Central

Holmes, Holly E.; Powell, Nick M.; Ma, Da; Ismail, Ozama; Harrison, Ian F.; Wells, Jack A.; Colgan, Niall; O'Callaghan, James M.; Johnson, Ross A.; Murray, Tracey K.; Ahmed, Zeshan; Heggenes, Morten; Fisher, Alice; Cardoso, M. Jorge; Modat, Marc; O'Neill, Michael J.; Collins, Emily C.; Fisher, Elizabeth M. C.; Ourselin, Sébastien; Lythgoe, Mark F.

2017-01-01

With increasingly large numbers of mouse models of human disease dedicated to MRI studies, compromises between in vivo and ex vivo MRI must be fully understood in order to inform the choice of imaging methodology. We investigate the application of high resolution in vivo and ex vivo MRI, in combination with tensor-based morphometry (TBM), to uncover morphological differences in the rTg4510 mouse model of tauopathy. The rTg4510 mouse also offers a novel paradigm by which the overexpression of mutant tau can be regulated by the administration of doxycycline, providing us with a platform on which to investigate more subtle alterations in morphology with morphometry. Both in vivo and ex vivo MRI allowed the detection of widespread bilateral patterns of atrophy in the rTg4510 mouse brain relative to wild-type controls. Regions of volume loss aligned with neuronal loss and pathological tau accumulation demonstrated by immunohistochemistry. When we sought to investigate more subtle structural alterations in the rTg4510 mice relative to a subset of doxycycline-treated rTg4510 mice, ex vivo imaging enabled the detection of more regions of morphological brain changes. The disadvantages of ex vivo MRI may however mitigate this increase in sensitivity: we observed a 10% global shrinkage in brain volume of the post-mortem tissues due to formalin fixation, which was most notable in the cerebellum and olfactory bulbs. However, many central brain regions were not adversely affected by the fixation protocol, perhaps due to our “in-skull” preparation. The disparity between our TBM findings from in vivo and ex vivo MRI underlines the importance of appropriate study design, given the trade-off between these two imaging approaches. We support the utility of in vivo MRI for morphological phenotyping of mouse models of disease; however, for subtler phenotypes, ex vivo offers enhanced sensitivity to discrete morphological changes. PMID:28408879

Comparison of In Vivo and Ex Vivo MRI for the Detection of Structural Abnormalities in a Mouse Model of Tauopathy.

PubMed

Holmes, Holly E; Powell, Nick M; Ma, Da; Ismail, Ozama; Harrison, Ian F; Wells, Jack A; Colgan, Niall; O'Callaghan, James M; Johnson, Ross A; Murray, Tracey K; Ahmed, Zeshan; Heggenes, Morten; Fisher, Alice; Cardoso, M Jorge; Modat, Marc; O'Neill, Michael J; Collins, Emily C; Fisher, Elizabeth M C; Ourselin, Sébastien; Lythgoe, Mark F

2017-01-01

With increasingly large numbers of mouse models of human disease dedicated to MRI studies, compromises between in vivo and ex vivo MRI must be fully understood in order to inform the choice of imaging methodology. We investigate the application of high resolution in vivo and ex vivo MRI, in combination with tensor-based morphometry (TBM), to uncover morphological differences in the rTg4510 mouse model of tauopathy. The rTg4510 mouse also offers a novel paradigm by which the overexpression of mutant tau can be regulated by the administration of doxycycline, providing us with a platform on which to investigate more subtle alterations in morphology with morphometry. Both in vivo and ex vivo MRI allowed the detection of widespread bilateral patterns of atrophy in the rTg4510 mouse brain relative to wild-type controls. Regions of volume loss aligned with neuronal loss and pathological tau accumulation demonstrated by immunohistochemistry. When we sought to investigate more subtle structural alterations in the rTg4510 mice relative to a subset of doxycycline-treated rTg4510 mice, ex vivo imaging enabled the detection of more regions of morphological brain changes. The disadvantages of ex vivo MRI may however mitigate this increase in sensitivity: we observed a 10% global shrinkage in brain volume of the post-mortem tissues due to formalin fixation, which was most notable in the cerebellum and olfactory bulbs. However, many central brain regions were not adversely affected by the fixation protocol, perhaps due to our "in-skull" preparation. The disparity between our TBM findings from in vivo and ex vivo MRI underlines the importance of appropriate study design, given the trade-off between these two imaging approaches. We support the utility of in vivo MRI for morphological phenotyping of mouse models of disease; however, for subtler phenotypes, ex vivo offers enhanced sensitivity to discrete morphological changes.

Neuroimaging studies in schizophrenia: an overview of research from Asia.

PubMed

Narayanaswamy, Janardhanan C; Venkatasubramanian, Ganesan; Gangadhar, Bangalore N

2012-10-01

Neuroimaging studies in schizophrenia help clarify the neural substrates underlying the pathogenesis of this neuropsychiatric disorder. Contemporary brain imaging in schizophrenia is predominated by magnetic resonance imaging (MRI)-based research approaches. This review focuses on the various imaging studies from India and their relevance to the understanding of brain abnormalities in schizophrenia. The existing studies are predominantly comprised of structural MRI reports involving region-of-interest and voxel-based morphometry approaches, magnetic resonance spectroscopy and single-photon emission computed tomography/positron emission tomography (SPECT/PET) studies. Most of these studies are significant in that they have evaluated antipsychotic-naïve schizophrenia patients--a relatively difficult population to obtain in contemporary research. Findings of these studies offer robust support to the existence of significant brain abnormalities at very early stages of the disorder. In addition, theoretically relevant relationships between these brain abnormalities and developmental aberrations suggest possible neurodevelopmental basis for these brain deficits.

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.

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

Use of a Quality Improvement Initiative to Achieve Consistent Reporting of Level of Suspicion for Tumor on Multiparametric Prostate MRI.

PubMed

Rosenkrantz, Andrew B; Pujara, Akshat C; Taneja, Samir S

2016-05-01

The purpose of this article is to evaluate the utility of a quality improvement (QI) initiative in achieving long-term adherence to an evolving structured format for reporting the level of suspicion for tumor on prostate MRI examinations. The original QI initiative occurred over a 4-month period in 2010, before which prostate MRI was reported using free text. The initiative consisted of development of a section-wide macro, an initial group training session, ordering physician input regarding the structured report's value, subsequent weekly sessions for ongoing review, and timely individualized feedback in instances of nonuse. The initial structured report included pick lists for describing the level of suspicion for tumor as negative, low, medium, or high. Pick lists were modified in 2011 to incorporate a 5-point Likert scale and again in 2015 to incorporate Prostate Imaging Data and Reporting System (PI-RADS) version 2. These refinements were implemented after accelerated training periods. The frequency of reports providing an MRI-based suspicion level during these periods was assessed. Fifty-five percent of reports provided an MRI-based level of suspicion for tumor before the initiative. For various cohorts evaluated after the initiative (using structured reports based on the low, medium, or high scheme; a numeric Likert scale; or PI-RADS), this frequency improved to 95-100% (p < 0.001). Among reports without a suspicion level, potential confounding factors included marked artifact from hip prosthesis and overt diffuse tumor. The QI initiative achieved excellent adherence in reporting a suspicion level for tumor on prostate MRI examinations. The described components of the initiative were useful for maintaining long-term adherence that persisted after serial modifications to the report lexicon.

MR imaging of the traumatic triangular fibrocartilaginous complex tear

PubMed Central

Griffith, James F.; Fung, Cindy S. Y.; Lee, Ryan K. L.; Tong, Cina S. L.; Wong, Clara W. Y.; Tse, Wing Lim; Ho, Pak Cheong

2017-01-01

Triangular fibrocartilage complex is a major stabilizer of the distal radioulnar joint (DRUJ). However, triangular fibrocartilage complex (TFCC) tear is difficult to be diagnosed on MRI for its intrinsic small and thin structure with complex anatomy. The purpose of this article is to review the anatomy of TFCC, state of art MRI imaging technique, normal appearance and features of tear on MRI according to the Palmar’s classification. Atypical tear and limitations of MRI in diagnosis of TFCC tear are also discussed. PMID:28932701

Detecting Brain State Changes via Fiber-Centered Functional Connectivity Analysis

PubMed Central

Li, Xiang; Lim, Chulwoo; Li, Kaiming; Guo, Lei; Liu, Tianming

2013-01-01

Diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) have been widely used to study structural and functional brain connectivity in recent years. A common assumption used in many previous functional brain connectivity studies is the temporal stationarity. However, accumulating literature evidence has suggested that functional brain connectivity is under temporal dynamic changes in different time scales. In this paper, a novel and intuitive approach is proposed to model and detect dynamic changes of functional brain states based on multimodal fMRI/DTI data. The basic idea is that functional connectivity patterns of all fiber-connected cortical voxels are concatenated into a descriptive functional feature vector to represent the brain’s state, and the temporal change points of brain states are decided by detecting the abrupt changes of the functional vector patterns via the sliding window approach. Our extensive experimental results have shown that meaningful brain state change points can be detected in task-based fMRI/DTI, resting state fMRI/DTI, and natural stimulus fMRI/DTI data sets. Particularly, the detected change points of functional brain states in task-based fMRI corresponded well to the external stimulus paradigm administered to the participating subjects, thus partially validating the proposed brain state change detection approach. The work in this paper provides novel perspective on the dynamic behaviors of functional brain connectivity and offers a starting point for future elucidation of the complex patterns of functional brain interactions and dynamics. PMID:22941508

Ultrashort Echo-Time Magnetic Resonance Imaging Is a Sensitive Method for the Evaluation of Early Cystic Fibrosis Lung Disease

PubMed Central

Roach, David J.; Crémillieux, Yannick; Fleck, Robert J.; Brody, Alan S.; Serai, Suraj D.; Szczesniak, Rhonda D.; Kerlakian, Stephanie; Clancy, John P.

2016-01-01

Rationale: Recent advancements that have been made in magnetic resonance imaging (MRI) improve our ability to assess pulmonary structure and function in patients with cystic fibrosis (CF). A nonionizing imaging modality that can be used as a serial monitoring tool throughout life can positively affect patient care and outcomes. Objectives: To compare an ultrashort echo-time MRI method with computed tomography (CT) as a biomarker of lung structure abnormalities in young children with early CF lung disease. Methods: Eleven patients with CF (mean age, 31.8 ± 5.7 mo; median age, 33 mo; 7 male and 4 female) were imaged via CT and ultrashort echo-time MRI. Eleven healthy age-matched patients (mean age, 22.5 ± 10.2 mo; median age, 23 mo; 5 male and 6 female) were imaged via ultrashort echo-time MRI. CT scans of 13 additional patients obtained for clinical indications not affecting the heart or lungs and interpreted as normal provided a CT control group (mean age, 24.1 ± 11.7 mo; median age, 24 mo; 6 male and 7 female). Studies were scored by two experienced radiologists using a well-validated CF-specific scoring system for CF lung disease. Measurements and Main Results: Correlations between CT and ultrashort echo-time MRI scores of patients with CF were very strong, with P values ≤0.001 for bronchiectasis (r = 0.96) and overall score (r = 0.90), and moderately strong for bronchial wall thickening (r = 0.62, P = 0.043). MRI easily differentiated CF and control groups via a reader CF-specific scoring system. Conclusions: Ultrashort echo-time MRI detected structural lung disease in very young patients with CF and provided imaging data that correlated well with CT. By quantifying early CF lung disease without using ionizing radiation, ultrashort echo-time MRI appears well suited for pediatric patients requiring longitudinal imaging for clinical care or research studies. Clinical Trial registered with www.clinicaltrials.gov (NCT01832519). PMID:27551814

Respiratory motion resolved, self-gated 4D-MRI using Rotating Cartesian K-space (ROCK)

PubMed Central

Han, Fei; Zhou, Ziwu; Cao, Minsong; Yang, Yingli; Sheng, Ke; Hu, Peng

2017-01-01

Purpose To propose and validate a respiratory motion resolved, self-gated (SG) 4D-MRI technique to assess patient-specific breathing motion of abdominal organs for radiation treatment planning. Methods The proposed 4D-MRI technique was based on the balanced steady-state free-precession (bSSFP) technique and 3D k-space encoding. A novel ROtating Cartesian K-space (ROCK) reordering method was designed that incorporates repeatedly sampled k-space centerline as the SG motion surrogate and allows for retrospective k-space data binning into different respiratory positions based on the amplitude of the surrogate. The multiple respiratory-resolved 3D k-space data were subsequently reconstructed using a joint parallel imaging and compressed sensing method with spatial and temporal regularization. The proposed 4D-MRI technique was validated using a custom-made dynamic motion phantom and was tested in 6 healthy volunteers, in whom quantitative diaphragm and kidney motion measurements based on 4D-MRI images were compared with those based on 2D-CINE images. Results The 5-minute 4D-MRI scan offers high-quality volumetric images in 1.2×1.2×1.6mm3 and 8 respiratory positions, with good soft-tissue contrast. In phantom experiments with triangular motion waveform, the motion amplitude measurements based on 4D-MRI were 11.89% smaller than the ground truth, whereas a −12.5% difference was expected due to data binning effects. In healthy volunteers, the difference between the measurements based on 4D-MRI and the ones based on 2D-CINE were 6.2±4.5% for the diaphragm, 8.2±4.9% and 8.9±5.1% for the right and left kidney. Conclusion The proposed 4D-MRI technique could provide high resolution, high quality, respiratory motion resolved 4D images with good soft-tissue contrast and are free of the “stitching” artifacts usually seen on 4D-CT and 4D-MRI based on resorting 2D-CINE. It could be used to visualize and quantify abdominal organ motion for MRI-based radiation treatment planning. PMID:28133752

Respiratory motion-resolved, self-gated 4D-MRI using rotating cartesian k-space (ROCK).

PubMed

Han, Fei; Zhou, Ziwu; Cao, Minsong; Yang, Yingli; Sheng, Ke; Hu, Peng

2017-04-01

To propose and validate a respiratory motion resolved, self-gated (SG) 4D-MRI technique to assess patient-specific breathing motion of abdominal organs for radiation treatment planning. The proposed 4D-MRI technique was based on the balanced steady-state free-precession (bSSFP) technique and 3D k-space encoding. A novel rotating cartesian k-space (ROCK) reordering method was designed which incorporates repeatedly sampled k-space centerline as the SG motion surrogate and allows for retrospective k-space data binning into different respiratory positions based on the amplitude of the surrogate. The multiple respiratory-resolved 3D k-space data were subsequently reconstructed using a joint parallel imaging and compressed sensing method with spatial and temporal regularization. The proposed 4D-MRI technique was validated using a custom-made dynamic motion phantom and was tested in six healthy volunteers, in whom quantitative diaphragm and kidney motion measurements based on 4D-MRI images were compared with those based on 2D-CINE images. The 5-minute 4D-MRI scan offers high-quality volumetric images in 1.2 × 1.2 × 1.6 mm 3 and eight respiratory positions, with good soft-tissue contrast. In phantom experiments with triangular motion waveform, the motion amplitude measurements based on 4D-MRI were 11.89% smaller than the ground truth, whereas a -12.5% difference was expected due to data binning effects. In healthy volunteers, the difference between the measurements based on 4D-MRI and the ones based on 2D-CINE were 6.2 ± 4.5% for the diaphragm, 8.2 ± 4.9% and 8.9 ± 5.1% for the right and left kidney. The proposed 4D-MRI technique could provide high-resolution, high-quality, respiratory motion-resolved 4D images with good soft-tissue contrast and are free of the "stitching" artifacts usually seen on 4D-CT and 4D-MRI based on resorting 2D-CINE. It could be used to visualize and quantify abdominal organ motion for MRI-based radiation treatment planning. © 2017 American Association of Physicists in Medicine.

SU-F-T-42: MRI and TRUS Image Fusion as a Mode of Generating More Accurate Prostate Contours

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

Petronek, M; Purysko, A; Balik, S

Purpose: Transrectal Ultrasound (TRUS) imaging is utilized intra-operatively for LDR permanent prostate seed implant treatment planning. Prostate contouring with TRUS can be challenging at the apex and base. This study attempts to improve accuracy of prostate contouring with MRI-TRUS fusion to prevent over- or under-estimation of the prostate volume. Methods: 14 patients with previous MRI guided prostate biopsy and undergone an LDR permanent prostate seed implant have been selected. The prostate was contoured on the MRI images (1 mm slice thickness) by a radiologist. The prostate was also contoured on TRUS images (5 mm slice thickness) during LDR procedure bymore » a urologist. MRI and TRUS images were rigidly fused manually and the prostate contours from MRI and TRUS were compared using Dice similarity coefficient, percentage volume difference and length, height and width differences. Results: The prostate volume was overestimated by 8 ± 18% (range: 34% to −25%) in TRUS images compared to MRI. The mean Dice was 0.77 ± 0.09 (range: 0.53 to 0.88). The mean difference (TRUS-MRI) in the prostate width was 0 ± 4 mm (range: −11 to 5 mm), height was −3 ± 6 mm (range: −13 to 6 mm) and length was 6 ± 6 (range: −10 to 16 mm). Prostate was overestimated with TRUS imaging at the base for 6 cases (mean: 8 ± 4 mm and range: 5 to 14 mm), at the apex for 6 cases (mean: 11 ± 3 mm and range: 5 to 15 mm) and 1 case was underestimated at both base and apex by 4 mm. Conclusion: Use of intra-operative TRUS and MRI image fusion can help to improve the accuracy of prostate contouring by accurately accounting for prostate over- or under-estimations, especially at the base and apex. The mean amount of discrepancy is within a range that is significant for LDR sources.« less

A discrete polar Stockwell transform for enhanced characterization of tissue structure using MRI.

PubMed

Pridham, Glen; Steenwijk, Martijn D; Geurts, Jeroen J G; Zhang, Yunyan

2018-05-02

The purpose of this study was to present an effective algorithm for computing the discrete polar Stockwell transform (PST), investigate its unique multiscale and multi-orientation features, and explore potentially new applications including denoising and tissue segmentation. We investigated PST responses using both synthetic and MR images. Moreover, we compared the features of PST with both Gabor and Morlet wavelet transforms, and compared the PST with two wavelet approaches for denoising using MRI. Using a synthetic image, we also tested the edge effect of PST through signal-padding. Then, we constructed a partially supervised classifier using radial, marginal PST spectra of T2-weighted MRI, acquired from postmortem brains with multiple sclerosis. The classification involved three histology-verified tissue types: normal appearing white matter (NAWM), lesion, or other, along with 5-fold cross-validation. The PST generated a series of images with varying orientations or rotation-invariant scales. Radial frequencies highlighted image structures of different size, and angular frequencies enhanced structures by orientation. Signal-padding helped suppress boundary artifacts but required attention to incidental artifacts. In comparison, the Gabor transform produced more redundant images and the wavelet spectra appeared less spatially smooth than the PST. In addition, the PST demonstrated lower root-mean-square errors than other transforms in denoising and achieved a 93% accuracy for NAWM pixels (296/317), and 88% accuracy for lesion pixels (165/188) in MRI segmentation. The PST is a unique local spectral density-assessing tool which is sensitive to both structure orientations and scales. This may facilitate multiple new applications including advanced characterization of tissue structure in standard MRI. © 2018 International Society for Magnetic Resonance in Medicine.

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

Bernstein, Dr. Ira

This grant was awarded in support of Phase 2 of the University of Vermont Center for Biomedical Imaging. Phase 2 outlined several specific aims including: The development of expertise in MRI and fMRI imaging and their applications The acquisition of peer reviewed extramural funding in support of the Center The development of a Core Imaging Advisory Board, fee structure and protocol review and approval process.

SU-E-J-219: A Dixon Based Pseudo-CT Generation Method for MR-Only Radiotherapy Treatment Planning of the Pelvis and Head and Neck

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

Maspero, M.; Meijer, G.J.; Lagendijk, J.J.W.

2015-06-15

Purpose: To develop an image processing method for MRI-based generation of electron density maps, known as pseudo-CT (pCT), without usage of model- or atlas-based segmentation, and to evaluate the method in the pelvic and head-neck region against CT. Methods: CT and MRI scans were obtained from the pelvic region of four patients in supine position using a flat table top only for CT. Stratified CT maps were generated by classifying each voxel based on HU ranges into one of four classes: air, adipose tissue, soft tissue or bone.A hierarchical region-selective algorithm, based on automatic thresholding and clustering, was used tomore » classify tissues from MR Dixon reconstructed fat, In-Phase (IP) and Opposed-Phase (OP) images. First, a body mask was obtained by thresholding the IP image. Subsequently, an automatic threshold on the Dixon fat image differentiated soft and adipose tissue. K-means clustering on IP and OP images resulted in a mask that, via a connected neighborhood analysis, allowing the user to select the components corresponding to bone structures.The pCT was estimated through assignment of bulk HU to the tissue classes. Bone-only Digital Reconstructed Radiographs (DRR) were generated as well. The pCT images were rigidly registered to the stratified CT to allow a volumetric and voxelwise comparison. Moreover, pCTs were also calculated within the head-neck region in two volunteers using the same pipeline. Results: The volumetric comparison resulted in differences <1% for each tissue class. A voxelwise comparison showed a good classification, ranging from 64% to 98%. The primary misclassified classes were adipose/soft tissue and bone/soft tissue. As the patients have been imaged on different table tops, part of the misclassification error can be explained by misregistration. Conclusion: The proposed approach does not rely on an anatomy model providing the flexibility to successfully generate the pCT in two different body sites. This research is founded by ZonMw IMDI Programme, project name: “RASOR sharp: MRI based radiotherapy planning using a single MRI sequence”, project number: 10-104003010.« less

Resource atlases for multi-atlas brain segmentations with multiple ontology levels based on T1-weighted MRI.

PubMed

Wu, Dan; Ma, Ting; Ceritoglu, Can; Li, Yue; Chotiyanonta, Jill; Hou, Zhipeng; Hsu, John; Xu, Xin; Brown, Timothy; Miller, Michael I; Mori, Susumu

2016-01-15

Technologies for multi-atlas brain segmentation of T1-weighted MRI images have rapidly progressed in recent years, with highly promising results. This approach, however, relies on a large number of atlases with accurate and consistent structural identifications. Here, we introduce our atlas inventories (n=90), which cover ages 4-82years with unique hierarchical structural definitions (286 structures at the finest level). This multi-atlas library resource provides the flexibility to choose appropriate atlases for various studies with different age ranges and structure-definition criteria. In this paper, we describe the details of the atlas resources and demonstrate the improved accuracy achievable with a dynamic age-matching approach, in which atlases that most closely match the subject's age are dynamically selected. The advanced atlas creation strategy, together with atlas pre-selection principles, is expected to support the further development of multi-atlas image segmentation. Copyright © 2015 Elsevier Inc. All rights reserved.

Biological Image-Guided Radiotherapy in Rectal Cancer: Challenges and Pitfalls

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

Roels, Sarah; Slagmolen, Pieter; Nuyts, Johan

2009-11-01

Purpose: To investigate the feasibility of integrating multiple imaging modalities for image-guided radiotherapy in rectal cancer. Patients and Methods: Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) were performed before, during, and after preoperative chemoradiotherapy (CRT) in patients with resectable rectal cancer. The FDG-PET signals were segmented with an adaptive threshold-based and a gradient-based method. Magnetic resonance tumor volumes (TVs) were manually delineated. A nonrigid registration algorithm was applied to register the images, and mismatch analyses were carried out between MR and FDG-PET TVs and between TVs over time. Tumor volumes delineated on the images after CRTmore » were compared with the pathologic TV. Results: Forty-five FDG-PET/CT and 45 MR images were analyzed from 15 patients. The mean MRI and FDG-PET TVs showed a tendency to shrink during and after CRT. In general, MRI showed larger TVs than FDG-PET. There was an approximately 50% mismatch between the FDG-PET TV and the MRI TV at baseline and during CRT. Sixty-one percent of the FDG-PET TV and 76% of the MRI TV obtained after 10 fractions of CRT remained inside the corresponding baseline TV. On MRI, residual tumor was still suspected in all 6 patients with a pathologic complete response, whereas FDG-PET showed a metabolic complete response in 3 of them. The FDG-PET TVs delineated with the gradient-based method matched closest with pathologic findings. Conclusions: Integration of MRI and FDG-PET into radiotherapy seems feasible. Gradient-based segmentation is recommended for FDG-PET. Spatial variance between MRI and FDG-PET TVs should be taken into account for target definition.« less

Fast estimate of Hartley entropy in image sharpening

NASA Astrophysics Data System (ADS)

Krbcová, Zuzana; Kukal, Jaromír.; Svihlik, Jan; Fliegel, Karel

2016-09-01

Two classes of linear IIR filters: Laplacian of Gaussian (LoG) and Difference of Gaussians (DoG) are frequently used as high pass filters for contextual vision and edge detection. They are also used for image sharpening when linearly combined with the original image. Resulting sharpening filters are radially symmetric in spatial and frequency domains. Our approach is based on the radial approximation of unknown optimal filter, which is designed as a weighted sum of Gaussian filters with various radii. The novel filter is designed for MRI image enhancement where the image intensity represents anatomical structure plus additive noise. We prefer the gradient norm of Hartley entropy of whole image intensity as a measure which has to be maximized for the best sharpening. The entropy estimation procedure is as fast as FFT included in the filter but this estimate is a continuous function of enhanced image intensities. Physically motivated heuristic is used for optimum sharpening filter design by its parameter tuning. Our approach is compared with Wiener filter on MRI images.

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.

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

[Magnetic resonance imaging and ultrasonography in dogs and cats with ocular and orbital diseases. Part 1: Ocular diseases].

PubMed

von Krosigk, F; Steinmetz, A; Ellenberger, C; Oechtering, G

2012-01-01

This two-part study describes the clinical usefulness and value of ultrasound and magnetic resonance imaging (MRI) in dogs and cats with ocular (n=30) and orbital diseases (n=31). MRI and ultrasonography characteristics are described in single cases with ocular and orbital disease. Ultrasonography and MRI were performed in 15 dogs and 15 cats with intraocular neoplasia or intraocular inflammatory disease. In all patients with intraocular neoplasia, sonography revealed masses with increased echogenicity and fairly uniform echotexture, thus allowing the tentative diagnosis of an intraocular tumour. In these cases, MRI often proved to be a valuable diagnostic tool in showing the complete extent of intraocular lesion. An additional benefit of MRI was seen in the tissue characterization of tumours based on MRI signal characteristics and pattern of contrast enhancement. Discreet intraocular inflammatory alterations, in particular to the anterior and posterior segment of the eyeball, were more clearly shown by ultrasound than by MRI. Neoplasia could be excluded and inflammatory disease was successfully diagnosed using MRI due to the different image sequences with or without contrast medium administration. Traumatic ruptures of the lens capsule and the globe after trauma were depicted more clearly with MRI. When opacity of the anterior eye segment is present, various intraocular changes can be quickly diagnosed by ultrasound with high accuracy, without requiring anaesthesia of the patient. MRI of the globe allows differentiation of diverse pathologies, gives detailed information of infiltration in orbital structures and the exact degree of ocular lesions after trauma. This additional evidence often makes it easier to predict the correct prognosis and choose the best therapy.

Automated discrimination of dementia spectrum disorders using extreme learning machine and structural T1 MRI features.

PubMed

Jongin Kim; Boreom Lee

2017-07-01

The classification of neuroimaging data for the diagnosis of Alzheimer's Disease (AD) is one of the main research goals of the neuroscience and clinical fields. In this study, we performed extreme learning machine (ELM) classifier to discriminate the AD, mild cognitive impairment (MCI) from normal control (NC). We compared the performance of ELM with that of a linear kernel support vector machine (SVM) for 718 structural MRI images from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The data consisted of normal control, MCI converter (MCI-C), MCI non-converter (MCI-NC), and AD. We employed SVM-based recursive feature elimination (RFE-SVM) algorithm to find the optimal subset of features. In this study, we found that the RFE-SVM feature selection approach in combination with ELM shows the superior classification accuracy to that of linear kernel SVM for structural T1 MRI data.

In-plane "superresolution" MRI with phaseless sub-pixel encoding.

PubMed

Hennel, Franciszek; Tian, Rui; Engel, Maria; Pruessmann, Klaas P

2018-04-15

Acquisition of high-resolution imaging data using multiple excitations without the sensitivity to fluctuations of the transverse magnetization phase, which is a major problem of multi-shot MRI. The concept of superresolution MRI based on microscopic tagging is analyzed using an analogy with the optical method of structured illumination. Sinusoidal tagging is shown to provide subpixel resolution by mixing of neighboring spatial frequency (k-space) bands. It represents a phaseless modulation added on top of the standard Fourier encoding, which allows the phase fluctuations to be discarded at an intermediate reconstruction step. Improvements are proposed to correct for tag distortions due to magnetic field inhomogeneity and to avoid the propagation of Gibbs ringing from intermediate low-resolution images to the final image. The method was applied to diffusion-weighted EPI. Artifact-free superresolution images can be obtained despite a finite duration of the tagging sequence and related pattern distortions by a field map based phase correction of band-wise reconstructed images. The ringing effect present in the intermediate images can be suppressed by partial overlapping of the mixed k-space bands in combination with an adapted filter. High-resolution diffusion-weighted images of the human head were obtained with a three-shot EPI sequence despite motion-related phase fluctuations between the shots. Due to its phaseless character, tagging-based sub-pixel encoding is an alternative to k-space segmenting in the presence of unknown phase fluctuations, in particular those due to motion under strong diffusion gradients. Proposed improvements render the method practicable in realistic conditions. © 2018 International Society for Magnetic Resonance in Medicine.

Manganese-containing Prussian blue nanoparticles for imaging of pediatric brain tumors

PubMed Central

Dumont, Matthieu F; Yadavilli, Sridevi; Sze, Raymond W; Nazarian, Javad; Fernandes, Rohan

2014-01-01

Pediatric brain tumors (PBTs) are a leading cause of death in children. For an improved prognosis in patients with PBTs, there is a critical need to develop molecularly-specific imaging agents to monitor disease progression and response to treatment. In this paper, we describe manganese-containing Prussian blue nanoparticles as agents for molecular magnetic resonance imaging (MRI) and fluorescence-based imaging of PBTs. Our core-shell nanoparticles consist of a core lattice structure that incorporates and retains paramagnetic Mn2+ ions, and generates MRI contrast (both negative and positive). The biofunctionalized shell is comprised of fluorescent avidin, which serves the dual purpose of enabling fluorescence imaging and functioning as a platform for the attachment of biotinylated ligands that target PBTs. The surfaces of our nanoparticles are modified with biotinylated antibodies targeting neuron-glial antigen 2 or biotinylated transferrin. Both neuron-glial antigen 2 and the transferrin receptor are protein markers overexpressed in PBTs. We describe the synthesis, biofunctionalization, and characterization of these multimodal nanoparticles. Further, we demonstrate the MRI and fluorescence imaging capabilities of manganese-containing Prussian blue nanoparticles in vitro. Finally, we demonstrate the potential of these nanoparticles as PBT imaging agents by measuring their organ and brain biodistribution in an orthotopic mouse model of PBTs using ex vivo fluorescence imaging. PMID:24920896

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.

Dynamic MRI-based computer aided diagnostic systems for early detection of kidney transplant rejection: A survey

NASA Astrophysics Data System (ADS)

Mostapha, Mahmoud; Khalifa, Fahmi; Alansary, Amir; Soliman, Ahmed; Gimel'farb, Georgy; El-Baz, Ayman

2013-10-01

Early detection of renal transplant rejection is important to implement appropriate medical and immune therapy in patients with transplanted kidneys. In literature, a large number of computer-aided diagnostic (CAD) systems using different image modalities, such as ultrasound (US), magnetic resonance imaging (MRI), computed tomography (CT), and radionuclide imaging, have been proposed for early detection of kidney diseases. A typical CAD system for kidney diagnosis consists of a set of processing steps including: motion correction, segmentation of the kidney and/or its internal structures (e.g., cortex, medulla), construction of agent kinetic curves, functional parameter estimation, diagnosis, and assessment of the kidney status. In this paper, we survey the current state-of-the-art CAD systems that have been developed for kidney disease diagnosis using dynamic MRI. In addition, the paper addresses several challenges that researchers face in developing efficient, fast and reliable CAD systems for the early detection of kidney diseases.

The Age-ility Project (Phase 1): Structural and functional imaging and electrophysiological data repository.

PubMed

Karayanidis, Frini; Keuken, Max C; Wong, Aaron; Rennie, Jaime L; de Hollander, Gilles; Cooper, Patrick S; Ross Fulham, W; Lenroot, Rhoshel; Parsons, Mark; Phillips, Natalie; Michie, Patricia T; Forstmann, Birte U

2016-01-01

Our understanding of the complex interplay between structural and functional organisation of brain networks is being advanced by the development of novel multi-modal analyses approaches. The Age-ility Project (Phase 1) data repository offers open access to structural MRI, diffusion MRI, and resting-state fMRI scans, as well as resting-state EEG recorded from the same community participants (n=131, 15-35 y, 66 male). Raw imaging and electrophysiological data as well as essential demographics are made available via the NITRC website. All data have been reviewed for artifacts using a rigorous quality control protocol and detailed case notes are provided. Copyright © 2015. Published by Elsevier Inc.

Multi-atlas segmentation of subcortical brain structures via the AutoSeg software pipeline

PubMed Central

Wang, Jiahui; Vachet, Clement; Rumple, Ashley; Gouttard, Sylvain; Ouziel, Clémentine; Perrot, Emilie; Du, Guangwei; Huang, Xuemei; Gerig, Guido; Styner, Martin

2014-01-01

Automated segmenting and labeling of individual brain anatomical regions, in MRI are challenging, due to the issue of individual structural variability. Although atlas-based segmentation has shown its potential for both tissue and structure segmentation, due to the inherent natural variability as well as disease-related changes in MR appearance, a single atlas image is often inappropriate to represent the full population of datasets processed in a given neuroimaging study. As an alternative for the case of single atlas segmentation, the use of multiple atlases alongside label fusion techniques has been introduced using a set of individual “atlases” that encompasses the expected variability in the studied population. In our study, we proposed a multi-atlas segmentation scheme with a novel graph-based atlas selection technique. We first paired and co-registered all atlases and the subject MR scans. A directed graph with edge weights based on intensity and shape similarity between all MR scans is then computed. The set of neighboring templates is selected via clustering of the graph. Finally, weighted majority voting is employed to create the final segmentation over the selected atlases. This multi-atlas segmentation scheme is used to extend a single-atlas-based segmentation toolkit entitled AutoSeg, which is an open-source, extensible C++ based software pipeline employing BatchMake for its pipeline scripting, developed at the Neuro Image Research and Analysis Laboratories of the University of North Carolina at Chapel Hill. AutoSeg performs N4 intensity inhomogeneity correction, rigid registration to a common template space, automated brain tissue classification based skull-stripping, and the multi-atlas segmentation. The multi-atlas-based AutoSeg has been evaluated on subcortical structure segmentation with a testing dataset of 20 adult brain MRI scans and 15 atlas MRI scans. The AutoSeg achieved mean Dice coefficients of 81.73% for the subcortical structures. PMID:24567717

Neural Signatures of Autism Spectrum Disorders: Insights into Brain Network Dynamics

PubMed Central

Hernandez, Leanna M; Rudie, Jeffrey D; Green, Shulamite A; Bookheimer, Susan; Dapretto, Mirella

2015-01-01

Neuroimaging investigations of autism spectrum disorders (ASDs) have advanced our understanding of atypical brain function and structure, and have recently converged on a model of altered network-level connectivity. Traditional task-based functional magnetic resonance imaging (MRI) and volume-based structural MRI studies have identified widespread atypicalities in brain regions involved in social behavior and other core ASD-related behavioral deficits. More recent advances in MR-neuroimaging methods allow for quantification of brain connectivity using diffusion tensor imaging, functional connectivity, and graph theoretic methods. These newer techniques have moved the field toward a systems-level understanding of ASD etiology, integrating functional and structural measures across distal brain regions. Neuroimaging findings in ASD as a whole have been mixed and at times contradictory, likely due to the vast genetic and phenotypic heterogeneity characteristic of the disorder. Future longitudinal studies of brain development will be crucial to yield insights into mechanisms of disease etiology in ASD sub-populations. Advances in neuroimaging methods and large-scale collaborations will also allow for an integrated approach linking neuroimaging, genetics, and phenotypic data. PMID:25011468

Evaluation of Morphological Plasticity in the Cerebella of Basketball Players with MRI

PubMed Central

Park, In Sung; Han, Jong Woo; Lee, Kea Joo; Lee, Nam Joon; Lee, Won Teak; Park, Kyung Ah

2006-01-01

Cerebellum is a key structure involved in motor learning and coordination. In animal models, motor skill learning increased the volume of molecular layer and the number of synapses on Purkinje cells in the cerebellar cortex. The aim of this study is to investigate whether the analogous change of cerebellar volume occurs in human population who learn specialized motor skills and practice them intensively for a long time. Magnetic resonance image (MRI)-based cerebellar volumetry was performed in basketball players and matched controls with V-works image software. Total brain volume, absolute and relative cerebellar volumes were compared between two groups. There was no significant group difference in the total brain volume, the absolute and the relative cerebellar volume. Thus we could not detect structural change in the cerebellum of this athlete group in the macroscopic level. PMID:16614526

MRI and histopathologic study of a novel cholesterol-fed rabbit model of xanthogranuloma.

PubMed

Chen, Yuanxin; Hamilton, Amanda M; Parkins, Katie M; Wang, Jian-Xiong; Rogers, Kem A; Zeineh, Michael M; Rutt, Brian K; Ronald, John A

2016-09-01

To develop a rabbit model of xanthogranuloma based on supplementation of dietary cholesterol. The aim of this study was to analyze the xanthogranulomatous lesions using magnetic resonance imaging (MRI) and histological examination. Rabbits were fed a low-level cholesterol (CH) diet (n = 10) or normal chow (n = 5) for 24 months. In vivo brain imaging was performed on a 3T MR system using fast imaging employing steady state acquisition, susceptibility-weighted imaging, spoiled gradient recalled, T1 -weighted inversion recovery imaging and T1 relaxometry, PD-weighted and T2 -weighted spin-echo imaging and T2 relaxometry, iterative decomposition of water and fat with echo asymmetry and least-squares estimation, ultrashort TE MRI (UTE-MRI), and T2* relaxometry. MR images were evaluated using a Likert scale for lesion presence and quantitative analysis of lesion size, ventricular volume, and T1 , T2 , and T2* values of lesions was performed. After imaging, brain specimens were examined using histological methods. In vivo MRI revealed that 6 of 10 CH-fed rabbits developed lesions in the choroid plexus. Region-of-interest analysis showed that for CH-fed rabbits the mean lesion volume was 8.5 ± 2.6 mm(3) and the volume of the lateral ventricle was significantly increased compared to controls (P < 0.01). The lesions showed significantly shorter mean T2 values (35 ± 12 msec, P < 0.001), longer mean T1 values (1581 ± 146 msec, P < 0.05), and shorter T2* values (22 ± 13 msec, P < 0.001) compared to adjacent brain structures. The ultrashort T2* components were visible using UTE-MRI. Histopathologic evaluation of lesions demonstrated features of human xanthogranuloma. Rabbits fed a low-level CH diet develop sizable intraventricular masses that have similar histopathological features as human xanthogranuloma. Multiparametric MRI techniques were able to provide information about the complex composition of these lesions. J. Magn. Reson. Imaging 2016;44:673-682. © 2016 International Society for Magnetic Resonance in Medicine.

Validation of a rapid, semiautomatic image analysis tool for measurement of gastric accommodation and emptying by magnetic resonance imaging

PubMed Central

Dixit, Sudeepa; Fox, Mark; Pal, Anupam

2014-01-01

Magnetic resonance imaging (MRI) has advantages for the assessment of gastrointestinal structures and functions; however, processing MRI data is time consuming and this has limited uptake to a few specialist centers. This study introduces a semiautomatic image processing system for rapid analysis of gastrointestinal MRI. For assessment of simpler regions of interest (ROI) such as the stomach, the system generates virtual images along arbitrary planes that intersect the ROI edges in the original images. This generates seed points that are joined automatically to form contours on each adjacent two-dimensional image and reconstructed in three dimensions (3D). An alternative thresholding approach is available for rapid assessment of complex structures like the small intestine. For assessment of dynamic gastrointestinal function, such as gastric accommodation and emptying, the initial 3D reconstruction is used as reference to process adjacent image stacks automatically. This generates four-dimensional (4D) reconstructions of dynamic volume change over time. Compared with manual processing, this semiautomatic system reduced the user input required to analyze a MRI gastric emptying study (estimated 100 vs. 10,000 mouse clicks). This analysis was not subject to variation in volume measurements seen between three human observers. In conclusion, the image processing platform presented processed large volumes of MRI data, such as that produced by gastric accommodation and emptying studies, with minimal user input. 3D and 4D reconstructions of the stomach and, potentially, other gastrointestinal organs are produced faster and more accurately than manual methods. This system will facilitate the application of MRI in gastrointestinal research and clinical practice. PMID:25540229

MRI appearance of posterior cruciate ligament tears.

PubMed

Rodriguez, William; Vinson, Emily N; Helms, Clyde A; Toth, Alison P

2008-10-01

There is little in the radiology literature regarding the MRI appearance of a torn posterior cruciate ligament (PCL). The purpose of this study was to describe the MRI appearance of surgically proven PCL tears and to emphasize previously unreported signs. The PCL is usually injured as the result of stretching deformation; on MRI, the ligament maintains continuity as a single structure with apparent thickening. On sagittal T2-weighted images, an anteroposterior diameter of 7 mm or more is highly suggestive of a torn PCL. Increased intrasubstance signal intensity in the PCL on proton-density images with lower signal intensity on T2-weighted images is another common feature.

Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method.

PubMed

Schullcke, Benjamin; Gong, Bo; Krueger-Ziolek, Sabine; Soleimani, Manuchehr; Mueller-Lisse, Ullrich; Moeller, Knut

2016-05-16

Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications.

Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method

PubMed Central

Schullcke, Benjamin; Gong, Bo; Krueger-Ziolek, Sabine; Soleimani, Manuchehr; Mueller-Lisse, Ullrich; Moeller, Knut

2016-01-01

Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications. PMID:27181695

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

The Marburg-Münster Affective Disorders Cohort Study (MACS): A quality assurance protocol for MR neuroimaging data.

PubMed

Vogelbacher, Christoph; Möbius, Thomas W D; Sommer, Jens; Schuster, Verena; Dannlowski, Udo; Kircher, Tilo; Dempfle, Astrid; Jansen, Andreas; Bopp, Miriam H A

2018-05-15

Large, longitudinal, multi-center MR neuroimaging studies require comprehensive quality assurance (QA) protocols for assessing the general quality of the compiled data, indicating potential malfunctions in the scanning equipment, and evaluating inter-site differences that need to be accounted for in subsequent analyses. We describe the implementation of a QA protocol for functional magnet resonance imaging (fMRI) data based on the regular measurement of an MRI phantom and an extensive variety of currently published QA statistics. The protocol is implemented in the MACS (Marburg-Münster Affective Disorders Cohort Study, http://for2107.de/), a two-center research consortium studying the neurobiological foundations of affective disorders. Between February 2015 and October 2016, 1214 phantom measurements have been acquired using a standard fMRI protocol. Using 444 healthy control subjects which have been measured between 2014 and 2016 in the cohort, we investigate the extent of between-site differences in contrast to the dependence on subject-specific covariates (age and sex) for structural MRI, fMRI, and diffusion tensor imaging (DTI) data. We show that most of the presented QA statistics differ severely not only between the two scanners used for the cohort but also between experimental settings (e.g. hardware and software changes), demonstrate that some of these statistics depend on external variables (e.g. time of day, temperature), highlight their strong dependence on proper handling of the MRI phantom, and show how the use of a phantom holder may balance this dependence. Site effects, however, do not only exist for the phantom data, but also for human MRI data. Using T1-weighted structural images, we show that total intracranial (TIV), grey matter (GMV), and white matter (WMV) volumes significantly differ between the MR scanners, showing large effect sizes. Voxel-based morphometry (VBM) analyses show that these structural differences observed between scanners are most pronounced in the bilateral basal ganglia, thalamus, and posterior regions. Using DTI data, we also show that fractional anisotropy (FA) differs between sites in almost all regions assessed. When pooling data from multiple centers, our data show that it is a necessity to account not only for inter-site differences but also for hardware and software changes of the scanning equipment. Also, the strong dependence of the QA statistics on the reliable placement of the MRI phantom shows that the use of a phantom holder is recommended to reduce the variance of the QA statistics and thus to increase the probability of detecting potential scanner malfunctions. Copyright © 2018 Elsevier Inc. All rights reserved.

Radiologic imaging of the renal parenchyma structure and function.

PubMed

Grenier, Nicolas; Merville, Pierre; Combe, Christian

2016-06-01

Radiologic imaging has the potential to identify several functional and/or structural biomarkers of acute and chronic kidney diseases that are useful diagnostics to guide patient management. A renal ultrasound examination can provide information regarding the gross anatomy and macrostructure of the renal parenchyma, and ultrasound imaging modalities based on Doppler or elastography techniques can provide haemodynamic and structural information, respectively. CT is also able to combine morphological and functional information, but the use of CT is limited due to the required exposure to X-ray irradiation and a risk of contrast-induced nephropathy following intravenous injection of a radio-contrast agent. MRI can be used to identify a wide range of anatomical and physiological parameters at the tissue and even cellular level, such as tissue perfusion, oxygenation, water diffusion, cellular phagocytic activity, tissue stiffness, and level of renal filtration. The ability of MRI to provide valuable information for most of these parameters within a renal context is still in development and requires more clinical experience, harmonization of technical procedures, and an evaluation of reliability and validity on a large scale.

Segmentation of left ventricle myocardium in porcine cardiac cine MR images using a hybrid of fully convolutional neural networks and convolutional LSTM

NASA Astrophysics Data System (ADS)

Zhang, Dongqing; Icke, Ilknur; Dogdas, Belma; Parimal, Sarayu; Sampath, Smita; Forbes, Joseph; Bagchi, Ansuman; Chin, Chih-Liang; Chen, Antong

2018-03-01

In the development of treatments for cardiovascular diseases, short axis cardiac cine MRI is important for the assessment of various structural and functional properties of the heart. In short axis cardiac cine MRI, Cardiac properties including the ventricle dimensions, stroke volume, and ejection fraction can be extracted based on accurate segmentation of the left ventricle (LV) myocardium. One of the most advanced segmentation methods is based on fully convolutional neural networks (FCN) and can be successfully used to do segmentation in cardiac cine MRI slices. However, the temporal dependency between slices acquired at neighboring time points is not used. Here, based on our previously proposed FCN structure, we proposed a new algorithm to segment LV myocardium in porcine short axis cardiac cine MRI by incorporating convolutional long short-term memory (Conv-LSTM) to leverage the temporal dependency. In this approach, instead of processing each slice independently in a conventional CNN-based approach, the Conv-LSTM architecture captures the dynamics of cardiac motion over time. In a leave-one-out experiment on 8 porcine specimens (3,600 slices), the proposed approach was shown to be promising by achieving average mean Dice similarity coefficient (DSC) of 0.84, Hausdorff distance (HD) of 6.35 mm, and average perpendicular distance (APD) of 1.09 mm when compared with manual segmentations, which improved the performance of our previous FCN-based approach (average mean DSC=0.84, HD=6.78 mm, and APD=1.11 mm). Qualitatively, our model showed robustness against low image quality and complications in the surrounding anatomy due to its ability to capture the dynamics of cardiac motion.

Basic concepts of MR imaging, diffusion MR imaging, and diffusion tensor imaging.

PubMed

de Figueiredo, Eduardo H M S G; Borgonovi, Arthur F N G; Doring, Thomas M

2011-02-01

MR image contrast is based on intrinsic tissue properties and specific pulse sequences and parameter adjustments. A growing number of MRI imaging applications are based on diffusion properties of water. To better understand MRI diffusion-weighted imaging, a brief overview of MR physics is presented in this article followed by physics of the evolving techniques of diffusion MR imaging and diffusion tensor imaging. Copyright © 2011. Published by Elsevier Inc.

Fractal analysis of the susceptibility weighted imaging patterns in malignant brain tumors during antiangiogenic treatment: technical report on four cases serially imaged by 7 T magnetic resonance during a period of four weeks.

PubMed

Di Ieva, Antonio; Matula, Christian; Grizzi, Fabio; Grabner, Günther; Trattnig, Siegfried; Tschabitscher, Manfred

2012-01-01

The need for new and objective indexes for the neuroradiologic follow-up of brain tumors and for monitoring the effects of antiangiogenic strategies in vivo led us to perform a technical study on four patients who received computerized analysis of tumor-associated vasculature with ultra-high-field (7 T) magnetic resonance imaging (MRI). The image analysis involved the application of susceptibility weighted imaging (SWI) to evaluate vascular structures. Four patients affected by recurrent malignant brain tumors were enrolled in the present study. After the first 7-T SWI MRI procedure, the patients underwent antiangiogenic treatment with bevacizumab. The imaging was repeated every 2 weeks for a period of 4 weeks. The SWI patterns visualized in the three MRI temporal sequences were analyzed by means of a computer-aided fractal-based method to objectively quantify their geometric complexity. In two clinically deteriorating patients we found an increase of the geometric complexity of the space-filling properties of the SWI patterns over time despite the antiangiogenic treatment. In one patient, who showed improvement with the therapy, the fractal dimension of the intratumoral structure decreased, whereas in the fourth patient, no differences were found. The qualitative changes of the intratumoral SWI patterns during a period of 4 weeks were quantified with the fractal dimension. Because SWI patterns are also related to the presence of vascular structures, the quantification of their space-filling properties with fractal dimension seemed to be a valid tool for the in vivo neuroradiologic follow-up of brain tumors. Copyright © 2012 Elsevier Inc. All rights reserved.

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

Korhonen, Juha, E-mail: juha.p.korhonen@hus.fi; Kapanen, Mika; Department of Oncology, Helsinki University Central Hospital, POB-180, 00029 HUS

Purpose: The lack of electron density information in magnetic resonance images (MRI) poses a major challenge for MRI-based radiotherapy treatment planning (RTP). In this study the authors convert MRI intensity values into Hounsfield units (HUs) in the male pelvis and thus enable accurate MRI-based RTP for prostate cancer patients with varying tissue anatomy and body fat contents. Methods: T{sub 1}/T{sub 2}*-weighted MRI intensity values and standard computed tomography (CT) image HUs in the male pelvis were analyzed using image data of 10 prostate cancer patients. The collected data were utilized to generate a dual model HU conversion technique from MRImore » intensity values of the single image set separately within and outside of contoured pelvic bones. Within the bone segment local MRI intensity values were converted to HUs by applying a second-order polynomial model. This model was tuned for each patient by two patient-specific adjustments: MR signal normalization to correct shifts in absolute intensity level and application of a cutoff value to accurately represent low density bony tissue HUs. For soft tissues, such as fat and muscle, located outside of the bone contours, a threshold-based segmentation method without requirements for any patient-specific adjustments was introduced to convert MRI intensity values into HUs. The dual model HU conversion technique was implemented by constructing pseudo-CT images for 10 other prostate cancer patients. The feasibility of these images for RTP was evaluated by comparing HUs in the generated pseudo-CT images with those in standard CT images, and by determining deviations in MRI-based dose distributions compared to those in CT images with 7-field intensity modulated radiation therapy (IMRT) with the anisotropic analytical algorithm and 360° volumetric-modulated arc therapy (VMAT) with the Voxel Monte Carlo algorithm. Results: The average HU differences between the constructed pseudo-CT images and standard CT images of each test patient ranged from −2 to 5 HUs and from 22 to 78 HUs in soft and bony tissues, respectively. The average local absolute value differences were 11 HUs in soft tissues and 99 HUs in bones. The planning target volume doses (volumes 95%, 50%, 5%) in the pseudo-CT images were within 0.8% compared to those in CT images in all of the 20 treatment plans. The average deviation was 0.3%. With all the test patients over 94% (IMRT) and 92% (VMAT) of dose points within body (lower than 10% of maximum dose suppressed) passed the 1 mm and 1% 2D gamma index criterion. The statistical tests (t- and F-tests) showed significantly improved (p ≤ 0.05) HU and dose calculation accuracies with the soft tissue conversion method instead of homogeneous representation of these tissues in MRI-based RTP images. Conclusions: This study indicates that it is possible to construct high quality pseudo-CT images by converting the intensity values of a single MRI series into HUs in the male pelvis, and to use these images for accurate MRI-based prostate RTP dose calculations.« less

Multicontrast multiecho FLASH MRI for targeting the subthalamic nucleus.

PubMed

Xiao, Yiming; Beriault, Silvain; Pike, G Bruce; Collins, D Louis

2012-06-01

The subthalamic nucleus (STN) is one of the most common stimulation targets for treating Parkinson's disease using deep brain stimulation (DBS). This procedure requires precise placement of the stimulating electrode. Common practice of DBS implantation utilizes microelectrode recording to locate the sites with the correct electrical response after an initial location estimate based on a universal human brain atlas that is linearly scaled to the patient's anatomy as seen on the preoperative images. However, this often results in prolonged surgical time and possible surgical complications since the small-sized STN is difficult to visualize on conventional magnetic resonance (MR) images and its intersubject variability is not sufficiently considered in the atlas customization. This paper proposes a multicontrast, multiecho MR imaging (MRI) method that directly delineates the STN and other basal ganglia structures through five co-registered image contrasts (T1-weighted navigation image, R2 map, susceptibility-weighted imaging (phase, magnitude and fusion image)) obtained within a clinically acceptable time. The image protocol was optimized through both simulation and in vivo experiments to obtain the best image quality. Taking advantage of the multiple echoes and high readout bandwidths, no interimage registration is required since all images are produced in one acquisition, and image distortion and chemical shift are reduced. This MRI protocol is expected to mitigate some of the shortcomings of the state-of-the-art DBS implantation methods. Copyright © 2012 Elsevier Inc. All rights reserved.

Magnetic Resonance Imaging Assessment of Intra-Articular Structures in the Canine Stifle Joint after Implantation of a Titanium Tibial Plateau Levelling Osteotomy Plate.

PubMed

Feichtenschlager, Christian; Gerwing, Martin; Failing, Klaus; Peppler, Christine; Kása, Andreas; Kramer, Martin; von Pückler, Kerstin H

2018-06-02

 To determine the effectiveness of magnetic resonance imaging (MRI) in the evaluation of anatomical stifle structures with respect to implant positioning after tibial plateau levelling osteotomy (TPLO) using a titanium plate.  Selected sagittal and dorsal sequences of pre- and postoperative MRI (1.0 T scanner) of 13 paired ( n  = 26) sound cadaveric stifle joints were evaluated. The effect of susceptibility artifact on adjacent anatomical stifle structures was graded from 0 to 5. The impact of implant positioning regarding assessment score was calculated using Spearman's rank correlation coefficient.  Sagittal turbo spin echo (TSE)-acquired images enabled interpretation of most soft tissue, osseous and cartilage structures without detrimental effect of susceptibility artifact distortions. In T2-weighted TSE images, the cranial cruciate ligament and caudal horn of the medial meniscus could be evaluated, independent of implant position, without any susceptibility artifact in all specimens. T2-weighted fast field echo, water selective, balanced fast field echo and short tau inversion recovery were most markedly affected by susceptibility artifact.  In selected TSE sequences, MRI allows evaluation of critical intra-articular structures after titanium TPLO plate implantation. Further investigations with confirmed stifle pathologies in dogs are required, to evaluate the accuracy of MRI after TPLO in clinical cases in this context. Schattauer GmbH Stuttgart.

First Application of 7T Magnetic Resonance Imaging in Endoscopic Endonasal Surgery of Skull Base Tumors

PubMed Central

Barrett, Thomas F; Dyvorne, Hadrien A; Padormo, Francesco; Pawha, Puneet S; Delman, Bradley N; Shrivastava, Raj K; Balchandani, Priti

2018-01-01

Background 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 7T MRI can be used to increase spatial and contrast resolution, which may lend itself to improved imaging of skull base. In this study, we apply a 7T imaging protocol to patients with skull base tumors and compare the images to clinical standard of care. Methods Images were acquired at 7T on 11 patients with skull base lesions. Two neuroradiologists evaluated clinical 1.5T, 3T, and 7T scans for detection of intracavernous cranial nerves and ICA branches. Detection rates were compared. Images were utilized for surgical planning and uploaded to a neuronavigation platform and used to guide surgery. Results Image analysis yielded improved detection rates of cranial nerves and ICA branches at 7T. 7T images were successfully incorporated into preoperative planning and intraoperative neuronavigation. Conclusion Our study represents the first application of 7T MRI to the full neurosurgical workflow for endoscopic endonasal surgery. We detected higher rates of cranial nerves and ICA branches at 7T MRI compared to 3T and 1.5 T, and found that integration of 7T into surgical planning and guidance was feasible. These results suggest a potential for 7T MRI to reduce surgical complications. Future studies comparing standardized 7T, 3T, and 1.5 T MRI protocols in a larger number of patients are warranted to determine the relative benefit of 7T MRI for endonasal endoscopic surgical efficacy. PMID:28359922

Surface-based reconstruction and diffusion MRI in the assessment of gray and white matter damage in multiple sclerosis

NASA Astrophysics Data System (ADS)

Caffini, Matteo; Bergsland, Niels; LaganÃ, Marcella; Tavazzi, Eleonora; Tortorella, Paola; Rovaris, Marco; Baselli, Giuseppe

2014-03-01

Despite advances in the application of nonconventional MRI techniques in furthering the understanding of multiple sclerosis pathogenic mechanisms, there are still many unanswered questions, such as the relationship between gray and white matter damage. We applied a combination of advanced surface-based reconstruction and diffusion tensor imaging techniques to address this issue. We found significant relationships between white matter tract integrity indices and corresponding cortical structures. Our results suggest a direct link between damage in white and gray matter and contribute to the notion of gray matter loss relating to clinical disability.

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.

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.

Analyzing and Assessing Brain Structure with Graph Connectivity Measures

DTIC Science & Technology

2014-05-09

structural brain networks, i.e. determining which regions of the brain are physically connected. Meanwhile, functional MRI ( fMRI ) yields an image of...produced by fMRI is a map of which parts are of the brain are active and which are not at a given time. In creating functional networks, regions of...the brain which often activitate together, i.e., often show up on fMRI as deoxygenated regions together, are considered connected. DTI allows the

Nitroxide-Based Macromolecular Contrast Agents with Unprecedented Transverse Relaxivity and Stability for Magnetic Resonance Imaging of Tumors

PubMed Central

2017-01-01

Metal-free magnetic resonance imaging (MRI) agents could overcome the established toxicity associated with metal-based agents in some patient populations and enable new modes of functional MRI in vivo. Herein, we report nitroxide-functionalized brush-arm star polymer organic radical contrast agents (BASP-ORCAs) that overcome the low contrast and poor in vivo stability associated with nitroxide-based MRI contrast agents. As a consequence of their unique nanoarchitectures, BASP-ORCAs possess per-nitroxide transverse relaxivities up to ∼44-fold greater than common nitroxides, exceptional stability in highly reducing environments, and low toxicity. These features combine to provide for accumulation of a sufficient concentration of BASP-ORCA in murine subcutaneous tumors up to 20 h following systemic administration such that MRI contrast on par with metal-based agents is observed. BASP-ORCAs are, to our knowledge, the first nitroxide MRI contrast agents capable of tumor imaging over long time periods using clinical high-field 1H MRI techniques. PMID:28776023

SU-F-J-17: Patient Localization Using MRI-Guided Soft Tissue for Head-And-Neck Radiotherapy: Indication for Margin Reduction and Its Feasibility

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

Qi, X; Yang, Y; Jack, N

Purpose: On-board MRI provides superior soft-tissue contrast, allowing patient alignment using tumor or nearby critical structures. This study aims to study H&N MRI-guided IGRT to analyze inter-fraction patient setup variations using soft-tissue targets and design appropriate CTV-to-PTV margin and clinical implication. Methods: 282 MR images for 10 H&N IMRT patients treated on a ViewRay system were retrospectively analyzed. Patients were immobilized using a thermoplastic mask on a customized headrest fitted in a radiofrequency coil and positioned to soft-tissue targets. The inter-fraction patient displacements were recorded to compute the PTV margins using the recipe: 2.5∑+0.7σ. New IMRT plans optimized on themore » revised PTVs were generated to evaluate the delivered dose distributions. An in-house dose deformation registration tool was used to assess the resulting dosimetric consequences when margin adaption is performed based on weekly MR images. The cumulative doses were compared to the reduced margin plans for targets and critical structures. Results: The inter-fraction displacements (and standard deviations), ∑ and σ were tabulated for MRI and compared to kVCBCT. The computed CTV-to-PTV margin was 3.5mm for soft-tissue based registration. There were minimal differences between the planned and delivered doses when comparing clinical and the PTV reduced margin plans: the paired t-tests yielded p=0.38 and 0.66 between the planned and delivered doses for the adapted margin plans for the maximum cord and mean parotid dose, respectively. Target V95 received comparable doses as planned for the reduced margin plans. Conclusion: The 0.35T MRI offers acceptable soft-tissue contrast and good spatial resolution for patient alignment and target visualization. Better tumor conspicuity from MRI allows soft-tissue based alignments with potentially improved accuracy, suggesting a benefit of margin reduction for H&N radiotherapy. The reduced margin plans (i.e., 2 mm) resulted in improved normal structure sparing and accurate dose delivery to achieve intended treatment goal under MR guidance.« less

[Fusion of MRI, fMRI and intraoperative MRI data. Methods and clinical significance exemplified by neurosurgical interventions].

PubMed

Moche, M; Busse, H; Dannenberg, C; Schulz, T; Schmitgen, A; Trantakis, C; Winkler, D; Schmidt, F; Kahn, T

2001-11-01

The aim of this work was to realize and clinically evaluate an image fusion platform for the integration of preoperative MRI and fMRI data into the intraoperative images of an interventional MRI system with a focus on neurosurgical procedures. A vertically open 0.5 T MRI scanner was equipped with a dedicated navigation system enabling the registration of additional imaging modalities (MRI, fMRI, CT) with the intraoperatively acquired data sets. These merged image data served as the basis for interventional planning and multimodal navigation. So far, the system has been used in 70 neurosurgical interventions (13 of which involved image data fusion--requiring 15 minutes extra time). The augmented navigation system is characterized by a higher frame rate and a higher image quality as compared to the system-integrated navigation based on continuously acquired (near) real time images. Patient movement and tissue shifts can be immediately detected by monitoring the morphological differences between both navigation scenes. The multimodal image fusion allowed a refined navigation planning especially for the resection of deeply seated brain lesions or pathologies close to eloquent areas. Augmented intraoperative orientation and instrument guidance improve the safety and accuracy of neurosurgical interventions.

Molecular Platform for Design and Synthesis of Targeted Dual-Modality Imaging Probes

PubMed Central

2015-01-01

We report a versatile dendritic structure based platform for construction of targeted dual-modality imaging probes. The platform contains multiple copies of 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) branching out from a 1,4,7-triazacyclononane-N,N′,N″-triacetic acid (NOTA) core. The specific coordination chemistries of the NOTA and DOTA moieties offer specific loading of 68/67Ga3+ and Gd3+, respectively, into a common molecular scaffold. The platform also contains three amino groups which can potentiate targeted dual-modality imaging of PET/MRI or SPECT/MRI (PET: positron emission tomography; SPECT: single photon emission computed tomography; MRI: magnetic resonance imaging) when further functionalized by targeting vectors of interest. To validate this design concept, a bimetallic complex was synthesized with six peripheral Gd-DOTA units and one Ga-NOTA core at the center, whose ion T1 relaxivity per gadolinium atom was measured to be 15.99 mM–1 s–1 at 20 MHz. Further, the bimetallic agent demonstrated its anticipated in vivo stability, tissue distribution, and pharmacokinetic profile when labeled with 67Ga. When conjugated with a model targeting peptide sequence, the trivalent construct was able to visualize tumors in a mouse xenograft model by both PET and MRI via a single dose injection. PMID:25615011

A feature-based developmental model of the infant brain in structural MRI.

PubMed

Toews, Matthew; Wells, William M; Zöllei, Lilla

2012-01-01

In this paper, anatomical development is modeled as a collection of distinctive image patterns localized in space and time. A Bayesian posterior probability is defined over a random variable of subject age, conditioned on data in the form of scale-invariant image features. The model is automatically learned from a large set of images exhibiting significant variation, used to discover anatomical structure related to age and development, and fit to new images to predict age. The model is applied to a set of 230 infant structural MRIs of 92 subjects acquired at multiple sites over an age range of 8-590 days. Experiments demonstrate that the model can be used to identify age-related anatomical structure, and to predict the age of new subjects with an average error of 72 days.

Resting State Functional Connectivity in Mild Traumatic Brain Injury at the Acute Stage: Independent Component and Seed-Based Analyses

PubMed Central

Iraji, Armin; Benson, Randall R.; Welch, Robert D.; O'Neil, Brian J.; Woodard, John L.; Imran Ayaz, Syed; Kulek, Andrew; Mika, Valerie; Medado, Patrick; Soltanian-Zadeh, Hamid; Liu, Tianming; Haacke, E. Mark

2015-01-01

Abstract Mild traumatic brain injury (mTBI) accounts for more than 1 million emergency visits each year. Most of the injured stay in the emergency department for a few hours and are discharged home without a specific follow-up plan because of their negative clinical structural imaging. Advanced magnetic resonance imaging (MRI), particularly functional MRI (fMRI), has been reported as being sensitive to functional disturbances after brain injury. In this study, a cohort of 12 patients with mTBI were prospectively recruited from the emergency department of our local Level-1 trauma center for an advanced MRI scan at the acute stage. Sixteen age- and sex-matched controls were also recruited for comparison. Both group-based and individual-based independent component analysis of resting-state fMRI (rsfMRI) demonstrated reduced functional connectivity in both posterior cingulate cortex (PCC) and precuneus regions in comparison with controls, which is part of the default mode network (DMN). Further seed-based analysis confirmed reduced functional connectivity in these two regions and also demonstrated increased connectivity between these regions and other regions of the brain in mTBI. Seed-based analysis using the thalamus, hippocampus, and amygdala regions further demonstrated increased functional connectivity between these regions and other regions of the brain, particularly in the frontal lobe, in mTBI. Our data demonstrate alterations of multiple brain networks at the resting state, particularly increased functional connectivity in the frontal lobe, in response to brain concussion at the acute stage. Resting-state functional connectivity of the DMN could serve as a potential biomarker for improved detection of mTBI in the acute setting. PMID:25285363

Machine learning in a graph framework for subcortical segmentation

NASA Astrophysics Data System (ADS)

Guo, Zhihui; Kashyap, Satyananda; Sonka, Milan; Oguz, Ipek

2017-02-01

Automated and reliable segmentation of subcortical structures from human brain magnetic resonance images is of great importance for volumetric and shape analyses in quantitative neuroimaging studies. However, poor boundary contrast and variable shape of these structures make the automated segmentation a tough task. We propose a 3D graph-based machine learning method, called LOGISMOS-RF, to segment the caudate and the putamen from brain MRI scans in a robust and accurate way. An atlas-based tissue classification and bias-field correction method is applied to the images to generate an initial segmentation for each structure. Then a 3D graph framework is utilized to construct a geometric graph for each initial segmentation. A locally trained random forest classifier is used to assign a cost to each graph node. The max-flow algorithm is applied to solve the segmentation problem. Evaluation was performed on a dataset of T1-weighted MRI's of 62 subjects, with 42 images used for training and 20 images for testing. For comparison, FreeSurfer, FSL and BRAINSCut approaches were also evaluated using the same dataset. Dice overlap coefficients and surface-to-surfaces distances between the automated segmentation and expert manual segmentations indicate the results of our method are statistically significantly more accurate than the three other methods, for both the caudate (Dice: 0.89 +/- 0.03) and the putamen (0.89 +/- 0.03).

Development of a brain MRI-based hidden Markov model for dementia recognition.

PubMed

Chen, Ying; Pham, Tuan D

2013-01-01

Dementia is an age-related cognitive decline which is indicated by an early degeneration of cortical and sub-cortical structures. Characterizing those morphological changes can help to understand the disease development and contribute to disease early prediction and prevention. But modeling that can best capture brain structural variability and can be valid in both disease classification and interpretation is extremely challenging. The current study aimed to establish a computational approach for modeling the magnetic resonance imaging (MRI)-based structural complexity of the brain using the framework of hidden Markov models (HMMs) for dementia recognition. Regularity dimension and semi-variogram were used to extract structural features of the brains, and vector quantization method was applied to convert extracted feature vectors to prototype vectors. The output VQ indices were then utilized to estimate parameters for HMMs. To validate its accuracy and robustness, experiments were carried out on individuals who were characterized as non-demented and mild Alzheimer's diseased. Four HMMs were constructed based on the cohort of non-demented young, middle-aged, elder and demented elder subjects separately. Classification was carried out using a data set including both non-demented and demented individuals with a wide age range. The proposed HMMs have succeeded in recognition of individual who has mild Alzheimer's disease and achieved a better classification accuracy compared to other related works using different classifiers. Results have shown the ability of the proposed modeling for recognition of early dementia. The findings from this research will allow individual classification to support the early diagnosis and prediction of dementia. By using the brain MRI-based HMMs developed in our proposed research, it will be more efficient, robust and can be easily used by clinicians as a computer-aid tool for validating imaging bio-markers for early prediction of dementia.

Atlas-based head modeling and spatial normalization for high-density diffuse optical tomography: in vivo validation against fMRI.

PubMed

Ferradal, Silvina L; Eggebrecht, Adam T; Hassanpour, Mahlega; Snyder, Abraham Z; Culver, Joseph P

2014-01-15

Diffuse optical imaging (DOI) is increasingly becoming a valuable neuroimaging tool when fMRI is precluded. Recent developments in high-density diffuse optical tomography (HD-DOT) overcome previous limitations of sparse DOI systems, providing improved image quality and brain specificity. These improvements in instrumentation prompt the need for advancements in both i) realistic forward light modeling for accurate HD-DOT image reconstruction, and ii) spatial normalization for voxel-wise comparisons across subjects. Individualized forward light models derived from subject-specific anatomical images provide the optimal inverse solutions, but such modeling may not be feasible in all situations. In the absence of subject-specific anatomical images, atlas-based head models registered to the subject's head using cranial fiducials provide an alternative solution. In addition, a standard atlas is attractive because it defines a common coordinate space in which to compare results across subjects. The question therefore arises as to whether atlas-based forward light modeling ensures adequate HD-DOT image quality at the individual and group level. Herein, we demonstrate the feasibility of using atlas-based forward light modeling and spatial normalization methods. Both techniques are validated using subject-matched HD-DOT and fMRI data sets for visual evoked responses measured in five healthy adult subjects. HD-DOT reconstructions obtained with the registered atlas anatomy (i.e. atlas DOT) had an average localization error of 2.7mm relative to reconstructions obtained with the subject-specific anatomical images (i.e. subject-MRI DOT), and 6.6mm relative to fMRI data. At the group level, the localization error of atlas DOT reconstruction was 4.2mm relative to subject-MRI DOT reconstruction, and 6.1mm relative to fMRI. These results show that atlas-based image reconstruction provides a viable approach to individual head modeling for HD-DOT when anatomical imaging is not available. Copyright © 2013. Published by Elsevier Inc.

Design of a novel class of protein-based magnetic resonance imaging contrast agents for the molecular imaging of cancer biomarkers

PubMed Central

Xue, Shenghui; Qiao, Jingjuan; Pu, Fan; Cameron, Mathew; Yang, Jenny J.

2014-01-01

Magnetic resonance imaging (MRI) of disease biomarkers, especially cancer biomarkers, could potentially improve our understanding of the disease and drug activity during preclinical and clinical drug treatment and patient stratification. MRI contrast agents with high relaxivity and targeting capability to tumor biomarkers are highly required. Extensive work has been done to develop MRI contrast agents. However, only a few limited literatures report that protein residues can function as ligands to bind Gd3+ with high binding affinity, selectivity, and relaxivity. In this paper, we focus on reporting our current progress on designing a novel class of protein-based Gd3+ MRI contrast agents (ProCAs) equipped with several desirable capabilities for in vivo application of MRI of tumor biomarkers. We will first discuss our strategy for improving the relaxivity by a novel protein-based design. We then discuss the effect of increased relaxivity of ProCAs on improving the detection limits for MRI contrast agent, especially for in vivo application. We will further report our efforts to improve in vivo imaging capability and our achievement in molecular imaging of cancer biomarkers with potential preclinical and clinical applications. PMID:23335551

DWI-based neural fingerprinting technology: a preliminary study on stroke analysis.

PubMed

Ye, Chenfei; Ma, Heather Ting; Wu, Jun; Yang, Pengfei; Chen, Xuhui; Yang, Zhengyi; Ma, Jingbo

2014-01-01

Stroke is a common neural disorder in neurology clinics. Magnetic resonance imaging (MRI) has become an important tool to assess the neural physiological changes under stroke, such as diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI). Quantitative analysis of MRI images would help medical doctors to localize the stroke area in the diagnosis in terms of structural information and physiological characterization. However, current quantitative approaches can only provide localization of the disorder rather than measure physiological variation of subtypes of ischemic stroke. In the current study, we hypothesize that each kind of neural disorder would have its unique physiological characteristics, which could be reflected by DWI images on different gradients. Based on this hypothesis, a DWI-based neural fingerprinting technology was proposed to classify subtypes of ischemic stroke. The neural fingerprint was constructed by the signal intensity of the region of interest (ROI) on the DWI images under different gradients. The fingerprint derived from the manually drawn ROI could classify the subtypes with accuracy 100%. However, the classification accuracy was worse when using semiautomatic and automatic method in ROI segmentation. The preliminary results showed promising potential of DWI-based neural fingerprinting technology in stroke subtype classification. Further studies will be carried out for enhancing the fingerprinting accuracy and its application in other clinical practices.

Prediction of activation patterns preceding hallucinations in patients with schizophrenia using machine learning with structured sparsity.

PubMed

de Pierrefeu, Amicie; Fovet, Thomas; Hadj-Selem, Fouad; Löfstedt, Tommy; Ciuciu, Philippe; Lefebvre, Stephanie; Thomas, Pierre; Lopes, Renaud; Jardri, Renaud; Duchesnay, Edouard

2018-04-01

Despite significant progress in the field, the detection of fMRI signal changes during hallucinatory events remains difficult and time-consuming. This article first proposes a machine-learning algorithm to automatically identify resting-state fMRI periods that precede hallucinations versus periods that do not. When applied to whole-brain fMRI data, state-of-the-art classification methods, such as support vector machines (SVM), yield dense solutions that are difficult to interpret. We proposed to extend the existing sparse classification methods by taking the spatial structure of brain images into account with structured sparsity using the total variation penalty. Based on this approach, we obtained reliable classifying performances associated with interpretable predictive patterns, composed of two clearly identifiable clusters in speech-related brain regions. The variation in transition-to-hallucination functional patterns not only from one patient to another but also from one occurrence to the next (e.g., also depending on the sensory modalities involved) appeared to be the major difficulty when developing effective classifiers. Consequently, second, this article aimed to characterize the variability within the prehallucination patterns using an extension of principal component analysis with spatial constraints. The principal components (PCs) and the associated basis patterns shed light on the intrinsic structures of the variability present in the dataset. Such results are promising in the scope of innovative fMRI-guided therapy for drug-resistant hallucinations, such as fMRI-based neurofeedback. © 2018 Wiley Periodicals, Inc.

Machine learning classification with confidence: application of transductive conformal predictors to MRI-based diagnostic and prognostic markers in depression.

PubMed

Nouretdinov, Ilia; Costafreda, Sergi G; Gammerman, Alexander; Chervonenkis, Alexey; Vovk, Vladimir; Vapnik, Vladimir; Fu, Cynthia H Y

2011-05-15

There is rapidly accumulating evidence that the application of machine learning classification to neuroimaging measurements may be valuable for the development of diagnostic and prognostic prediction tools in psychiatry. However, current methods do not produce a measure of the reliability of the predictions. Knowing the risk of the error associated with a given prediction is essential for the development of neuroimaging-based clinical tools. We propose a general probabilistic classification method to produce measures of confidence for magnetic resonance imaging (MRI) data. We describe the application of transductive conformal predictor (TCP) to MRI images. TCP generates the most likely prediction and a valid measure of confidence, as well as the set of all possible predictions for a given confidence level. We present the theoretical motivation for TCP, and we have applied TCP to structural and functional MRI data in patients and healthy controls to investigate diagnostic and prognostic prediction in depression. We verify that TCP predictions are as accurate as those obtained with more standard machine learning methods, such as support vector machine, while providing the additional benefit of a valid measure of confidence for each prediction. Copyright © 2010 Elsevier Inc. All rights reserved.

The VALiDATe29 MRI Based Multi-Channel Atlas of the Squirrel Monkey Brain.

PubMed

Schilling, Kurt G; Gao, Yurui; Stepniewska, Iwona; Wu, Tung-Lin; Wang, Feng; Landman, Bennett A; Gore, John C; Chen, Li Min; Anderson, Adam W

2017-10-01

We describe the development of the first digital atlas of the normal squirrel monkey brain and present the resulting product, VALiDATe29. The VALiDATe29 atlas is based on multiple types of magnetic resonance imaging (MRI) contrast acquired on 29 squirrel monkeys, and is created using unbiased, nonlinear registration techniques, resulting in a population-averaged stereotaxic coordinate system. The atlas consists of multiple anatomical templates (proton density, T1, and T2* weighted), diffusion MRI templates (fractional anisotropy and mean diffusivity), and ex vivo templates (fractional anisotropy and a structural MRI). In addition, the templates are combined with histologically defined cortical labels, and diffusion tractography defined white matter labels. The combination of intensity templates and image segmentations make this atlas suitable for the fundamental atlas applications of spatial normalization and label propagation. Together, this atlas facilitates 3D anatomical localization and region of interest delineation, and enables comparisons of experimental data across different subjects or across different experimental conditions. This article describes the atlas creation and its contents, and demonstrates the use of the VALiDATe29 atlas in typical applications. The atlas is freely available to the scientific community.

MEG-BIDS, the brain imaging data structure extended to magnetoencephalography

PubMed Central

Niso, Guiomar; Gorgolewski, Krzysztof J.; Bock, Elizabeth; Brooks, Teon L.; Flandin, Guillaume; Gramfort, Alexandre; Henson, Richard N.; Jas, Mainak; Litvak, Vladimir; T. Moreau, Jeremy; Oostenveld, Robert; Schoffelen, Jan-Mathijs; Tadel, Francois; Wexler, Joseph; Baillet, Sylvain

2018-01-01

We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG measures brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS was a solution to organise magnetic resonance imaging (MRI) data. The nature and acquisition parameters of MRI and MEG data are strongly dissimilar. Although there is no standard data format for MEG, we propose MEG-BIDS as a principled solution to store, organise, process and share the multidimensional data volumes produced by the modality. The standard also includes well-defined metadata, to facilitate future data harmonisation and sharing efforts. This responds to unmet needs from the multimodal neuroimaging community and paves the way to further integration of other techniques in electrophysiology. MEG-BIDS builds on MRI-BIDS, extending BIDS to a multimodal data structure. We feature several data-analytics software that have adopted MEG-BIDS, and a diverse sample of open MEG-BIDS data resources available to everyone. PMID:29917016

MEG-BIDS, the brain imaging data structure extended to magnetoencephalography.

PubMed

Niso, Guiomar; Gorgolewski, Krzysztof J; Bock, Elizabeth; Brooks, Teon L; Flandin, Guillaume; Gramfort, Alexandre; Henson, Richard N; Jas, Mainak; Litvak, Vladimir; T Moreau, Jeremy; Oostenveld, Robert; Schoffelen, Jan-Mathijs; Tadel, Francois; Wexler, Joseph; Baillet, Sylvain

2018-06-19

We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG measures brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS was a solution to organise magnetic resonance imaging (MRI) data. The nature and acquisition parameters of MRI and MEG data are strongly dissimilar. Although there is no standard data format for MEG, we propose MEG-BIDS as a principled solution to store, organise, process and share the multidimensional data volumes produced by the modality. The standard also includes well-defined metadata, to facilitate future data harmonisation and sharing efforts. This responds to unmet needs from the multimodal neuroimaging community and paves the way to further integration of other techniques in electrophysiology. MEG-BIDS builds on MRI-BIDS, extending BIDS to a multimodal data structure. We feature several data-analytics software that have adopted MEG-BIDS, and a diverse sample of open MEG-BIDS data resources available to everyone.

Structural and Functional Magnetic Resonance Imaging of the Cerebellum: Considerations for Assessing Cerebellar Ataxias.

PubMed

Deistung, Andreas; Stefanescu, Maria R; Ernst, Thomas M; Schlamann, Marc; Ladd, Mark E; Reichenbach, Jürgen R; Timmann, Dagmar

2016-02-01

Magnetic resonance imaging (MRI) of the brain is of high interest for diagnosing and understanding degenerative ataxias. Here, we present state-of-the-art MRI methods to characterize structural alterations of the cerebellum and introduce initial experiments to show abnormalities in the cerebellar nuclei. Clinically, T1-weighted MR images are used to assess atrophy of the cerebellar cortex, the brainstem, and the spinal cord, whereas T2-weighted and PD-weighted images are typically employed to depict potential white matter lesions that may be associated with certain types of ataxias. More recently, attention has also focused on the characterization of the cerebellar nuclei, which are discernible on spatially highly resolved iron-sensitive MR images due to their relatively high iron content, including T2 (*)-weighted images, susceptibility-weighted images (SWI), effective transverse relaxation rate (R2 (*)) maps, and quantitative susceptibility maps (QSM). Among these iron-sensitive techniques, QSM reveals the best contrast between cerebellar nuclei and their surroundings. In particular, the gyrification of the dentate nuclei is prominently depicted, even at the clinically widely available field strength of 3 T. The linear relationship between magnetic susceptibility and local iron content allows for determination of iron deposition in cerebellar nuclei non-invasively. The increased signal-to-noise ratio of ultrahigh-field MRI (B0 ≥ 7 T) and advances in spatial normalization methods enable functional MRI (fMRI) at the level of the cerebellar cortex and cerebellar nuclei. Data from initial fMRI studies are presented in three common forms of hereditary ataxias (Friedreich's ataxia, spinocerebellar ataxia type 3, and spinocerebellar ataxia type 6). Characteristic changes in the fMRI signal are discussed in the light of histopathological data and current knowledge of the underlying physiology of the fMRI signal in the cerebellum.

Multifractal analysis of white matter structural changes on 3D magnetic resonance imaging between normal aging and early Alzheimer’s disease

NASA Astrophysics Data System (ADS)

Ni, Huang-Jing; Zhou, Lu-Ping; Zeng, Peng; Huang, Xiao-Lin; Liu, Hong-Xing; Ning, Xin-Bao

2015-07-01

Applications of multifractal analysis to white matter structure changes on magnetic resonance imaging (MRI) have recently received increasing attentions. Although some progresses have been made, there is no evident study on applying multifractal analysis to evaluate the white matter structural changes on MRI for Alzheimer’s disease (AD) research. In this paper, to explore multifractal analysis of white matter structural changes on 3D MRI volumes between normal aging and early AD, we not only extend the traditional box-counting multifractal analysis (BCMA) into the 3D case, but also propose a modified integer ratio based BCMA (IRBCMA) algorithm to compensate for the rigid division rule in BCMA. We verify multifractal characteristics in 3D white matter MRI volumes. In addition to the previously well studied multifractal feature, Δα, we also demonstrated Δf as an alternative and effective multifractal feature to distinguish NC from AD subjects. Both Δα and Δf are found to have strong positive correlation with the clinical MMSE scores with statistical significance. Moreover, the proposed IRBCMA can be an alternative and more accurate algorithm for 3D volume analysis. Our findings highlight the potential usefulness of multifractal analysis, which may contribute to clarify some aspects of the etiology of AD through detection of structural changes in white matter. Project supported by the National Natural Science Foundation of China (Grant No. 61271079), the Vice Chancellor Research Grant in University of Wollongong, and the Priority Academic Program Development of Jiangsu Higher Education Institutions, China.

Affibody Modified and Radiolabeled Gold-Iron Oxide Hetero-nanostructures for Tumor PET, Optical and MR Imaging

PubMed Central

Yang, Meng; Cheng, Kai; Qi, Shibo; Liu, Hongguang; Jiang, Yuxin; Jiang, Han; Li, Jinbo; Chen, Kai; Zhang, Huimao; Cheng, Zhen

2013-01-01

A highly monodispersed hetero-nanostructure with two different functional nanomaterials (gold (Au) and iron oxide (Fe3O4, IO)) within one structure was successfully developed as Affibody based trimodality nanoprobe (positron emission tomography, PET; optical imaging; and magnetic resonance imaging, MRI) for imaging of epidermal growth factor receptor (EGFR) positive tumors. Unlike other regular nanostructures with a single component, the Au-IO hetero-nanostructures (Au-IONPs) with unique chemical and physical properties have capability to combine several imaging modalities together to provide complementary information. The IO component within hetero-nanostructures serve as a T2 reporter for MRI; and gold component serve as both optical and PET reporters. Moreover, such hetero-nanoprobes could provide a robust nano-platform for surface-specific modification with both targeting molecules (anti-EGFR Affibody protein) and PET imaging reporters (radiometal 64Cu chelators) in highly efficient and reliable manner. In vitro and in vivo study showed that the resultant nanoprobe provided high specificity, sensitivity, and excellent tumor contrast for both PET and MRI imaging in the human EGFR-expressing cells and tumors. Our study data also highlighted the EGFR targeting efficiency of hetero-nanoparticles and the feasibility for their further theranostic applications. PMID:23343632

Magnetic resonance imaging, computed tomography, and gross anatomy of the canine tarsus.

PubMed

Deruddere, Kirsten J; Milne, Marjorie E; Wilson, Kane M; Snelling, Sam R

2014-11-01

To describe the normal anatomy of the soft tissues of the canine tarsus as identified on computed tomography (CT) and magnetic resonance imaging (MRI) and to evaluate specific MRI sequences and planes for observing structures of diagnostic interest. Prospective descriptive study. Canine cadavers (n = 3). A frozen cadaver pelvic limb was used to trial multiple MRI sequences using a 1.5 T superconducting magnet and preferred sequences were selected. Radiographs of 6 canine cadaver pelvic limbs confirmed the tarsi were radiographically normal. A 16-slice CT scanner was used to obtain 1 mm contiguous slices through the tarsi. T1-weighted, proton density with fat suppression (PD FS) and T2-weighted MRI sequences were obtained in the sagittal plane, T1-weighted, and PD FS sequences in the dorsal plane and PD FS sequences in the transverse plane. The limbs were frozen for one month and sliced into 4-5 mm thick frozen sections. Anatomic sections were photographed and visually correlated to CT and MR images. Most soft tissue structures were easiest to identify on the transverse MRI sections with cross reference to either the sagittal or dorsal plane. Bony structures were easily identified on all CT, MR, and gross sections. The anatomy of the canine tarsus can be readily identified on MR imaging. © Copyright 2014 by The American College of Veterinary Surgeons.

[Anatomy of the skull base and the cranial nerves in slice imaging].

PubMed

Bink, A; Berkefeld, J; Zanella, F

2009-07-01

Computed tomography (CT) and magnetic resonance imaging (MRI) are suitable methods for examination of the skull base. Whereas CT is used to evaluate mainly bone destruction e.g. for planning surgical therapy, MRI is used to show pathologies in the soft tissue and bone invasion. High resolution and thin slice thickness are indispensible for both modalities of skull base imaging. Detailed anatomical knowledge is necessary even for correct planning of the examination procedures. This knowledge is a requirement to be able to recognize and interpret pathologies. MRI is the method of choice for examining the cranial nerves. The total path of a cranial nerve can be visualized by choosing different sequences taking into account the tissue surrounding this cranial nerve. This article summarizes examination methods of the skull base in CT and MRI, gives a detailed description of the anatomy and illustrates it with image examples.

Compressed Sensing SEMAC: 8-fold Accelerated High Resolution Metal Artifact Reduction MRI of Cobalt-Chromium Knee Arthroplasty Implants.

PubMed

Fritz, Jan; Ahlawat, Shivani; Demehri, Shadpour; Thawait, Gaurav K; Raithel, Esther; Gilson, Wesley D; Nittka, Mathias

2016-10-01

The aim of this study was to prospectively test the hypothesis that a compressed sensing-based slice encoding for metal artifact correction (SEMAC) turbo spin echo (TSE) pulse sequence prototype facilitates high-resolution metal artifact reduction magnetic resonance imaging (MRI) of cobalt-chromium knee arthroplasty implants within acquisition times of less than 5 minutes, thereby yielding better image quality than high-bandwidth (BW) TSE of similar length and similar image quality than lengthier SEMAC standard of reference pulse sequences. This prospective study was approved by our institutional review board. Twenty asymptomatic subjects (12 men, 8 women; mean age, 56 years; age range, 44-82 years) with total knee arthroplasty implants underwent MRI of the knee using a commercially available, clinical 1.5 T MRI system. Two compressed sensing-accelerated SEMAC prototype pulse sequences with 8-fold undersampling and acquisition times of approximately 5 minutes each were compared with commercially available high-BW and SEMAC pulse sequences with acquisition times of approximately 5 minutes and 11 minutes, respectively. For each pulse sequence type, sagittal intermediate-weighted (TR, 3750-4120 milliseconds; TE, 26-28 milliseconds; voxel size, 0.5 × 0.5 × 3 mm) and short tau inversion recovery (TR, 4010 milliseconds; TE, 5.2-7.5 milliseconds; voxel size, 0.8 × 0.8 × 4 mm) were acquired. Outcome variables included image quality, display of the bone-implant interfaces and pertinent knee structures, artifact size, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Statistical analysis included Friedman, repeated measures analysis of variances, and Cohen weighted k tests. Bonferroni-corrected P values of 0.005 and less were considered statistically significant. Image quality, bone-implant interfaces, anatomic structures, artifact size, SNR, and CNR parameters were statistically similar between the compressed sensing-accelerated SEMAC prototype and SEMAC commercial pulse sequences. There was mild blur on images of both SEMAC sequences when compared with high-BW images (P < 0.001), which however did not impair the assessment of knee structures. Metal artifact reduction and visibility of central knee structures and bone-implant interfaces were good to very good and significantly better on both types of SEMAC than on high-BW images (P < 0.004). All 3 pulse sequences showed peripheral structures similarly well. The implant artifact size was 46% to 51% larger on high-BW images when compared with both types of SEMAC images (P < 0.0001). Signal-to-noise ratios and CNRs of fat tissue, tendon tissue, muscle tissue, and fluid were statistically similar on intermediate-weighted MR images of all 3 pulse sequence types. On short tau inversion recovery images, the SNRs of tendon tissue and the CNRs of fat and fluid, fluid and muscle, as well as fluid and tendon were significantly higher on SEMAC and compressed sensing SEMAC images (P < 0.005, respectively). We accept the hypothesis that prospective compressed sensing acceleration of SEMAC is feasible for high-quality metal artifact reduction MRI of cobalt-chromium knee arthroplasty implants in less than 5 minutes and yields better quality than high-BW TSE and similarly high quality than lengthier SEMAC pulse sequences.

Fast implementation for compressive recovery of highly accelerated cardiac cine MRI using the balanced sparse model.

PubMed

Ting, Samuel T; Ahmad, Rizwan; Jin, Ning; Craft, Jason; Serafim da Silveira, Juliana; Xue, Hui; Simonetti, Orlando P

2017-04-01

Sparsity-promoting regularizers can enable stable recovery of highly undersampled magnetic resonance imaging (MRI), promising to improve the clinical utility of challenging applications. However, lengthy computation time limits the clinical use of these methods, especially for dynamic MRI with its large corpus of spatiotemporal data. Here, we present a holistic framework that utilizes the balanced sparse model for compressive sensing and parallel computing to reduce the computation time of cardiac MRI recovery methods. We propose a fast, iterative soft-thresholding method to solve the resulting ℓ1-regularized least squares problem. In addition, our approach utilizes a parallel computing environment that is fully integrated with the MRI acquisition software. The methodology is applied to two formulations of the multichannel MRI problem: image-based recovery and k-space-based recovery. Using measured MRI data, we show that, for a 224 × 144 image series with 48 frames, the proposed k-space-based approach achieves a mean reconstruction time of 2.35 min, a 24-fold improvement compared a reconstruction time of 55.5 min for the nonlinear conjugate gradient method, and the proposed image-based approach achieves a mean reconstruction time of 13.8 s. Our approach can be utilized to achieve fast reconstruction of large MRI datasets, thereby increasing the clinical utility of reconstruction techniques based on compressed sensing. Magn Reson Med 77:1505-1515, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

The OMERACT Rheumatoid Arthritis Magnetic Resonance Imaging (MRI) Scoring System: Updated Recommendations by the OMERACT MRI in Arthritis Working Group.

PubMed

Østergaard, Mikkel; Peterfy, Charles G; Bird, Paul; Gandjbakhch, Frédérique; Glinatsi, Daniel; Eshed, Iris; Haavardsholm, Espen A; Lillegraven, Siri; Bøyesen, Pernille; Ejbjerg, Bo; Foltz, Violaine; Emery, Paul; Genant, Harry K; Conaghan, Philip G

2017-11-01

The Outcome Measures in Rheumatology (OMERACT) Rheumatoid Arthritis (RA) Magnetic Resonance Imaging (MRI) scoring system (RAMRIS), evaluating bone erosion, bone marrow edema/osteitis, and synovitis, was introduced in 2002, and is now the standard method of objectively quantifying inflammation and damage by MRI in RA trials. The objective of this paper was to identify subsequent advances and based on them, to provide updated recommendations for the RAMRIS. MRI studies relevant for RAMRIS and technical and scientific advances were analyzed by the OMERACT MRI in Arthritis Working Group, which used these data to provide updated considerations on image acquisition, RAMRIS definitions, and scoring systems for the original and new RA pathologies. Further, a research agenda was outlined. Since 2002, longitudinal studies and clinical trials have documented RAMRIS variables to have face, construct, and criterion validity; high reliability and sensitivity to change; and the ability to discriminate between therapies. This has enabled RAMRIS to demonstrate inhibition of structural damage progression with fewer patients and shorter followup times than has been possible with conventional radiography. Technical improvements, including higher field strengths and improved pulse sequences, allow higher image resolution and contrast-to-noise ratio. These have facilitated development and validation of scoring methods of new pathologies: joint space narrowing and tenosynovitis. These have high reproducibility and moderate sensitivity to change, and can be added to RAMRIS. Combined scores of inflammation or joint damage may increase sensitivity to change and discriminative power. However, this requires further research. Updated 2016 RAMRIS recommendations and a research agenda were developed.

Neuroimaging basis in the conversion of aMCI patients with APOE-ε4 to AD: study protocol of a prospective diagnostic trial.

PubMed

Chen, Guan-Qun; Sheng, Can; Li, Yu-Xia; Yu, Yang; Wang, Xiao-Ni; Sun, Yu; Li, Hong-Yan; Li, Xuan-Yu; Xie, Yun-Yan; Han, Ying

2016-05-12

The ε4 allele of the Apolipoprotein E gene (APOE-ε4) is a potent genetic risk factor for sporadic Alzheimer's disease (AD). Amnestic mild cognitive impairment (aMCI) is an intermediate state between normal cognitive aging and dementia, which is easy to convert to AD dementia. It is an urgent problem in the field of cognitive neuroscience to reveal the conversion of aMCI-ε4 to AD. Based on our preliminary work, we will study the neuroimaging features in the special group of aMCI-ε4 with multi-modality magnetic resonance imaging (structural MRI, resting state-fMRI and diffusion tensor imaging) longitudinally. In this study, 200 right-handed subjects who are diagnosed as aMCI with APOE-ε4 will be recruited at the memory clinic of the Neurology Department, XuanWu Hospital, Capital Medical University, Beijing, China. All subjects will undergo the neuroimaging and neuropsychological evaluation at a 1 year-interval for 3 years. The primary outcome measures are 1) Microstructural alterations revealed with multimodal MRI scans including structure MRI (sMRI), resting state functional MRI (rs-fMRI), diffusion tensor imaging (DTI); 2) neuropsychological evaluation, including the World Health Organization-University of California-LosAngeles Auditory Verbal Learning Test (WHO-UCLA AVLT), Addenbrook's cognitive examination-revised (ACE-R), mini-mental state examination (MMSE), Montreal Cognitive Assessment (MoCA), Clinical Dementia Rating scale (CDR). This study is to find out the neuroimaging biomarker and the changing laws of the marker during the progress of aMCI-ε4 to AD, and the final purpose is to provide scientific evidence for new prevention, diagnosis and treatment of AD. This study has been registered to ClinicalTrials.gov (NCT02225964, https://www.clinicaltrials.gov/ ) in August 24, 2014.

1.5 T augmented reality navigated interventional MRI: paravertebral sympathetic plexus injections

PubMed Central

Marker, David R.; U-Thainual, Paweena; Ungi, Tamas; Flammang, Aaron J.; Fichtinger, Gabor; Iordachita, Iulian I.; Carrino, John A.; Fritz, Jan

2017-01-01

PURPOSE The high contrast resolution and absent ionizing radiation of interventional magnetic resonance imaging (MRI) can be advantageous for paravertebral sympathetic nerve plexus injections. We assessed the feasibility and technical performance of MRI-guided paravertebral sympathetic injections utilizing augmented reality navigation and 1.5 T MRI scanner. METHODS A total of 23 bilateral injections of the thoracic (8/23, 35%), lumbar (8/23, 35%), and hypogastric (7/23, 30%) paravertebral sympathetic plexus were prospectively planned in twelve human cadavers using a 1.5 Tesla (T) MRI scanner and augmented reality navigation system. MRI-conditional needles were used. Gadolinium-DTPA-enhanced saline was injected. Outcome variables included the number of control magnetic resonance images, target error of the needle tip, punctures of critical nontarget structures, distribution of the injected fluid, and procedure length. RESULTS Augmented-reality navigated MRI guidance at 1.5 T provided detailed anatomical visualization for successful targeting of the paravertebral space, needle placement, and perineural paravertebral injections in 46 of 46 targets (100%). A mean of 2 images (range, 1–5 images) were required to control needle placement. Changes of the needle trajectory occurred in 9 of 46 targets (20%) and changes of needle advancement occurred in 6 of 46 targets (13%), which were statistically not related to spinal regions (P = 0.728 and P = 0.86, respectively) and cadaver sizes (P = 0.893 and P = 0.859, respectively). The mean error of the needle tip was 3.9±1.7 mm. There were no punctures of critical nontarget structures. The mean procedure length was 33±12 min. CONCLUSION 1.5 T augmented reality-navigated interventional MRI can provide accurate imaging guidance for perineural injections of the thoracic, lumbar, and hypogastric sympathetic plexus. PMID:28420598

1.5 T augmented reality navigated interventional MRI: paravertebral sympathetic plexus injections.

PubMed

Marker, David R; U Thainual, Paweena; Ungi, Tamas; Flammang, Aaron J; Fichtinger, Gabor; Iordachita, Iulian I; Carrino, John A; Fritz, Jan

2017-01-01

The high contrast resolution and absent ionizing radiation of interventional magnetic resonance imaging (MRI) can be advantageous for paravertebral sympathetic nerve plexus injections. We assessed the feasibility and technical performance of MRI-guided paravertebral sympathetic injections utilizing augmented reality navigation and 1.5 T MRI scanner. A total of 23 bilateral injections of the thoracic (8/23, 35%), lumbar (8/23, 35%), and hypogastric (7/23, 30%) paravertebral sympathetic plexus were prospectively planned in twelve human cadavers using a 1.5 Tesla (T) MRI scanner and augmented reality navigation system. MRI-conditional needles were used. Gadolinium-DTPA-enhanced saline was injected. Outcome variables included the number of control magnetic resonance images, target error of the needle tip, punctures of critical nontarget structures, distribution of the injected fluid, and procedure length. Augmented-reality navigated MRI guidance at 1.5 T provided detailed anatomical visualization for successful targeting of the paravertebral space, needle placement, and perineural paravertebral injections in 46 of 46 targets (100%). A mean of 2 images (range, 1-5 images) were required to control needle placement. Changes of the needle trajectory occurred in 9 of 46 targets (20%) and changes of needle advancement occurred in 6 of 46 targets (13%), which were statistically not related to spinal regions (P = 0.728 and P = 0.86, respectively) and cadaver sizes (P = 0.893 and P = 0.859, respectively). The mean error of the needle tip was 3.9±1.7 mm. There were no punctures of critical nontarget structures. The mean procedure length was 33±12 min. 1.5 T augmented reality-navigated interventional MRI can provide accurate imaging guidance for perineural injections of the thoracic, lumbar, and hypogastric sympathetic plexus.

Method for multimodal analysis of independent source differences in schizophrenia: combining gray matter structural and auditory oddball functional data.

PubMed

Calhoun, V D; Adali, T; Giuliani, N R; Pekar, J J; Kiehl, K A; Pearlson, G D

2006-01-01

The acquisition of both structural MRI (sMRI) and functional MRI (fMRI) data for a given study is a very common practice. However, these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform independent component analysis across image modalities, specifically, gray matter images and fMRI activation images as well as a joint histogram visualization technique. Joint independent component analysis (jICA) is used to decompose a matrix with a given row consisting of an fMRI activation image resulting from auditory oddball target stimuli and an sMRI gray matter segmentation image, collected from the same individual. We analyzed data collected on a group of schizophrenia patients and healthy controls using the jICA approach. Spatially independent joint-components are estimated and resulting components were further analyzed only if they showed a significant difference between patients and controls. The main finding was that group differences in bilateral parietal and frontal as well as posterior temporal regions in gray matter were associated with bilateral temporal regions activated by the auditory oddball target stimuli. A finding of less patient gray matter and less hemodynamic activity for target detection in these bilateral anterior temporal lobe regions was consistent with previous work. An unexpected corollary to this finding was that, in the regions showing the largest group differences, gray matter concentrations were larger in patients vs. controls, suggesting that more gray matter may be related to less functional connectivity in the auditory oddball fMRI task. Hum Brain Mapp, 2005. (c) 2005 Wiley-Liss, Inc.

Prostatome: A combined anatomical and disease based MRI atlas of the prostate

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

Rusu, Mirabela; Madabhushi, Anant, E-mail: anant.madabhushi@case.edu; Bloch, B. Nicolas

Purpose: In this work, the authors introduce a novel framework, the anatomically constrained registration (AnCoR) scheme and apply it to create a fused anatomic-disease atlas of the prostate which the authors refer to as the prostatome. The prostatome combines a MRI based anatomic and a histology based disease atlas. Statistical imaging atlases allow for the integration of information across multiple scales and imaging modalities into a single canonical representation, in turn enabling a fused anatomical-disease representation which may facilitate the characterization of disease appearance relative to anatomic structures. While statistical atlases have been extensively developed and studied for the brain,more » approaches that have attempted to combine pathology and imaging data for study of prostate pathology are not extant. This works seeks to address this gap. Methods: The AnCoR framework optimizes a scoring function composed of two surface (prostate and central gland) misalignment measures and one intensity-based similarity term. This ensures the correct mapping of anatomic regions into the atlas, even when regional MRI intensities are inconsistent or highly variable between subjects. The framework allows for creation of an anatomic imaging and a disease atlas, while enabling their fusion into the anatomic imaging-disease atlas. The atlas presented here was constructed using 83 subjects with biopsy confirmed cancer who had pre-operative MRI (collected at two institutions) followed by radical prostatectomy. The imaging atlas results from mapping thein vivo MRI into the canonical space, while the anatomic regions serve as domain constraints. Elastic co-registration MRI and corresponding ex vivo histology provides “ground truth” mapping of cancer extent on in vivo imaging for 23 subjects. Results: AnCoR was evaluated relative to alternative construction strategies that use either MRI intensities or the prostate surface alone for registration. The AnCoR framework yielded a central gland Dice similarity coefficient (DSC) of 90%, and prostate DSC of 88%, while the misalignment of the urethra and verumontanum was found to be 3.45 mm, and 4.73 mm, respectively, which were measured to be significantly smaller compared to the alternative strategies. As might have been anticipated from our limited cohort of biopsy confirmed cancers, the disease atlas showed that most of the tumor extent was limited to the peripheral zone. Moreover, central gland tumors were typically larger in size, possibly because they are only discernible at a much later stage. Conclusions: The authors presented the AnCoR framework to explicitly model anatomic constraints for the construction of a fused anatomic imaging-disease atlas. The framework was applied to constructing a preliminary version of an anatomic-disease atlas of the prostate, the prostatome. The prostatome could facilitate the quantitative characterization of gland morphology and imaging features of prostate cancer. These techniques, may be applied on a large sample size data set to create a fully developed prostatome that could serve as a spatial prior for targeted biopsies by urologists. Additionally, the AnCoR framework could allow for incorporation of complementary imaging and molecular data, thereby enabling their careful correlation for population based radio-omics studies.« less

Mutual interferences and design principles for mechatronic devices in magnetic resonance imaging.

PubMed

Yu, Ningbo; Gassert, Roger; Riener, Robert

2011-07-01

Robotic and mechatronic devices that work compatibly with magnetic resonance imaging (MRI) are applied in diagnostic MRI, image-guided surgery, neurorehabilitation and neuroscience. MRI-compatible mechatronic systems must address the challenges imposed by the scanner's electromagnetic fields. We have developed objective quantitative evaluation criteria for device characteristics needed to formulate design guidelines that ensure MRI-compatibility based on safety, device functionality and image quality. The mutual interferences between an MRI system and mechatronic devices working in its vicinity are modeled and tested. For each interference, the involved components are listed, and a numerical measure for "MRI-compatibility" is proposed. These interferences are categorized into an MRI-compatibility matrix, with each element representing possible interactions between one part of the mechatronic system and one component of the electromagnetic fields. Based on this formulation, design principles for MRI-compatible mechatronic systems are proposed. Furthermore, test methods are developed to examine whether a mechatronic device indeed works without interferences within an MRI system. Finally, the proposed MRI-compatibility criteria and design guidelines have been applied to an actual design process that has been validated by the test procedures. Objective and quantitative MRI-compatibility measures for mechatronic and robotic devices have been established. Applying the proposed design principles, potential problems in safety, device functionality and image quality can be considered in the design phase to ensure that the mechatronic system will fulfill the MRI-compatibility criteria. New guidelines and test procedures for MRI instrument compatibility provide a rational basis for design and evaluation of mechatronic devices in various MRI applications. Designers can apply these criteria and use the tests, so that MRI-compatibility results can accrue to build an experiential database.

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.

Differentiating between bipolar and unipolar depression in functional and structural MRI studies.

PubMed

Han, Kyu-Man; De Berardis, Domenico; Fornaro, Michele; Kim, Yong-Ku

2018-03-28

Distinguishing depression in bipolar disorder (BD) from unipolar depression (UD) solely based on clinical clues is difficult, which has led to the exploration of promising neural markers in neuroimaging measures for discriminating between BD depression and UD. In this article, we review structural and functional magnetic resonance imaging (MRI) studies that directly compare UD and BD depression based on neuroimaging modalities including functional MRI studies on regional brain activation or functional connectivity, structural MRI on gray or white matter morphology, and pattern classification analyses using a machine learning approach. Numerous studies have reported distinct functional and structural alterations in emotion- or reward-processing neural circuits between BD depression and UD. Different activation patterns in neural networks including the amygdala, anterior cingulate cortex (ACC), prefrontal cortex (PFC), and striatum during emotion-, reward-, or cognition-related tasks have been reported between BD and UD. A stronger functional connectivity pattern in BD was pronounced in default mode and in frontoparietal networks and brain regions including the PFC, ACC, parietal and temporal regions, and thalamus compared to UD. Gray matter volume differences in the ACC, hippocampus, amygdala, and dorsolateral prefrontal cortex (DLPFC) have been reported between BD and UD, along with a thinner DLPFC in BD compared to UD. BD showed reduced integrity in the anterior part of the corpus callosum and posterior cingulum compared to UD. Several studies performed pattern classification analysis using structural and functional MRI data to distinguish between UD and BD depression using a supervised machine learning approach, which yielded a moderate level of accuracy in classification. Copyright © 2018 Elsevier Inc. All rights reserved.

Deformable templates guided discriminative models for robust 3D brain MRI segmentation.

PubMed

Liu, Cheng-Yi; Iglesias, Juan Eugenio; Tu, Zhuowen

2013-10-01

Automatically segmenting anatomical structures from 3D brain MRI images is an important task in neuroimaging. One major challenge is to design and learn effective image models accounting for the large variability in anatomy and data acquisition protocols. A deformable template is a type of generative model that attempts to explicitly match an input image with a template (atlas), and thus, they are robust against global intensity changes. On the other hand, discriminative models combine local image features to capture complex image patterns. In this paper, we propose a robust brain image segmentation algorithm that fuses together deformable templates and informative features. It takes advantage of the adaptation capability of the generative model and the classification power of the discriminative models. The proposed algorithm achieves both robustness and efficiency, and can be used to segment brain MRI images with large anatomical variations. We perform an extensive experimental study on four datasets of T1-weighted brain MRI data from different sources (1,082 MRI scans in total) and observe consistent improvement over the state-of-the-art systems.

A digital 3D atlas of the marmoset brain based on multi-modal MRI.

PubMed

Liu, Cirong; Ye, Frank Q; Yen, Cecil Chern-Chyi; Newman, John D; Glen, Daniel; Leopold, David A; Silva, Afonso C

2018-04-01

The common marmoset (Callithrix jacchus) is a New-World monkey of growing interest in neuroscience. Magnetic resonance imaging (MRI) is an essential tool to unveil the anatomical and functional organization of the marmoset brain. To facilitate identification of regions of interest, it is desirable to register MR images to an atlas of the brain. However, currently available atlases of the marmoset brain are mainly based on 2D histological data, which are difficult to apply to 3D imaging techniques. Here, we constructed a 3D digital atlas based on high-resolution ex-vivo MRI images, including magnetization transfer ratio (a T1-like contrast), T2w images, and multi-shell diffusion MRI. Based on the multi-modal MRI images, we manually delineated 54 cortical areas and 16 subcortical regions on one hemisphere of the brain (the core version). The 54 cortical areas were merged into 13 larger cortical regions according to their locations to yield a coarse version of the atlas, and also parcellated into 106 sub-regions using a connectivity-based parcellation method to produce a refined atlas. Finally, we compared the new atlas set with existing histology atlases and demonstrated its applications in connectome studies, and in resting state and stimulus-based fMRI. The atlas set has been integrated into the widely-distributed neuroimaging data analysis software AFNI and SUMA, providing a readily usable multi-modal template space with multi-level anatomical labels (including labels from the Paxinos atlas) that can facilitate various neuroimaging studies of marmosets. Published by Elsevier Inc.

[Recent advances in newborn MRI].

PubMed

Morel, B; Hornoy, P; Husson, B; Bloch, I; Adamsbaum, C

2014-07-01

The accurate morphological exploration of the brain is a major challenge in neonatology that advances in magnetic resonance imaging (MRI) can now provide. MRI is the gold standard if an hypoxic ischemic pathology is suspected in a full term neonate. In prematures, the specific role of MRI remains to be defined, secondary to US in any case. We present a state of the art of hardware and software technical developments in MRI. The increase in magnetic field strength (3 tesla) and the emergence of new MRI sequences provide access to new information. They both have positive and negative consequences on the daily clinical data acquisition use. The semiology of brain imaging in full term newborns and prematures is more extensive and complex and thereby more difficult to interpret. The segmentation of different brain structures in the newborn, even very premature, is now available. It is now possible to dissociate the cortex and basal ganglia from the cerebral white matter, to calculate the volume of anatomical structures, which improves the morphometric quantification and the understanding of the normal and abnormal brain development. MRI is a powerful tool to analyze the neonatal brain. The relevance of the diagnostic contribution requires an adaptation of the parameters of the sequences to acquire and of the image processing methods. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

A comparative study of volumetric breast density estimation in digital mammography and magnetic resonance imaging: results from a high-risk population

NASA Astrophysics Data System (ADS)

Kontos, Despina; Xing, Ye; Bakic, Predrag R.; Conant, Emily F.; Maidment, Andrew D. A.

2010-03-01

We performed a study to compare methods for volumetric breast density estimation in digital mammography (DM) and magnetic resonance imaging (MRI) for a high-risk population of women. DM and MRI images of the unaffected breast from 32 women with recently detected abnormalities and/or previously diagnosed breast cancer (age range 31-78 yrs, mean 50.3 yrs) were retrospectively analyzed. DM images were analyzed using QuantraTM (Hologic Inc). The MRI images were analyzed using a fuzzy-C-means segmentation algorithm on the T1 map. Both methods were compared to Cumulus (Univ. Toronto). Volumetric breast density estimates from DM and MRI are highly correlated (r=0.90, p<=0.001). The correlation between the volumetric and the area-based density measures is lower and depends on the training background of the Cumulus software user (r=0.73-84, p<=0.001). In terms of absolute values, MRI provides the lowest volumetric estimates (mean=14.63%), followed by the DM volumetric (mean=22.72%) and area-based measures (mean=29.35%). The MRI estimates of the fibroglandular volume are statistically significantly lower than the DM estimates for women with very low-density breasts (p<=0.001). We attribute these differences to potential partial volume effects in MRI and differences in the computational aspects of the image analysis methods in MRI and DM. The good correlation between the volumetric and the area-based measures, shown to correlate with breast cancer risk, suggests that both DM and MRI volumetric breast density measures can aid in breast cancer risk assessment. Further work is underway to fully-investigate the association between volumetric breast density measures and breast cancer risk.

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.

Clinical utility for diffusion MRI sequence in emergency and inpatient spine protocols.

PubMed

Hoch, Michael J; Rispoli, Joanne; Bruno, Mary; Wauchope, Mervin; Lui, Yvonne W; Shepherd, Timothy M

Diffusion imaging of the spine has the potential to change clinical management, but is challenging due to the small size of the cord and susceptibility artifacts from adjacent structures. Reduced field-of-view (rFOV) diffusion can improve image quality by decreasing the echo train length. Over the past 2 years, we have acquired a rFOV diffusion sequence for MRI spine protocols on most inpatients and emergency room patients. We provide selected imaging diagnoses to illustrate the utility of including diffusion spine MRI in clinical practice. Our experiences support using diffusion MRI to improve diagnostic certainty and facilitate prompt treatment or clinical management. Copyright © 2017 Elsevier Inc. All rights reserved.

TH-C-BRD-06: A Novel MRI Based CT Artifact Correction Method for Improving Proton Range Calculation in the Presence of Severe CT Artifacts

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

Park, P; Schreibmann, E; Fox, T

2014-06-15

Purpose: Severe CT artifacts can impair our ability to accurately calculate proton range thereby resulting in a clinically unacceptable treatment plan. In this work, we investigated a novel CT artifact correction method based on a coregistered MRI and investigated its ability to estimate CT HU and proton range in the presence of severe CT artifacts. Methods: The proposed method corrects corrupted CT data using a coregistered MRI to guide the mapping of CT values from a nearby artifact-free region. First patient MRI and CT images were registered using 3D deformable image registration software based on B-spline and mutual information. Themore » CT slice with severe artifacts was selected as well as a nearby slice free of artifacts (e.g. 1cm away from the artifact). The two sets of paired MRI and CT images at different slice locations were further registered by applying 2D deformable image registration. Based on the artifact free paired MRI and CT images, a comprehensive geospatial analysis was performed to predict the correct CT HU of the CT image with severe artifact. For a proof of concept, a known artifact was introduced that changed the ground truth CT HU value up to 30% and up to 5cm error in proton range. The ability of the proposed method to recover the ground truth was quantified using a selected head and neck case. Results: A significant improvement in image quality was observed visually. Our proof of concept study showed that 90% of area that had 30% errors in CT HU was corrected to 3% of its ground truth value. Furthermore, the maximum proton range error up to 5cm was reduced to 4mm error. Conclusion: MRI based CT artifact correction method can improve CT image quality and proton range calculation for patients with severe CT artifacts.« less

Functional MRI registration with tissue-specific patch-based functional correlation tensors.

PubMed

Zhou, Yujia; Zhang, Han; Zhang, Lichi; Cao, Xiaohuan; Yang, Ru; Feng, Qianjin; Yap, Pew-Thian; Shen, Dinggang

2018-06-01

Population studies of brain function with resting-state functional magnetic resonance imaging (rs-fMRI) rely on accurate intersubject registration of functional areas. This is typically achieved through registration using high-resolution structural images with more spatial details and better tissue contrast. However, accumulating evidence has suggested that such strategy cannot align functional regions well because functional areas are not necessarily consistent with anatomical structures. To alleviate this problem, a number of registration algorithms based directly on rs-fMRI data have been developed, most of which utilize functional connectivity (FC) features for registration. However, most of these methods usually extract functional features only from the thin and highly curved cortical grey matter (GM), posing great challenges to accurate estimation of whole-brain deformation fields. In this article, we demonstrate that additional useful functional features can also be extracted from the whole brain, not restricted to the GM, particularly the white-matter (WM), for improving the overall functional registration. Specifically, we quantify local anisotropic correlation patterns of the blood oxygenation level-dependent (BOLD) signals using tissue-specific patch-based functional correlation tensors (ts-PFCTs) in both GM and WM. Functional registration is then performed by integrating the features from different tissues using the multi-channel large deformation diffeomorphic metric mapping (mLDDMM) algorithm. Experimental results show that our method achieves superior functional registration performance, compared with conventional registration methods. © 2018 Wiley Periodicals, Inc.

Quantitative [Fe]MRI of PSMA-targeted SPIONs specifically discriminates among prostate tumor cell types based on their PSMA expression levels.

PubMed

Sillerud, Laurel O

2016-01-01

We report the development, experimental verification, and application of a general theory called [Fe]MRI (pronounced fem-ree) for the non-invasive, quantitative molecular magnetic resonance imaging (MRI) of added magnetic nanoparticles or other magnetic contrast agents in biological tissues and other sites. [Fe]MRI can easily be implemented on any MRI instrument, requiring only measurements of the background nuclear magnetic relaxation times (T1, T2) of the tissue of interest, injection of the magnetic particles, and the subsequent acquisition of a pair of T1-weighted and T2-weighted images. These images, converted into contrast images, are subtracted to yield a contrast difference image proportional to the absolute nanoparticle, iron concentration, ([Fe]) image. [Fe]MRI was validated with the samples of superparamagnetic iron oxide nanoparticles (SPIONs) both in agarose gels and bound to human prostate tumor cells. The [Fe]MRI measurement of the binding of anti-prostate specific membrane antigen (PSMA) conjugated SPIONs to PSMA-positive LNCaP and PSMA-negative DU145 cells in vitro allowed a facile discrimination among prostate tumor cell types based on their PSMA expression level. The low [Fe] detection limit of ~2 μM for SPIONs allows sensitive MRI of added iron at concentrations considerably below the US Food and Drug Administration's human iron dosage guidelines (<90 μM, 5 mg/kg).

Accelerating Fibre Orientation Estimation from Diffusion Weighted Magnetic Resonance Imaging Using GPUs

PubMed Central

Hernández, Moisés; Guerrero, Ginés D.; Cecilia, José M.; García, José M.; Inuggi, Alberto; Jbabdi, Saad; Behrens, Timothy E. J.; Sotiropoulos, Stamatios N.

2013-01-01

With the performance of central processing units (CPUs) having effectively reached a limit, parallel processing offers an alternative for applications with high computational demands. Modern graphics processing units (GPUs) are massively parallel processors that can execute simultaneously thousands of light-weight processes. In this study, we propose and implement a parallel GPU-based design of a popular method that is used for the analysis of brain magnetic resonance imaging (MRI). More specifically, we are concerned with a model-based approach for extracting tissue structural information from diffusion-weighted (DW) MRI data. DW-MRI offers, through tractography approaches, the only way to study brain structural connectivity, non-invasively and in-vivo. We parallelise the Bayesian inference framework for the ball & stick model, as it is implemented in the tractography toolbox of the popular FSL software package (University of Oxford). For our implementation, we utilise the Compute Unified Device Architecture (CUDA) programming model. We show that the parameter estimation, performed through Markov Chain Monte Carlo (MCMC), is accelerated by at least two orders of magnitude, when comparing a single GPU with the respective sequential single-core CPU version. We also illustrate similar speed-up factors (up to 120x) when comparing a multi-GPU with a multi-CPU implementation. PMID:23658616

Differences in Velopharyngeal Structure during Speech among Asians Revealed by 3-Tesla Magnetic Resonance Imaging Movie Mode.

PubMed

Nunthayanon, Kulthida; Honda, Ei-ichi; Shimazaki, Kazuo; Ohmori, Hiroko; Inoue-Arai, Maristela Sayuri; Kurabayashi, Tohru; Ono, Takashi

2015-01-01

Different bony structures can affect the function of the velopharyngeal muscles. Asian populations differ morphologically, including the morphologies of their bony structures. The purpose of this study was to compare the velopharyngeal structures during speech in two Asian populations: Japanese and Thai. Ten healthy Japanese and Thai females (five each) were evaluated with a 3-Tesla (3 T) magnetic resonance imaging (MRI) scanner while they produced vowel-consonant-vowel syllable (/asa/). A gradient-echo sequence, fast low-angle shot with segmented cine and parallel imaging technique was used to obtain sagittal images of the velopharyngeal structures. MRI was carried out in real time during speech production, allowing investigations of the time-to-time changes in the velopharyngeal structures. Thai subjects had a significantly longer hard palate and produced shorter consonant than Japanese subjects. The velum of the Thai participants showed significant thickening during consonant production and their retroglossal space was significantly wider at rest, whereas the dimensional change during task performance was similar in the two populations. The 3 T MRI movie method can be used to investigate velopharyngeal function and diagnose velopharyngeal insufficiency. The racial differences may include differences in skeletal patterns and soft-tissue morphology that result in functional differences for the affected structures.

Comprehensive cellular‐resolution atlas of the adult human brain

PubMed Central

Royall, Joshua J.; Sunkin, Susan M.; Ng, Lydia; Facer, Benjamin A.C.; Lesnar, Phil; Guillozet‐Bongaarts, Angie; McMurray, Bergen; Szafer, Aaron; Dolbeare, Tim A.; Stevens, Allison; Tirrell, Lee; Benner, Thomas; Caldejon, Shiella; Dalley, Rachel A.; Dee, Nick; Lau, Christopher; Nyhus, Julie; Reding, Melissa; Riley, Zackery L.; Sandman, David; Shen, Elaine; van der Kouwe, Andre; Varjabedian, Ani; Write, Michelle; Zollei, Lilla; Dang, Chinh; Knowles, James A.; Koch, Christof; Phillips, John W.; Sestan, Nenad; Wohnoutka, Paul; Zielke, H. Ronald; Hohmann, John G.; Jones, Allan R.; Bernard, Amy; Hawrylycz, Michael J.; Hof, Patrick R.; Fischl, Bruce

2016-01-01

ABSTRACT Detailed anatomical understanding of the human brain is essential for unraveling its functional architecture, yet current reference atlases have major limitations such as lack of whole‐brain coverage, relatively low image resolution, and sparse structural annotation. We present the first digital human brain atlas to incorporate neuroimaging, high‐resolution histology, and chemoarchitecture across a complete adult female brain, consisting of magnetic resonance imaging (MRI), diffusion‐weighted imaging (DWI), and 1,356 large‐format cellular resolution (1 µm/pixel) Nissl and immunohistochemistry anatomical plates. The atlas is comprehensively annotated for 862 structures, including 117 white matter tracts and several novel cyto‐ and chemoarchitecturally defined structures, and these annotations were transferred onto the matching MRI dataset. Neocortical delineations were done for sulci, gyri, and modified Brodmann areas to link macroscopic anatomical and microscopic cytoarchitectural parcellations. Correlated neuroimaging and histological structural delineation allowed fine feature identification in MRI data and subsequent structural identification in MRI data from other brains. This interactive online digital atlas is integrated with existing Allen Institute for Brain Science gene expression atlases and is publicly accessible as a resource for the neuroscience community. J. Comp. Neurol. 524:3127–3481, 2016. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc. PMID:27418273

Comparison of computed tomography and high-field (3.0 T) magnetic resonance imaging of age-related variances in selected equine maxillary cheek teeth and adjacent tissues.

PubMed

Schoppe, Christin; Hellige, Maren; Rohn, Karl; Ohnesorge, Bernhard; Bienert-Zeit, Astrid

2017-09-06

Modern imaging techniques such as computed tomography (CT) and magnetic resonance imaging (MRI) have the advantage of producing images without superimposition. Whilst CT is a well-established technique for dental diagnostics, MRI examinations are rarely used for the evaluation of dental diseases in horses. Regarding equine endodontic therapies which are increasingly implemented, MRI could help to portray changes of the periodontal ligament and display gross pulpar anatomy. Knowledge of age-related changes is essential for diagnosis, as cheek teeth and surrounding structures alter with increasing age. The aim of the present study was to highlight the advantages of CT and MRI regarding age-related changes in selected equine cheek teeth and their adjacent structures. The CT and MRI appearances of the maxillary 08 s and 09 s and adjacent structures were described by evaluation of post-mortem examinations of nine horses of different ages (Group A: <6 years, B: 6-15 years, C: ≥16 years). Most of the tissues selected were imaged accurately with MRI and CT. Magnetic resonance imaging gives an excellent depiction of soft endo- and periodontal units, and CT of hard dental and bony tissues. Negative correlation between dental age and pulpar sizes was found: 71.3% of the changes in pulp dimensions can be explained by teeth aging. Pulpar sizes ranged from 14.3 to 1.3 mm and were significantly smaller in older horses (p < 0.05). A common pulp chamber was present in 33% of the teeth with a mean dental age of 2.25 years. Ninety-four percent of the 08 and 09 alveoli of all groups were in direct contact with the maxillary sinus. An age-related regression was found (R 2  = 0.88) for the distance between alveoli and the infraorbital canal. The present study provides information about the dental and periodontal age-related morphology and its visibility using different imaging techniques. These results aid in evaluating diagnostic images and in deciding which is the superior imaging modality for clinical cases.

A semi-automated algorithm for hypothalamus volumetry in 3 Tesla magnetic resonance images.

PubMed

Wolff, Julia; Schindler, Stephanie; Lucas, Christian; Binninger, Anne-Sophie; Weinrich, Luise; Schreiber, Jan; Hegerl, Ulrich; Möller, Harald E; Leitzke, Marco; Geyer, Stefan; Schönknecht, Peter

2018-07-30

The hypothalamus, a small diencephalic gray matter structure, is part of the limbic system. Volumetric changes of this structure occur in psychiatric diseases, therefore there is increasing interest in precise volumetry. Based on our detailed volumetry algorithm for 7 Tesla magnetic resonance imaging (MRI), we developed a method for 3 Tesla MRI, adopting anatomical landmarks and work in triplanar view. We overlaid T1-weighted MR images with gray matter-tissue probability maps to combine anatomical information with tissue class segmentation. Then, we outlined regions of interest (ROIs) that covered potential hypothalamus voxels. Within these ROIs, seed growing technique helped define the hypothalamic volume using gray matter probabilities from the tissue probability maps. This yielded a semi-automated method with short processing times of 20-40 min per hypothalamus. In the MRIs of ten subjects, reliabilities were determined as intraclass correlations (ICC) and volume overlaps in percent. Three raters achieved very good intra-rater reliabilities (ICC 0.82-0.97) and good inter-rater reliabilities (ICC 0.78 and 0.82). Overlaps of intra- and inter-rater runs were very good (≥ 89.7%). We present a fast, semi-automated method for in vivo hypothalamus volumetry in 3 Tesla MRI. Copyright © 2018 Elsevier B.V. All rights reserved.

Population differences in brain morphology: Need for population specific brain template.

PubMed

Rao, Naren P; Jeelani, Haris; Achalia, Rashmin; Achalia, Garima; Jacob, Arpitha; Bharath, Rose Dawn; Varambally, Shivarama; Venkatasubramanian, Ganesan; K Yalavarthy, Phaneendra

2017-07-30

Brain templates provide a standard anatomical platform for population based morphometric assessments. Typically, standard brain templates for such assessments are created using Caucasian brains, which may not be ideal to analyze brains from other ethnicities. To effectively demonstrate this, we compared brain morphometric differences between T1 weighted structural MRI images of 27 healthy Indian and Caucasian subjects of similar age and same sex ratio. Furthermore, a population specific brain template was created from MRI images of healthy Indian subjects and compared with standard Montreal Neurological Institute (MNI-152) template. We also examined the accuracy of registration of by acquiring a different T1 weighted MRI data set and registering them to newly created Indian template and MNI-152 template. The statistical analysis indicates significant difference in global brain measures and regional brain structures of Indian and Caucasian subjects. Specifically, the global brain measurements of the Indian brain template were smaller than that of the MNI template. Also, Indian brain images were better realigned to the newly created template than to the MNI-152 template. The notable variations in Indian and Caucasian brains convey the need to build a population specific Indian brain template and atlas. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Fully automatic, multiorgan segmentation in normal whole body magnetic resonance imaging (MRI), using classification forests (CFs), convolutional neural networks (CNNs), and a multi-atlas (MA) approach.

PubMed

Lavdas, Ioannis; Glocker, Ben; Kamnitsas, Konstantinos; Rueckert, Daniel; Mair, Henrietta; Sandhu, Amandeep; Taylor, Stuart A; Aboagye, Eric O; Rockall, Andrea G

2017-10-01

As part of a program to implement automatic lesion detection methods for whole body magnetic resonance imaging (MRI) in oncology, we have developed, evaluated, and compared three algorithms for fully automatic, multiorgan segmentation in healthy volunteers. The first algorithm is based on classification forests (CFs), the second is based on 3D convolutional neural networks (CNNs) and the third algorithm is based on a multi-atlas (MA) approach. We examined data from 51 healthy volunteers, scanned prospectively with a standardized, multiparametric whole body MRI protocol at 1.5 T. The study was approved by the local ethics committee and written consent was obtained from the participants. MRI data were used as input data to the algorithms, while training was based on manual annotation of the anatomies of interest by clinical MRI experts. Fivefold cross-validation experiments were run on 34 artifact-free subjects. We report three overlap and three surface distance metrics to evaluate the agreement between the automatic and manual segmentations, namely the dice similarity coefficient (DSC), recall (RE), precision (PR), average surface distance (ASD), root-mean-square surface distance (RMSSD), and Hausdorff distance (HD). Analysis of variances was used to compare pooled label metrics between the three algorithms and the DSC on a 'per-organ' basis. A Mann-Whitney U test was used to compare the pooled metrics between CFs and CNNs and the DSC on a 'per-organ' basis, when using different imaging combinations as input for training. All three algorithms resulted in robust segmenters that were effectively trained using a relatively small number of datasets, an important consideration in the clinical setting. Mean overlap metrics for all the segmented structures were: CFs: DSC = 0.70 ± 0.18, RE = 0.73 ± 0.18, PR = 0.71 ± 0.14, CNNs: DSC = 0.81 ± 0.13, RE = 0.83 ± 0.14, PR = 0.82 ± 0.10, MA: DSC = 0.71 ± 0.22, RE = 0.70 ± 0.34, PR = 0.77 ± 0.15. Mean surface distance metrics for all the segmented structures were: CFs: ASD = 13.5 ± 11.3 mm, RMSSD = 34.6 ± 37.6 mm and HD = 185.7 ± 194.0 mm, CNNs; ASD = 5.48 ± 4.84 mm, RMSSD = 17.0 ± 13.3 mm and HD = 199.0 ± 101.2 mm, MA: ASD = 4.22 ± 2.42 mm, RMSSD = 6.13 ± 2.55 mm, and HD = 38.9 ± 28.9 mm. The pooled performance of CFs improved when all imaging combinations (T2w + T1w + DWI) were used as input, while the performance of CNNs deteriorated, but in neither case, significantly. CNNs with T2w images as input, performed significantly better than CFs with all imaging combinations as input for all anatomical labels, except for the bladder. Three state-of-the-art algorithms were developed and used to automatically segment major organs and bones in whole body MRI; good agreement to manual segmentations performed by clinical MRI experts was observed. CNNs perform favorably, when using T2w volumes as input. Using multimodal MRI data as input to CNNs did not improve the segmentation performance. © 2017 American Association of Physicists in Medicine.

Structural abnormalities and altered regional brain activity in multiple sclerosis with simple spinal cord involvement.

PubMed

Yin, Ping; Liu, Yi; Xiong, Hua; Han, Yongliang; Sah, Shambhu Kumar; Zeng, Chun; Wang, Jingjie; Li, Yongmei

2018-02-01

To assess the changes of the structural and functional abnormalities in multiple sclerosis with simple spinal cord involvement (MS-SSCI) by using resting-state functional MRI (RS-fMRI), voxel based morphology (VBM) and diffusion tensor tractography. The amplitude of low-frequency fluctuation (ALFF) of 22 patients with MS-SSCI and 22 healthy controls (HCs) matched for age, gender and education were compared by using RS-fMRI. We also compared the volume, fractional anisotropy (FA) and apparent diffusion coefficient of the brain regions in baseline brain activity by using VBM and diffusion tensor imaging. The relationships between the expanded disability states scale (EDSS) scores, changed parameters of structure and function were further explored. (1) Compared with HCs, the ALFF of the bilateral hippocampus and right middle temporal gyrus in MS-SSCI decreased significantly. However, patients exhibited increased ALFF in the left middle frontal gyrus, left posterior cingulate gyrus and right middle occipital gyrus ( two-sample t-test, after AlphaSim correction, p < 0.01, voxel size > 40). The volume of right middle frontal gyrus reduced significantly (p < 0.01). The FA and ADC of right hippocampus, the FA of left hippocampus and right middle temporal gyrus were significantly different. (2) A significant correlation between EDSS scores and ALFF was noted only in the left posterior cingulate gyrus. Our results detected structural and functional abnormalities in MS-SSCI and functional parameters were associated with clinical abnormalities. Multimodal imaging plays an important role in detecting structural and functional abnormalities in MS-SSCI. Advances in knowledge: This is the first time to apply RS-fMRI, VBM and diffusion tensor tractography to study the structural and functional abnormalities in MS-SSCI, and to explore its correlation with EDSS score.

Multimodal Wavelet Embedding Representation for data Combination (MaWERiC): Integrating Magnetic Resonance Imaging and Spectroscopy for Prostate Cancer Detection

PubMed Central

Tiwari, Pallavi; Kurhanewicz, John; Viswanath, Satish; Sridhar, Akshay; Madabhushi, Anant

2011-01-01

Rationale and Objectives To develop a computerized data integration framework (MaWERiC) for quantitatively combining structural and metabolic information from different Magnetic Resonance (MR) imaging modalities. Materials and Methods In this paper, we present a novel computerized support system that we call Multimodal Wavelet Embedding Representation for data Combination (MaWERiC) which (1) employs wavelet theory and dimensionality reduction for providing a common, uniform representation of the different imaging (T2-w) and non-imaging (spectroscopy) MRI channels, and (2) leverages a random forest classifier for automated prostate cancer detection on a per voxel basis from combined 1.5 Tesla in vivo MRI and MRS. Results A total of 36 1.5 T endorectal in vivo T2-w MRI, MRS patient studies were evaluated on a per-voxel via MaWERiC, using a three-fold cross validation scheme across 25 iterations. Ground truth for evaluation of the results was obtained via ex-vivo whole-mount histology sections which served as the gold standard for expert radiologist annotations of prostate cancer on a per-voxel basis. The results suggest that MaWERiC based MRS-T2-w meta-classifier (mean AUC, μ = 0.89 ± 0.02) significantly outperformed (i) a T2-w MRI (employing wavelet texture features) classifier (μ = 0.55± 0.02), (ii) a MRS (employing metabolite ratios) classifier (μ= 0.77 ± 0.03), (iii) a decision-fusion classifier, obtained by combining individual T2-w MRI and MRS classifier outputs (μ = 0.85 ± 0.03) and (iv) a data combination scheme involving combination of metabolic MRS and MR signal intensity features (μ = 0.66± 0.02). Conclusion A novel data integration framework, MaWERiC, for combining imaging and non-imaging MRI channels was presented. Application to prostate cancer detection via combination of T2-w MRI and MRS data demonstrated significantly higher AUC and accuracy values compared to the individual T2-w MRI, MRS modalities and other data integration strategies. PMID:21960175

Motion‐related artifacts in structural brain images revealed with independent estimates of in‐scanner head motion

PubMed Central

Savalia, Neil K.; Agres, Phillip F.; Chan, Micaela Y.; Feczko, Eric J.; Kennedy, Kristen M.

2016-01-01

Abstract Motion‐contaminated T1‐weighted (T1w) magnetic resonance imaging (MRI) results in misestimates of brain structure. Because conventional T1w scans are not collected with direct measures of head motion, a practical alternative is needed to identify potential motion‐induced bias in measures of brain anatomy. Head movements during functional MRI (fMRI) scanning of 266 healthy adults (20–89 years) were analyzed to reveal stable features of in‐scanner head motion. The magnitude of head motion increased with age and exhibited within‐participant stability across different fMRI scans. fMRI head motion was then related to measurements of both quality control (QC) and brain anatomy derived from a T1w structural image from the same scan session. A procedure was adopted to “flag” individuals exhibiting excessive head movement during fMRI or poor T1w quality rating. The flagging procedure reliably reduced the influence of head motion on estimates of gray matter thickness across the cortical surface. Moreover, T1w images from flagged participants exhibited reduced estimates of gray matter thickness and volume in comparison to age‐ and gender‐matched samples, resulting in inflated effect sizes in the relationships between regional anatomical measures and age. Gray matter thickness differences were noted in numerous regions previously reported to undergo prominent atrophy with age. Recommendations are provided for mitigating this potential confound, and highlight how the procedure may lead to more accurate measurement and comparison of anatomical features. Hum Brain Mapp 38:472–492, 2017. © 2016 Wiley Periodicals, Inc. PMID:27634551

The Human Connectome Project: A data acquisition perspective

PubMed Central

Van Essen, D.C.; Ugurbil, K.; Auerbach, E.; Barch, D.; Behrens, T.E.J.; Bucholz, R.; Chang, A.; Chen, L.; Corbetta, M.; Curtiss, S.W.; Della Penna, S.; Feinberg, D.; Glasser, M.F.; Harel, N.; Heath, A.C.; Larson-Prior, L.; Marcus, D.; Michalareas, G.; Moeller, S.; Oostenveld, R.; Petersen, S.E.; Prior, F.; Schlaggar, B.L.; Smith, S.M.; Snyder, A.Z.; Xu, J.; Yacoub, E.

2012-01-01

The Human Connectome Project (HCP) is an ambitious 5-year effort to characterize brain connectivity and function and their variability in healthy adults. This review summarizes the data acquisition plans being implemented by a consortium of HCP investigators who will study a population of 1200 subjects (twins and their non-twin siblings) using multiple imaging modalities along with extensive behavioral and genetic data. The imaging modalities will include diffusion imaging (dMRI), resting-state fMRI (R-fMRI), task-evoked fMRI (T-fMRI), T1- and T2-weighted MRI for structural and myelin mapping, plus combined magnetoencephalography and electroencephalography (MEG/EEG). Given the importance of obtaining the best possible data quality, we discuss the efforts underway during the first two years of the grant (Phase I) to refine and optimize many aspects of HCP data acquisition, including a new 7T scanner, a customized 3T scanner, and improved MR pulse sequences. PMID:22366334

Convergent Findings of Altered Functional and Structural Brain Connectivity in Individuals with High Functioning Autism: A Multimodal MRI Study

PubMed Central

Samson, Andrea C.; Kirsch, Valerie; Blautzik, Janusch; Grothe, Michel; Erat, Okan; Hegenloh, Michael; Coates, Ute; Reiser, Maximilian F.; Hennig-Fast, Kristina; Meindl, Thomas

2013-01-01

Brain tissue changes in autism spectrum disorders seem to be rather subtle and widespread than anatomically distinct. Therefore a multimodal, whole brain imaging technique appears to be an appropriate approach to investigate whether alterations in white and gray matter integrity relate to consistent changes in functional resting state connectivity in individuals with high functioning autism (HFA). We applied diffusion tensor imaging (DTI), voxel-based morphometry (VBM) and resting state functional connectivity magnetic resonance imaging (fcMRI) to assess differences in brain structure and function between 12 individuals with HFA (mean age 35.5, SD 11.4, 9 male) and 12 healthy controls (mean age 33.3, SD 9.0, 8 male). Psychological measures of empathy and emotionality were obtained and correlated with the most significant DTI, VBM and fcMRI findings. We found three regions of convergent structural and functional differences between HFA participants and controls. The right temporo-parietal junction area and the left frontal lobe showed decreased fractional anisotropy (FA) values along with decreased functional connectivity and a trend towards decreased gray matter volume. The bilateral superior temporal gyrus displayed significantly decreased functional connectivity that was accompanied by the strongest trend of gray matter volume decrease in the temporal lobe of HFA individuals. FA decrease in the right temporo-parietal region was correlated with psychological measurements of decreased emotionality. In conclusion, our results indicate common sites of structural and functional alterations in higher order association cortex areas and may therefore provide multimodal imaging support to the long-standing hypothesis of autism as a disorder of impaired higher-order multisensory integration. PMID:23825652

Segmentation precision of abdominal anatomy for MRI-based radiotherapy

PubMed Central

Noel, Camille E.; Zhu, Fan; Lee, Andrew Y.; Yanle, Hu; Parikh, Parag J.

2014-01-01

The limited soft tissue visualization provided by computed tomography, the standard imaging modality for radiotherapy treatment planning and daily localization, has motivated studies on the use of magnetic resonance imaging (MRI) for better characterization of treatment sites, such as the prostate and head and neck. However, no studies have been conducted on MRI-based segmentation for the abdomen, a site that could greatly benefit from enhanced soft tissue targeting. We investigated the interobserver and intraobserver precision in segmentation of abdominal organs on MR images for treatment planning and localization. Manual segmentation of 8 abdominal organs was performed by 3 independent observers on MR images acquired from 14 healthy subjects. Observers repeated segmentation 4 separate times for each image set. Interobserver and intraobserver contouring precision was assessed by computing 3-dimensional overlap (Dice coefficient [DC]) and distance to agreement (Hausdorff distance [HD]) of segmented organs. The mean and standard deviation of intraobserver and interobserver DC and HD values were DCintraobserver = 0.89 ± 0.12, HDintraobserver = 3.6 mm ± 1.5, DCinterobserver = 0.89 ± 0.15, and HDinterobserver = 3.2 mm ± 1.4. Overall, metrics indicated good interobserver/intraobserver precision (mean DC > 0.7, mean HD < 4 mm). Results suggest that MRI offers good segmentation precision for abdominal sites. These findings support the utility of MRI for abdominal planning and localization, as emerging MRI technologies, techniques, and onboard imaging devices are beginning to enable MRI-based radiotherapy. PMID:24726701

Segmentation precision of abdominal anatomy for MRI-based radiotherapy

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

Noel, Camille E.; Zhu, Fan; Lee, Andrew Y.

2014-10-01

The limited soft tissue visualization provided by computed tomography, the standard imaging modality for radiotherapy treatment planning and daily localization, has motivated studies on the use of magnetic resonance imaging (MRI) for better characterization of treatment sites, such as the prostate and head and neck. However, no studies have been conducted on MRI-based segmentation for the abdomen, a site that could greatly benefit from enhanced soft tissue targeting. We investigated the interobserver and intraobserver precision in segmentation of abdominal organs on MR images for treatment planning and localization. Manual segmentation of 8 abdominal organs was performed by 3 independent observersmore » on MR images acquired from 14 healthy subjects. Observers repeated segmentation 4 separate times for each image set. Interobserver and intraobserver contouring precision was assessed by computing 3-dimensional overlap (Dice coefficient [DC]) and distance to agreement (Hausdorff distance [HD]) of segmented organs. The mean and standard deviation of intraobserver and interobserver DC and HD values were DC{sub intraobserver} = 0.89 ± 0.12, HD{sub intraobserver} = 3.6 mm ± 1.5, DC{sub interobserver} = 0.89 ± 0.15, and HD{sub interobserver} = 3.2 mm ± 1.4. Overall, metrics indicated good interobserver/intraobserver precision (mean DC > 0.7, mean HD < 4 mm). Results suggest that MRI offers good segmentation precision for abdominal sites. These findings support the utility of MRI for abdominal planning and localization, as emerging MRI technologies, techniques, and onboard imaging devices are beginning to enable MRI-based radiotherapy.« less

A Fully-Automated Subcortical and Ventricular Shape Generation Pipeline Preserving Smoothness and Anatomical Topology

PubMed Central

Tang, Xiaoying; Luo, Yuan; Chen, Zhibin; Huang, Nianwei; Johnson, Hans J.; Paulsen, Jane S.; Miller, Michael I.

2018-01-01

In this paper, we present a fully-automated subcortical and ventricular shape generation pipeline that acts on structural magnetic resonance images (MRIs) of the human brain. Principally, the proposed pipeline consists of three steps: (1) automated structure segmentation using the diffeomorphic multi-atlas likelihood-fusion algorithm; (2) study-specific shape template creation based on the Delaunay triangulation; (3) deformation-based shape filtering using the large deformation diffeomorphic metric mapping for surfaces. The proposed pipeline is shown to provide high accuracy, sufficient smoothness, and accurate anatomical topology. Two datasets focused upon Huntington's disease (HD) were used for evaluating the performance of the proposed pipeline. The first of these contains a total of 16 MRI scans, each with a gold standard available, on which the proposed pipeline's outputs were observed to be highly accurate and smooth when compared with the gold standard. Visual examinations and outlier analyses on the second dataset, which contains a total of 1,445 MRI scans, revealed 100% success rates for the putamen, the thalamus, the globus pallidus, the amygdala, and the lateral ventricle in both hemispheres and rates no smaller than 97% for the bilateral hippocampus and caudate. Another independent dataset, consisting of 15 atlas images and 20 testing images, was also used to quantitatively evaluate the proposed pipeline, with high accuracy having been obtained. In short, the proposed pipeline is herein demonstrated to be effective, both quantitatively and qualitatively, using a large collection of MRI scans. PMID:29867332

A Fully-Automated Subcortical and Ventricular Shape Generation Pipeline Preserving Smoothness and Anatomical Topology.

PubMed

Tang, Xiaoying; Luo, Yuan; Chen, Zhibin; Huang, Nianwei; Johnson, Hans J; Paulsen, Jane S; Miller, Michael I

2018-01-01

In this paper, we present a fully-automated subcortical and ventricular shape generation pipeline that acts on structural magnetic resonance images (MRIs) of the human brain. Principally, the proposed pipeline consists of three steps: (1) automated structure segmentation using the diffeomorphic multi-atlas likelihood-fusion algorithm; (2) study-specific shape template creation based on the Delaunay triangulation; (3) deformation-based shape filtering using the large deformation diffeomorphic metric mapping for surfaces. The proposed pipeline is shown to provide high accuracy, sufficient smoothness, and accurate anatomical topology. Two datasets focused upon Huntington's disease (HD) were used for evaluating the performance of the proposed pipeline. The first of these contains a total of 16 MRI scans, each with a gold standard available, on which the proposed pipeline's outputs were observed to be highly accurate and smooth when compared with the gold standard. Visual examinations and outlier analyses on the second dataset, which contains a total of 1,445 MRI scans, revealed 100% success rates for the putamen, the thalamus, the globus pallidus, the amygdala, and the lateral ventricle in both hemispheres and rates no smaller than 97% for the bilateral hippocampus and caudate. Another independent dataset, consisting of 15 atlas images and 20 testing images, was also used to quantitatively evaluate the proposed pipeline, with high accuracy having been obtained. In short, the proposed pipeline is herein demonstrated to be effective, both quantitatively and qualitatively, using a large collection of MRI scans.

Characterization of Cerebral White Matter Properties Using Quantitative Magnetic Resonance Imaging Stains

PubMed Central

Hurley, Samuel A.; Samsonov, Alexey A.; Adluru, Nagesh; Hosseinbor, Ameer Pasha; Mossahebi, Pouria; Tromp, Do P.M.; Zakszewski, Elizabeth; Field, Aaron S.

2011-01-01

Abstract The image contrast in magnetic resonance imaging (MRI) is highly sensitive to several mechanisms that are modulated by the properties of the tissue environment. The degree and type of contrast weighting may be viewed as image filters that accentuate specific tissue properties. Maps of quantitative measures of these mechanisms, akin to microstructural/environmental-specific tissue stains, may be generated to characterize the MRI and physiological properties of biological tissues. In this article, three quantitative MRI (qMRI) methods for characterizing white matter (WM) microstructural properties are reviewed. All of these measures measure complementary aspects of how water interacts with the tissue environment. Diffusion MRI, including diffusion tensor imaging, characterizes the diffusion of water in the tissues and is sensitive to the microstructural density, spacing, and orientational organization of tissue membranes, including myelin. Magnetization transfer imaging characterizes the amount and degree of magnetization exchange between free water and macromolecules like proteins found in the myelin bilayers. Relaxometry measures the MRI relaxation constants T1 and T2, which in WM have a component associated with the water trapped in the myelin bilayers. The conduction of signals between distant brain regions occurs primarily through myelinated WM tracts; thus, these methods are potential indicators of pathology and structural connectivity in the brain. This article provides an overview of the qMRI stain mechanisms, acquisition and analysis strategies, and applications for these qMRI stains. PMID:22432902

Yield of MRI, high-density electric source imaging (HD-ESI), SPECT and PET in epilepsy surgery candidates.

PubMed

Lascano, Agustina M; Perneger, Thomas; Vulliemoz, Serge; Spinelli, Laurent; Garibotto, Valentina; Korff, Christian M; Vargas, Maria I; Michel, Christoph M; Seeck, Margitta

2016-01-01

Preoperative workup aims at localizing the epileptogenic focus to achieve postoperative seizure-freedom. We studied the predictive value of non-invasive techniques, i.e. structural magnetic resonance imaging [MRI], high-density electric source imaging [HD-ESI] and metabolic imaging (positron emission tomography [PET]; single-photon emission computed tomography [SPECT]), in surgically treated patients. A prospective study of 190 epileptic operated patients, with >12 months follow-up and analyzed with state-of-the-art algorithms. 58 patients underwent all techniques. We computed sensitivity, specificity, predictive value and diagnostic odds ratio (OR) in relation to postoperative outcome. Of 190 patients, 148 (77.9%) were seizure-free at follow-up. Resection of the epileptogenic focus was associated with favorable postsurgical outcome (p<0.05). Among 58 patients who underwent all tests, only MRI and HD-ESI were favorable outcome predictors (MRI: OR 10.9, p=0.004; HD-ESI: OR 13.1, p=0.004). Patients with concordant structural MRI and HD-ESI results had 92.3% (24/26) probability of favorable outcome. When both results were negative, probability was 0% (0/5); and when they disagreed, it was 63.0% (17/27). Combination of MRI and HD-ESI offered the highest predictive value for postoperative seizure-freedom. This finding highlights the added value of HD-ESI in the presurgical workup, in particular in combination with an informative MRI. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Direct depiction of bone microstructure using MRI with zero echo time.

PubMed

Weiger, Markus; Stampanoni, Marco; Pruessmann, Klaas P

2013-05-01

This paper reports a proof of principle of direct depiction of trabecular bone microstructure in vitro by means of magnetic resonance imaging (MRI). Such depiction is achieved by (1)H imaging of water embedded in the bone matrix. The fast transverse relaxation of this compartment with T2(⁎) on the order of a few hundreds of microseconds is addressed by a three-dimensional MRI technique with zero echo time (ZTE). ZTE imaging at an isotropic spatial resolution of 56 μm is demonstrated in a trabecular bone specimen extracted from a bovine bone. In the MR images, the trabecular bone structure is clearly depicted and a high level of robustness against off-resonance artefacts is observed. The structural accuracy of the MR data is investigated by comparison with x-ray micro-computed tomography. Copyright © 2013 Elsevier Inc. All rights reserved.

Human developmental anatomy: microscopic magnetic resonance imaging (μMRI) of four human embryos (from Carnegie Stage 10 to 20).

PubMed

Lhuaire, Martin; Martinez, Agathe; Kaplan, Hervé; Nuzillard, Jean-Marc; Renard, Yohann; Tonnelet, Romain; Braun, Marc; Avisse, Claude; Labrousse, Marc

2014-12-01

Technological advances in the field of biological imaging now allow multi-modal studies of human embryo anatomy. The aim of this study was to assess the high magnetic field μMRI feasibility in the study of small human embryos (less than 21mm crown-rump) as a new tool for the study of human descriptive embryology and to determine better sequence characteristics to obtain higher spatial resolution and higher signal/noise ratio. Morphological study of four human embryos belonging to the historical collection of the Department of Anatomy in the Faculty of Medicine of Reims was undertaken by μMRI. These embryos had, successively, crown-rump lengths of 3mm (Carnegie Stage, CS 10), 12mm (CS 16), 17mm (CS 18) and 21mm (CS 20). Acquisition of images was performed using a vertical nuclear magnetic resonance spectrometer, a Bruker Avance III, 500MHz, 11.7T equipped for imaging. All images were acquired using 2D (transverse, sagittal and coronal) and 3D sequences, either T1-weighted or T2-weighted. Spatial resolution between 24 and 70μm/pixel allowed clear visualization of all anatomical structures of the embryos. The study of human embryos μMRI has already been reported in the literature and a few atlases exist for educational purposes. However, to our knowledge, descriptive or morphological studies of human developmental anatomy based on data collected these few μMRI studies of human embryos are rare. This morphological noninvasive imaging method coupled with other techniques already reported seems to offer new perspectives to descriptive studies of human embryology.

WE-G-BRD-07: Automated MR Image Standardization and Auto-Contouring Strategy for MRI-Based Adaptive Brachytherapy for Cervix Cancer

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

Saleh, H Al; Erickson, B; Paulson, E

Purpose: MRI-based adaptive brachytherapy (ABT) is an emerging treatment modality for patients with gynecological tumors. However, MR image intensity non-uniformities (IINU) can vary from fraction to fraction, complicating image interpretation and auto-contouring accuracy. We demonstrate here an automated MR image standardization and auto-contouring strategy for MRI-based ABT of cervix cancer. Methods: MR image standardization consisted of: 1) IINU correction using the MNI N3 algorithm, 2) noise filtering using anisotropic diffusion, and 3) signal intensity normalization using the volumetric median. This post-processing chain was implemented as a series of custom Matlab and Java extensions in MIM (v6.4.5, MIM Software) and wasmore » applied to 3D T2 SPACE images of six patients undergoing MRI-based ABT at 3T. Coefficients of variation (CV=σ/µ) were calculated for both original and standardized images and compared using Mann-Whitney tests. Patient-specific cumulative MR atlases of bladder, rectum, and sigmoid contours were constructed throughout ABT, using original and standardized MR images from all previous ABT fractions. Auto-contouring was performed in MIM two ways: 1) best-match of one atlas image to the daily MR image, 2) multi-match of all previous fraction atlas images to the daily MR image. Dice’s Similarity Coefficients (DSCs) were calculated for auto-generated contours relative to reference contours for both original and standardized MR images and compared using Mann-Whitney tests. Results: Significant improvements in CV were detected following MR image standardization (p=0.0043), demonstrating an improvement in MR image uniformity. DSCs consistently increased for auto-contoured bladder, rectum, and sigmoid following MR image standardization, with the highest DSCs detected when the combination of MR image standardization and multi-match cumulative atlas-based auto-contouring was utilized. Conclusion: MR image standardization significantly improves MR image uniformity. The combination of MR image standardization and multi-match cumulative atlas-based auto-contouring produced the highest DSCs and is a promising strategy for MRI-based ABT for cervix cancer.« less

Magnetic resonance imaging in multiple sclerosis--patients' experiences, information interests and responses to an education programme.

PubMed

Brand, Judith; Köpke, Sascha; Kasper, Jürgen; Rahn, Anne; Backhus, Imke; Poettgen, Jana; Stellmann, Jan-Patrick; Siemonsen, Susanne; Heesen, Christoph

2014-01-01

Magnetic resonance imaging (MRI) is a key diagnostic and monitoring tool in multiple sclerosis (MS) management. However, many scientific uncertainties, especially concerning correlates to impairment and prognosis remain. Little is known about MS patients' experiences, knowledge, attitudes, and unmet information needs concerning MRI. We performed qualitative interviews (n = 5) and a survey (n = 104) with MS patients regarding MRI patient information, and basic MRI knowledge. Based on these findings an interactive training program of 2 hours was developed and piloted in n = 26 patients. Interview analyses showed that patients often feel lost in the MRI scanner and left alone with MRI results and images while 90% of patients in the survey expressed a high interest in MRI education. Knowledge on MRI issues was fair with some important knowledge gaps. Major information interests were relevance of lesions as well as the prognostic and diagnostic value of MRI results. The education program was highly appreciated and resulted in a substantial knowledge increase. Patients reported that, based on the program, they felt more competent to engage in encounters with their physicians. This work strongly supports the further development of an evidence-based MRI education program for MS patients to enhance participation in health-care.

Lipid-based nanoparticles for contrast-enhanced MRI and molecular imaging.

PubMed

Mulder, Willem J M; Strijkers, Gustav J; van Tilborg, Geralda A F; Griffioen, Arjan W; Nicolay, Klaas

2006-02-01

In the field of MR imaging and especially in the emerging field of cellular and molecular MR imaging, flexible strategies to synthesize contrast agents that can be manipulated in terms of size and composition and that can be easily conjugated with targeting ligands are required. Furthermore, the relaxivity of the contrast agents, especially for molecular imaging applications, should be very high to deal with the low sensitivity of MRI. Lipid-based nanoparticles, such as liposomes or micelles, have been used extensively in recent decades as drug carrier vehicles. A relatively new and promising application of lipidic nanoparticles is their use as multimodal MR contrast agents. Lipids are amphiphilic molecules with both a hydrophobic and a hydrophilic part, which spontaneously assemble into aggregates in an aqueous environment. In these aggregates, the amphiphiles are arranged such that the hydrophobic parts cluster together and the hydrophilic parts face the water. In the low concentration regime, a wide variety of structures can be formed, ranging from spherical micelles to disks or liposomes. Furthermore, a monolayer of lipids can serve as a shell to enclose a hydrophobic core. Hydrophobic iron oxide particles, quantum dots or perfluorocarbon emulsions can be solubilized using this approach. MR-detectable and fluorescent amphiphilic molecules can easily be incorporated in lipidic nanoparticles. Furthermore, targeting ligands can be conjugated to lipidic particles by incorporating lipids with a functional moiety to allow a specific interaction with molecular markers and to achieve accumulation of the particles at disease sites. In this review, an overview of different lipidic nanoparticles for use in MRI is given, with the main emphasis on Gd-based contrast agents. The mechanisms of particle formation, conjugation strategies and applications in the field of contrast-enhanced, cellular and molecular MRI are discussed. 2006 John Wiley & Sons, Ltd.

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.

Optimal Control-Enabled Imaging and Spectroscopy using a Nanowire Magnetic Resonance Force Microscope

NASA Astrophysics Data System (ADS)

Rose, William; Haas, Holger; Chen, Angela; Cory, David; Budakian, Raffi

Magnetic resonance imaging (MRI) is a powerful non-invasive technique that has transformed our ability to study the structure and function of biological systems. Key to its success has been the unique ability to combine imaging with magnetic resonance spectroscopy. Although it remains a significant challenge, there is considerable interest in extending MRI spectroscopy to the nanometer scale because it would provide a fundamentally new route for determining the structure and function of complex biomolecules. We present data taken with a nanowire magnetic resonance force microscopy (MRFM) setup. We show how the capabilities of this very sensitive spin-detection system can be extended to include spectroscopy and nanometer-scale imaging by combining optimal control theory (OCT) techniques with magic echo sequences. We apply OCT-based dynamical-decoupling pulses to nanoscale ensembles of proton spins in polystyrene, and demonstrate a 500-fold line-narrowing of the proton spin resonance, from 30 kHz to 60 Hz. We further demonstrate 1-D imaging over a 35-nm region with an average voxel size of 2.2 nm. Funding provided by the U.S. Army Research Office, Grant No. W911NF-12-1-0341.

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.

Differential diagnosis of neurodegenerative diseases using structural MRI data

PubMed Central

Koikkalainen, Juha; Rhodius-Meester, Hanneke; Tolonen, Antti; Barkhof, Frederik; Tijms, Betty; Lemstra, Afina W.; Tong, Tong; Guerrero, Ricardo; Schuh, Andreas; Ledig, Christian; Rueckert, Daniel; Soininen, Hilkka; Remes, Anne M.; Waldemar, Gunhild; Hasselbalch, Steen; Mecocci, Patrizia; van der Flier, Wiesje; Lötjönen, Jyrki

2016-01-01

Different neurodegenerative diseases can cause memory disorders and other cognitive impairments. The early detection and the stratification of patients according to the underlying disease are essential for an efficient approach to this healthcare challenge. This emphasizes the importance of differential diagnostics. Most studies compare patients and controls, or Alzheimer's disease with one other type of dementia. Such a bilateral comparison does not resemble clinical practice, where a clinician is faced with a number of different possible types of dementia. Here we studied which features in structural magnetic resonance imaging (MRI) scans could best distinguish four types of dementia, Alzheimer's disease, frontotemporal dementia, vascular dementia, and dementia with Lewy bodies, and control subjects. We extracted an extensive set of features quantifying volumetric and morphometric characteristics from T1 images, and vascular characteristics from FLAIR images. Classification was performed using a multi-class classifier based on Disease State Index methodology. The classifier provided continuous probability indices for each disease to support clinical decision making. A dataset of 504 individuals was used for evaluation. The cross-validated classification accuracy was 70.6% and balanced accuracy was 69.1% for the five disease groups using only automatically determined MRI features. Vascular dementia patients could be detected with high sensitivity (96%) using features from FLAIR images. Controls (sensitivity 82%) and Alzheimer's disease patients (sensitivity 74%) could be accurately classified using T1-based features, whereas the most difficult group was the dementia with Lewy bodies (sensitivity 32%). These results were notable better than the classification accuracies obtained with visual MRI ratings (accuracy 44.6%, balanced accuracy 51.6%). Different quantification methods provided complementary information, and consequently, the best results were obtained by utilizing several quantification methods. The results prove that automatic quantification methods and computerized decision support methods are feasible for clinical practice and provide comprehensive information that may help clinicians in the diagnosis making. PMID:27104138

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

Cervical soft tissue imaging using a mobile CBCT scanner with a flat panel detector in comparison with corresponding CT and MRI data sets.

PubMed

Heiland, Max; Pohlenz, Philipp; Blessmann, Marco; Habermann, Christian R; Oesterhelweg, Lars; Begemann, Philipp C; Schmidgunst, Christian; Blake, Felix A S; Püschel, Klaus; Schmelzle, Rainer; Schulze, Dirk

2007-12-01

The aim of this study was to evaluate soft tissue image quality of a mobile cone-beam computed tomography (CBCT) scanner with an integrated flat-panel detector. Eight fresh human cadavers were used in this study. For evaluation of soft tissue visualization, CBCT data sets and corresponding computed tomography (CT) and magnetic resonance imaging (MRI) data sets were acquired. Evaluation was performed with the help of 10 defined cervical anatomical structures. The statistical analysis of the scoring results of 3 examiners revealed the CBCT images to be of inferior quality regarding the visualization of most of the predefined structures. Visualization without a significant difference was found regarding the demarcation of the vertebral bodies and the pyramidal cartilages, the arteriosclerosis of the carotids (compared with CT), and the laryngeal skeleton (compared with MRI). Regarding arteriosclerosis of the carotids compared with MRI, CBCT proved to be superior. The integration of a flat-panel detector improves soft tissue visualization using a mobile CBCT scanner.

Volume estimation of brain abnormalities in MRI data

NASA Astrophysics Data System (ADS)

Suprijadi, Pratama, S. H.; Haryanto, F.

2014-02-01

The abnormality of brain tissue always becomes a crucial issue in medical field. This medical condition can be recognized through segmentation of certain region from medical images obtained from MRI dataset. Image processing is one of computational methods which very helpful to analyze the MRI data. In this study, combination of segmentation and rendering image were used to isolate tumor and stroke. Two methods of thresholding were employed to segment the abnormality occurrence, followed by filtering to reduce non-abnormality area. Each MRI image is labeled and then used for volume estimations of tumor and stroke-attacked area. The algorithms are shown to be successful in isolating tumor and stroke in MRI images, based on thresholding parameter and stated detection accuracy.

MR and CT image fusion for postimplant analysis in permanent prostate seed implants.

PubMed

Polo, Alfredo; Cattani, Federica; Vavassori, Andrea; Origgi, Daniela; Villa, Gaetano; Marsiglia, Hugo; Bellomi, Massimo; Tosi, Giampiero; De Cobelli, Ottavio; Orecchia, Roberto

2004-12-01

To compare the outcome of two different image-based postimplant dosimetry methods in permanent seed implantation. Between October 1999 and October 2002, 150 patients with low-risk prostate carcinoma were treated with (125)I and (103)Pd in our institution. A CT-MRI image fusion protocol was used in 21 consecutive patients treated with exclusive brachytherapy. The accuracy and reproducibility of the method was calculated, and then the CT-based dosimetry was compared with the CT-MRI-based dosimetry using the dose-volume histogram (DVH) related parameters recommended by the American Brachytherapy Society and the American Association of Physicists in Medicine. Our method for CT-MRI image fusion was accurate and reproducible (median shift <1 mm). Differences in prostate volume were found, depending on the image modality used. Quality assurance DVH-related parameters strongly depended on the image modality (CT vs. CT-MRI): V(100) = 82% vs. 88%, p < 0.05. D(90) = 96% vs. 115%, p < 0.05. Those results depend on the institutional implant technique and reflect the importance of lowering inter- and intraobserver discrepancies when outlining prostate and organs at risk for postimplant dosimetry. Computed tomography-MRI fused images allow accurate determination of prostate size, significantly improving the dosimetric evaluation based on DVH analysis. This provides a consistent method to judge a prostate seed implant's quality.

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.

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

Structural Magnetic Resonance Imaging Markers of Alzheimer's Disease and Its Retranslation to Rodent Models.

PubMed

Kincses, Zsigmond Tamas; Király, András; Veréb, Dániel; Vécsei, László

2015-01-01

The importance of imaging biomarkers has been acknowledged in the diagnosis and in the follow-up of Alzheimer's disease (AD), one of the major causes of dementia. Next to the molecular biomarkers and PET imaging investigations, structural MRI approaches provide important information about the disease progression and about the pathomechanism. Furthermore,a growing body of literature retranslates these imaging biomarkers to various rodent models of the disease. The goal of this review is to provide an overview of the macro- and microstructural imaging biomarkers of AD, concentrating on atrophy measures and diffusion MRI alterations. A survey is also given of the imaging approaches used in rodent models of dementias that can promote drug development.

MRI-based morphometric characterizations of sexual dimorphism of the cerebrum of ferrets (Mustela putorius).

PubMed

Sawada, Kazuhiko; Horiuchi-Hirose, Miwa; Saito, Shigeyoshi; Aoki, Ichio

2013-12-01

The present study aimed to characterize cerebral morphology in young adult ferrets and its sexual dimorphism using high-field MRI and MRI-based morphometry. Ex vivo short TR/TE (typical T1-weighted parameter setting for conventional MRI) and T2W (long TR/TE) MRI with high spatial resolution at 7-tesla could visualize major subcortical and archicortical structures, i.e., the caudate nucleus, lentiform nucleus, amygdala and hippocampus. In particular, laminar organization of the olfactory bulb was identifiable by short TR/TE-MRI. The primary and secondary sulci observable in the adult ferret were distinguishable on either short TR/TE- or T2W-MRI, and the cortical surface morphology was reproduced well by 3D-rendered images obtained by short TR/TE-MRI. The cerebrum had a significantly lower volume in females than in males, which was attributed to region-specific volume reduction in the cerebral cortex and subcortical white matter in females. A sexual difference was also detected, manifested by an overall reduction in normalized signal ratios of short TR/TE-MRI in all cerebral structures examined in females than in males. On the other hand, an alternating array of higher and lower short TR/TE-MRI intensity transverse zones throughout the cortex, which was reminiscent of the functional cortical areas, was revealed by maximum intensity projection (MIP) in 3D. The normalized signal ratio of short TR/TE-MRI, but not T2W-MRI in the cortex, was negatively correlated with the density of myelin-basic protein immunoreactive fibers (males, r=-0.440; females, r=-0.481). The present results suggest that sexual differences in the adult ferret cerebrum are characterized by reduced volumes of the cerebral cortex and subcortical white matter in females, and by overall reductions in physiochemical characteristics, as obtained by short TR/TE-MRI, in females. It should be noted that short TR/TE-MRI-based MIP delineated functional cortical areas related to myeloarchitecture in 3D. Such an approach makes possible conventional investigation of the functional organization of the cerebral cortex and its abnormalities using high-field MRI. Copyright © 2013 Elsevier Inc. All rights reserved.

Real time 3D visualization of intraoperative organ deformations using structured dictionary.

PubMed

Wang, Dan; Tewfik, Ahmed H

2012-04-01

Restricted visualization of the surgical field is one of the most critical challenges for minimally invasive surgery (MIS). Current intraoperative visualization systems are promising. However, they can hardly meet the requirements of high resolution and real time 3D visualization of the surgical scene to support the recognition of anatomic structures for safe MIS procedures. In this paper, we present a new approach for real time 3D visualization of organ deformations based on optical imaging patches with limited field-of-view and a single preoperative scan of magnetic resonance imaging (MRI) or computed tomography (CT). The idea for reconstruction is motivated by our empirical observation that the spherical harmonic coefficients corresponding to distorted surfaces of a given organ lie in lower dimensional subspaces in a structured dictionary that can be learned from a set of representative training surfaces. We provide both theoretical and practical designs for achieving these goals. Specifically, we discuss details about the selection of limited optical views and the registration of partial optical images with a single preoperative MRI/CT scan. The design proposed in this paper is evaluated with both finite element modeling data and ex vivo experiments. The ex vivo test is conducted on fresh porcine kidneys using 3D MRI scans with 1.2 mm resolution and a portable laser scanner with an accuracy of 0.13 mm. Results show that the proposed method achieves a sub-3 mm spatial resolution in terms of Hausdorff distance when using only one preoperative MRI scan and the optical patch from the single-sided view of the kidney. The reconstruction frame rate is between 10 frames/s and 39 frames/s depending on the complexity of the test model.

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.

Individual white matter fractional anisotropy analysis on patients with MRI negative partial epilepsy.

PubMed

Duning, Thomas; Kellinghaus, Christoph; Mohammadi, Siawoosh; Schiffbauer, Hagen; Keller, Simon; Ringelstein, E Bernd; Knecht, Stefan; Deppe, Michael

2010-02-01

Conventional structural MRI fails to identify a cerebral lesion in 25% of patients with cryptogenic partial epilepsy (CPE). Diffusion tensor imaging is an MRI technique sensitive to microstructural abnormalities of cerebral white matter (WM) by quantification of fractional anisotropy (FA). The objectives of the present study were to identify focal FA abnormalities in patients with CPE who were deemed MRI negative during routine presurgical evaluation. Diffusion tensor imaging at 3 T was performed in 12 patients with CPE and normal conventional MRI and in 67 age matched healthy volunteers. WM integrity was compared between groups on the basis of automated voxel-wise statistics of FA maps using an analysis of covariance. Volumetric measurements from high resolution T1-weighted images were also performed. Significant FA reductions in WM regions encompassing diffuse areas of the brain were observed when all patients as a group were compared with controls. On an individual basis, voxel based analyses revealed widespread symmetrical FA reduction in CPE patients. Furthermore, asymmetrical temporal lobe FA reduction was consistently ipsilateral to the electroclinical focus. No significant correlations were found between FA alterations and clinical data. There were no differences in brain volumes of CPE patients compared with controls. Despite normal conventional MRI, WM integrity abnormalities in CPE patients extend far beyond the epileptogenic zone. Given that unilateral temporal lobe FA abnormalities were consistently observed ipsilateral to the seizure focus, analysis of temporal FA may provide an informative in vivo investigation into the localisation of the epileptogenic zone in MRI negative patients.

SU-E-J-264: Using Magnetic Resonance Imaging-Derived Features to Quantify Radiotherapy-Induced Normal Tissue Morbidity

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

Thor, M; Tyagi, N; Deasy, J

2015-06-15

Purpose: The aim of this study was to explore the use of Magnetic Resonance Imaging (MRI)-derived features as indicators of Radiotherapy (RT)-induced normal tissue morbidity. We also investigate the relationship between these features and RT dose in four critical structures. Methods: We demonstrate our approach for four patients treated with RT for base of tongue cancer in 2005–2007. For each patient, two MRI scans (T1-weighted pre (T1pre) and post (T1post) gadolinium contrast-enhancement) were acquired within the first six months after RT. The assessed morbidity endpoint observed in 2/4 patients was Grade 2+ CTCAEv.3 trismus. Four ipsilateral masticatory-related structures (masseter, lateralmore » and medial pterygoid, and the temporal muscles) were delineated on both T1pre and T1post and these scans were co-registered to the treatment planning CT using a deformable demons algorithm. For each structure, the maximum and mean RT dose, and six MRI-derived features (the second order texture features entropy and homogeneity, and the first order mean, median, kurtosis, and skewness) were extracted and compared structure-wise between patients with and without trismus. All MRI-derived features were calculated as the difference between T1pre and T1post, ΔS. Results: For 5/6 features and all structures, ΔS diverged between trismus and non-trismus patients particularly for the masseter, lateral pterygoid, and temporal muscles using the kurtosis feature (−0.2 vs. 6.4 for lateral pterygoid). Both the maximum and mean RT dose in all four muscles were higher amongst the trismus patients (with the maximum dose being up to 25 Gy higher). Conclusion: Using MRI-derived features to quantify RT-induced normal tissue complications is feasible. We showed that several features are different between patients with and without morbidity and that the RT dose in all investigated structures are higher amongst patients with morbidity. MRI-derived features, therefore, has the potential to improve predictions of normal tissue morbidity.« less

A Feature-based Developmental Model of the Infant Brain in Structural MRI

PubMed Central

Toews, Matthew; Wells, William M.; Zöllei, Lilla

2014-01-01

In this paper, anatomical development is modeled as a collection of distinctive image patterns localized in space and time. A Bayesian posterior probability is defined over a random variable of subject age, conditioned on data in the form of scale-invariant image features. The model is automatically learned from a large set of images exhibiting significant variation, used to discover anatomical structure related to age and development, and fit to new images to predict age. The model is applied to a set of 230 infant structural MRIs of 92 subjects acquired at multiple sites over an age range of 8-590 days. Experiments demonstrate that the model can be used to identify age-related anatomical structure, and to predict the age of new subjects with an average error of 72 days. PMID:23286050

Automated assessment of thigh composition using machine learning for Dixon magnetic resonance images.

PubMed

Yang, Yu Xin; Chong, Mei Sian; Tay, Laura; Yew, Suzanne; Yeo, Audrey; Tan, Cher Heng

2016-10-01

To develop and validate a machine learning based automated segmentation method that jointly analyzes the four contrasts provided by Dixon MRI technique for improved thigh composition segmentation accuracy. The automatic detection of body composition is formulized as a three-class classification issue. Each image voxel in the training dataset is assigned with a correct label. A voxel classifier is trained and subsequently used to predict unseen data. Morphological operations are finally applied to generate volumetric segmented images for different structures. We applied this algorithm on datasets of (1) four contrast images, (2) water and fat images, and (3) unsuppressed images acquired from 190 subjects. The proposed method using four contrasts achieved most accurate and robust segmentation compared to the use of combined fat and water images and the use of unsuppressed image, average Dice coefficients of 0.94 ± 0.03, 0.96 ± 0.03, 0.80 ± 0.03, and 0.97 ± 0.01 has been achieved to bone region, subcutaneous adipose tissue (SAT), inter-muscular adipose tissue (IMAT), and muscle respectively. Our proposed method based on machine learning produces accurate tissue quantification and showed an effective use of large information provided by the four contrast images from Dixon MRI.

Assessment of pulmonary structure-function relationships in young children and adolescents with cystic fibrosis by multivolume proton-MRI and CT.

PubMed

Pennati, Francesca; Roach, David J; Clancy, John P; Brody, Alan S; Fleck, Robert J; Aliverti, Andrea; Woods, Jason C

2018-02-19

Lung disease is the most frequent cause of morbidity and mortality in patients with cystic fibrosis (CF), and there is a shortage of sensitive biomarkers able to regionally monitor disease progression and to assess early responses to therapy. To determine the feasibility of noncontrast-enhanced multivolume MRI, which assesses intensity changes between expiratory and inspiratory breath-hold images, to detect and quantify regional ventilation abnormalities in CF lung disease, with a focus on the structure-function relationship. Retrospective. Twenty-nine subjects, including healthy young children (n = 9, 7-37 months), healthy adolescents (n = 4, 14-22 years), young children with CF lung disease (n = 10, 7-47 months), and adolescents with CF lung disease (n = 6, 8-18 years) were studied. 3D spoiled gradient-recalled sequence at 1.5T. Subjects were scanned during breath-hold at functional residual capacity (FRC) and total lung capacity (TLC) through noncontrast-enhanced MRI and CT. Expiratory-inspiratory differences in MR signal-intensity (Δ 1 H-MRI) and CT-density (ΔHU) were computed to estimate regional ventilation. MR and CT images were also evaluated using a CF-specific scoring system. Quadratic regression, Spearman's correlation, one-way analysis of variance (ANOVA). Δ 1 H-MRI maps were sensitive to ventilation heterogeneity related to gravity dependence in healthy lung and to ventilation impairment in CF lung disease. A high correlation was found between MRI and CT ventilation maps (R 2  = 0.79, P < 0.001). Globally, Δ 1 H-MRI and ΔHU decrease with increasing morphological score (respectively, R 2  = 0.56, P < 0.001 and R 2  = 0.31, P < 0.001). Locally, Δ 1 H-MRI was higher in healthy regions (median 15%) compared to regions with bronchiectasis, air trapping, consolidation, and to segments fed by airways with bronchial wall thickening (P < 0.001). Multivolume noncontrast-enhanced MRI, as a nonionizing imaging modality that can be used on nearly any MRI scanner without specialized equipment or gaseous tracers, may be particularly valuable in CF care, providing a new imaging biomarker to detect early alterations in regional lung structure-function. 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Multi-atlas and label fusion approach for patient-specific MRI based skull estimation.

PubMed

Torrado-Carvajal, Angel; Herraiz, Joaquin L; Hernandez-Tamames, Juan A; San Jose-Estepar, Raul; Eryaman, Yigitcan; Rozenholc, Yves; Adalsteinsson, Elfar; Wald, Lawrence L; Malpica, Norberto

2016-04-01

MRI-based skull segmentation is a useful procedure for many imaging applications. This study describes a methodology for automatic segmentation of the complete skull from a single T1-weighted volume. The skull is estimated using a multi-atlas segmentation approach. Using a whole head computed tomography (CT) scan database, the skull in a new MRI volume is detected by nonrigid image registration of the volume to every CT, and combination of the individual segmentations by label-fusion. We have compared Majority Voting, Simultaneous Truth and Performance Level Estimation (STAPLE), Shape Based Averaging (SBA), and the Selective and Iterative Method for Performance Level Estimation (SIMPLE) algorithms. The pipeline has been evaluated quantitatively using images from the Retrospective Image Registration Evaluation database (reaching an overlap of 72.46 ± 6.99%), a clinical CT-MR dataset (maximum overlap of 78.31 ± 6.97%), and a whole head CT-MRI pair (maximum overlap 78.68%). A qualitative evaluation has also been performed on MRI acquisition of volunteers. It is possible to automatically segment the complete skull from MRI data using a multi-atlas and label fusion approach. This will allow the creation of complete MRI-based tissue models that can be used in electromagnetic dosimetry applications and attenuation correction in PET/MR. © 2015 Wiley Periodicals, Inc.

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.

Competitive Advantage of PET/MRI

PubMed Central

Jadvar, Hossein; Colletti, Patrick M.

2013-01-01

Multimodality imaging has made great strides in the imaging evaluation of patients with a variety of diseases. Positron emission tomography/computed tomography (PET/CT) is now established as the imaging modality of choice in many clinical conditions, particularly in oncology. While the initial development of combined PET/magnetic resonance imaging (PET/MRI) was in the preclinical arena, hybrid PET/MR scanners are now available for clinical use. PET/MRI combines the unique features of MRI including excellent soft tissue contrast, diffusion-weighted imaging, dynamic contrast-enhanced imaging, fMRI and other specialized sequences as well as MR spectroscopy with the quantitative physiologic information that is provided by PET. Most evidence for the potential clinical utility of PET/MRI is based on studies performed with side-by-side comparison or software-fused MRI and PET images. Data on distinctive utility of hybrid PET/MRI are rapidly emerging. There are potential competitive advantages of PET/MRI over PET/CT. In general, PET/MRI may be preferred over PET/CT where the unique features of MRI provide more robust imaging evaluation in certain clinical settings. The exact role and potential utility of simultaneous data acquisition in specific research and clinical settings will need to be defined. It may be that simultaneous PET/MRI will be best suited for clinical situations that are disease-specific, organ-specific, related to diseases of the children or in those patients undergoing repeated imaging for whom cumulative radiation dose must be kept as low as reasonably achievable. PET/MRI also offers interesting opportunities for use of dual modality probes. Upon clear definition of clinical utility, other important and practical issues related to business operational model, clinical workflow and reimbursement will also be resolved. PMID:23791129

Competitive advantage of PET/MRI.

PubMed

Jadvar, Hossein; Colletti, Patrick M

2014-01-01

Multimodality imaging has made great strides in the imaging evaluation of patients with a variety of diseases. Positron emission tomography/computed tomography (PET/CT) is now established as the imaging modality of choice in many clinical conditions, particularly in oncology. While the initial development of combined PET/magnetic resonance imaging (PET/MRI) was in the preclinical arena, hybrid PET/MR scanners are now available for clinical use. PET/MRI combines the unique features of MRI including excellent soft tissue contrast, diffusion-weighted imaging, dynamic contrast-enhanced imaging, fMRI and other specialized sequences as well as MR spectroscopy with the quantitative physiologic information that is provided by PET. Most evidence for the potential clinical utility of PET/MRI is based on studies performed with side-by-side comparison or software-fused MRI and PET images. Data on distinctive utility of hybrid PET/MRI are rapidly emerging. There are potential competitive advantages of PET/MRI over PET/CT. In general, PET/MRI may be preferred over PET/CT where the unique features of MRI provide more robust imaging evaluation in certain clinical settings. The exact role and potential utility of simultaneous data acquisition in specific research and clinical settings will need to be defined. It may be that simultaneous PET/MRI will be best suited for clinical situations that are disease-specific, organ-specific, related to diseases of the children or in those patients undergoing repeated imaging for whom cumulative radiation dose must be kept as low as reasonably achievable. PET/MRI also offers interesting opportunities for use of dual modality probes. Upon clear definition of clinical utility, other important and practical issues related to business operational model, clinical workflow and reimbursement will also be resolved. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Gender differences in the structural connectome of the teenage brain revealed by generalized q-sampling MRI.

PubMed

Tyan, Yeu-Sheng; Liao, Jan-Ray; Shen, Chao-Yu; Lin, Yu-Chieh; Weng, Jun-Cheng

2017-01-01

The question of whether there are biological differences between male and female brains is a fraught one, and political positions and prior expectations seem to have a strong influence on the interpretation of scientific data in this field. This question is relevant to issues of gender differences in the prevalence of psychiatric conditions, including autism, attention deficit hyperactivity disorder (ADHD), Tourette's syndrome, schizophrenia, dyslexia, depression, and eating disorders. Understanding how gender influences vulnerability to these conditions is significant. Diffusion magnetic resonance imaging (dMRI) provides a non-invasive method to investigate brain microstructure and the integrity of anatomical connectivity. Generalized q-sampling imaging (GQI) has been proposed to characterize complicated fiber patterns and distinguish fiber orientations, providing an opportunity for more accurate, higher-order descriptions through the water diffusion process. Therefore, we aimed to investigate differences in the brain's structural network between teenage males and females using GQI. This study included 59 (i.e., 33 males and 26 females) age- and education-matched subjects (age range: 13 to 14 years). The structural connectome was obtained by graph theoretical and network-based statistical (NBS) analyses. Our findings show that teenage male brains exhibit better intrahemispheric communication, and teenage female brains exhibit better interhemispheric communication. Our results also suggest that the network organization of teenage male brains is more local, more segregated, and more similar to small-world networks than teenage female brains. We conclude that the use of an MRI study with a GQI-based structural connectomic approach like ours presents novel insights into network-based systems of the brain and provides a new piece of the puzzle regarding gender differences.

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.

Changes in Gray Matter Density, Regional Homogeneity, and Functional Connectivity in Methamphetamine-Associated Psychosis: A Resting-State Functional Magnetic Resonance Imaging (fMRI) Study.

PubMed

Zhang, Shengyu; Hu, Qiang; Tang, Tao; Liu, Chao; Li, Chengchong; Zang, Yin-Yin; Cai, Wei-Xiong

2018-06-13

BACKGROUND Using regional homogeneity (ReHo) blood oxygen level-dependent functional MR (BOLD-fMRI), we investigated the structural and functional alterations of brain regions among patients with methamphetamine-associated psychosis (MAP). MATERIAL AND METHODS This retrospective study included 17 MAP patients, 16 schizophrenia (SCZ) patients, and 18 healthy controls. Informed consent was obtained from all patients before the clinical assessment, the severity of clinical symptoms was evaluated prior to the fMRI scanning, and then images were acquired and preprocessed after each participant received 6-min fRMI scanning. The participants all underwent BOLD-fMRI scanning. Voxel-based morphometry was used to measure gray matter density (GMD). Resting-state fMRI (rs-fMRI) was conducted to analyze functional MR, ReHo, and functional connectivity (FC). RESULTS GMD analysis results suggest that MAP patients, SCZ patients, and healthy volunteers show different GMDs within different brain regions. Similarly, the ReHo analysis results suggest that MAP patients, SCZ patients, and healthy volunteers have different GMDs within different brain regions. Negative correlations were found between ReHo- and the PANSS-positive scores within the left orbital interior frontal gyrus (L-orb-IFG) of MAP patients. ReHo- and PANSS-negative scores of R-SFG were negatively correlated among SCZ patients. The abnormal FC of R-MFG showed a negative correlation with the PANSS score among MAP patients. CONCLUSIONS The abnormalities in brain structure and FC were associated with the development of MAP.

Brain tumor segmentation using holistically nested neural networks in MRI images.

PubMed

Zhuge, Ying; Krauze, Andra V; Ning, Holly; Cheng, Jason Y; Arora, Barbara C; Camphausen, Kevin; Miller, Robert W

2017-10-01

Gliomas are rapidly progressive, neurologically devastating, largely fatal brain tumors. Magnetic resonance imaging (MRI) is a widely used technique employed in the diagnosis and management of gliomas in clinical practice. MRI is also the standard imaging modality used to delineate the brain tumor target as part of treatment planning for the administration of radiation therapy. Despite more than 20 yr of research and development, computational brain tumor segmentation in MRI images remains a challenging task. We are presenting a novel method of automatic image segmentation based on holistically nested neural networks that could be employed for brain tumor segmentation of MRI images. Two preprocessing techniques were applied to MRI images. The N4ITK method was employed for correction of bias field distortion. A novel landmark-based intensity normalization method was developed so that tissue types have a similar intensity scale in images of different subjects for the same MRI protocol. The holistically nested neural networks (HNN), which extend from the convolutional neural networks (CNN) with a deep supervision through an additional weighted-fusion output layer, was trained to learn the multiscale and multilevel hierarchical appearance representation of the brain tumor in MRI images and was subsequently applied to produce a prediction map of the brain tumor on test images. Finally, the brain tumor was obtained through an optimum thresholding on the prediction map. The proposed method was evaluated on both the Multimodal Brain Tumor Image Segmentation (BRATS) Benchmark 2013 training datasets, and clinical data from our institute. A dice similarity coefficient (DSC) and sensitivity of 0.78 and 0.81 were achieved on 20 BRATS 2013 training datasets with high-grade gliomas (HGG), based on a two-fold cross-validation. The HNN model built on the BRATS 2013 training data was applied to ten clinical datasets with HGG from a locally developed database. DSC and sensitivity of 0.83 and 0.85 were achieved. A quantitative comparison indicated that the proposed method outperforms the popular fully convolutional network (FCN) method. In terms of efficiency, the proposed method took around 10 h for training with 50,000 iterations, and approximately 30 s for testing of a typical MRI image in the BRATS 2013 dataset with a size of 160 × 216 × 176, using a DELL PRECISION workstation T7400, with an NVIDIA Tesla K20c GPU. An effective brain tumor segmentation method for MRI images based on a HNN has been developed. The high level of accuracy and efficiency make this method practical in brain tumor segmentation. It may play a crucial role in both brain tumor diagnostic analysis and in the treatment planning of radiation therapy. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

"MRI Stealth" robot for prostate interventions.

PubMed

Stoianovici, Dan; Song, Danny; Petrisor, Doru; Ursu, Daniel; Mazilu, Dumitru; Muntener, Michael; Mutener, Michael; Schar, Michael; Patriciu, Alexandru

2007-01-01

The paper reports an important achievement in MRI instrumentation, a pneumatic, fully actuated robot located within the scanner alongside the patient and operating under remote control based on the images. Previous MRI robots commonly used piezoelectric actuation limiting their compatibility. Pneumatics is an ideal choice for MRI compatibility because it is decoupled from electromagnetism, but pneumatic actuators were hardly controllable. This achievement was possible due to a recent technology breakthrough, the invention of a new type of pneumatic motor, PneuStep 1, designed for the robot reported here with uncompromised MRI compatibility, high-precision, and medical safety. MrBot is one of the "MRI stealth" robots today (the second is described in this issue by Zangos et al.). Both of these systems are also multi-imager compatible, being able to operate with the imager of choice or cross-imaging modalities. For MRI compatibility the robot is exclusively constructed of nonmagnetic and dielectric materials such as plastics, ceramics, crystals, rubbers and is electricity free. Light-based encoding is used for feedback, so that all electric components are distally located outside the imager's room. MRI robots are modern, digital medical instruments in line with advanced imaging equipment and methods. These allow for accessing patients within closed bore scanners and performing interventions under direct (in scanner) imaging feedback. MRI robots could allow e.g. to biopsy small lesions imaged with cutting edge cancer imaging methods, or precisely deploy localized therapy at cancer foci. Our robot is the first to show the feasibility of fully automated in-scanner interventions. It is customized for the prostate and operates transperineally for needle interventions. It can accommodate various needle drivers for different percutaneous procedures such as biopsy, thermal ablations, or brachytherapy. The first needle driver is customized for fully automated low-dose radiation seed brachytherapy. This paper gives an introduction to the challenges of MRI robot compatibility and presents the solutions adopted in making the MrBot. Its multi-imager compatibility and other preclinical tests are included. The robot shows the technical feasibility of MRI-guided prostate interventions, yet its clinical utility is still to be determined.

Continuous EEG source imaging enhances analysis of EEG-fMRI in focal epilepsy.

PubMed

Vulliemoz, S; Rodionov, R; Carmichael, D W; Thornton, R; Guye, M; Lhatoo, S D; Michel, C M; Duncan, J S; Lemieux, L

2010-02-15

EEG-correlated fMRI (EEG-fMRI) studies can reveal haemodynamic changes associated with Interictal Epileptic Discharges (IED). Methodological improvements are needed to increase sensitivity and specificity for localising the epileptogenic zone. We investigated whether the estimated EEG source activity improved models of the BOLD changes in EEG-fMRI data, compared to conventional < event-related > designs based solely on the visual identification of IED. Ten patients with pharmaco-resistant focal epilepsy underwent EEG-fMRI. EEG Source Imaging (ESI) was performed on intra-fMRI averaged IED to identify the irritative zone. The continuous activity of this estimated IED source (cESI) over the entire recording was used for fMRI analysis (cESI model). The maps of BOLD signal changes explained by cESI were compared to results of the conventional IED-related model. ESI was concordant with non-invasive data in 13/15 different types of IED. The cESI model explained significant additional BOLD variance in regions concordant with video-EEG, structural MRI or, when available, intracranial EEG in 10/15 IED. The cESI model allowed better detection of the BOLD cluster, concordant with intracranial EEG in 4/7 IED, compared to the IED model. In 4 IED types, cESI-related BOLD signal changes were diffuse with a pattern suggestive of contamination of the source signal by artefacts, notably incompletely corrected motion and pulse artefact. In one IED type, there was no significant BOLD change with either model. Continuous EEG source imaging can improve the modelling of BOLD changes related to interictal epileptic activity and this may enhance the localisation of the irritative zone. Copyright 2009 Elsevier Inc. All rights reserved.

Visualizing the anatomical-functional correlation of the human brain

NASA Astrophysics Data System (ADS)

Chang, YuKuang; Rockwood, Alyn P.; Reiman, Eric M.

1995-04-01

Three-dimensional tomographic images obtained from different modalities or from the same modality at different times provide complementary information. For example, while PET shows brain function, images from MRI identify anatomical structures. In this paper, we investigate the problem of displaying available information about structures and function together. Several steps are described to achieve our goal. These include segmentation of the data, registration, resampling, and display. Segmentation is used to identify brain tissue from surrounding tissues, especially in the MRI data. Registration aligns the different modalities as closely as possible. Resampling arises from the registration since two data sets do not usually correspond and the rendering method is most easily achieved if the data correspond to the same grid used in display. We combine several techniques to display the data. MRI data is reconstructed from 2D slices into 3D structures from which isosurfaces are extracted and represented by approximating polygonalizations. These are then displayed using standard graphics pipelines including shaded and transparent images. PET data measures the qualitative rates of cerebral glucose utilization or oxygen consumption. PET image is best displayed as a volume of luminous particles. The combination of both display methods allows the viewer to compare the functional information contained in the PET data with the anatomically more precise MRI data.

CAIPIRINHA accelerated SPACE enables 10-min isotropic 3D TSE MRI of the ankle for optimized visualization of curved and oblique ligaments and tendons.

PubMed

Kalia, Vivek; Fritz, Benjamin; Johnson, Rory; Gilson, Wesley D; Raithel, Esther; Fritz, Jan

2017-09-01

To test the hypothesis that a fourfold CAIPIRINHA accelerated, 10-min, high-resolution, isotropic 3D TSE MRI prototype protocol of the ankle derives equal or better quality than a 20-min 2D TSE standard protocol. Following internal review board approval and informed consent, 3-Tesla MRI of the ankle was obtained in 24 asymptomatic subjects including 10-min 3D CAIPIRINHA SPACE TSE prototype and 20-min 2D TSE standard protocols. Outcome variables included image quality and visibility of anatomical structures using 5-point Likert scales. Non-parametric statistical testing was used. P values ≤0.001 were considered significant. Edge sharpness, contrast resolution, uniformity, noise, fat suppression and magic angle effects were without statistical difference on 2D and 3D TSE images (p > 0.035). Fluid was mildly brighter on intermediate-weighted 2D images (p < 0.001), whereas 3D images had substantially less partial volume, chemical shift and no pulsatile-flow artifacts (p < 0.001). Oblique and curved planar 3D images resulted in mildly-to-substantially improved visualization of joints, spring, bifurcate, syndesmotic, collateral and sinus tarsi ligaments, and tendons (p < 0.001, respectively). 3D TSE MRI with CAIPIRINHA acceleration enables high-spatial resolution oblique and curved planar MRI of the ankle and visualization of ligaments, tendons and joints equally well or better than a more time-consuming anisotropic 2D TSE MRI. • High-resolution 3D TSE MRI improves visualization of ankle structures. • Limitations of current 3D TSE MRI include long scan times. • 3D CAIPIRINHA SPACE allows now a fourfold-accelerated data acquisition. • 3D CAIPIRINHA SPACE enables high-spatial-resolution ankle MRI within 10 min. • 10-min 3D CAIPIRINHA SPACE produces equal-or-better quality than 20-min 2D TSE.

In Amnio MRI of Mouse Embryos

PubMed Central

Roberts, Thomas A.; Norris, Francesca C.; Carnaghan, Helen; Savery, Dawn; Wells, Jack A.; Siow, Bernard; Scambler, Peter J.; Pierro, Agostino; De Coppi, Paolo; Eaton, Simon; Lythgoe, Mark F.

2014-01-01

Mouse embryo imaging is conventionally carried out on ex vivo embryos excised from the amniotic sac, omitting vital structures and abnormalities external to the body. Here, we present an in amnio MR imaging methodology in which the mouse embryo is retained in the amniotic sac and demonstrate how important embryonic structures can be visualised in 3D with high spatial resolution (100 µm/px). To illustrate the utility of in amnio imaging, we subsequently apply the technique to examine abnormal mouse embryos with abdominal wall defects. Mouse embryos at E17.5 were imaged and compared, including three normal phenotype embryos, an abnormal embryo with a clear exomphalos defect, and one with a suspected gastroschisis phenotype. Embryos were excised from the mother ensuring the amnion remained intact and stereo microscopy was performed. Embryos were next embedded in agarose for 3D, high resolution MRI on a 9.4T scanner. Identification of the abnormal embryo phenotypes was not possible using stereo microscopy or conventional ex vivo MRI. Using in amnio MRI, we determined that the abnormal embryos had an exomphalos phenotype with varying severities. In amnio MRI is ideally suited to investigate the complex relationship between embryo and amnion, together with screening for other abnormalities located outside of the mouse embryo, providing a valuable complement to histology and existing imaging methods available to the phenotyping community. PMID:25330230

Locally Enhanced Image Quality with Tunable Hybrid Metasurfaces

NASA Astrophysics Data System (ADS)

Shchelokova, Alena V.; Slobozhanyuk, Alexey P.; Melchakova, Irina V.; Glybovski, Stanislav B.; Webb, Andrew G.; Kivshar, Yuri S.; Belov, Pavel A.

2018-01-01

Metasurfaces represent a new paradigm in artificial subwavelength structures due to their potential to overcome many challenges typically associated with bulk metamaterials. The ability to make very thin structures and change their properties dynamically makes metasurfaces an exceptional meta-optics platform for engineering advanced electromagnetic and photonic metadevices. Here, we suggest and demonstrate experimentally a tunable metasurface capable of enhancing significantly the local image quality in magnetic resonance imaging. We present a design of the hybrid metasurface based on electromagnetically coupled dielectric and metallic elements. We demonstrate how to tailor the spectral characteristics of the metasurface eigenmodes by changing dynamically the effective permittivity of the structure. By maximizing a coupling between metasurface eigenmodes and transmitted and received fields in the magnetic resonance imaging (MRI) system, we enhance the device sensitivity that results in a substantial improvement of the image quality.

Structural Abnormalities on Magnetic Resonance Imaging in Patients With Patellofemoral Pain: A Cross-sectional Case-Control Study.

PubMed

van der Heijden, Rianne A; de Kanter, Janneke L M; Bierma-Zeinstra, Sita M A; Verhaar, Jan A N; van Veldhoven, Peter L J; Krestin, Gabriel P; Oei, Edwin H G; van Middelkoop, Marienke

2016-09-01

Structural abnormalities of the patellofemoral joint might play a role in the pathogenesis of patellofemoral pain (PFP), a common knee problem among young and physically active individuals. No previous study has investigated if PFP is associated with structural abnormalities of the patellofemoral joint using high-resolution magnetic resonance imaging (MRI). To investigate the presence of structural abnormalities of the patellofemoral joint on high-resolution MRI in patients with PFP compared with healthy control subjects. Cross-sectional study; Level of evidence, 3. Patients with PFP and healthy control subjects between 14 and 40 years of age underwent high-resolution 3-T MRI. All images were scored using the Magnetic Resonance Imaging Osteoarthritis Knee Score with the addition of specific patellofemoral features. Associations between PFP and the presence of structural abnormalities were analyzed using logistic regression analyses adjusted for age, body mass index (BMI), sex, and sports participation. A total of 64 patients and 70 control subjects were included in the study. Mean ± SD age was 23.2 ± 6.4 years, mean BMI ± SD was 22.9 ± 3.4 kg/m(2), and 56.7% were female. Full-thickness cartilage loss was not present. Minor patellar cartilage defects, patellar bone marrow lesions, and high signal intensity of the Hoffa fat pad were frequently seen in both patients (23%, 53%, and 58%, respectively) and control subjects (21%, 51%, and 51%, respectively). After adjustment for age, BMI, sex, and sports participation, none of the structural abnormalities were statistically significantly associated with PFP. Structural abnormalities of the patellofemoral joint have been hypothesized as a factor in the pathogenesis of PFP, but the study findings suggest that structural abnormalities of the patellofemoral joint on MRI are not associated with PFP. © 2016 The Author(s).

Discriminative analysis of schizophrenia using support vector machine and recursive feature elimination on structural MRI images.

PubMed

Lu, Xiaobing; Yang, Yongzhe; Wu, Fengchun; Gao, Minjian; Xu, Yong; Zhang, Yue; Yao, Yongcheng; Du, Xin; Li, Chengwei; Wu, Lei; Zhong, Xiaomei; Zhou, Yanling; Fan, Ni; Zheng, Yingjun; Xiong, Dongsheng; Peng, Hongjun; Escudero, Javier; Huang, Biao; Li, Xiaobo; Ning, Yuping; Wu, Kai

2016-07-01

Structural abnormalities in schizophrenia (SZ) patients have been well documented with structural magnetic resonance imaging (MRI) data using voxel-based morphometry (VBM) and region of interest (ROI) analyses. However, these analyses can only detect group-wise differences and thus, have a poor predictive value for individuals. In the present study, we applied a machine learning method that combined support vector machine (SVM) with recursive feature elimination (RFE) to discriminate SZ patients from normal controls (NCs) using their structural MRI data. We first employed both VBM and ROI analyses to compare gray matter volume (GMV) and white matter volume (WMV) between 41 SZ patients and 42 age- and sex-matched NCs. The method of SVM combined with RFE was used to discriminate SZ patients from NCs using significant between-group differences in both GMV and WMV as input features. We found that SZ patients showed GM and WM abnormalities in several brain structures primarily involved in the emotion, memory, and visual systems. An SVM with a RFE classifier using the significant structural abnormalities identified by the VBM analysis as input features achieved the best performance (an accuracy of 88.4%, a sensitivity of 91.9%, and a specificity of 84.4%) in the discriminative analyses of SZ patients. These results suggested that distinct neuroanatomical profiles associated with SZ patients might provide a potential biomarker for disease diagnosis, and machine-learning methods can reveal neurobiological mechanisms in psychiatric diseases.

Identification and characterisation of midbrain nuclei using optimised functional magnetic resonance imaging

PubMed Central

Limbrick-Oldfield, Eve H.; Brooks, Jonathan C.W.; Wise, Richard J.S.; Padormo, Francesco; Hajnal, Jo V.; Beckmann, Christian F.; Ungless, Mark A.

2012-01-01

Localising activity in the human midbrain with conventional functional MRI (fMRI) is challenging because the midbrain nuclei are small and located in an area that is prone to physiological artefacts. Here we present a replicable and automated method to improve the detection and localisation of midbrain fMRI signals. We designed a visual fMRI task that was predicted would activate the superior colliculi (SC) bilaterally. A limited number of coronal slices were scanned, orientated along the long axis of the brainstem, whilst simultaneously recording cardiac and respiratory traces. A novel anatomical registration pathway was used to optimise the localisation of the small midbrain nuclei in stereotactic space. Two additional structural scans were used to improve registration between functional and structural T1-weighted images: an echo-planar image (EPI) that matched the functional data but had whole-brain coverage, and a whole-brain T2-weighted image. This pathway was compared to conventional registration pathways, and was shown to significantly improve midbrain registration. To reduce the physiological artefacts in the functional data, we estimated and removed structured noise using a modified version of a previously described physiological noise model (PNM). Whereas a conventional analysis revealed only unilateral SC activity, the PNM analysis revealed the predicted bilateral activity. We demonstrate that these methods improve the measurement of a biologically plausible fMRI signal. Moreover they could be used to investigate the function of other midbrain nuclei. PMID:21867762

Studying variability in human brain aging in a population-based German cohort-rationale and design of 1000BRAINS.

PubMed

Caspers, Svenja; Moebus, Susanne; Lux, Silke; Pundt, Noreen; Schütz, Holger; Mühleisen, Thomas W; Gras, Vincent; Eickhoff, Simon B; Romanzetti, Sandro; Stöcker, Tony; Stirnberg, Rüdiger; Kirlangic, Mehmet E; Minnerop, Martina; Pieperhoff, Peter; Mödder, Ulrich; Das, Samir; Evans, Alan C; Jöckel, Karl-Heinz; Erbel, Raimund; Cichon, Sven; Nöthen, Markus M; Sturma, Dieter; Bauer, Andreas; Jon Shah, N; Zilles, Karl; Amunts, Katrin

2014-01-01

The ongoing 1000 brains study (1000BRAINS) is an epidemiological and neuroscientific investigation of structural and functional variability in the human brain during aging. The two recruitment sources are the 10-year follow-up cohort of the German Heinz Nixdorf Recall (HNR) Study, and the HNR MultiGeneration Study cohort, which comprises spouses and offspring of HNR subjects. The HNR is a longitudinal epidemiological investigation of cardiovascular risk factors, with a comprehensive collection of clinical, laboratory, socioeconomic, and environmental data from population-based subjects aged 45-75 years on inclusion. HNR subjects underwent detailed assessments in 2000, 2006, and 2011, and completed annual postal questionnaires on health status. 1000BRAINS accesses these HNR data and applies a separate protocol comprising: neuropsychological tests of attention, memory, executive functions and language; examination of motor skills; ratings of personality, life quality, mood and daily activities; analysis of laboratory and genetic data; and state-of-the-art magnetic resonance imaging (MRI, 3 Tesla) of the brain. The latter includes (i) 3D-T1- and 3D-T2-weighted scans for structural analyses and myelin mapping; (ii) three diffusion imaging sequences optimized for diffusion tensor imaging, high-angular resolution diffusion imaging for detailed fiber tracking and for diffusion kurtosis imaging; (iii) resting-state and task-based functional MRI; and (iv) fluid-attenuated inversion recovery and MR angiography for the detection of vascular lesions and the mapping of white matter lesions. The unique design of 1000BRAINS allows: (i) comprehensive investigation of various influences including genetics, environment and health status on variability in brain structure and function during aging; and (ii) identification of the impact of selected influencing factors on specific cognitive subsystems and their anatomical correlates.

Fusing DTI and FMRI Data: A Survey of Methods and Applications

PubMed Central

Zhu, Dajiang; Zhang, Tuo; Jiang, Xi; Hu, Xintao; Chen, Hanbo; Yang, Ning; Lv, Jinglei; Han, Junwei; Guo, Lei; Liu, Tianming

2014-01-01

The relationship between brain structure and function has been one of the centers of research in neuroimaging for decades. In recent years, diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) techniques have been widely available and popular in cognitive and clinical neurosciences for examining the brain’s white matter (WM) micro-structures and gray matter (GM) functions, respectively. Given the intrinsic integration of WM/GM and the complementary information embedded in DTI/fMRI data, it is natural and well-justified to combine these two neuroimaging modalities together to investigate brain structure and function and their relationships simultaneously. In the past decade, there have been remarkable achievements of DTI/fMRI fusion methods and applications in neuroimaging and human brain mapping community. This survey paper aims to review recent advancements on methodologies and applications in incorporating multimodal DTI and fMRI data, and offer our perspectives on future research directions. We envision that effective fusion of DTI/fMRI techniques will play increasingly important roles in neuroimaging and brain sciences in the years to come. PMID:24103849

Catlas: An magnetic resonance imaging-based three-dimensional cortical atlas and tissue probability maps for the domestic cat (Felis catus).

PubMed

Stolzberg, Daniel; Wong, Carmen; Butler, Blake E; Lomber, Stephen G

2017-10-15

Brain atlases play an important role in effectively communicating results from neuroimaging studies in a standardized coordinate system. Furthermore, brain atlases extend analysis of functional magnetic resonance imaging (MRI) data by delineating regions of interest over which to evaluate the extent of functional activation as well as measures of inter-regional connectivity. Here, we introduce a three-dimensional atlas of the cat cerebral cortex based on established cytoarchitectonic and electrophysiological findings. In total, 71 cerebral areas were mapped onto the gray matter (GM) of an averaged T1-weighted structural MRI acquired at 7 T from eight adult domestic cats. In addition, a nonlinear registration procedure was used to generate a common template brain as well as GM, white matter, and cerebral spinal fluid tissue probability maps to facilitate tissue segmentation as part of the standard preprocessing pipeline for MRI data analysis. The atlas and associated files can also be used for planning stereotaxic surgery and for didactic purposes. © 2017 Wiley Periodicals, Inc.

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

Parcellation of the human orbitofrontal cortex based on gray matter volume covariance.

PubMed

Liu, Huaigui; Qin, Wen; Qi, Haotian; Jiang, Tianzi; Yu, Chunshui

2015-02-01

The human orbitofrontal cortex (OFC) is an enigmatic brain region that cannot be parcellated reliably using diffusional and functional magnetic resonance imaging (fMRI) because there is signal dropout that results from an inherent defect in imaging techniques. We hypothesise that the OFC can be reliably parcellated into subregions based on gray matter volume (GMV) covariance patterns that are derived from artefact-free structural images. A total of 321 healthy young subjects were examined by high-resolution structural MRI. The OFC was parcellated into subregions-based GMV covariance patterns; and then sex and laterality differences in GMV covariance pattern of each OFC subregion were compared. The human OFC was parcellated into the anterior (OFCa), medial (OFCm), posterior (OFCp), intermediate (OFCi), and lateral (OFCl) subregions. This parcellation scheme was validated by the same analyses of the left OFC and the bilateral OFCs in male and female subjects. Both visual observation and quantitative comparisons indicated a unique GMV covariance pattern for each OFC subregion. These OFC subregions mainly covaried with the prefrontal and temporal cortices, cingulate cortex and amygdala. In addition, GMV correlations of most OFC subregions were similar across sex and laterality except for significant laterality difference in the OFCl. The right OFCl had stronger GMV correlation with the right inferior frontal cortex. Using high-resolution structural images, we established a reliable parcellation scheme for the human OFC, which may provide an in vivo guide for subregion-level studies of this region and improve our understanding of the human OFC at subregional levels. © 2014 Wiley Periodicals, Inc.

Variability of Target and Normal Structure Delineation Using Multimodality Imaging for Radiation Therapy of Pancreatic Cancer

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

Dalah, Entesar; Moraru, Ion; Paulson, Eric

Purpose: To explore the potential of multimodality imaging (dynamic contrast–enhanced magnetic resonance imaging [DCE-MRI], apparent diffusion-coefficient diffusion-weighted imaging [ADC-DWI], fluorodeoxyglucose positron emission tomography [FDG-PET], and computed tomography) to define the gross tumor volume (GTV) and organs at risk in radiation therapy planning for pancreatic cancer. Delineated volumetric changes of DCE-MRI, ADC-DWI, and FDG-PET were assessed in comparison with the finding on 3-dimensional/4-dimensional CT with and without intravenous contrast, and with pathology specimens for resectable and borderline resectable cases of pancreatic cancer. Methods and Materials: We studied a total of 19 representative patients, whose DCE-MRI, ADC-DWI, and FDG-PET data were reviewed.more » Gross tumor volume and tumor burden/active region inside pancreatic head/neck or body were delineated on MRI (denoted GTV{sub DCE}, and GTV{sub ADC}), a standardized uptake value (SUV) of 2.5, 40%SUVmax, and 50%SUVmax on FDG-PET (GTV2.5, GTV{sub 40%}, and GTV{sub 50%}). Volumes of the pancreas, duodenum, stomach, liver, and kidneys were contoured according to CT (V{sub CT}), T1-weighted MRI (V{sub T1}), and T2-weighted MRI (V{sub T2}) for 7 patients. Results: Significant statistical differences were found between the GTVs from DCE-MRI, ADC-DW, and FDG-PET, with a mean and range of 4.73 (1.00-9.79), 14.52 (3.21-25.49), 22.04 (1.00-45.69), 19.10 (4.84-45.59), and 9.80 (0.32-35.21) cm{sup 3} for GTV{sub DCE}, GTV{sub ADC}, GTV2.5, GTV{sub 40%}, and GTV{sub 50%}, respectively. The mean difference and range in the measurements of maximum dimension of tumor on DCE-MRI, ADC-DW, SUV2.5, 40%SUVmax, and 50%SUVmax compared with pathologic specimens were −0.84 (−2.24 to 0.9), 0.41 (−0.15 to 2.3), 0.58 (−1.41 to 3.69), 0.66 (−0.67 to 1.32), and 0.15 (−1.53 to 2.38) cm, respectively. The T1- and T2-based volumes for pancreas, duodenum, stomach, and liver were generally smaller compared with those from CT, except for the kidneys. Conclusions: Differences exists between DCE-, ADC-, and FDG-PET–defined target volumes for RT of pancreatic cancer. Organ at risk volumes based on MRI are generally smaller than those based on CT. Further studies combined with pathologic specimens are required to identify the optimal imaging modality or sequence to define GTV.« less

Use of multidimensional, multimodal imaging and PACS to support neurological diagnoses

NASA Astrophysics Data System (ADS)

Wong, Stephen T. C.; Knowlton, Robert C.; Hoo, Kent S.; Huang, H. K.

1995-05-01

Technological advances in brain imaging have revolutionized diagnosis in neurology and neurological surgery. Major imaging techniques include magnetic resonance imaging (MRI) to visualize structural anatomy, positron emission tomography (PET) to image metabolic function and cerebral blood flow, magnetoencephalography (MEG) to visualize the location of physiologic current sources, and magnetic resonance spectroscopy (MRS) to measure specific biochemicals. Each of these techniques studies different biomedical aspects of the brain, but there lacks an effective means to quantify and correlate the disparate imaging datasets in order to improve clinical decision making processes. This paper describes several techniques developed in a UNIX-based neurodiagnostic workstation to aid the noninvasive presurgical evaluation of epilepsy patients. These techniques include online access to the picture archiving and communication systems (PACS) multimedia archive, coregistration of multimodality image datasets, and correlation and quantitation of structural and functional information contained in the registered images. For illustration, we describe the use of these techniques in a patient case of nonlesional neocortical epilepsy. We also present out future work based on preliminary studies.

Magnetic Resonance Imaging of Liver Metastasis.

PubMed

Karaosmanoglu, Ali Devrim; Onur, Mehmet Ruhi; Ozmen, Mustafa Nasuh; Akata, Deniz; Karcaaltincaba, Musturay

2016-12-01

Liver magnetic resonance imaging (MRI) is becoming the gold standard in liver metastasis detection and treatment response assessment. The most sensitive magnetic resonance sequences are diffusion-weighted images and hepatobiliary phase images after Gd-EOB-DTPA. Peripheral ring enhancement, diffusion restriction, and hypointensity on hepatobiliary phase images are hallmarks of liver metastases. In patients with normal ultrasonography, computed tomography (CT), and positron emission tomography (PET)-CT findings and high clinical suspicion of metastasis, MRI should be performed for diagnosis of unseen metastasis. In melanoma, colon cancer, and neuroendocrine tumor metastases, MRI allows confident diagnosis of treatment-related changes in liver and enables differential diagnosis from primary liver tumors. Focal nodular hyperplasia-like nodules in patients who received platinum-based chemotherapy, hypersteatosis, and focal fat can mimic metastasis. In cancer patients with fatty liver, MRI should be preferred to CT. Although the first-line imaging for metastases is CT, MRI can be used as a problem-solving method. MRI may be used as the first-line method in patients who would undergo curative surgery or metastatectomy. Current limitation of MRI is low sensitivity for metastasis smaller than 3mm. MRI fingerprinting, glucoCEST MRI, and PET-MRI may allow simpler and more sensitive diagnosis of liver metastasis. Copyright © 2016 Elsevier Inc. All rights reserved.

An iterative reduced field-of-view reconstruction for periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) MRI.

PubMed

Lin, Jyh-Miin; Patterson, Andrew J; Chang, Hing-Chiu; Gillard, Jonathan H; Graves, Martin J

2015-10-01

To propose a new reduced field-of-view (rFOV) strategy for iterative reconstructions in a clinical environment. Iterative reconstructions can incorporate regularization terms to improve the image quality of periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) MRI. However, the large amount of calculations required for full FOV iterative reconstructions has posed a huge computational challenge for clinical usage. By subdividing the entire problem into smaller rFOVs, the iterative reconstruction can be accelerated on a desktop with a single graphic processing unit (GPU). This rFOV strategy divides the iterative reconstruction into blocks, based on the block-diagonal dominant structure. A near real-time reconstruction system was developed for the clinical MR unit, and parallel computing was implemented using the object-oriented model. In addition, the Toeplitz method was implemented on the GPU to reduce the time required for full interpolation. Using the data acquired from the PROPELLER MRI, the reconstructed images were then saved in the digital imaging and communications in medicine format. The proposed rFOV reconstruction reduced the gridding time by 97%, as the total iteration time was 3 s even with multiple processes running. A phantom study showed that the structure similarity index for rFOV reconstruction was statistically superior to conventional density compensation (p < 0.001). In vivo study validated the increased signal-to-noise ratio, which is over four times higher than with density compensation. Image sharpness index was improved using the regularized reconstruction implemented. The rFOV strategy permits near real-time iterative reconstruction to improve the image quality of PROPELLER images. Substantial improvements in image quality metrics were validated in the experiments. The concept of rFOV reconstruction may potentially be applied to other kinds of iterative reconstructions for shortened reconstruction duration.

Advances in Magnetic Resonance Imaging Contrast Agents for Biomarker Detection

PubMed Central

Sinharay, Sanhita; Pagel, Mark D.

2016-01-01

Recent advances in magnetic resonance imaging (MRI) contrast agents have provided new capabilities for biomarker detection through molecular imaging. MRI contrast agents based on the T2 exchange mechanism have more recently expanded the armamentarium of agents for molecular imaging. Compared with T1 and T2* agents, T2 exchange agents have a slower chemical exchange rate, which improves the ability to design these MRI contrast agents with greater specificity for detecting the intended biomarker. MRI contrast agents that are detected through chemical exchange saturation transfer (CEST) have even slower chemical exchange rates. Another emerging class of MRI contrast agents uses hyperpolarized 13C to detect the agent with outstanding sensitivity. These hyperpolarized 13C agents can be used to track metabolism and monitor characteristics of the tissue microenvironment. Together, these various MRI contrast agents provide excellent opportunities to develop molecular imaging for biomarker detection. PMID:27049630

Department of Veterans Affairs, Gulf War Veterans’ Illnesses Task Force to the Secretary of Veterans Affairs

DTIC Science & Technology

2010-09-29

estimate for FY10 includes 40% of MRI imaging equipment upgrade at San Francisco for Gulf War research and use of unobligated FY2009 UTSW Contract funds...atrophy. (2) Explore the sensitivity of these tests to the localization of focal brain damage as confirmed on magnetic resonance imaging ( MRI ) in...2004 Gulf War RFA Effects of Gulf War Illness on Brain Structure, Function and Metabolism: MRI /MRS at 4 Tesla Gulf War Veterans Determine if

Department of Veterans Affairs Gulf War Veterans’ Illnesses Task Force to the Secretary of Veterans Affairs

DTIC Science & Technology

2010-09-29

estimate for FY10 includes 40% of MRI imaging equipment upgrade at San Francisco for Gulf War research and use of unobligated FY2009 UTSW Contract...atrophy. (2) Explore the sensitivity of these tests to the localization of focal brain damage as confirmed on magnetic resonance imaging ( MRI ) in...16 2004 Gulf War RFA Effects of Gulf War Illness on Brain Structure, Function and Metabolism: MRI /MRS at 4 Tesla Gulf War Veterans Determine

Interactive 3D visualization tools for stereotactic atlas-based functional neurosurgery

NASA Astrophysics Data System (ADS)

St. Jean, Philippe; Kasrai, Reza; Clonda, Diego; Sadikot, Abbas F.; Evans, Alan C.; Peters, Terence M.

1998-06-01

Many of the critical basal ganglia structures are not distinguishable on anatomical magnetic resonance imaging (MRI) scans, even though they differ in functionality. In order to provide the neurosurgeon with this missing information, a deformable volumetric atlas of the basal ganglia has been created from the Shaltenbrand and Wahren atlas of cryogenic slices. The volumetric atlas can be non-linearly deformed to an individual patient's MRI. To facilitate the clinical use of the atlas, a visualization platform has been developed for pre- and intra-operative use which permits manipulation of the merged atlas and MRI data sets in two- and three-dimensional views. The platform includes graphical tools which allow the visualization of projections of the leukotome and other surgical tools with respect to the atlas data, as well as pre- registered images from any other imaging modality. In addition, a graphical interface has been designed to create custom virtual lesions using computer models of neurosurgical tools for intra-operative planning. To date 17 clinical cases have been successfully performed using the described system.

Comparative analysis of methods for extracting vessel network on breast MRI images

NASA Astrophysics Data System (ADS)

Gaizer, Bence T.; Vassiou, Katerina G.; Lavdas, Eleftherios; Arvanitis, Dimitrios L.; Fezoulidis, Ioannis V.; Glotsos, Dimitris T.

2017-11-01

Digital processing of MRI images aims to provide an automatized diagnostic evaluation of regular health screenings. Cancerous lesions are proven to cause an alteration in the vessel structure of the diseased organ. Currently there are several methods used for extraction of the vessel network in order to quantify its properties. In this work MRI images (Signa HDx 3.0T, GE Healthcare, courtesy of University Hospital of Larissa) of 30 female breasts were subjected to three different vessel extraction algorithms to determine the location of their vascular network. The first method is an experiment to build a graph over known points of the vessel network; the second algorithm aims to determine the direction and diameter of vessels at these points; the third approach is a seed growing algorithm, spreading selection to neighbors of the known vessel pixels. The possibilities shown by the different methods were analyzed, and quantitative measurements were performed. The data provided by these measurements showed no clear correlation with the presence or malignancy of tumors, based on the radiological diagnosis of skilled physicians.

Non-invasive imaging of transplanted human neural stem cells and ECM scaffold remodeling in the stroke-damaged rat brain by (19)F- and diffusion-MRI.

PubMed

Bible, Ellen; Dell'Acqua, Flavio; Solanky, Bhavana; Balducci, Anthony; Crapo, Peter M; Badylak, Stephen F; Ahrens, Eric T; Modo, Michel

2012-04-01

Transplantation of human neural stem cells (hNSCs) is emerging as a viable treatment for stroke related brain injury. However, intraparenchymal grafts do not regenerate lost tissue, but rather integrate into the host parenchyma without significantly affecting the lesion cavity. Providing a structural support for the delivered cells appears important for cell based therapeutic approaches. The non-invasive monitoring of therapeutic methods would provide valuable information regarding therapeutic strategies but remains a challenge. Labeling transplanted cells with metal-based (1)H-magnetic resonance imaging (MRI) contrast agents affects the visualization of the lesion cavity. Herein, we demonstrate that a (19)F-MRI contrast agent can adequately monitor the distribution of transplanted cells, whilst allowing an evaluation of the lesion cavity and the formation of new tissue on (1)H-MRI scans. Twenty percent of cells labeled with the (19)F agent were of host origin, potentially reflecting the re-uptake of label from dead transplanted cells. Both T(2)- and diffusion-weighted MRI scans indicated that transplantation of hNSCs suspended in a gel form of a xenogeneic extracellular matrix (ECM) bioscaffold resulted in uniformly distributed cells throughout the lesion cavity. However, diffusion MRI indicated that the injected materials did not yet establish diffusion barriers (i.e. cellular network, fiber tracts) normally found within striatal tissue. The ECM bioscaffold therefore provides an important support to hNSCs for the creation of de novo tissue and multi-nuclei MRI represents an adept method for the visualization of some aspects of this process. However, significant developments of both the transplantation paradigm, as well as regenerative imaging, are required to successfully create new tissue in the lesion cavity and to monitor this process non-invasively. Copyright © 2011 Elsevier Ltd. All rights reserved.

Improved medical image fusion based on cascaded PCA and shift invariant wavelet transforms.

PubMed

Reena Benjamin, J; Jayasree, T

2018-02-01

In the medical field, radiologists need more informative and high-quality medical images to diagnose diseases. Image fusion plays a vital role in the field of biomedical image analysis. It aims to integrate the complementary information from multimodal images, producing a new composite image which is expected to be more informative for visual perception than any of the individual input images. The main objective of this paper is to improve the information, to preserve the edges and to enhance the quality of the fused image using cascaded principal component analysis (PCA) and shift invariant wavelet transforms. A novel image fusion technique based on cascaded PCA and shift invariant wavelet transforms is proposed in this paper. PCA in spatial domain extracts relevant information from the large dataset based on eigenvalue decomposition, and the wavelet transform operating in the complex domain with shift invariant properties brings out more directional and phase details of the image. The significance of maximum fusion rule applied in dual-tree complex wavelet transform domain enhances the average information and morphological details. The input images of the human brain of two different modalities (MRI and CT) are collected from whole brain atlas data distributed by Harvard University. Both MRI and CT images are fused using cascaded PCA and shift invariant wavelet transform method. The proposed method is evaluated based on three main key factors, namely structure preservation, edge preservation, contrast preservation. The experimental results and comparison with other existing fusion methods show the superior performance of the proposed image fusion framework in terms of visual and quantitative evaluations. In this paper, a complex wavelet-based image fusion has been discussed. The experimental results demonstrate that the proposed method enhances the directional features as well as fine edge details. Also, it reduces the redundant details, artifacts, distortions.

Preoperative magnetic resonance and intraoperative ultrasound fusion imaging for real-time neuronavigation in brain tumor surgery.

PubMed

Prada, F; Del Bene, M; Mattei, L; Lodigiani, L; DeBeni, S; Kolev, V; Vetrano, I; Solbiati, L; Sakas, G; DiMeco, F

2015-04-01

Brain shift and tissue deformation during surgery for intracranial lesions are the main actual limitations of neuro-navigation (NN), which currently relies mainly on preoperative imaging. Ultrasound (US), being a real-time imaging modality, is becoming progressively more widespread during neurosurgical procedures, but most neurosurgeons, trained on axial computed tomography (CT) and magnetic resonance imaging (MRI) slices, lack specific US training and have difficulties recognizing anatomic structures with the same confidence as in preoperative imaging. Therefore real-time intraoperative fusion imaging (FI) between preoperative imaging and intraoperative ultrasound (ioUS) for virtual navigation (VN) is highly desirable. We describe our procedure for real-time navigation during surgery for different cerebral lesions. We performed fusion imaging with virtual navigation for patients undergoing surgery for brain lesion removal using an ultrasound-based real-time neuro-navigation system that fuses intraoperative cerebral ultrasound with preoperative MRI and simultaneously displays an MRI slice coplanar to an ioUS image. 58 patients underwent surgery at our institution for intracranial lesion removal with image guidance using a US system equipped with fusion imaging for neuro-navigation. In all cases the initial (external) registration error obtained by the corresponding anatomical landmark procedure was below 2 mm and the craniotomy was correctly placed. The transdural window gave satisfactory US image quality and the lesion was always detectable and measurable on both axes. Brain shift/deformation correction has been successfully employed in 42 cases to restore the co-registration during surgery. The accuracy of ioUS/MRI fusion/overlapping was confirmed intraoperatively under direct visualization of anatomic landmarks and the error was < 3 mm in all cases (100 %). Neuro-navigation using intraoperative US integrated with preoperative MRI is reliable, accurate and user-friendly. Moreover, the adjustments are very helpful in correcting brain shift and tissue distortion. This integrated system allows true real-time feedback during surgery and is less expensive and time-consuming than other intraoperative imaging techniques, offering high precision and orientation. © Georg Thieme Verlag KG Stuttgart · New York.

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.

Natural image classification driven by human brain activity

NASA Astrophysics Data System (ADS)

Zhang, Dai; Peng, Hanyang; Wang, Jinqiao; Tang, Ming; Xue, Rong; Zuo, Zhentao

2016-03-01

Natural image classification has been a hot topic in computer vision and pattern recognition research field. Since the performance of an image classification system can be improved by feature selection, many image feature selection methods have been developed. However, the existing supervised feature selection methods are typically driven by the class label information that are identical for different samples from the same class, ignoring with-in class image variability and therefore degrading the feature selection performance. In this study, we propose a novel feature selection method, driven by human brain activity signals collected using fMRI technique when human subjects were viewing natural images of different categories. The fMRI signals associated with subjects viewing different images encode the human perception of natural images, and therefore may capture image variability within- and cross- categories. We then select image features with the guidance of fMRI signals from brain regions with active response to image viewing. Particularly, bag of words features based on GIST descriptor are extracted from natural images for classification, and a sparse regression base feature selection method is adapted to select image features that can best predict fMRI signals. Finally, a classification model is built on the select image features to classify images without fMRI signals. The validation experiments for classifying images from 4 categories of two subjects have demonstrated that our method could achieve much better classification performance than the classifiers built on image feature selected by traditional feature selection methods.

Chemical addressability of potato virus X for its applications in bio/nanotechnology.

PubMed

Le, Duc H T; Hu, He; Commandeur, Ulrich; Steinmetz, Nicole F

2017-12-01

Potato virus X (PVX), a type member of the plant virus potexvirus group, offers a unique nanotechnology platform based on its high aspect ratio and flexible filamentous shape. The PVX platform has already been engineered and studied for its uses in imaging, drug delivery, and immunotherapies. While genetic engineering procedures are well established for PVX, there is limited information about chemical conjugation strategies for functionalizing PVX, partly due to the lack of structural information of PVX at high resolution. To overcome these challenges, we built a structural model of the PVX particle based on the available structures from pepino mosaic virus (PepMV), a close cousin of PVX. Using the model and a series of chemical conjugation experiments, we identified and probed the addressability of cysteine side chains. Chemical reactivity of cysteines was confirmed using Michael-addition and thiol-selective probes, including fluorescent dyes and biotin tags. LC/MS/MS was used to map Cys 121 as having the highest selectivity for modification. Finally, building on the availability of two reactive groups, the newly identified Cys and previously established Lys side chains, we prepared multifunctional PVX nanoparticles by conjugating Gd-DOTA for magnetic resonance imaging (MRI) to lysines and fluorescent dyes for optical imaging to cysteines. The resulting functionalized nanofilament could have applications in dual-modal optical-MRI imaging applications. These results further extend the understanding of the chemical properties of PVX and enable development of novel multifunctional platforms in bio/nanotechnology. Copyright © 2017 Elsevier Inc. All rights reserved.

Reading visually embodied meaning from the brain: Visually grounded computational models decode visual-object mental imagery induced by written text.

PubMed

Anderson, Andrew James; Bruni, Elia; Lopopolo, Alessandro; Poesio, Massimo; Baroni, Marco

2015-10-15

Embodiment theory predicts that mental imagery of object words recruits neural circuits involved in object perception. The degree of visual imagery present in routine thought and how it is encoded in the brain is largely unknown. We test whether fMRI activity patterns elicited by participants reading objects' names include embodied visual-object representations, and whether we can decode the representations using novel computational image-based semantic models. We first apply the image models in conjunction with text-based semantic models to test predictions of visual-specificity of semantic representations in different brain regions. Representational similarity analysis confirms that fMRI structure within ventral-temporal and lateral-occipital regions correlates most strongly with the image models and conversely text models correlate better with posterior-parietal/lateral-temporal/inferior-frontal regions. We use an unsupervised decoding algorithm that exploits commonalities in representational similarity structure found within both image model and brain data sets to classify embodied visual representations with high accuracy (8/10) and then extend it to exploit model combinations to robustly decode different brain regions in parallel. By capturing latent visual-semantic structure our models provide a route into analyzing neural representations derived from past perceptual experience rather than stimulus-driven brain activity. Our results also verify the benefit of combining multimodal data to model human-like semantic representations. Copyright © 2015 Elsevier Inc. All rights reserved.

Structural and functional evaluation of cortical motor areas in Amyotrophic Lateral Sclerosis.

PubMed

Cosottini, Mirco; Pesaresi, Ilaria; Piazza, Selina; Diciotti, Stefano; Cecchi, Paolo; Fabbri, Serena; Carlesi, Cecilia; Mascalchi, Mario; Siciliano, Gabriele

2012-03-01

The structural and functional data gathered with Magnetic Resonance Imaging (MRI) techniques about the brain cortical motor damage in Amyotrophic Lateral Sclerosis (ALS) are controversial. In fact some structural MRI studies showed foci of gray matter (GM) atrophy in the precentral gyrus, even in the early stage, while others did not. Most functional MRI (fMRI) studies in ALS reported hyperactivation of extra-primary motor cortices, while contradictory results were obtained on the activation of the primary motor cortex. We aimed to investigate the cortical motor circuitries in ALS patients by a combined structural and functional approach. Twenty patients with definite ALS and 16 healthy subjects underwent a structural examination with acquisition of a 3D T1-weighted sequence and fMRI examination during a maximal force handgrip task executed with the right-hand, the left-hand and with both hands simultaneously. The T1-weighted images were analyzed with Voxel-Based Morphometry (VBM) that showed several clusters of reduced cortical GM in ALS patients compared to controls including the pre and postcentral gyri, the superior, middle and inferior frontal gyri, the supplementary motor area, the superior and inferior parietal cortices and the temporal lobe, bilaterally but more extensive on the right side. In ALS patients a significant hypoactivation of the primary sensory motor cortex and frontal dorsal premotor areas as compared to controls was observed. The hypoactivated areas matched with foci of cortical atrophy demonstrated by VBM. The fMRI analysis also showed an enhanced activation in the ventral premotor frontal areas and in the parietal cortex pertaining to the fronto-parietal motor circuit which paralleled with disease progression rate and matched with cortical regions of atrophy. The hyperactivation of the fronto-parietal circuit was asymmetric and prevalent in the left hemisphere. VBM and fMRI identified structural and functional markers of an extended cortical damage within the motor circuit of ALS patients. The functional changes in non-primary motor cortices pertaining to fronto-parietal circuit suggest an over-recruitment of a pre-existing physiological sensory-motor network. However, the concomitant fronto-parietal cortical atrophy arises the possibility that such a hyper-activation reflects cortical hyper-excitability due to loss of inhibitory inter-neurons. Copyright © 2011 Elsevier Inc. All rights reserved.

Fast Room Temperature Very Low Field-Magnetic Resonance Imaging System Compatible with MagnetoEncephaloGraphy Environment

PubMed Central

Galante, Angelo; Sinibaldi, Raffaele; Conti, Allegra; De Luca, Cinzia; Catallo, Nadia; Sebastiani, Piero; Pizzella, Vittorio; Romani, Gian Luca; Sotgiu, Antonello; Della Penna, Stefania

2015-01-01

In recent years, ultra-low field (ULF)-MRI is being given more and more attention, due to the possibility of integrating ULF-MRI and Magnetoencephalography (MEG) in the same device. Despite the signal-to-noise ratio (SNR) reduction, there are several advantages to operating at ULF, including increased tissue contrast, reduced cost and weight of the scanners, the potential to image patients that are not compatible with clinical scanners, and the opportunity to integrate different imaging modalities. The majority of ULF-MRI systems are based, until now, on magnetic field pulsed techniques for increasing SNR, using SQUID based detectors with Larmor frequencies in the kHz range. Although promising results were recently obtained with such systems, it is an open question whether similar SNR and reduced acquisition time can be achieved with simpler devices. In this work a room-temperature, MEG-compatible very-low field (VLF)-MRI device working in the range of several hundred kHz without sample pre-polarization is presented. This preserves many advantages of ULF-MRI, but for equivalent imaging conditions and SNR we achieve reduced imaging time based on preliminary results using phantoms and ex-vivo rabbits heads. PMID:26630172

Fast high resolution reconstruction in multi-slice and multi-view cMRI

NASA Astrophysics Data System (ADS)

Velasco Toledo, Nelson; Romero Castro, Eduardo

2015-01-01

Cardiac magnetic resonance imaging (cMRI) is an useful tool in diagnosis, prognosis and research since it functionally tracks the heart structure. Although useful, this imaging technique is limited in spatial resolution because heart is a constant moving organ, also there are other non controled conditions such as patient movements and volumetric changes during apnea periods when data is acquired, those conditions limit the time to capture high quality information. This paper presents a very fast and simple strategy to reconstruct high resolution 3D images from a set of low resolution series of 2D images. The strategy is based on an information reallocation algorithm which uses the DICOM header to relocate voxel intensities in a regular grid. An interpolation method is applied to fill empty places with estimated data, the interpolation resamples the low resolution information to estimate the missing information. As a final step a gaussian filter that denoises the final result. A reconstructed image evaluation is performed using as a reference a super-resolution reconstructed image. The evaluation reveals that the method maintains the general heart structure with a small loss in detailed information (edge sharpening and blurring), some artifacts related with input information quality are detected. The proposed method requires low time and computational resources.

Performance of μMRI-Based Virtual Bone Biopsy for Structural and Mechanical Analysis at the Distal Tibia at 7T Field Strength

PubMed Central

Bhagat, Yusuf A.; Rajapakse, Chamith S.; Magland, Jeremy F.; Love, James H.; Wright, Alexander C.; Wald, Michael J.; Song, Hee Kwon; Wehrli, Felix W.

2010-01-01

Purpose To assess the performance of a 3D fast spin echo (FSE) pulse sequence utilizing out-of-slab cancellation through phase alternation and micro magnetic resonance imaging (μMRI) based virtual bone biopsy processing methods to probe the serial reproducibility and sensitivity of structural and mechanical parameters of the distal tibia at 7.0T. Materials and Methods The distal tibia of five healthy subjects was imaged at three time-points with a 3D FSE sequence at 137×137×410 μm3 voxel size. Follow-up images were retrospectively 3D registered to baseline images. Coefficients of variation (CV) and intraclass correlation coefficients (ICC) for measures of scale and topology of the whole tibial trabecular bone (TB) cross-section as well as finite-element derived Young’s and shear moduli of central cuboidal TB sub-volumes (8 × 8 × 5 mm3) were evaluated as measures of reproducibility and reliability. Four additional cubic TB sub-regions (anterior, medial, lateral and posterior) of similar dimensions were extracted and analyzed to determine associations between whole cross-section and sub-regional structural parameters. Results Mean SNR over the fifteen image acquisitions was 27.5 ± 2.1. Retrospective registration yielded an average common analysis volume of 67% across the 3 exams per subject. Reproducibility (mean CV=3.6%; range, 1.5–5%) and reliability (ICCs, 0.95–0.99) of all parameters permitted parameter-based discrimination of the five subjects in spite of the narrow age range (26–36 years) covered. Parameters characterizing topology were better able to distinguish two individuals who demonstrated similar values for scalar measurements (~34% difference, p<0.001). Whole-section axial stiffness encompassing the cortex was superior at distinguishing 2 individuals relative to its central sub-regional TB counterpart (~8% difference; p<0.05). Inter-region comparisons showed that although all parameters were correlated (mean R2 = 0.78; range 0.57 to 0.99), the strongest associations observed were those for the erosion index (mean R2 = 0.95, p≤0.01). Conclusion The reproducibility, and structural and mechanical parameter-based discriminative ability achieved in five healthy subjects suggests that 7T-derived μMRI of TB can be applied towards serial patient studies of osteoporosis and may enable earlier detection of disease or treatment-based effects. PMID:21274979

Gradient-based reliability maps for ACM-based segmentation of hippocampus.

PubMed

Zarpalas, Dimitrios; Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos

2014-04-01

Automatic segmentation of deep brain structures, such as the hippocampus (HC), in MR images has attracted considerable scientific attention due to the widespread use of MRI and to the principal role of some structures in various mental disorders. In this literature, there exists a substantial amount of work relying on deformable models incorporating prior knowledge about structures' anatomy and shape information. However, shape priors capture global shape characteristics and thus fail to model boundaries of varying properties; HC boundaries present rich, poor, and missing gradient regions. On top of that, shape prior knowledge is blended with image information in the evolution process, through global weighting of the two terms, again neglecting the spatially varying boundary properties, causing segmentation faults. An innovative method is hereby presented that aims to achieve highly accurate HC segmentation in MR images, based on the modeling of boundary properties at each anatomical location and the inclusion of appropriate image information for each of those, within an active contour model framework. Hence, blending of image information and prior knowledge is based on a local weighting map, which mixes gradient information, regional and whole brain statistical information with a multi-atlas-based spatial distribution map of the structure's labels. Experimental results on three different datasets demonstrate the efficacy and accuracy of the proposed method.

Posterolateral complex knee injuries: magnetic resonance imaging with surgical correlation.

PubMed

Theodorou, D J; Theodorou, S J; Fithian, D C; Paxton, L; Garelick, D H; Resnick, D

2005-05-01

To describe the magnetic resonance imaging (MRI) findings of injuries of the posterolateral aspect of the knee and to evaluate the diagnostic capabilities of MRI in the assessment of these injuries. The MRI studies of 14 patients (mean age 33 years) with trauma to the posterolateral aspect of the knee were retrospectively reviewed, and the imaging findings were correlated with those of surgery. In all patients, MRI showed an intact iliotibial (ITB) band. MRI showed injury to the biceps tendon in 11 (79%), the gastrocnemius tendon in 1 (7%)), the popliteus tendon in 5 (36%), and the lateral collateral ligament (LCL) in 14 (100%) patients. Tear of the anterior cruciate ligament (ACL) was seen in 11 (79%) patients and tear of the posterior cruciate ligament (PCL) in 4 (29%) patients. With routine MRI, visualization of the popliteofibular or fabellofibular ligaments was incomplete. On MRI, the lateral meniscus and the medial meniscus were torn with equal frequency (n = 4; 29%). Osteochondral defects were seen in 5 (36%) cases and joint effusion in all 14 (100%) cases on MRI. Using surgical findings as the standard for diagnosis, MRI proved 86% accurate in the detection of injury to the ITB band, the biceps tendon (93%), the gastrocnemius tendon (100%), the popliteus tendon (86%), the LCL (100%), the ACL (79%), the PCL (86%), the lateral meniscus (90%), the medial meniscus (82%), and the osteochondral structures (79%). Surgical correlation confirmed the MRI findings of joint effusion in all cases. MRI is well suited for demonstrating the presence and extent of injuries of the major structures of the posterolateral complex of the knee, allowing characterization of the severity of injury.

Rotator cuff disorders: How to write a surgically relevant magnetic resonance imaging report?

PubMed Central

Tawfik, Ahmed M; El-Morsy, Ahmad; Badran, Mohamed Aboelnour

2014-01-01

Evaluation of rotator cuff is a common indication for magnetic resonance imaging (MRI) scanning of the shoulder. Conventional MRI is the most commonly used technique, while magnetic resonance (MR) arthrography is reserved for certain cases. Rotator cuff disorders are thought to be caused by a combination of internal and external mechanisms. A well-structured MRI report should comment on the relevant anatomic structures including the acromial type and orientation, the presence of os acromiale, acromio-clavicular degenerative spurs and fluid in the subacromial subdeltoid bursa. In addition, specific injuries of the rotator cuff tendons and the condition of the long head of biceps should be accurately reported. The size and extent of tendon tears, tendon retraction and fatty degeneration or atrophy of the muscles are all essential components of a surgically relevant MRI report. PMID:24976930

“MRI Stealth” robot for prostate interventions

PubMed Central

STOIANOVICI, DAN; SONG, DANNY; PETRISOR, DORU; URSU, DANIEL; MAZILU, DUMITRU; MUTENER, MICHAEL; SCHAR, MICHAEL; PATRICIU, ALEXANDRU

2011-01-01

The paper reports an important achievement in MRI instrumentation, a pneumatic, fully actuated robot located within the scanner alongside the patient and operating under remote control based on the images. Previous MRI robots commonly used piezoelectric actuation limiting their compatibility. Pneumatics is an ideal choice for MRI compatibility because it is decoupled from electromagnetism, but pneumatic actuators were hardly controllable. This achievement was possible due to a recent technology breakthrough, the invention of a new type of pneumatic motor, PneuStep (1), designed for the robot reported here with uncompromised MRI compatibility, high-precision, and medical safety. MrBot is one of the “MRI stealth” robots today (the second is described in this issue by Zangos et al.). Both of these systems are also multi-imager compatible, being able to operate with the imager of choice or cross-imaging modalities. For MRI compatibility the robot is exclusively constructed of nonmagnetic and dielectric materials such as plastics, ceramics, crystals, rubbers and is electricity free. Light-based encoding is used for feedback, so that all electric components are distally located outside the imager’s room. MRI robots are modern, digital medical instruments in line with advanced imaging equipment and methods. These allow for accessing patients within closed bore scanners and performing interventions under direct (in scanner) imaging feedback. MRI robots could allow e.g. to biopsy small lesions imaged with cutting edge cancer imaging methods, or precisely deploy localized therapy at cancer foci. Our robot is the first to show the feasibility of fully automated in-scanner interventions. It is customized for the prostate and operates transperineally for needle interventions. It can accommodate various needle drivers for different percutaneous procedures such as biopsy, thermal ablations, or brachytherapy. The first needle driver is customized for fully automated low-dose radiation seed brachytherapy. This paper gives an introduction to the challenges of MRI robot compatibility and presents the solutions adopted in making the MrBot. Its multi-imager compatibility and other preclinical tests are included. The robot shows the technical feasibility of MRI-guided prostate interventions, yet its clinical utility is still to be determined. PMID:17763098

[Comparison of image distortion between three magnetic resonance imaging systems of different magnetic field strengths for use in stereotactic irradiation of brain].

PubMed

Takemura, Akihiro; Sasamoto, Kouhei; Nakamura, Kaori; Kuroda, Tatsunori; Shoji, Saori; Matsuura, Yukihiro; Matsushita, Tatsuhiko

2013-06-01

In this study, we evaluated the image distortion of three magnetic resonance imaging (MRI) systems with magnetic field strengths of 0.4 T, 1.5 T and 3 T, during stereotactic irradiation of the brain. A quality assurance phantom for MRI image distortion in radiosurgery was used for these measurements of image distortion. Images were obtained from a 0.4-T MRI (APERTO Eterna, HITACHI), a 1.5-T MRI (Signa HDxt, GE Healthcare) and a 3-T MRI (Signa HDx 3.0 T, GE Healthcare) system. Imaging sequences for the 0.4-T and 3-T MRI were based on the 1.5-T MRI sequence used for stereotactic irradiation in the clinical setting. The same phantom was scanned using a computed tomography (CT) system (Aquilion L/B, Toshiba) as the standard. The results showed mean errors in the Z direction to be the least satisfactory of all the directions in all results. The mean error in the Z direction for 1.5-T MRI at －110 mm in the axial plane showed the largest error of 4.0 mm. The maximum errors for the 0.4-T and 3-T MRI were 1.7 mm and 2.8 mm, respectively. The errors in the plane were not uniform and did not show linearity, suggesting that simple distortion correction using outside markers is unlikely to be effective. The 0.4-T MRI showed the lowest image distortion of the three. However, other items, such as image noise, contrast and study duration need to be evaluated in MRI systems when applying frameless stereotactic irradiation.

Ultra high spatial and temporal resolution breast imaging at 7T.

PubMed

van de Bank, B L; Voogt, I J; Italiaander, M; Stehouwer, B L; Boer, V O; Luijten, P R; Klomp, D W J

2013-04-01

There is a need to obtain higher specificity in the detection of breast lesions using MRI. To address this need, Dynamic Contrast-Enhanced (DCE) MRI has been combined with other structural and functional MRI techniques. Unfortunately, owing to time constraints structural images at ultra-high spatial resolution can generally not be obtained during contrast uptake, whereas the relatively low spatial resolution of functional imaging (e.g. diffusion and perfusion) limits the detection of small lesions. To be able to increase spatial as well as temporal resolution simultaneously, the sensitivity of MR detection needs to increase as well as the ability to effectively accelerate the acquisition. The required gain in signal-to-noise ratio (SNR) can be obtained at 7T, whereas acceleration can be obtained with high-density receiver coil arrays. In this case, morphological imaging can be merged with DCE-MRI, and other functional techniques can be obtained at higher spatial resolution, and with less distortion [e.g. Diffusion Weighted Imaging (DWI)]. To test the feasibility of this concept, we developed a unilateral breast coil for 7T. It comprises a volume optimized dual-channel transmit coil combined with a 30-channel receive array coil. The high density of small coil elements enabled efficient acceleration in any direction to acquire ultra high spatial resolution MRI of close to 0.6 mm isotropic detail within a temporal resolution of 69 s, high spatial resolution MRI of 1.5 mm isotropic within an ultra high temporal resolution of 6.7 s and low distortion DWI at 7T, all validated in phantoms, healthy volunteers and a patient with a lesion in the right breast classified as Breast Imaging Reporting and Data System (BI-RADS) IV. Copyright © 2012 John Wiley & Sons, Ltd.

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

[3 Tesla MRI: successful results with higher field strengths].

PubMed

Schmitt, F; Grosu, D; Mohr, C; Purdy, D; Salem, K; Scott, K T; Stoeckel, B

2004-01-01

The recent development of 3 Tesla MRI (3T MRI) has been fueled by promise of increased signal-to-noise ratio(SNR). Many are excited about the opportunity to not only use the increased SNR for clearer images, but also the chance to exchange it for better resolution or faster scans. These possibilities have caused a rapid increase in the market for 3T MRI, where the faster scanning tips an already advantageous economic outlook in favor of the user. As a result, the global market for 3T has grown from a research only market just a few years ago to an ever-increasing clinically oriented customer base. There are, however, significant obstacles to 3T MRI presented by the physics at higher field strengths. For example, the T1 relaxation times are prolonged with increasing magnet field strength. Further, the increased RF-energy deposition (SAR), the larger the chemical shift and the stronger susceptibility effect have to be considered as challenges. It is critical that one looks at both the advantages and disadvantages of using 3T. While there are many issues to address aand a number of different methods for doing so, to properly tackle each of these concerns will take time and effort on the part od researchers and clinicians. The optimization of 3T MRI scanning will have to be a combined effort, though much of the work to date has been in neuroimaging. Multiple applications have been explored in addition to clinical anatomical imaging, where resolution is improved showing structure in the brain never seen before in human MRI. Body and cardiac imaging provide a great challenge but are also achievable at 3T. As an example, the full range of clinical applications currently achieved on today's state-of-the-art 1.5T cardiac MR scanners has also been demonstrated at 3T. In the body, the full range of contrast is available over large fields of view allowing whole liver studies in the clinic or, as needed, one may choose a smaller field of view for high-resolution imaging of the pancreas. The ability to increase resolution for musculoskeletal imaging has provided previously unseen detail. Bone structure, cartilage, and tendons and ligaments can be clearly visualized and pathology more easily detected due to an increased image quality. As the increase in field strength continues, a push to look at 7T has begun. The design philosophy is to keep the system as similar as possible, while changing only the frequency-dependent components. To date, both animal and human imaging have been performed on a whole body 7T scanner. Results show promise for both detailed imaging and functional MRI, but the road ahead is too long to be able to predict where it will end. The move toward higher field strengths is an exciting adventure in which 3T plays the role of trailblazer.

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

Understanding Magnetic Resonance Imaging of Knee Cartilage Repair: A Focus on Clinical Relevance.

PubMed

Hayashi, Daichi; Li, Xinning; Murakami, Akira M; Roemer, Frank W; Trattnig, Siegfried; Guermazi, Ali

2017-06-01

The aims of this review article are (a) to describe the principles of morphologic and compositional magnetic resonance imaging (MRI) techniques relevant for the imaging of knee cartilage repair surgery and their application to longitudinal studies and (b) to illustrate the clinical relevance of pre- and postsurgical MRI with correlation to intraoperative images. First, MRI sequences that can be applied for imaging of cartilage repair tissue in the knee are described, focusing on comparison of 2D and 3D fast spin echo and gradient recalled echo sequences. Imaging features of cartilage repair tissue are then discussed, including conventional (morphologic) MRI and compositional MRI techniques. More specifically, imaging techniques for specific cartilage repair surgery techniques as described above, as well as MRI-based semiquantitative scoring systems for the knee cartilage repair tissue-MR Observation of Cartilage Repair Tissue and Cartilage Repair OA Knee Score-are explained. Then, currently available surgical techniques are reviewed, including marrow stimulation, osteochondral autograft, osteochondral allograft, particulate cartilage allograft, autologous chondrocyte implantation, and others. Finally, ongoing research efforts and future direction of cartilage repair tissue imaging are discussed.

Tract-based Spatial Statistics and fMRI Analysis in Patients with Small Cell Lung Cancer before Prophylactic Cranial Irradiation

NASA Astrophysics Data System (ADS)

Benezi, S.; Bromis, K.; Karavasilis, E.; Karanasiou, I. S.; Koutsoupidou, M.; Matsopoulos, G.; Ventouras, E.; Uzunoglu, N.; Kouloulias, V.; Papathanasiou, M.; Foteineas, A.; Efstathopoulos, E.; Kelekis, N.; Kelekis, D.

2015-09-01

Prophylactic cranial irradiation (PCI) is known to increase life expectancy to a significant degree in Small Cell Lung Cancer (SCLC) patients. The overall scope of this research is to investigate changes in structural and functional connectivity between SCLC patients and controls before and after PCI treatment. In the current study specifically we use diffusion tensor imaging (DTI) and functional Magnetic Resonance (fMRI) to identify potential alterations in white matter structure and brain function respectively, in SCLC patients before PCI compared to healthy participants. The results in DTI analysis have showed lower fractional anisotropy (FA) and higher eigenvalues in white matter regions in the patient group. Similarly, in fMRI analysis a lower level of activation in the primary somatosensory cortex was reported. The results presented herein are subject to further investigation with larger patient and control groups.

A fast multiparameter MRI approach for acute stroke assessment on a 3T clinical scanner: preliminary results in a non-human primate model with transient ischemic occlusion.

PubMed

Zhang, Xiaodong; Tong, Frank; Li, Chun-Xia; Yan, Yumei; Nair, Govind; Nagaoka, Tsukasa; Tanaka, Yoji; Zola, Stuart; Howell, Leonard

2014-04-01

Many MRI parameters have been explored and demonstrated the capability or potential to evaluate acute stroke injury, providing anatomical, microstructural, functional, or neurochemical information for diagnostic purposes and therapeutic development. However, the application of multiparameter MRI approach is hindered in clinic due to the very limited time window after stroke insult. Parallel imaging technique can accelerate MRI data acquisition dramatically and has been incorporated in modern clinical scanners and increasingly applied for various diagnostic purposes. In the present study, a fast multiparameter MRI approach including structural T1-weighted imaging (T1W), T2-weighted imaging (T2W), diffusion tensor imaging (DTI), T2-mapping, proton magnetic resonance spectroscopy, cerebral blood flow (CBF), and magnetization transfer (MT) imaging, was implemented and optimized for assessing acute stroke injury on a 3T clinical scanner. A macaque model of transient ischemic stroke induced by a minimal interventional approach was utilized for evaluating the multiparameter MRI approach. The preliminary results indicate the surgical procedure successfully induced ischemic occlusion in the cortex and/or subcortex in adult macaque monkeys (n=4). Application of parallel imaging technique substantially reduced the scanning duration of most MRI data acquisitions, allowing for fast and repeated evaluation of acute stroke injury. Hence, the use of the multiparameter MRI approach with up to five quantitative measures can provide significant advantages in preclinical or clinical studies of stroke disease.

Magnetic resonance imaging of female prostate pathology.

PubMed

Wimpissinger, Florian; Tscherney, Robert; Stackl, Walter

2009-06-01

The female prostate (paraurethral glands) is a well-known, yet poorly understood, anatomic structure. Imaging studies of the female prostate, its physiology, and pathologies are still highly controversial. To study the anatomy of the female prostate with contemporary magnetic resonance imaging (MRI) techniques and correlate these findings to clinical features. Female prostate pathologic anatomy on MRI. Women with clinical signs of function (or dysfunction) of paraurethral glands have been examined with 1.5 or 3 Tesla MRI and urethroscopy. Seven women aged 17 to 62 years (median 40 years) have been prospectively included into the study. Clinically, one of the seven women reported ejaculation at orgasm, whereas three women presented with occasional secretions independent of sexual stimulation. In two women, paraurethral glands have been randomly found on MRI that has been performed in the diagnostic workup of other diseases. One woman presented with swelling of the external urethral meatus at puberty. In this woman, a paraurethral gland has been found, besides the erectile tissue at the external meatus. Two women reported lower urinary tract symptoms (LUTS) with mainly urethral symptoms (recurrent infections in one and paraurethral stones in the other). On MRI, paraurethral glands could be visualized in six of the seven patients. There was no relation between glandular volume and ejaculation status. In cases where glands or related pathologies could be found on physical examination, there was a clear correlation with MRI anatomy. MRI has the potential to become the standard imaging modality for female prostate pathology. Exact visualization of this highly variable structure is possible by tailored MRI protocols. This tool can aid in understanding an individual woman's symptoms related to paraurethral glands with an impact on her sexual life.

Parametric fMRI of paced motor responses uncovers novel whole-brain imaging biomarkers in spinocerebellar ataxia type 3.

PubMed

Duarte, João Valente; Faustino, Ricardo; Lobo, Mercês; Cunha, Gil; Nunes, César; Ferreira, Carlos; Januário, Cristina; Castelo-Branco, Miguel

2016-10-01

Machado-Joseph Disease, inherited type 3 spinocerebellar ataxia (SCA3), is the most common form worldwide. Neuroimaging and neuropathology have consistently demonstrated cerebellar alterations. Here we aimed to discover whole-brain functional biomarkers, based on parametric performance-level-dependent signals. We assessed 13 patients with early SCA3 and 14 healthy participants. We used a combined parametric behavioral/functional neuroimaging design to investigate disease fingerprints, as a function of performance levels, coupled with structural MRI and voxel-based morphometry. Functional magnetic resonance imaging (fMRI) was designed to parametrically analyze behavior and neural responses to audio-paced bilateral thumb movements at temporal frequencies of 1, 3, and 5 Hz. Our performance-level-based design probing neuronal correlates of motor coordination enabled the discovery that neural activation and behavior show critical loss of parametric modulation specifically in SCA3, associated with frequency-dependent cortico/subcortical activation/deactivation patterns. Cerebellar/cortical rate-dependent dissociation patterns could clearly differentiate between groups irrespective of grey matter loss. Our findings suggest functional reorganization of the motor network and indicate a possible role of fMRI as a tool to monitor disease progression in SCA3. Accordingly, fMRI patterns proved to be potential biomarkers in early SCA3, as tested by receiver operating characteristic analysis of both behavior and neural activation at different frequencies. Discrimination analysis based on BOLD signal in response to the applied parametric finger-tapping task significantly often reached >80% sensitivity and specificity in single regions-of-interest.Functional fingerprints based on cerebellar and cortical BOLD performance dependent signal modulation can thus be combined as diagnostic and/or therapeutic targets in hereditary ataxia. Hum Brain Mapp 37:3656-3668, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Documenting the location of systematic transrectal ultrasound-guided prostate biopsies: correlation with multi-parametric MRI.

PubMed

Turkbey, Baris; Xu, Sheng; Kruecker, Jochen; Locklin, Julia; Pang, Yuxi; Shah, Vijay; Bernardo, Marcelino; Baccala, Angelo; Rastinehad, Ardeshir; Benjamin, Compton; Merino, Maria J; Wood, Bradford J; Choyke, Peter L; Pinto, Peter A

2011-03-29

During transrectal ultrasound (TRUS)-guided prostate biopsies, the actual location of the biopsy site is rarely documented. Here, we demonstrate the capability of TRUS-magnetic resonance imaging (MRI) image fusion to document the biopsy site and correlate biopsy results with multi-parametric MRI findings. Fifty consecutive patients (median age 61 years) with a median prostate-specific antigen (PSA) level of 5.8 ng/ml underwent 12-core TRUS-guided biopsy of the prostate. Pre-procedural T2-weighted magnetic resonance images were fused to TRUS. A disposable needle guide with miniature tracking sensors was attached to the TRUS probe to enable fusion with MRI. Real-time TRUS images during biopsy and the corresponding tracking information were recorded. Each biopsy site was superimposed onto the MRI. Each biopsy site was classified as positive or negative for cancer based on the results of each MRI sequence. Sensitivity, specificity, and receiver operating curve (ROC) area under the curve (AUC) values were calculated for multi-parametric MRI. Gleason scores for each multi-parametric MRI pattern were also evaluated. Six hundred and 5 systemic biopsy cores were analyzed in 50 patients, of whom 20 patients had 56 positive cores. MRI identified 34 of 56 positive cores. Overall, sensitivity, specificity, and ROC area values for multi-parametric MRI were 0.607, 0.727, 0.667, respectively. TRUS-MRI fusion after biopsy can be used to document the location of each biopsy site, which can then be correlated with MRI findings. Based on correlation with tracked biopsies, T2-weighted MRI and apparent diffusion coefficient maps derived from diffusion-weighted MRI are the most sensitive sequences, whereas the addition of delayed contrast enhancement MRI and three-dimensional magnetic resonance spectroscopy demonstrated higher specificity consistent with results obtained using radical prostatectomy specimens.

Advanced magnetic resonance imaging of neurodegenerative diseases.

PubMed

Agosta, Federica; Galantucci, Sebastiano; Filippi, Massimo

2017-01-01

Magnetic resonance imaging (MRI) is playing an increasingly important role in the study of neurodegenerative diseases, delineating the structural and functional alterations determined by these conditions. Advanced MRI techniques are of special interest for their potential to characterize the signature of each neurodegenerative condition and aid both the diagnostic process and the monitoring of disease progression. This aspect will become crucial when disease-modifying (personalized) therapies will be established. MRI techniques are very diverse and go from the visual inspection of MRI scans to more complex approaches, such as manual and automatic volume measurements, diffusion tensor MRI, and functional MRI. All these techniques allow us to investigate the different features of neurodegeneration. In this review, we summarize the most recent advances concerning the use of MRI in some of the most important neurodegenerative conditions, putting an emphasis on the advanced techniques.

A Randomised Controlled Trial of Efficacy of Cognitive Rehabilitation in Multiple Sclerosis: A Cognitive, Behavioural, and MRI Study.

PubMed

Campbell, J; Langdon, D; Cercignani, M; Rashid, W

2016-01-01

Aim. To explore the efficacy of home-based, computerised, cognitive rehabilitation in patients with multiple sclerosis using neuropsychological assessment and advanced structural and functional magnetic resonance imaging (fMRI). Methods. 38 patients with MS and cognitive impairment on the Brief International Cognitive Assessment for MS (BICAMS) were enrolled. Patients were randomised to undergo 45 minutes of computerised cognitive rehabilitation using RehaCom software ( n = 19) three times weekly for six weeks or to a control condition ( n = 19). Neuropsychological and MRI data were obtained at baseline (time 1), following the 6-week intervention (time 2), and after a further twelve weeks (time 3). Cortical activations were explored using fMRI and microstructural changes were explored using quantitative magnetisation transfer (QMT) imaging. Results. The treatment group showed a greater improvement in SDMT gain scores between baseline and time 2 compared to the control group ( p = 0.005). The treatment group exhibited increased activation in the bilateral prefrontal cortex and right temporoparietal regions relative to control group at time 3 ( p < 0.05 FWE  corrected ). No significant changes were observed on QMT. Conclusion. This study supports the hypothesis that home-based, computerised, cognitive rehabilitation may be effective in improving cognitive performance in patients with MS. Clinical trials registration is ISRCTN54901925.

In vivo functional connectome of human brainstem nuclei of the ascending arousal, autonomic, and motor systems by high spatial resolution 7-Tesla fMRI.

PubMed

Bianciardi, Marta; Toschi, Nicola; Eichner, Cornelius; Polimeni, Jonathan R; Setsompop, Kawin; Brown, Emery N; Hämäläinen, Matti S; Rosen, Bruce R; Wald, Lawrence L

2016-06-01

Our aim was to map the in vivo human functional connectivity of several brainstem nuclei with the rest of the brain by using seed-based correlation of ultra-high magnetic field functional magnetic resonance imaging (fMRI) data. We used the recently developed template of 11 brainstem nuclei derived from multi-contrast structural MRI at 7 Tesla as seed regions to determine their connectivity to the rest of the brain. To achieve this, we used the increased contrast-to-noise ratio of 7-Tesla fMRI compared with 3 Tesla and time-efficient simultaneous multi-slice imaging to cover the brain with high spatial resolution (1.1-mm isotropic nominal resolution) while maintaining a short repetition time (2.5 s). The delineated Pearson's correlation-based functional connectivity diagrams (connectomes) of 11 brainstem nuclei of the ascending arousal, motor, and autonomic systems from 12 controls are presented and discussed in the context of existing histology and animal work. Considering that the investigated brainstem nuclei play a crucial role in several vital functions, the delineated preliminary connectomes might prove useful for future in vivo research and clinical studies of human brainstem function and pathology, including disorders of consciousness, sleep disorders, autonomic disorders, Parkinson's disease, and other motor disorders.

Voltage-based device tracking in a 1.5 Tesla MRI during imaging: initial validation in swine models.

PubMed

Schmidt, Ehud J; Tse, Zion T H; Reichlin, Tobias R; Michaud, Gregory F; Watkins, Ronald D; Butts-Pauly, Kim; Kwong, Raymond Y; Stevenson, William; Schweitzer, Jeffrey; Byrd, Israel; Dumoulin, Charles L

2014-03-01

Voltage-based device-tracking (VDT) systems are commonly used for tracking invasive devices in electrophysiological cardiac-arrhythmia therapy. During electrophysiological procedures, electro-anatomic mapping workstations provide guidance by integrating VDT location and intracardiac electrocardiogram information with X-ray, computerized tomography, ultrasound, and MR images. MR assists navigation, mapping, and radiofrequency ablation. Multimodality interventions require multiple patient transfers between an MRI and the X-ray/ultrasound electrophysiological suite, increasing the likelihood of patient-motion and image misregistration. An MRI-compatible VDT system may increase efficiency, as there is currently no single method to track devices both inside and outside the MRI scanner. An MRI-compatible VDT system was constructed by modifying a commercial system. Hardware was added to reduce MRI gradient-ramp and radiofrequency unblanking pulse interference. VDT patches and cables were modified to reduce heating. Five swine cardiac VDT electro-anatomic mapping interventions were performed, navigating inside and thereafter outside the MRI. Three-catheter VDT interventions were performed at >12 frames per second both inside and outside the MRI scanner with <3 mm error. Catheters were followed on VDT- and MRI-derived maps. Simultaneous VDT and imaging was possible in repetition time >32 ms sequences with <0.5 mm errors, and <5% MRI signal-to-noise ratio (SNR) loss. At shorter repetition times, only intracardiac electrocardiogram was reliable. Radiofrequency heating was <1.5°C. An MRI-compatible VDT system is feasible. Copyright © 2013 Wiley Periodicals, Inc.

Voltage-based Device Tracking in a 1.5 Tesla MRI during Imaging: Initial validation in swine models

PubMed Central

Schmidt, Ehud J; Tse, Zion TH; Reichlin, Tobias R; Michaud, Gregory F; Watkins, Ronald D; Butts-Pauly, Kim; Kwong, Raymond Y; Stevenson, William; Schweitzer, Jeffrey; Byrd, Israel; Dumoulin, Charles L

2013-01-01

Purpose Voltage-based device-tracking (VDT) systems are commonly used for tracking invasive devices in electrophysiological (EP) cardiac-arrhythmia therapy. During EP procedures, electro-anatomic-mapping (EAM) workstations provide guidance by integrating VDT location and intra-cardiac-ECG information with X-ray, CT, Ultrasound, and MR images. MR assists navigation, mapping and radio-frequency-ablation. Multi-modality interventions require multiple patient transfers between an MRI and the X-ray/ultrasound EP suite, increasing the likelihood of patient-motion and image mis-registration. An MRI-compatible VDT system may increase efficiency, since there is currently no single method to track devices both inside and outside the MRI scanner. Methods An MRI-compatible VDT system was constructed by modifying a commercial system. Hardware was added to reduce MRI gradient-ramp and radio-frequency-unblanking-pulse interference. VDT patches and cables were modified to reduce heating. Five swine cardiac VDT EAM-mapping interventions were performed, navigating inside and thereafter outside the MRI. Results Three-catheter VDT interventions were performed at >12 frames-per-second both inside and outside the MRI scanner with <3mm error. Catheters were followed on VDT- and MRI-derived maps. Simultaneous VDT and imaging was possible in repetition-time (TR) >32 msec sequences with <0.5mm errors, and <5% MRI SNR loss. At shorter TRs, only intra-cardiac-ECG was reliable. RF Heating was <1.5C°. Conclusion An MRI-compatible VDT system is feasible. PMID:23580479

A comparison of 3-T magnetic resonance imaging and computed tomography arthrography to identify structural cartilage defects of the fetlock joint in the horse.

PubMed

Hontoir, Fanny; Nisolle, Jean-François; Meurisse, Hubert; Simon, Vincent; Tallier, Max; Vanderstricht, Renaud; Antoine, Nadine; Piret, Joëlle; Clegg, Peter; Vandeweerd, Jean-Michel

2014-01-01

Articular cartilage defects are prevalent in metacarpo/metatarsophalangeal (MCP/MTP) joints of horses. The aim of this study was to determine and compare the sensitivity and specificity of 3-Tesla magnetic resonance imaging (3-T MRI) and computed tomography arthrography (CTA) to identify structural cartilage defects in the equine MCP/MTP joint. Forty distal cadaver limbs were imaged by CTA (after injection of contrast medium) and by 3-T MRI using specific sequences, namely, dual-echo in the steady-state (DESS), and sampling perfection with application-optimised contrast using different flip-angle evolutions (SPACE). Gross anatomy was used as the gold standard to evaluate sensitivity and specificity of both imaging techniques. CTA sensitivity and specificity were 0.82 and 0.96, respectively, and were significantly higher than those of MRI (0.41 and 0.93, respectively) in detecting overall cartilage defects (no defect vs. defect). The intra and inter-rater agreements were 0.96 and 0.92, respectively, and 0.82 and 0.88, respectively, for CT and MRI. The positive predictive value for MRI was low (0.57). CTA was considered a valuable tool for assessing cartilage defects in the MCP/MTP joint due to its short acquisition time, its specificity and sensitivity, and it was also more accurate than MRI. However, MRI permits assessment of soft tissues and subchondral bone and is a useful technique for joint evaluation, although clinicians should be aware of the limitations of this diagnostic technique, including reduced accuracy. Copyright © 2013 Elsevier Ltd. All rights reserved.

Robust registration of sparsely sectioned histology to ex-vivo MRI of temporal lobe resections

NASA Astrophysics Data System (ADS)

Goubran, Maged; Khan, Ali R.; Crukley, Cathie; Buchanan, Susan; Santyr, Brendan; deRibaupierre, Sandrine; Peters, Terry M.

2012-02-01

Surgical resection of epileptic foci is a typical treatment for drug-resistant epilepsy, however, accurate preoperative localization is challenging and often requires invasive sub-dural or intra-cranial electrode placement. The presence of cellular abnormalities in the resected tissue can be used to validate the effectiveness of multispectralMagnetic Resonance Imaging (MRI) in pre-operative foci localization and surgical planning. If successful, these techniques can lead to improved surgical outcomes and less invasive procedures. Towards this goal, a novel pipeline is presented here for post-operative imaging of temporal lobe specimens involving MRI and digital histology, and present and evaluate methods for bringing these images into spatial correspondence. The sparsely-sectioned histology images of resected tissue represents a challenge for 3D reconstruction which we address with a combined 3D and 2D rigid registration algorithm that alternates between slice-based and volume-based registration with the ex-vivo MRI. We also evaluate four methods for non-rigid within-plane registration using both images and fiducials, with the top performing method resulting in a target registration error of 0.87 mm. This work allows for the spatially-local comparison of histology with post-operative MRI and paves the way for eventual registration with pre-operative MRI images.

Compressed Sensing for Body MRI

PubMed Central

Feng, Li; Benkert, Thomas; Block, Kai Tobias; Sodickson, Daniel K; Otazo, Ricardo; Chandarana, Hersh

2016-01-01

The introduction of compressed sensing for increasing imaging speed in MRI has raised significant interest among researchers and clinicians, and has initiated a large body of research across multiple clinical applications over the last decade. Compressed sensing aims to reconstruct unaliased images from fewer measurements than that are traditionally required in MRI by exploiting image compressibility or sparsity. Moreover, appropriate combinations of compressed sensing with previously introduced fast imaging approaches, such as parallel imaging, have demonstrated further improved performance. The advent of compressed sensing marks the prelude to a new era of rapid MRI, where the focus of data acquisition has changed from sampling based on the nominal number of voxels and/or frames to sampling based on the desired information content. This paper presents a brief overview of the application of compressed sensing techniques in body MRI, where imaging speed is crucial due to the presence of respiratory motion along with stringent constraints on spatial and temporal resolution. The first section provides an overview of the basic compressed sensing methodology, including the notion of sparsity, incoherence, and non-linear reconstruction. The second section reviews state-of-the-art compressed sensing techniques that have been demonstrated for various clinical body MRI applications. In the final section, the paper discusses current challenges and future opportunities. PMID:27981664

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.

Multimodal-3D imaging based on μMRI and μCT techniques bridges the gap with histology in visualization of the bone regeneration process.

PubMed

Sinibaldi, R; Conti, A; Sinjari, B; Spadone, S; Pecci, R; Palombo, M; Komlev, V S; Ortore, M G; Tromba, G; Capuani, S; Guidotti, R; De Luca, F; Caputi, S; Traini, T; Della Penna, S

2018-03-01

Bone repair/regeneration is usually investigated through X-ray computed microtomography (μCT) supported by histology of extracted samples, to analyse biomaterial structure and new bone formation processes. Magnetic resonance imaging (μMRI) shows a richer tissue contrast than μCT, despite at lower resolution, and could be combined with μCT in the perspective of conducting non-destructive 3D investigations of bone. A pipeline designed to combine μMRI and μCT images of bone samples is here described and applied on samples of extracted human jawbone core following bone graft. We optimized the coregistration procedure between μCT and μMRI images to avoid bias due to the different resolutions and contrasts. Furthermore, we used an Adaptive Multivariate Clustering, grouping homologous voxels in the coregistered images, to visualize different tissue types within a fused 3D metastructure. The tissue grouping matched the 2D histology applied only on 1 slice, thus extending the histology labelling in 3D. Specifically, in all samples, we could separate and map 2 types of regenerated bone, calcified tissue, soft tissues, and/or fat and marrow space. Remarkably, μMRI and μCT alone were not able to separate the 2 types of regenerated bone. Finally, we computed volumes of each tissue in the 3D metastructures, which might be exploited by quantitative simulation. The 3D metastructure obtained through our pipeline represents a first step to bridge the gap between the quality of information obtained from 2D optical microscopy and the 3D mapping of the bone tissue heterogeneity and could allow researchers and clinicians to non-destructively characterize and follow-up bone regeneration. Copyright © 2017 John Wiley & Sons, Ltd.

Quantification of red myotomal muscle volume and geometry in the shortfin mako shark (Isurus oxyrinchus) and the salmon shark (Lamna ditropis) using T1-weighted magnetic resonance imaging.

PubMed

Perry, Cameron N; Cartamil, Daniel P; Bernal, Diego; Sepulveda, Chugey A; Theilmann, Rebecca J; Graham, Jeffrey B; Frank, Lawrence R

2007-04-01

T1-weighted magnetic resonance imaging (MRI) in conjunction with image and segmentation analysis (i.e., the process of digitally partitioning tissues based on specified MR image characteristics) was evaluated as a noninvasive alternative for differentiating muscle fiber types and quantifying the amounts of slow, red aerobic muscle in the shortfin mako shark (Isurus oxyrinchus) and the salmon shark (Lamna ditropis). MRI-determinations of red muscle quantity and position made for the mid-body sections of three mako sharks (73.5-110 cm fork length, FL) are in close agreement (within the 95% confidence intervals) with data obtained for the same sections by the conventional dissection method involving serial cross-sectioning and volumetric analyses, and with previously reported findings for this species. The overall distribution of salmon shark red muscle as a function of body fork length was also found to be consistent with previously acquired serial dissection data for this species; however, MR imaging revealed an anterior shift in peak red muscle cross-sectional area corresponding to an increase in body mass. Moreover, MRI facilitated visualization of the intact and anatomically correct relationship of tendon linking the red muscle and the caudal peduncle. This study thus demonstrates that MRI is effective in acquiring high-resolution three-dimensional digital data with high contrast between different fish tissue types. Relative to serial dissection, MRI allows more precise quantification of the position, volume, and other details about the types of muscle within the fish myotome, while conserving specimen structural integrity. Copyright (c) 2007 Wiley-Liss, Inc.

Generation and evaluation of an ultra-high-field atlas with applications in DBS planning

NASA Astrophysics Data System (ADS)

Wang, Brian T.; Poirier, Stefan; Guo, Ting; Parrent, Andrew G.; Peters, Terry M.; Khan, Ali R.

2016-03-01

Purpose Deep brain stimulation (DBS) is a common treatment for Parkinson's disease (PD) and involves the use of brain atlases or intrinsic landmarks to estimate the location of target deep brain structures, such as the subthalamic nucleus (STN) and the globus pallidus pars interna (GPi). However, these structures can be difficult to localize with conventional clinical magnetic resonance imaging (MRI), and thus targeting can be prone to error. Ultra-high-field imaging at 7T has the ability to clearly resolve these structures and thus atlases built with these data have the potential to improve targeting accuracy. Methods T1 and T2-weighted images of 12 healthy control subjects were acquired using a 7T MR scanner. These images were then used with groupwise registration to generate an unbiased average template with T1w and T2w contrast. Deep brain structures were manually labelled in each subject by two raters and rater reliability was assessed. We compared the use of this unbiased atlas with two other methods of atlas-based segmentation (single-template and multi-template) for subthalamic nucleus (STN) segmentation on 7T MRI data. We also applied this atlas to clinical DBS data acquired at 1.5T to evaluate its efficacy for DBS target localization as compared to using a standard atlas. Results The unbiased templates provide superb detail of subcortical structures. Through one-way ANOVA tests, the unbiased template is significantly (p <0.05) more accurate than a single-template in atlas-based segmentation and DBS target localization tasks. Conclusion The generated unbiased averaged templates provide better visualization of deep brain nuclei and an increase in accuracy over single-template and lower field strength atlases.

Imaging Modalities Relevant to Intracranial Pressure Assessment in Astronauts

NASA Technical Reports Server (NTRS)

Sargsyan, Ashot E.; Kramer, Larry A.; Hamilton, Douglas R.; Fogarty, Jennifer; Polk, J. D.

2011-01-01

Learning Objectives of this slide presentation are: 1: To review the morphological changes in orbit structures caused by elevated Intracranial Pressure (ICP), and their imaging representation. 2: To learn about the similarities and differences between MRI and sonographic imaging of the eye and orbit. 3: To learn about the role of MRI and sonography in the noninvasive assessment of intracranial pressure in aerospace medicine, and the added benefits from their combined interpretation.

PET Imaging - from Physics to Clinical Molecular Imaging

NASA Astrophysics Data System (ADS)

Majewski, Stan

2008-03-01

From the beginnings many years ago in a few physics laboratories and first applications as a research brain function imager, PET became lately a leading molecular imaging modality used in diagnosis, staging and therapy monitoring of cancer, as well as has increased use in assessment of brain function (early diagnosis of Alzheimer's, etc) and in cardiac function. To assist with anatomic structure map and with absorption correction CT is often used with PET in a duo system. Growing interest in the last 5-10 years in dedicated organ specific PET imagers (breast, prostate, brain, etc) presents again an opportunity to the particle physics instrumentation community to contribute to the important field of medical imaging. In addition to the bulky standard ring structures, compact, economical and high performance mobile imagers are being proposed and build. The latest development in standard PET imaging is introduction of the well known TOF concept enabling clearer tomographic pictures of the patient organs. Development and availability of novel photodetectors such as Silicon PMT immune to magnetic fields offers an exciting opportunity to use PET in conjunction with MRI and fMRI. As before with avalanche photodiodes, particle physics community plays a leading role in developing these devices. The presentation will mostly focus on present and future opportunities for better PET designs based on new technologies and methods: new scintillators, photodetectors, readout, software.

Computer-Based Learning: Graphical Integration of Whole and Sectional Neuroanatomy Improves Long-Term Retention

ERIC Educational Resources Information Center

Naaz, Farah; Chariker, Julia H.; Pani, John R.

2014-01-01

A study was conducted to test the hypothesis that instruction with graphically integrated representations of whole and sectional neuroanatomy is especially effective for learning to recognize neural structures in sectional imagery (such as magnetic resonance imaging [MRI]). Neuroanatomy was taught to two groups of participants using computer…

Experimental MRI-SPECT insert system with Hybrid Semiconductor detectors Timepix for MR animal scanner Bruker 47/20

NASA Astrophysics Data System (ADS)

Zajicek, J.; Burian, M.; Soukup, P.; Novak, V.; Macko, M.; Jakubek, J.

2017-01-01

Multimodal medical imaging based on Magnetic Resonance is mainly combinated with one of the scintigraphic method like PET or SPECT. These methods provide functional information whereas magnetic resonance imaging provides high spatial resolution of anatomical information or complementary functional information. Fusion of imaging modalities allows researchers to obtain complimentary information in a single measurement. The combination of MRI with SPECT is still relatively new and challenging in many ways. The main complication of using SPECT in MRI systems is the presence of a high magnetic field therefore (ferro)magnetic materials have to be eliminated. Furthermore the application of radiofrequency fields within the MR gantry does not allow for the use of conductive structures such as the common heavy metal collimators. This work presents design and construction of an experimental MRI-SPECT insert system and its initial tests. This unique insert system consists of an MR-compatible SPECT setup with CdTe pixelated sensors Timepix tungsten collimators and a radiofrequency coil. Measurements were performed on a gelatine and tissue phantom with an embedded radioisotopic source (57Co 122 keV γ ray) inside the RF coil by the Bruker BioSpec 47/20 (4.7 T) MR animal scanner. The project was performed in the framework of the Medipix Collaboration.

Initial tests of a prototype MRI-compatible PET imager

NASA Astrophysics Data System (ADS)

Raylman, Raymond R.; Majewski, Stan; Lemieux, Susan; Velan, S. Sendhil; Kross, Brain; Popov, Vladimir; Smith, Mark F.; Weisenberger, Andrew G.; Wojcik, Randy

2006-12-01

Multi-modality imaging is rapidly becoming a valuable tool in the diagnosis of disease and in the development of new drugs. Functional images produced with PET fused with anatomical structure images created by MRI, will allow the correlation of form with function. Our group (a collaboration of West Virginia University and Jefferson Lab) is developing a system to acquire MRI and PET images contemporaneously. The prototype device consists of two opposed detector heads, operating in coincidence mode with an active FOV of 5×5×4 cm 3. Each MRI-PET detector module consists of an array of LSO detector elements (2.5×2.5×15 mm 3) coupled through a long fiber optic light guide to a single Hamamatsu flat panel PSPMT. The fiber optic light guide is made of a glued assembly of 2 mm diameter acrylic fibers with a total length of 2.5 m. The use of a light guides allows the PSPMTs to be positioned outside the bore of the 3 T General Electric MRI scanner used in the tests. Photon attenuation in the light guides resulted in an energy resolution of ˜60% FWHM, interaction of the magnetic field with PSPMT further reduced energy resolution to ˜85% FWHM. Despite this effect, excellent multi-plane PET and MRI images of a simple disk phantom were acquired simultaneously. Future work includes improved light guides, optimized magnetic shielding for the PSPMTs, construction of specialized coils to permit high-resolution MRI imaging, and use of the system to perform simultaneous PET and MRI or MR-spectroscopy .

Sensitivity analysis of brain morphometry based on MRI-derived surface models

NASA Astrophysics Data System (ADS)

Klein, Gregory J.; Teng, Xia; Schoenemann, P. T.; Budinger, Thomas F.

1998-07-01

Quantification of brain structure is important for evaluating changes in brain size with growth and aging and for characterizing neurodegeneration disorders. Previous quantification efforts using ex vivo techniques suffered considerable error due to shrinkage of the cerebrum after extraction from the skull, deformation of slices during sectioning, and numerous other factors. In vivo imaging studies of brain anatomy avoid these problems and allow repetitive studies following progression of brain structure changes due to disease or natural processes. We have developed a methodology for obtaining triangular mesh models of the cortical surface from MRI brain datasets. The cortex is segmented from nonbrain tissue using a 2D region-growing technique combined with occasional manual edits. Once segmented, thresholding and image morphological operations (erosions and openings) are used to expose the regions between adjacent surfaces in deep cortical folds. A 2D region- following procedure is then used to find a set of contours outlining the cortical boundary on each slice. The contours on all slices are tiled together to form a closed triangular mesh model approximating the cortical surface. This model can be used for calculation of cortical surface area and volume, as well as other parameters of interest. Except for the initial segmentation of the cortex from the skull, the technique is automatic and requires only modest computation time on modern workstations. Though the use of image data avoids many of the pitfalls of ex vivo and sectioning techniques, our MRI-based technique is still vulnerable to errors that may impact the accuracy of estimated brain structure parameters. Potential inaccuracies include segmentation errors due to incorrect thresholding, missed deep sulcal surfaces, falsely segmented holes due to image noise and surface tiling artifacts. The focus of this paper is the characterization of these errors and how they affect measurements of cortical surface area and volume.