Utility of texture analysis for quantifying hepatic fibrosis on proton density MRI.

PubMed

Yu, HeiShun; Buch, Karen; Li, Baojun; O'Brien, Michael; Soto, Jorge; Jara, Hernan; Anderson, Stephan W

2015-11-01

To evaluate the potential utility of texture analysis of proton density maps for quantifying hepatic fibrosis in a murine model of hepatic fibrosis. Following Institutional Animal Care and Use Committee (IACUC) approval, a dietary model of hepatic fibrosis was used and 15 ex vivo murine liver tissues were examined. All images were acquired using a 30 mm bore 11.7T magnetic resonance imaging (MRI) scanner with a multiecho spin-echo sequence. A texture analysis was employed extracting multiple texture features including histogram-based, gray-level co-occurrence matrix-based (GLCM), gray-level run-length-based features (GLRL), gray level gradient matrix (GLGM), and Laws' features. Texture features were correlated with histopathologic and digital image analysis of hepatic fibrosis. Histogram features demonstrated very weak to moderate correlations (r = -0.29 to 0.51) with hepatic fibrosis. GLCM features correlation and contrast demonstrated moderate-to-strong correlations (r = -0.71 and 0.59, respectively) with hepatic fibrosis. Moderate correlations were seen between hepatic fibrosis and the GLRL feature short run low gray-level emphasis (SRLGE) (r = -0. 51). GLGM features demonstrate very weak to weak correlations with hepatic fibrosis (r = -0.27 to 0.09). Moderate correlations were seen between hepatic fibrosis and Laws' features L6 and L7 (r = 0.58). This study demonstrates the utility of texture analysis applied to proton density MRI in a murine liver fibrosis model and validates the potential utility of texture-based features for the noninvasive, quantitative assessment of hepatic fibrosis. © 2015 Wiley Periodicals, Inc.

ACCELERATING MR PARAMETER MAPPING USING SPARSITY-PROMOTING REGULARIZATION IN PARAMETRIC DIMENSION

PubMed Central

Velikina, Julia V.; Alexander, Andrew L.; Samsonov, Alexey

2013-01-01

MR parameter mapping requires sampling along additional (parametric) dimension, which often limits its clinical appeal due to a several-fold increase in scan times compared to conventional anatomic imaging. Data undersampling combined with parallel imaging is an attractive way to reduce scan time in such applications. However, inherent SNR penalties of parallel MRI due to noise amplification often limit its utility even at moderate acceleration factors, requiring regularization by prior knowledge. In this work, we propose a novel regularization strategy, which utilizes smoothness of signal evolution in the parametric dimension within compressed sensing framework (p-CS) to provide accurate and precise estimation of parametric maps from undersampled data. The performance of the method was demonstrated with variable flip angle T1 mapping and compared favorably to two representative reconstruction approaches, image space-based total variation regularization and an analytical model-based reconstruction. The proposed p-CS regularization was found to provide efficient suppression of noise amplification and preservation of parameter mapping accuracy without explicit utilization of analytical signal models. The developed method may facilitate acceleration of quantitative MRI techniques that are not suitable to model-based reconstruction because of complex signal models or when signal deviations from the expected analytical model exist. PMID:23213053

Arterial Spin Labeling - Fast Imaging with Steady-State Free Precession (ASL-FISP): A Rapid and Quantitative Perfusion Technique for High Field MRI

PubMed Central

Gao, Ying; Goodnough, Candida L.; Erokwu, Bernadette O.; Farr, George W.; Darrah, Rebecca; Lu, Lan; Dell, Katherine M.; Yu, Xin; Flask, Chris A.

2014-01-01

Arterial Spin Labeling (ASL) is a valuable non-contrast perfusion MRI technique with numerous clinical applications. Many previous ASL MRI studies have utilized either Echo-Planar Imaging (EPI) or True Fast Imaging with Steady-State Free Precession (True FISP) readouts that are prone to off-resonance artifacts on high field MRI scanners. We have developed a rapid ASL-FISP MRI acquisition for high field preclinical MRI scanners providing perfusion-weighted images with little or no artifacts in less than 2 seconds. In this initial implementation, a FAIR (Flow-Sensitive Alternating Inversion Recovery) ASL preparation was combined with a rapid, centrically-encoded FISP readout. Validation studies on healthy C57/BL6 mice provided consistent estimation of in vivo mouse brain perfusion at 7 T and 9.4 T (249±38 ml/min/100g and 241±17 ml/min/100g, respectively). The utility of this method was further demonstrated in detecting significant perfusion deficits in a C57/BL6 mouse model of ischemic stroke. Reasonable kidney perfusion estimates were also obtained for a healthy C57/BL6 mouse exhibiting differential perfusion in the renal cortex and medulla. Overall, the ASL-FISP technique provides a rapid and quantitative in vivo assessment of tissue perfusion for high field MRI scanners with minimal image artifacts. PMID:24891124

Cost-effectiveness of EOB-MRI for Hepatocellular Carcinoma in Japan.

PubMed

Nishie, Akihiro; Goshima, Satoshi; Haradome, Hiroki; Hatano, Etsuro; Imai, Yasuharu; Kudo, Masatoshi; Matsuda, Masanori; Motosugi, Utaroh; Saitoh, Satoshi; Yoshimitsu, Kengo; Crawford, Bruce; Kruger, Eliza; Ball, Graeme; Honda, Hiroshi

2017-04-01

The objective of the study was to evaluate the cost-effectiveness of gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI) in the diagnosis and treatment of hepatocellular carcinoma (HCC) in Japan compared with extracellular contrast media-enhanced MRI (ECCM-MRI) and contrast media-enhanced computed tomography (CE-CT) scanning. A 6-stage Markov model was developed to estimate lifetime direct costs and clinical outcomes associated with EOB-MRI. Diagnostic sensitivity and specificity, along with clinical data on HCC survival, recurrence, treatment patterns, costs, and health state utility values, were derived from predominantly Japanese publications. Parameters unavailable from publications were estimated in a Delphi panel of Japanese clinical experts who also confirmed the structure and overall approach of the model. Sensitivity analyses, including one-way, probabilistic, and scenario analyses, were conducted to account for uncertainty in the results. Over a lifetime horizon, EOB-MRI was associated with lower direct costs (¥2,174,869) and generated a greater number of quality-adjusted life years (QALYs) (9.502) than either ECCM-MRI (¥2,365,421, 9.303 QALYs) or CE-CT (¥2,482,608, 9.215 QALYs). EOB-MRI was superior to the other diagnostic strategies considered, and this finding was robust over sensitivity and scenario analyses. A majority of the direct costs associated with HCC in Japan were found to be costs of treatment. The model results revealed the superior cost-effectiveness of the EOB-MRI diagnostic strategy compared with ECCM-MRI and CE-CT. EOB-MRI could be the first-choice imaging modality for medical care of HCC among patients with hepatitis or liver cirrhosis in Japan. Widespread implementation of EOB-MRI could reduce health care expenditures, particularly downstream treatment costs, associated with HCC. Copyright © 2017 Elsevier HS Journals, Inc. All rights reserved.

Nonvascular thoracic magnetic resonance imaging: the current state of training, utilization, and perceived value: survey of the Society of Thoracic Radiology membership.

PubMed

Ackman, Jeanne B; Wu, Carol C; Halpern, Elkan F; Abbott, Gerald F; Shepard, Jo-Anne O

2014-07-01

The aim of the study was to determine the current state of training, utilization, and perceived value of nonvascular thoracic magnetic resonance imaging (MRI). The URL link for this anonymous, IRB-approved survey was e-mailed to all Society of Thoracic Radiology members with available e-mail addresses (733), of whom 693 were qualified to respond as per the survey's instructions. Survey questions focused on MRI training, interpretation volume, perceived value of thoracic MRI, and barriers to its utilization. Study data were collected and managed using Research Electronic Data Capture (REDCap) electronic data capture tools and analyzed with χ tests. The survey response rate was 27% (190/693). Thirty-seven percent (67/180) of respondents reported that they interpreted and reported zero thoracic MRIs and 64% (116/182) interpreted or reported <10 MRIs over the prior year. The perceived value of thoracic MRI was highest for chest wall and neurovascular involvement and evaluation of the mediastinum, particularly thymus, next highest for assessment of pleural or diaphragmatic lesions, and lowest for assessment of lung function with hyperpolarized gases. Seventy-three percent (121/166) of respondents felt it would be of value to increase utilization of thoracic MRI. Perceived obstacles to increasing thoracic MRI utilization included lack of: awareness of referring health care providers as to the value of thoracic MRI (59%, 98/166), radiologist proficiency or comfort with thoracic MRI (46%, 77/166), standardized protocols (38%, 64/166), technologist experience (38%, 63/166), and sufficient training during residency and/or fellowship (32%, 54/166). Twenty-five percent (41/166) of respondents reported insufficient thoracic MRI literature and limited CME courses and lectures in this field as an additional impediment. The majority of survey respondents reported limited experience in thoracic MRI interpretation, a recognition of thoracic MRI's value, and an interest in increasing its utilization. Improved education of radiologists, technologists, and referring clinicians would ameliorate the current state.

Infinite von Mises-Fisher Mixture Modeling of Whole Brain fMRI Data.

PubMed

Røge, Rasmus E; Madsen, Kristoffer H; Schmidt, Mikkel N; Mørup, Morten

2017-10-01

Cluster analysis of functional magnetic resonance imaging (fMRI) data is often performed using gaussian mixture models, but when the time series are standardized such that the data reside on a hypersphere, this modeling assumption is questionable. The consequences of ignoring the underlying spherical manifold are rarely analyzed, in part due to the computational challenges imposed by directional statistics. In this letter, we discuss a Bayesian von Mises-Fisher (vMF) mixture model for data on the unit hypersphere and present an efficient inference procedure based on collapsed Markov chain Monte Carlo sampling. Comparing the vMF and gaussian mixture models on synthetic data, we demonstrate that the vMF model has a slight advantage inferring the true underlying clustering when compared to gaussian-based models on data generated from both a mixture of vMFs and a mixture of gaussians subsequently normalized. Thus, when performing model selection, the two models are not in agreement. Analyzing multisubject whole brain resting-state fMRI data from healthy adult subjects, we find that the vMF mixture model is considerably more reliable than the gaussian mixture model when comparing solutions across models trained on different groups of subjects, and again we find that the two models disagree on the optimal number of components. The analysis indicates that the fMRI data support more than a thousand clusters, and we confirm this is not a result of overfitting by demonstrating better prediction on data from held-out subjects. Our results highlight the utility of using directional statistics to model standardized fMRI data and demonstrate that whole brain segmentation of fMRI data requires a very large number of functional units in order to adequately account for the discernible statistical patterns in the data.

Automatic diagnosis of lumbar disc herniation with shape and appearance features from MRI

NASA Astrophysics Data System (ADS)

Alomari, Raja'S.; Corso, Jason J.; Chaudhary, Vipin; Dhillon, Gurmeet

2010-03-01

Intervertebral disc herniation is a major reason for lower back pain (LBP), which is the second most common neurological ailment in the United States. Automation of herniated disc diagnosis reduces the large burden on radiologists who have to diagnose hundreds of cases each day using clinical MRI. We present a method for automatic diagnosis of lumbar disc herniation using appearance and shape features. We jointly use the intensity signal for modeling the appearance of herniated disc and the active shape model for modeling the shape of herniated disc. We utilize a Gibbs distribution for classification of discs using appearance and shape features. We use 33 clinical MRI cases of the lumbar area for training and testing both appearance and shape models. We achieve over 91% accuracy in detection of herniation in a cross-validation experiment with specificity of 91% and sensitivity of 94%.

Improved brain tumor segmentation by utilizing tumor growth model in longitudinal brain MRI

NASA Astrophysics Data System (ADS)

Pei, Linmin; Reza, Syed M. S.; Li, Wei; Davatzikos, Christos; Iftekharuddin, Khan M.

2017-03-01

In this work, we propose a novel method to improve texture based tumor segmentation by fusing cell density patterns that are generated from tumor growth modeling. To model tumor growth, we solve the reaction-diffusion equation by using Lattice-Boltzmann method (LBM). Computational tumor growth modeling obtains the cell density distribution that potentially indicates the predicted tissue locations in the brain over time. The density patterns is then considered as novel features along with other texture (such as fractal, and multifractal Brownian motion (mBm)), and intensity features in MRI for improved brain tumor segmentation. We evaluate the proposed method with about one hundred longitudinal MRI scans from five patients obtained from public BRATS 2015 data set, validated by the ground truth. The result shows significant improvement of complete tumor segmentation using ANOVA analysis for five patients in longitudinal MR images.

Improved brain tumor segmentation by utilizing tumor growth model in longitudinal brain MRI.

PubMed

Pei, Linmin; Reza, Syed M S; Li, Wei; Davatzikos, Christos; Iftekharuddin, Khan M

2017-02-11

In this work, we propose a novel method to improve texture based tumor segmentation by fusing cell density patterns that are generated from tumor growth modeling. In order to model tumor growth, we solve the reaction-diffusion equation by using Lattice-Boltzmann method (LBM). Computational tumor growth modeling obtains the cell density distribution that potentially indicates the predicted tissue locations in the brain over time. The density patterns is then considered as novel features along with other texture (such as fractal, and multifractal Brownian motion (mBm)), and intensity features in MRI for improved brain tumor segmentation. We evaluate the proposed method with about one hundred longitudinal MRI scans from five patients obtained from public BRATS 2015 data set, validated by the ground truth. The result shows significant improvement of complete tumor segmentation using ANOVA analysis for five patients in longitudinal MR images.

Fabrication of custom-shaped grafts for cartilage regeneration.

PubMed

Koo, Seungbum; Hargreaves, Brian A; Gold, Garry E; Dragoo, Jason L

2010-10-01

to create a custom-shaped graft through 3D tissue shape reconstruction and rapid-prototype molding methods using MRI data, and to test the accuracy of the custom-shaped graft against the original anatomical defect. An iatrogenic defect on the distal femur was identified with a 1.5 Tesla MRI and its shape was reconstructed into a three-dimensional (3D) computer model by processing the 3D MRI data. First, the accuracy of the MRI-derived 3D model was tested against a laser-scan based 3D model of the defect. A custom-shaped polyurethane graft was fabricated from the laser-scan based 3D model by creating custom molds through computer aided design and rapid-prototyping methods. The polyurethane tissue was laser-scanned again to calculate the accuracy of this process compared to the original defect. The volumes of the defect models from MRI and laser-scan were 537 mm3 and 405 mm3, respectively, implying that the MRI model was 33% larger than the laser-scan model. The average (±SD) distance deviation of the exterior surface of the MRI model from the laser-scan model was 0.4 ± 0.4 mm. The custom-shaped tissue created from the molds was qualitatively very similar to the original shape of the defect. The volume of the custom-shaped cartilage tissue was 463 mm3 which was 15% larger than the laser-scan model. The average (±SD) distance deviation between the two models was 0.04 ± 0.19 mm. This investigation proves the concept that custom-shaped engineered grafts can be fabricated from standard sequence 3-D MRI data with the use of CAD and rapid-prototyping technology. The accuracy of this technology may help solve the interfacial problem between native cartilage and graft, if the grafts are custom made for the specific defect. The major source of error in fabricating a 3D custom-shaped cartilage graft appears to be the accuracy of a MRI data itself; however, the precision of the model is expected to increase by the utilization of advanced MR sequences with higher magnet strengths.

Cost Analysis of the Addition of Hyperacute Magnetic Resonance Imaging for Selection of Patients for Endovascular Stroke Therapy.

PubMed

John, Seby; Thompson, Nicolas R; Lesko, Terry; Papesh, Nancy; Obuchowski, Nancy; Tomic, Dan; Wisco, Dolora; Khawaja, Zeshaun; Uchino, Ken; Man, Shumei; Cheng-Ching, Esteban; Toth, Gabor; Masaryk, Thomas; Ruggieri, Paul; Modic, Michael; Hussain, Muhammad Shazam

2017-10-01

Patient selection is important to determine the best candidates for endovascular stroke therapy. In application of a hyperacute magnetic resonance imaging (MRI) protocol for patient selection, we have shown decreased utilization with improved outcomes. A cost analysis comparing the pre- and post-MRI protocol time periods was performed to determine if the previous findings translated into cost opportunities. We retrospectively identified individuals considered for endovascular stroke therapy from January 2008 to August 2012 who were ≤8 h from stroke symptoms onset. Patients prior to April 30, 2010 were selected based on results of the computed tomography/computed tomography angiography alone (pre-hyperacute), whereas patients after April 30, 2010 were selected based on results of MRI (post-hyperacute MRI). Demographic, outcome, and financial information was collected. Log-transformed average daily direct costs were regressed on time period. The regression model included demographic and clinical covariates as potential confounders. Multiple imputation was used to account for missing data. We identified 267 patients in our database (88 patients in pre-hyperacute MRI period, 179 in hyperacute MRI protocol period). Patient length of stay was not significantly different in the hyperacute MRI protocol period as compared to the pre-hyperacute MRI period (10.6 vs. 9.9 days, p < 0.42). The median of average daily direct costs was reduced by 24.5% (95% confidence interval 14.1-33.7%, p < 0.001). Use of the hyperacute MRI protocol translated into reduced costs, in addition to reduced utilization and better outcomes. MRI selection of patients is an effective strategy, both for patients and hospital systems.

Characterization of anomalous relaxation using the time-fractional Bloch equation and multiple echo T2 *-weighted magnetic resonance imaging at 7 T.

PubMed

Qin, Shanlin; Liu, Fawang; Turner, Ian W; Yu, Qiang; Yang, Qianqian; Vegh, Viktor

2017-04-01

To study the utility of fractional calculus in modeling gradient-recalled echo MRI signal decay in the normal human brain. We solved analytically the extended time-fractional Bloch equations resulting in five model parameters, namely, the amplitude, relaxation rate, order of the time-fractional derivative, frequency shift, and constant offset. Voxel-level temporal fitting of the MRI signal was performed using the classical monoexponential model, a previously developed anomalous relaxation model, and using our extended time-fractional relaxation model. Nine brain regions segmented from multiple echo gradient-recalled echo 7 Tesla MRI data acquired from five participants were then used to investigate the characteristics of the extended time-fractional model parameters. We found that the extended time-fractional model is able to fit the experimental data with smaller mean squared error than the classical monoexponential relaxation model and the anomalous relaxation model, which do not account for frequency shift. We were able to fit multiple echo time MRI data with high accuracy using the developed model. Parameters of the model likely capture information on microstructural and susceptibility-induced changes in the human brain. Magn Reson Med 77:1485-1494, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Supervised dictionary learning for inferring concurrent brain networks.

PubMed

Zhao, Shijie; Han, Junwei; Lv, Jinglei; Jiang, Xi; Hu, Xintao; Zhao, Yu; Ge, Bao; Guo, Lei; Liu, Tianming

2015-10-01

Task-based fMRI (tfMRI) has been widely used to explore functional brain networks via predefined stimulus paradigm in the fMRI scan. Traditionally, the general linear model (GLM) has been a dominant approach to detect task-evoked networks. However, GLM focuses on task-evoked or event-evoked brain responses and possibly ignores the intrinsic brain functions. In comparison, dictionary learning and sparse coding methods have attracted much attention recently, and these methods have shown the promise of automatically and systematically decomposing fMRI signals into meaningful task-evoked and intrinsic concurrent networks. Nevertheless, two notable limitations of current data-driven dictionary learning method are that the prior knowledge of task paradigm is not sufficiently utilized and that the establishment of correspondences among dictionary atoms in different brains have been challenging. In this paper, we propose a novel supervised dictionary learning and sparse coding method for inferring functional networks from tfMRI data, which takes both of the advantages of model-driven method and data-driven method. The basic idea is to fix the task stimulus curves as predefined model-driven dictionary atoms and only optimize the other portion of data-driven dictionary atoms. Application of this novel methodology on the publicly available human connectome project (HCP) tfMRI datasets has achieved promising results.

Evaluation of neovascularization patterns in an orthotopic rat glioma model with dynamic contrast-enhanced MRI.

PubMed

Xuesong, Du; Wei, Xue; Heng, Liu; Xiao, Chen; Shunan, Wang; Yu, Guo; Weiguo, Zhang

2017-09-01

Background Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been proved useful in evaluating glioma angiogenesis, but the utility in evaluating neovascularization patterns has not been reported. Purpose To evaluate in vivo real-time glioma neovascularization patterns by measuring glioma perfusion quantitatively using DCE-MRI. Material and Methods Thirty Sprague-Dawley rats were used to establish C6 orthotopic glioma model and underwent MRI and pathology detections. As MRI and pathology were performed at six time points (i.e. 4, 8, 12, 16, 20, and 24 days) post transplantation, neovascularization patterns were evaluated via DCE-MRI. Results Four neovascularization patterns were observed in glioma tissues. Sprout angiogenesis and intussusceptive microvascular growth located inside tumor, while vascular co-option and vascular mimicry were found in the tumor margin and necrotic area, respectively. Sprout angiogenesis and intussusceptive microvascular growth increased with K trans , K ep , and V p inside tumor tissue. In addition, K ep and V p were positively correlated with sprout angiogenesis and intussusceptive microvascular growth. Vascular co-option was decreased at 12 and 16 days post transplantation and correlated negatively with K trans and K ep detected in the glioma margin, respectively. Changes of vascular mimicry showed no significant statistical difference at the six time points. Conclusion Our results indicate that DCE-MRI can evaluate neovascularization patterns in a glioma model. Furthermore, DCE-MRI could be an imaging biomarker for guidance of antiangiogenic treatments in humans in the future.

Non-Invasive Magnetic Resonance Imaging of Nanoparticle Migration and Water Velocity Inside Sandstone

NASA Astrophysics Data System (ADS)

Phoenix, V. R.; Shukla, M.; Vallatos, A.; Riley, M. S.; Tellam, J. H.; Holmes, W. M.

2015-12-01

Manufactured nanoparticles (NPs) are already utilized in a diverse array of applications, including cosmetics, optics, medical technology, textiles and catalysts. Problematically, once in the natural environment, NPs can have a wide range of toxic effects. To protect groundwater from detrimental NPs we must be able to predict nanoparticle movement within the aquifer. The often complex transport behavior of nanoparticles ensures the development of NP transport models is not a simple task. To enhance our understanding of NP transport processes, we utilize novel magnetic resonance imaging (MRI) which enables us to look inside the rock and image the movement of nanoparticles within. For this, we use nanoparticles that are paramagnetic, making them visible to the MRI and enabling us to collect spatially resolved data from which we can develop more robust transport models. In this work, a core of Bentheimer sandstone (3 x 7 cm) was saturated with water and imaged inside a 7Tesla Bruker Biospec MRI. Firstly the porosity of the core was mapped using a MSME MRI sequence. Prior to imaging NP transport, the velocity of water (in absence on nanoparticles) was mapped using an APGSTE-RARE sequence. Nano-magnetite nanoparticles were then pumped into the core and their transport through the core was imaged using a RARE sequence. These images were calibrated using T2 parameter maps to provide fully quantitative maps of nanoparticle concentration at regular time intervals throughout the column (T2 being the spin-spin relaxation time of 1H nuclei). This work demonstrated we are able to spatially resolve porosity, water velocity and nanoparticle movement, inside rock, using a single technique (MRI). Significantly, this provides us with a unique and powerful dataset from which we are now developing new models of nanoparticle transport.

Accurate reconstruction of 3D cardiac geometry from coarsely-sliced MRI.

PubMed

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

2014-02-01

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

Dynamic deformable models for 3D MRI heart segmentation

NASA Astrophysics Data System (ADS)

Zhukov, Leonid; Bao, Zhaosheng; Gusikov, Igor; Wood, John; Breen, David E.

2002-05-01

Automated or semiautomated segmentation of medical images decreases interstudy variation, observer bias, and postprocessing time as well as providing clincally-relevant quantitative data. In this paper we present a new dynamic deformable modeling approach to 3D segmentation. It utilizes recently developed dynamic remeshing techniques and curvature estimation methods to produce high-quality meshes. The approach has been implemented in an interactive environment that allows a user to specify an initial model and identify key features in the data. These features act as hard constraints that the model must not pass through as it deforms. We have employed the method to perform semi-automatic segmentation of heart structures from cine MRI data.

A comparison of exogenous and endogenous CEST MRI methods for evaluating in vivo pH.

PubMed

Lindeman, Leila R; Randtke, Edward A; High, Rachel A; Jones, Kyle M; Howison, Christine M; Pagel, Mark D

2018-05-01

Extracellular pH (pHe) is an important biomarker for cancer cell metabolism. Acido-chemical exchange saturation transfer (CEST) MRI uses the contrast agent iopamidol to create spatial maps of pHe. Measurements of amide proton transfer exchange rates (k ex ) from endogenous CEST MRI were compared to pHe measurements by exogenous acido-CEST MRI to determine whether endogenous k ex could be used as a proxy for pHe measurements. Spatial maps of pHe and k ex were obtained using exogenous acidoCEST MRI and an endogenous CEST MRI analyzed with the omega plot method, respectively, to evaluate mouse kidney, a flank tumor model, and a spontaneous lung tumor model. The pHe and k ex results were evaluated using pixelwise comparisons. The k ex values obtained from endogenous CEST measurements did not correlate with the pHe results from exogenous CEST measurements. The k ex measurements were limited to fewer pixels and had a limited dynamic range relative to pHe measurements. Measurements of k ex with endogenous CEST MRI cannot substitute for pHe measurements with acidoCEST MRI. Whereas endogenous CEST MRI may still have good utility for evaluating some specific pathologies, exogenous acido-CEST MRI is more appropriate when evaluating pathologies based on pHe values. Magn Reson Med 79:2766-2772, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Bayesian estimation of optical properties of the human head via 3D structural MRI

NASA Astrophysics Data System (ADS)

Barnett, Alexander H.; Culver, Joseph P.; Sorensen, A. Gregory; Dale, Anders M.; Boas, David A.

2003-10-01

Knowledge of the baseline optical properties of the tissues of the human head is essential for absolute cerebral oximetry, and for quantitative studies of brain activation. In this work we numerically model the utility of signals from a small 6-optode time-resolved diffuse optical tomographic apparatus for inferring baseline scattering and absorption coefficients of the scalp, skull and brain, when complete geometric information is available from magnetic resonance imaging (MRI). We use an optical model where MRI-segmented tissues are assumed homogeneous. We introduce a noise model capturing both photon shot noise and forward model numerical accuracy, and use Bayesian inference to predict errorbars and correlations on the measurments. We also sample from the full posterior distribution using Markov chain Monte Carlo. We conclude that ~ 106 detected photons are sufficient to measure the brain"s scattering and absorption to a few percent. We present preliminary results using a fast multi-layer slab model, comparing the case when layer thicknesses are known versus unknown.

A behavioural and neural evaluation of prospective decision-making under risk

PubMed Central

Symmonds, Mkael; Bossaerts, Peter; Dolan, Raymond J.

2010-01-01

Making the best choice when faced with a chain of decisions requires a person to judge both anticipated outcomes and future actions. Although economic decision-making models account for both risk and reward in single choice contexts there is a dearth of similar knowledge about sequential choice. Classical utility-based models assume that decision-makers select and follow an optimal pre-determined strategy, irrespective of the particular order in which options are presented. An alternative model involves continuously re-evaluating decision utilities, without prescribing a specific future set of choices. Here, using behavioral and functional magnetic resonance imaging (fMRI) data, we studied human subjects in a sequential choice task and use these data to compare alternative decision models of valuation and strategy selection. We provide evidence that subjects adopt a model of re-evaluating decision utilities, where available strategies are continuously updated and combined in assessing action values. We validate this model by using simultaneously-acquired fMRI data to show that sequential choice evokes a pattern of neural response consistent with a tracking of anticipated distribution of future reward, as expected in such a model. Thus, brain activity evoked at each decision point reflects the expected mean, variance and skewness of possible payoffs, consistent with the idea that sequential choice evokes a prospective evaluation of both available strategies and possible outcomes. PMID:20980595

A behavioral and neural evaluation of prospective decision-making under risk.

PubMed

Symmonds, Mkael; Bossaerts, Peter; Dolan, Raymond J

2010-10-27

Making the best choice when faced with a chain of decisions requires a person to judge both anticipated outcomes and future actions. Although economic decision-making models account for both risk and reward in single-choice contexts, there is a dearth of similar knowledge about sequential choice. Classical utility-based models assume that decision-makers select and follow an optimal predetermined strategy, regardless of the particular order in which options are presented. An alternative model involves continuously reevaluating decision utilities, without prescribing a specific future set of choices. Here, using behavioral and functional magnetic resonance imaging (fMRI) data, we studied human subjects in a sequential choice task and use these data to compare alternative decision models of valuation and strategy selection. We provide evidence that subjects adopt a model of reevaluating decision utilities, in which available strategies are continuously updated and combined in assessing action values. We validate this model by using simultaneously acquired fMRI data to show that sequential choice evokes a pattern of neural response consistent with a tracking of anticipated distribution of future reward, as expected in such a model. Thus, brain activity evoked at each decision point reflects the expected mean, variance, and skewness of possible payoffs, consistent with the idea that sequential choice evokes a prospective evaluation of both available strategies and possible outcomes.

MO-FG-207-03: Maximizing the Utility of Integrated PET/MRI in Clinical Applications

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

Behr, S.

2015-06-15

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applicationsmore » that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee.« less

Fabrication of Custom-Shaped Grafts for Cartilage Regeneration

PubMed Central

Koo, Seungbum; Hargreaves, Brian A.; Gold, Garry E.; Dragoo, Jason L.

2011-01-01

Transplantation of engineered cartilage grafts is a promising method to treat diseased articular cartilage. The interfacial areas between the graft and the native tissues play an important role in the successful integration of the graft to adjacent native tissues. The purposes of the study were to create a custom shaped graft through 3D tissue shape reconstruction and rapid-prototype molding methods using MRI data, and to test the accuracy of the custom shaped graft against the original anatomical defect. An iatrogenic defect on the distal femur was identified with a 1.5 Tesla MRI and its shape was reconstructed into a three-dimensional (3D) computer model by processing the 3D MRI data. First, the accuracy of the MRI-derived 3D model was tested against a laser-scan based 3D model of the defect. A custom-shaped polyurethane graft was fabricated from the laser-scan based 3D model by creating custom molds through computer aided design and rapid-prototyping methods. The polyurethane tissue was laser-scanned again to calculate the accuracy of this process compared to the original defect. The volumes of the defect models from MRI and laser-scan were 537 mm3 and 405 mm3, respectively, implying that the MRI model was 33% larger than the laser-scan model. The average (±SD) distance deviation of the exterior surface of the MRI model from the laser-scan model was 0.4±0.4 mm. The custom-shaped tissue created from the molds was qualitatively very similar to the original shape of the defect. The volume of the custom-shaped cartilage tissue was 463 mm3 which was 15% larger than the laser-scan model. The average (±SD) distance deviation between the two models was 0.04±0.19 mm. Custom-shaped engineered grafts can be fabricated from standard sequence 3-D MRI data with the use of CAD and rapid-prototyping technology, which may help solve the interfacial problem between native cartilage and graft, if the grafts are custom made for the specific defect. The major source of error in fabricating a 3D custom shaped cartilage graft appears to be the accuracy of a MRI data itself; however, the precision of the model is expected to increase by the utilization of advanced MR sequences with higher magnet strengths. PMID:21058268

Blood oxygenation level-dependent MRI for assessment of renal oxygenation

PubMed Central

Neugarten, Joel; Golestaneh, Ladan

2014-01-01

Blood oxygen level-dependent magnetic resonance imaging (BOLD MRI) has recently emerged as an important noninvasive technique to assess intrarenal oxygenation under physiologic and pathophysiologic conditions. Although this tool represents a major addition to our armamentarium of methodologies to investigate the role of hypoxia in the pathogenesis of acute kidney injury and progressive chronic kidney disease, numerous technical limitations confound interpretation of data derived from this approach. BOLD MRI has been utilized to assess intrarenal oxygenation in numerous experimental models of kidney disease and in human subjects with diabetic and nondiabetic chronic kidney disease, acute kidney injury, renal allograft rejection, contrast-associated nephropathy, and obstructive uropathy. However, confidence in conclusions based on data derived from BOLD MRI measurements will require continuing advances and technical refinements in the use of this technique. PMID:25473304

Impact of sequential proton density fat fraction for quantification of hepatic steatosis in nonalcoholic fatty liver disease.

PubMed

Idilman, Ilkay S; Keskin, Onur; Elhan, Atilla Halil; Idilman, Ramazan; Karcaaltincaba, Musturay

2014-05-01

To determine the utility of sequential MRI-estimated proton density fat fraction (MRI-PDFF) for quantification of the longitudinal changes in liver fat content in individuals with nonalcoholic fatty liver disease (NAFLD). A total of 18 consecutive individuals (M/F: 10/8, mean age: 47.7±9.8 years) diagnosed with NAFLD, who underwent sequential PDFF calculations for the quantification of hepatic steatosis at two different time points, were included in the study. All patients underwent T1-independent volumetric multi-echo gradient-echo imaging with T2* correction and spectral fat modeling. A close correlation for quantification of hepatic steatosis between the initial MRI-PDFF and liver biopsy was observed (rs=0.758, p<0.001). The median interval between two sequential MRI-PDFF measurements was 184 days. From baseline to the end of the follow-up period, serum GGT level and homeostasis model assessment score were significantly improved (p=0.015, p=0.006, respectively), whereas BMI, serum AST, and ALT levels were slightly decreased. MRI-PDFFs were significantly improved (p=0.004). A good correlation between two sequential MRI-PDFF calculations was observed (rs=0.714, p=0.001). With linear regression analyses, only delta serum ALT levels had a significant effect on delta MRI-PDFF calculations (r2=38.6%, p=0.006). At least 5.9% improvement in MRI-PDFF is needed to achieve a normalized abnormal ALT level. The improvement of MRI-PDFF score was associated with the improvement of biochemical parameters in patients who had improvement in delta MRI-PDFF (p<0.05). MRI-PDFF can be used for the quantification of the longitudinal changes of hepatic steatosis. The changes in serum ALT levels significantly reflected changes in MRI-PDFF in patients with NAFLD.

A semi-automatic method for left ventricle volume estimate: an in vivo validation study

NASA Technical Reports Server (NTRS)

Corsi, C.; Lamberti, C.; Sarti, A.; Saracino, G.; Shiota, T.; Thomas, J. D.

2001-01-01

This study aims to the validation of the left ventricular (LV) volume estimates obtained by processing volumetric data utilizing a segmentation model based on level set technique. The validation has been performed by comparing real-time volumetric echo data (RT3DE) and magnetic resonance (MRI) data. A validation protocol has been defined. The validation protocol was applied to twenty-four estimates (range 61-467 ml) obtained from normal and pathologic subjects, which underwent both RT3DE and MRI. A statistical analysis was performed on each estimate and on clinical parameters as stroke volume (SV) and ejection fraction (EF). Assuming MRI estimates (x) as a reference, an excellent correlation was found with volume measured by utilizing the segmentation procedure (y) (y=0.89x + 13.78, r=0.98). The mean error on SV was 8 ml and the mean error on EF was 2%. This study demonstrated that the segmentation technique is reliably applicable on human hearts in clinical practice.

Predicting Progression from Mild Cognitive Impairment to Alzheimer's Dementia Using Clinical, MRI, and Plasma Biomarkers via Probabilistic Pattern Classification

PubMed Central

Korolev, Igor O.; Symonds, Laura L.; Bozoki, Andrea C.

2016-01-01

Background Individuals with mild cognitive impairment (MCI) have a substantially increased risk of developing dementia due to Alzheimer's disease (AD). In this study, we developed a multivariate prognostic model for predicting MCI-to-dementia progression at the individual patient level. Methods Using baseline data from 259 MCI patients and a probabilistic, kernel-based pattern classification approach, we trained a classifier to distinguish between patients who progressed to AD-type dementia (n = 139) and those who did not (n = 120) during a three-year follow-up period. More than 750 variables across four data sources were considered as potential predictors of progression. These data sources included risk factors, cognitive and functional assessments, structural magnetic resonance imaging (MRI) data, and plasma proteomic data. Predictive utility was assessed using a rigorous cross-validation framework. Results Cognitive and functional markers were most predictive of progression, while plasma proteomic markers had limited predictive utility. The best performing model incorporated a combination of cognitive/functional markers and morphometric MRI measures and predicted progression with 80% accuracy (83% sensitivity, 76% specificity, AUC = 0.87). Predictors of progression included scores on the Alzheimer's Disease Assessment Scale, Rey Auditory Verbal Learning Test, and Functional Activities Questionnaire, as well as volume/cortical thickness of three brain regions (left hippocampus, middle temporal gyrus, and inferior parietal cortex). Calibration analysis revealed that the model is capable of generating probabilistic predictions that reliably reflect the actual risk of progression. Finally, we found that the predictive accuracy of the model varied with patient demographic, genetic, and clinical characteristics and could be further improved by taking into account the confidence of the predictions. Conclusions We developed an accurate prognostic model for predicting MCI-to-dementia progression over a three-year period. The model utilizes widely available, cost-effective, non-invasive markers and can be used to improve patient selection in clinical trials and identify high-risk MCI patients for early treatment. PMID:26901338

Sparse dictionary learning of resting state fMRI networks.

PubMed

Eavani, Harini; Filipovych, Roman; Davatzikos, Christos; Satterthwaite, Theodore D; Gur, Raquel E; Gur, Ruben C

2012-07-02

Research in resting state fMRI (rsfMRI) has revealed the presence of stable, anti-correlated functional subnetworks in the brain. Task-positive networks are active during a cognitive process and are anti-correlated with task-negative networks, which are active during rest. In this paper, based on the assumption that the structure of the resting state functional brain connectivity is sparse, we utilize sparse dictionary modeling to identify distinct functional sub-networks. We propose two ways of formulating the sparse functional network learning problem that characterize the underlying functional connectivity from different perspectives. Our results show that the whole-brain functional connectivity can be concisely represented with highly modular, overlapping task-positive/negative pairs of sub-networks.

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.

Initial Investigation of preclinical integrated SPECT and MR imaging.

PubMed

Hamamura, Mark J; Ha, Seunghoon; Roeck, Werner W; Wagenaar, Douglas J; Meier, Dirk; Patt, Bradley E; Nalcioglu, Orhan

2010-02-01

Single-photon emission computed tomography (SPECT) can provide specific functional information while magnetic resonance imaging (MRI) can provide high-spatial resolution anatomical information as well as complementary functional information. In this study, we utilized a dual modality SPECT/MRI (MRSPECT) system to investigate the integration of SPECT and MRI for improved image accuracy. The MRSPECT system consisted of a cadmium-zinc-telluride (CZT) nuclear radiation detector interfaced with a specialized radiofrequency (RF) coil that was placed within a whole-body 4 T MRI system. The importance of proper corrections for non-uniform detector sensitivity and Lorentz force effects was demonstrated. MRI data were utilized for attenuation correction (AC) of the nuclear projection data and optimized Wiener filtering of the SPECT reconstruction for improved image accuracy. Finally, simultaneous dual-imaging of a nude mouse was performed to demonstrated the utility of co-registration for accurate localization of a radioactive source.

Initial Investigation of Preclinical Integrated SPECT and MR Imaging

PubMed Central

Hamamura, Mark J.; Ha, Seunghoon; Roeck, Werner W.; Wagenaar, Douglas J.; Meier, Dirk; Patt, Bradley E.; Nalcioglu, Orhan

2014-01-01

Single-photon emission computed tomography (SPECT) can provide specific functional information while magnetic resonance imaging (MRI) can provide high-spatial resolution anatomical information as well as complementary functional information. In this study, we utilized a dual modality SPECT/MRI (MRSPECT) system to investigate the integration of SPECT and MRI for improved image accuracy. The MRSPECT system consisted of a cadmium-zinc-telluride (CZT) nuclear radiation detector interfaced with a specialized radiofrequency (RF) coil that was placed within a whole-body 4 T MRI system. The importance of proper corrections for non-uniform detector sensitivity and Lorentz force effects was demonstrated. MRI data were utilized for attenuation correction (AC) of the nuclear projection data and optimized Wiener filtering of the SPECT reconstruction for improved image accuracy. Finally, simultaneous dual-imaging of a nude mouse was performed to demonstrated the utility of co-registration for accurate localization of a radioactive source. PMID:20082527

R6/2 Huntington's disease mice develop early and progressive abnormal brain metabolism and seizures.

PubMed

Cepeda-Prado, Efrain; Popp, Susanna; Khan, Usman; Stefanov, Dimitre; Rodríguez, Jorge; Menalled, Liliana B; Dow-Edwards, Diana; Small, Scott A; Moreno, Herman

2012-05-09

A hallmark feature of Huntington's disease pathology is the atrophy of brain regions including, but not limited to, the striatum. Though MRI studies have identified structural CNS changes in several Huntington's disease (HD) mouse models, the functional consequences of HD pathology during the progression of the disease have yet to be investigated using in vivo functional MRI (fMRI). To address this issue, we first established the structural and functional MRI phenotype of juvenile HD mouse model R6/2 at early and advanced stages of disease. Significantly higher fMRI signals [relative cerebral blood volumes (rCBVs)] and atrophy were observed in both age groups in specific brain regions. Next, fMRI results were correlated with electrophysiological analysis, which showed abnormal increases in neuronal activity in affected brain regions, thus identifying a mechanism accounting for the abnormal fMRI findings. [(14)C] 2-deoxyglucose maps to investigate patterns of glucose utilization were also generated. An interesting mismatch between increases in rCBV and decreases in glucose uptake was observed. Finally, we evaluated the sensitivity of this mouse line to audiogenic seizures early in the disease course. We found that R6/2 mice had an increased susceptibility to develop seizures. Together, these findings identified seizure activity in R6/2 mice and show that neuroimaging measures sensitive to oxygen metabolism can be used as in vivo biomarkers, preceding the onset of an overt behavioral phenotype. Since fMRI-rCBV can also be obtained in patients, we propose that it may serve as a translational tool to evaluate therapeutic responses in humans and HD mouse models.

Optimized Design and Analysis of Sparse-Sampling fMRI Experiments

PubMed Central

Perrachione, Tyler K.; Ghosh, Satrajit S.

2013-01-01

Sparse-sampling is an important methodological advance in functional magnetic resonance imaging (fMRI), in which silent delays are introduced between MR volume acquisitions, allowing for the presentation of auditory stimuli without contamination by acoustic scanner noise and for overt vocal responses without motion-induced artifacts in the functional time series. As such, the sparse-sampling technique has become a mainstay of principled fMRI research into the cognitive and systems neuroscience of speech, language, hearing, and music. Despite being in use for over a decade, there has been little systematic investigation of the acquisition parameters, experimental design considerations, and statistical analysis approaches that bear on the results and interpretation of sparse-sampling fMRI experiments. In this report, we examined how design and analysis choices related to the duration of repetition time (TR) delay (an acquisition parameter), stimulation rate (an experimental design parameter), and model basis function (an analysis parameter) act independently and interactively to affect the neural activation profiles observed in fMRI. First, we conducted a series of computational simulations to explore the parameter space of sparse design and analysis with respect to these variables; second, we validated the results of these simulations in a series of sparse-sampling fMRI experiments. Overall, these experiments suggest the employment of three methodological approaches that can, in many situations, substantially improve the detection of neurophysiological response in sparse fMRI: (1) Sparse analyses should utilize a physiologically informed model that incorporates hemodynamic response convolution to reduce model error. (2) The design of sparse fMRI experiments should maintain a high rate of stimulus presentation to maximize effect size. (3) TR delays of short to intermediate length can be used between acquisitions of sparse-sampled functional image volumes to increase the number of samples and improve statistical power. PMID:23616742

Impact of an Advanced Imaging Utilization Review Program on Downstream Health Care Utilization and Costs for Low Back Pain.

PubMed

Graves, Janessa M; Fulton-Kehoe, Deborah; Jarvik, Jeffrey G; Franklin, Gary M

2018-06-01

Early magnetic resonance imaging (MRI) for acute low back pain (LBP) has been associated with increased costs, greater health care utilization, and longer disability duration in workers' compensation claimants. To assess the impact of a state policy implemented in June 2010 that required prospective utilization review (UR) for early MRI among workers' compensation claimants with LBP. Interrupted time series. In total, 76,119 Washington State workers' compensation claimants with LBP between 2006 and 2014. Proportion of workers receiving imaging per month (MRI, computed tomography, radiographs) and lumbosacral injections and surgery; mean total health care costs per worker; mean duration of disability per worker. Measures were aggregated monthly and attributed to injury month. After accounting for secular trends, decreases in early MRI [level change: -5.27 (95% confidence interval, -4.22 to -6.31); trend change: -0.06 (-0.01 to -0.12)], any MRI [-4.34 (-3.01 to -5.67); -0.10 (-0.04 to -0.17)], and injection [trend change: -0.12 (-0.06 to -0.18)] utilization were associated with the policy. Radiograph utilization increased in parallel [level change: 2.46 (1.24-3.67)]. In addition, the policy resulted in significant decreasing changes in mean costs per claim, mean disability duration, and proportion of workers who received disability benefits. The policy had no effect on computed tomography or surgery utilization. The UR policy had discernable effects on health care utilization, costs, and disability. Integrating evidence-based guidelines with UR can improve quality of care and patient outcomes, while reducing use of low-value health services.

Detection of prostate cancer in peripheral zone: comparison of MR diffusion tensor imaging, quantitative dynamic contrast-enhanced MRI, and the two techniques combined at 3.0 T.

PubMed

Li, Chunmei; Chen, Min; Li, Saying; Zhao, Xuna; Zhang, Chen; Luo, Xiaojie; Zhou, Cheng

2014-03-01

Previous studies have shown that the diagnostic accuracy for prostate cancer improved with diffusion tensor imaging (DTI) or quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) only. However, the efficacy of combined DTI and quantitative DCE-MRI in detecting prostate cancer at 3.0 T is still indeterminate. To investigate the utility of diffusion tensor imaging (DTI), quantitative DCE-MRI, and the two techniques combined at 3.0 T in detecting prostate cancer of the peripheral zone (PZ). DTI and DCE-MRI of 33 patients was acquired prior to prostate biopsy. Regions of interest (ROIs) were drawn according to biopsy zones which were apex, mid-gland, and base on each side of the PZ. Apparent diffusion coefficient (ADC), fractional anisotropy (FA), volume transfer constant (K(trans)), and rate constant (kep) values of cancerous sextants and non-cancerous sextants in PZ were calculated. Logistic regression models were generated for DTI, DCE-MRI, and DTI + DCE-MRI. Receiver-operating characteristic (ROC) curves were used to compare the ability of these models to differentiate cancerous sextants from non-cancerous sextants of PZ. There were significant differences in the ADC, FA, K(trans), and kep values between cancerous sextants and non-cancerous sextants in PZ (P < 0.0001, P < 0.0001, P < 0.0001, and P < 0.0001, respectively). The area under curve (AUC) for DTI + DCE-MRI was significantly greater than that for either DTI (0.93 vs. 0.86, P = 0.0017) or DCE-MRI (0.93 vs. 0.84, P = 0.0034) alone. The combination of DTI and quantitative DCE-MRI has better diagnostic performance in detecting prostate cancer of the PZ than either technique alone.

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.

Game controller modification for fMRI hyperscanning experiments in a cooperative virtual reality environment.

PubMed

Trees, Jason; Snider, Joseph; Falahpour, Maryam; Guo, Nick; Lu, Kun; Johnson, Douglas C; Poizner, Howard; Liu, Thomas T

2014-01-01

Hyperscanning, an emerging technique in which data from multiple interacting subjects' brains are simultaneously recorded, has become an increasingly popular way to address complex topics, such as "theory of mind." However, most previous fMRI hyperscanning experiments have been limited to abstract social interactions (e.g. phone conversations). Our new method utilizes a virtual reality (VR) environment used for military training, Virtual Battlespace 2 (VBS2), to create realistic avatar-avatar interactions and cooperative tasks. To control the virtual avatar, subjects use a MRI compatible Playstation 3 game controller, modified by removing all extraneous metal components and replacing any necessary ones with 3D printed plastic models. Control of both scanners' operation is initiated by a VBS2 plugin to sync scanner time to the known time within the VR environment. Our modifications include:•Modification of game controller to be MRI compatible.•Design of VBS2 virtual environment for cooperative interactions.•Syncing two MRI machines for simultaneous recording.

Improved application of independent component analysis to functional magnetic resonance imaging study via linear projection techniques.

PubMed

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

2009-02-01

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

Game controller modification for fMRI hyperscanning experiments in a cooperative virtual reality environment

PubMed Central

Trees, Jason; Snider, Joseph; Falahpour, Maryam; Guo, Nick; Lu, Kun; Johnson, Douglas C.; Poizner, Howard; Liu, Thomas T.

2014-01-01

Hyperscanning, an emerging technique in which data from multiple interacting subjects’ brains are simultaneously recorded, has become an increasingly popular way to address complex topics, such as “theory of mind.” However, most previous fMRI hyperscanning experiments have been limited to abstract social interactions (e.g. phone conversations). Our new method utilizes a virtual reality (VR) environment used for military training, Virtual Battlespace 2 (VBS2), to create realistic avatar-avatar interactions and cooperative tasks. To control the virtual avatar, subjects use a MRI compatible Playstation 3 game controller, modified by removing all extraneous metal components and replacing any necessary ones with 3D printed plastic models. Control of both scanners’ operation is initiated by a VBS2 plugin to sync scanner time to the known time within the VR environment. Our modifications include:•Modification of game controller to be MRI compatible.•Design of VBS2 virtual environment for cooperative interactions.•Syncing two MRI machines for simultaneous recording. PMID:26150964

Left ventricular energy model predicts adverse events in women with suspected myocardial ischemia: results from the NHLBI-sponsored women’s ischemia syndrome evaluation (WISE) study

PubMed Central

Weinberg, Nicole; Pohost, Gerald M.; Bairey Merz, C. Noel; Shaw, Leslee J.; Sopko, George; Fuisz, Anthon; Rogers, William J.; Walsh, Edward G.; Johnson, B. Delia; Sharaf, Barry L.; Pepine, Carl J.; Mankad, Sunil; Reis, Steven E.; Rayarao, Geetha; Vido, Diane A.; Bittner, Vera; Tauxe, Lindsey; Olson, Marian B.; Kelsey, Sheryl F.; Biederman, Robert WW

2013-01-01

Objectives To assess the prognostic value of a left ventricular energy-model in women with suspected myocardial ischemia. Background The prognostic value of internal energy utilization (IEU) of the left ventricle in women with suspected myocardial ischemia is unknown. Methods Women [n=227, mean age 59±12 years (range, 31-86 years)], with symptoms of myocardial ischemia, underwent myocardial perfusion imaging (MPI) assessment for regional perfusion defects along with measurement of ventricular volumes separately by gated Single Photon Emission Computed Tomography (SPECT) (n=207) and magnetic resonance imaging (MRI) (n=203). During follow-up (40±17 months), time to first major adverse cardiovascular event (MACE, death, myocardial infarction or hospitalization for congestive heart failure) was analyzed using MRI and gated SPECT variables. Results Adverse events occurred in 31 (14%). Multivariable Cox models were formed for each modality: IEU and wall thickness by MRI (Chi-squared 34, P<0.005) and IEU and systolic blood pressure by gated SEPCT (Chi-squared 34, P<0.005). The models remained predictive after adjustment for age, disease history and Framingham risk score. For each Cox model, patients were categorized as high-risk if the model hazard was positive and not high-risk otherwise. Kaplan-Meier analysis of time to MACE was performed for high-risk vs. not high-risk for MR (log rank 25.3, P<0.001) and gated SEPCT (log rank 18.2, P<0.001) models. Conclusions Among women with suspected myocardial ischemia a high internal energy utilization has higher prognostic value than either a low EF or the presence of a myocardial perfusion defect assessed using two independent modalities of MR or gated SPECT. PMID:24015377

MRI-based modeling for radiocarpal joint mechanics: validation criteria and results for four specimen-specific models.

PubMed

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

2011-10-01

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

Large-scale DCMs for resting-state fMRI.

PubMed

Razi, Adeel; Seghier, Mohamed L; Zhou, Yuan; McColgan, Peter; Zeidman, Peter; Park, Hae-Jeong; Sporns, Olaf; Rees, Geraint; Friston, Karl J

2017-01-01

This paper considers the identification of large directed graphs for resting-state brain networks based on biophysical models of distributed neuronal activity, that is, effective connectivity . This identification can be contrasted with functional connectivity methods based on symmetric correlations that are ubiquitous in resting-state functional MRI (fMRI). We use spectral dynamic causal modeling (DCM) to invert large graphs comprising dozens of nodes or regions. The ensuing graphs are directed and weighted, hence providing a neurobiologically plausible characterization of connectivity in terms of excitatory and inhibitory coupling. Furthermore, we show that the use of to discover the most likely sparse graph (or model) from a parent (e.g., fully connected) graph eschews the arbitrary thresholding often applied to large symmetric (functional connectivity) graphs. Using empirical fMRI data, we show that spectral DCM furnishes connectivity estimates on large graphs that correlate strongly with the estimates provided by stochastic DCM. Furthermore, we increase the efficiency of model inversion using functional connectivity modes to place prior constraints on effective connectivity. In other words, we use a small number of modes to finesse the potentially redundant parameterization of large DCMs. We show that spectral DCM-with functional connectivity priors-is ideally suited for directed graph theoretic analyses of resting-state fMRI. We envision that directed graphs will prove useful in understanding the psychopathology and pathophysiology of neurodegenerative and neurodevelopmental disorders. We will demonstrate the utility of large directed graphs in clinical populations in subsequent reports, using the procedures described in this paper.

Advanced Imaging Utilization and Cost Savings Among Medicare Shared Savings Program Accountable Care Organizations: An Initial Exploratory Analysis.

PubMed

Rosenkrantz, Andrew B; Duszak, Richard

2018-03-01

The purpose of this study was to explore associations between CT and MRI utilization and cost savings achieved by Medicare Shared Savings Program (MSSP)-participating accountable care organizations (ACOs). Summary data were obtained for all MSSP-participating ACOs (n = 214 in 2013; n = 333 in 2014). Multivariable regressions were performed to assess associations of CT and MRI utilization with ACOs' total savings and reaching minimum savings rates to share in Medicare savings. In 2014, 54.4% of ACOs achieved savings, meeting minimum rates to share in savings in 27.6%. Independent positive predictors of total savings included beneficiary risk scores (β = +20,265,720, P = .003) and MRI events (β = +19,964, P = .018) but not CT events (β = +2,084, P = .635). Independent positive predictors of meeting minimum savings rates included beneficiary risk scores (odds ratio = 2108, P = .001) and MRI events (odds ratio = 1.008, P = .002), but not CT events (odds ratio = 1.002, P = .289). Measures not independently associated with savings were total beneficiaries; beneficiaries' gender, age, race or ethnicity; and Medicare enrollment type (P > .05). For ACOs with 2013 and 2014 data, neither increases nor decreases in CT and MRI events between years were associated with 2014 total savings or meeting savings thresholds (P ≥ .466). Higher MRI utilization rates were independently associated with small but significant MSSP ACO savings. The value of MRI might relate to the favorable impact of appropriate advanced imaging utilization on downstream outcomes and other resource utilization. Because MSSP ACOs represent a highly select group of sophisticated organizations subject to rigorous quality and care coordination standards, further research will be necessary to determine if these associations are generalizable to other health care settings. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Breast MRI: patterns of utilization and impact on patient management in the community hospital setting.

PubMed

Lobrano, Mary Beth; Stolier, Alan; L'Hoste, Robert; Luttrell, Carol Anne

2012-01-01

The objective of our study was to investigate the indications for breast magnetic resonance imaging, or MRI, in our community hospital, determine how many probably benign MRI findings were malignant at follow-up, determine how many cancers were identified by MRI in screening patients, and evaluate the utility of MRI for surgical planning and problem-solving. Five hundred twenty-eight contrast-enhanced MRI's of the breast in 434 patients were retrospectively reviewed. MRI images/reports were compared to surgical pathology reports and the results of follow-up studies. Screening was the most common indication for breast MRI in our patient population. Five percent of findings termed "probably benign" on MRI proved to be malignant at follow-up. Eight malignancies were detected in six of 202 screened patients. Ten malignancies were diagnosed in 66 patients referred to MRI for problem-solving. In two of 74 patients with known breast cancer, an unsuspected ipsilateral cancer was identified on MRI. MRI proved useful in the community hospital setting for screening high-risk patients and problem-solving. The rate of malignancy in probably benign MRI findings was higher than the corresponding rate in mammography. The detection of additional ipsilateral and contralateral cancers in pre-operative patients with known breast cancer was not as high as expected, based on prior studies.

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.

Toward a comprehensive hybrid physical-virtual reality simulator of peripheral anesthesia with ultrasound and neurostimulator guidance.

PubMed

Samosky, Joseph T; Allen, Pete; Boronyak, Steve; Branstetter, Barton; Hein, Steven; Juhas, Mark; Nelson, Douglas A; Orebaugh, Steven; Pinto, Rohan; Smelko, Adam; Thompson, Mitch; Weaver, Robert A

2011-01-01

We are developing a simulator of peripheral nerve block utilizing a mixed-reality approach: the combination of a physical model, an MRI-derived virtual model, mechatronics and spatial tracking. Our design uses tangible (physical) interfaces to simulate surface anatomy, haptic feedback during needle insertion, mechatronic display of muscle twitch corresponding to the specific nerve stimulated, and visual and haptic feedback for the injection syringe. The twitch response is calculated incorporating the sensed output of a real neurostimulator. The virtual model is isomorphic with the physical model and is derived from segmented MRI data. This model provides the subsurface anatomy and, combined with electromagnetic tracking of a sham ultrasound probe and a standard nerve block needle, supports simulated ultrasound display and measurement of needle location and proximity to nerves and vessels. The needle tracking and virtual model also support objective performance metrics of needle targeting technique.

Optimized design and analysis of sparse-sampling FMRI experiments.

PubMed

Perrachione, Tyler K; Ghosh, Satrajit S

2013-01-01

Sparse-sampling is an important methodological advance in functional magnetic resonance imaging (fMRI), in which silent delays are introduced between MR volume acquisitions, allowing for the presentation of auditory stimuli without contamination by acoustic scanner noise and for overt vocal responses without motion-induced artifacts in the functional time series. As such, the sparse-sampling technique has become a mainstay of principled fMRI research into the cognitive and systems neuroscience of speech, language, hearing, and music. Despite being in use for over a decade, there has been little systematic investigation of the acquisition parameters, experimental design considerations, and statistical analysis approaches that bear on the results and interpretation of sparse-sampling fMRI experiments. In this report, we examined how design and analysis choices related to the duration of repetition time (TR) delay (an acquisition parameter), stimulation rate (an experimental design parameter), and model basis function (an analysis parameter) act independently and interactively to affect the neural activation profiles observed in fMRI. First, we conducted a series of computational simulations to explore the parameter space of sparse design and analysis with respect to these variables; second, we validated the results of these simulations in a series of sparse-sampling fMRI experiments. Overall, these experiments suggest the employment of three methodological approaches that can, in many situations, substantially improve the detection of neurophysiological response in sparse fMRI: (1) Sparse analyses should utilize a physiologically informed model that incorporates hemodynamic response convolution to reduce model error. (2) The design of sparse fMRI experiments should maintain a high rate of stimulus presentation to maximize effect size. (3) TR delays of short to intermediate length can be used between acquisitions of sparse-sampled functional image volumes to increase the number of samples and improve statistical power.

Characterization of skin abnormalities in a mouse model of osteogenesis imperfecta using high resolution magnetic resonance imaging and Fourier transform infrared imaging spectroscopy.

PubMed

Canuto, H C; Fishbein, K W; Huang, A; Doty, S B; Herbert, R A; Peckham, J; Pleshko, N; Spencer, R G

2012-01-01

Evaluation of the skin phenotype in osteogenesis imperfecta (OI) typically involves biochemical measurements, such as histologic or biochemical assessment of the collagen produced from biopsy-derived dermal fibroblasts. As an alternative, the current study utilized non-invasive magnetic resonance imaging (MRI) microscopy and optical spectroscopy to define biophysical characteristics of skin in an animal model of OI. MRI of skin harvested from control, homozygous oim/oim and heterozygous oim/+ mice demonstrated several differences in anatomic and biophysical properties. Fourier transform infrared imaging spectroscopy (FT-IRIS) was used to interpret observed MRI signal characteristics in terms of chemical composition. Differences between wild-type and OI mouse skin included the appearance of a collagen-depleted lower dermal layer containing prominent hair follicles in the oim/oim mice, accounting for 55% of skin thickness in these. The MRI magnetization transfer rate was lower by 50% in this layer as compared to the upper dermis, consistent with lower collagen content. The MRI transverse relaxation time, T2, was greater by 30% in the dermis of the oim/oim mice compared to controls, consistent with a more highly hydrated collagen network. Similarly, an FT-IRIS-defined measure of collagen integrity was 30% lower in the oim/oim mice. We conclude that characterization of phenotypic differences between the skin of OI and wild-type mice by MRI and FT-IRIS is feasible, and that these techniques provide powerful complementary approaches for the analysis of the skin phenotype in animal models of disease. Copyright © 2011 John Wiley & Sons, Ltd.

Evaluating Dynamic Bivariate Correlations in Resting-state fMRI: A comparison study and a new approach

PubMed Central

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

2014-01-01

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

New Directions in 3D Medical Modeling: 3D-Printing Anatomy and Functions in Neurosurgical Planning

PubMed Central

Árnadóttir, Íris; Gíslason, Magnús; Ólafsson, Ingvar

2017-01-01

This paper illustrates the feasibility and utility of combining cranial anatomy and brain function on the same 3D-printed model, as evidenced by a neurosurgical planning case study of a 29-year-old female patient with a low-grade frontal-lobe glioma. We herein report the rapid prototyping methodology utilized in conjunction with surgical navigation to prepare and plan a complex neurosurgery. The method introduced here combines CT and MRI images with DTI tractography, while using various image segmentation protocols to 3D model the skull base, tumor, and five eloquent fiber tracts. This 3D model is rapid-prototyped and coregistered with patient images and a reported surgical navigation system, establishing a clear link between the printed model and surgical navigation. This methodology highlights the potential for advanced neurosurgical preparation, which can begin before the patient enters the operation theatre. Moreover, the work presented here demonstrates the workflow developed at the National University Hospital of Iceland, Landspitali, focusing on the processes of anatomy segmentation, fiber tract extrapolation, MRI/CT registration, and 3D printing. Furthermore, we present a qualitative and quantitative assessment for fiber tract generation in a case study where these processes are applied in the preparation of brain tumor resection surgery. PMID:29065569

Optimizing the general linear model for functional near-infrared spectroscopy: an adaptive hemodynamic response function approach

PubMed Central

Uga, Minako; Dan, Ippeita; Sano, Toshifumi; Dan, Haruka; Watanabe, Eiju

2014-01-01

Abstract. An increasing number of functional near-infrared spectroscopy (fNIRS) studies utilize a general linear model (GLM) approach, which serves as a standard statistical method for functional magnetic resonance imaging (fMRI) data analysis. While fMRI solely measures the blood oxygen level dependent (BOLD) signal, fNIRS measures the changes of oxy-hemoglobin (oxy-Hb) and deoxy-hemoglobin (deoxy-Hb) signals at a temporal resolution severalfold higher. This suggests the necessity of adjusting the temporal parameters of a GLM for fNIRS signals. Thus, we devised a GLM-based method utilizing an adaptive hemodynamic response function (HRF). We sought the optimum temporal parameters to best explain the observed time series data during verbal fluency and naming tasks. The peak delay of the HRF was systematically changed to achieve the best-fit model for the observed oxy- and deoxy-Hb time series data. The optimized peak delay showed different values for each Hb signal and task. When the optimized peak delays were adopted, the deoxy-Hb data yielded comparable activations with similar statistical power and spatial patterns to oxy-Hb data. The adaptive HRF method could suitably explain the behaviors of both Hb parameters during tasks with the different cognitive loads during a time course, and thus would serve as an objective method to fully utilize the temporal structures of all fNIRS data. PMID:26157973

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.

Health IT and inappropriate utilization of outpatient imaging: A cross-sectional study of U.S. hospitals.

PubMed

Appari, Ajit; Johnson, M Eric; Anthony, Denise L

2018-01-01

To determine whether the use of information technology (IT), measured by Meaningful Use capability, is associated with lower rates of inappropriate utilization of imaging services in hospital outpatient settings. A retrospective cross-sectional analysis of 3332 nonfederal U.S. hospitals using data from: Hospital Compare (2011 outpatient imaging efficiency measures), HIMSS Analytics (2009 health IT), and Health Indicator Warehouse (market characteristics). Hospitals were categorized for their health IT infrastructure including EHR Stage-1 capability, and three advanced imaging functionalities/systems including integrated picture archiving and communication system, Web-based image distribution, and clinical decision support (CDS) with physician pathways. Three imaging efficiency measures suggesting inappropriate utilization during 2011 included: percentage of "combined" (with and without contrast) computed tomography (CT) studies out of all CT studies for abdomen and chest respectively, and percentage of magnetic resonance imaging (MRI) studies of lumbar spine without antecedent conservative therapy within 60days. For each measure, three separate regression models (GLM with gamma-log link function, and denominator of imaging measure as exposure) were estimated adjusting for hospital characteristics, market characteristics, and state fixed effects. Additionally, Heckman's Inverse Mills Ratio and propensity for Stage-1 EHR capability were used to account for selection bias. We find support for association of each of the four health IT capabilities with inappropriate utilization rates of one or more imaging modality. Stage-1 EHR capability is associated with lower inappropriate utilization rates for chest CT (incidence rate ratio IRR=0.72, p-value <0.01) and lumbar MRI (IRR=0.87, p-value <0.05). Integrated PACS is associated with lower inappropriate utilization rate of abdomen CT (IRR=0.84, p-value <0.05). Imaging distribution over Web capability is associated with lower inappropriate utilization rates for chest CT (IRR=0.66, p-value <0.05) and lumbar MRI (IRR=0.86, p-value <0.05). CDS with physician pathways is associated with lower inappropriate utilization rates for abdomen CT (IRR=0.87, p-value <0.01) and lumbar MRI (IRR=0.90, p-value <0.05). All other cases showed no association. The study offers mixed results. Taken together, the results suggest that the use of Stage-1 Meaningful Use capable EHR systems along with advanced imaging related functionalities could have a beneficial impact on reducing some of the inappropriate utilization of outpatient imaging. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Utility of functional MRI in pediatric neurology.

PubMed

Freilich, Emily R; Gaillard, William D

2010-01-01

Functional MRI (fMRI), a tool increasingly used to study cognitive function, is also an important tool for understanding not only normal development in healthy children, but also abnormal development, as seen in children with epilepsy, attention-deficit/hyperactivity disorder, and autism. Since its inception almost 15 years ago, fMRI has seen an explosion in its use and applications in the adult literature. However, only recently has it found a home in pediatric neurology. New adaptations in study design and technologic advances, especially the study of resting state functional connectivity as well as the use of passive task design in sedated children, have increased the utility of functional imaging in pediatrics to help us gain understanding into the developing brain at work. This article reviews the background of fMRI in pediatrics and highlights the most recent literature and clinical applications.

Neurofeedback and networks of depression

PubMed Central

Linden, David E. J.

2014-01-01

Recent advances in imaging technology and in the understanding of neural circuits relevant to emotion, motivation, and depression have boosted interest and experimental work in neuromodulation for affective disorders. Real-time functional magnetic resonance imaging (fMRI) can be used to train patients in the self regulation of these circuits, and thus complement existing neurofeedback technologies based on electroencephalography (EEG). EEG neurofeedback for depression has mainly been based on models of altered hemispheric asymmetry. fMRI-based neurofeedback (fMRI-NF) can utilize functional localizer scans that allow the dynamic adjustment of the target areas or networks for self-regulation training to individual patterns of emotion processing. An initial application of fMRI-NF in depression has produced promising clinical results, and further clinical trials are under way. Challenges lie in the design of appropriate control conditions for rigorous clinical trials, and in the transfer of neurofeedback protocols from the laboratory to mobile devices to enhance the sustainability of any clinical benefits. PMID:24733975

Clinical utility of MRI and SPECT in the diagnosis of cognitive impairment referred to memory clinic.

PubMed

Guinane, John; Ng, Boon Lung

2018-05-01

ABSTRACTBackground:Despite of their limited availability and potential for significant variation between and within each modality, this is the first study to prospectively measure the clinical utility of MRI and/or SPECT brain scanning in addition to the routine diagnostic workup of patients presenting to memory clinic. A single center study was conducted over a convenience of 12-month sampling period. For each patient referred for MRI and/or SPECT scanning, the primary geriatrician or psychogeriatrician was asked to assign an initial diagnosis. The initial diagnosis was then compared with the final consensus diagnosis after any scans or neuropsychology testing had been completed. During the 12-month study period, 66 patients (26%) were referred for scans out of a total of 253 patients included in the study. There were 16/44 (36%) positive MRI outcomes and 13/35 (37%) positive SPECT outcomes. The diagnosis changed consistent with the MRI scan findings in 11/44 (25%) and changed consistent with the SPECT scan findings in 9/35 (26%). Potentially reversible pathology was identified in a single patient, 1/50 (2%), via an MRI scan that suggested normal pressure hydrocephalus. The number needed to test for one positive outcome was 3.8 (95% CI 2.0-23.3), 6.0 (95% CI NA), and 1.7 (95% CI 1.3-2.5) for MRI only, SPECT only, and MRI and SPECT together, respectively. The clinical utility of MRI and/or SPECT scanning in this study may be broadly superior to the available international evidence, and further research is needed to identify predictors of positive scan outcomes.

Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET)/MRI for Lung Cancer Staging.

PubMed

Ohno, Yoshiharu; Koyama, Hisanobu; Lee, Ho Yun; Yoshikawa, Takeshi; Sugimura, Kazuro

2016-07-01

Tumor, lymph node, and metastasis (TNM) classification of lung cancer is typically performed with the TNM staging system, as recommended by the Union Internationale Contre le Cancer (UICC), the American Joint Committee on Cancer (AJCC), and the International Association for the Study of Lung Cancer (IASLC). Radiologic examinations for TNM staging of lung cancer patients include computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography with 2-[fluorine-18] fluoro-2-deoxy-D-glucose (FDG-PET), and FDG-PET combined with CT (FDG-PET/CT) and are used for pretherapeutic assessments. Recent technical advances in MR systems, application of fast and parallel imaging and/or introduction of new MR techniques, and utilization of contrast media have markedly improved the diagnostic utility of MRI in this setting. In addition, FDG-PET can be combined or fused with MRI (PET/MRI) for clinical practice. This review article will focus on these recent advances in MRI as well as on PET/MRI for lung cancer staging, in addition to a discussion of their potential and limitations for routine clinical practice in comparison with other modalities such as CT, FDG-PET, and PET/CT.

Intraoperative magnetic resonance imaging assessment of non-functioning pituitary adenomas during transsphenoidal surgery.

PubMed

Patel, Kunal S; Yao, Yong; Wang, Renzhi; Carter, Bob S; Chen, Clark C

2016-04-01

To review the utility of intraoperative imaging in facilitating maximal resection of non-functioning pituitary adenomas (NFAs). We performed an exhaustive MEDLINE search, which yielded 5598 articles. Upon careful review of these studies, 31 were pertinent to the issue of interest. Nine studies examined whether intraoperative MRI (iMRI) findings correlated with the presence of residual tumor on MRI taken 3 months after surgical resection. All studies using iMRI of >0.15T showed a ≥90% concordance between iMRI and 3-month post-operative MRI findings. 24 studies (22 iMRI and 2 intraoperative CT) examined whether intraoperative imaging improved the surgeon's ability to achieve a more complete resection. The resections were carried out under microscopic magnification in 17 studies and under endoscopic visualization in 7 studies. All studies support the value of intraoperative imaging in this regard, with improved resection in 15-83% of patients. Two studies examined whether iMRI (≥0.3T) improved visualization of residual NFA when compared to endoscopic visualization. Both studies demonstrated the value of iMRI in this regard, particularly when the tumor is located lateral of the sella, in the cavernous sinus, and in the suprasellar space. The currently available literature supports the utility of intraoperative imaging in facilitating increased NFA resection, without compromising safety.

The utility of magnetic resonance imaging in the diagnosis and management of pediatric benign ovarian lesions.

PubMed

Emil, Sherif; Youssef, Fouad; Arbash, Ghaidaa; Baird, Robert; Laberge, Jean-Martin; Puligandla, Pramod; Albuquerque, Pedro

2018-01-31

The utility of magnetic resonance imaging (MRI) in the diagnosis and management of pediatric ovarian lesions has not been well defined. A retrospective review of all girls who underwent MRI evaluation of ovarian masses during the period 2009-2015 was performed. The accuracy of MRI was evaluated by comparing results with surgical findings, pathology reports, and subsequent imaging. The influence of the MRI on the treatment plan was specifically explored. Eighteen girls, 12-17years of age, underwent 27 MRIs, subsequent to ultrasound identification of ovarian lesions. Of 9 neoplastic lesions diagnosed on MRI, 8 (89%) were confirmed by surgical and pathological findings. Of 18 functional lesions, 17 (94.4%) were confirmed pathologically or by resolution on subsequent imaging. Twenty MRI exams (74%) directly influenced the treatment plan, by leading to appropriate operative intervention in 9 and appropriate observation in 11. The extent of ovarian resection was guided by MRI findings in 8 of 9 (89%) neoplastic lesions. For characterizing lesions as neoplastic, the sensitivity, specificity, negative predictive value, positive predictive value, and accuracy of MRI were 89%, 94%, 94%, 89%, and 93% respectively. MRI can differentiate functional from neoplastic pediatric ovarian masses, and guide ovarian resection in appropriate cases. II. Copyright © 2018. Published by Elsevier Inc.

Direct estimation of tracer-kinetic parameter maps from highly undersampled brain dynamic contrast enhanced MRI.

PubMed

Guo, Yi; Lingala, Sajan Goud; Zhu, Yinghua; Lebel, R Marc; Nayak, Krishna S

2017-10-01

The purpose of this work was to develop and evaluate a T 1 -weighted dynamic contrast enhanced (DCE) MRI methodology where tracer-kinetic (TK) parameter maps are directly estimated from undersampled (k,t)-space data. The proposed reconstruction involves solving a nonlinear least squares optimization problem that includes explicit use of a full forward model to convert parameter maps to (k,t)-space, utilizing the Patlak TK model. The proposed scheme is compared against an indirect method that creates intermediate images by parallel imaging and compressed sensing before to TK modeling. Thirteen fully sampled brain tumor DCE-MRI scans with 5-second temporal resolution are retrospectively undersampled at rates R = 20, 40, 60, 80, and 100 for each dynamic frame. TK maps are quantitatively compared based on root mean-squared-error (rMSE) and Bland-Altman analysis. The approach is also applied to four prospectively R = 30 undersampled whole-brain DCE-MRI data sets. In the retrospective study, the proposed method performed statistically better than indirect method at R ≥ 80 for all 13 cases. This approach provided restoration of TK parameter values with less errors in tumor regions of interest, an improvement compared to a state-of-the-art indirect method. Applied prospectively, the proposed method provided whole-brain, high-resolution TK maps with good image quality. Model-based direct estimation of TK maps from k,t-space DCE-MRI data is feasible and is compatible up to 100-fold undersampling. Magn Reson Med 78:1566-1578, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Dipy, a library for the analysis of diffusion MRI data.

PubMed

Garyfallidis, Eleftherios; Brett, Matthew; Amirbekian, Bagrat; Rokem, Ariel; van der Walt, Stefan; Descoteaux, Maxime; Nimmo-Smith, Ian

2014-01-01

Diffusion Imaging in Python (Dipy) is a free and open source software project for the analysis of data from diffusion magnetic resonance imaging (dMRI) experiments. dMRI is an application of MRI that can be used to measure structural features of brain white matter. Many methods have been developed to use dMRI data to model the local configuration of white matter nerve fiber bundles and infer the trajectory of bundles connecting different parts of the brain. Dipy gathers implementations of many different methods in dMRI, including: diffusion signal pre-processing; reconstruction of diffusion distributions in individual voxels; fiber tractography and fiber track post-processing, analysis and visualization. Dipy aims to provide transparent implementations for all the different steps of dMRI analysis with a uniform programming interface. We have implemented classical signal reconstruction techniques, such as the diffusion tensor model and deterministic fiber tractography. In addition, cutting edge novel reconstruction techniques are implemented, such as constrained spherical deconvolution and diffusion spectrum imaging (DSI) with deconvolution, as well as methods for probabilistic tracking and original methods for tractography clustering. Many additional utility functions are provided to calculate various statistics, informative visualizations, as well as file-handling routines to assist in the development and use of novel techniques. In contrast to many other scientific software projects, Dipy is not being developed by a single research group. Rather, it is an open project that encourages contributions from any scientist/developer through GitHub and open discussions on the project mailing list. Consequently, Dipy today has an international team of contributors, spanning seven different academic institutions in five countries and three continents, which is still growing.

Dipy, a library for the analysis of diffusion MRI data

PubMed Central

Garyfallidis, Eleftherios; Brett, Matthew; Amirbekian, Bagrat; Rokem, Ariel; van der Walt, Stefan; Descoteaux, Maxime; Nimmo-Smith, Ian

2014-01-01

Diffusion Imaging in Python (Dipy) is a free and open source software project for the analysis of data from diffusion magnetic resonance imaging (dMRI) experiments. dMRI is an application of MRI that can be used to measure structural features of brain white matter. Many methods have been developed to use dMRI data to model the local configuration of white matter nerve fiber bundles and infer the trajectory of bundles connecting different parts of the brain. Dipy gathers implementations of many different methods in dMRI, including: diffusion signal pre-processing; reconstruction of diffusion distributions in individual voxels; fiber tractography and fiber track post-processing, analysis and visualization. Dipy aims to provide transparent implementations for all the different steps of dMRI analysis with a uniform programming interface. We have implemented classical signal reconstruction techniques, such as the diffusion tensor model and deterministic fiber tractography. In addition, cutting edge novel reconstruction techniques are implemented, such as constrained spherical deconvolution and diffusion spectrum imaging (DSI) with deconvolution, as well as methods for probabilistic tracking and original methods for tractography clustering. Many additional utility functions are provided to calculate various statistics, informative visualizations, as well as file-handling routines to assist in the development and use of novel techniques. In contrast to many other scientific software projects, Dipy is not being developed by a single research group. Rather, it is an open project that encourages contributions from any scientist/developer through GitHub and open discussions on the project mailing list. Consequently, Dipy today has an international team of contributors, spanning seven different academic institutions in five countries and three continents, which is still growing. PMID:24600385

Clinical Utility of Magnetic Resonance Imaging (MRI) and Ultrasonography (US) for Diagnosis of Polycystic Ovary Syndrome (PCOS) in Adolescent Girls

PubMed Central

Kenigsberg, Lisa E; Agarwal, Chhavi; Sin, Sanghun; Shifteh, Keivan; Isasi, Carmen R; Crespi, Rebecca; Ivanova, Janeta; Coupey, Susan M; Heptulla, Rubina A; Arens, Raanan

2015-01-01

Objectives Evaluate ovarian morphology using 3-dimensional MRI in adolescent girls with and without PCOS. Compare the utility of MRI versus ultrasonography (US) for diagnosis of PCOS Design Cross-sectional Setting Urban academic tertiary-care children’s hospital Patients Thirty-nine adolescent girls with untreated PCOS and 22 age/BMI-matched controls. Intervention MRI and/or transvaginal/transabdominal US Main Outcome Measure Ovarian volume (OV); follicle number per section (FNPS); correlation between OV on MRI and US; proportion of subjects with features of polycystic ovaries on MRI and US. Results MRI demonstrated larger OV and higher FNPS in subjects with PCOS compared to controls. Within the PCOS group, median OV was 11.9 (7.7) cm3 by MRI, compared with 8.8 (7.8) cm3 by US. Correlation coefficient between OV by MRI and US was 0.701. Due to poor resolution, FNPS could not be determined by US or compared with MRI. ROC curve analysis for MRI demonstrated that increasing volume cut-offs for polycystic ovaries from 10cm3 to 14cm3, increased specificity from 77% to 95%. For FNPS on MRI, specificity increased from 82% to 98% by increasing cut-offs from ≥12 to ≥17. Using Rotterdam cut-offs, 91% of subjects with PCOS met polycystic ovary criteria on MRI, while only 52% met criteria by US. Conclusions US measures smaller OV than MRI, cannot accurately detect follicle number, and is a poor imaging modality for characterizing polycystic ovaries in adolescents with suspected PCOS. For adolescents in whom diagnosis of PCOS remains uncertain after clinical and laboratory evaluation, MRI should be considered as a diagnostic imaging modality. PMID:26354095

Multispecialty retrospective review of the clinical utility of pelvic magnetic resonance imaging in the setting of pelvic pain.

PubMed

Moore, John R; Pathak, Ram A; Snowden, Caroline; Bolan, Candice W; Young, Paul R; Broderick, Gregory A

2017-12-01

Pelvic pain is a common complaint, and management of it is often difficult. We sought to evaluate the utility of magnetic resonance imaging (MRI) in the diagnosis of male pelvic pain. Though MRIs are commonly ordered to evaluate pelvic pain, there are very few studies obtaining the efficacy of pelvic MRI in determining a definitive diagnosis. The primary aim of our study was to evaluate the clinical utility of pelvic MRI for a diagnosis code that included pain. After receiving institutional review board approval, a retrospective study was performed of all pelvic MRIs completed at our institution from January 2, 2010 to December 31, 2014. These were further delineated into ordering providers by specialty and urology-specific International Classification of Diseases, Ninth Revision (ICD-9) code diagnoses (male pelvic pain, prostatitis, groin pain, scrotal pain, testicular pain, and penile pain). Clinical utility was defined as positive if MRI findings resulted in a change in management. Subanalysis was performed on patients with an ICD-9 co-diagnosis of previous oncologic concern. A total of 2,643 pelvic MRIs were ordered at our institution over a 5-year period. Of these, 597 pelvic MRIs (23%) were ordered for a diagnosis code that included pain (hip pain, rectal pain, joint pain, penile pain, scrotal pain, male pelvic pain and orchitis). Total utility for MRIs to find anatomic abnormalities potentially responsible for the present pain was 34% (205/597). When ordered by urologic providers, utility was 23%. Oncologists represented the highest positivity rate at 57%. Chronic pelvic pain is a multispecialty complaint that is difficult to treat. We were surprised to find the large number of both specialists and generalists invested in the management of pelvic pain. The increasing availability of MRI technology makes it a likely candidate to test for a clinically significant anatomic reason for pain. Though MRI is a test with minimal adverse effect and no increased risk of radiation exposure, the cost on the healthcare system should be offset by a clear clinical utility. We found total utility to be 34% across all ordering providers and an increase in positivity with concern of oncologic disease. Therefore, we would recommend pelvic MRIs in the evaluation of patients with refractory pelvic pain.

Fiber Optic Force Sensors for MRI-Guided Interventions and Rehabilitation: A Review

PubMed Central

Iordachita, Iulian I.; Tokuda, Junichi; Hata, Nobuhiko; Liu, Xuan; Seifabadi, Reza; Xu, Sheng; Wood, Bradford; Fischer, Gregory S.

2017-01-01

Magnetic Resonance Imaging (MRI) provides both anatomical imaging with excellent soft tissue contrast and functional MRI imaging (fMRI) of physiological parameters. The last two decades have witnessed the manifestation of increased interest in MRI-guided minimally invasive intervention procedures and fMRI for rehabilitation and neuroscience research. Accompanying the aspiration to utilize MRI to provide imaging feedback during interventions and brain activity for neuroscience study, there is an accumulated effort to utilize force sensors compatible with the MRI environment to meet the growing demand of these procedures, with the goal of enhanced interventional safety and accuracy, improved efficacy and rehabilitation outcome. This paper summarizes the fundamental principles, the state of the art development and challenges of fiber optic force sensors for MRI-guided interventions and rehabilitation. It provides an overview of MRI-compatible fiber optic force sensors based on different sensing principles, including light intensity modulation, wavelength modulation, and phase modulation. Extensive design prototypes are reviewed to illustrate the detailed implementation of these principles. Advantages and disadvantages of the sensor designs are compared and analyzed. A perspective on the future development of fiber optic sensors is also presented which may have additional broad clinical applications. Future surgical interventions or rehabilitation will rely on intelligent force sensors to provide situational awareness to augment or complement human perception in these procedures. PMID:28652857

Automatic EEG-assisted retrospective motion correction for fMRI (aE-REMCOR).

PubMed

Wong, Chung-Ki; Zotev, Vadim; Misaki, Masaya; Phillips, Raquel; Luo, Qingfei; Bodurka, Jerzy

2016-04-01

Head motions during functional magnetic resonance imaging (fMRI) impair fMRI data quality and introduce systematic artifacts that can affect interpretation of fMRI results. Electroencephalography (EEG) recordings performed simultaneously with fMRI provide high-temporal-resolution information about ongoing brain activity as well as head movements. Recently, an EEG-assisted retrospective motion correction (E-REMCOR) method was introduced. E-REMCOR utilizes EEG motion artifacts to correct the effects of head movements in simultaneously acquired fMRI data on a slice-by-slice basis. While E-REMCOR is an efficient motion correction approach, it involves an independent component analysis (ICA) of the EEG data and identification of motion-related ICs. Here we report an automated implementation of E-REMCOR, referred to as aE-REMCOR, which we developed to facilitate the application of E-REMCOR in large-scale EEG-fMRI studies. The aE-REMCOR algorithm, implemented in MATLAB, enables an automated preprocessing of the EEG data, an ICA decomposition, and, importantly, an automatic identification of motion-related ICs. aE-REMCOR has been used to perform retrospective motion correction for 305 fMRI datasets from 16 subjects, who participated in EEG-fMRI experiments conducted on a 3T MRI scanner. Performance of aE-REMCOR has been evaluated based on improvement in temporal signal-to-noise ratio (TSNR) of the fMRI data, as well as correction efficiency defined in terms of spike reduction in fMRI motion parameters. The results show that aE-REMCOR is capable of substantially reducing head motion artifacts in fMRI data. In particular, when there are significant rapid head movements during the scan, a large TSNR improvement and high correction efficiency can be achieved. Depending on a subject's motion, an average TSNR improvement over the brain upon the application of aE-REMCOR can be as high as 27%, with top ten percent of the TSNR improvement values exceeding 55%. The average correction efficiency over the 305 fMRI scans is 18% and the largest achieved efficiency is 71%. The utility of aE-REMCOR on the resting state fMRI connectivity of the default mode network is also examined. The motion-induced position-dependent error in the DMN connectivity analysis is shown to be reduced when aE-REMCOR is utilized. These results demonstrate that aE-REMCOR can be conveniently and efficiently used to improve fMRI motion correction in large clinical EEG-fMRI studies. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Thermo-Acoustic Ultrasound for Detection of RF-Induced Device Lead Heating in MRI.

PubMed

Dixit, Neerav; Stang, Pascal P; Pauly, John M; Scott, Greig C

2018-02-01

Patients who have implanted medical devices with long conductive leads are often restricted from receiving MRI scans due to the danger of RF-induced heating near the lead tips. Phantom studies have shown that this heating varies significantly on a case-by-case basis, indicating that many patients with implanted devices can receive clinically useful MRI scans without harm. However, the difficulty of predicting RF-induced lead tip heating prior to scanning prevents numerous implant recipients from being scanned. Here, we demonstrate that thermo-acoustic ultrasound (TAUS) has the potential to be utilized for a pre-scan procedure assessing the risk of RF-induced lead tip heating in MRI. A system was developed to detect TAUS signals by four different TAUS acquisition methods. We then integrated this system with an MRI scanner and detected a peak in RF power absorption near the tip of a model lead when transmitting from the scanner's body coil. We also developed and experimentally validated simulations to characterize the thermo-acoustic signal generated near lead tips. These results indicate that TAUS is a promising method for assessing RF implant safety, and with further development, a TAUS pre-scan could allow many more patients to have access to MRI scans of significant clinical value.

Lying about Facial Recognition: An fMRI Study

ERIC Educational Resources Information Center

Bhatt, S.; Mbwana, J.; Adeyemo, A.; Sawyer, A.; Hailu, A.; VanMeter, J.

2009-01-01

Novel deception detection techniques have been in creation for centuries. Functional magnetic resonance imaging (fMRI) is a neuroscience technology that non-invasively measures brain activity associated with behavior and cognition. A number of investigators have explored the utilization and efficiency of fMRI in deception detection. In this study,…

SU-F-BRF-10: Deformable MRI to CT Validation Employing Same Day Planning MRI for Surrogate Analysis

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

Padgett, K; Stoyanova, R; Johnson, P

Purpose: To compare rigid and deformable registrations of the prostate in the multi-modality setting (diagnostic-MRI to planning-CT) by utilizing a planning-MRI as a surrogate. The surrogate allows for the direct quantitative analysis which can be difficult in the multi-modality domain where intensity mapping differs. Methods: For ten subjects, T2 fast-spin-echo images were acquired at two different time points, the first several weeks prior to planning (diagnostic-MRI) and the second on the same day in which the planning CT was collected (planning-MRI). Significant effort in patient positioning and bowel/bladder preparation was undertaken to minimize distortion of the prostate in all datasets.more » The diagnostic-MRI was deformed to the planning-CT utilizing a commercially available deformable registration algorithm synthesized from local registrations. The deformed MRI was then rigidly aligned to the planning MRI which was used as the surrogate for the planning-CT. Agreement between the two MRI datasets was scored using intensity based metrics including Pearson correlation and normalized mutual information, NMI. A local analysis was performed by looking only within the prostate, proximal seminal vesicles, penile bulb and combined areas. A similar method was used to assess a rigid registration between the diagnostic-MRI and planning-CT. Results: Utilizing the NMI, the deformable registrations were superior to the rigid registrations in 9 of 10 cases demonstrating a 15.94% improvement (p-value < 0.001) within the combined area. The Pearson correlation showed similar results with the deformable registration superior in the same number of cases and demonstrating a 6.97% improvement (p-value <0.011). Conclusion: Validating deformable multi-modality registrations using spatial intensity based metrics is difficult due to the inherent differences in intensity mapping. This population provides an ideal testing ground for MRI to CT deformable registrations by obviating the need for multi-modality comparisons which are inherently more challenging. Deformable registrations generated in this work significantly outperformed rigid alignments. Research reported in this abstract was supported by the NIH National Cancer Institute R21CA153826 “MRI-Guided Radiotherapy and Biomarkers for Prostate Cancer” and Bankhead-Coley Cancer Research Program 10BT-03 “MRI-Guided Radiotherapy and Biomarkers for Prostate Cancer”.« less

Disparities in staging prostate magnetic resonance imaging utilization for nonmetastatic prostate cancer patients undergoing definitive radiation therapy.

PubMed

Ajayi, Ayobami; Hwang, Wei-Ting; Vapiwala, Neha; Rosen, Mark; Chapman, Christina H; Both, Stefan; Shah, Meera; Wang, Xingmei; Agawu, Atu; Gabriel, Peter; Christodouleas, John; Tochner, Zelig; Deville, Curtiland

2016-01-01

There is growing evidence supporting incorporating multiparametric (mp) magnetic resonance imaging (MRI) scans into risk stratification, active surveillance, and treatment paradigms for prostate cancer. The purpose of our study was to determine whether demographic disparities exist in staging MRI utilization for prostate cancer patients. An institutional database of 705 nonmetastatic prostate cancer patients treated with radiation therapy from 2005 through 2013 was used to identify patients undergoing versus not undergoing pretreatment diagnostic prostate mpMRI. Uni- and multivariable logistic regression evaluated the relationship of clinical and demographic characteristics with MRI utilization. All demographic variables assessed, except the other race category, were significantly associated with MRI utilization (all P < .05), including age (odds ratio [OR], 0.92), black race (OR, 0.51), poverty (OR, 0.53), closer distance to radiation facility (OR, 1.79), and nonprivate primary insurance (OR, 0.57) on univariable analysis, while clinical stage T3 (OR, 3.37) was the only clinical characteristic. On multivariable analysis stratified by D'Amico risk group, age remained significant across all risk groups, whereas the black versus white racial (OR, 0.21; 95% confidence interval, 0.08-0.55) and nonprivate versus private insurance type (OR, 0.37; 95% confidence interval, 0.16-0.86) disparities persisted in the low-risk group. Clinical stage T3 remained associated in the high-risk group. For race specifically, the percentages of whites, blacks, and others undergoing MRI in the overall cohort and by risk group were, respectively: overall, 80% (343/427), 68% (156/231), and 85% (40/47); low risk, 86%, 56%, and 63%; intermediate risk, 79%, 72%, and 95%; and high risk, 72%, 72%, and 100%. In this urban, academic center cohort, older patients across all risk groups and black or nonprivate insurance patients in the low risk group were less likely to undergo staging prostate MRI scans. Further research should investigate these differences to ensure equitable utilization across all demographic groups considering the burden of prostate cancer disparities.

Health care utilization and costs associated with adherence to clinical practice guidelines for early magnetic resonance imaging among workers with acute occupational low back pain.

PubMed

Graves, Janessa M; Fulton-Kehoe, Deborah; Jarvik, Jeffrey G; Franklin, Gary M

2014-04-01

To estimate health care utilization and costs associated with adherence to clinical practice guidelines for the use of early magnetic resonance imaging (MRI; within the first 6 weeks of injury) for acute occupational low back pain (LBP). Washington State Disability Risk Identification Study Cohort (D-RISC), consisting of administrative claims and patient interview data from workers' compensation claimants (2002-2004). In this prospective, population-based cohort study, we compared health care utilization and costs among workers whose imaging was adherent to guidelines (no early MRI) to workers whose imaging was not adherent to guidelines (early MRI in the absence of red flags). We identified workers (age>18) with work-related LBP using administrative claims. We obtained demographic, injury, health, and employment information through telephone interviews to adjust for baseline differences between groups. We ascertained health care utilization and costs from administrative claims for 1 year following injury. Of 1,770 workers, 336 (19.0 percent) were classified as nonadherent to guidelines. Outpatient and physical/occupational therapy utilization was 52-54 percent higher for workers whose imaging was not adherent to guidelines compared to workers with guideline-adherent imaging; utilization of chiropractic care was significantly lower (18 percent). Nonadherence to guidelines for early MRI was associated with increased likelihood of lumbosacral injections or surgery and higher costs for out-patient, inpatient, and nonmedical services, and disability compensation. © Health Research and Educational Trust.

Impact of value based breast cancer care pathway implementation on pre-operative breast magnetic resonance imaging utilization.

PubMed

McCray, Devina K S; Grobmyer, Stephen R; Pederson, Holly J

2017-02-01

Bilateral breast magnetic resonance imaging (MRI) is commonly used in the diagnostic workup of breast cancer (BC) to assess extent of disease and identify occult foci of disease. However, evidence for routine use of pre-operative MRI is lacking. Breast MRI is costly and can lead to unnecessary tests and treatment delays. Clinical care pathways (care paths) are value-based guidelines, which define management recommendations derived by expert consensus and available evidence based data. At Cleveland Clinic, care paths created for newly diagnosed BC patients recommend selective use of pre-operative MRI. We evaluated the number of pre-operative MRIs ordered before and after implementing an institution wide BC care paths in April 2014. A retrospective review was conducted of BC cases during the years 2012, 2014, and part of 2015. Patient, tumor and treatment characteristics were collected. Pre-operative MRI utilization was compared before and after care path implementation. We identified 1,515 BC patients during the study period. Patients were more likely to undergo pre-operative MRI in 2012 than 2014 (OR: 2.77; P<0.001; 95% CI: 1.94-3.94) or 2015 (OR: 4.14; P<0.001; 95% CI: 2.51-6.83). There was a significant decrease in pre-operative MRI utilization between 2012 and 2014 (P<0.001) after adjustment for pre-operative MRIs ordered for care path indications. Implementation of online BC care paths at our institution was associated with a decreased use of pre-operative MRI overall and in patients without a BC care path indication, driving value based care through the reduction of pre-operative breast MRIs.

Location of core diagnostic information across various sequences in brain MRI and implications for efficiency of MRI scanner utilization.

PubMed

Sharma, Aseem; Chatterjee, Arindam; Goyal, Manu; Parsons, Matthew S; Bartel, Seth

2015-04-01

Targeting redundancy within MRI can improve its cost-effective utilization. We sought to quantify potential redundancy in our brain MRI protocols. In this retrospective review, we aggregated 207 consecutive adults who underwent brain MRI and reviewed their medical records to document clinical indication, core diagnostic information provided by MRI, and its clinical impact. Contributory imaging abnormalities constituted positive core diagnostic information whereas absence of imaging abnormalities constituted negative core diagnostic information. The senior author selected core sequences deemed sufficient for extraction of core diagnostic information. For validating core sequences selection, four readers assessed the relative ease of extracting core diagnostic information from the core sequences. Potential redundancy was calculated by comparing the average number of core sequences to the average number of sequences obtained. Scanning had been performed using 9.4±2.8 sequences over 37.3±12.3 minutes. Core diagnostic information was deemed extractable from 2.1±1.1 core sequences, with an assumed scanning time of 8.6±4.8 minutes, reflecting a potential redundancy of 74.5%±19.1%. Potential redundancy was least in scans obtained for treatment planning (14.9%±25.7%) and highest in scans obtained for follow-up of benign diseases (81.4%±12.6%). In 97.4% of cases, all four readers considered core diagnostic information to be either easily extractable from core sequences or the ease to be equivalent to that from the entire study. With only one MRI lacking clinical impact (0.48%), overutilization did not seem to contribute to potential redundancy. High potential redundancy that can be targeted for more efficient scanner utilization exists in brain MRI protocols.

Diagnostic tests in urology: magnetic resonance imaging (MRI) for the staging of prostate cancer.

PubMed

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

2013-03-01

WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: The use of MRI for prostate cancer diagnosis and staging is increasing. Indications for prostate MRI are not defined and many clinicians are unsure of how best to use MRI to aid clinical decisions. This evidence-based medicine article addresses the clinical utility of prostate MRI for preoperative staging. Based on a common patient scenario, a guide to calculating the probability of extraprostatic extension is provided. © 2013 BJU International.

Functional connectivity studies of patients with auditory verbal hallucinations.

PubMed

Hoffman, Ralph E; Hampson, Michelle

2011-12-02

Functional connectivity (FC) studies of brain mechanisms leading to auditory verbal hallucinations (AVHs) utilizing functional magnetic resonance imaging (fMRI) data are reviewed. Initial FC studies utilized fMRI data collected during performance of various tasks, which suggested frontotemporal disconnection and/or source-monitoring disturbances. Later FC studies have utilized resting (no-task) fMRI data. These studies have produced a mixed picture of disconnection and hyperconnectivity involving different pathways associated with AVHs. Results of our most recent FC study of AVHs are reviewed in detail. This study suggests that the core mechanism producing AVHs involves not a single pathway, but a more complex functional loop. Components of this loop include Wernicke's area and its right homologue, the left inferior frontal cortex, and the putamen. It is noteworthy that the putamen appears to play a critical role in the generation of spontaneous language, and in determining whether auditory stimuli are registered consciously as percepts. Excessive functional coordination linking this region with the Wernicke's seed region in patients with schizophrenia could, therefore, generate an overabundance of potentially conscious language representations. In our model, intact FC in the other two legs of corticostriatal loop (Wernicke's with left IFG, and left IFG with putamen) appeared to allow hyperconnectivity linking the putamen and Wernicke's area (common to schizophrenia overall) to be expressed as conscious hallucinations of speech. Recommendations for future studies are discussed, including inclusion of multiple methodologies applied to the same subjects in order to compare and contrast different mechanistic hypotheses, utilizing EEG to better parse time-course of neural synchronization leading to AVHs, and ascertaining experiential subtypes of AVHs that may reflect distinct mechanisms.

Using Neural Data to Test A Theory of Investor Behavior: An Application to Realization Utility.

PubMed

Frydman, Cary; Barberis, Nicholas; Camerer, Colin; Bossaerts, Peter; Rangel, Antonio

2014-04-01

We use measures of neural activity provided by functional magnetic resonance imaging (fMRI) to test the "realization utility" theory of investor behavior, which posits that people derive utility directly from the act of realizing gains and losses. Subjects traded stocks in an experimental market while we measured their brain activity. We find that all subjects exhibit a strong disposition effect in their trading, even though it is suboptimal. Consistent with the realization utility explanation for this behavior, we find that activity in the ventromedial prefrontal cortex, an area known to encode the value of options during choices, correlates with the capital gains of potential trades; that the neural measures of realization utility correlate across subjects with their individual tendency to exhibit a disposition effect; and that activity in the ventral striatum, an area known to encode information about changes in the present value of experienced utility, exhibits a positive response when subjects realize capital gains. These results provide support for the realization utility model and, more generally, demonstrate how neural data can be helpful in testing models of investor behavior.

Anatomical and functional assessment of brown adipose tissue by magnetic resonance imaging.

PubMed

Chen, Y Iris; Cypess, Aaron M; Sass, Christina A; Brownell, Anna-Liisa; Jokivarsi, Kimmo T; Kahn, C Ronald; Kwong, Kenneth K

2012-07-01

Brown adipose tissue (BAT) is the primary tissue responsible for nonshivering thermogenesis in mammals. The amount of BAT and its level of activation help regulate the utilization of excessive calories for thermogenesis as opposed to storage in white adipose tissue (WAT) which would lead to weight gain. Over the past several years, BAT activity in vivo has been primarily assessed by positron emission tomography-computed tomography (PET-CT) scan using 2-[18F]-fluoro-2-deoxy-D-glucose (18F-FDG) to measure glucose utilization associated with BAT mitochondrial respiration. In this study, we demonstrate the feasibility of mapping and estimating BAT volume and metabolic function in vivo in rats at a 9.4T magnetic resonance imaging (MRI) scanner using sequences available from clinical MR scanners. Based on the morphological characteristics of BAT, we measured the volume distribution of BAT with MRI sequences that have strong fat-water contrast. We also investigated BAT volume by utilizing spin-echo MRI sequences. The in vivo MRI-estimated BAT volumes were correlated with direct measurement of BAT mass from dissected samples. Using MRI, we also were able to map hemodynamic responses to changes in BAT metabolism induced pharmacologically by β3-adrenergic receptor agonist, CL-316,243 and compare this to BAT activity in response to CL-316,243 assessed by PET 18F-FDG. In conclusion, we demonstrate the feasibility of measuring BAT volume and function in vivo using routine MRI sequences. The MRI measurement of BAT volume is consistent with quantitative measurement of the tissue ex vivo.

Computed tomography-magnetic resonance image fusion: a clinical evaluation of an innovative approach for improved tumor localization in primary central nervous system lesions.

PubMed

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

1997-01-01

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

Validation of a deformable MRI to CT registration algorithm employing same day planning MRI for surrogate analysis.

PubMed

Padgett, Kyle R; Stoyanova, Radka; Pirozzi, Sara; Johnson, Perry; Piper, Jon; Dogan, Nesrin; Pollack, Alan

2018-03-01

Validating deformable multimodality image registrations is challenging due to intrinsic differences in signal characteristics and their spatial intensity distributions. Evaluating multimodality registrations using these spatial intensity distributions is also complicated by the fact that these metrics are often employed in the registration optimization process. This work evaluates rigid and deformable image registrations of the prostate in between diagnostic-MRI and radiation treatment planning-CT by utilizing a planning-MRI after fiducial marker placement as a surrogate. The surrogate allows for the direct quantitative analysis that can be difficult in the multimodality domain. For thirteen prostate patients, T2 images were acquired at two different time points, the first several weeks prior to planning (diagnostic-MRI) and the second on the same day as the planning-CT (planning-MRI). The diagnostic-MRI was deformed to the planning-CT utilizing a commercially available algorithm which synthesizes a deformable image registration (DIR) algorithm from local rigid registrations. The planning-MRI provided an independent surrogate for the planning-CT for assessing registration accuracy using image similarity metrics, including Pearson correlation and normalized mutual information (NMI). A local analysis was performed by looking only within the prostate, proximal seminal vesicles, penile bulb, and combined areas. The planning-MRI provided an excellent surrogate for the planning-CT with residual error in fiducial alignment between the two datasets being submillimeter, 0.78 mm. DIR was superior to the rigid registration in 11 of 13 cases demonstrating a 27.37% improvement in NMI (P < 0.009) within a regional area surrounding the prostate and associated critical organs. Pearson correlations showed similar results, demonstrating a 13.02% improvement (P < 0.013). By utilizing the planning-MRI as a surrogate for the planning-CT, an independent evaluation of registration accuracy is possible. This population provides an ideal testing ground for MRI to CT DIR by obviating the need for multimodality comparisons which are inherently more challenging. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

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

Clinical utility of BOLD fMRI in preoperative work-up of epilepsy

PubMed Central

Ganesan, Karthik; Ursekar, Meher

2014-01-01

Surgical techniques have emerged as a viable therapeutic option in patients with drug refractory epilepsy. Pre-surgical evaluation of epilepsy requires a comprehensive, multiparametric, and multimodal approach for precise localization of the epileptogenic focus. Various non-invasive techniques are available at the disposal of the treating physician to detect the epileptogenic focus, which include electroencephalography (EEG), video-EEG, magnetic resonance imaging (MRI), functional MRI including blood oxygen level dependent (BOLD) techniques, single photon emission tomography (SPECT), and 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET). Currently, non-invasive high-resolution MR imaging techniques play pivotal roles in the preoperative detection of the seizure focus, and represent the foundation for successful epilepsy surgery. BOLD functional magnetic resonance imaging (fMRI) maps allow for precise localization of the eloquent cortex in relation to the seizure focus. This review article focuses on the clinical utility of BOLD (fMRI) in the pre-surgical work-up of epilepsy patients. PMID:24851002

The utility of micro-CT and MRI in the assessment of longitudinal growth of liver metastases in a preclinical model of colon carcinoma.

PubMed

Pandit, Prachi; Johnston, Samuel M; Qi, Yi; Story, Jennifer; Nelson, Rendon; Johnson, G Allan

2013-04-01

Liver is a common site for distal metastases in colon and rectal cancer. Numerous clinical studies have analyzed the relative merits of different imaging modalities for detection of liver metastases. Several exciting new therapies are being investigated in preclinical models. But, technical challenges in preclinical imaging make it difficult to translate conclusions from clinical studies to the preclinical environment. This study addresses the technical challenges of preclinical magnetic resonance imaging (MRI) and micro-computed tomography (CT) to enable comparison of state-of-the-art methods for following metastatic liver disease. We optimized two promising preclinical protocols to enable a parallel longitudinal study tracking metastatic human colon carcinoma growth in a mouse model: T2-weighted MRI using two-shot PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction) and contrast-enhanced micro-CT using a liposomal contrast agent. Both methods were tailored for high throughput with attention to animal support and anesthesia to limit biological stress. Each modality has its strengths. Micro-CT permitted more rapid acquisition (<10 minutes) with the highest spatial resolution (88-micron isotropic resolution). But detection of metastatic lesions requires the use of a blood pool contrast agent, which could introduce a confound in the evaluation of new therapies. MRI was slower (30 minutes) and had lower anisotropic spatial resolution. But MRI eliminates the need for a contrast agent and the contrast-to-noise between tumor and normal parenchyma was higher, making earlier detection of small lesions possible. Both methods supported a relatively high-throughput, longitudinal study of the development of metastatic lesions. Copyright © 2013 AUR. Published by Elsevier Inc. All rights reserved.

Utility of brain MRI in children with sleep-disordered breathing.

PubMed

Selvadurai, Sarah; Al-Saleh, Suhail; Amin, Reshma; Zweerink, Allison; Drake, James; Propst, Evan J; Narang, Indra

2017-02-01

To investigate the utility of a brain magnetic resonance imaging (MRI) in children with sleep-disordered breathing (SDB), classified as isolated obstructive sleep apnea (OSA) in the absence of adenotonsillar hypertrophy, persistent OSA following adenotonsillectomy, isolated central sleep apnea (CSA) of unclear etiology, OSA with coexisting CSA of unclear etiology, or unexplained nocturnal hypoventilation (NH). Retrospective chart review of polysomnography (PSG) and brain MRI data. Children with PSG evidence of SDB, as described above, and who subsequently had their first brain MRI, were included. PSG, MRI data, and subsequent interventions were recorded. A total of 59 of 6,087 (1%) children met inclusion criteria. Of those, 28 of 59 (47%) were nonsyndromic children and 31 of 59 (53%) were syndromic children with an underlying medical disorder. Abnormal brain MRI findings were observed in 19 of 59 (32%) children, where eight of 19 (42%) were nonsyndromic and 11 of 19 (58%) were syndromic. Abnormal brain MRI findings were most common in syndromic children with combined OSA and CSA without adenotonsillar hypertrophy. Isolated OSA was also a common PSG finding associated with an abnormal brain MRI. Of the nonsyndromic children with an abnormal brain MRI, the most common abnormal brain MRI finding was Chiari malformation (CM), observed in 88% of the group. A brainstem tumor was identified in one nonsyndromic child. Interventions following brain MRI included neurosurgery, chemotherapy, and noninvasive positive pressure ventilation (NiPPV). A brain MRI is an important diagnostic tool in syndromic and nonsyndromic children, especially in children with either isolated OSA or combined OSA and CSA without a clear etiology. 4. Laryngoscope, 2016 127:513-519, 2017. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

Clinical utility of magnetic resonance imaging and ultrasonography for diagnosis of polycystic ovary syndrome in adolescent girls.

PubMed

Kenigsberg, Lisa E; Agarwal, Chhavi; Sin, Sanghun; Shifteh, Keivan; Isasi, Carmen R; Crespi, Rebecca; Ivanova, Janeta; Coupey, Susan M; Heptulla, Rubina A; Arens, Raanan

2015-11-01

To evaluate ovarian morphology using three-dimensional magnetic resonance imaging (MRI) in adolescent girls with and without polycystic ovary syndrome (PCOS). Also compare the utility of MRI versus ultrasonography (US) for diagnosis of PCOS. Cross-sectional study. Urban academic tertiary-care children's hospital. Thirty-nine adolescent girls with untreated PCOS and 22 age/body mass index (BMI)-matched controls. Magnetic resonance imaging and/or transvaginal/transabdominal US. Ovarian volume (OV); follicle number per section (FNPS); correlation between OV on MRI and US; proportion of subjects with features of polycystic ovaries (PCOs) on MRI and US. Magnetic resonance imaging demonstrated larger OV and higher FNPS in subjects with PCOS compared with controls. Within the PCOS group, median OV was 11.9 (7.7) cm(3) by MRI compared with 8.8 (7.8) cm(3) by US. Correlation coefficient between OV by MRI and US was 0.701. Due to poor resolution, FNPS could not be determined by US or compared with MRI. The receiver operating characteristic curve analysis for MRI demonstrated that increasing volume cutoffs for PCOs from 10-14 cm(3) increased specificity from 77%-95%. For FNPS on MRI, specificity increased from 82%-98% by increasing cutoffs from ≥ 12 to ≥ 17. Using Rotterdam cutoffs, 91% of subjects with PCOS met PCO criteria on MRI, whereas only 52% met criteria by US. Ultrasonography measures smaller OV than MRI, cannot accurately detect follicle number, and is a poor imaging modality for characterizing PCOs in adolescents with suspected PCOS. For adolescents in whom diagnosis of PCOS remains uncertain after clinical and laboratory evaluation, MRI should be considered as a diagnostic imaging modality. Copyright © 2015 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Health Care Utilization and Costs Associated with Adherence to Clinical Practice Guidelines for Early Magnetic Resonance Imaging among Workers with Acute Occupational Low Back Pain

PubMed Central

Graves, Janessa M; Fulton-Kehoe, Deborah; Jarvik, Jeffrey G; Franklin, Gary M

2014-01-01

Objective To estimate health care utilization and costs associated with adherence to clinical practice guidelines for the use of early magnetic resonance imaging (MRI; within the first 6 weeks of injury) for acute occupational low back pain (LBP). Data Sources Washington State Disability Risk Identification Study Cohort (D-RISC), consisting of administrative claims and patient interview data from workers’ compensation claimants (2002–2004). Study Design In this prospective, population-based cohort study, we compared health care utilization and costs among workers whose imaging was adherent to guidelines (no early MRI) to workers whose imaging was not adherent to guidelines (early MRI in the absence of red flags). Data Collection/Extraction Methods We identified workers (age >18) with work-related LBP using administrative claims. We obtained demographic, injury, health, and employment information through telephone interviews to adjust for baseline differences between groups. We ascertained health care utilization and costs from administrative claims for 1 year following injury. Principal Findings Of 1,770 workers, 336 (19.0 percent) were classified as nonadherent to guidelines. Outpatient and physical/occupational therapy utilization was 52–54 percent higher for workers whose imaging was not adherent to guidelines compared to workers with guideline-adherent imaging; utilization of chiropractic care was significantly lower (18 percent). Conclusions Nonadherence to guidelines for early MRI was associated with increased likelihood of lumbosacral injections or surgery and higher costs for out-patient, inpatient, and nonmedical services, and disability compensation. PMID:23910019

Role of Intra-operative MRI (iMRI) in Improving Extent of Resection and Survival in Patients with Glioblastoma Multiforme.

PubMed

Khan, Inamullah; Waqas, Muhammad; Shamim, Muhammad Shahzad

2017-07-01

Multiple intraoperative aids have been introduced to improve the extent of resection (EOR) in Glioblastoma Multiforme (GBM) patients, avoiding any new neurological deficits. Intraoperative MRI (iMRI) has been debated for its utility and cost for nearly two decades in neurosurgical literature. Review of literature suggests improved EOR in GBM patients who underwent iMRI assisted surgical resections leading to higher overall survival (OS) and progression free survival (PFS). iMRI provides real time intraoperative imaging with reasonable quality. Higher risk for new postoperative deficits with increased EOR is not reported in any study using iMRI. The level of evidence regarding prognostic benefits of iMRI is still of low quality..

The Cascade of Medical Services and Associated Longitudinal Costs Due to Nonadherent Magnetic Resonance Imaging for Low Back Pain

PubMed Central

Webster, Barbara S.; Choi, YoonSun; Bauer, Ann Z.; Cifuentes, Manuel

2014-01-01

Study Design. Retrospective cohort study. Objective. To compare type, timing, and longitudinal medical costs incurred after adherent versus nonadherent magnetic resonance imaging (MRI) for work-related low back pain. Summary of Background Data. Guidelines advise against MRI for acute uncomplicated low back pain, but is an option for persistent radicular pain after a trial of conservative care. Yet, MRI has become frequent and often nonadherent. Few studies have documented the nature and impact of medical services (including type and timing) initiated by nonadherent MRI. Methods. A longitudinal, workers' compensation administrative data source was accessed to select low back pain claims filed between January 1, 2006 and December 31, 2006. Cases were grouped by MRI timing (early, timely, no MRI) and subgrouped by severity (“less severe,” “more severe”) (final cohort = 3022). Health care utilization for each subgroup was evaluated at 3, 6, 9, and 12 months post-MRI. Multivariate logistic regression models examined risk of receiving subsequent diagnostic studies and/or treatments, adjusting for pain indicators and demographic covariates. Results. The adjusted relative risks for MRI group cases to receive electromyography, nerve conduction testing, advanced imaging, injections, and surgery within 6 months post-MRI risks in the range from 6.5 (95% CI: 2.20–19.09) to 54.9 (95% CI: 22.12–136.21) times the rate for the referent group (no MRI less severe). The timely and early MRI less severe subgroups had similar adjusted relative risks to receive most services. The early MRI more severe subgroup cases had generally higher adjusted relative risks than timely MRI more severe subgroup cases. Medical costs for both early MRI subgroups were highest and increased the most over time. Conclusion. The impact of nonadherent MRI includes a wide variety of expensive and potentially unnecessary services, and occurs relatively soon post-MRI. Study results provide evidence to promote provider and patient conversations to help patients choose care that is based on evidence, free from harm, less costly, and truly necessary. Level of Evidence: N/A PMID:24831502

Using Neural Data to Test A Theory of Investor Behavior: An Application to Realization Utility

PubMed Central

Frydman, Cary; Barberis, Nicholas; Camerer, Colin; Bossaerts, Peter; Rangel, Antonio

2015-01-01

We use measures of neural activity provided by functional magnetic resonance imaging (fMRI) to test the “realization utility” theory of investor behavior, which posits that people derive utility directly from the act of realizing gains and losses. Subjects traded stocks in an experimental market while we measured their brain activity. We find that all subjects exhibit a strong disposition effect in their trading, even though it is suboptimal. Consistent with the realization utility explanation for this behavior, we find that activity in the ventromedial prefrontal cortex, an area known to encode the value of options during choices, correlates with the capital gains of potential trades; that the neural measures of realization utility correlate across subjects with their individual tendency to exhibit a disposition effect; and that activity in the ventral striatum, an area known to encode information about changes in the present value of experienced utility, exhibits a positive response when subjects realize capital gains. These results provide support for the realization utility model and, more generally, demonstrate how neural data can be helpful in testing models of investor behavior. PMID:25774065

Detecting functional magnetic resonance imaging activation in white matter: Interhemispheric transfer across the corpus callosum

PubMed Central

Mazerolle, Erin L; D'Arcy, Ryan CN; Beyea, Steven D

2008-01-01

Background It is generally believed that activation in functional magnetic resonance imaging (fMRI) is restricted to gray matter. Despite this, a number of studies have reported white matter activation, particularly when the corpus callosum is targeted using interhemispheric transfer tasks. These findings suggest that fMRI signals may not be neatly confined to gray matter tissue. In the current experiment, 4 T fMRI was employed to evaluate whether it is possible to detect white matter activation. We used an interhemispheric transfer task modelled after neurological studies of callosal disconnection. It was hypothesized that white matter activation could be detected using fMRI. Results Both group and individual data were considered. At liberal statistical thresholds (p < 0.005, uncorrected), group level activation was detected in the isthmus of the corpus callosum. This region connects the superior parietal cortices, which have been implicated previously in interhemispheric transfer. At the individual level, five of the 24 subjects (21%) had activation clusters that were located primarily within the corpus callosum. Consistent with the group results, the clusters of all five subjects were located in posterior callosal regions. The signal time courses for these clusters were comparable to those observed for task related gray matter activation. Conclusion The findings support the idea that, despite the inherent challenges, fMRI activation can be detected in the corpus callosum at the individual level. Future work is needed to determine whether the detection of this activation can be improved by utilizing higher spatial resolution, optimizing acquisition parameters, and analyzing the data with tissue specific models of the hemodynamic response. The ability to detect white matter fMRI activation expands the scope of basic and clinical brain mapping research, and provides a new approach for understanding brain connectivity. PMID:18789154

Complete fourier direct magnetic resonance imaging (CFD-MRI) for diffusion MRI

PubMed Central

Özcan, Alpay

2013-01-01

The foundation for an accurate and unifying Fourier-based theory of diffusion weighted magnetic resonance imaging (DW–MRI) is constructed by carefully re-examining the first principles of DW–MRI signal formation and deriving its mathematical model from scratch. The derivations are specifically obtained for DW–MRI signal by including all of its elements (e.g., imaging gradients) using complex values. Particle methods are utilized in contrast to conventional partial differential equations approach. The signal is shown to be the Fourier transform of the joint distribution of number of the magnetic moments (at a given location at the initial time) and magnetic moment displacement integrals. In effect, the k-space is augmented by three more dimensions, corresponding to the frequency variables dual to displacement integral vectors. The joint distribution function is recovered by applying the Fourier transform to the complete high-dimensional data set. In the process, to obtain a physically meaningful real valued distribution function, phase corrections are applied for the re-establishment of Hermitian symmetry in the signal. Consequently, the method is fully unconstrained and directly presents the distribution of displacement integrals without any assumptions such as symmetry or Markovian property. The joint distribution function is visualized with isosurfaces, which describe the displacement integrals, overlaid on the distribution map of the number of magnetic moments with low mobility. The model provides an accurate description of the molecular motion measurements via DW–MRI. The improvement of the characterization of tissue microstructure leads to a better localization, detection and assessment of biological properties such as white matter integrity. The results are demonstrated on the experimental data obtained from an ex vivo baboon brain. PMID:23596401

Real-time fMRI processing with physiological noise correction - Comparison with off-line analysis.

PubMed

Misaki, Masaya; Barzigar, Nafise; Zotev, Vadim; Phillips, Raquel; Cheng, Samuel; Bodurka, Jerzy

2015-12-30

While applications of real-time functional magnetic resonance imaging (rtfMRI) are growing rapidly, there are still limitations in real-time data processing compared to off-line analysis. We developed a proof-of-concept real-time fMRI processing (rtfMRIp) system utilizing a personal computer (PC) with a dedicated graphic processing unit (GPU) to demonstrate that it is now possible to perform intensive whole-brain fMRI data processing in real-time. The rtfMRIp performs slice-timing correction, motion correction, spatial smoothing, signal scaling, and general linear model (GLM) analysis with multiple noise regressors including physiological noise modeled with cardiac (RETROICOR) and respiration volume per time (RVT). The whole-brain data analysis with more than 100,000voxels and more than 250volumes is completed in less than 300ms, much faster than the time required to acquire the fMRI volume. Real-time processing implementation cannot be identical to off-line analysis when time-course information is used, such as in slice-timing correction, signal scaling, and GLM. We verified that reduced slice-timing correction for real-time analysis had comparable output with off-line analysis. The real-time GLM analysis, however, showed over-fitting when the number of sampled volumes was small. Our system implemented real-time RETROICOR and RVT physiological noise corrections for the first time and it is capable of processing these steps on all available data at a given time, without need for recursive algorithms. Comprehensive data processing in rtfMRI is possible with a PC, while the number of samples should be considered in real-time GLM. Copyright © 2015 Elsevier B.V. All rights reserved.

Multiscale and multi-modality visualization of angiogenesis in a human breast cancer model

PubMed Central

Cebulla, Jana; Kim, Eugene; Rhie, Kevin; Zhang, Jiangyang

2017-01-01

Angiogenesis in breast cancer helps fulfill the metabolic demands of the progressing tumor and plays a critical role in tumor metastasis. Therefore, various imaging modalities have been used to characterize tumor angiogenesis. While micro-CT (μCT) is a powerful tool for analyzing the tumor microvascular architecture at micron-scale resolution, magnetic resonance imaging (MRI) with its sub-millimeter resolution is useful for obtaining in vivo vascular data (e.g. tumor blood volume and vessel size index). However, integration of these microscopic and macroscopic angiogenesis data across spatial resolutions remains challenging. Here we demonstrate the feasibility of ‘multiscale’ angiogenesis imaging in a human breast cancer model, wherein we bridge the resolution gap between ex vivo μCT and in vivo MRI using intermediate resolution ex vivo MR microscopy (μMRI). To achieve this integration, we developed suitable vessel segmentation techniques for the ex vivo imaging data and co-registered the vascular data from all three imaging modalities. We showcase two applications of this multiscale, multi-modality imaging approach: (1) creation of co-registered maps of vascular volume from three independent imaging modalities, and (2) visualization of differences in tumor vasculature between viable and necrotic tumor regions by integrating μCT vascular data with tumor cellularity data obtained using diffusion-weighted MRI. Collectively, these results demonstrate the utility of ‘mesoscopic’ resolution μMRI for integrating macroscopic in vivo MRI data and microscopic μCT data. Although focused on the breast tumor xenograft vasculature, our imaging platform could be extended to include additional data types for a detailed characterization of the tumor microenvironment and computational systems biology applications. PMID:24719185

The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI Methods

PubMed Central

Jack, Clifford R.; Bernstein, Matt A.; Fox, Nick C.; Thompson, Paul; Alexander, Gene; Harvey, Danielle; Borowski, Bret; Britson, Paula J.; Whitwell, Jennifer L.; Ward, Chadwick; Dale, Anders M.; Felmlee, Joel P.; Gunter, Jeffrey L.; Hill, Derek L.G.; Killiany, Ron; Schuff, Norbert; Fox-Bosetti, Sabrina; Lin, Chen; Studholme, Colin; DeCarli, Charles S.; Krueger, Gunnar; Ward, Heidi A.; Metzger, Gregory J.; Scott, Katherine T.; Mallozzi, Richard; Blezek, Daniel; Levy, Joshua; Debbins, Josef P.; Fleisher, Adam S.; Albert, Marilyn; Green, Robert; Bartzokis, George; Glover, Gary; Mugler, John; Weiner, Michael W.

2008-01-01

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a longitudinal multisite observational study of healthy elders, mild cognitive impairment (MCI), and Alzheimer's disease. Magnetic resonance imaging (MRI), (18F)-fluorode-oxyglucose positron emission tomography (FDG PET), urine serum, and cerebrospinal fluid (CSF) biomarkers, as well as clinical/psychometric assessments are acquiredat multiple time points. All data will be cross-linked and made available to the general scientific community. The purpose of this report is to describe the MRI methods employed in ADNI. The ADNI MRI core established specifications thatguided protocol development. A major effort was devoted toevaluating 3D T1-weighted sequences for morphometric analyses. Several options for this sequence were optimized for the relevant manufacturer platforms and then compared in a reduced-scale clinical trial. The protocol selected for the ADNI study includes: back-to-back 3D magnetization prepared rapid gradient echo (MP-RAGE) scans; B1-calibration scans when applicable; and an axial proton density-T2 dual contrast (i.e., echo) fast spin echo/turbo spin echo (FSE/TSE) for pathology detection. ADNI MRI methods seek to maximize scientific utility while minimizing the burden placed on participants. The approach taken in ADNI to standardization across sites and platforms of the MRI protocol, postacquisition corrections, and phantom-based monitoring of all scanners could be used as a model for other multisite trials. PMID:18302232

The Clinical Utility and Diagnostic Performance of MRI for Identification of Early and Advanced Knee Osteoarthritis: A Systematic Review

PubMed Central

Quatman, Carmen E.; Hettrich, Carolyn M.; Schmitt, Laura C.; Spindler, Kurt P.

2013-01-01

Background Current diagnostic strategies for detection of structural articular cartilage abnormalities, the earliest structural signs of osteoarthritis, often do not capture the condition until it is too far advanced for the most potential benefit of non-invasive interventions. Purpose Systematically review the literature relative to the following questions: (1) Is MRI a valid, sensitive, specific, accurate and reliable instrument to identify knee articular cartilage abnormalities compared to arthroscopy? (2) Is MRI a sensitive tool that can be utilized to identify early cartilage degeneration? Study Design Systematic Review Methods A systematic search was performed in November 2010 using PubMed MEDLINE (from 1966), CINAHL (from 1982), SPORTDiscus (from 1985), and SCOPUS (from 1996) databases. Results Fourteen level I and 13 level II studies were identified that met inclusion criteria and provided information related to diagnostic performance of MRI compared to arthroscopic evaluation. The diagnostic performance of MRI demonstrated a large range of sensitivities, specificities, and accuracies. The sensitivity for identifying articular cartilage abnormalities in the knee joint was reported between 26–96%. Specificity and accuracy was reported between 50–100% and 49–94%, respectively. The sensitivity, specificity, and accuracy for identifying early osteoarthritis were reported between 0–86%, 48–95%, and 5–94%, respectively. As a result of inconsistencies between imaging techniques and methodological shortcomings of many of the studies, a meta-analysis was not performed and it was difficult to fully synthesize the information to state firm conclusions about the diagnostic performance of MRI. Conclusions There is evidence in some MRI protocols that MRI is a relatively valid, sensitive, specific, accurate, and reliable clinical tool for identifying articular cartilage degeneration. Due to heterogeneity of MRI sequences it is not possible to make definitive conclusions regarding its global clinical utility for guiding diagnosis and treatment strategies. Clinical Relevance Traumatic sports injuries to the knee may be significant precursor events to early onset of posttraumatic osteoarthritis. MRI may aid in early identification of structural injuries to articular cartilage as evidenced by articular cartilage degeneration grading. PMID:21730207

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.

Advanced magnetic resonance imaging in glioblastoma: a review.

PubMed

Shukla, Gaurav; Alexander, Gregory S; Bakas, Spyridon; Nikam, Rahul; Talekar, Kiran; Palmer, Joshua D; Shi, Wenyin

2017-08-01

Glioblastoma, the most common and most rapidly progressing primary malignant tumor of the central nervous system, continues to portend a dismal prognosis, despite improvements in diagnostic and therapeutic strategies over the last 20 years. The standard of care radiographic characterization of glioblastoma is magnetic resonance imaging (MRI), which is a widely utilized examination in the diagnosis and post-treatment management of patients with glioblastoma. Basic MRI modalities available from any clinical scanner, including native T1-weighted (T1w) and contrast-enhanced (T1CE), T2-weighted (T2w), and T2-fluid-attenuated inversion recovery (T2-FLAIR) sequences, provide critical clinical information about various processes in the tumor environment. In the last decade, advanced MRI modalities are increasingly utilized to further characterize glioblastomas more comprehensively. These include multi-parametric MRI sequences, such as dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE), higher order diffusion techniques such as diffusion tensor imaging (DTI), and MR spectroscopy (MRS). Significant efforts are ongoing to implement these advanced imaging modalities into improved clinical workflows and personalized therapy approaches. Functional MRI (fMRI) and tractography are increasingly being used to identify eloquent cortices and important tracts to minimize postsurgical neuro-deficits. A contemporary review of the application of standard and advanced MRI in clinical neuro-oncologic practice is presented here.

A semi-supervised Support Vector Machine model for predicting the language outcomes following cochlear implantation based on pre-implant brain fMRI imaging.

PubMed

Tan, Lirong; Holland, Scott K; Deshpande, Aniruddha K; Chen, Ye; Choo, Daniel I; Lu, Long J

2015-12-01

We developed a machine learning model to predict whether or not a cochlear implant (CI) candidate will develop effective language skills within 2 years after the CI surgery by using the pre-implant brain fMRI data from the candidate. The language performance was measured 2 years after the CI surgery by the Clinical Evaluation of Language Fundamentals-Preschool, Second Edition (CELF-P2). Based on the CELF-P2 scores, the CI recipients were designated as either effective or ineffective CI users. For feature extraction from the fMRI data, we constructed contrast maps using the general linear model, and then utilized the Bag-of-Words (BoW) approach that we previously published to convert the contrast maps into feature vectors. We trained both supervised models and semi-supervised models to classify CI users as effective or ineffective. Compared with the conventional feature extraction approach, which used each single voxel as a feature, our BoW approach gave rise to much better performance for the classification of effective versus ineffective CI users. The semi-supervised model with the feature set extracted by the BoW approach from the contrast of speech versus silence achieved a leave-one-out cross-validation AUC as high as 0.97. Recursive feature elimination unexpectedly revealed that two features were sufficient to provide highly accurate classification of effective versus ineffective CI users based on our current dataset. We have validated the hypothesis that pre-implant cortical activation patterns revealed by fMRI during infancy correlate with language performance 2 years after cochlear implantation. The two brain regions highlighted by our classifier are potential biomarkers for the prediction of CI outcomes. Our study also demonstrated the superiority of the semi-supervised model over the supervised model. It is always worthwhile to try a semi-supervised model when unlabeled data are available.

Primary vaginal cancer: role of MRI in diagnosis, staging and treatment

PubMed Central

Sunil, J; Klopp, A H; Devine, C E; Sagebiel, T; Viswanathan, C; Bhosale, P R

2015-01-01

Primary carcinoma of the vagina is rare, accounting for 1–3% of all gynaecological malignancies. MRI has an increasing role in diagnosis, staging, treatment and assessment of complications in gynaecologic malignancy. In this review, we illustrate the utility of MRI in patients with primary vaginal cancer and highlight key aspects of staging, treatment, recurrence and complications. PMID:25966291

Application of Independent Component Analysis for the Data Mining of Simultaneous EEG-fMRI: Preliminary Experience on Sleep Onset

PubMed Central

Lee, Jong-Hwan; Oh, Sungsuk; Jolesz, Ferenc A.; Park, Hyunwook; Yoo, Seung-Schik

2010-01-01

The simultaneous acquisition of electroencephalogram (EEG) and functional MRI (fMRI) signals is potentially advantageous because of the superior resolution that is achieved in both the temporal and spatial domains, respectively. However, ballistocardiographic artifacts along with the ocular artifacts are a major obstacle for the detection of the EEG signatures of interest. Since the sources corresponding to these artifacts are independent from those producing the EEG signatures, we applied the Infomax-based independent component analysis (ICA) technique to separate the EEG signatures from the artifacts. The isolated EEG signatures were further utilized to model the canonical hemodynamic response functions (HRFs). Subsequently, the brain areas from which these EEG signatures originated were identified as locales of activation patterns from the analysis of fMRI data. Upon the identification and subsequent evaluation of brain areas generating interictal epileptic discharge (IED) spikes from an epileptic subject, the presented method was successfully applied to detect the theta- and alpha-rhythms that are sleep onset related EEG signatures along with the subsequent neural circuitries from a sleep deprived volunteer. These results suggest that the ICA technique may be useful for the preprocessing of simultaneous EEG-fMRI acquisitions, especially when a reference paradigm is unavailable. PMID:19922343

Application of independent component analysis for the data mining of simultaneous Eeg-fMRI: preliminary experience on sleep onset.

PubMed

Lee, Jong-Hwan; Oh, Sungsuk; Jolesz, Ferenc A; Park, Hyunwook; Yoo, Seung-Schik

2009-01-01

The simultaneous acquisition of electroencephalogram (EEG) and functional MRI (fMRI) signals is potentially advantageous because of the superior resolution that is achieved in both the temporal and spatial domains, respectively. However, ballistocardiographic artifacts along with ocular artifacts are a major obstacle for the detection of the EEG signatures of interest. Since the sources corresponding to these artifacts are independent from those producing the EEG signatures, we applied the Infomax-based independent component analysis (ICA) technique to separate the EEG signatures from the artifacts. The isolated EEG signatures were further utilized to model the canonical hemodynamic response functions (HRFs). Subsequently, the brain areas from which these EEG signatures originated were identified as locales of activation patterns from the analysis of fMRI data. Upon the identification and subsequent evaluation of brain areas generating interictal epileptic discharge (IED) spikes from an epileptic subject, the presented method was successfully applied to detect the theta and alpha rhythms that are sleep onset-related EEG signatures along with the subsequent neural circuitries from a sleep-deprived volunteer. These results suggest that the ICA technique may be useful for the preprocessing of simultaneous EEG-fMRI acquisitions, especially when a reference paradigm is unavailable.

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

Jansen, F.

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applicationsmore » that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee.« less

Use of bio-informatics assessment schema (BIAS) to improve diagnosis and prognosis of myocardial perfusion data: results from the NHLBI-sponsored women's ischemia syndrome evaluation (WISE).

PubMed

Doyle, Mark; Pohost, Gerald M; Bairey Merz, C Noel; Shaw, Leslee J; Sopko, George; Rogers, William J; Sharaf, Barry L; Pepine, Carl J; Thompson, Diane V; Rayarao, Geetha; Tauxe, Lindsey; Kelsey, Sheryl F; Biederman, Robert W W

2016-10-01

We introduce an algorithmic approach to optimize diagnostic and prognostic value of gated cardiac single photon emission computed tomography (SPECT) and magnetic resonance (MR) myocardial perfusion imaging (MPI) modalities in women with suspected myocardial ischemia. The novel approach: bio-informatics assessment schema (BIAS) forms a mathematical model utilizing MPI data and cardiac metrics generated by one modality to predict the MPI status of another modality. The model identifies cardiac features that either enhance or mask the image-based evidence of ischemia. For each patient, the BIAS model value is used to set an appropriate threshold for the detection of ischemia. Women (n=130), with symptoms and signs of suspected myocardial ischemia, underwent MPI assessment for regional perfusion defects using two different modalities: gated SPECT and MR. To determine perfusion status, MR data were evaluated qualitatively (MRI QL ) and semi-quantitatively (MRI SQ ) while SPECT data were evaluated using conventional clinical criteria. Evaluators were masked to results of the alternate modality. These MPI status readings were designated "original". Two regression models designated "BIAS" models were generated to model MPI status obtained with one modality (e.g., MRI) compared with a second modality (e.g., SPECT), but importantly, the BIAS models did not include the primary Original MPI reading of the predicting modality. Instead, the BIAS models included auxiliary measurements like left ventricular chamber volumes and myocardial wall thickness. For each modality, the BIAS model was used to set a progressive threshold for interpretation of MPI status. Women were then followed for 38±14 months for the development of a first major adverse cardiovascular event [MACE: CV death, nonfatal myocardial infarction (MI) or hospitalization for heart failure]. Original and BIAS-augmented perfusion status were compared in their ability to detect coronary artery disease (CAD) and for prediction of MACE. Adverse events occurred in 14 (11%) women and CAD was present in 13 (10%). There was a positive correlation of maximum coronary artery stenosis and BIAS score for MRI and SPECT (P<0.001). Receiver operator characteristic (ROC) analysis was conducted and showed an increase in the area under the curve of the BIAS-augmented MPI interpretation of MACE vs . the original for MRI SQ (0.78 vs . 0.54), MRI QL (0.78 vs . 0.64), SPECT (0.82 vs . 0.63) and the average of the three readings (0.80±0.02 vs . 0.60±0.05, P<0.05). Increasing values of the BIAS score generated by both MRI and SPECT corresponded to the increasing prevalence of CAD and MACE. The BIAS-augmented detection of ischemia better predicted MACE compared with the Original reading for the MPI data for both MRI and SPECT.

Preclinical Magnetic Resonance Imaging and Spectroscopy Studies of Memory, Aging, and Cognitive Decline

PubMed Central

Febo, Marcelo; Foster, Thomas C.

2016-01-01

Neuroimaging provides for non-invasive evaluation of brain structure and activity and has been employed to suggest possible mechanisms for cognitive aging in humans. However, these imaging procedures have limits in terms of defining cellular and molecular mechanisms. In contrast, investigations of cognitive aging in animal models have mostly utilized techniques that have offered insight on synaptic, cellular, genetic, and epigenetic mechanisms affecting memory. Studies employing magnetic resonance imaging and spectroscopy (MRI and MRS, respectively) in animal models have emerged as an integrative set of techniques bridging localized cellular/molecular phenomenon and broader in vivo neural network alterations. MRI methods are remarkably suited to longitudinal tracking of cognitive function over extended periods permitting examination of the trajectory of structural or activity related changes. Combined with molecular and electrophysiological tools to selectively drive activity within specific brain regions, recent studies have begun to unlock the meaning of fMRI signals in terms of the role of neural plasticity and types of neural activity that generate the signals. The techniques provide a unique opportunity to causally determine how memory-relevant synaptic activity is processed and how memories may be distributed or reconsolidated over time. The present review summarizes research employing animal MRI and MRS in the study of brain function, structure, and biochemistry, with a particular focus on age-related cognitive decline. PMID:27468264

Multi-shot PROPELLER for high-field preclinical MRI

PubMed Central

Pandit, Prachi; Qi, Yi; Story, Jennifer; King, Kevin F.; Johnson, G. Allan

2012-01-01

With the development of numerous mouse models of cancer, there is a tremendous need for an appropriate imaging technique to study the disease evolution. High-field T2-weighted imaging using PROPELLER MRI meets this need. The 2-shot PROPELLER technique presented here, provides (a) high spatial resolution, (b) high contrast resolution, and (c) rapid and non-invasive imaging, which enables high-throughput, longitudinal studies in free-breathing mice. Unique data collection and reconstruction makes this method robust against motion artifacts. The 2-shot modification introduced here, retains more high-frequency information and provides higher SNR than conventional single-shot PROPELLER, making this sequence feasible at high-fields, where signal loss is rapid. Results are shown in a liver metastases model to demonstrate the utility of this technique in one of the more challenging regions of the mouse, which is the abdomen. PMID:20572138

Multishot PROPELLER for high-field preclinical MRI.

PubMed

Pandit, Prachi; Qi, Yi; Story, Jennifer; King, Kevin F; Johnson, G Allan

2010-07-01

With the development of numerous mouse models of cancer, there is a tremendous need for an appropriate imaging technique to study the disease evolution. High-field T(2)-weighted imaging using PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction) MRI meets this need. The two-shot PROPELLER technique presented here provides (a) high spatial resolution, (b) high contrast resolution, and (c) rapid and noninvasive imaging, which enables high-throughput, longitudinal studies in free-breathing mice. Unique data collection and reconstruction makes this method robust against motion artifacts. The two-shot modification introduced here retains more high-frequency information and provides higher signal-to-noise ratio than conventional single-shot PROPELLER, making this sequence feasible at high fields, where signal loss is rapid. Results are shown in a liver metastases model to demonstrate the utility of this technique in one of the more challenging regions of the mouse, which is the abdomen. (c) 2010 Wiley-Liss, Inc.

MRI of the stomach: a pictorial review with a focus on oncological applications and gastric motility.

PubMed

Sheybani, Arman; Menias, Christine O; Luna, Antonio; Fowler, Kathryn J; Hara, Amy Kiyo; Silva, Alvin C; Yano, Motoyo; Sandrasegaran, Kumar

2015-04-01

The purpose of this pictorial review is to demonstrate gastric pathology seen on magnetic resonance imaging (MRI) and discuss the essential MRI sequences for the evaluation of benign and malignant gastric pathologies. Common tumors of the stomach, polyposis syndromes, iatrogenic conditions, as well as other conditions of the stomach will be reviewed. The utility of MRI in the evaluation of patients with gastric malignancies and disorders of gastric motility will also be discussed.

Magnetic resonance imaging in prostate brachytherapy: Evidence, clinical end points to data, and direction forward.

PubMed

Pugh, Thomas J; Pokharel, Sajal S

The integration of multiparametric MRI into prostate brachytherapy has become a subject of interest over the past 2 decades. MRI directed high-dose-rate and low-dose-rate prostate brachytherapy offers the potential to improve treatment accuracy and standardize postprocedure quality. This article reviews the evidence to date on MRI utilization in prostate brachytherapy and postulates future pathways for MRI integration. Copyright © 2016 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Technical Note: Building a combined cyclotron and MRI facility: Implications for interference

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

Hofman, Mark B. M.; Kuijer, Joost P. A.; Ridder, Jan Willem de

2013-01-15

Purpose: With the introduction of hybrid PET/MRI systems, it has become more likely that the cyclotron and MRI systems will be located close to each other. This study considered the interference between a cyclotron and a superconducting MRI system. Methods: Interactions between cyclotrons and MRIs are theoretically considered. The main interference is expected to be the perturbation of the magnetic field in the MRI due to switching on or off the magnetic field of the cyclotron. MR imaging is distorted by a dynamic spatial gradient of an external inplane magnetic field larger than 0.5-0.04 {mu}T/m, depending on the specific MRmore » application. From the design of a cyclotron, it is expected that the magnetic fringe field at large distances behaves as a magnetic dipolar field. This allows estimation of the full dipolar field and its spatial gradients from a single measurement. Around an 18 MeV cyclotron (Cyclone, IBA), magnetic field measurements were performed on 5 locations and compared with calculations based upon a dipolar field model. Results: At the measurement locations the estimated and measured values of the magnetic field component and its spatial gradients of the inplane component were compared, and found to agree within a factor 1.1 for the magnetic field and within a factor of 1.5 for the spatial gradients of the field. In the specific case of the 18 MeV cyclotron with a vertical magnetic field and a 3T superconducting whole body MR system, a minimum distance of 20 m has to be considered to prevent interference. Conclusions: This study showed that a dipole model is sufficiently accurate to predict the interference of a cyclotron on a MRI scanner, for site planning purposes. The cyclotron and a whole body MRI system considered in this study need to be placed more than 20 m apart, or magnetic shielding should be utilized.« less

MULTISCALE ADAPTIVE SMOOTHING MODELS FOR THE HEMODYNAMIC RESPONSE FUNCTION IN FMRI*

PubMed Central

Wang, Jiaping; Zhu, Hongtu; Fan, Jianqing; Giovanello, Kelly; Lin, Weili

2012-01-01

In the event-related functional magnetic resonance imaging (fMRI) data analysis, there is an extensive interest in accurately and robustly estimating the hemodynamic response function (HRF) and its associated statistics (e.g., the magnitude and duration of the activation). Most methods to date are developed in the time domain and they have utilized almost exclusively the temporal information of fMRI data without accounting for the spatial information. The aim of this paper is to develop a multiscale adaptive smoothing model (MASM) in the frequency domain by integrating the spatial and temporal information to adaptively and accurately estimate HRFs pertaining to each stimulus sequence across all voxels in a three-dimensional (3D) volume. We use two sets of simulation studies and a real data set to examine the finite sample performance of MASM in estimating HRFs. Our real and simulated data analyses confirm that MASM outperforms several other state-of-art methods, such as the smooth finite impulse response (sFIR) model. PMID:24533041

Spatially adapted augmentation of age-specific atlas-based segmentation using patch-based priors

NASA Astrophysics Data System (ADS)

Liu, Mengyuan; Seshamani, Sharmishtaa; Harrylock, Lisa; Kitsch, Averi; Miller, Steven; Chau, Van; Poskitt, Kenneth; Rousseau, Francois; Studholme, Colin

2014-03-01

One of the most common approaches to MRI brain tissue segmentation is to employ an atlas prior to initialize an Expectation- Maximization (EM) image labeling scheme using a statistical model of MRI intensities. This prior is commonly derived from a set of manually segmented training data from the population of interest. However, in cases where subject anatomy varies significantly from the prior anatomical average model (for example in the case where extreme developmental abnormalities or brain injuries occur), the prior tissue map does not provide adequate information about the observed MRI intensities to ensure the EM algorithm converges to an anatomically accurate labeling of the MRI. In this paper, we present a novel approach for automatic segmentation of such cases. This approach augments the atlas-based EM segmentation by exploring methods to build a hybrid tissue segmentation scheme that seeks to learn where an atlas prior fails (due to inadequate representation of anatomical variation in the statistical atlas) and utilize an alternative prior derived from a patch driven search of the atlas data. We describe a framework for incorporating this patch-based augmentation of EM (PBAEM) into a 4D age-specific atlas-based segmentation of developing brain anatomy. The proposed approach was evaluated on a set of MRI brain scans of premature neonates with ages ranging from 27.29 to 46.43 gestational weeks (GWs). Results indicated superior performance compared to the conventional atlas-based segmentation method, providing improved segmentation accuracy for gray matter, white matter, ventricles and sulcal CSF regions.

A New MRI-Based Model of Heart Function with Coupled Hemodynamics and Application to Normal and Diseased Canine Left Ventricles

PubMed Central

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

2015-01-01

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

MO-FG-207-01: Technological Advances and Challenges: Experience with the First Integrated Whole-Body PET/MRI

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

Laforest, R.

2015-06-15

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applicationsmore » that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee.« less

The utility of high-resolution intraoperative MRI in endoscopic transsphenoidal surgery for pituitary macroadenomas: early experience in the Advanced Multimodality Image Guided Operating suite.

PubMed

Zaidi, Hasan A; De Los Reyes, Kenneth; Barkhoudarian, Garni; Litvack, Zachary N; Bi, Wenya Linda; Rincon-Torroella, Jordina; Mukundan, Srinivasan; Dunn, Ian F; Laws, Edward R

2016-03-01

Endoscopic skull base surgery has become increasingly popular among the skull base surgery community, with improved illumination and angled visualization potentially improving tumor resection rates. Intraoperative MRI (iMRI) is used to detect residual disease during the course of the resection. This study is an investigation of the utility of 3-T iMRI in combination with transnasal endoscopy with regard to gross-total resection (GTR) of pituitary macroadenomas. The authors retrospectively reviewed all endoscopic transsphenoidal operations performed in the Advanced Multimodality Image Guided Operating (AMIGO) suite from November 2011 to December 2014. Inclusion criteria were patients harboring presumed pituitary macroadenomas with optic nerve or chiasmal compression and visual loss, operated on by a single surgeon. Of the 27 patients who underwent transsphenoidal resection in the AMIGO suite, 20 patients met the inclusion criteria. The endoscope alone, without the use of iMRI, would have correctly predicted extent of resection in 13 (65%) of 20 cases. Gross-total resection was achieved in 12 patients (60%) prior to MRI. Intraoperative MRI helped convert 1 STR and 4 NTRs to GTRs, increasing the number of GTRs from 12 (60%) to 16 (80%). Despite advances in visualization provided by the endoscope, the incidence of residual disease can potentially place the patient at risk for additional surgery. The authors found that iMRI can be useful in detecting unexpected residual tumor. The cost-effectiveness of this tool is yet to be determined.

Development and Validation of a qRT-PCR Classifier for Lung Cancer Prognosis

PubMed Central

Chen, Guoan; Kim, Sinae; Taylor, Jeremy MG; Wang, Zhuwen; Lee, Oliver; Ramnath, Nithya; Reddy, Rishindra M; Lin, Jules; Chang, Andrew C; Orringer, Mark B; Beer, David G

2011-01-01

Purpose This prospective study aimed to develop a robust and clinically-applicable method to identify high-risk early stage lung cancer patients and then to validate this method for use in future translational studies. Patients and Methods Three published Affymetrix microarray data sets representing 680 primary tumors were used in the survival-related gene selection procedure using clustering, Cox model and random survival forest (RSF) analysis. A final set of 91 genes was selected and tested as a predictor of survival using a qRT-PCR-based assay utilizing an independent cohort of 101 lung adenocarcinomas. Results The RSF model built from 91 genes in the training set predicted patient survival in an independent cohort of 101 lung adenocarcinomas, with a prediction error rate of 26.6%. The mortality risk index (MRI) was significantly related to survival (Cox model p < 0.00001) and separated all patients into low, medium, and high-risk groups (HR = 1.00, 2.82, 4.42). The MRI was also related to survival in stage 1 patients (Cox model p = 0.001), separating patients into low, medium, and high-risk groups (HR = 1.00, 3.29, 3.77). Conclusions The development and validation of this robust qRT-PCR platform allows prediction of patient survival with early stage lung cancer. Utilization will now allow investigators to evaluate it prospectively by incorporation into new clinical trials with the goal of personalized treatment of lung cancer patients and improving patient survival. PMID:21792073

MO-FG-207-00: Technological Advances in PET/MR Imaging

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

NONE

2015-06-15

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applicationsmore » that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee.« less

MITK-based segmentation of co-registered MRI for subject-related regional anesthesia simulation

NASA Astrophysics Data System (ADS)

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

2008-03-01

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

Assessing Intrarenal Non-perfusion and Vascular Leakage in Acute Kidney Injury withzz 19F MRI and Perfluorocarbon Nanoparticles

PubMed Central

Hu, Lingzhi; Chen, Junjie; Yang, Xiaoxia; Senpan, Angana; Allen, John S.; Yanaba, Noriko; Caruthers, Shelton D.; Lanza, Gregory M.; Hammerman, Marc R.; Wickline, Samuel A.

2014-01-01

Purpose We sought to develop a unique sensor-reporter approach for functional kidney imaging that employs circulating perfluorocarbon nanoparticles (PFC NPs) and 19F MRI. Methods Because the detected 19F signal intensity directly reflects local blood volume, and the 19F R1 is linearly proportional to local blood oxygen content (pO2), 19F spin density weighted and T1 weighted images were utilized to generate quantitative functional mapping in both healthy and ischemia-reperfusion (acute kidney injury, AKI) injured mouse kidneys. 1H Blood-Oxygenation-Level-Dependant (BOLD) MRI was also employed as a supplementary approach to facilitate the compressive analysis of renal circulation and its pathological changes in AKI. Results Heterogeneous blood volume distribution and intrarenal oxygenation gradient were confirmed in healthy kidneys by 19F MRI. In a mouse model of AKI, 19F MRI, in conjunction with BOLR MRI, sensitively delineated renal vascular damage and recovery. In the cortico-medullary (CM) junction region, we observed 25% lower 19F signal (p<0.05) and 70% longer 1H T2* (p<0.01) in injured kidneys compared to contralateral kidneys at 24 hours after initial ischemia-reperfusion injury. We also detected 71% higher 19F signal (p<0.01) and 40% lower 1H T2* (p<0.05) in the renal medulla region of injured kidneys compared to contralateral kidneys. Conclusion With demonstrated superior diagnostic capability, functional kidney 19F MRI using PFC NPs could serve as a new diagnostic measures for comprehensive evaluation of renal function and pathology. PMID:23929727

Wallerian Degeneration Beyond the Corticospinal Tracts: Conventional and Advanced MRI Findings.

PubMed

Chen, Yin Jie; Nabavizadeh, Seyed Ali; Vossough, Arastoo; Kumar, Sunil; Loevner, Laurie A; Mohan, Suyash

2017-05-01

Wallerian degeneration (WD) is defined as progressive anterograde disintegration of axons and accompanying demyelination after an injury to the proximal axon or cell body. Since the 1980s and 1990s, conventional magnetic resonance imaging (MRI) sequences have been shown to be sensitive to changes of WD in the subacute to chronic phases. More recently, advanced MRI techniques, such as diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI), have demonstrated some of earliest changes attributed to acute WD, typically on the order of days. In addition, there is increasing evidence on the value of advanced MRI techniques in providing important prognostic information related to WD. This article reviews the utility of conventional and advanced MRI techniques for assessing WD, by focusing not only on the corticospinal tract but also other neural tracts less commonly thought of, including corticopontocerebellar tract, dentate-rubro-olivary pathway, posterior column of the spinal cord, corpus callosum, limbic circuit, and optic pathway. The basic anatomy of these neural pathways will be discussed, followed by a comprehensive review of existing literature supported by instructive clinical examples. The goal of this review is for readers to become more familiar with both conventional and advanced MRI findings of WD involving important neural pathways, as well as to illustrate increasing utility of advanced MRI techniques in providing important prognostic information for various pathologies. Copyright © 2016 by the American Society of Neuroimaging.

Monitoring the development of xenograft triple-negative breast cancer models using diffusion-weighted magnetic resonance imaging.

PubMed

Stephen, Renu M; Pagel, Mark D; Brown, Kathy; Baker, Amanda F; Meuillet, Emmanuelle J; Gillies, Robert J

2012-11-01

Evaluations of tumor growth rates and molecular biomarkers are traditionally used to assess new mouse models of human breast cancers. This study investigated the utility of diffusion weighted (DW)-magnetic resonance imaging (MRI) for evaluating cellular proliferation of new tumor models of triple-negative breast cancer, which may augment traditional analysis methods. Eleven human breast cancer cell lines were used to develop xenograft tumors in severe combined immunodeficient mice, with two of these cell lines exhibiting sufficient growth to be serially passaged. DW-MRI was performed to measure the distributions of the apparent diffusion coefficient (ADC) in these two tumor xenograft models, which showed a correlation with tumor growth rates and doubling times during each passage. The distributions of the ADC values were also correlated with expression of Ki67, a biomarker of cell proliferation, and hypoxia inducible factor (HIF)-1α and vascular endothelial growth factor receptor-2 (VEGFR2), which are essential proteins involved in regulating aerobic glycolysis and angiogenesis that support tumor cell proliferation. Although phosphatase and tensin homolog (PTEN) levels were different between the two xenograft models, AKT levels did not differ nor did they correlate with tumor growth. This last result demonstrates the complexity of signaling protein pathways and the difficulty in interpreting the effects of protein expression on tumor cell proliferation. In contrast, DW-MRI may be a more direct assessment of tumor growth and cancer cell proliferation.

4D flow imaging with MRI

PubMed Central

Stankovic, Zoran; Allen, Bradley D.; Garcia, Julio; Jarvis, Kelly B.

2014-01-01

Magnetic resonance imaging (MRI) has become an important tool for the clinical evaluation of patients with cardiovascular disease. Since its introduction in the late 1980s, 2-dimensional phase contrast MRI (2D PC-MRI) has become a routine part of standard-of-care cardiac MRI for the assessment of regional blood flow in the heart and great vessels. More recently, time-resolved PC-MRI with velocity encoding along all three flow directions and three-dimensional (3D) anatomic coverage (also termed ‘4D flow MRI’) has been developed and applied for the evaluation of cardiovascular hemodynamics in multiple regions of the human body. 4D flow MRI allows for the comprehensive evaluation of complex blood flow patterns by 3D blood flow visualization and flexible retrospective quantification of flow parameters. Recent technical developments, including the utilization of advanced parallel imaging techniques such as k-t GRAPPA, have resulted in reasonable overall scan times, e.g., 8-12 minutes for 4D flow MRI of the aorta and 10-20 minutes for whole heart coverage. As a result, the application of 4D flow MRI in a clinical setting has become more feasible, as documented by an increased number of recent reports on the utility of the technique for the assessment of cardiac and vascular hemodynamics in patient studies. A number of studies have demonstrated the potential of 4D flow MRI to provide an improved assessment of hemodynamics which might aid in the diagnosis and therapeutic management of cardiovascular diseases. The purpose of this review is to describe the methods used for 4D flow MRI acquisition, post-processing and data analysis. In addition, the article provides an overview of the clinical applications of 4D flow MRI and includes a review of applications in the heart, thoracic aorta and hepatic system. PMID:24834414

Two-stage decompositions for the analysis of functional connectivity for fMRI with application to Alzheimer’s disease risk

PubMed Central

Caffo, Brian S.; Crainiceanu, Ciprian M.; Verduzco, Guillermo; Joel, Suresh; Mostofsky, Stewart H.; Bassett, Susan Spear; Pekar, James J.

2010-01-01

Functional connectivity is the study of correlations in measured neurophysiological signals. Altered functional connectivity has been shown to be associated with a variety of cognitive and memory impairments and dysfunction, including Alzheimer’s disease. In this manuscript we use a two-stage application of the singular value decomposition to obtain data driven population-level measures of functional connectivity in functional magnetic resonance imaging (fMRI). The method is computationally simple and amenable to high dimensional fMRI data with large numbers of subjects. Simulation studies suggest the ability of the decomposition methods to recover population brain networks and their associated loadings. We further demonstrate the utility of these decompositions in a functional logistic regression model. The method is applied to a novel fMRI study of Alzheimer’s disease risk under a verbal paired associates task. We found a indication of alternative connectivity in clinically asymptomatic at-risk subjects when compared to controls, that was not significant in the light of multiple comparisons adjustment. The relevant brain network loads primarily on the temporal lobe and overlaps significantly with the olfactory areas and temporal poles. PMID:20227508

Two-stage decompositions for the analysis of functional connectivity for fMRI with application to Alzheimer's disease risk.

PubMed

Caffo, Brian S; Crainiceanu, Ciprian M; Verduzco, Guillermo; Joel, Suresh; Mostofsky, Stewart H; Bassett, Susan Spear; Pekar, James J

2010-07-01

Functional connectivity is the study of correlations in measured neurophysiological signals. Altered functional connectivity has been shown to be associated with a variety of cognitive and memory impairments and dysfunction, including Alzheimer's disease. In this manuscript we use a two-stage application of the singular value decomposition to obtain data driven population-level measures of functional connectivity in functional magnetic resonance imaging (fMRI). The method is computationally simple and amenable to high dimensional fMRI data with large numbers of subjects. Simulation studies suggest the ability of the decomposition methods to recover population brain networks and their associated loadings. We further demonstrate the utility of these decompositions in a functional logistic regression model. The method is applied to a novel fMRI study of Alzheimer's disease risk under a verbal paired associates task. We found an indication of alternative connectivity in clinically asymptomatic at-risk subjects when compared to controls, which was not significant in the light of multiple comparisons adjustment. The relevant brain network loads primarily on the temporal lobe and overlaps significantly with the olfactory areas and temporal poles. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Network diffusion accurately models the relationship between structural and functional brain connectivity networks

PubMed Central

Abdelnour, Farras; Voss, Henning U.; Raj, Ashish

2014-01-01

The relationship between anatomic connectivity of large-scale brain networks and their functional connectivity is of immense importance and an area of active research. Previous attempts have required complex simulations which model the dynamics of each cortical region, and explore the coupling between regions as derived by anatomic connections. While much insight is gained from these non-linear simulations, they can be computationally taxing tools for predicting functional from anatomic connectivities. Little attention has been paid to linear models. Here we show that a properly designed linear model appears to be superior to previous non-linear approaches in capturing the brain’s long-range second order correlation structure that governs the relationship between anatomic and functional connectivities. We derive a linear network of brain dynamics based on graph diffusion, whereby the diffusing quantity undergoes a random walk on a graph. We test our model using subjects who underwent diffusion MRI and resting state fMRI. The network diffusion model applied to the structural networks largely predicts the correlation structures derived from their fMRI data, to a greater extent than other approaches. The utility of the proposed approach is that it can routinely be used to infer functional correlation from anatomic connectivity. And since it is linear, anatomic connectivity can also be inferred from functional data. The success of our model confirms the linearity of ensemble average signals in the brain, and implies that their long-range correlation structure may percolate within the brain via purely mechanistic processes enacted on its structural connectivity pathways. PMID:24384152

Concurrent segmentation of the prostate on MRI and CT via linked statistical shape models for radiotherapy planning

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

Chowdhury, Najeeb; Toth, Robert; Chappelow, Jonathan

2012-04-15

Purpose: Prostate gland segmentation is a critical step in prostate radiotherapy planning, where dose plans are typically formulated on CT. Pretreatment MRI is now beginning to be acquired at several medical centers. Delineation of the prostate on MRI is acknowledged as being significantly simpler to perform, compared to delineation on CT. In this work, the authors present a novel framework for building a linked statistical shape model (LSSM), a statistical shape model (SSM) that links the shape variation of a structure of interest (SOI) across multiple imaging modalities. This framework is particularly relevant in scenarios where accurate boundary delineations ofmore » the SOI on one of the modalities may not be readily available, or difficult to obtain, for training a SSM. In this work the authors apply the LSSM in the context of multimodal prostate segmentation for radiotherapy planning, where the prostate is concurrently segmented on MRI and CT. Methods: The framework comprises a number of logically connected steps. The first step utilizes multimodal registration of MRI and CT to map 2D boundary delineations of the prostate from MRI onto corresponding CT images, for a set of training studies. Hence, the scheme obviates the need for expert delineations of the gland on CT for explicitly constructing a SSM for prostate segmentation on CT. The delineations of the prostate gland on MRI and CT allows for 3D reconstruction of the prostate shape which facilitates the building of the LSSM. In order to perform concurrent prostate MRI and CT segmentation using the LSSM, the authors employ a region-based level set approach where the authors deform the evolving prostate boundary to simultaneously fit to MRI and CT images in which voxels are classified to be either part of the prostate or outside the prostate. The classification is facilitated by using a combination of MRI-CT probabilistic spatial atlases and a random forest classifier, driven by gradient and Haar features. Results: The authors acquire a total of 20 MRI-CT patient studies and use the leave-one-out strategy to train and evaluate four different LSSMs. First, a fusion-based LSSM (fLSSM) is built using expert ground truth delineations of the prostate on MRI alone, where the ground truth for the gland on CT is obtained via coregistration of the corresponding MRI and CT slices. The authors compare the fLSSM against another LSSM (xLSSM), where expert delineations of the gland on both MRI and CT are employed in the model building; xLSSM representing the idealized LSSM. The authors also compare the fLSSM against an exclusive CT-based SSM (ctSSM), built from expert delineations of the gland on CT alone. In addition, two LSSMs trained using trainee delineations (tLSSM) on CT are compared with the fLSSM. The results indicate that the xLSSM, tLSSMs, and the fLSSM perform equivalently, all of them out-performing the ctSSM. Conclusions: The fLSSM provides an accurate alternative to SSMs that require careful expert delineations of the SOI that may be difficult or laborious to obtain. Additionally, the fLSSM has the added benefit of providing concurrent segmentations of the SOI on multiple imaging modalities.« less

Longitudinal Brain Magnetic Resonance Imaging CO2 Stress Testing in Individual Adolescent Sports-Related Concussion Patients: A Pilot Study.

PubMed

Mutch, W Alan C; Ellis, Michael J; Ryner, Lawrence N; Morissette, Marc P; Pries, Philip J; Dufault, Brenden; Essig, Marco; Mikulis, David J; Duffin, James; Fisher, Joseph A

2016-01-01

Advanced neuroimaging studies in concussion have been limited to detecting group differences between concussion patients and healthy controls. In this small pilot study, we used brain magnetic resonance imaging (MRI) CO2 stress testing to longitudinally assess cerebrovascular responsiveness (CVR) in individual sports-related concussion (SRC) patients. Six SRC patients (three males and three females; mean age = 15.7, range = 15-17 years) underwent longitudinal brain MRI CO2 stress testing using blood oxygen level-dependent (BOLD) MRI and model-based prospective end-tidal CO2 targeting under isoxic conditions. First-level and second-level comparisons were undertaken using statistical parametric mapping (SPM) to score the scans and compare them to an atlas of 24 healthy control subjects. All tests were well tolerated and without any serious adverse events. Anatomical MRI was normal in all study participants. The CO2 stimulus was consistent between the SRC patients and control subjects and within SRC patients across the longitudinal study. Individual SRC patients demonstrated both quantitative and qualitative patient-specific alterations in CVR (p < 0.005) that correlated strongly with clinical findings, and that persisted beyond clinical recovery. Standardized brain MRI CO2 stress testing is capable of providing a longitudinal assessment of CVR in individual SRC patients. Consequently, larger prospective studies are needed to examine the utility of brain MRI CO2 stress testing as a clinical tool to help guide the evaluation, classification, and longitudinal management of SRC patients.

Delineating potential epileptogenic areas utilizing resting functional magnetic resonance imaging (fMRI) in epilepsy patients.

PubMed

Pizarro, Ricardo; Nair, Veena; Meier, Timothy; Holdsworth, Ryan; Tunnell, Evelyn; Rutecki, Paul; Sillay, Karl; Meyerand, Mary E; Prabhakaran, Vivek

2016-08-01

Seizure localization includes neuroimaging like electroencephalogram, and magnetic resonance imaging (MRI) with limited ability to characterize the epileptogenic network. Temporal clustering analysis (TCA) characterizes epileptogenic network congruent with interictal epileptiform discharges by clustering together voxels with transient signals. We generated epileptogenic areas for 12 of 13 epilepsy patients with TCA, congruent with different areas of seizure onset. Resting functional MRI (fMRI) scans are noninvasive, and can be acquired quickly, in patients with different levels of severity and function. Analyzing resting fMRI data using TCA is quick and can complement clinical methods to characterize the epileptogenic network.

MR guided breast interventions: role in biopsy targeting and lumpectomies

PubMed Central

Jagadeesan, Jayender; Richman, Danielle M; Kacher, Daniel F

2015-01-01

Synopsis Contrast enhanced breast MRI is increasingly being used to diagnose breast cancer and to perform biopsy procedures. The American Cancer Society has advised women at high risk for breast cancer to have breast MRI screening as an adjunct to screening mammography. This article places special emphasis on biopsy and operative planning involving MRI and reviews utility of breast MRI in monitoring response to neoadjuvant chemotherapy. We describe peer-reviewed data on currently accepted MR-guided therapeutic methods for addressing benign and malignant breast diseases, including intraoperative imaging. PMID:26499274

Tau and Beta-Amyloid Deposition, Micro-Hemorrhage and Brain Function after Traumatic Brain Injury in War Veterans

DTIC Science & Technology

2016-10-01

tau PET imaging and 7T- MRI to the Australian Imaging Biomarkers and Lifestyle - Veterans study (AIBL-VETS) of post-traumatic stress disorder and...focal and widespread changes in white matter integrity. 4. 7T- MRI will reveal more extensive microhemorrhage than seen on 3T- MRI and this will relate...injury in war veterans. 6 | P a g e 1. Introduction The project will utilize tau, amyloid and FDG PET imaging, and MRI as well as clinical and

Ranking and averaging independent component analysis by reproducibility (RAICAR).

PubMed

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

2008-06-01

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

TWave: High-Order Analysis of Functional MRI

PubMed Central

Barnathan, Michael; Megalooikonomou, Vasileios; Faloutsos, Christos; Faro, Scott; Mohamed, Feroze B.

2011-01-01

The traditional approach to functional image analysis models images as matrices of raw voxel intensity values. Although such a representation is widely utilized and heavily entrenched both within neuroimaging and in the wider data mining community, the strong interactions among space, time, and categorical modes such as subject and experimental task inherent in functional imaging yield a dataset with “high-order” structure, which matrix models are incapable of exploiting. Reasoning across all of these modes of data concurrently requires a high-order model capable of representing relationships between all modes of the data in tandem. We thus propose to model functional MRI data using tensors, which are high-order generalizations of matrices equivalent to multidimensional arrays or data cubes. However, several unique challenges exist in the high-order analysis of functional medical data: naïve tensor models are incapable of exploiting spatiotemporal locality patterns, standard tensor analysis techniques exhibit poor efficiency, and mixtures of numeric and categorical modes of data are very often present in neuroimaging experiments. Formulating the problem of image clustering as a form of Latent Semantic Analysis and using the WaveCluster algorithm as a baseline, we propose a comprehensive hybrid tensor and wavelet framework for clustering, concept discovery, and compression of functional medical images which successfully addresses these challenges. Our approach reduced runtime and dataset size on a 9.3 GB finger opposition motor task fMRI dataset by up to 98% while exhibiting improved spatiotemporal coherence relative to standard tensor, wavelet, and voxel-based approaches. Our clustering technique was capable of automatically differentiating between the frontal areas of the brain responsible for task-related habituation and the motor regions responsible for executing the motor task, in contrast to a widely used fMRI analysis program, SPM, which only detected the latter region. Furthermore, our approach discovered latent concepts suggestive of subject handedness nearly 100x faster than standard approaches. These results suggest that a high-order model is an integral component to accurate scalable functional neuroimaging. PMID:21729758

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

Registering and Analyzing Rat fMRI Data in the Stereotaxic Framework by Exploiting Intrinsic Anatomical Features

PubMed Central

Lu, Hanbing; Scholl, Clara A.; Zuo, Yantao; Demny, Steven; Rea, William; Stein, Elliot A.; Yang, Yihong

2009-01-01

The value of analyzing neuroimaging data on a group level has been well established in human studies. However, there is no standard procedure for registering and analyzing fMRI data into common space in rodent functional magnetic resonance imaging (fMRI) studies. An approach for performing rat imaging data analysis in the stereotaxic framework is presented. This method is rooted in the biological observation that the skull shape and size of rat brain are essentially the same as long as their weights are within certain range. Registration is performed using rigid-body transformations without scaling or shearing, preserving the unique properties of the stable shape and size inherent in rat brain structure. Also, it does not require brain tissue masking, and is not biased towards surface coil sensitivity profile. A standard rat brain atlas is used to facilitate the identification of activated areas in common space, allowing accurate region-of-interest (ROI) analysis. This technique is evaluated from a group of rats (n = 11) undergoing routine MRI scans; the registration accuracy is estimated to be within 400 μm. The analysis of fMRI data acquired with an electrical forepaw stimulation model demonstrates the utility of this technique. The method is implemented within the AFNI framework and can be readily extended to other studies. PMID:19608368

Multiparametric Breast MRI of Breast Cancer

PubMed Central

Rahbar, Habib; Partridge, Savannah C.

2015-01-01

Synopsis Breast MRI has increased in popularity over the past two decades due to evidence for its high sensitivity for cancer detection. Current clinical MRI approaches rely on the use of a dynamic contrast enhanced (DCE-MRI) acquisition that facilitates morphologic and semi-quantitative kinetic assessments of breast lesions. The use of more functional and quantitative parameters, such as pharmacokinetic features from high temporal resolution DCE-MRI, apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) on diffusion weighted MRI, and choline concentrations on MR spectroscopy, hold promise to broaden the utility of MRI and improve its specificity. However, due to wide variations in approach among centers for measuring these parameters and the considerable technical challenges, robust multicenter data supporting their routine use is not yet available, limiting current applications of many of these tools to research purposes. PMID:26613883

The utility of high-resolution intraoperative MRI in endoscopic transsphenoidal surgery for pituitary macroadenomas: early experience in the Advanced Multimodality Image Guided Operating suite

PubMed Central

Zaidi, Hasan A.; De Los Reyes, Kenneth; Barkhoudarian, Garni; Litvack, Zachary N.; Bi, Wenya Linda; Rincon-Torroella, Jordina; Mukundan, Srinivasan; Dunn, Ian F.; Laws, Edward R.

2016-01-01

Objective Endoscopic skull base surgery has become increasingly popular among the skull base surgery community, with improved illumination and angled visualization potentially improving tumor resection rates. Intraoperative MRI (iMRI) is used to detect residual disease during the course of the resection. This study is an investigation of the utility of 3-T iMRI in combination with transnasal endoscopy with regard to gross-total resection (GTR) of pituitary macroadenomas. Methods The authors retrospectively reviewed all endoscopic transsphenoidal operations performed in the Advanced Multimodality Image Guided Operating (AMIGO) suite from November 2011 to December 2014. Inclusion criteria were patients harboring presumed pituitary macroadenomas with optic nerve or chiasmal compression and visual loss, operated on by a single surgeon. Results Of the 27 patients who underwent transsphenoidal resection in the AMIGO suite, 20 patients met the inclusion criteria. The endoscope alone, without the use of iMRI, would have correctly predicted 13 (65%) of 20 cases. Gross-total resection was achieved in 12 patients (60%) prior to MRI. Intraoperative MRI helped convert 1 STR and 4 NTRs to GTRs, increasing the number of GTRs from 12 (60%) to 16 (80%). Conclusions Despite advances in visualization provided by the endoscope, the incidence of residual disease can potentially place the patient at risk for additional surgery. The authors found that iMRI can be useful in detecting unexpected residual tumor. The cost-effectiveness of this tool is yet to be determined. PMID:26926058

Method for Controlled Mitochondrial Perturbation during Phosphorus MRS in Children

PubMed Central

Cree-Green, Melanie; Newcomer, Bradley R.; Brown, Mark; Hull, Amber; West, Amy D.; Singel, Debra; Reusch, Jane E.B.; McFann, Kim; Regensteiner, Judith G.; Nadeau, Kristen J.

2014-01-01

Introduction Insulin resistance (IR) is increasingly prevalent in children, and may be related to muscle mitochondrial dysfunction, necessitating development of mitochondrial assessment techniques. Recent studies used 31Phosphorus magnetic resonance spectroscopy (31P-MRS), a non-invasive technique appealing for clinical research. 31P-MRS requires exercise at a precise percentage of maximum volitional contraction (MVC). MVC measurement in children, particularly with disease, is problematic due to variability in perception of effort and motivation. We therefore developed a method to predict MVC, using maximal calf muscle cross-sectional area (MCSA) to assure controlled and reproducible muscle metabolic perturbations. Methods Data were collected from 66 sedentary 12–20 year-olds. Plantar flexion-volitional MVC was assessed using a MRI-compatible exercise treadle device. MCSA of the calf muscles were measured from MRI images. Data from the first 26 participants were utilized to model the relationship between MVC and MCSA (predicted MVC = 24.763+0.0047*MCSA). This model was then applied to the subsequent 40 participants. Results Volitional vs. model-predicted mean MVC was 43.9±0.8 kg vs. 44.2±1.81 (P=0.90). 31P-MRS results when predicted and volitional MVC were similar showed expected changes during volitional MVC-based exercise. In contrast, volitional MVC was markedly lower than predicted in 4 participants, and produced minimal metabolic perturbation. Upon repeat testing, these individuals could perform their predicted MVC with coaching, which produced expected metabolic perturbations. Conclusions Compared to using MVC testing alone, utilizing MRI to predict muscle strength allows for a more accurate and standardized 31P-MRS protocol during exercise in children. This method overcomes a major obstacle in assessing mitochondrial function in youth. These studies have importance as we seek to determine the role of mitochondrial function in youth with IR and diabetes and response to interventions. PMID:24576856

Fetal tracheolaryngeal airway obstruction: prenatal evaluation by sonography and MRI

PubMed Central

Courtier, Jesse; Poder, Liina; Wang, Zhen J.; Westphalen, Antonio C.; Yeh, Benjamin M.

2010-01-01

We reviewed the sonographic and MRI findings of tracheolaryngeal obstruction in the fetus. Conditions that can cause tracheolaryngeal obstruction include extrinsic causes such as lymphatic malformation, cervical teratoma and vascular rings and intrinsic causes such as congenital high airway obstruction syndrome (CHAOS). Accurate distinction of these conditions by sonography or MRI can help facilitate parental counseling and management, including the decision to utilize the ex utero intrapartum treatment (EXIT) procedure. PMID:20737145

The clinical utility and diagnostic performance of magnetic resonance imaging for identification of early and advanced knee osteoarthritis: a systematic review.

PubMed

Quatman, Carmen E; Hettrich, Carolyn M; Schmitt, Laura C; Spindler, Kurt P

2011-07-01

Current diagnostic strategies for detection of structural articular cartilage abnormalities, the earliest structural signs of osteoarthritis, often do not capture the condition until it is too far advanced for the most potential benefit of noninvasive interventions. To systematically review the literature relative to the following questions: (1) Is magnetic resonance imaging (MRI) a valid, sensitive, specific, accurate, and reliable instrument to identify knee articular cartilage abnormalities compared with arthroscopy? (2) Is MRI a sensitive tool that can be utilized to identify early cartilage degeneration? Systematic review. A systematic search was performed in November 2010 using PubMed MEDLINE (from 1966), CINAHL (from 1982), SPORTDiscus (from 1985), SCOPUS (from 1996), and EMBASE (from 1974) databases. Fourteen level I and 13 level II studies were identified that met inclusion criteria and provided information related to diagnostic performance of MRI compared with arthroscopic evaluation. The diagnostic performance of MRI demonstrated a large range of sensitivities, specificities, and accuracies. The sensitivity for identifying articular cartilage abnormalities in the knee joint was reported between 26% and 96%. Specificity and accuracy were reported between 50% and 100% and between 49% and 94%, respectively. The sensitivity, specificity, and accuracy for identifying early osteoarthritis were reported between 0% and 86%, 48% and 95%, and 5% and 94%, respectively. As a result of inconsistencies between imaging techniques and methodological shortcomings of many of the studies, a meta-analysis was not performed, and it was difficult to fully synthesize the information to state firm conclusions about the diagnostic performance of MRI. There is evidence in some MRI protocols that MRI is a relatively valid, sensitive, specific, accurate, and reliable clinical tool for identifying articular cartilage degeneration. Because of heterogeneity of MRI sequences, it is not possible to make definitive conclusions regarding its global clinical utility for guiding diagnosis and treatment strategies. Traumatic sports injuries to the knee may be significant precursor events to early onset of posttraumatic osteoarthritis. Magnetic resonance imaging may aid in early identification of structural injuries to articular cartilage as evidenced by articular cartilage degeneration grading.

Positron emission tomography (PET) and magnetic resonance imaging (MRI) for the assessment of axillary lymph node metastases in early breast cancer: systematic review and economic evaluation.

PubMed

Cooper, K L; Meng, Y; Harnan, S; Ward, S E; Fitzgerald, P; Papaioannou, D; Wyld, L; Ingram, C; Wilkinson, I D; Lorenz, E

2011-01-01

Breast cancer is the most common type of cancer in women. Evaluation of axillary lymph node metastases is important for breast cancer staging and treatment planning. To evaluate the diagnostic accuracy, cost-effectiveness and effect on patient outcomes of positron emission tomography (PET), with or without computed tomography (CT), and magnetic resonance imaging (MRI) in the evaluation of axillary lymph node metastases in patients with newly diagnosed early-stage breast cancer. A systematic review of literature and an economic evaluation were carried out. Key databases (including MEDLINE, EMBASE and nine others) plus research registers and conference proceedings were searched for relevant studies up to April 2009. A decision-analytical model was developed to determine cost-effectiveness in the UK. One reviewer assessed titles and abstracts of studies identified by the search strategy, obtained the full text of relevant papers and screened them against inclusion criteria. Data from included studies were extracted by one reviewer using a standardised data extraction form and checked by a second reviewer. Discrepancies were resolved by discussion. Quality of included studies was assessed using the quality assessment of diagnostic accuracy studies (QUADAS) checklist, applied by one reviewer and checked by a second. Forty-five citations relating to 35 studies were included in the clinical effectiveness review: 26 studies of PET and nine studies of MRI. Two studies were included in the cost-effectiveness review: one of PET and one of MRI. Of the seven studies evaluating PET/CT (n = 862), the mean sensitivity was 56% [95% confidence interval (CI) 44% to 67%] and mean specificity 96% (95% CI 90% to 99%). Of the 19 studies evaluating PET only (n = 1729), the mean sensitivity was 66% (95% CI 50% to 79%) and mean specificity 93% (95% CI 89% to 96%). PET performed less well for small metastases; the mean sensitivity was 11% (95% CI 5% to 22%) for micrometastases (≤ 2 mm; five studies; n = 63), and 57% (95% CI 47% to 66%) for macrometastases (> 2 mm; four studies; n = 111). The smallest metastatic nodes detected by PET measured 3 mm, while PET failed to detect some nodes measuring > 15 mm. Studies in which all patients were clinically node negative showed a trend towards lower sensitivity of PET compared with studies with a mixed population. Across five studies evaluating ultrasmall super-paramagnetic iron oxide (USPIO)-enhanced MRI (n = 93), the mean sensitivity was 98% (95% CI 61% to 100%) and mean specificity 96% (95% CI 72% to 100%). Across three studies of gadolinium-enhanced MRI (n = 187), the mean sensitivity was 88% (95% CI 78% to 94%) and mean specificity 73% (95% CI 63% to 81%). In the single study of in vivo proton magnetic resonance spectroscopy (n = 27), the sensitivity was 65% (95% CI 38% to 86%) and specificity 100% (95% CI 69% to 100%). USPIO-enhanced MRI showed a trend towards higher sensitivity and specificity than gadolinium-enhanced MRI. Results of the decision modelling suggest that the MRI replacement strategy is the most cost-effective strategy and dominates the baseline 4-node sampling (4-NS) and sentinel lymph node biopsy (SLNB) strategies in most sensitivity analyses undertaken. The PET replacement strategy is not as robust as the MRI replacement strategy, as its cost-effectiveness is significantly affected by the utility decrement for lymphoedema and the probability of relapse for false-negative (FN) patients. No included studies directly compared PET and MRI. Studies demonstrated that PET and MRI have lower sensitivity and specificity than SLNB and 4-NS but are associated with fewer adverse events. Included studies indicated a significantly higher mean sensitivity for MRI than for PET, with USPIO-enhanced MRI providing the highest sensitivity. However, sensitivity and specificity of PET and MRI varied widely between studies, and MRI studies were relatively small and varied in their methods; therefore, results should be interpreted with caution. Decision modelling based on these results suggests that the most cost-effective strategy may be MRI rather than SLNB or 4-NS. This strategy reduces costs and increases quality-adjusted life-years (QALYs) because there are fewer adverse events for the majority of patients. However, this strategy leads to more FN cases at higher risk of cancer recurrence and more false- positive (FP) cases who would undergo unnecessary axillary lymph node dissection. Adding MRI prior to SLNB or 4-NS has little effect on QALYs, though this analysis is limited by lack of available data. Future research should include large, well-conducted studies of MRI, particularly using USPIO; data on the long-term impacts of lymphoedema on cost and patient utility; studies of the comparative effectiveness and cost-effectiveness of SLNB and 4-NS; and more robust UK cost data for 4-NS and SLNB as well as the cost of MRI and PET techniques. This study was funded by the Health Technology Assessment programme of the National Institute of Health Research.

MRI to assess renal structure and function.

PubMed

Artunc, Ferruh; Rossi, Cristina; Boss, Andreas

2011-11-01

In addition to excellent anatomical depiction, MRI techniques have expanded to study functional aspects of renal physiology, such as renal perfusion, glomerular filtration rate (GFR) or tissue oxygenation. This review will focus on current developments with an emphasis on clinical applicability. The method of GFR determination is largely heterogeneous and still has weaknesses. However, the technique of employing liver disappearance curves has been shown to be accurate in healthy persons and patients with chronic kidney disease. In potential kidney donors, complete evaluation of kidney anatomy and function can be accomplished in a single-stop investigation. Techniques without contrast media can be utilized to measure renal tissue oxygenation (blood oxygen level-dependent MRI) or perfusion (arterial spin labeling) and could aid in the diagnosis and treatment of ischemic renal diseases, such as renal artery stenosis. Diffusion imaging techniques may provide information on spatially restricted water diffusion and tumor cellularity. Functional MRI opens new horizons in studying renal physiology and pathophysiology in vivo. Although extensively utilized in research, labor-intensive postprocessing and lack of standardization currently limit the clinical applicability of functional MRI. Further studies are necessary to evaluate the clinical value of functional magnetic resonance techniques for early discovery and characterization of kidney disease.

Comparison of 4D Phase-Contrast MRI Flow Measurements to Computational Fluid Dynamics Simulations of Cerebrospinal Fluid Motion in the Cervical Spine

PubMed Central

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

2012-01-01

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

Lung magnetic resonance imaging for pneumonia in children.

PubMed

Liszewski, Mark C; Görkem, Süreyya; Sodhi, Kushaljit S; Lee, Edward Y

2017-10-01

Technical factors have historically limited the role of MRI in the evaluation of pneumonia in children in routine clinical practice. As imaging technology has advanced, recent studies utilizing practical MR imaging protocols have shown MRI to be an accurate potential alternative to CT for the evaluation of pneumonia and its complications. This article provides up-to-date MR imaging techniques that can be implemented in most radiology departments to evaluate pneumonia in children. Imaging findings in pneumonia on MRI are also reviewed. In addition, the current literature describing the diagnostic performance of MRI for pneumonia is discussed. Furthermore, potential risks and limitations of MRI for the evaluation of pneumonia in children are described.

A novel electron accelerator for MRI-Linac radiotherapy.

PubMed

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

2016-03-01

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

A novel electron accelerator for MRI-Linac radiotherapy

PubMed Central

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

2016-01-01

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

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

Live-cell MRI with xenon hyper-CEST biosensors targeted to metabolically labeled cell-surface glycans.

PubMed

Witte, Christopher; Martos, Vera; Rose, Honor May; Reinke, Stefan; Klippel, Stefan; Schröder, Leif; Hackenberger, Christian P R

2015-02-23

The targeting of metabolically labeled glycans with conventional MRI contrast agents has proved elusive. In this work, which further expands the utility of xenon Hyper-CEST biosensors in cell experiments, we present the first successful molecular imaging of such glycans using MRI. Xenon Hyper-CEST biosensors are a novel class of MRI contrast agents with very high sensitivity. We designed a multimodal biosensor for both fluorescent and xenon MRI detection that is targeted to metabolically labeled sialic acid through bioorthogonal chemistry. Through the use of a state of the art live-cell bioreactor, it was demonstrated that xenon MRI biosensors can be used to image cell-surface glycans at nanomolar concentrations. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

On estimating intraventricular hemodynamic forces from endocardial dynamics: A comparative study with 4D flow MRI.

PubMed

Pedrizzetti, Gianni; Arvidsson, Per M; Töger, Johannes; Borgquist, Rasmus; Domenichini, Federico; Arheden, Håkan; Heiberg, Einar

2017-07-26

Intraventricular pressure gradients or hemodynamic forces, which are their global measure integrated over the left ventricular volume, have a fundamental importance in ventricular function. They may help revealing a sub-optimal cardiac function that is not evident in terms of tissue motion, which is naturally heterogeneous and variable, and can influence cardiac adaptation. However, hemodynamic forces are not utilized in clinical cardiology due to the unavailability of simple non-invasive measurement tools. Hemodynamic forces depend on the intraventricular flow; nevertheless, most of them are imputable to the dynamics of the endocardial flow boundary and to the exchange of momentum across the mitral and aortic orifices. In this study, we introduce a simplified model based on first principles of fluid dynamics that allows estimating hemodynamic forces without knowing the velocity field inside the LV. The model is validated with 3D phase-contrast MRI (known as 4D flow MRI) in 15 subjects, (5 healthy and 10 patients) using the endocardial surface reconstructed from the three standard long-axis projections. Results demonstrate that the model provides consistent estimates for the base-apex component (mean correlation coefficient r=0.77 for instantaneous values and r=0.88 for root mean square) and good estimates of the inferolateral-anteroseptal component (r=0.50 and 0.84, respectively). The present method represents a potential integration to the existing ones quantifying endocardial deformation in MRI and echocardiography to add a physics-based estimation of the corresponding hemodynamic forces. These could help the clinician to early detect sub-clinical diseases and differentiate between different cardiac dysfunctional states. Copyright © 2017 Elsevier Ltd. All rights reserved.

A step-wise approach for analysis of the mouse embryonic heart using 17.6 Tesla MRI

PubMed Central

Gabbay-Benziv, Rinat; Reece, E. Albert; Wang, Fang; Bar-Shir, Amnon; Harman, Chris; Turan, Ozhan M.; Yang, Peixin; Turan, Sifa

2018-01-01

Background The mouse embryo is ideal for studying human cardiac development. However, laboratory discoveries do not easily translate into clinical findings partially because of histological diagnostic techniques that induce artifacts and lack standardization. Aim To present a step-wise approach using 17.6 T MRI, for evaluation of mice embryonic heart and accurate identification of congenital heart defects. Subjects 17.5-embryonic days embryos from low-risk (non-diabetic) and high-risk (diabetic) model dams. Study design Embryos were imaged using 17.6 Tesla MRI. Three-dimensional volumes were analyzed using ImageJ software. Outcome measures Embryonic hearts were evaluated utilizing anatomic landmarks to locate the four-chamber view, the left- and right-outflow tracts, and the arrangement of the great arteries. Inter- and intra-observer agreement were calculated using kappa scores by comparing two researchers’ evaluations independently analyzing all hearts, blinded to the model, on three different, timed occasions. Each evaluated 16 imaging volumes of 16 embryos: 4 embryos from normal dams, and 12 embryos from diabetic dams. Results Inter-observer agreement and reproducibility were 0.779 (95% CI 0.653–0.905) and 0.763 (95% CI 0.605–0.921), respectively. Embryonic hearts were structurally normal in 4/4 and 7/12 embryos from normal and diabetic dams, respectively. Five embryos from diabetic dams had defects: ventricular septal defects (n = 2), transposition of great arteries (n = 2) and Tetralogy of Fallot (n = 1). Both researchers identified all cardiac lesions. Conclusion A step-wise approach for analysis of MRI-derived 3D imaging provides reproducible detailed cardiac evaluation of normal and abnormal mice embryonic hearts. This approach can accurately reveal cardiac structure and, thus, increases the yield of animal model in congenital heart defect research. PMID:27569369

Edge Sharpness Assessment by Parametric Modeling: Application to Magnetic Resonance Imaging.

PubMed

Ahmad, R; Ding, Y; Simonetti, O P

2015-05-01

In biomedical imaging, edge sharpness is an important yet often overlooked image quality metric. In this work, a semi-automatic method to quantify edge sharpness in the presence of significant noise is presented with application to magnetic resonance imaging (MRI). The method is based on parametric modeling of image edges. First, an edge map is automatically generated and one or more edges-of-interest (EOI) are manually selected using graphical user interface. Multiple exclusion criteria are then enforced to eliminate edge pixels that are potentially not suitable for sharpness assessment. Second, at each pixel of the EOI, an image intensity profile is read along a small line segment that runs locally normal to the EOI. Third, the profiles corresponding to all EOI pixels are individually fitted with a sigmoid function characterized by four parameters, including one that represents edge sharpness. Last, the distribution of the sharpness parameter is used to quantify edge sharpness. For validation, the method is applied to simulated data as well as MRI data from both phantom imaging and cine imaging experiments. This method allows for fast, quantitative evaluation of edge sharpness even in images with poor signal-to-noise ratio. Although the utility of this method is demonstrated for MRI, it can be adapted for other medical imaging applications.

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

Whole body MRI, including diffusion-weighted imaging in follow-up of patients with testicular cancer.

PubMed

Mosavi, Firas; Laurell, Anna; Ahlström, Håkan

2015-11-01

Whole body (WB) magnetic resonance imaging (MRI), including diffusion-weighted imaging (DWI) has become increasingly utilized in cancer imaging, yet the clinical utility of these techniques in follow-up of testicular cancer patients has not been evaluated. The purpose of this study was to evaluate the feasibility of WB MRI with continuous table movement (CTM) technique, including multistep DWI in follow-up of patients with testicular cancer. WB MRI including DWI was performed in follow-up of 71 consecutive patients (median age, 37 years; range 19-84) with histologically confirmed testicular cancer. WB MRI protocol included axial T1-Dixon and T2-BLADE sequences using CTM technique. Furthermore, multi-step DWI was performed using b-value 50 and 1000 s/mm(2). One criterion for feasibility was patient tolerance and satisfactory image quality. Another criterion was the accuracy in detection of any pathological mass, compared to standard of reference. Signal intensity in DWI was used for evaluation of residual mass activity. Clinical, laboratory and imaging follow-up were applied as standard of reference for the evaluation of WB MRI. WB MRI was tolerated in nearly all patients (69/71 patients, 97%) and the image quality was satisfactory. Metal artifacts deteriorated the image quality in six patients, but it did not influence the overall results. No case of clinical relapse was observed during the follow-up time. There was a good agreement between conventional WB MRI and standard of reference in all patients. Three patients showed residual masses and DWI signal was not restricted in these patients. Furthermore, DWI showed abnormally high signal intensity in a normal-sized retroperitoneal lymph node indicating metastasis. The subsequent (18)F-FDG PET/CT could verify the finding. WB MRI with CTM technique including multi-step DWI is feasible in follow-up of patients with testicular cancer. DWI may contribute to important added-value data to conventional MRI sequences regarding the activity of residual masses.

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

Avkshtol, V; Tanny, S; Reddy, K

Purpose: Stereotactic radiation therapy (SRT) provides an excellent alternative to embolization and surgical excision for the management of appropriately selected cerebral arteriovenous malformations (AVMs). The currently accepted standard for delineating AVMs is planar digital subtraction angiography (DSA). DSA can be used to acquire a 3D data set that preserves osseous structures (3D-DA) at the time of the angiography for SRT planning. Magnetic resonance imaging (MRI) provides an alternative noninvasive method of visualizing the AVM nidus with comparable spatial resolution. We utilized 3D-DA and T1 post-contrast MRI data to evaluate the differences in SRT target volumes. Methods: Four patients underwent 3D-DAmore » and high-resolution MRI. 3D T1 post-contrast images were obtained in all three reconstruction planes. A planning CT was fused with MRI and 3D-DA data sets. The AVMs were contoured utilizing one of the image sets at a time. Target volume, centroid, and maximum and minimum dimensions were analyzed for each patient. Results: Targets delineated using post-contrast MRI demonstrated a larger mean volume. AVMs >2 cc were found to have a larger difference between MRI and 3D-DA volumes. Larger AVMs also demonstrated a smaller relative uncertainty in contour centroid position (1 mm). AVM targets <2 cc had smaller absolute differences in volume, but larger differences in contour centroid position (2.5 mm). MRI targets demonstrated a more irregular shape compared to 3D-DA targets. Conclusions: Our preliminary data supports the use of MRI alone to delineate AVM targets >2 cc. The greater centroid stability for AVMs >2 cc ensures accurate target localization during image fusion. The larger MRI target volumes did not result in prohibitively greater volumes of normal brain tissue receiving the prescription dose. The larger centroid instability for AVMs <2 cc precludes the use of MRI alone for target delineation. We recommend incorporating a 3D-DA for these patients.« less

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.

Targeted endomyocardial injections of therapeutic cells using x-ray fused with MRI guidance

NASA Astrophysics Data System (ADS)

Gutiérrez, Luis F.; de Silva, Ranil; McVeigh, Elliot R.; Ozturk, Cengizhan; Lederman, Robert J.

2006-03-01

The utility of X-ray fused with MRI (XFM) using external fiducial markers to perform targeted endomyocardial injections in infarcted hearts of swine was tested. Endomyocardial injections of feridex-labeled mesenchymal stromal cells (Fe-MSC) were performed in the previously infarcted hearts of 12 Yucatan miniswine (33-67 kg). Animals had pre-injection cardiac MRI, XFM-guided endomyocardial injection of Fe-MSC suspension spiked with tissue dye, and post-injection MRI. 24 hours later, after euthanasia, the hearts were excised, sliced and stained with TTC. During the injection procedure, operators were provided with 3D surfaces of endocardium, epicardium, myocardial wall thickness and infarct registered with live XF images to facilitate device navigation and choice of injection location. 130 injections were performed in hearts where diastolic wall thickness ranged from 2.6 to 17.7 mm. Visual inspection of the pattern of dye staining on TTC stained heart slices correlated (r=0.98) with XFM-derived injection locations mapped onto delayed hyperenhancement MRI and the susceptibility artifacts seen on the post-injection T2*-weighted gradient echo MRI. The in vivo target registration error was 3.17+/-2.61 mm (n=64) and 75% of injections were within 4 mm of the predicted location. 3D to 2D registration of XF and MR images using external fiducial markers enables accurate targeted endomyocardial injection in a swine model of myocardial infarction. The present data suggest that the safety and efficacy of this approach for performing targeted endomyocardial delivery should be evaluated further clinically.

MRI-guided prostate focal laser ablation therapy using a mechatronic needle guidance system

NASA Astrophysics Data System (ADS)

Cepek, Jeremy; Lindner, Uri; Ghai, Sangeet; Davidson, Sean R. H.; Trachtenberg, John; Fenster, Aaron

2014-03-01

Focal therapy of localized prostate cancer is receiving increased attention due to its potential for providing effective cancer control in select patients with minimal treatment-related side effects. Magnetic resonance imaging (MRI)-guided focal laser ablation (FLA) therapy is an attractive modality for such an approach. In FLA therapy, accurate placement of laser fibers is critical to ensuring that the full target volume is ablated. In practice, error in needle placement is invariably present due to pre- to intra-procedure image registration error, needle deflection, prostate motion, and variability in interventionalist skill. In addition, some of these sources of error are difficult to control, since the available workspace and patient positions are restricted within a clinical MRI bore. In an attempt to take full advantage of the utility of intraprocedure MRI, while minimizing error in needle placement, we developed an MRI-compatible mechatronic system for guiding needles to the prostate for FLA therapy. The system has been used to place interstitial catheters for MRI-guided FLA therapy in eight subjects in an ongoing Phase I/II clinical trial. Data from these cases has provided quantification of the level of uncertainty in needle placement error. To relate needle placement error to clinical outcome, we developed a model for predicting the probability of achieving complete focal target ablation for a family of parameterized treatment plans. Results from this work have enabled the specification of evidence-based selection criteria for the maximum target size that can be confidently ablated using this technique, and quantify the benefit that may be gained with improvements in needle placement accuracy.

A comparison of early diagnostic utility of Alzheimer disease biomarkers in brain magnetic resonance and cerebrospinal fluid.

PubMed

Monge Argilés, J A; Blanco Cantó, M A; Leiva Salinas, C; Flors, L; Muñoz Ruiz, C; Sánchez Payá, J; Gasparini Berenguer, R; Leiva Santana, C

2014-09-01

The goals of this study were to compare the early diagnostic utility of Alzheimer disease biomarkers in the CSF with those in brain MRI in conditions found in our clinical practice, and to ascertain the diagnostic accuracy of both techniques used together. Between 2008 and 2009, we included 30 patients with mild cognitive impairment (MCI) who were examined using 1.5 Tesla brain MRI and AD biomarker analysis in CSF. MRI studies were evaluated by 2 radiologists according to the Korf́s visual scale. CSF biomarkers were analysed using INNOTEST reagents for Aβ1-42, total-tau and phospho-tau181p. We evaluated clinical changes 2 years after inclusion. By 2 years after inclusion, 15 of the original 30 patients (50%) had developed AD (NINCDS-ADRA criteria). The predictive utility of AD biomarkers in CSF (RR 2.7; 95% CI, 1.1-6.7; P<.01) was greater than that of MRI (RR 1.5; 95% CI 95%, 0.7-3.4; P<.2); using both techniques together yielded a sensitivity and a negative predictive value of 100%. Normal results on both complementary tests ruled out progression to AD (100%) within 2 years of inclusion. Our results show that the diagnostic accuracy of biomarkers in CSF is higher than that of biomarkers in MRI. Combined use of both techniques is highly accurate for either early diagnosis or exclusion of AD in patients with MCI. Copyright © 2013 Sociedad Española de Neurología. Published by Elsevier Espana. All rights reserved.

Magnetic resonance imaging in active surveillance—a modern approach

PubMed Central

Moore, Caroline M.

2018-01-01

In recent years, active surveillance has been increasingly adopted as a conservative management approach to low and sometimes intermediate risk prostate cancer, to avoid or delay treatment until there is evidence of higher risk disease. A number of studies have investigated the role of multiparametric magnetic resonance imaging (mpMRI) in this setting. MpMRI refers to the use of multiple MRI sequences (T2-weighted anatomical and functional imaging which can include diffusion-weighted imaging, dynamic contrast enhanced imaging, spectroscopy). Each of the parameters investigates different aspects of the prostate gland (anatomy, cellularity, vascularity, etc.). In addition to a qualitative assessment, the radiologist can also extrapolate quantitative imaging biomarkers from these sequences, for example the apparent diffusion coefficient from diffusion-weighted imaging. There are many different types of articles (e.g., reviews, commentaries, consensus meetings, etc.) that address the use of mpMRI in men on active surveillance for prostate cancer. In this paper, we compare original articles that investigate the role of the different mpMRI sequences in men on active surveillance for prostate cancer, in order to discuss the relative utility of the different sequences, and combinations of sequences. We searched MEDLINE/PubMed for manuscripts published from inception to 1st December 2017. The search terms used were (prostate cancer or prostate adenocarcinoma or prostatic carcinoma or prostate carcinoma or prostatic adenocarcinoma) and (MRI or NMR or magnetic resonance imaging or mpMRI or multiparametric MRI) and active surveillance. Overall, 425 publications were found. All abstracts were reviewed to identify papers with original data. Twenty-five papers were analysed and summarised. Some papers based their analysis only on one mpMRI sequence, while others assessed two or more. The evidence from this review suggests that qualitative assessments and quantitative data from different mpMRI sequences hold promise in the management of men on active surveillance for prostate cancer. Both qualitative and quantitative approaches should be considered when assessing mpMRI of the prostate. There is a need for robust studies assessing the relative utility of different combinations of sequences in a systematic manner to determine the most efficient use of mpMRI in men on active surveillance. PMID:29594026

A Bayesian spatial model for neuroimaging data based on biologically informed basis functions.

PubMed

Huertas, Ismael; Oldehinkel, Marianne; van Oort, Erik S B; Garcia-Solis, David; Mir, Pablo; Beckmann, Christian F; Marquand, Andre F

2017-11-01

The dominant approach to neuroimaging data analysis employs the voxel as the unit of computation. While convenient, voxels lack biological meaning and their size is arbitrarily determined by the resolution of the image. Here, we propose a multivariate spatial model in which neuroimaging data are characterised as a linearly weighted combination of multiscale basis functions which map onto underlying brain nuclei or networks or nuclei. In this model, the elementary building blocks are derived to reflect the functional anatomy of the brain during the resting state. This model is estimated using a Bayesian framework which accurately quantifies uncertainty and automatically finds the most accurate and parsimonious combination of basis functions describing the data. We demonstrate the utility of this framework by predicting quantitative SPECT images of striatal dopamine function and we compare a variety of basis sets including generic isotropic functions, anatomical representations of the striatum derived from structural MRI, and two different soft functional parcellations of the striatum derived from resting-state fMRI (rfMRI). We found that a combination of ∼50 multiscale functional basis functions accurately represented the striatal dopamine activity, and that functional basis functions derived from an advanced parcellation technique known as Instantaneous Connectivity Parcellation (ICP) provided the most parsimonious models of dopamine function. Importantly, functional basis functions derived from resting fMRI were more accurate than both structural and generic basis sets in representing dopamine function in the striatum for a fixed model order. We demonstrate the translational validity of our framework by constructing classification models for discriminating parkinsonian disorders and their subtypes. Here, we show that ICP approach is the only basis set that performs well across all comparisons and performs better overall than the classical voxel-based approach. This spatial model constitutes an elegant alternative to voxel-based approaches in neuroimaging studies; not only are their atoms biologically informed, they are also adaptive to high resolutions, represent high dimensions efficiently, and capture long-range spatial dependencies, which are important and challenging objectives for neuroimaging data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Magnetic resonance imaging of the brain and spine

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

Atlas, S.W.

This book will be of use to neuroradiologists, neurologists, neurosurgeons, and all other clinicians who interact to discuss the results of MRI in patients with neurologic disease. It is hoped that this book will aid in this interaction by adding insight into the interpretation of scans and by promulgating a common language. Neuroradiologists and others who interpret MRI of the brain and spine will benefit from the detailed discussions concerning the basis of signal intensity derangements, whether on the fundamental level (i.e., physical or biochemical) or at the level of correlations with clinical and neuropathological findings. It is anticipated thatmore » all neuroscience personnel interested in clinical disease states and in neurological research will be able to utilize this text as a starting point and reference for proposed work utilizing MRI.« less

Utility of immediate postoperative hip MRI in developmental hip dysplasia: closed vs. open reduction.

PubMed

Jadhav, Siddharth P; More, Snehal R; Shenava, Vinitha; Zhang, Wei; Kan, J Herman

2018-04-25

Magnetic resonance imaging (MRI) of the hips is being increasingly used to confirm hip reduction after surgery and spica cast placement for developmental dysplasia of the hip (DDH). To review a single institutional experience with post-spica MRI in children undergoing closed or open hip reduction and describe the utility of MRI in directing the need for re-intervention. Seventy-four patients (52 female, 22 male) who underwent post-spica hip MRI over a 6-year period were retrospectively reviewed. One hundred and seven hips were included. Data reviewed included age at intervention, gender, type of intervention performed, MRI findings, the need for re-intervention and the interval between interventions. Gender was compared between the closed and open reduction groups via the Fisher exact test. Age at the first procedure was compared via the Wilcoxon rank test. Rates of re-intervention after closed and open reduction were calculated and the reasons for re-intervention were reviewed. The mean age at the time of the first intervention was 16.4 months (range: 4 to 63 months). Mean age for the closed reduction group was 10.5 months (range: 4-24 months) and for the open reduction group was 23.7 months (range: 5-63 months), which was significant (P-value <0.0001). Of the 52 hips that underwent closed reduction, 16 (31%) needed re-intervention. Of the 55 hips that underwent open reduction, MRI was useful in deciding re-intervention in only 1 (2%). This patient had prior multiple failed closed and open reductions at an outside institute. Post intervention hip spica MRI is useful in determining the need for re-intervention after closed hip reduction, but its role after open reduction is questionable.

The Effect of Study Design Biases on the Diagnostic Accuracy of Magnetic Resonance Imaging to Detect Silicone Breast Implant Ruptures: A Meta-Analysis

PubMed Central

Song, Jae W.; Kim, Hyungjin Myra; Bellfi, Lillian T.; Chung, Kevin C.

2010-01-01

Background All silicone breast implant recipients are recommended by the US Food and Drug Administration to undergo serial screening to detect implant rupture with magnetic resonance imaging (MRI). We performed a systematic review of the literature to assess the quality of diagnostic accuracy studies utilizing MRI or ultrasound to detect silicone breast implant rupture and conducted a meta-analysis to examine the effect of study design biases on the estimation of MRI diagnostic accuracy measures. Method Studies investigating the diagnostic accuracy of MRI and ultrasound in evaluating ruptured silicone breast implants were identified using MEDLINE, EMBASE, ISI Web of Science, and Cochrane library databases. Two reviewers independently screened potential studies for inclusion and extracted data. Study design biases were assessed using the QUADAS tool and the STARDS checklist. Meta-analyses estimated the influence of biases on diagnostic odds ratios. Results Among 1175 identified articles, 21 met the inclusion criteria. Most studies using MRI (n= 10 of 16) and ultrasound (n=10 of 13) examined symptomatic subjects. Meta-analyses revealed that MRI studies evaluating symptomatic subjects had 14-fold higher diagnostic accuracy estimates compared to studies using an asymptomatic sample (RDOR 13.8; 95% CI 1.83–104.6) and 2-fold higher diagnostic accuracy estimates compared to studies using a screening sample (RDOR 1.89; 95% CI 0.05–75.7). Conclusion Many of the published studies utilizing MRI or ultrasound to detect silicone breast implant rupture are flawed with methodological biases. These methodological shortcomings may result in overestimated MRI diagnostic accuracy measures and should be interpreted with caution when applying the data to a screening population. PMID:21364405

The association between histological, macroscopic and magnetic resonance imaging assessed synovitis in end-stage knee osteoarthritis: a cross-sectional study.

PubMed

Riis, R G C; Gudbergsen, H; Simonsen, O; Henriksen, M; Al-Mashkur, N; Eld, M; Petersen, K K; Kubassova, O; Bay Jensen, A C; Damm, J; Bliddal, H; Arendt-Nielsen, L; Boesen, M

2017-02-01

To investigate the association between magnetic resonance imaging (MRI), macroscopic and histological assessments of synovitis in end-stage knee osteoarthritis (KOA). Synovitis of end-stage osteoarthritic knees was assessed using non-contrast-enhanced (CE), contrast-enhanced magnetic resonance imaging (CE-MRI) and dynamic contrast-enhanced (DCE)-MRI prior to (TKR) and correlated with microscopic and macroscopic assessments of synovitis obtained intraoperatively. Multiple bivariate correlations were used with a pre-specified threshold of 0.70 for significance. Also, multiple regression analyses with different subsets of MRI-variables as explanatory variables and the histology score as outcome variable were performed with the intention to find MRI-variables that best explain the variance in histological synovitis (i.e., highest R 2 ). A stepped approach was taken starting with basic characteristics and non-CE MRI-variables (model 1), after which CE-MRI-variables were added (model 2) with the final model also including DCE-MRI-variables (model 3). 39 patients (56.4% women, mean age 68 years, Kellgren-Lawrence (KL) grade 4) had complete MRI and histological data. Only the DCE-MRI variable MExNvoxel (surrogate of the volume and degree of synovitis) and the macroscopic score showed correlations above the pre-specified threshold for acceptance with histological inflammation. The maximum R 2 -value obtained in Model 1 was R 2  = 0.39. In Model 2, where the CE-MRI-variables were added, the highest R 2  = 0.52. In Model 3, a four-variable model consisting of the gender, one CE-MRI and two DCE-MRI-variables yielded a R 2  = 0.71. DCE-MRI is correlated with histological synovitis in end-stage KOA and the combination of CE and DCE-MRI may be a useful, non-invasive tool in characterising synovitis in KOA. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Color-coded visualization of magnetic resonance imaging multiparametric maps

NASA Astrophysics Data System (ADS)

Kather, Jakob Nikolas; Weidner, Anja; Attenberger, Ulrike; Bukschat, Yannick; Weis, Cleo-Aron; Weis, Meike; Schad, Lothar R.; Zöllner, Frank Gerrit

2017-01-01

Multiparametric magnetic resonance imaging (mpMRI) data are emergingly used in the clinic e.g. for the diagnosis of prostate cancer. In contrast to conventional MR imaging data, multiparametric data typically include functional measurements such as diffusion and perfusion imaging sequences. Conventionally, these measurements are visualized with a one-dimensional color scale, allowing only for one-dimensional information to be encoded. Yet, human perception places visual information in a three-dimensional color space. In theory, each dimension of this space can be utilized to encode visual information. We addressed this issue and developed a new method for tri-variate color-coded visualization of mpMRI data sets. We showed the usefulness of our method in a preclinical and in a clinical setting: In imaging data of a rat model of acute kidney injury, the method yielded characteristic visual patterns. In a clinical data set of N = 13 prostate cancer mpMRI data, we assessed diagnostic performance in a blinded study with N = 5 observers. Compared to conventional radiological evaluation, color-coded visualization was comparable in terms of positive and negative predictive values. Thus, we showed that human observers can successfully make use of the novel method. This method can be broadly applied to visualize different types of multivariate MRI data.

Exploiting the wavelet structure in compressed sensing MRI.

PubMed

Chen, Chen; Huang, Junzhou

2014-12-01

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

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.

Framework for 3D histologic reconstruction and fusion with in vivo MRI: Preliminary results of characterizing pulmonary inflammation in a mouse model.

PubMed

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

2015-08-01

Pulmonary inflammation is associated with a variety of diseases. Assessing pulmonary inflammation on in vivo imaging may facilitate the early detection and treatment of lung diseases. Although routinely used in thoracic imaging, computed tomography has thus far not been compellingly shown to characterize inflammation in vivo. Alternatively, magnetic resonance imaging (MRI) is a nonionizing radiation technique to better visualize and characterize pulmonary tissue. Prior to routine adoption of MRI for early characterization of inflammation in humans, a rigorous and quantitative characterization of the utility of MRI to identify inflammation is required. Such characterization may be achieved by considering ex vivo histology as the ground truth, since it enables the definitive spatial assessment of inflammation. In this study, the authors introduce a novel framework to integrate 2D histology, ex vivo and in vivo imaging to enable the mapping of the extent of disease from ex vivo histology onto in vivo imaging, with the goal of facilitating computerized feature analysis and interrogation of disease appearance on in vivo imaging. The authors' framework was evaluated in a preclinical preliminary study aimed to identify computer extracted features on in vivo MRI associated with chronic pulmonary inflammation. The authors' image analytics framework first involves reconstructing the histologic volume in 3D from individual histology slices. Second, the authors map the disease ground truth onto in vivo MRI via coregistration with 3D histology using the ex vivo lung MRI as a conduit. Finally, computerized feature analysis of the disease extent is performed to identify candidate in vivo imaging signatures of disease presence and extent. The authors evaluated the framework by assessing the quality of the 3D histology reconstruction and the histology-MRI fusion, in the context of an initial use case involving characterization of chronic inflammation in a mouse model. The authors' evaluation considered three mice, two with an inflammation phenotype and one control. The authors' iterative 3D histology reconstruction yielded a 70.1% ± 2.7% overlap with the ex vivo MRI volume. Across a total of 17 anatomic landmarks manually delineated at the division of airways, the target registration error between the ex vivo MRI and 3D histology reconstruction was 0.85 ± 0.44 mm, suggesting that a good alignment of the ex vivo 3D histology and ex vivo MRI had been achieved. The 3D histology-in vivo MRI coregistered volumes resulted in an overlap of 73.7% ± 0.9%. Preliminary computerized feature analysis was performed on an additional four control mice, for a total of seven mice considered in this study. Gabor texture filters appeared to best capture differences between the inflamed and noninflamed regions on MRI. The authors' 3D histology reconstruction and multimodal registration framework were successfully employed to reconstruct the histology volume of the lung and fuse it with in vivo MRI to create a ground truth map for inflammation on in vivo MRI. The analytic platform presented here lays the framework for a rigorous validation of the identified imaging features for chronic lung inflammation on MRI in a large prospective cohort.

Comparison of classification methods for voxel-based prediction of acute ischemic stroke outcome following intra-arterial intervention

NASA Astrophysics Data System (ADS)

Winder, Anthony J.; Siemonsen, Susanne; Flottmann, Fabian; Fiehler, Jens; Forkert, Nils D.

2017-03-01

Voxel-based tissue outcome prediction in acute ischemic stroke patients is highly relevant for both clinical routine and research. Previous research has shown that features extracted from baseline multi-parametric MRI datasets have a high predictive value and can be used for the training of classifiers, which can generate tissue outcome predictions for both intravenous and conservative treatments. However, with the recent advent and popularization of intra-arterial thrombectomy treatment, novel research specifically addressing the utility of predictive classi- fiers for thrombectomy intervention is necessary for a holistic understanding of current stroke treatment options. The aim of this work was to develop three clinically viable tissue outcome prediction models using approximate nearest-neighbor, generalized linear model, and random decision forest approaches and to evaluate the accuracy of predicting tissue outcome after intra-arterial treatment. Therefore, the three machine learning models were trained, evaluated, and compared using datasets of 42 acute ischemic stroke patients treated with intra-arterial thrombectomy. Classifier training utilized eight voxel-based features extracted from baseline MRI datasets and five global features. Evaluation of classifier-based predictions was performed via comparison to the known tissue outcome, which was determined in follow-up imaging, using the Dice coefficient and leave-on-patient-out cross validation. The random decision forest prediction model led to the best tissue outcome predictions with a mean Dice coefficient of 0.37. The approximate nearest-neighbor and generalized linear model performed equally suboptimally with average Dice coefficients of 0.28 and 0.27 respectively, suggesting that both non-linearity and machine learning are desirable properties of a classifier well-suited to the intra-arterial tissue outcome prediction problem.

The role of fMRI in drug development

PubMed Central

Carmichael, Owen; Schwarz, Adam J.; Chatham, Christopher H.; Scott, David; Turner, Jessica A.; Upadhyay, Jaymin; Coimbra, Alexandre; Goodman, James A.; Baumgartner, Richard; English, Brett A.; Apolzan, John W.; Shankapal, Preetham; Hawkins, Keely R.

2017-01-01

Functional magnetic resonance imaging (fMRI) has been known for over a decade to have the potential to greatly enhance the process of developing novel therapeutic drugs for prevalent health conditions. However, the use of fMRI in drug development continues to be relatively limited because of a variety of technical, biological, and strategic barriers that continue to limit progress. Here, we briefly review the roles that fMRI can have in the drug development process and the requirements it must meet to be useful in this setting. We then provide an update on our current understanding of the strengths and limitations of fMRI as a tool for drug developers and recommend activities to enhance its utility. PMID:29154758

Diffusion Weighted/Tensor Imaging, Functional MRI and Perfusion Weighted Imaging in Glioblastoma-Foundations and Future.

PubMed

Salama, Gayle R; Heier, Linda A; Patel, Praneil; Ramakrishna, Rohan; Magge, Rajiv; Tsiouris, Apostolos John

2017-01-01

In this article, we review the basics of diffusion tensor imaging and functional MRI, their current utility in preoperative neurosurgical mapping, and their limitations. We also discuss potential future applications, including implementation of resting state functional MRI. We then discuss perfusion and diffusion-weighted imaging and their application in advanced neuro-oncologic practice. We explain how these modalities can be helpful in guiding surgical biopsies and differentiating recurrent tumor from treatment related changes.

Diffusion Weighted/Tensor Imaging, Functional MRI and Perfusion Weighted Imaging in Glioblastoma—Foundations and Future

PubMed Central

Salama, Gayle R.; Heier, Linda A.; Patel, Praneil; Ramakrishna, Rohan; Magge, Rajiv; Tsiouris, Apostolos John

2018-01-01

In this article, we review the basics of diffusion tensor imaging and functional MRI, their current utility in preoperative neurosurgical mapping, and their limitations. We also discuss potential future applications, including implementation of resting state functional MRI. We then discuss perfusion and diffusion-weighted imaging and their application in advanced neuro-oncologic practice. We explain how these modalities can be helpful in guiding surgical biopsies and differentiating recurrent tumor from treatment related changes. PMID:29403420

New method for predicting estrogen receptor status utilizing breast MRI texture kinetic analysis

NASA Astrophysics Data System (ADS)

Chaudhury, Baishali; Hall, Lawrence O.; Goldgof, Dmitry B.; Gatenby, Robert A.; Gillies, Robert; Drukteinis, Jennifer S.

2014-03-01

Magnetic Resonance Imaging (MRI) of breast cancer typically shows that tumors are heterogeneous with spatial variations in blood flow and cell density. Here, we examine the potential link between clinical tumor imaging and the underlying evolutionary dynamics behind heterogeneity in the cellular expression of estrogen receptors (ER) in breast cancer. We assume, in an evolutionary environment, that ER expression will only occur in the presence of significant concentrations of estrogen, which is delivered via the blood stream. Thus, we hypothesize, the expression of ER in breast cancer cells will correlate with blood flow on gadolinium enhanced breast MRI. To test this hypothesis, we performed quantitative analysis of blood flow on dynamic contrast enhanced MRI (DCE-MRI) and correlated it with the ER status of the tumor. Here we present our analytic methods, which utilize a novel algorithm to analyze 20 volumetric DCE-MRI breast cancer tumors. The algorithm generates post initial enhancement (PIE) maps from DCE-MRI and then performs texture features extraction from the PIE map, feature selection, and finally classification of tumors into ER positive and ER negative status. The combined gray level co-occurrence matrices, gray level run length matrices and local binary pattern histogram features allow quantification of breast tumor heterogeneity. The algorithm predicted ER expression with an accuracy of 85% using a Naive Bayes classifier in leave-one-out cross-validation. Hence, we conclude that our data supports the hypothesis that imaging characteristics can, through application of evolutionary principles, provide insights into the cellular and molecular properties of cancer cells.

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

A UML model for the description of different brain-computer interface systems.

PubMed

Quitadamo, Lucia Rita; Abbafati, Manuel; Saggio, Giovanni; Marciani, Maria Grazia; Cardarilli, Gian Carlo; Bianchi, Luigi

2008-01-01

BCI research lacks a universal descriptive language among labs and a unique standard model for the description of BCI systems. This results in a serious problem in comparing performances of different BCI processes and in unifying tools and resources. In such a view we implemented a Unified Modeling Language (UML) model for the description virtually of any BCI protocol and we demonstrated that it can be successfully applied to the most common ones such as P300, mu-rhythms, SCP, SSVEP, fMRI. Finally we illustrated the advantages in utilizing a standard terminology for BCIs and how the same basic structure can be successfully adopted for the implementation of new systems.

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.

Implanting Glioblastoma Spheroids into Rat Brains and Monitoring Tumor Growth by MRI Volumetry.

PubMed

Löhr, Mario; Linsenmann, Thomas; Jawork, Anna; Kessler, Almuth F; Timmermann, Nils; Homola, György A; Ernestus, Ralf-Ingo; Hagemann, Carsten

2017-01-01

The outcome of patients suffering from glioblastoma multiforme (GBM) remains poor with a median survival of less than 15 months. To establish innovative therapeutical approaches or to analyze the effect of protein overexpression or protein knockdown by RNA interference in vivo, animal models are mandatory. Here, we describe the implantation of C6 glioma spheroids into the rats' brain and how to follow tumor growth by MRI scans. We show that C6 cells grown in Sprague-Dawley rats share several morphologic features of human glioblastoma like pleomorphic cells, areas of necrosis, vascular proliferation, and tumor cell invasion into the surrounding brain tissue. In addition, we describe a method for tumor volumetry utilizing the CISS 3D- or contrast-enhanced T1-weighted 3D sequence and freely available post-processing software.

STABILITY OF FMRI STRIATAL RESPONSE TO ALCOHOL CUES: A HIERARCHICAL LINEAR MODELING APPROACH

PubMed Central

Schacht, Joseph P.; Anton, Raymond F.; Randall, Patrick K.; Li, Xingbao; Henderson, Scott; Myrick, Hugh

2011-01-01

In functional magnetic resonance imaging (fMRI) studies of alcohol-dependent individuals, alcohol cues elicit activation of the ventral and dorsal aspects of the striatum (VS and DS), which are believed to underlie aspects of reward learning critical to the initiation and maintenance of alcohol dependence. Cue-elicited striatal activation may represent a biological substrate through which treatment efficacy may be measured. However, to be useful for this purpose, VS or DS activation must first demonstrate stability across time. Using hierarchical linear modeling (HLM), this study tested the stability of cue-elicited activation in anatomically and functionally defined regions of interest in bilateral VS and DS. Nine non-treatment-seeking alcohol-dependent participants twice completed an alcohol cue reactivity task during two fMRI scans separated by 14 days. HLM analyses demonstrated that, across all participants, alcohol cues elicited significant activation in each of the regions of interest. At the group level, these activations attenuated slightly between scans, but session-wise differences were not significant. Within-participants stability was best in the anatomically defined right VS and DS and in a functionally defined region that encompassed right caudate and putamen (intraclass correlation coefficients of .75, .81, and .76, respectively). Thus, within this small sample, alcohol cue-elicited fMRI activation had good reliability in the right striatum, though a larger sample is necessary to ensure generalizability and further evaluate stability. This study also demonstrates the utility of HLM analytic techniques for serial fMRI studies, in which separating within-participants variance (individual changes in activation) from between-participants factors (time or treatment) is critical. PMID:21316465

Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features

PubMed Central

Hu, Yu-Chuan; Li, Gang; Yang, Yang; Han, Yu; Sun, Ying-Zhi; Liu, Zhi-Cheng; Tian, Qiang; Han, Zi-Yang; Liu, Le-De; Hu, Bin-Quan; Qiu, Zi-Yu; Wang, Wen; Cui, Guang-Bin

2017-01-01

Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of different machine learning methods in glioma grading have not been investigated.A comprehensive comparison of varied machine learning methods in differentiating low-grade gliomas (LGGs) and high-grade gliomas (HGGs) as well as WHO grade II, III and IV gliomas based on multi-parametric MRI images was proposed in the current study. The parametric histogram and image texture attributes of 120 glioma patients were extracted from the perfusion, diffusion and permeability parametric maps of preoperative MRI. Then, 25 commonly used machine learning classifiers combined with 8 independent attribute selection methods were applied and evaluated using leave-one-out cross validation (LOOCV) strategy. Besides, the influences of parameter selection on the classifying performances were investigated. We found that support vector machine (SVM) exhibited superior performance to other classifiers. By combining all tumor attributes with synthetic minority over-sampling technique (SMOTE), the highest classifying accuracy of 0.945 or 0.961 for LGG and HGG or grade II, III and IV gliomas was achieved. Application of Recursive Feature Elimination (RFE) attribute selection strategy further improved the classifying accuracies. Besides, the performances of LibSVM, SMO, IBk classifiers were influenced by some key parameters such as kernel type, c, gama, K, etc. SVM is a promising tool in developing automated preoperative glioma grading system, especially when being combined with RFE strategy. Model parameters should be considered in glioma grading model optimization. PMID:28599282

Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features.

PubMed

Zhang, Xin; Yan, Lin-Feng; Hu, Yu-Chuan; Li, Gang; Yang, Yang; Han, Yu; Sun, Ying-Zhi; Liu, Zhi-Cheng; Tian, Qiang; Han, Zi-Yang; Liu, Le-De; Hu, Bin-Quan; Qiu, Zi-Yu; Wang, Wen; Cui, Guang-Bin

2017-07-18

Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of different machine learning methods in glioma grading have not been investigated.A comprehensive comparison of varied machine learning methods in differentiating low-grade gliomas (LGGs) and high-grade gliomas (HGGs) as well as WHO grade II, III and IV gliomas based on multi-parametric MRI images was proposed in the current study. The parametric histogram and image texture attributes of 120 glioma patients were extracted from the perfusion, diffusion and permeability parametric maps of preoperative MRI. Then, 25 commonly used machine learning classifiers combined with 8 independent attribute selection methods were applied and evaluated using leave-one-out cross validation (LOOCV) strategy. Besides, the influences of parameter selection on the classifying performances were investigated. We found that support vector machine (SVM) exhibited superior performance to other classifiers. By combining all tumor attributes with synthetic minority over-sampling technique (SMOTE), the highest classifying accuracy of 0.945 or 0.961 for LGG and HGG or grade II, III and IV gliomas was achieved. Application of Recursive Feature Elimination (RFE) attribute selection strategy further improved the classifying accuracies. Besides, the performances of LibSVM, SMO, IBk classifiers were influenced by some key parameters such as kernel type, c, gama, K, etc. SVM is a promising tool in developing automated preoperative glioma grading system, especially when being combined with RFE strategy. Model parameters should be considered in glioma grading model optimization.

Endovascular ischemic stroke models of adult rhesus monkeys: a comparison of two endovascular methods.

PubMed

Wu, Di; Chen, Jian; Wang, Bincheng; Zhang, Mo; Shi, Jingfei; Ma, Yanhui; Zhu, Zixin; Yan, Feng; He, Xiaoduo; Li, Shengli; Dornbos Iii, David; Ding, Yuchuan; Ji, Xunming

2016-08-18

To further investigate and improve upon current stroke models in nonhuman primates, infarct size, neurologic function and survival were evaluated in two endovascular ischemic models in sixteen rhesus monkeys. The first method utilized a micro-catheter or an inflatable balloon to occlude the M1 segment in six monkeys. In the second model, an autologous clot was injected via a micro-catheter into the M1 segment in ten monkeys. MRI scanning was performed on all monkeys both at baseline and 3 hours after the onset of ischemia. Spetzler neurologic functions were assessed post-operatively, and selective perfusion deficits were confirmed by DSA and MRI in all monkeys. Animals undergoing micro-catheter or balloon occlusion demonstrated more profound hemiparesis, larger infarct sizes, lower Spetzler neurologic scores and increased mortality compared to the thrombus occlusion group. In animals injected with the clot, there was no evidence of dissolution, and the thrombus was either near the injection site (M1) or flushed into the superior division of the MCA (M2). All animals survived the M2 occlusion. M1 occlusion with thrombus generated 50% mortality. This study highlighted clinically important differences in these two models, providing a platform for further study of a translational thromboembolic model of acute ischemic stroke.

Creating a strategic management plan for magnetic resonance imaging (MRI) provision.

PubMed

Szczepura, A; Clark, M

2000-09-01

We were commissioned by the West Midlands NHS Regional Specialized Services Group (RSSG) to formulate a strategic plan for the management of Magnetic Resonance Imaging (MRI) within the West Midlands, UK. We needed to establish whether an increase in MRI provision was required, and if so to develop criteria to shape both the nature and location of MRI provision. We found that the UK had relatively low MRI provision per capita by international standards, and that the West Midlands region of the UK had less than the UK average level of MRI provision per capita. Within the region there was a 'mixed economy' of MRI provision involving fixed site scanners owned by the NHS and private companies, and private sector mobile MRI provision. There was little evidence of inappropriate MRI use, but considerable evidence of under-provision. Most MRI scanners in the region were heavily utilized, and average waiting times for MRI frequently exceeded guidelines (of a maximum 13-week wait for non-urgent MRI scans). Projections from NHS Trusts, MRI suppliers, and experts in the MRI field, led us to the conclusion that demand for MRI was likely to grow by between 12.5 and 18.5% per annum. This implies that 8-14 additional MRI scanners might be required within the West Midlands over the next 5 years, to meet existing, and rising demand for MRI. We therefore developed criteria (outlined in the paper) to enhance the productive and allocative efficiency of the deployment of MRI provision, whilst improving the configuration of MRI with reference to geographical equality of access to MRI.

Translating state-of-the-art spinal cord MRI techniques to clinical use: A systematic review of clinical studies utilizing DTI, MT, MWF, MRS, and fMRI

PubMed Central

Martin, Allan R.; Aleksanderek, Izabela; Cohen-Adad, Julien; Tarmohamed, Zenovia; Tetreault, Lindsay; Smith, Nathaniel; Cadotte, David W.; Crawley, Adrian; Ginsberg, Howard; Mikulis, David J.; Fehlings, Michael G.

2015-01-01

Background A recent meeting of international imaging experts sponsored by the International Spinal Research Trust (ISRT) and the Wings for Life Foundation identified 5 state-of-the-art MRI techniques with potential to transform the field of spinal cord imaging by elucidating elements of the microstructure and function: diffusion tensor imaging (DTI), magnetization transfer (MT), myelin water fraction (MWF), MR spectroscopy (MRS), and functional MRI (fMRI). However, the progress toward clinical translation of these techniques has not been established. Methods A systematic review of the English literature was conducted using MEDLINE, MEDLINE-in-Progress, Embase, and Cochrane databases to identify all human studies that investigated utility, in terms of diagnosis, correlation with disability, and prediction of outcomes, of these promising techniques in pathologies affecting the spinal cord. Data regarding study design, subject characteristics, MRI methods, clinical measures of impairment, and analysis techniques were extracted and tabulated to identify trends and commonalities. The studies were assessed for risk of bias, and the overall quality of evidence was assessed for each specific finding using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework. Results A total of 6597 unique citations were identified in the database search, and after full-text review of 274 articles, a total of 104 relevant studies were identified for final inclusion (97% from the initial database search). Among these, 69 studies utilized DTI and 25 used MT, with both techniques showing an increased number of publications in recent years. The review also identified 1 MWF study, 11 MRS studies, and 8 fMRI studies. Most of the studies were exploratory in nature, lacking a priori hypotheses and showing a high (72%) or moderately high (20%) risk of bias, due to issues with study design, acquisition techniques, and analysis methods. The acquisitions for each technique varied widely across studies, rendering direct comparisons of metrics invalid. The DTI metric fractional anisotropy (FA) had the strongest evidence of utility, with moderate quality evidence for its use as a biomarker showing correlation with disability in several clinical pathologies, and a low level of evidence that it identifies tissue injury (in terms of group differences) compared with healthy controls. However, insufficient evidence exists to determine its utility as a sensitive and specific diagnostic test or as a tool to predict clinical outcomes. Very low quality evidence suggests that other metrics also show group differences compared with controls, including DTI metrics mean diffusivity (MD) and radial diffusivity (RD), the diffusional kurtosis imaging (DKI) metric mean kurtosis (MK), MT metrics MT ratio (MTR) and MT cerebrospinal fluid ratio (MTCSF), and the MRS metric of N-acetylaspartate (NAA) concentration, although these results were somewhat inconsistent. Conclusions State-of-the-art spinal cord MRI techniques are emerging with great potential to improve the diagnosis and management of various spinal pathologies, but the current body of evidence has only showed limited clinical utility to date. Among these imaging tools DTI is the most mature, but further work is necessary to standardize and validate its use before it will be adopted in the clinical realm. Large, well-designed studies with a priori hypotheses, standardized acquisition methods, detailed clinical data collection, and robust automated analysis techniques are needed to fully demonstrate the potential of these rapidly evolving techniques. PMID:26862478

Accelerating the reconstruction of magnetic resonance imaging by three-dimensional dual-dictionary learning using CUDA.

PubMed

Jiansen Li; Jianqi Sun; Ying Song; Yanran Xu; Jun Zhao

2014-01-01

An effective way to improve the data acquisition speed of magnetic resonance imaging (MRI) is using under-sampled k-space data, and dictionary learning method can be used to maintain the reconstruction quality. Three-dimensional dictionary trains the atoms in dictionary in the form of blocks, which can utilize the spatial correlation among slices. Dual-dictionary learning method includes a low-resolution dictionary and a high-resolution dictionary, for sparse coding and image updating respectively. However, the amount of data is huge for three-dimensional reconstruction, especially when the number of slices is large. Thus, the procedure is time-consuming. In this paper, we first utilize the NVIDIA Corporation's compute unified device architecture (CUDA) programming model to design the parallel algorithms on graphics processing unit (GPU) to accelerate the reconstruction procedure. The main optimizations operate in the dictionary learning algorithm and the image updating part, such as the orthogonal matching pursuit (OMP) algorithm and the k-singular value decomposition (K-SVD) algorithm. Then we develop another version of CUDA code with algorithmic optimization. Experimental results show that more than 324 times of speedup is achieved compared with the CPU-only codes when the number of MRI slices is 24.

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.

Utility of magnetic resonance imaging in diagnosing cervical spine injury in children with severe traumatic brain injury.

PubMed

Qualls, David; Leonard, Jeffrey R; Keller, Martin; Pineda, Jose; Leonard, Julie C

2015-06-01

Evaluation of children for cervical spine injuries (CSIs) after blunt trauma is complicated, particularly if the patient is unresponsive because of severe traumatic brain injury. Plain radiography and computed tomography (CT) are commonly used, but CT combined with magnetic resonance imaging (MRI) is still considered the gold standard in CSI detection. However, MRI is expensive and can delay cervical clearance. The purpose of this study is to determine the added benefit of MRI as an adjunct to CT in the clearance of children with severe head trauma. We performed a retrospective chart review of pediatric head trauma patients admitted to the pediatric intensive care unit at St. Louis Children's Hospital from 2002 to 2012. Patients who received both cervical spine CT and MRI and presented with a Glasgow Coma Scale score of 8 or lower were included in the study. Imaging was analyzed by two pediatric trauma subspecialists and classified as demonstrating "no injury," "stable injury," or "unstable injury." Results were compared, and discrepancies between CT and MRI findings were noted. A total of 1,196 head-injured children were admitted to the pediatric intensive care unit between January 2002 and December 2012. Sixty-three children underwent CT and MRI and met Glasgow Coma Scale criteria. Seven children were identified with negative CT and positive MRI findings, but none of these injuries were considered unstable by our criteria. Five children were determined to have unstable injuries, and all were detected on CT. The results of this study suggest that MRI does not detect unstable CSIs in the setting of negative CT imaging. Given the limited patient population for this study, further and more extensive studies investigating the utility of MRI in the head-injured pediatric patient are warranted. Diagnostic and care management study, level IV.

The diagnostic utility of 3D-ESI rotating and moving dipole methodology in the pre-surgical evaluation of MRI-negative childhood epilepsy due to focal cortical dysplasia.

PubMed

Russo, Angelo; Lallas, Matt; Jayakar, Prasanna; Miller, Ian; Hyslop, Ann; Dunoyer, Catalina; Resnick, Trevor; Duchowny, Michael

2016-09-01

This study investigates whether a combined rotating dipole (RD) and moving dipole (MD) solution enhances three-dimensional electroencephalography (EEG) source imaging (3D-ESI) localization in magnetic resonance imaging (MRI)-negative pediatric patients with focal cortical dysplasia (FCD). We retrospectively selected 14 MRI-negative patients with FCD from a cohort of 60 pediatric patients previously used to evaluate the diagnostic utility of 3D-ESI in epilepsy surgery. Patients were younger than 18 years at time of surgery and had at least 1 year of outcome data. RD and MD models were constructed for each interictal spike or sharp wave, and it was determined whether each inverse algorithm localized within the surgical resection cavity (SRC). We also compared the 3D-ESI findings and surgical outcome with positron emission tomography (PET) and ictal single photon emission computed tomography (iSPECT). RD analyses revealed a high concordance with the SRC (78.6%), particularly for temporal lobe resection (100.0%), and showed superior localization compared to PET and iSPECT, with the highest correlation in FCD type I and temporal lobe resection. Furthermore, the RD method was superior to iSPECT in FCD type II cases and to PET in extratemporal resections. RD and MD results were comparable, but in 18.2% of patients with FCD type I with localizing RDs, the MD solution was only partially within the SRC; in all of these patients 3D-ESI also correlated with superior surgical outcome compared to PET and iSPECT, especially when RD and MD solutions were analyzed together. 3D-ESI in MRI-negative cases showed superior localization compared to iSPECT or PET, especially in FCD type I and temporal lobe epilepsy, and correlated with superior surgical outcome compared to iSPECT and PET at 1 year and 2 years postoperatively, especially when RD and MD solutions were analyzed together. These findings suggest that 3D-ESI based on a combined RD-MD solution improves surgical accuracy in MRI-negative patients with FCD. Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.

Diagnostic Imaging Services in Magnet and Non-Magnet Hospitals: Trends in Utilization and Costs.

PubMed

Jayawardhana, Jayani; Welton, John M

2015-12-01

The purpose of this study was to better understand trends in utilization and costs of diagnostic imaging services at Magnet hospitals (MHs) and non-Magnet hospitals (NMHs). A data set was created by merging hospital-level data from the American Hospital Association's annual survey and Medicare cost reports, individual-level inpatient data from the Healthcare Cost and Utilization Project, and Magnet recognition status data from the American Nurses Credentialing Center. A descriptive analysis was conducted to evaluate the trends in utilization and costs of CT, MRI, and ultrasound procedures among MHs and NMHs in urban locations between 2000 and 2006 from the following ten states: Arizona, California, Colorado, Florida, Iowa, Maryland, North Carolina, New Jersey, New York, and Washington. When matched by bed size, severity of illness (case mix index), and clinical technological sophistication (Saidin index) quantiles, MHs in higher quantiles indicated higher rates of utilization of imaging services for MRI, CT, and ultrasound in comparison with NMHs in the same quantiles. However, average costs of MRI, CT, and ultrasounds were lower at MHs in comparison with NMHs in the same quantiles. Overall, MHs that are larger in size (number of beds), serve more severely ill patients (case mix index), and are more technologically sophisticated (Saidin index) show higher utilization of diagnostic imaging services, although costs per procedure at MHs are lower in comparison with similar NMHs, indicating possible cost efficiency at MHs. Further research is necessary to understand the relationship between the utilization of diagnostic imaging services among MHs and its impact on patient outcomes. Copyright © 2015 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Comparison of Deep Brain Stimulation Lead Targeting Accuracy and Procedure Duration between 1.5- and 3-Tesla Interventional Magnetic Resonance Imaging Systems: An Initial 12-Month Experience.

PubMed

Southwell, Derek G; Narvid, Jared A; Martin, Alastair J; Qasim, Salman E; Starr, Philip A; Larson, Paul S

2016-01-01

Interventional magnetic resonance imaging (iMRI) allows deep brain stimulator lead placement under general anesthesia. While the accuracy of lead targeting has been described for iMRI systems utilizing 1.5-tesla magnets, a similar assessment of 3-tesla iMRI procedures has not been performed. To compare targeting accuracy, the number of lead targeting attempts, and surgical duration between procedures performed on 1.5- and 3-tesla iMRI systems. Radial targeting error, the number of targeting attempts, and procedure duration were compared between surgeries performed on 1.5- and 3-tesla iMRI systems (SmartFrame and ClearPoint systems). During the first year of operation of each system, 26 consecutive leads were implanted using the 1.5-tesla system, and 23 consecutive leads were implanted using the 3-tesla system. There was no significant difference in radial error (Mann-Whitney test, p = 0.26), number of lead placements that required multiple targeting attempts (Fisher's exact test, p = 0.59), or bilateral procedure durations between surgeries performed with the two systems (p = 0.15). Accurate DBS lead targeting can be achieved with iMRI systems utilizing either 1.5- or 3-tesla magnets. The use of a 3-tesla magnet, however, offers improved visualization of the target structures and allows comparable accuracy and efficiency of placement at the selected targets. © 2016 S. Karger AG, Basel.

Magnetic resonance imaging: A tool to monitor and optimize enzyme distribution during porcine pancreas distention for islet isolation

PubMed Central

Scott, WE; Weegman, BP; Balamurugan, AN; Ferrer-Fabrega, J; Anazawa, T; Karatzas, T; Jie, T; Hammer, BE; Matsumoto, S; Avgoustiniatos, ES; Maynard, KS; Sutherland, DER; Hering, BJ; Papas, KK

2014-01-01

Background Porcine islet xenotransplantation is emerging as a potential alternative for allogeneic clinical islet transplantation. Optimization of porcine islet isolation in terms of yield and quality is critical for the success and cost effectiveness of this approach. Incomplete pancreas distension and inhomogeneous enzyme distribution have been identified as key factors for limiting viable islet yield per porcine pancreas. The aim of this study was to explore the utility of Magnetic Resonance Imaging (MRI) as a tool to investigate the homogeneity of enzyme delivery in porcine pancreata. Traditional and novel methods for enzyme delivery aimed at optimizing enzyme distribution were examined. Methods Pancreata were procured from Landrace pigs via en bloc viscerectomy. The main pancreatic duct was then cannulated with an 18g winged catheter and MRI performed at 1.5 T. Images were collected before and after ductal infusion of chilled MRI contrast agent (gadolinium) in physiological saline. Results Regions of the distal aspect of the splenic lobe and portions of the connecting lobe and bridge exhibited reduced delivery of solution when traditional methods of distension were utilized. Use of alternative methods of delivery (such as selective re-cannulation and distension of identified problem regions) resolved these issues and MRI was successfully utilized as a guide and assessment tool for improved delivery. Conclusion Current methods of porcine pancreas distension do not consistently deliver enzyme uniformly or adequately to all regions of the pancreas. Novel methods of enzyme delivery should be investigated and implemented for improved enzyme distribution. MRI serves as a valuable tool to visualize and evaluate the efficacy of current and prospective methods of pancreas distension and enzyme delivery. PMID:24986758

Magnetic resonance imaging: a tool to monitor and optimize enzyme distribution during porcine pancreas distention for islet isolation.

PubMed

Scott, William E; Weegman, Bradley P; Balamurugan, Appakalai N; Ferrer-Fabrega, Joana; Anazawa, Takayuki; Karatzas, Theodore; Jie, Tun; Hammer, Bruce E; Matsumoto, Shuchiro; Avgoustiniatos, Efstathios S; Maynard, Kristen S; Sutherland, David E R; Hering, Bernhard J; Papas, Klearchos K

2014-01-01

Porcine islet xenotransplantation is emerging as a potential alternative for allogeneic clinical islet transplantation. Optimization of porcine islet isolation in terms of yield and quality is critical for the success and cost-effectiveness of this approach. Incomplete pancreas distention and inhomogeneous enzyme distribution have been identified as key factors for limiting viable islet yield per porcine pancreas. The aim of this study was to explore the utility of magnetic resonance imaging (MRI) as a tool to investigate the homogeneity of enzyme delivery in porcine pancreata. Traditional and novel methods for enzyme delivery aimed at optimizing enzyme distribution were examined. Pancreata were procured from Landrace pigs via en bloc viscerectomy. The main pancreatic duct was then cannulated with an 18-g winged catheter and MRI performed at 1.5-T. Images were collected before and after ductal infusion of chilled MRI contrast agent (gadolinium) in physiological saline. Regions of the distal aspect of the splenic lobe and portions of the connecting lobe and bridge exhibited reduced delivery of solution when traditional methods of distention were utilized. Use of alternative methods of delivery (such as selective re-cannulation and distention of identified problem regions) resolved these issues, and MRI was successfully utilized as a guide and assessment tool for improved delivery. Current methods of porcine pancreas distention do not consistently deliver enzyme uniformly or adequately to all regions of the pancreas. Novel methods of enzyme delivery should be investigated and implemented for improved enzyme distribution. MRI serves as a valuable tool to visualize and evaluate the efficacy of current and prospective methods of pancreas distention and enzyme delivery. © 2014 John Wiley & Sons A/S Published by John Wiley & Sons Ltd.

Utility of Early Post-operative High Resolution Volumetric MR Imaging after Transsphenoidal Pituitary Tumor Surgery

PubMed Central

Patel, Kunal S.; Kazam, Jacob; Tsiouris, Apostolos J.; Anand, Vijay K.; Schwartz, Theodore H.

2014-01-01

Objective Controversy exists over the utility of early post-operative magnetic resonance imaging (MRI) after transsphenoidal pituitary surgery for macroadenomas. We investigate whether valuable information can be derived from current higher resolution scans. Methods Volumetric MRI scans were obtained in the early (<10 days) and late (>30 days) post-operative periods in a series of patients undergoing transsphenoidal pituitary surgery. The volume of the residual tumor, resection cavity, and corresponding visual field tests were recorded at each time point. Statistical analyses of changes in tumor volume and cavity size were calculated using the late MRI as the gold standard. Results 40 patients met the inclusion criteria. Pre-operative tumor volume averaged 8.8 cm3. Early postoperative assessment of average residual tumor volume (1.18 cm3) was quite accurate and did not differ statistically from late post-operative volume (1.23 cm3, p=.64), indicating the utility of early scans to measure residual tumor. Early scans were 100% sensitive and 91% specific for predicting ≥ 98% resection (p<.001, Fisher’s exact test). The average percent decrease in cavity volume from pre-operative MRI (tumor volume) to early post-operative imaging was 45% with decreases in all but 3 patients. There was no correlation between the size of the early cavity and the visual outcome. Conclusions Early high resolution volumetric MRI is valuable in determining the presence or absence of residual tumor. Cavity volume almost always decreases after surgery and a lack of decrease should alert the surgeon to possible persistent compression of the optic apparatus that may warrant re-operation. PMID:25045791

An investigation of fMRI time series stationarity during motor sequence learning foot tapping tasks.

PubMed

Muhei-aldin, Othman; VanSwearingen, Jessie; Karim, Helmet; Huppert, Theodore; Sparto, Patrick J; Erickson, Kirk I; Sejdić, Ervin

2014-04-30

Understanding complex brain networks using functional magnetic resonance imaging (fMRI) is of great interest to clinical and scientific communities. To utilize advanced analysis methods such as graph theory for these investigations, the stationarity of fMRI time series needs to be understood as it has important implications on the choice of appropriate approaches for the analysis of complex brain networks. In this paper, we investigated the stationarity of fMRI time series acquired from twelve healthy participants while they performed a motor (foot tapping sequence) learning task. Since prior studies have documented that learning is associated with systematic changes in brain activation, a sequence learning task is an optimal paradigm to assess the degree of non-stationarity in fMRI time-series in clinically relevant brain areas. We predicted that brain regions involved in a "learning network" would demonstrate non-stationarity and may violate assumptions associated with some advanced analysis approaches. Six blocks of learning, and six control blocks of a foot tapping sequence were performed in a fixed order. The reverse arrangement test was utilized to investigate the time series stationarity. Our analysis showed some non-stationary signals with a time varying first moment as a major source of non-stationarity. We also demonstrated a decreased number of non-stationarities in the third block as a result of priming and repetition. Most of the current literature does not examine stationarity prior to processing. The implication of our findings is that future investigations analyzing complex brain networks should utilize approaches robust to non-stationarities, as graph-theoretical approaches can be sensitive to non-stationarities present in data. Copyright © 2014 Elsevier B.V. All rights reserved.

Utility of the cumulative stress and mismatch hypotheses in understanding the neurobiological impacts of childhood abuse and recent stress in youth with emerging mental disorder.

PubMed

Paquola, Casey; Bennett, Maxwell R; Hatton, Sean N; Hermens, Daniel F; Lagopoulos, Jim

2017-05-01

Childhood abuse has an enduring impact on the brain's stress system. Whether the effects of childhood abuse and adulthood stress are additive (cumulative stress hypothesis) or interactive (mismatch hypothesis) is widely disputed, however. The primary aim of this study was to test the utility of the cumulative stress and mismatch hypotheses in understanding brain and behaviour. We recruited 64 individuals (aged 14-26) from a specialised clinic for assessment and early intervention of mental health problems in young people. A T1-weighted MRI, a resting state fMRI and clinical assessment were acquired from each participant. Grey matter estimates and resting state functional connectivity (rsFC) of the hippocampus, amygdala and anterior cingulate cortex (ACC) were determined using segmentation and seed-to-voxel rsFC analyses. We explored the effects of childhood abuse and recent stress on the structure and function of the regions of interest within general linear models. Worse psychiatric symptoms were significantly related to higher levels of life time stress. Individuals with mismatched childhood and recent stress levels had reduced left hippocampal volume, reduced ACC-ventrolateral prefrontal cortex rsFC and greater ACC-hippocampus rsFC, compared to individuals with matched childhood and recent stress levels. These results show specific utility of the cumulative stress hypothesis in understanding psychiatric symptomatology and of the mismatch hypothesis in modelling hippocampal grey matter, prefrontal rsFC, and prefrontal-hippocampal rsFC. We provide novel evidence for the enduring impact of childhood abuse on stress reactivity in a clinical population, and demonstrate the distinct effects of stress in different systems. Hum Brain Mapp 38:2709-2721, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Atlas-based fuzzy connectedness segmentation and intensity nonuniformity correction applied to brain MRI.

PubMed

Zhou, Yongxin; Bai, Jing

2007-01-01

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

MRI in the assessment and monitoring of multiple sclerosis: an update on best practice

PubMed Central

Kaunzner, Ulrike W.; Gauthier, Susan A.

2017-01-01

Magnetic resonance imaging (MRI) has developed into the most important tool for the diagnosis and monitoring of multiple sclerosis (MS). Its high sensitivity for the evaluation of inflammatory and neurodegenerative processes in the brain and spinal cord has made it the most commonly used technique for the evaluation of patients with MS. Moreover, MRI has become a powerful tool for treatment monitoring, safety assessment as well as for the prognostication of disease progression. Clinically, the use of MRI has increased in the past couple decades as a result of improved technology and increased availability that now extends well beyond academic centers. Consequently, there are numerous studies supporting the role of MRI in the management of patients with MS. The aim of this review is to summarize the latest insights into the utility of MRI in MS. PMID:28607577

The virtual craniofacial patient: 3D jaw modeling and animation.

PubMed

Enciso, Reyes; Memon, Ahmed; Fidaleo, Douglas A; Neumann, Ulrich; Mah, James

2003-01-01

In this paper, we present new developments in the area of 3D human jaw modeling and animation. CT (Computed Tomography) scans have traditionally been used to evaluate patients with dental implants, assess tumors, cysts, fractures and surgical procedures. More recently this data has been utilized to generate models. Researchers have reported semi-automatic techniques to segment and model the human jaw from CT images and manually segment the jaw from MRI images. Recently opto-electronic and ultrasonic-based systems (JMA from Zebris) have been developed to record mandibular position and movement. In this research project we introduce: (1) automatic patient-specific three-dimensional jaw modeling from CT data and (2) three-dimensional jaw motion simulation using jaw tracking data from the JMA system (Zebris).

An MRI-Compatible Robotic System With Hybrid Tracking for MRI-Guided Prostate Intervention

PubMed Central

Krieger, Axel; Iordachita, Iulian I.; Guion, Peter; Singh, Anurag K.; Kaushal, Aradhana; Ménard, Cynthia; Pinto, Peter A.; Camphausen, Kevin; Fichtinger, Gabor

2012-01-01

This paper reports the development, evaluation, and first clinical trials of the access to the prostate tissue (APT) II system—a scanner independent system for magnetic resonance imaging (MRI)-guided transrectal prostate interventions. The system utilizes novel manipulator mechanics employing a steerable needle channel and a novel six degree-of-freedom hybrid tracking method, comprising passive fiducial tracking for initial registration and subsequent incremental motion measurements. Targeting accuracy of the system in prostate phantom experiments and two clinical human-subject procedures is shown to compare favorably with existing systems using passive and active tracking methods. The portable design of the APT II system, using only standard MRI image sequences and minimal custom scanner interfacing, allows the system to be easily used on different MRI scanners. PMID:22009867

Diffusion and perfusion weighted magnetic resonance imaging for tumor volume definition in radiotherapy of brain tumors.

PubMed

Guo, Lu; Wang, Gang; Feng, Yuanming; Yu, Tonggang; Guo, Yu; Bai, Xu; Ye, Zhaoxiang

2016-09-21

Accurate target volume delineation is crucial for the radiotherapy of tumors. Diffusion and perfusion magnetic resonance imaging (MRI) can provide functional information about brain tumors, and they are able to detect tumor volume and physiological changes beyond the lesions shown on conventional MRI. This review examines recent studies that utilized diffusion and perfusion MRI for tumor volume definition in radiotherapy of brain tumors, and it presents the opportunities and challenges in the integration of multimodal functional MRI into clinical practice. The results indicate that specialized and robust post-processing algorithms and tools are needed for the precise alignment of targets on the images, and comprehensive validations with more clinical data are important for the improvement of the correlation between histopathologic results and MRI parameter images.

Brain tissues volume measurements from 2D MRI using parametric approach

NASA Astrophysics Data System (ADS)

L'vov, A. A.; Toropova, O. A.; Litovka, Yu. V.

2018-04-01

The purpose of the paper is to propose a fully automated method of volume assessment of structures within human brain. Our statistical approach uses maximum interdependency principle for decision making process of measurements consistency and unequal observations. Detecting outliers performed using maximum normalized residual test. We propose a statistical model which utilizes knowledge of tissues distribution in human brain and applies partial data restoration for precision improvement. The approach proposes completed computationally efficient and independent from segmentation algorithm used in the application.

DCE-MRI: a review and applications in veterinary oncology.

PubMed

Boss, M Keara; Muradyan, N; Thrall, D E

2013-06-01

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is a functional imaging technique that assesses the physiology of tumour tissue by exploiting abnormal tumour microvasculature. Advances made through DCE-MRI include improvement in the diagnosis of cancer, optimization of treatment choices, assessment of treatment efficacy and non-invasive identification of prognostic information. DCE-MRI enables quantitative assessment of tissue vessel density, integrity, and permeability, and this information can be applied to study of angiogenesis, hypoxia and the evaluation of various biomarkers. Reproducibility of DCE-MRI results is important in determining the significance of observed changes in the parameters. As improvements are made towards the utility of DCE-MRI and interpreting biologic associations, the technique will be applied more frequently in the study of cancer in animals. Given the importance of tumour perfusion with respect to tumour oxygenation and drug delivery, the use of DCE-MRI is a convenient and powerful way to gain basic information about a tumour. © 2011 John Wiley & Sons Ltd.

A Comparative Study of Average, Linked Mastoid, and REST References for ERP Components Acquired during fMRI

PubMed Central

Yang, Ping; Fan, Chenggui; Wang, Min; Li, Ling

2017-01-01

In simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) studies, average reference (AR), and digitally linked mastoid (LM) are popular re-referencing techniques in event-related potential (ERP) analyses. However, they may introduce their own physiological signals and alter the EEG/ERP outcome. A reference electrode standardization technique (REST) that calculated a reference point at infinity was proposed to solve this problem. To confirm the advantage of REST in ERP analyses of synchronous EEG-fMRI studies, we compared the reference effect of AR, LM, and REST on task-related ERP results of a working memory task during an fMRI scan. As we hypothesized, we found that the adopted reference did not change the topography map of ERP components (N1 and P300 in the present study), but it did alter the task-related effect on ERP components. LM decreased or eliminated the visual working memory (VWM) load effect on P300, and the AR distorted the distribution of VWM location-related effect at left posterior electrodes as shown in the statistical parametric scalp mapping (SPSM) of N1. ERP cortical source estimates, which are independent of the EEG reference choice, were used as the golden standard to infer the relative utility of different references on the ERP task-related effect. By comparison, REST reference provided a more integrated and reasonable result. These results were further confirmed by the results of fMRI activations and a corresponding EEG-only study. Thus, we recommend the REST, especially with a realistic head model, as the optimal reference method for ERP data analysis in simultaneous EEG-fMRI studies. PMID:28529472

Using pre-operative MRI to predict intraoperative hamstring graft size for anterior cruciate ligament reconstruction.

PubMed

Leiter, Jeff; Elkurbo, Mohamed; McRae, Sheila; Chiu, James; Froese, Warren; MacDonald, Peter

2017-01-01

Large variation in tendon size between individuals makes hamstring graft diameter for anterior cruciate ligament (ACL) reconstruction unpredictable. Inadequate graft diameter may necessitate an alternative source of tissue requiring pre-operative planning. The purpose of this study was to determine whether magnetic resonance image (MRI) measurements and clinical anthropometric data are predictive of hamstring tendon graft diameter. Data from 109 patients having ACL reconstruction with semitendinosus-gracilis (STGT) autograft were retrospectively evaluated. Cross-sectional area (CSA) of the gracilis tendon (GT) and semitendinosus tendon (ST) were determined from pre-operative MRI scans. Variables included pre-operative height, weight, body mass index (BMI), age and gender; and intra-operative graft diameter. Correlations between anthropometric variables, hamstring tendons CSA and intra-operative graft diameter were calculated. Multiple stepwise regression was performed to assess the predictive value of these variables to graft diameter. Sensitivity and specificity were calculated to evaluate the utility of MRI CSA measurements in accurately identifying inadequate graft diameter (<8 mm). All anthropometric variables were positively correlated with intraoperative graft diameter (p < 0.01). Semitendinosus-gracilis tendon CSA (p < 0.001) and STGT CSA and weight (p < 0.001) were significantly predictive models of graft diameter. Sensitivity and specificity were 79 and 74 %, respectively. The strongest indicators of a four-stranded STGT graft for primary ACL reconstruction were STGT CSA on MRI plus weight. Measurement of graft diameter can be performed pre-operatively via MRI to identify tendons that may be of inadequate size for ACL reconstruction. This can assist with surgical planning to determine the most appropriate graft choice. III.

A Comparative Study of Average, Linked Mastoid, and REST References for ERP Components Acquired during fMRI.

PubMed

Yang, Ping; Fan, Chenggui; Wang, Min; Li, Ling

2017-01-01

In simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) studies, average reference (AR), and digitally linked mastoid (LM) are popular re-referencing techniques in event-related potential (ERP) analyses. However, they may introduce their own physiological signals and alter the EEG/ERP outcome. A reference electrode standardization technique (REST) that calculated a reference point at infinity was proposed to solve this problem. To confirm the advantage of REST in ERP analyses of synchronous EEG-fMRI studies, we compared the reference effect of AR, LM, and REST on task-related ERP results of a working memory task during an fMRI scan. As we hypothesized, we found that the adopted reference did not change the topography map of ERP components (N1 and P300 in the present study), but it did alter the task-related effect on ERP components. LM decreased or eliminated the visual working memory (VWM) load effect on P300, and the AR distorted the distribution of VWM location-related effect at left posterior electrodes as shown in the statistical parametric scalp mapping (SPSM) of N1. ERP cortical source estimates, which are independent of the EEG reference choice, were used as the golden standard to infer the relative utility of different references on the ERP task-related effect. By comparison, REST reference provided a more integrated and reasonable result. These results were further confirmed by the results of fMRI activations and a corresponding EEG-only study. Thus, we recommend the REST, especially with a realistic head model, as the optimal reference method for ERP data analysis in simultaneous EEG-fMRI studies.

Evaluation of intervertebral disc cartilaginous endplate structure using magnetic resonance imaging.

PubMed

Moon, Sung M; Yoder, Jonathon H; Wright, Alexander C; Smith, Lachlan J; Vresilovic, Edward J; Elliott, Dawn M

2013-08-01

The cartilaginous endplate (CEP) is a thin layer of hyaline cartilage positioned between the vertebral endplate and nucleus pulposus (NP) that functions both as a mechanical barrier and as a gateway for nutrient transport into the disc. Despite its critical role in disc nutrition and degeneration, the morphology of the CEP has not been well characterized. The objective of this study was to visualize and report observations of the CEP three-dimensional morphology, and quantify CEP thickness using an MRI FLASH (fast low-angle shot) pulse sequence. MR imaging of ex vivo human cadaveric lumbar spine segments (N = 17) was performed in a 7T MRI scanner with sequence parameters that were selected by utilizing high-resolution T1 mapping, and an analytical MRI signal model to optimize image contrast between CEP and NP. The CEP thickness at five locations along the mid-sagittal AP direction (center, 5 mm, 10 mm off-center towards anterior and posterior) was measured, and analyzed using two-way ANOVA and a post hoc Bonferonni test. For further investigation, six in vivo volunteers were imaged with a similar sequence in a 3T MRI scanner. In addition, decalcified and undecalcified histology was performed, which confirmed that the FLASH sequence successfully detected the CEP. CEP thickness determined by MRI in the mid-sagittal plane across all lumbar disc levels and locations was 0.77 ± 0.24 mm ex vivo. The CEP thickness was not different across disc levels, but was thinner toward the center of the disc. This study demonstrates the potential of MRI FLASH imaging for structural quantification of the CEP geometry, which may be developed as a technique to evaluate changes in the CEP with disc degeneration in future applications.

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.

Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model.

PubMed

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

2017-02-01

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

Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model

PubMed Central

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

2017-01-01

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

Life cycle costing as a decision making tool for technology acquisition in radio-diagnosis

PubMed Central

Chakravarty, Abhijit; Debnath, Jyotindu

2014-01-01

Background Life cycle costing analysis is an emerging conceptual tool to validate capital investment in healthcare. Methods A preliminary study was done to analyze the long-term cost impact of acquiring a new 3 T MRI system when compared to technological upgradation of the existing 1.5 T MRI system with a view to evolve a decision matrix for correct investment planning and technology management. Operating costing method was utilized to estimate cost per unit MRI scan, costing inputs were considered for the existing 1.5 T and the proposed 3 T machine. Cost for each expected year in the life span of both 1.5 T and 3 T MRI scan options were then discounted to its Net Present Value. Net Present Value thus calculated for both the alternative options of 1.5 T and 3 T MRI machine was charted along with various intangible but critical Figures of Merit (FOM) to create a decision matrix for capital investment planning. Result Considering all fixed and variable costs contributing towards assumed operation, unit cost per MRI procedure was found to be Rs. 4244.58 for the 1.5 T upgrade and Rs. 6059.37 for the new 3 T MRI machine. Life Cycle Cost Analysis of the proposed 1.5 T upgrade and new 3 T machine showed a Net Present Value of Rs. 42,148,587.80 and Rs. 27,587,842.38 respectively. Conclusion The utility of life cycle costing as a strategic decision making tool towards evaluating alternative options for capital investment planning in health care environment is reiterated. PMID:25609862

Biology and therapy of fibromyalgia. Functional magnetic resonance imaging findings in fibromyalgia

PubMed Central

Williams, David A; Gracely, Richard H

2006-01-01

Techniques in neuroimaging such as functional magnetic resonance imaging (fMRI) have helped to provide insights into the role of supraspinal mechanisms in pain perception. This review focuses on studies that have applied fMRI in an attempt to gain a better understanding of the mechanisms involved in the processing of pain associated with fibromyalgia. This article provides an overview of the nociceptive system as it functions normally, reviews functional brain imaging methods, and integrates the existing literature utilizing fMRI to study central pain mechanisms in fibromyalgia. PMID:17254318

Emotion Regulation Training for Training Warfighters with Combat Related PTSD Using Real Time fMRI and EEG Assisted Neurofeedback

DTIC Science & Technology

2016-10-01

AWARD NUMBER: W81XWH-12-1-0607 TITLE: Emotion Regulation Training for Treating Warfighters with Combat-Related PTSD Using Real -Time fMRI...Related PTSD Using Real -Time fMRI and EEG-Assisted Neurofeedback 5a. CONTRACT NUMBER W81XWH-12-1-0607 5b. GRANT NUMBER PT110256 5c. PROGRAM ELEMENT...emphasize dysregulation of the amygdala, which is involved in the regulation of PTSD-relevant emotions. We are utilizing real -time functional magnetic

Framework for 3D histologic reconstruction and fusion with in vivo MRI: Preliminary results of characterizing pulmonary inflammation in a mouse model

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

Rusu, Mirabela, E-mail: mirabela.rusu@gmail.com; Wang, Haibo; Madabhushi, Anant

Purpose: Pulmonary inflammation is associated with a variety of diseases. Assessing pulmonary inflammation on in vivo imaging may facilitate the early detection and treatment of lung diseases. Although routinely used in thoracic imaging, computed tomography has thus far not been compellingly shown to characterize inflammation in vivo. Alternatively, magnetic resonance imaging (MRI) is a nonionizing radiation technique to better visualize and characterize pulmonary tissue. Prior to routine adoption of MRI for early characterization of inflammation in humans, a rigorous and quantitative characterization of the utility of MRI to identify inflammation is required. Such characterization may be achieved by considering exmore » vivo histology as the ground truth, since it enables the definitive spatial assessment of inflammation. In this study, the authors introduce a novel framework to integrate 2D histology, ex vivo and in vivo imaging to enable the mapping of the extent of disease from ex vivo histology onto in vivo imaging, with the goal of facilitating computerized feature analysis and interrogation of disease appearance on in vivo imaging. The authors’ framework was evaluated in a preclinical preliminary study aimed to identify computer extracted features on in vivo MRI associated with chronic pulmonary inflammation. Methods: The authors’ image analytics framework first involves reconstructing the histologic volume in 3D from individual histology slices. Second, the authors map the disease ground truth onto in vivo MRI via coregistration with 3D histology using the ex vivo lung MRI as a conduit. Finally, computerized feature analysis of the disease extent is performed to identify candidate in vivo imaging signatures of disease presence and extent. Results: The authors evaluated the framework by assessing the quality of the 3D histology reconstruction and the histology—MRI fusion, in the context of an initial use case involving characterization of chronic inflammation in a mouse model. The authors’ evaluation considered three mice, two with an inflammation phenotype and one control. The authors’ iterative 3D histology reconstruction yielded a 70.1% ± 2.7% overlap with the ex vivo MRI volume. Across a total of 17 anatomic landmarks manually delineated at the division of airways, the target registration error between the ex vivo MRI and 3D histology reconstruction was 0.85 ± 0.44 mm, suggesting that a good alignment of the ex vivo 3D histology and ex vivo MRI had been achieved. The 3D histology-in vivo MRI coregistered volumes resulted in an overlap of 73.7% ± 0.9%. Preliminary computerized feature analysis was performed on an additional four control mice, for a total of seven mice considered in this study. Gabor texture filters appeared to best capture differences between the inflamed and noninflamed regions on MRI. Conclusions: The authors’ 3D histology reconstruction and multimodal registration framework were successfully employed to reconstruct the histology volume of the lung and fuse it with in vivo MRI to create a ground truth map for inflammation on in vivo MRI. The analytic platform presented here lays the framework for a rigorous validation of the identified imaging features for chronic lung inflammation on MRI in a large prospective cohort.« less

Towards a neural circuit model of verbal humor processing: an fMRI study of the neural substrates of incongruity detection and resolution.

PubMed

Chan, Yu-Chen; Chou, Tai-Li; Chen, Hsueh-Chih; Yeh, Yu-Chu; Lavallee, Joseph P; Liang, Keng-Chen; Chang, Kuo-En

2013-02-01

The present study builds on our previous study within the framework of Wyer and Collin's comprehension-elaboration theory of humor processing. In this study, an attempt is made to segregate the neural substrates of incongruity detection and incongruity resolution during the comprehension of verbal jokes. Although a number of fMRI studies have investigated the incongruity-resolution process, the differential neurological substrates of comprehension are still not fully understood. The present study utilized an event-related fMRI design incorporating three conditions (unfunny, nonsensical and funny) to examine distinct brain regions associated with the detection and resolution of incongruities. Stimuli in the unfunny condition contained no incongruities; stimuli in the nonsensical condition contained irresolvable incongruities; and stimuli in the funny condition contained resolvable incongruities. The results showed that the detection of incongruities was associated with greater activation in the right middle temporal gyrus and right medial frontal gyrus, and the resolution of incongruities with greater activation in the left superior frontal gyrus and left inferior parietal lobule. Further analysis based on participants' rating scores provided converging results. Our findings suggest a three-stage neural circuit model of verbal humor processing: incongruity detection and incongruity resolution during humor comprehension and inducement of the feeling of amusement during humor elaboration. Copyright © 2012 Elsevier Inc. All rights reserved.

Phenotypic characterization of the Komeda miniature rat Ishikawa, an animal model of dwarfism caused by a mutation in Prkg2.

PubMed

Tsuchida, Atsuko; Yokoi, Norihide; Namae, Misako; Fuse, Masanori; Masuyama, Taku; Sasaki, Masashi; Kawazu, Shoji; Komeda, Kajuro

2008-12-01

The Komeda miniature rat Ishikawa (KMI) is a spontaneous animal model of dwarfism caused by a mutation in Prkg2, which encodes cGMP-dependent protein kinase type II (cGKII). This strain has been maintained as a segregating inbred strain for the mutated allele mri. In this study, we characterized the phenotype of the KMI strain, particularly growth traits, craniofacial measurements, and organ weights. The homozygous mutant (mri/mri) animals were approximately 70% to 80% of the size of normal, heterozygous (mri/+) animals in regard to body length, weight, and naso-occipital length of the calvarium, and the retroperitoneal fat of mri/mri rats was reduced greatly. In addition, among progeny of the (BNxKMI-mri/mri)F1xKMI-mri/mri backcross, animals with the KMI phenotype (mri/mri) were easily distinguished from those showing the wild-type phenotype (mri/+) by using growth traits such as body length and weight. Genetic analysis revealed that all of the backcrossed progeny exhibiting the KMI phenotype were homozygous for the KMI allele in the 1.2-cM region between D14Rat5 and D14Rat80 on chromosome 14, suggesting strongly that mri acts in a completely recessive manner. The KMI strain is the first and only rat model with a confirmed mutation in Prkg2 and is a valuable model for studying dwarfism and longitudinal growth traits in humans and for functional studies of cGKII.

Phenotypic Characterization of the Komeda Miniature Rat Ishikawa, an Animal Model of Dwarfism Caused by a Mutation in Prkg2

PubMed Central

Tsuchida, Atsuko; Yokoi, Norihide; Namae, Misako; Fuse, Masanori; Masuyama, Taku; Sasaki, Masashi; Kawazu, Shoji; Komeda, Kajuro

2008-01-01

The Komeda miniature rat Ishikawa (KMI) is a spontaneous animal model of dwarfism caused by a mutation in Prkg2, which encodes cGMP-dependent protein kinase type II (cGKII). This strain has been maintained as a segregating inbred strain for the mutated allele mri. In this study, we characterized the phenotype of the KMI strain, particularly growth traits, craniofacial measurements, and organ weights. The homozygous mutant (mri/mri) animals were approximately 70% to 80% of the size of normal, heterozygous (mri/+) animals in regard to body length, weight, and naso-occipital length of the calvarium, and the retroperitoneal fat of mri/mri rats was reduced greatly. In addition, among progeny of the (BN×KMI-mri/mri)F1×KMI-mri/mri backcross, animals with the KMI phenotype (mri/mri) were easily distinguished from those showing the wild-type phenotype (mri/+) by using growth traits such as body length and weight. Genetic analysis revealed that all of the backcrossed progeny exhibiting the KMI phenotype were homozygous for the KMI allele in the 1.2-cM region between D14Rat5 and D14Rat80 on chromosome 14, suggesting strongly that mri acts in a completely recessive manner. The KMI strain is the first and only rat model with a confirmed mutation in Prkg2 and is a valuable model for studying dwarfism and longitudinal growth traits in humans and for functional studies of cGKII. PMID:19149413

WE-EF-BRD-00: New Developments in Hybrid MR-Treatment: Applications

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

NONE

2015-06-15

MRI-guided treatment is a growing area of medicine, particularly in radiotherapy and surgery. The exquisite soft tissue anatomic contrast offered by MRI, along with functional imaging, makes the use of MRI during therapeutic procedures very attractive. Challenging the utility of MRI in the therapy room are many issues including the physics of MRI and the impact on the environment and therapeutic instruments, the impact of the room and instruments on the MRI; safety, space, design and cost. In this session, the applications and challenges of MRI-guided treatment will be described. The session format is: Past, present and future: MRI-guided radiotherapymore » from 2005 to 2025: Jan Lagendijk Battling Maxwell’s equations: Physics challenges and solutions for hybrid MRI systems: Paul Keall I want it now!: Advances in MRI acquisition, reconstruction and the use of priors to enable fast anatomic and physiologic imaging to inform guidance and adaptation decisions: Yanle Hu MR in the OR: The growth and applications of MRI for interventional radiology and surgery: Rebecca Fahrig Learning Objectives: To understand the history and trajectory of MRI-guided radiotherapy To understand the challenges of integrating MR imaging systems with linear accelerators To understand the latest in fast MRI methods to enable the visualisation of anatomy and physiology on radiotherapy treatment timescales To understand the growing role and challenges of MRI for image-guided surgical procedures My disclosures are publicly available and updated at: http://sydney.edu.au/medicine/radiation-physics/about-us/disclosures.php.« less

Right ventricular functional analysis utilizing first pass radionuclide angiography for pre-operative ventricular assist device planning: a multi-modality comparison.

PubMed

Avery, Ryan; Day, Kevin; Jokerst, Clinton; Kazui, Toshinobu; Krupinski, Elizabeth; Khalpey, Zain

2017-10-10

Advanced heart failure treated with a left ventricular assist device is associated with a higher risk of right heart failure. Many advanced heart failures patients are treated with an ICD, a relative contraindication to MRI, prior to assist device placement. Given this limitation, left and right ventricular function for patients with an ICD is calculated using radionuclide angiography utilizing planar multigated acquisition (MUGA) and first pass radionuclide angiography (FPRNA), respectively. Given the availability of MRI protocols that can accommodate patients with ICDs, we have correlated the findings of ventricular functional analysis using radionuclide angiography to cardiac MRI, the reference standard for ventricle function calculation, to directly correlate calculated ejection fractions between these modalities, and to also assess agreement between available echocardiographic and hemodynamic parameters of right ventricular function. A retrospective review from January 2012 through May 2014 was performed to identify advanced heart failure patients who underwent both cardiac MRI and radionuclide angiography for ventricular functional analysis. Nine heart failure patients (8 men, 1 woman; mean age of 57.0 years) were identified. The average time between the cardiac MRI and radionuclide angiography exams was 38.9 days (range: 1 - 119 days). All patients undergoing cardiac MRI were scanned using an institutionally approved protocol for ICD with no device-related complications identified. A retrospective chart review of each patient for cardiomyopathy diagnosis, clinical follow-up, and echocardiogram and right heart catheterization performed during evaluation was also performed. The 9 patients demonstrated a mean left ventricular ejection fraction (LVEF) using cardiac MRI of 20.7% (12 - 40%). Mean LVEF using MUGA was 22.6% (12 - 49%). The mean right ventricular ejection fraction (RVEF) utilizing cardiac MRI was 28.3% (16 - 43%), and the mean RVEF calculated by FPRNA was 32.6% (9 - 56%). The mean discrepancy for LVEF between cardiac MRI and MUGA was 4.1% (0 - 9%), and correlation of calculated LVEF using cardiac MRI and MUGA demonstrated an R of 0.9. The mean discrepancy for RVEF between cardiac MRI and FPRNA was 12.0% (range: 2 - 24%) with a moderate correlation (R = 0.5). The increased discrepancies for RV analysis were statistically significant using an unpaired t-test (t = 3.19, p = 0.0061). Echocardiogram parameters of RV function, including TAPSE and FAC, were for available for all 9 patients and agreement with cardiac MRI demonstrated a kappa statistic for TAPSE of 0.39 (95% CI of 0.06 - 0.72) and for FAC of 0.64 (95% of 0.21 - 1.00). Heart failure patients are increasingly requiring left ventricular assist device placement; however, definitive evaluation of biventricular function is required due to the increased mortality rate associated with right heart failure after assist device placement. Our results suggest that FPRNA only has a moderate correlation with reference standard RVEFs calculated using cardiac MRI, which was similar to calculated agreements between cardiac MRI and echocardiographic parameters of right ventricular function. Given the need for identification of patients at risk for right heart failure, further studies are warranted to determine a more accurate estimate of RVEF for heart failure patients during pre-operative ventricular assist device planning.

Active appearance model and deep learning for more accurate prostate segmentation on MRI

NASA Astrophysics Data System (ADS)

Cheng, Ruida; Roth, Holger R.; Lu, Le; Wang, Shijun; Turkbey, Baris; Gandler, William; McCreedy, Evan S.; Agarwal, Harsh K.; Choyke, Peter; Summers, Ronald M.; McAuliffe, Matthew J.

2016-03-01

Prostate segmentation on 3D MR images is a challenging task due to image artifacts, large inter-patient prostate shape and texture variability, and lack of a clear prostate boundary specifically at apex and base levels. We propose a supervised machine learning model that combines atlas based Active Appearance Model (AAM) with a Deep Learning model to segment the prostate on MR images. The performance of the segmentation method is evaluated on 20 unseen MR image datasets. The proposed method combining AAM and Deep Learning achieves a mean Dice Similarity Coefficient (DSC) of 0.925 for whole 3D MR images of the prostate using axial cross-sections. The proposed model utilizes the adaptive atlas-based AAM model and Deep Learning to achieve significant segmentation accuracy.

Protostellar Disk Evolution over Million-year Timescales with a Prescription for Magnetized Turbulence

NASA Astrophysics Data System (ADS)

Landry, Russell; Dodson-Robinson, Sarah E.; Turner, Neal J.; Abram, Greg

2013-07-01

Magnetorotational instability (MRI) is the most promising mechanism behind accretion in low-mass protostellar disks. Here we present the first analysis of the global structure and evolution of non-ideal MRI-driven T-Tauri disks on million-year timescales. We accomplish this in a 1+1D simulation by calculating magnetic diffusivities and utilizing turbulence activity criteria to determine thermal structure and accretion rate without resorting to a three-dimensional magnetohydrodynamical (MHD) simulation. Our major findings are as follows. First, even for modest surface densities of just a few times the minimum-mass solar nebula, the dead zone encompasses the giant planet-forming region, preserving any compositional gradients. Second, the surface density of the active layer is nearly constant in time at roughly 10 g cm-2, which we use to derive a simple prescription for viscous heating in MRI-active disks for those who wish to avoid detailed MHD computations. Furthermore, unlike a standard disk with constant-α viscosity, the disk midplane does not cool off over time, though the surface cools as the star evolves along the Hayashi track. Instead, the MRI may pile material in the dead zone, causing it to heat up over time. The ice line is firmly in the terrestrial planet-forming region throughout disk evolution and can move either inward or outward with time, depending on whether pileups form near the star. Finally, steady-state mass transport is an extremely poor description of flow through an MRI-active disk, as we see both the turnaround in the accretion flow required by conservation of angular momentum and peaks in \\dot{M}(R) bracketing each side of the dead zone. We caution that MRI activity is sensitive to many parameters, including stellar X-ray flux, grain size, gas/small grain mass ratio and magnetic field strength, and we have not performed an exhaustive parameter study here. Our 1+1D model also does not include azimuthal information, which prevents us from modeling the effects of Rossby waves.

PROTOSTELLAR DISK EVOLUTION OVER MILLION-YEAR TIMESCALES WITH A PRESCRIPTION FOR MAGNETIZED TURBULENCE

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

Landry, Russell; Dodson-Robinson, Sarah E.; Turner, Neal J.

2013-07-10

Magnetorotational instability (MRI) is the most promising mechanism behind accretion in low-mass protostellar disks. Here we present the first analysis of the global structure and evolution of non-ideal MRI-driven T-Tauri disks on million-year timescales. We accomplish this in a 1+1D simulation by calculating magnetic diffusivities and utilizing turbulence activity criteria to determine thermal structure and accretion rate without resorting to a three-dimensional magnetohydrodynamical (MHD) simulation. Our major findings are as follows. First, even for modest surface densities of just a few times the minimum-mass solar nebula, the dead zone encompasses the giant planet-forming region, preserving any compositional gradients. Second, themore » surface density of the active layer is nearly constant in time at roughly 10 g cm{sup -2}, which we use to derive a simple prescription for viscous heating in MRI-active disks for those who wish to avoid detailed MHD computations. Furthermore, unlike a standard disk with constant-{alpha} viscosity, the disk midplane does not cool off over time, though the surface cools as the star evolves along the Hayashi track. Instead, the MRI may pile material in the dead zone, causing it to heat up over time. The ice line is firmly in the terrestrial planet-forming region throughout disk evolution and can move either inward or outward with time, depending on whether pileups form near the star. Finally, steady-state mass transport is an extremely poor description of flow through an MRI-active disk, as we see both the turnaround in the accretion flow required by conservation of angular momentum and peaks in M-dot (R) bracketing each side of the dead zone. We caution that MRI activity is sensitive to many parameters, including stellar X-ray flux, grain size, gas/small grain mass ratio and magnetic field strength, and we have not performed an exhaustive parameter study here. Our 1+1D model also does not include azimuthal information, which prevents us from modeling the effects of Rossby waves.« less

Computational dosimetry of induced electric fields during realistic movements in the vicinity of a 3 T MRI scanner

NASA Astrophysics Data System (ADS)

Laakso, Ilkka; Kännälä, Sami; Jokela, Kari

2013-04-01

Medical staff working near magnetic resonance imaging (MRI) scanners are exposed both to the static magnetic field itself and also to electric currents that are induced in the body when the body moves in the magnetic field. However, there are currently limited data available on the induced electric field for realistic movements. This study computationally investigates the movement induced electric fields for realistic movements in the magnetic field of a 3 T MRI scanner. The path of movement near the MRI scanner is based on magnetic field measurements using a coil sensor attached to a human volunteer. Utilizing realistic models for both the motion of the head and the magnetic field of the MRI scanner, the induced fields are computationally determined using the finite-element method for five high-resolution numerical anatomical models. The results show that the time-derivative of the magnetic flux density (dB/dt) is approximately linearly proportional to the induced electric field in the head, independent of the position of the head with respect to the magnet. This supports the use of dB/dt measurements for occupational exposure assessment. For the path of movement considered herein, the spatial maximum of the induced electric field is close to the basic restriction for the peripheral nervous system and exceeds the basic restriction for the central nervous system in the international guidelines. The 99th percentile electric field is a considerably less restrictive metric for the exposure than the spatial maximum electric field; the former is typically 60-70% lower than the latter. However, the 99th percentile electric field may exceed the basic restriction for dB/dt values that can be encountered during tasks commonly performed by MRI workers. It is also shown that the movement-induced eddy currents may reach magnitudes that could electrically stimulate the vestibular system, which could play a significant role in the generation of vertigo-like sensations reported by people moving in a strong static magnetic field.

Effect of disease progression on liver apparent diffusion coefficient and T2 values in a murine model of hepatic fibrosis at 11.7 Tesla MRI.

PubMed

Anderson, Stephan W; Jara, Hernan; Ozonoff, Al; O'Brien, Michael; Hamilton, James A; Soto, Jorge A

2012-01-01

To evaluate the effects of hepatic fibrosis on ADC and T(2) values of ex vivo murine liver specimens imaged using 11.7 Tesla (T) MRI. This animal study was IACUC approved. Seventeen male, C57BL/6 mice were divided into control (n = 2) and experimental groups (n = 15), the latter fed a 3, 5-dicarbethoxy-1, 4-dihydrocollidine (DDC) supplemented diet, inducing hepatic fibrosis. Ex vivo liver specimens were imaged using an 11.7T MRI scanner. Spin-echo pulsed field gradient and multi-echo spin-echo acquisitions were used to generate parametric ADC and T(2) maps, respectively. Degrees of fibrosis were determined by the evaluation of a pathologist as well as digital image analysis. Scatterplot graphs comparing ADC and T(2) to degrees of fibrosis were generated and correlation coefficients were calculated. Strong correlation was found between degrees of hepatic fibrosis and ADC with higher degrees of fibrosis associated with lower hepatic ADC values. Moderate correlation between hepatic fibrosis and T(2) values was seen with higher degrees of fibrosis associated with lower T(2) values. Inverse relationships between degrees of fibrosis and both ADC and T(2) are seen, highlighting the utility of these parameters in the ongoing development of an MRI methodology to quantify hepatic fibrosis. Copyright © 2011 Wiley Periodicals, Inc.

Bayesian uncertainty quantification in linear models for diffusion MRI.

PubMed

Sjölund, Jens; Eklund, Anders; Özarslan, Evren; Herberthson, Magnus; Bånkestad, Maria; Knutsson, Hans

2018-03-29

Diffusion MRI (dMRI) is a valuable tool in the assessment of tissue microstructure. By fitting a model to the dMRI signal it is possible to derive various quantitative features. Several of the most popular dMRI signal models are expansions in an appropriately chosen basis, where the coefficients are determined using some variation of least-squares. However, such approaches lack any notion of uncertainty, which could be valuable in e.g. group analyses. In this work, we use a probabilistic interpretation of linear least-squares methods to recast popular dMRI models as Bayesian ones. This makes it possible to quantify the uncertainty of any derived quantity. In particular, for quantities that are affine functions of the coefficients, the posterior distribution can be expressed in closed-form. We simulated measurements from single- and double-tensor models where the correct values of several quantities are known, to validate that the theoretically derived quantiles agree with those observed empirically. We included results from residual bootstrap for comparison and found good agreement. The validation employed several different models: Diffusion Tensor Imaging (DTI), Mean Apparent Propagator MRI (MAP-MRI) and Constrained Spherical Deconvolution (CSD). We also used in vivo data to visualize maps of quantitative features and corresponding uncertainties, and to show how our approach can be used in a group analysis to downweight subjects with high uncertainty. In summary, we convert successful linear models for dMRI signal estimation to probabilistic models, capable of accurate uncertainty quantification. Copyright © 2018 Elsevier Inc. All rights reserved.

Induction and imaging of photothrombotic stroke in conscious and freely moving rats

NASA Astrophysics Data System (ADS)

Lu, Hongyang; Li, Yao; Yuan, Lu; Li, Hangdao; Lu, Xiaodan; Tong, Shanbao

2014-09-01

In experimental stroke research, anesthesia is common and serves as a major reason for translational failure. Real-time cerebral blood flow (CBF) monitoring during stroke onset can provide important information for the prediction of brain injury; however, this is difficult to achieve in clinical practice due to various technical problems. We created a photothrombotic focal ischemic stroke model utilizing our self-developed miniature headstage in conscious and freely moving rats. In this model, a high spatiotemporal resolution imager using laser speckle contrast imaging technology was integrated to acquire real-time two-dimensional CBF information during thrombosis. The feasibility, stability, and reliability of the system were tested in terms of CBF, behavior, and T2-weighted magnetic resonance imaging (MRI) findings. After completion of occlusion, the CBF in the targeted cortex of the stroke group was reduced to 16±9% of the baseline value. The mean infarct volume measured by MRI 24 h postmodeling was 77±11 mm3 and correlated well with CBF (R2=0.74). This rodent model of focal cerebral ischemia and real-time blood flow imaging opens the possibility of performing various fundamental and translational studies on stroke without the influence of anesthetics.

Generalized cerebral atrophy seen on MRI in a naturally exposed animal model for creutzfeldt-jakob disease

PubMed Central

2010-01-01

Background Magnetic resonance imaging has been used in the diagnosis of human prion diseases such as sCJD and vCJD, but patients are scanned only when clinical signs appear, often at the late stage of disease. This study attempts to answer the questions "Could MRI detect prion diseases before clinical symptoms appear?, and if so, with what confidence?" Methods Scrapie, the prion disease of sheep, was chosen for the study because sheep can fit into a human sized MRI scanner (and there were no large animal MRI scanners at the time of this study), and because the USDA had, at the time of the study, a sizeable sample of scrapie exposed sheep, which we were able to use for this purpose. 111 genetically susceptible sheep that were naturally exposed to scrapie were used in this study. Results Our MRI findings revealed no clear, consistent hyperintense or hypointense signal changes in the brain on either clinically affected or asymptomatic positive animals on any sequence. However, in all 37 PrPSc positive sheep (28 asymptomatic and 9 symptomatic), there was a greater ventricle to cerebrum area ratio on MRI compared to 74 PrPSc negative sheep from the scrapie exposed flock and 6 control sheep from certified scrapie free flocks as defined by immunohistochemistry (IHC). Conclusions Our findings indicate that MRI imaging can detect diffuse cerebral atrophy in asymptomatic and symptomatic sheep infected with scrapie. Nine of these 37 positive sheep, including 2 one-year old animals, were PrPSc positive only in lymph tissues but PrPSc negative in the brain. This suggests either 1) that the cerebral atrophy/neuronal loss is not directly related to the accumulation of PrPSc within the brain or 2) that the amount of PrPSc in the brain is below the detectable limits of the utilized immunohistochemistry assay. The significance of these findings remains to be confirmed in human subjects with CJD. PMID:21108848

Utility of STIR MRI in pediatric cervical spine clearance after trauma.

PubMed

Henry, Mark; Scarlata, Katherine; Riesenburger, Ron I; Kryzanski, James; Rideout, Leslie; Samdani, Amer; Jea, Andrew; Hwang, Steven W

2013-07-01

Although MRI with short-term T1 inversion recovery (STIR) sequencing has been widely adopted in the clearance of cervical spine in adults who have sustained trauma, its applicability for cervical spine clearance in pediatric trauma patients remains unclear. The authors sought to review a Level 1 trauma center's experience using MRI for posttraumatic evaluation of the cervical spine in pediatric patients. A pediatric trauma database was retrospectively queried for patients who received an injury warranting radiographic imaging of the cervical spine and had a STIR-MRI sequence of the cervical spine performed within 48 hours of injury between 2002 and 2011. Demographic, radiographic, and outcome data were retrospectively collected through medical records. Seventy-three cases were included in the analysis. The mean duration of follow-up was 10 months (range 4 days-7 years). The mean age of the patients at the time of trauma evaluation was 8.3 ± 5.8 years, and 65% were male. The majority of patients were involved in a motor vehicle accident. In 70 cases, the results of MRI studies were negative, and the patients were cleared prior to discharge with no clinical suggestion of instability on follow-up. In 3 cases, the MRI studies had abnormal findings; 2 of these 3 patients were cleared with dynamic radiographs during the same admission. Only 1 patient had an unstable injury and required surgical stabilization. The sensitivity of STIR MRI to detect cervical instability was 100% with a specificity of 97%. The positive predictive value was 33% and the negative predictive value was 100%. Although interpretation of our results are diminished by limitations of the study, in our series, STIR MRI in routine screening for pediatric cervical trauma had a high sensitivity and slightly lower specificity, but may have utility in future practices and should be considered for implementation into protocols.

Utility of Neurodiagnostic Studies in the Diagnosis of Autoimmune Encephalitis in Children.

PubMed

Albert, Dara V; Pluto, Charles P; Weber, Amanda; Vidaurre, Jorge; Barbar-Smiley, Fatima; Abdul Aziz, Rabheh; Driest, Kyla; Bout-Tabaku, Sharon; Ruess, Lynne; Rusin, Jerome A; Morgan-Followell, Bethanie

2016-02-01

Autoimmune encephalitis is currently a clinical diagnosis without widely accepted diagnostic criteria, often leading to a delay in diagnosis. The utility of magnetic resonance imaging (MRI) and electroencephalography (EEG) in this disease is unknown. The objective of this study was to identify disease-specific patterns of neurodiagnostic studies (MRI and EEG) for autoimmune encephalitis in children. We completed a retrospective chart review of encephalopathic patients seen at a large pediatric hospital over a four year interval. Clinical presentation, autoantibody status, and MRI and EEG findings were identified and compared. Individuals with autoantibodies were considered "definite" cases, whereas those without antibodies or those with only thyroperoxidase antibodies were characterized as "suspected." Eighteen patients met the inclusion criteria and autoantibodies were identified in nine of these. The patients with definite autoimmune encephalitis had MRI abnormalities within limbic structures, most notably the anteromedial temporal lobes (56%). Only individuals with suspected disease had nontemporal lobe cortical lesions. Sixteen patients had an EEG and 13 (81%) of these were abnormal. The most common findings were abnormal background rhythm (63%), generalized slowing (50%), focal slowing (43%), and focal epileptiform discharges (31%). Sleep spindle abnormalities occurred in 38% of patients. There were no specific differences in the EEG findings between the definite and suspected cases. Focal EEG findings only correlated with a focal lesion on MRI in a single definite case. Pediatric patients with definite autoimmune encephalitis have a narrow spectrum of MRI abnormalities. Conversely, EEG abnormalities are mostly nonspecific. All patients in our cohort had abnormalities on one or both of these neurodiagnostic studies. Copyright © 2016 Elsevier Inc. All rights reserved.

Efficiency Improvement in a Busy Radiology Practice: Determination of Musculoskeletal Magnetic Resonance Imaging Protocol Using Deep-Learning Convolutional Neural Networks.

PubMed

Lee, Young Han

2018-04-04

The purposes of this study are to evaluate the feasibility of protocol determination with a convolutional neural networks (CNN) classifier based on short-text classification and to evaluate the agreements by comparing protocols determined by CNN with those determined by musculoskeletal radiologists. Following institutional review board approval, the database of a hospital information system (HIS) was queried for lists of MRI examinations, referring department, patient age, and patient gender. These were exported to a local workstation for analyses: 5258 and 1018 consecutive musculoskeletal MRI examinations were used for the training and test datasets, respectively. The subjects for pre-processing were routine or tumor protocols and the contents were word combinations of the referring department, region, contrast media (or not), gender, and age. The CNN Embedded vector classifier was used with Word2Vec Google news vectors. The test set was tested with each classification model and results were output as routine or tumor protocols. The CNN determinations were evaluated using the receiver operating characteristic (ROC) curves. The accuracies were evaluated by a radiologist-confirmed protocol as the reference protocols. The optimal cut-off values for protocol determination between routine protocols and tumor protocols was 0.5067 with a sensitivity of 92.10%, a specificity of 95.76%, and an area under curve (AUC) of 0.977. The overall accuracy was 94.2% for the ConvNet model. All MRI protocols were correct in the pelvic bone, upper arm, wrist, and lower leg MRIs. Deep-learning-based convolutional neural networks were clinically utilized to determine musculoskeletal MRI protocols. CNN-based text learning and applications could be extended to other radiologic tasks besides image interpretations, improving the work performance of the radiologist.

MRI-based decision tree model for diagnosis of biliary atresia.

PubMed

Kim, Yong Hee; Kim, Myung-Joon; Shin, Hyun Joo; Yoon, Haesung; Han, Seok Joo; Koh, Hong; Roh, Yun Ho; Lee, Mi-Jung

2018-02-23

To evaluate MRI findings and to generate a decision tree model for diagnosis of biliary atresia (BA) in infants with jaundice. We retrospectively reviewed features of MRI and ultrasonography (US) performed in infants with jaundice between January 2009 and June 2016 under approval of the institutional review board, including the maximum diameter of periportal signal change on MRI (MR triangular cord thickness, MR-TCT) or US (US-TCT), visibility of common bile duct (CBD) and abnormality of gallbladder (GB). Hepatic subcapsular flow was reviewed on Doppler US. We performed conditional inference tree analysis using MRI findings to generate a decision tree model. A total of 208 infants were included, 112 in the BA group and 96 in the non-BA group. Mean age at the time of MRI was 58.7 ± 36.6 days. Visibility of CBD, abnormality of GB and MR-TCT were good discriminators for the diagnosis of BA and the MRI-based decision tree using these findings with MR-TCT cut-off 5.1 mm showed 97.3 % sensitivity, 94.8 % specificity and 96.2 % accuracy. MRI-based decision tree model reliably differentiates BA in infants with jaundice. MRI can be an objective imaging modality for the diagnosis of BA. • MRI-based decision tree model reliably differentiates biliary atresia in neonatal cholestasis. • Common bile duct, gallbladder and periportal signal changes are the discriminators. • MRI has comparable performance to ultrasonography for diagnosis of biliary atresia.

WE-EF-BRD-04: MR in the OR: The Growth and Applications of MRI for Interventional Radiology and Surgery

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

Fahrig, R.

MRI-guided treatment is a growing area of medicine, particularly in radiotherapy and surgery. The exquisite soft tissue anatomic contrast offered by MRI, along with functional imaging, makes the use of MRI during therapeutic procedures very attractive. Challenging the utility of MRI in the therapy room are many issues including the physics of MRI and the impact on the environment and therapeutic instruments, the impact of the room and instruments on the MRI; safety, space, design and cost. In this session, the applications and challenges of MRI-guided treatment will be described. The session format is: Past, present and future: MRI-guided radiotherapymore » from 2005 to 2025: Jan Lagendijk Battling Maxwell’s equations: Physics challenges and solutions for hybrid MRI systems: Paul Keall I want it now!: Advances in MRI acquisition, reconstruction and the use of priors to enable fast anatomic and physiologic imaging to inform guidance and adaptation decisions: Yanle Hu MR in the OR: The growth and applications of MRI for interventional radiology and surgery: Rebecca Fahrig Learning Objectives: To understand the history and trajectory of MRI-guided radiotherapy To understand the challenges of integrating MR imaging systems with linear accelerators To understand the latest in fast MRI methods to enable the visualisation of anatomy and physiology on radiotherapy treatment timescales To understand the growing role and challenges of MRI for image-guided surgical procedures My disclosures are publicly available and updated at: http://sydney.edu.au/medicine/radiation-physics/about-us/disclosures.php.« less

WE-EF-BRD-02: Battling Maxwell’s Equations: Physics Challenges and Solutions for Hybrid MRI Systems

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

Keall, P.

MRI-guided treatment is a growing area of medicine, particularly in radiotherapy and surgery. The exquisite soft tissue anatomic contrast offered by MRI, along with functional imaging, makes the use of MRI during therapeutic procedures very attractive. Challenging the utility of MRI in the therapy room are many issues including the physics of MRI and the impact on the environment and therapeutic instruments, the impact of the room and instruments on the MRI; safety, space, design and cost. In this session, the applications and challenges of MRI-guided treatment will be described. The session format is: Past, present and future: MRI-guided radiotherapymore » from 2005 to 2025: Jan Lagendijk Battling Maxwell’s equations: Physics challenges and solutions for hybrid MRI systems: Paul Keall I want it now!: Advances in MRI acquisition, reconstruction and the use of priors to enable fast anatomic and physiologic imaging to inform guidance and adaptation decisions: Yanle Hu MR in the OR: The growth and applications of MRI for interventional radiology and surgery: Rebecca Fahrig Learning Objectives: To understand the history and trajectory of MRI-guided radiotherapy To understand the challenges of integrating MR imaging systems with linear accelerators To understand the latest in fast MRI methods to enable the visualisation of anatomy and physiology on radiotherapy treatment timescales To understand the growing role and challenges of MRI for image-guided surgical procedures My disclosures are publicly available and updated at: http://sydney.edu.au/medicine/radiation-physics/about-us/disclosures.php.« less

WE-EF-BRD-01: Past, Present and Future: MRI-Guided Radiotherapy From 2005 to 2025

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

Lagendijk, J.

MRI-guided treatment is a growing area of medicine, particularly in radiotherapy and surgery. The exquisite soft tissue anatomic contrast offered by MRI, along with functional imaging, makes the use of MRI during therapeutic procedures very attractive. Challenging the utility of MRI in the therapy room are many issues including the physics of MRI and the impact on the environment and therapeutic instruments, the impact of the room and instruments on the MRI; safety, space, design and cost. In this session, the applications and challenges of MRI-guided treatment will be described. The session format is: Past, present and future: MRI-guided radiotherapymore » from 2005 to 2025: Jan Lagendijk Battling Maxwell’s equations: Physics challenges and solutions for hybrid MRI systems: Paul Keall I want it now!: Advances in MRI acquisition, reconstruction and the use of priors to enable fast anatomic and physiologic imaging to inform guidance and adaptation decisions: Yanle Hu MR in the OR: The growth and applications of MRI for interventional radiology and surgery: Rebecca Fahrig Learning Objectives: To understand the history and trajectory of MRI-guided radiotherapy To understand the challenges of integrating MR imaging systems with linear accelerators To understand the latest in fast MRI methods to enable the visualisation of anatomy and physiology on radiotherapy treatment timescales To understand the growing role and challenges of MRI for image-guided surgical procedures My disclosures are publicly available and updated at: http://sydney.edu.au/medicine/radiation-physics/about-us/disclosures.php.« less

NIR-labeled perfluoropolyether nanoemulsions for drug delivery and imaging

PubMed Central

O’Hanlon, Claire E.; Amede, Konjit G.; O’Hear, Meredith R.; Janjic, Jelena M.

2012-01-01

Theranostic nanoparticle development recently took center stage in the field of drug delivery nanoreagent design. Theranostic nanoparticles combine therapeutic delivery systems (liposomes, micelles, nanoemulsions, etc.) with imaging reagents (MRI, optical, PET, CT). This combination allows for non-invasive in vivo monitoring of therapeutic nanoparticles in diseased organs and tissues. Here, we report a novel perfluoropolyether (PFPE) nanoemulsion with a water-insoluble lipophilic drug. The formulation enables non-invasive monitoring of nanoemulsion biodistribution using two imaging modalities, 19F MRI and near-infrared (NIR) optical imaging. The nanoemulsion is composed of PFPE-tyramide as a 19F MRI tracer, hydrocarbon oil, surfactants, and a NIR dye. Preparation utilizes a combination of self-assembly and high energy emulsification methods, resulting in droplets with average diameter 180 nm and low polydispersity index (PDI less than 0.2). A model nonsteroidal anti-inflammatory drug (NSAID), celecoxib, was incorporated into the formulation at 0.2 mg/mL. The reported nanoemulsion’s properties, including small particle size, visibility under 19F NMR and NIR fluorescence spectroscopy, and the ability to carry drugs make it an attractive potential theranostic agent for cancer imaging and treatment. PMID:22675234

The accuracy of ultrashort echo time MRI sequences for medical additive manufacturing.

PubMed

van Eijnatten, Maureen; Rijkhorst, Erik-Jan; Hofman, Mark; Forouzanfar, Tymour; Wolff, Jan

2016-01-01

Additively manufactured bone models, implants and drill guides are becoming increasingly popular amongst maxillofacial surgeons and dentists. To date, such constructs are commonly manufactured using CT technology that induces ionizing radiation. Recently, ultrashort echo time (UTE) MRI sequences have been developed that allow radiation-free imaging of facial bones. The aim of the present study was to assess the feasibility of UTE MRI sequences for medical additive manufacturing (AM). Three morphologically different dry human mandibles were scanned using a CT and MRI scanner. Additionally, optical scans of all three mandibles were made to acquire a "gold standard". All CT and MRI scans were converted into Standard Tessellation Language (STL) models and geometrically compared with the gold standard. To quantify the accuracy of the AM process, the CT, MRI and gold-standard STL models of one of the mandibles were additively manufactured, optically scanned and compared with the original gold-standard STL model. Geometric differences between all three CT-derived STL models and the gold standard were <1.0 mm. All three MRI-derived STL models generally presented deviations <1.5 mm in the symphyseal and mandibular area. The AM process introduced minor deviations of <0.5 mm. This study demonstrates that MRI using UTE sequences is a feasible alternative to CT in generating STL models of the mandible and would therefore be suitable for surgical planning and AM. Further in vivo studies are necessary to assess the usability of UTE MRI sequences in clinical settings.

Recent improvements in SPE3D: a VR-based surgery planning environment

NASA Astrophysics Data System (ADS)

Witkowski, Marcin; Sitnik, Robert; Verdonschot, Nico

2014-02-01

SPE3D is a surgery planning environment developed within TLEMsafe project [1] (funded by the European Commission FP7). It enables the operator to plan a surgical procedure on the customized musculoskeletal (MS) model of the patient's lower limbs, send the modified model to the biomechanical analysis module, and export the scenario's parameters to the surgical navigation system. The personalized patient-specific three-dimensional (3-D) MS model is registered with 3-D MRI dataset of lower limbs and the two modalities may be visualized simultaneously. Apart from main planes, any arbitrary MRI cross-section can be rendered on the 3-D MS model in real time. The interface provides tools for: bone cutting, manipulating and removal, repositioning muscle insertion points, modifying muscle force, removing muscles and placing implants stored in the implant library. SPE3D supports stereoscopic viewing as well as natural inspection/manipulation with use of haptic devices. Alternatively, it may be controlled with use of a standard computer keyboard, mouse and 2D display or a touch screen (e.g. in an operating room). The interface may be utilized in two main fields. Experienced surgeons may use it to simulate their operative plans and prepare input data for a surgical navigation system while student or novice surgeons can use it for training.

Design and preliminary accuracy studies of an MRI-guided transrectal prostate intervention system.

PubMed

Krieger, Axel; Csoma, Csaba; Iordachital, Iulian I; Guion, Peter; Singh, Anurag K; Fichtinger, Gabor; Whitcomb, Louis L

2007-01-01

This paper reports a novel system for magnetic resonance imaging (MRI) guided transrectal prostate interventions, such as needle biopsy, fiducial marker placement, and therapy delivery. The system utilizes a hybrid tracking method, comprised of passive fiducial tracking for initial registration and subsequent incremental motion measurement along the degrees of freedom using fiber-optical encoders and mechanical scales. Targeting accuracy of the system is evaluated in prostate phantom experiments. Achieved targeting accuracy and procedure times were found to compare favorably with existing systems using passive and active tracking methods. Moreover, the portable design of the system using only standard MRI image sequences and minimal custom scanner interfacing allows the system to be easily used on different MRI scanners.

A brain stress test: Cerebral perfusion during memory encoding in mild cognitive impairment.

PubMed

Xie, Long; Dolui, Sudipto; Das, Sandhitsu R; Stockbower, Grace E; Daffner, Molly; Rao, Hengyi; Yushkevich, Paul A; Detre, John A; Wolk, David A

2016-01-01

Arterial spin labeled perfusion magnetic resonance imaging (ASL MRI) provides non-invasive quantification of cerebral blood flow, which can be used as a biomarker of brain function due to the tight coupling between cerebral blood flow (CBF) and brain metabolism. A growing body of literature suggests that regional CBF is altered in neurodegenerative diseases. Here we examined ASL MRI CBF in subjects with amnestic mild cognitive impairment (n = 65) and cognitively normal healthy controls (n = 62), both at rest and during performance of a memory-encoding task. As compared to rest, task-enhanced ASL MRI improved group discrimination, which supports the notion that physiologic measures during a cognitive challenge, or "stress test", may increase the ability to detect subtle functional changes in early disease stages. Further, logistic regression analysis demonstrated that ASL MRI and concomitantly acquired structural MRI provide complementary information of disease status. The current findings support the potential utility of task-enhanced ASL MRI as a biomarker in early Alzheimer's disease.

R1 dispersion contrast at high field with fast field-cycling MRI

NASA Astrophysics Data System (ADS)

Bödenler, Markus; Basini, Martina; Casula, Maria Francesca; Umut, Evrim; Gösweiner, Christian; Petrovic, Andreas; Kruk, Danuta; Scharfetter, Hermann

2018-05-01

Contrast agents with a strong R1 dispersion have been shown to be effective in generating target-specific contrast in MRI. The utilization of this R1 field dependence requires the adaptation of an MRI scanner for fast field-cycling (FFC). Here, we present the first implementation and validation of FFC-MRI at a clinical field strength of 3 T. A field-cycling range of ±100 mT around the nominal B0 field was realized by inserting an additional insert coil into an otherwise conventional MRI system. System validation was successfully performed with selected iron oxide magnetic nanoparticles and comparison to FFC-NMR relaxometry measurements. Furthermore, we show proof-of-principle R1 dispersion imaging and demonstrate the capability of generating R1 dispersion contrast at high field with suppressed background signal. With the presented ready-to-use hardware setup it is possible to investigate MRI contrast agents with a strong R1 dispersion at a field strength of 3 T.

Inner experience in the scanner: can high fidelity apprehensions of inner experience be integrated with fMRI?

PubMed Central

Kühn, Simone; Fernyhough, Charles; Alderson-Day, Benjamin; Hurlburt, Russell T.

2014-01-01

To provide full accounts of human experience and behavior, research in cognitive neuroscience must be linked to inner experience, but introspective reports of inner experience have often been found to be unreliable. The present case study aimed at providing proof of principle that introspection using one method, descriptive experience sampling (DES), can be reliably integrated with fMRI. A participant was trained in the DES method, followed by nine sessions of sampling within an MRI scanner. During moments where the DES interview revealed ongoing inner speaking, fMRI data reliably showed activation in classic speech processing areas including left inferior frontal gyrus. Further, the fMRI data validated the participant’s DES observations of the experiential distinction between inner speaking and innerly hearing her own voice. These results highlight the precision and validity of the DES method as a technique of exploring inner experience and the utility of combining such methods with fMRI. PMID:25538649

Comparison of endorectal coil and nonendorectal coil T2W and diffusion-weighted MRI at 3 Tesla for localizing prostate cancer: correlation with whole-mount histopathology.

PubMed

Turkbey, Baris; Merino, Maria J; Gallardo, Elma Carvajal; Shah, Vijay; Aras, Omer; Bernardo, Marcelino; Mena, Esther; Daar, Dagane; Rastinehad, Ardeshir R; Linehan, W Marston; Wood, Bradford J; Pinto, Peter A; Choyke, Peter L

2014-06-01

To compare utility of T2-weighted (T2W) MRI and diffusion-weighted MRI (DWI-MRI) obtained with and without an endorectal coil at 3 Tesla (T) for localizing prostate cancer. This Institutional Review Board-approved study included 20 patients (median prostate-specific antigen, 8.4 ng/mL). Patients underwent consecutive prostate MRIs at 3T, first with a surface coil alone, then with combination of surface, endorectal coils (dual coil) followed by robotic assisted radical prostatectomy. Lesions were mapped at time of acquisition on dual-coil T2W, DWI-MRI. To avoid bias, 6 months later nonendorectal coil T2W, DWI-MRI were mapped. Both MRI evaluations were performed by two readers blinded to pathology with differences resolved by consensus. A lesion-based correlation with whole-mount histopathology was performed. At histopathology 51 cancer foci were present ranging in size from 2 to 60 mm. The sensitivity of the endorectal dual-coil, nonendorectal coil MRIs were 0.76, 0.45, respectively. PPVs for endorectal dual-coil, nonendorectal coil MRI were 0.80, 0.64, respectively. Mean size of detected lesions with nonendorectal coil MRI were larger than those detected by dual-coil MRI (22 mm versus 17.4 mm). Dual-coil prostate MRI detected more cancer foci than nonendorectal coil MRI. While nonendorectal coil MRI is an attractive alternative, physicians performing prostate MRI should be aware of its limitations. Copyright © 2013 Wiley Periodicals, Inc.

The hidden-Markov brain: comparison and inference of white matter hyperintensities on magnetic resonance imaging (MRI)

NASA Astrophysics Data System (ADS)

Pham, Tuan D.; Salvetti, Federica; Wang, Bing; Diani, Marco; Heindel, Walter; Knecht, Stefan; Wersching, Heike; Baune, Bernhard T.; Berger, Klaus

2011-02-01

Rating and quantification of cerebral white matter hyperintensities on magnetic resonance imaging (MRI) are important tasks in various clinical and scientific settings. As manual evaluation is time consuming and imprecise, much effort has been made to automate the quantification of white matter hyperintensities. There is rarely any report that attempts to study the similarity/dissimilarity of white matter hyperintensity patterns that have different sizes, shapes and spatial localizations on the MRI. This paper proposes an original computational neuroscience framework for such a conceptual study with a standpoint that the prior knowledge about white matter hyperintensities can be accumulated and utilized to enable a reliable inference of the rating of a new white matter hyperintensity observation. This computational approach for rating inference of white matter hyperintensities, which appears to be the first study, can be utilized as a computerized rating-assisting tool and can be very economical for diagnostic evaluation of brain tissue lesions.

PREOPERATIVE MRI IMPROVES PREDICTION OF EXTENSIVE OCCULT AXILLARY LYMPH NODE METASTASES IN BREAST CANCER PATIENTS WITH A POSITIVE SENTINEL LYMPH NODE BIOPSY

PubMed Central

Loiselle, Christopher; Eby, Peter R.; Kim, Janice N.; Calhoun, Kristine E.; Allison, Kimberly H.; Gadi, Vijayakrishna K.; Peacock, Sue; Storer, Barry; Mankoff, David A.; Partridge, Savannah C.; Lehman, Constance D.

2014-01-01

Rationale and Objectives To test the ability of quantitative measures from preoperative Dynamic Contrast Enhanced MRI (DCE-MRI) to predict, independently and/or with the Katz pathologic nomogram, which breast cancer patients with a positive sentinel lymph node biopsy will have ≥ 4 positive axillary lymph nodes upon completion axillary dissection. Methods and Materials A retrospective review was conducted to identify clinically node-negative invasive breast cancer patients who underwent preoperative DCE-MRI, followed by sentinel node biopsy with positive findings and complete axillary dissection (6/2005 – 1/2010). Clinical/pathologic factors, primary lesion size and quantitative DCE-MRI kinetics were collected from clinical records and prospective databases. DCE-MRI parameters with univariate significance (p < 0.05) to predict ≥ 4 positive axillary nodes were modeled with stepwise regression and compared to the Katz nomogram alone and to a combined MRI-Katz nomogram model. Results Ninety-eight patients with 99 positive sentinel biopsies met study criteria. Stepwise regression identified DCE-MRI total persistent enhancement and volume adjusted peak enhancement as significant predictors of ≥4 metastatic nodes. Receiver operating characteristic (ROC) curves demonstrated an area under the curve (AUC) of 0.78 for the Katz nomogram, 0.79 for the DCE-MRI multivariate model, and 0.87 for the combined MRI-Katz model. The combined model was significantly more predictive than the Katz nomogram alone (p = 0.003). Conclusion Integration of DCE-MRI primary lesion kinetics significantly improved the Katz pathologic nomogram accuracy to predict presence of metastases in ≥ 4 nodes. DCE-MRI may help identify sentinel node positive patients requiring further localregional therapy. PMID:24331270

Gadolinium Endohedral Metallofullerene-Based MRI Contrast Agents

NASA Astrophysics Data System (ADS)

Bolskar, Robert D.

With the ability to encapsulate and carry the highly paramagnetic Gd3+ ion, gadolinium endohedral metallofullerenes or "gadofullerenes" are being explored as alternatives to the chelate complexes that are currently used for contrast-enhanced magnetic resonance imaging (MRI). Reviewed here are the various water-soluble derivatives of the gadofullerenes Gd@C82, Gd@C60, and Gd3N@C80 that have been investigated as MRI contrast agents. The water proton r1 relaxivities of gadofullerenes can be more than an order of magnitude higher than those of clinically used chelate agents. Gadofullerene relaxivity mechanisms have been studied, and multiple factors are found to contribute to their high relaxivities. In vitro and in vivoT1-weighted MRI tests of gadofullerene derivatives have shown their utility as bright image-enhancing agents. The gadofullerene MRI contrast agents are a promising new and unique style of gadolinium carrier for advanced imaging applications, including cellular and molecular imaging.

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.

NEURAL SUBSTRATES OF CUE-REACTIVITY: ASSOCIATION WITH TREATMENT OUTCOMES AND RELAPSE

PubMed Central

Courtney, Kelly E.; Schacht, Joseph P.; Hutchison, Kent; Roche, Daniel J.O.; Ray, Lara A.

2016-01-01

Given the strong evidence for neurological alterations at the basis of drug dependence, functional magnetic resonance imaging (fMRI) represents an important tool in the clinical neuroscience of addiction. fMRI cue-reactivity paradigms represent an ideal platform to probe the involvement of neurobiological pathways subserving the reward/motivation system in addiction and potentially offer a translational mechanism by which interventions and behavioral predictions can be tested. Thus, this review summarizes the research that has applied fMRI cue-reactivity paradigms to the study of adult substance use disorder treatment responses. Studies utilizing fMRI cue-reactivity paradigms for the prediction of relapse, and as a means to investigate psychosocial and pharmacological treatment effects on cue-elicited brain activation are presented within four primary categories of substances: alcohol, nicotine, cocaine, and opioids. Lastly, suggestions for how to leverage fMRI technology to advance addiction science and treatment development are provided. PMID:26435524

Biophysical and physiological origins of blood oxygenation level-dependent fMRI signals.

PubMed

Kim, Seong-Gi; Ogawa, Seiji

2012-07-01

After its discovery in 1990, blood oxygenation level-dependent (BOLD) contrast in functional magnetic resonance imaging (fMRI) has been widely used to map brain activation in humans and animals. Since fMRI relies on signal changes induced by neural activity, its signal source can be complex and is also dependent on imaging parameters and techniques. In this review, we identify and describe the origins of BOLD fMRI signals, including the topics of (1) effects of spin density, volume fraction, inflow, perfusion, and susceptibility as potential contributors to BOLD fMRI, (2) intravascular and extravascular contributions to conventional gradient-echo and spin-echo BOLD fMRI, (3) spatial specificity of hemodynamic-based fMRI related to vascular architecture and intrinsic hemodynamic responses, (4) BOLD signal contributions from functional changes in cerebral blood flow (CBF), cerebral blood volume (CBV), and cerebral metabolic rate of O(2) utilization (CMRO(2)), (5) dynamic responses of BOLD, CBF, CMRO(2), and arterial and venous CBV, (6) potential sources of initial BOLD dips, poststimulus BOLD undershoots, and prolonged negative BOLD fMRI signals, (7) dependence of stimulus-evoked BOLD signals on baseline physiology, and (8) basis of resting-state BOLD fluctuations. These discussions are highly relevant to interpreting BOLD fMRI signals as physiological means.

Biophysical and physiological origins of blood oxygenation level-dependent fMRI signals

PubMed Central

Kim, Seong-Gi; Ogawa, Seiji

2012-01-01

After its discovery in 1990, blood oxygenation level-dependent (BOLD) contrast in functional magnetic resonance imaging (fMRI) has been widely used to map brain activation in humans and animals. Since fMRI relies on signal changes induced by neural activity, its signal source can be complex and is also dependent on imaging parameters and techniques. In this review, we identify and describe the origins of BOLD fMRI signals, including the topics of (1) effects of spin density, volume fraction, inflow, perfusion, and susceptibility as potential contributors to BOLD fMRI, (2) intravascular and extravascular contributions to conventional gradient-echo and spin-echo BOLD fMRI, (3) spatial specificity of hemodynamic-based fMRI related to vascular architecture and intrinsic hemodynamic responses, (4) BOLD signal contributions from functional changes in cerebral blood flow (CBF), cerebral blood volume (CBV), and cerebral metabolic rate of O2 utilization (CMRO2), (5) dynamic responses of BOLD, CBF, CMRO2, and arterial and venous CBV, (6) potential sources of initial BOLD dips, poststimulus BOLD undershoots, and prolonged negative BOLD fMRI signals, (7) dependence of stimulus-evoked BOLD signals on baseline physiology, and (8) basis of resting-state BOLD fluctuations. These discussions are highly relevant to interpreting BOLD fMRI signals as physiological means. PMID:22395207

Analysis strategies for high-resolution UHF-fMRI data.

PubMed

Polimeni, Jonathan R; Renvall, Ville; Zaretskaya, Natalia; Fischl, Bruce

2018-03-01

Functional MRI (fMRI) benefits from both increased sensitivity and specificity with increasing magnetic field strength, making it a key application for Ultra-High Field (UHF) MRI scanners. Most UHF-fMRI studies utilize the dramatic increases in sensitivity and specificity to acquire high-resolution data reaching sub-millimeter scales, which enable new classes of experiments to probe the functional organization of the human brain. This review article surveys advanced data analysis strategies developed for high-resolution fMRI at UHF. These include strategies designed to mitigate distortion and artifacts associated with higher fields in ways that attempt to preserve spatial resolution of the fMRI data, as well as recently introduced analysis techniques that are enabled by these extremely high-resolution data. Particular focus is placed on anatomically-informed analyses, including cortical surface-based analysis, which are powerful techniques that can guide each step of the analysis from preprocessing to statistical analysis to interpretation and visualization. New intracortical analysis techniques for laminar and columnar fMRI are also reviewed and discussed. Prospects for single-subject individualized analyses are also presented and discussed. Altogether, there are both specific challenges and opportunities presented by UHF-fMRI, and the use of proper analysis strategies can help these valuable data reach their full potential. Copyright © 2017 Elsevier Inc. All rights reserved.

An fMRI and effective connectivity study investigating miss errors during advice utilization from human and machine agents.

PubMed

Goodyear, Kimberly; Parasuraman, Raja; Chernyak, Sergey; de Visser, Ewart; Madhavan, Poornima; Deshpande, Gopikrishna; Krueger, Frank

2017-10-01

As society becomes more reliant on machines and automation, understanding how people utilize advice is a necessary endeavor. Our objective was to reveal the underlying neural associations during advice utilization from expert human and machine agents with fMRI and multivariate Granger causality analysis. During an X-ray luggage-screening task, participants accepted or rejected good or bad advice from either the human or machine agent framed as experts with manipulated reliability (high miss rate). We showed that the machine-agent group decreased their advice utilization compared to the human-agent group and these differences in behaviors during advice utilization could be accounted for by high expectations of reliable advice and changes in attention allocation due to miss errors. Brain areas involved with the salience and mentalizing networks, as well as sensory processing involved with attention, were recruited during the task and the advice utilization network consisted of attentional modulation of sensory information with the lingual gyrus as the driver during the decision phase and the fusiform gyrus as the driver during the feedback phase. Our findings expand on the existing literature by showing that misses degrade advice utilization, which is represented in a neural network involving salience detection and self-processing with perceptual integration.

The topographical model of multiple sclerosis

PubMed Central

Cook, Karin; De Nino, Scott; Fletcher, Madhuri

2016-01-01

Relapses and progression contribute to multiple sclerosis (MS) disease course, but neither the relationship between them nor the spectrum of clinical heterogeneity has been fully characterized. A hypothesis-driven, biologically informed model could build on the clinical phenotypes to encompass the dynamic admixture of factors underlying MS disease course. In this medical hypothesis, we put forth a dynamic model of MS disease course that incorporates localization and other drivers of disability to propose a clinical manifestation framework that visualizes MS in a clinically individualized way. The topographical model encapsulates 5 factors (localization of relapses and causative lesions; relapse frequency, severity, and recovery; and progression rate), visualized utilizing dynamic 3-dimensional renderings. The central hypothesis is that, like symptom recrudescence in Uhthoff phenomenon and pseudoexacerbations, progression clinically recapitulates prior relapse symptoms and unmasks previously silent lesions, incrementally revealing underlying lesion topography. The model uses real-time simulation software to depict disease course archetypes and illuminate several well-described but poorly reconciled phenomena including the clinical/MRI paradox and prognostic significance of lesion location and burden on disease outcomes. Utilization of this model could allow for earlier and more clinically precise identification of progressive MS and predictive implications can be empirically tested. PMID:27648465

The accuracy of ultrashort echo time MRI sequences for medical additive manufacturing

PubMed Central

Rijkhorst, Erik-Jan; Hofman, Mark; Forouzanfar, Tymour; Wolff, Jan

2016-01-01

Objectives: Additively manufactured bone models, implants and drill guides are becoming increasingly popular amongst maxillofacial surgeons and dentists. To date, such constructs are commonly manufactured using CT technology that induces ionizing radiation. Recently, ultrashort echo time (UTE) MRI sequences have been developed that allow radiation-free imaging of facial bones. The aim of the present study was to assess the feasibility of UTE MRI sequences for medical additive manufacturing (AM). Methods: Three morphologically different dry human mandibles were scanned using a CT and MRI scanner. Additionally, optical scans of all three mandibles were made to acquire a “gold standard”. All CT and MRI scans were converted into Standard Tessellation Language (STL) models and geometrically compared with the gold standard. To quantify the accuracy of the AM process, the CT, MRI and gold-standard STL models of one of the mandibles were additively manufactured, optically scanned and compared with the original gold-standard STL model. Results: Geometric differences between all three CT-derived STL models and the gold standard were <1.0 mm. All three MRI-derived STL models generally presented deviations <1.5 mm in the symphyseal and mandibular area. The AM process introduced minor deviations of <0.5 mm. Conclusions: This study demonstrates that MRI using UTE sequences is a feasible alternative to CT in generating STL models of the mandible and would therefore be suitable for surgical planning and AM. Further in vivo studies are necessary to assess the usability of UTE MRI sequences in clinical settings. PMID:26943179

Have clinicians adopted the use of brain MRI for patients with TIA and minor stroke?

PubMed

Chaturvedi, Seemant; Ofner, Susan; Baye, Fitsum; Myers, Laura J; Phipps, Mike; Sico, Jason J; Damush, Teresa; Miech, Edward; Reeves, Mat; Johanning, Jason; Williams, Linda S; Arling, Greg; Cheng, Eric; Yu, Zhangsheng; Bravata, Dawn

2017-01-17

Use of MRI with diffusion-weighted imaging (DWI) can identify infarcts in 30%-50% of patients with TIA. Previous guidelines have indicated that MRI-DWI is the preferred imaging modality for patients with TIA. We assessed the frequency of MRI utilization and predictors of MRI performance. A review of TIA and minor stroke patients evaluated at Veterans Affairs hospitals was conducted with regard to medical history, use of diagnostic imaging within 2 days of presentation, and in-hospital care variables. Chart abstraction was performed in a subset of hospitals to assess clinical variables not available in the administrative data. A total of 7,889 patients with TIA/minor stroke were included. Overall, 6,694 patients (84.9%) had CT or MRI, with 3,396/6,694 (50.7%) having MRI. Variables that were associated with increased odds of CT performance were age >80 years, prior stroke, history of atrial fibrillation, heart failure, coronary artery disease, anxiety, and low hospital complexity, while blood pressure >140/90 mm Hg and high hospital complexity were associated with increased likelihood of MRI. Diplopia (87% had MRI, p = 0.03), neurologic consultation on the day of presentation (73% had MRI, p < 0.0001), and symptom duration of >6 hours (74% had MRI, p = 0.0009) were associated with MRI performance. Within a national health system, about 40% of patients with TIA/minor stroke had MRI performed within 2 days. Performance of MRI appeared to be influenced by several patient and facility-level variables, suggesting that there has been partial acceptance of the previous guideline that endorsed MRI for patients with TIA. © 2016 American Academy of Neurology.

WE-EF-BRD-03: I Want It Now!: Advances in MRI Acquisition, Reconstruction and the Use of Priors to Enable Fast Anatomic and Physiologic Imaging to Inform Guidance and Adaptation Decisions

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

Hu, Y.

MRI-guided treatment is a growing area of medicine, particularly in radiotherapy and surgery. The exquisite soft tissue anatomic contrast offered by MRI, along with functional imaging, makes the use of MRI during therapeutic procedures very attractive. Challenging the utility of MRI in the therapy room are many issues including the physics of MRI and the impact on the environment and therapeutic instruments, the impact of the room and instruments on the MRI; safety, space, design and cost. In this session, the applications and challenges of MRI-guided treatment will be described. The session format is: Past, present and future: MRI-guided radiotherapymore » from 2005 to 2025: Jan Lagendijk Battling Maxwell’s equations: Physics challenges and solutions for hybrid MRI systems: Paul Keall I want it now!: Advances in MRI acquisition, reconstruction and the use of priors to enable fast anatomic and physiologic imaging to inform guidance and adaptation decisions: Yanle Hu MR in the OR: The growth and applications of MRI for interventional radiology and surgery: Rebecca Fahrig Learning Objectives: To understand the history and trajectory of MRI-guided radiotherapy To understand the challenges of integrating MR imaging systems with linear accelerators To understand the latest in fast MRI methods to enable the visualisation of anatomy and physiology on radiotherapy treatment timescales To understand the growing role and challenges of MRI for image-guided surgical procedures My disclosures are publicly available and updated at: http://sydney.edu.au/medicine/radiation-physics/about-us/disclosures.php.« less

3D printing from MRI Data: Harnessing strengths and minimizing weaknesses.

PubMed

Ripley, Beth; Levin, Dmitry; Kelil, Tatiana; Hermsen, Joshua L; Kim, Sooah; Maki, Jeffrey H; Wilson, Gregory J

2017-03-01

3D printing facilitates the creation of accurate physical models of patient-specific anatomy from medical imaging datasets. While the majority of models to date are created from computed tomography (CT) data, there is increasing interest in creating models from other datasets, such as ultrasound and magnetic resonance imaging (MRI). MRI, in particular, holds great potential for 3D printing, given its excellent tissue characterization and lack of ionizing radiation. There are, however, challenges to 3D printing from MRI data as well. Here we review the basics of 3D printing, explore the current strengths and weaknesses of printing from MRI data as they pertain to model accuracy, and discuss considerations in the design of MRI sequences for 3D printing. Finally, we explore the future of 3D printing and MRI, including creative applications and new materials. 5 J. Magn. Reson. Imaging 2017;45:635-645. © 2016 International Society for Magnetic Resonance in Medicine.

MRI-guided stereotactic neurosurgical procedures in a diagnostic MRI suite: Background and safe practice recommendations.

PubMed

Larson, Paul S; Willie, Jon T; Vadivelu, Sudhakar; Azmi-Ghadimi, Hooman; Nichols, Amy; Fauerbach, Loretta Litz; Johnson, Helen Boehm; Graham, Denise

2017-07-01

The development of navigation technology facilitating MRI-guided stereotactic neurosurgery has enabled neurosurgeons to perform a variety of procedures ranging from deep brain stimulation to laser ablation entirely within an intraoperative or diagnostic MRI suite while having real-time visualization of brain anatomy. Prior to this technology, some of these procedures required multisite workflow patterns that presented significant risk to the patient during transport. For those facilities with access to this technology, safe practice guidelines exist only for procedures performed within an intraoperative MRI. There are currently no safe practice guidelines or parameters available for facilities looking to integrate this technology into practice in conventional MRI suites. Performing neurosurgical procedures in a diagnostic MRI suite does require precautionary measures. The relative novelty of technology and workflows for direct MRI-guided procedures requires consideration of safe practice recommendations, including those pertaining to infection control and magnet safety issues. This article proposes a framework of safe practice recommendations designed for assessing readiness and optimization of MRI-guided neurosurgical interventions in the diagnostic MRI suite in an effort to mitigate patient risk. The framework is based on existing clinical evidence, recommendations, and guidelines related to infection control and prevention, health care-associated infections, and magnet safety, as well as the clinical and practical experience of neurosurgeons utilizing this technology. © 2017 American Society for Healthcare Risk Management of the American Hospital Association.

Current whole-body MRI applications in the neurofibromatoses

PubMed Central

Fayad, Laura M.; Khan, Muhammad Shayan; Bredella, Miriam A.; Harris, Gordon J.; Evans, D. Gareth; Farschtschi, Said; Jacobs, Michael A.; Chhabra, Avneesh; Salamon, Johannes M.; Wenzel, Ralph; Mautner, Victor F.; Dombi, Eva; Cai, Wenli; Plotkin, Scott R.; Blakeley, Jaishri O.

2016-01-01

Objectives: The Response Evaluation in Neurofibromatosis and Schwannomatosis (REiNS) International Collaboration Whole-Body MRI (WB-MRI) Working Group reviewed the existing literature on WB-MRI, an emerging technology for assessing disease in patients with neurofibromatosis type 1 (NF1), neurofibromatosis type 2 (NF2), and schwannomatosis (SWN), to recommend optimal image acquisition and analysis methods to enable WB-MRI as an endpoint in NF clinical trials. Methods: A systematic process was used to review all published data about WB-MRI in NF syndromes to assess diagnostic accuracy, feasibility and reproducibility, and data about specific techniques for assessment of tumor burden, characterization of neoplasms, and response to therapy. Results: WB-MRI at 1.5T or 3.0T is feasible for image acquisition. Short tau inversion recovery (STIR) sequence is used in all investigations to date, suggesting consensus about the utility of this sequence for detection of WB tumor burden in people with NF. There are insufficient data to support a consensus statement about the optimal imaging planes (axial vs coronal) or 2D vs 3D approaches. Functional imaging, although used in some NF studies, has not been systematically applied or evaluated. There are no comparative studies between regional vs WB-MRI or evaluations of WB-MRI reproducibility. Conclusions: WB-MRI is feasible for identifying tumors using both 1.5T and 3.0T systems. The STIR sequence is a core sequence. Additional investigation is needed to define the optimal approach for volumetric analysis, the reproducibility of WB-MRI in NF, and the diagnostic performance of WB-MRI vs regional MRI. PMID:27527647

EARLY VERSUS LATE MRI IN ASPHYXIATED NEWBORNS TREATED WITH HYPOTHERMIA

PubMed Central

Wintermark, Pia; Hansen, Anne; Soul, Janet; Labrecque, Michelle; Robertson, Richard L.; Warfield, Simon K.

2012-01-01

Objective The purposes of this feasibility study are to assess: (1) the potential utility of early brain magnetic resonance imaging (MRI) in asphyxiated newborns treated with hypothermia; (2) whether early MRI predicts later brain injury observed in these newborns after hypothermia is completed; and (3) whether early MRI indicators of brain injury in these newborns represent reversible changes. Patients and Methods All consecutive asphyxiated term newborns meeting the criteria for therapeutic hypothermia were enrolled prospectively. Each of them underwent 1–2 “early” MRI scans while receiving hypothermia, on day of life (DOL) 1 and DOL 2–3, and also 1–2 “late” MRI scans on DOL 8–13 and at 1 month of age. Results Thirty-seven MRI scans were obtained in twelve asphyxiated neonates treated with induced hypothermia. Four newborns did develop MRI evidence of brain injury, already visible on early MRI scans. The remaining eight newborns did not develop significant MRI evidence of brain injury on any of the MRI scans. In addition, two patients displayed unexpected findings on early MRIs, leading to early termination of hypothermia treatment. Conclusions MRI scans obtained on DOL 2–3 during hypothermia seem to predict later brain injuries in asphyxiated newborns in this feasibility study. Brain injuries identified during this early time appear to represent irreversible changes. Early MRI scans might also be useful to demonstrate unexpected findings not related to hypoxic-ischemic encephalopathy, which could potentially be exacerbated by induced hypothermia. Additional studies with larger numbers of patients will be useful to more definitively confirm these results. PMID:20688865

Changing Utilization of Noninvasive Diagnostic Imaging Over 2 Decades: An Examination Family-Focused Analysis of Medicare Claims Using the Neiman Imaging Types of Service Categorization System.

PubMed

Rosman, David A; Duszak, Richard; Wang, Wenyi; Hughes, Danny R; Rosenkrantz, Andrew B

2018-02-01

The objective of our study was to use a new modality and body region categorization system to assess changing utilization of noninvasive diagnostic imaging in the Medicare fee-for-service population over a recent 20-year period (1994-2013). All Medicare Part B Physician Fee Schedule services billed between 1994 and 2013 were identified using Physician/Supplier Procedure Summary master files. Billed codes for diagnostic imaging were classified using the Neiman Imaging Types of Service (NITOS) coding system by both modality and body region. Utilization rates per 1000 beneficiaries were calculated for families of services. Among all diagnostic imaging modalities, growth was greatest for MRI (+312%) and CT (+151%) and was lower for ultrasound, nuclear medicine, and radiography and fluoroscopy (range, +1% to +31%). Among body regions, service growth was greatest for brain (+126%) and spine (+74%) imaging; showed milder growth (range, +18% to +67%) for imaging of the head and neck, breast, abdomen and pelvis, and extremity; and showed slight declines (range, -2% to -7%) for cardiac and chest imaging overall. The following specific imaging service families showed massive (> +100%) growth: cardiac CT, cardiac MRI, and breast MRI. NITOS categorization permits identification of temporal shifts in noninvasive diagnostic imaging by specific modality- and region-focused families, providing a granular understanding and reproducible analysis of global changes in imaging overall. Service family-level perspectives may help inform ongoing policy efforts to optimize imaging utilization and appropriateness.

Effects of Interpersonal Skills Training on MRI Operations in a Saturated Market: A Randomized Trial.

PubMed

Ajam, Amna A; Nguyen, Xuan V; Kelly, Ronda A; Ladapo, Joseph A; Lang, Elvira V

2017-07-01

The aim of this study was to assess the effects of team training on operational efficiency during outpatient MRI. In this institutional review board-approved, HIPAA-compliant study, six MRI outpatient sites of a midwestern hospital system were randomized to serve as controls or have their teams trained in advanced communication skills. The fourth quarter of fiscal year 2015 was the trial baseline. The trial ended in the third quarter (Q3) of fiscal year 2016 (FY16). Equipment utilization (completed scans/available slots), hourly scan rates (total orders completed per machine per hour of operation), and no-show rates stratified by time were analyzed using the Cochran-Mantel-Haenszel method, with individual comparisons performed with Bonferroni correction. The study encompassed 27,425 MRI examinations. Overall volume peaked at baseline and then declined over the following quarters. Compared with baseline, untrained sites experienced significant drops in equipment utilization (P < .01 for the first quarter of FY16 and P < .0001 for the second quarter of FY16 and Q3 FY16), decreasing from 77% to 65% over the study period, corresponding to a decrease from 1.15 to 0.97 in hourly scan rates. For trained sites, these metrics showed no significant change, with maintenance of hourly scan rates of 1.23 and 1.27 and equipment utilization rates of 83% and 85% between baseline and Q3 FY16. No-show rates remained stable at trained sites but increased at untrained sites in the last two quarters (P < .05). Nationally benchmarked patient satisfaction percentile ranking gradually increased at trained sites from 56th at baseline to 70th and successively decreased at untrained sites from 66th to 44th. MRI outpatient facilities trained in advanced communication techniques may have more favorable operational efficiency than untrained sites in a saturated market. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Predicting conversion from MCI to AD using resting-state fMRI, graph theoretical approach and SVM.

PubMed

Hojjati, Seyed Hani; Ebrahimzadeh, Ata; Khazaee, Ali; Babajani-Feremi, Abbas

2017-04-15

We investigated identifying patients with mild cognitive impairment (MCI) who progress to Alzheimer's disease (AD), MCI converter (MCI-C), from those with MCI who do not progress to AD, MCI non-converter (MCI-NC), based on resting-state fMRI (rs-fMRI). Graph theory and machine learning approach were utilized to predict progress of patients with MCI to AD using rs-fMRI. Eighteen MCI converts (average age 73.6 years; 11 male) and 62 age-matched MCI non-converters (average age 73.0 years, 28 male) were included in this study. We trained and tested a support vector machine (SVM) to classify MCI-C from MCI-NC using features constructed based on the local and global graph measures. A novel feature selection algorithm was developed and utilized to select an optimal subset of features. Using subset of optimal features in SVM, we classified MCI-C from MCI-NC with an accuracy, sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve of 91.4%, 83.24%, 90.1%, and 0.95, respectively. Furthermore, results of our statistical analyses were used to identify the affected brain regions in AD. To the best of our knowledge, this is the first study that combines the graph measures (constructed based on rs-fMRI) with machine learning approach and accurately classify MCI-C from MCI-NC. Results of this study demonstrate potential of the proposed approach for early AD diagnosis and demonstrate capability of rs-fMRI to predict conversion from MCI to AD by identifying affected brain regions underlying this conversion. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma.

PubMed

Hu, Leland S; Ning, Shuluo; Eschbacher, Jennifer M; Gaw, Nathan; Dueck, Amylou C; Smith, Kris A; Nakaji, Peter; Plasencia, Jonathan; Ranjbar, Sara; Price, Stephen J; Tran, Nhan; Loftus, Joseph; Jenkins, Robert; O'Neill, Brian P; Elmquist, William; Baxter, Leslie C; Gao, Fei; Frakes, David; Karis, John P; Zwart, Christine; Swanson, Kristin R; Sarkaria, Jann; Wu, Teresa; Mitchell, J Ross; Li, Jing

2015-01-01

Genetic profiling represents the future of neuro-oncology but suffers from inadequate biopsies in heterogeneous tumors like Glioblastoma (GBM). Contrast-enhanced MRI (CE-MRI) targets enhancing core (ENH) but yields adequate tumor in only ~60% of cases. Further, CE-MRI poorly localizes infiltrative tumor within surrounding non-enhancing parenchyma, or brain-around-tumor (BAT), despite the importance of characterizing this tumor segment, which universally recurs. In this study, we use multiple texture analysis and machine learning (ML) algorithms to analyze multi-parametric MRI, and produce new images indicating tumor-rich targets in GBM. We recruited primary GBM patients undergoing image-guided biopsies and acquired pre-operative MRI: CE-MRI, Dynamic-Susceptibility-weighted-Contrast-enhanced-MRI, and Diffusion Tensor Imaging. Following image coregistration and region of interest placement at biopsy locations, we compared MRI metrics and regional texture with histologic diagnoses of high- vs low-tumor content (≥80% vs <80% tumor nuclei) for corresponding samples. In a training set, we used three texture analysis algorithms and three ML methods to identify MRI-texture features that optimized model accuracy to distinguish tumor content. We confirmed model accuracy in a separate validation set. We collected 82 biopsies from 18 GBMs throughout ENH and BAT. The MRI-based model achieved 85% cross-validated accuracy to diagnose high- vs low-tumor in the training set (60 biopsies, 11 patients). The model achieved 81.8% accuracy in the validation set (22 biopsies, 7 patients). Multi-parametric MRI and texture analysis can help characterize and visualize GBM's spatial histologic heterogeneity to identify regional tumor-rich biopsy targets.

A Java-based fMRI processing pipeline evaluation system for assessment of univariate general linear model and multivariate canonical variate analysis-based pipelines.

PubMed

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

2008-01-01

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

Is hunger important to model in fMRI visual food-cue reactivity paradigms in adults with obesity and how should this be done?

PubMed

Chin, Shao-Hua; Kahathuduwa, Chanaka N; Stearns, Macy B; Davis, Tyler; Binks, Martin

2018-01-01

We considered 1) influence of self-reported hunger in behavioral and fMRI food-cue reactivity (fMRI-FCR) 2) optimal methods to model this. Adults (N = 32; 19-60 years; F = 21; BMI 30-39.9 kg/m 2 ) participated in an fMRI-FCR task that required rating 240 images of food and matched objects for 'appeal'. Hunger, satiety, thirst, fullness and emptiness were measured pre- and post-scan (visual analogue scales). Hunger, satiety, fullness and emptiness were combined to form a latent factor (appetite). Post-vs. pre-scores were compared using paired t-tests. In mixed-effects models, appeal/fMRI-FCR responses were regressed on image (i.e. food/objects), with random intercepts and slopes of image for functional runs nested within subjects. Each of hunger, satiety, thirst, fullness, emptiness and appetite were added as covariates in 4 forms (separate models): 1) change; 2) post- and pre-mean; 3) pre-; 4) change and pre-. Satiety decreased (Δ = -13.39, p = 0.001) and thirst increased (Δ = 11.78, p = 0.006) during the scan. Changes in other constructs were not significant (p's > 0.05). Including covariates did not influence food vs. object contrast of appeal ratings/fMRI-FCR. Significant image X covariate interactions were observed in some fMRI models. However, including these constructs did not improve the overall model fit. While some subjective, self-reported hunger, satiety and related constructs may be moderating fMRI-FCR, these constructs do not appear to be salient influences on appeal/fMRI-FCR in people with obesity undergoing fMRI. Copyright © 2017 Elsevier Ltd. All rights reserved.

Imaging as a biomarker in drug discovery for Alzheimer’s disease: is MRI a suitable technology?

PubMed Central

2014-01-01

This review provides perspectives on the utility of magnetic resonance imaging (MRI) as a neuroimaging approach in the development of novel treatments for Alzheimer’s disease. These considerations were generated in a roundtable at a recent Wellcome Trust meeting that included experts from academia and industry. It was agreed that MRI, either structural or functional, could be used as a diagnostic, for assessing worsening of disease status, for monitoring vascular pathology, and for stratifying clinical trial populations. It was agreed also that MRI implementation is in its infancy, requiring more evidence of association with the disease states, test-retest data, better standardization across multiple clinical sites, and application in multimodal approaches which include other imaging technologies, such as positron emission tomography, electroencephalography, and magnetoencephalography. PMID:25484927

Functional MR imaging assessment of a non-responsive brain injured patient.

PubMed

Moritz, C H; Rowley, H A; Haughton, V M; Swartz, K R; Jones, J; Badie, B

2001-10-01

Functional magnetic resonance imaging (fMRI) was requested to assist in the evaluation of a comatose 38-year-old woman who had sustained multiple cerebral contusions from a motor vehicle accident. Previous electrophysiologic studies suggested absence of thalamocortical processing in response to median nerve stimulation. Whole-brain fMRI was performed utilizing visual, somatosensory, and auditory stimulation paradigms. Results demonstrated intact task-correlated sensory and cognitive blood oxygen level dependent (BOLD) hemodynamic response to stimuli. Electrodiagnostic studies were repeated and evoked potentials indicated supratentorial recovery in the cerebrum. At 3-months post trauma the patient had recovered many cognitive & sensorimotor functions, accurately reflecting the prognostic fMRI evaluation. These results indicate that fMRI examinations may provide a useful evaluation for brain function in non-responsive brain trauma patients.

Selective magnetic resonance imaging (MRI) in invasive lobular breast cancer based on mammographic density: does it lead to an appropriate change in surgical treatment?

PubMed

Bansal, Gaurav J; Santosh, Divya; Davies, Eleri L

2016-01-01

The purpose of this study was to evaluate whether high mammographic density can be used as one of the selection criteria for MRI in invasive lobular breast cancer (ILC). In our institute, high breast density has been used as one of the indications for performing MRI scan in patients with ILC. We divided the patients in two groups, one with MRI performed pre-operatively and other without MRI. We compared their surgical procedures and analyzed whether surgical plan was altered after MRI. In case of alteration of plan, we analyzed whether the change was adequate by comparing post-operative histological findings. Between 2011 and 2015, there were a total of 1601 breast cancers with 97 lobular cancers, out of which 36 had pre-operative MRI and 61 had no MRI scan. 12 (33.3%) had mastectomy following MRI, out of which 9 (25%) had change in surgical plan from conservation to mastectomy following MRI. There were no unnecessary mastectomies in the MRI group. However, utilization of MRI in this cohort of patients did not reduce reoperation rate (19.3%). Lobular carcinoma in situ (LCIS) was identified in 60% of reoperations on post-surgical histology. Patients in the "No MRI" group had higher mastectomy rate 26 (42.6%), which was again appropriate. High mammographic density is a useful risk stratification criterion for selective MRI in ILC within a multidisciplinary team meeting setting. Provided additional lesions identified on MRI are confirmed with biopsy, pre-operative MRI does not cause unnecessary mastectomies. Used in this selective manner, reoperation rates were not eliminated, albeit reduced when compared to literature. High mammographic breast density can be used as one of the selection criteria for pre-operative MRI in ILC without an increase in inappropriate mastectomies with potential time and cost savings. In this cohort, re-excisions were not reduced markedly with pre-operative MRI.

A review of MRI evaluation of demyelination in cuprizone murine model

NASA Astrophysics Data System (ADS)

Krutenkova, E.; Pan, E.; Khodanovich, M.

2015-11-01

The cuprizone mouse model of non-autoimmune demyelination reproduces some phenomena of multiple sclerosis and is appropriate for validation and specification of a new method of non-invasive diagnostics. In the review new data which are collected using the new MRI method are compared with one or more conventional MRI tools. Also the paper reviewed the validation of MRI approaches using histological or immunohistochemical methods. Luxol fast blue histological staining and myelin basic protein immunostaining is widespread. To improve the accuracy of non-invasive conventional MRI, multimodal scanning could be applied. The new quantitative MRI method of fast mapping of the macromolecular proton fraction is a reliable biomarker of myelin in the brain and can be used for research of demyelination in animals. To date, a validation of MPF method on the CPZ mouse model of demyelination is not performed, although this method is probably the best way to evaluate demyelination using MRI.

SU-E-J-218: Novel Validation Paradigm of MRI to CT Deformation of Prostate

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

Padgett, K; University of Miami School of Medicine - Radiology, Miami, FL; Pirozzi, S

2015-06-15

Purpose: Deformable registration algorithms are inherently difficult to characterize in the multi-modality setting due to a significant differences in the characteristics of the different modalities (CT and MRI) as well as tissue deformations. We present a unique paradigm where this is overcome by utilizing a planning-MRI acquired within an hour of the planning-CT serving as a surrogate for quantifying MRI to CT deformation by eliminating the issues of multi-modality comparisons. Methods: For nine subjects, T2 fast-spin-echo images were acquired at two different time points, the first several weeks prior to planning (diagnostic-MRI) and the second on the same day asmore » the planning-CT (planning-MRI). Significant effort in patient positioning and bowel/bladder preparation was undertaken to minimize distortion of the prostate in all datasets. The diagnostic-MRI was rigidly and deformably aligned to the planning-CT utilizing a commercially available deformable registration algorithm synthesized from local registrations. Additionally, the quality of rigid alignment was ranked by an imaging physicist. The distances between corresponding anatomical landmarks on rigid and deformed registrations (diagnostic-MR to planning-CT) were evaluated. Results: It was discovered that in cases where the rigid registration was of acceptable quality the deformable registration didn’t improve the alignment, this was true of all metrics employed. If the analysis is separated into cases where the rigid alignment was ranked as unacceptable the deformable registration significantly improved the alignment, 4.62mm residual error in landmarks as compared to 5.72mm residual error in rigid alignments with a p-value of 0.0008. Conclusion: This paradigm provides an ideal testing ground for MR to CT deformable registration algorithms by allowing for inter-modality comparisons of multi-modality registrations. Consistent positioning, bowel and bladder preparation may Result in higher quality rigid registrations than typically achieved which limits the impact of deformable registrations. In this study cases where significant differences exist, deformable registrations provide significant value.« less

Safety and utility of magnetic resonance imaging in patients with cardiac implantable electronic devices.

PubMed

Strom, Jordan B; Whelan, Jill B; Shen, Changyu; Zheng, Shuang Qi; Mortele, Koenraad J; Kramer, Daniel B

2017-08-01

Off-label magnetic resonance imaging (MRI) for patients with cardiac implantable electrical devices has been limited owing to concerns about safety and unclear diagnostic and prognostic utility. The purpose of this study was to define major and minor adverse events with off-label MRI scans. We prospectively evaluated patients with non-MRI-conditional cardiac implantable electrical devices referred for MRI scans under a strict clinical protocol. The primary safety outcome was incidence of major adverse events (loss of pacing, inappropriate shock or antitachycardia pacing, need for system revision, or death) or minor adverse events (inappropriate pacing, arrhythmias, power-on-reset events, heating at the generator site, or changes in device parameters at baseline or at 6 months). A total of 189 MRI scans were performed in 123 patients (63.1% [78] men; median age 70 ± 18.5 years; 56.9% [70] patients with implantable cardioverter-defibrillators; 33.3% [41] pacemaker-dependent patients) predominantly for brain or spinal conditions. A minority of scans (22.7% [43]) were performed for urgent or emergent indications. Major adverse events were rare: 1 patient with loss of pacing, no deaths, or system revisions (overall rate 0.5%; 95% confidence interval 0.01-2.91). Minor adverse events were similarly rare (overall rate 1.6%; 95% confidence interval 0.3-4.6). Nearly all studies (98.4% [186]) were interpretable, while 75.1% [142] were determined to change management according to the prespecified criteria. No clinically significant changes were observed in device parameters acutely after MRI or at 6 months as compared with baseline across all patient and device categories. Off-label MRI scans performed under a strict protocol demonstrated excellent short- and medium-term safety while providing interpretable imaging that frequently influenced clinical care. Copyright © 2017 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Safety and utility of magnetic resonance imaging in patients with cardiac implantable electronic devices

PubMed Central

Strom, Jordan B.; Whelan, Jill B.; Shen, Changyu; Zheng, Shuang Qi; Mortele, Koenraad J.; Kramer, Daniel B.

2017-01-01

BACKGROUND Off-label magnetic resonance imaging (MRI) for patients with cardiac implantable electrical devices has been limited owing to concerns about safety and unclear diagnostic and prognostic utility. OBJECTIVE The purpose of this study was to define major and minor adverse events with off-label MRI scans. METHODS We prospectively evaluated patients with non–MRI-conditional cardiac implantable electrical devices referred for MRI scans under a strict clinical protocol. The primary safety outcome was incidence of major adverse events (loss of pacing, inappropriate shock or antitachycardia pacing, need for system revision, or death) or minor adverse events (inappropriate pacing, arrhythmias, power-on-reset events, heating at the generator site, or changes in device parameters at baseline or at 6 months). RESULTS A total of 189 MRI scans were performed in 123 patients (63.1% [78] men; median age 70 ± 18.5 years; 37.0% [70] patients with implantable cardioverter-defibrillators; 21.8% [41] pacemaker-dependent patients) predominantly for brain or spinal conditions. A minority of scans (22.7% [43]) were performed for urgent or emergent indications. Major adverse events were rare: 1 patient with loss of pacing, no deaths, or system revisions (overall rate 0.5%; 95% confidence interval 0.01–2.91). Minor adverse events were similarly rare (overall rate 1.6%; 95% confidence interval 0.3–4.6). Nearly all studies (98.4% [186]) were interpretable, while 74.9% [142] were determined to change management according to the prespecified criteria. No clinically significant changes were observed in device parameters acutely after MRI or at 6 months as compared with baseline across all patient and device categories. CONCLUSION Off-label MRI scans performed under a strict protocol demonstrated excellent short- and medium-term safety while providing interpretable imaging that frequently influenced clinical care. PMID:28385671

Interplay between Functional Connectivity and Scale-Free Dynamics in Intrinsic fMRI Networks

PubMed Central

Ciuciu, Philippe; Abry, Patrice; He, Biyu J.

2014-01-01

Studies employing functional connectivity-type analyses have established that spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals are organized within large-scale brain networks. Meanwhile, fMRI signals have been shown to exhibit 1/f-type power spectra – a hallmark of scale-free dynamics. We studied the interplay between functional connectivity and scale-free dynamics in fMRI signals, utilizing the fractal connectivity framework – a multivariate extension of the univariate fractional Gaussian noise model, which relies on a wavelet formulation for robust parameter estimation. We applied this framework to fMRI data acquired from healthy young adults at rest and performing a visual detection task. First, we found that scale-invariance existed beyond univariate dynamics, being present also in bivariate cross-temporal dynamics. Second, we observed that frequencies within the scale-free range do not contribute evenly to inter-regional connectivity, with a systematically stronger contribution of the lowest frequencies, both at rest and during task. Third, in addition to a decrease of the Hurst exponent and inter-regional correlations, task performance modified cross-temporal dynamics, inducing a larger contribution of the highest frequencies within the scale-free range to global correlation. Lastly, we found that across individuals, a weaker task modulation of the frequency contribution to inter-regional connectivity was associated with better task performance manifesting as shorter and less variable reaction times. These findings bring together two related fields that have hitherto been studied separately – resting-state networks and scale-free dynamics, and show that scale-free dynamics of human brain activity manifest in cross-regional interactions as well. PMID:24675649

The representation of object viewpoint in human visual cortex.

PubMed

Andresen, David R; Vinberg, Joakim; Grill-Spector, Kalanit

2009-04-01

Understanding the nature of object representations in the human brain is critical for understanding the neural basis of invariant object recognition. However, the degree to which object representations are sensitive to object viewpoint is unknown. Using fMRI we employed a parametric approach to examine the sensitivity to object view as a function of rotation (0 degrees-180 degrees ), category (animal/vehicle) and fMRI-adaptation paradigm (short or long-lagged). For both categories and fMRI-adaptation paradigms, object-selective regions recovered from adaptation when a rotated view of an object was shown after adaptation to a specific view of that object, suggesting that representations are sensitive to object rotation. However, we found evidence for differential representations across categories and ventral stream regions. Rotation cross-adaptation was larger for animals than vehicles, suggesting higher sensitivity to vehicle than animal rotation, and was largest in the left fusiform/occipito-temporal sulcus (pFUS/OTS), suggesting that this region has low sensitivity to rotation. Moreover, right pFUS/OTS and FFA responded more strongly to front than back views of animals (without adaptation) and rotation cross-adaptation depended both on the level of rotation and the adapting view. This result suggests a prevalence of neurons that prefer frontal views of animals in fusiform regions. Using a computational model of view-tuned neurons, we demonstrate that differential neural view tuning widths and relative distributions of neural-tuned populations in fMRI voxels can explain the fMRI results. Overall, our findings underscore the utility of parametric approaches for studying the neural basis of object invariance and suggest that there is no complete invariance to object view in the human ventral stream.

CORRELATION OF MRI GRADING OF BONE STRESS INJURIES WITH CLINICAL RISK FACTORS AND RETURN TO PLAY: A 5-YEAR PROSPECTIVE STUDY IN COLLEGIATE TRACK AND FIELD ATHLETES

PubMed Central

Nattiv, Aurelia; Kennedy, Gannon; Barrack, Michelle T.; Abdelkerim, Ashraf; Goolsby, Marci A.; Arends, Julie C.; Seeger, Leanne L.

2015-01-01

Background Bone stress injuries are common in track and field athletes. Knowledge of risk factors and correlation of these to magnetic resonance imaging (MRI) grading could be helpful in determining recovery time. Purpose To examine the relationships between MRI grading of bone stress injury with clinical risk factors and time to return to sport in collegiate track and field athletes. Study Design Prospective cohort over 5 years. Methods Two hundred and eleven male and female collegiate track and field and cross-country athletes were followed prospectively through their competitive seasons. All athletes had a pre-participation history, physical exam, and anthropometric measurements obtained annually. An additional questionnaire was completed regarding nutritional behaviors, menstrual patterns and prior injuries, as well as a 3-day diet record. Dual energy X-ray absorptiometry was obtained at baseline and each year of participation in the study. Athletes with clinical evidence of bone stress injuries had plain radiographs. If radiographs were negative, MRI was obtained. Bone stress injuries were evaluated by two independent radiologists utilizing an MRI grading system. MRI grading and risk factors were evaluated to identify predictors of time to return to sport. Results Thirty-four (12 males, 22 females) of the 211 collegiate athletes sustained 61 bone stress injuries during the 5-year study period. The average prospective assessment for participants was 2.1 years. MRI grade and total body bone mineral density (BMD) emerged as significant and independent predictors of time to return to sport in the multiple regression model. Specifically, the higher the MRI grade, the longer the recovery time (p<0.002). Location of bone injury at predominantly trabecular sites of the femoral neck, pubic bone and sacrum (p<0.001), and lower total body BMD (p<0.029) independently predicted prolonged time to return to sport. Conclusions Higher MRI grade, lower BMD, and skeletal sites of predominant trabecular bone structure were independently associated with delayed recovery of bone stress injuries in track and field athletes. Knowledge of these risk factors, as well as nutritional and menstrual factors, can be clinically useful in determining time to return to sport. PMID:23825184

Predictive equations for central obesity via anthropometrics, stereovision imaging, and MRI in adults

PubMed Central

Lee, Jane J; Freeland-Graves, Jeanne H; Pepper, M Reese; Yao, Ming; Xu, Bugao

2013-01-01

Objective Abdominal visceral adiposity is related to risks for insulin resistance and metabolic perturbations. Magnetic resonance imaging (MRI) and computed tomography are advanced instruments that quantify abdominal adiposity; yet field use is constrained by their bulkiness and costliness. The purpose of this study is to develop prediction equations for total abdominal, subcutaneous, and visceral adiposity via anthropometrics, stereovision body imaging (SBI), and MRI. Design and Methods Participants (67 men and 55 women) were measured for anthropometrics, and abdominal adiposity volumes evaluated by MRI umbilicus scans. Body circumferences and central obesity were obtained via SBI. Prediction models were developed via multiple linear regression analysis, utilizing body measurements and demographics as independent predictors, and abdominal adiposity as a dependent variable. Cross-validation was performed by the data-splitting method. Results The final total abdominal adiposity prediction equation was –470.28+7.10waist circumference–91.01gender+5.74sagittal diameter (R²=89.9%); subcutaneous adiposity was –172.37+8.57waist circumference–62.65gender–450.16stereovision waist-to-hip ratio (R²=90.4%); and visceral adiposity was –96.76+11.48central obesity depth–5.09 central obesity width+204.74stereovision waist-to-hip ratio–18.59gender (R²=71.7%). R² significantly improved for predicting visceral fat when SBI variables were included, but not for total abdominal or subcutaneous adiposity. Conclusions SBI is effective for predicting visceral adiposity and the prediction equations derived from SBI measurements can assess obesity. PMID:23613161

Predictive equations for central obesity via anthropometrics, stereovision imaging and MRI in adults.

PubMed

Lee, Jane J; Freeland-Graves, Jeanne H; Pepper, M Reese; Yao, Ming; Xu, Bugao

2014-03-01

Abdominal visceral adiposity is related to risks for insulin resistance and metabolic perturbations. Magnetic resonance imaging (MRI) and computed tomography are advanced instruments that quantify abdominal adiposity; yet field use is constrained by their bulkiness and costliness. The purpose of this study is to develop prediction equations for total abdominal, subcutaneous, and visceral adiposity via anthropometrics, stereovision body imaging (SBI), and MRI. Participants (67 men and 55 women) were measured for anthropometrics and abdominal adiposity volumes evaluated by MRI umbilicus scans. Body circumferences and central obesity were obtained via SBI. Prediction models were developed via multiple linear regression analysis, utilizing body measurements and demographics as independent predictors, and abdominal adiposity as a dependent variable. Cross-validation was performed by the data-splitting method. The final total abdominal adiposity prediction equation was -470.28 + 7.10 waist circumference - 91.01 gender + 5.74 sagittal diameter (R2 = 89.9%), subcutaneous adiposity was -172.37 + 8.57 waist circumference - 62.65 gender - 450.16 stereovision waist-to-hip ratio (R2 =90.4%), and visceral adiposity was -96.76 + 11.48 central obesity depth - 5.09 central obesity width + 204.74 stereovision waist-to-hip ratio - 18.59 gender (R2 = 71.7%). R2 significantly improved for predicting visceral fat when SBI variables were included, but not for total abdominal or subcutaneous adiposity. SBI is effective for predicting visceral adiposity and the prediction equations derived from SBI measurements can assess obesity. Copyright © 2013 The Obesity Society.

Mapping cardiac fiber orientations from high-resolution DTI to high-frequency 3D ultrasound

NASA Astrophysics Data System (ADS)

Qin, Xulei; Wang, Silun; Shen, Ming; Zhang, Xiaodong; Wagner, Mary B.; Fei, Baowei

2014-03-01

The orientation of cardiac fibers affects the anatomical, mechanical, and electrophysiological properties of the heart. Although echocardiography is the most common imaging modality in clinical cardiac examination, it can only provide the cardiac geometry or motion information without cardiac fiber orientations. If the patient's cardiac fiber orientations can be mapped to his/her echocardiography images in clinical examinations, it may provide quantitative measures for diagnosis, personalized modeling, and image-guided cardiac therapies. Therefore, this project addresses the feasibility of mapping personalized cardiac fiber orientations to three-dimensional (3D) ultrasound image volumes. First, the geometry of the heart extracted from the MRI is translated to 3D ultrasound by rigid and deformable registration. Deformation fields between both geometries from MRI and ultrasound are obtained after registration. Three different deformable registration methods were utilized for the MRI-ultrasound registration. Finally, the cardiac fiber orientations imaged by DTI are mapped to ultrasound volumes based on the extracted deformation fields. Moreover, this study also demonstrated the ability to simulate electricity activations during the cardiac resynchronization therapy (CRT) process. The proposed method has been validated in two rat hearts and three canine hearts. After MRI/ultrasound image registration, the Dice similarity scores were more than 90% and the corresponding target errors were less than 0.25 mm. This proposed approach can provide cardiac fiber orientations to ultrasound images and can have a variety of potential applications in cardiac imaging.

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.

MRI Proton Density Fat Fraction Is Robust Across the Biologically Plausible Range of Triglyceride Spectra in Adults With Nonalcoholic Steatohepatitis

PubMed Central

Hong, Cheng William; Mamidipalli, Adrija; Hooker, Jonathan C.; Hamilton, Gavin; Wolfson, Tanya; Chen, Dennis H.; Dehkordy, Soudabeh Fazeli; Middleton, Michael S.; Reeder, Scott B.; Loomba, Rohit; Sirlin, Claude B.

2017-01-01

Background Proton density fat fraction (PDFF) estimation requires spectral modeling of the hepatic triglyceride (TG) signal. Deviations in the TG spectrum may occur, leading to bias in PDFF quantification. Purpose To investigate the effects of varying six-peak TG spectral models on PDFF estimation bias. Study Type Retrospective secondary analysis of prospectively acquired clinical research data. Population Forty-four adults with biopsy-confirmed nonalcoholic steatohepatitis. Field Strength/Sequence Confounder-corrected chemical-shift-encoded 3T MRI (using a 2D multiecho gradient-recalled echo technique with magnitude reconstruction) and MR spectroscopy. Assessment In each patient, 61 pairs of colocalized MRI-PDFF and MRS-PDFF values were estimated: one pair used the standard six-peak spectral model, the other 60 were six-peak variants calculated by adjusting spectral model parameters over their biologically plausible ranges. MRI-PDFF values calculated using each variant model and the standard model were compared, and the agreement between MRI-PDFF and MRS-PDFF was assessed. Statistical Tests MRS-PDFF and MRI-PDFF were summarized descriptively. Bland–Altman (BA) analyses were performed between PDFF values calculated using each variant model and the standard model. Linear regressions were performed between BA biases and mean PDFF values for each variant model, and between MRI-PDFF and MRS-PDFF. Results Using the standard model, mean MRS-PDFF of the study population was 17.9±8.0% (range: 4.1–34.3%). The difference between the highest and lowest mean variant MRI-PDFF values was 1.5%. Relative to the standard model, the model with the greatest absolute BA bias overestimated PDFF by 1.2%. Bias increased with increasing PDFF (P < 0.0001 for 59 of the 60 variant models). MRI-PDFF and MRS-PDFF agreed closely for all variant models (R2=0.980, P < 0.0001). Data Conclusion Over a wide range of hepatic fat content, PDFF estimation is robust across the biologically plausible range of TG spectra. Although absolute estimation bias increased with higher PDFF, its magnitude was small and unlikely to be clinically meaningful. Level of Evidence 3 Technical Efficacy Stage 2 PMID:28851124

THE ROLE OF THE MAGNETOROTATIONAL INSTABILITY IN MASSIVE STARS

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

Wheeler, J. Craig; Kagan, Daniel; Chatzopoulos, Emmanouil, E-mail: wheel@astro.as.utexas.edu

2015-01-20

The magnetorotational instability (MRI) is key to physics in accretion disks and is widely considered to play some role in massive star core collapse. Models of rotating massive stars naturally develop very strong shear at composition boundaries, a necessary condition for MRI instability, and the MRI is subject to triply diffusive destabilizing effects in radiative regions. We have used the MESA stellar evolution code to compute magnetic effects due to the Spruit-Tayler (ST) mechanism and the MRI, separately and together, in a sample of massive star models. We find that the MRI can be active in the later stages ofmore » massive star evolution, leading to mixing effects that are not captured in models that neglect the MRI. The MRI and related magnetorotational effects can move models of given zero-age main sequence mass across ''boundaries'' from degenerate CO cores to degenerate O/Ne/Mg cores and from degenerate O/Ne/Mg cores to iron cores, thus affecting the final evolution and the physics of core collapse. The MRI acting alone can slow the rotation of the inner core in general agreement with the observed ''initial'' rotation rates of pulsars. The MRI analysis suggests that localized fields ∼10{sup 12} G may exist at the boundary of the iron core. With both the ST and MRI mechanisms active in the 20 M {sub ☉} model, we find that the helium shell mixes entirely out into the envelope. Enhanced mixing could yield a population of yellow or even blue supergiant supernova progenitors that would not be standard SN IIP.« less

Preclinical evaluation of implantable cardioverter-defibrillator developed for magnetic resonance imaging use.

PubMed

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

2015-03-01

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

Burden of alcohol-related injuries on radiology services at a level I trauma center.

PubMed

Roudsari, Bahman; Psoter, Kevin J; Mack, Christopher; Vavilala, Monica S; Jarvik, Jeffrey G

2012-10-01

The purpose of our study was to evaluate the burden of alcohol-related injuries on a radiology department at a level 1 trauma center. We linked the trauma registry (2005-2009) of Harborview Medical Center to billing department data and extracted patient demographic and injury-related characteristics and the radiology services provided. Multivariate negative binomial analysis was used to evaluate the association between blood alcohol concentration (BAC) and CT and MRI utilization rates. A total of 125,776 CT and 4681 MRI examinations were performed on 27,274 patients during the study period. Higher BAC was generally associated with higher utilization rates for all types of CT even after adjusting for potential confounding variables. Compared with patients with a BAC of 0, the greatest increases in utilization were observed in individuals with a BAC of 240 mg/dL or more for head CT (incidence rate ratio [IRR], 1.43; 95% CI, 1.32-1.54), cervical spine (IRR, 1.45; 95% CI, 1.32-1.58), and maxillofacial (IRR, 1.66; 95% CI, 1.42-1.95), with no increase observed for MRI. This association was more prominent in less severely injured patients with utilization rates for head CT (IRR, 1.83; 95% CI, 1.56-2.13), abdomen (IRR, 1.46; 95% CI, 1.32-1.63), and thorax (IRR, 1.57; 95% CI, 1.30-1.89) in individuals with a BAC of 240 mg/dL or more compared with those with a BAC of 0. Higher BAC was associated with increased CT utilization for most body region-specific CT scans and was more strongly associated in patients with less severe injuries. Any guideline that could potentially decrease unnecessary imaging for patients with alcohol-involved injuries would represent a cost-saving strategy.

Prostate cancer gene 3 and multiparametric magnetic resonance can reduce unnecessary biopsies: decision curve analysis to evaluate predictive models.

PubMed

Busetto, Gian Maria; De Berardinis, Ettore; Sciarra, Alessandro; Panebianco, Valeria; Giovannone, Riccardo; Rosato, Stefano; D'Errigo, Paola; Di Silverio, Franco; Gentile, Vincenzo; Salciccia, Stefano

2013-12-01

To overcome the well-known prostate-specific antigen limits, several new biomarkers have been proposed. Since its introduction in clinical practice, the urinary prostate cancer gene 3 (PCA3) assay has shown promising results for prostate cancer (PC) detection. Furthermore, multiparametric magnetic resonance imaging (mMRI) has the ability to better describe several aspects of PC. A prospective study of 171 patients with negative prostate biopsy findings and a persistent high prostate-specific antigen level was conducted to assess the role of mMRI and PCA3 in identifying PC. All patients underwent the PCA3 test and mMRI before a second transrectal ultrasound-guided prostate biopsy. The accuracy and reliability of PCA3 (3 different cutoff points) and mMRI were evaluated. Four multivariate logistic regression models were analyzed, in terms of discrimination and the cost benefit, to assess the clinical role of PCA3 and mMRI in predicting the biopsy outcome. A decision curve analysis was also plotted. Repeated transrectal ultrasound-guided biopsy identified 68 new cases (41.7%) of PC. The sensitivity and specificity of the PCA3 test and mMRI was 68% and 49% and 74% and 90%, respectively. Evaluating the regression models, the best discrimination (area under the curve 0.808) was obtained using the full model (base clinical model plus mMRI and PCA3). The decision curve analysis, to evaluate the cost/benefit ratio, showed good performance in predicting PC with the model that included mMRI and PCA3. mMRI increased the accuracy and sensitivity of the PCA3 test, and the use of the full model significantly improved the cost/benefit ratio, avoiding unnecessary biopsies. Copyright © 2013 Elsevier Inc. All rights reserved.

Predicting individual brain functional connectivity using a Bayesian hierarchical model.

PubMed

Dai, Tian; Guo, Ying

2017-02-15

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

Development of a cerebrospinal fluid lateral reservoir model in rhesus monkeys (Macaca mulatta).

PubMed

Lester McCully, Cynthia M; Bacher, John; MacAllister, Rhonda P; Steffen-Smith, Emilie A; Saleem, Kadharbatcha; Thomas, Marvin L; Cruz, Rafael; Warren, Katherine E

2015-02-01

Rapid, serial, and humane collection of cerebrospinal fluid (CSF) in nonhuman primates (NHP) is an essential element of numerous research studies and is currently accomplished via two different models. The CSF reservoir model (FR) combines a catheter in the 4th ventricle with a flexible silastic reservoir to permit circulating CSF flow. The CSF lateral port model (LP) consists of a lateral ventricular catheter and an IV port that provides static access to CSF and volume restrictions on sample collection. The FR model is associated with an intensive, prolonged recovery and frequent postsurgical hydrocephalus and nonpatency, whereas the LP model is associated with an easier recovery. To maximize the advantages of both systems, we developed the CSF lateral reservoir model (LR), which combines the beneficial features of the 2 previous models but avoids their limitations by using a reservoir for circulating CSF flow combined with catheter placement in the lateral ventricle. Nine adult male rhesus monkeys were utilized in this study. Pre-surgical MRI was performed to determine the coordinates of the lateral ventricle and location of choroid plexus (CP). The coordinates were determined to avoid the CP and major blood vessels. The predetermined coordinates were 100% accurate, according to MRI validation. The LR system functioned successfully in 67% of cases for 221 d, and 44% remain functional at 426 to 510 d postoperatively. Compared with established models, our LR model markedly reduced postoperative complications and recovery time. Development of the LR model was successful in rhesus macaques and is a useful alternative to the FR and LP methods of CSF collection from nonhuman primates.

Advanced Imaging Adds Little Value in the Diagnosis of Femoroacetabular Impingement Syndrome.

PubMed

Cunningham, Daniel J; Paranjape, Chinmay S; Harris, Joshua D; Nho, Shane J; Olson, Steven A; Mather, Richard C

2017-12-20

Femoroacetabular impingement (FAI) syndrome is an increasingly recognized source of hip pain and disability in young active adults. In order to confirm the diagnosis, providers often supplement physical examination maneuvers and radiographs with intra-articular hip injection, magnetic resonance imaging (MRI), or magnetic resonance arthrography (MRA). Since diagnostic imaging represents the fastest rising cost segment in U.S. health care, there is a need for value-driven diagnostic algorithms. The purpose of this study was to identify cost-effective diagnostic strategies for symptomatic FAI, comparing history and physical examination (H&P) alone (utilizing only radiographic imaging) with supplementation with injection, MRI, or MRA. A simple-chain decision model run as a cost-utility analysis was constructed to assess the diagnostic value of the MRI, MRA, and injection that are added to the H&P and radiographs in diagnosing symptomatic FAI. Strategies were compared using the incremental cost-utility ratio (ICUR) with a willingness to pay (WTP) of $100,000/QALY (quality-adjusted life year). Direct costs were measured using the Humana database (PearlDiver). Diagnostic test accuracy, treatment outcome probabilities, and utilities were extracted from the literature. H&P with and without supplemental diagnostic injection was the most cost-effective. Adjunct injection was preferred in situations with a WTP of >$60,000/QALY, low examination sensitivity, and high FAI prevalence. With low disease prevalence and low examination sensitivity, as may occur in a general practitioner's office, H&P with injection was the most cost-effective strategy, whereas in the reciprocal scenario, H&P with injection was only favored at exceptionally high WTP (∼$990,000). H&P and radiographs with supplemental diagnostic injection are preferred over advanced imaging, even with reasonable deviations from published values of disease prevalence, test sensitivity, and test specificity. Providers with low examination sensitivity in situations with low disease prevalence may benefit most from including injection in their diagnostic strategy. Providers with high examination sensitivity in situations with high disease prevalence may not benefit from including injection in their diagnostic strategy. Providers should not routinely rely on advanced imaging to diagnose FAI syndrome, although advanced imaging may have a role in challenging clinical scenarios. Economic and Decision Analysis Level IV. See Instructions for Authors for a complete description of levels of evidence.

First multimodal embolization particles visible on x-ray/computed tomography and magnetic resonance imaging.

PubMed

Bartling, Soenke H; Budjan, Johannes; Aviv, Hagit; Haneder, Stefan; Kraenzlin, Bettina; Michaely, Henrik; Margel, Shlomo; Diehl, Steffen; Semmler, Wolfhard; Gretz, Norbert; Schönberg, Stefan O; Sadick, Maliha

2011-03-01

Embolization therapy is gaining importance in the treatment of malignant lesions, and even more in benign lesions. Current embolization materials are not visible in imaging modalities. However, it is assumed that directly visible embolization material may provide several advantages over current embolization agents, ranging from particle shunt and reflux prevention to improved therapy control and follow-up assessment. X-ray- as well as magnetic resonance imaging (MRI)-visible embolization materials have been demonstrated in experiments. In this study, we present an embolization material with the property of being visible in more than one imaging modality, namely MRI and x-ray/computed tomography (CT). Characterization and testing of the substance in animal models was performed. To reduce the chance of adverse reactions and to facilitate clinical approval, materials have been applied that are similar to those that are approved and being used on a routine basis in diagnostic imaging. Therefore, x-ray-visible Iodine was combined with MRI-visible Iron (Fe3O4) in a macroparticle (diameter, 40-200 μm). Its core, consisting of a copolymerized monomer MAOETIB (2-methacryloyloxyethyl [2,3,5-triiodobenzoate]), was coated with ultra-small paramagnetic iron oxide nanoparticles (150 nm). After in vitro testing, including signal to noise measurements in CT and MRI (n = 5), its ability to embolize tissue was tested in an established tumor embolization model in rabbits (n = 6). Digital subtraction angiography (DSA) (Integris, Philips), CT (Definition, Siemens Healthcare Section, Forchheim, Germany), and MRI (3 Tesla Magnetom Tim Trio MRI, Siemens Healthcare Section, Forchheim, Germany) were performed before, during, and after embolization. Imaging signal changes that could be attributed to embolization particles were assessed by visual inspection and rated on an ordinal scale by 3 radiologists, from 1 to 3. Histologic analysis of organs was performed. Particles provided a sufficient image contrast on DSA, CT (signal to noise [SNR], 13 ± 2.5), and MRI (SNR, 35 ± 1) in in vitro scans. Successful embolization of renal tissue was confirmed by catheter angiography, revealing at least partial perfusion stop in all kidneys. Signal changes that were attributed to particles residing within the kidney were found in all cases in all the 3 imaging modalities. Localization distribution of particles corresponded well in all imaging modalities. Dynamic imaging during embolization provided real-time monitoring of the inflow of embolization particles within DSA, CT, and MRI. Histologic visualization of the residing particles as well as associated thrombosis in renal arteries could be performed. Visual assessment of the likelihood of embolization particle presence received full rating scores (153/153) after embolization. Multimodal-visible embolization particles have been developed, characterized, and tested in vivo in an animal model. Their implementation in clinical radiology may provide optimization of embolization procedures with regard to prevention of particle misplacement and direct intraprocedural visualization, at the same time improving follow-up examinations by utilizing the complementary characteristics of CT and MRI. Radiation dose savings can also be considered. All these advantages could contribute to future refinements and improvements in embolization therapy. Additionally, new approaches in embolization research may open up.

MRI reconstruction with joint global regularization and transform learning.

PubMed

Tanc, A Korhan; Eksioglu, Ender M

2016-10-01

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

Real-time myocardium segmentation for the assessment of cardiac function variation

NASA Astrophysics Data System (ADS)

Zoehrer, Fabian; Huellebrand, Markus; Chitiboi, Teodora; Oechtering, Thekla; Sieren, Malte; Frahm, Jens; Hahn, Horst K.; Hennemuth, Anja

2017-03-01

Recent developments in MRI enable the acquisition of image sequences with high spatio-temporal resolution. Cardiac motion can be captured without gating and triggering. Image size and contrast relations differ from conventional cardiac MRI cine sequences requiring new adapted analysis methods. We suggest a novel segmentation approach utilizing contrast invariant polar scanning techniques. It has been tested with 20 datasets of arrhythmia patients. The results do not differ significantly more between automatic and manual segmentations than between observers. This indicates that the presented solution could enable clinical applications of real-time MRI for the examination of arrhythmic cardiac motion in the future.

The NAIMS cooperative pilot project: Design, implementation and future directions.

PubMed

Oh, Jiwon; Bakshi, Rohit; Calabresi, Peter A; Crainiceanu, Ciprian; Henry, Roland G; Nair, Govind; Papinutto, Nico; Constable, R Todd; Reich, Daniel S; Pelletier, Daniel; Rooney, William; Schwartz, Daniel; Tagge, Ian; Shinohara, Russell T; Simon, Jack H; Sicotte, Nancy L

2017-10-01

The North American Imaging in Multiple Sclerosis (NAIMS) Cooperative represents a network of 27 academic centers focused on accelerating the pace of magnetic resonance imaging (MRI) research in multiple sclerosis (MS) through idea exchange and collaboration. Recently, NAIMS completed its first project evaluating the feasibility of implementation and reproducibility of quantitative MRI measures derived from scanning a single MS patient using a high-resolution 3T protocol at seven sites. The results showed the feasibility of utilizing advanced quantitative MRI measures in multicenter studies and demonstrated the importance of careful standardization of scanning protocols, central image processing, and strategies to account for inter-site variability.

A review of technical aspects of T1-weighted dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in human brain tumors.

PubMed

Bergamino, M; Bonzano, L; Levrero, F; Mancardi, G L; Roccatagliata, L

2014-09-01

In the last few years, several imaging methods, such as magnetic resonance imaging (MRI) and computed tomography, have been used to investigate the degree of blood-brain barrier (BBB) permeability in patients with neurological diseases including multiple sclerosis, ischemic stroke, and brain tumors. One promising MRI method for assessing the BBB permeability of patients with neurological diseases in vivo is T1-weighted dynamic contrast-enhanced (DCE)-MRI. Here we review the technical issues involved in DCE-MRI in the study of human brain tumors. In the first part of this paper, theoretical models for the DCE-MRI analysis will be described, including the Toft-Kety models, the adiabatic approximation to the tissue homogeneity model and the two-compartment exchange model. These models can be used to estimate important kinetic parameters related to BBB permeability. In the second part of this paper, details of the data acquisition, issues related to the arterial input function, and procedures for DCE-MRI image analysis are illustrated. Copyright © 2014 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Utility of MRI versus tumor markers for post-treatment surveillance of marker-positive CNS germ cell tumors.

PubMed

Cheung, Victoria; Segal, Devorah; Gardner, Sharon L; Zagzag, David; Wisoff, Jeffrey H; Allen, Jeffrey C; Karajannis, Matthias A

2016-09-01

Patients with marker-positive central nervous system (CNS) germ cell tumors are typically monitored for tumor recurrence with both tumor markers (AFP and b-hCG) and MRI. We hypothesize that the recurrence of these tumors will always be accompanied by an elevation in tumor markers, and that surveillance MRI may not be necessary. We retrospectively identified 28 patients with CNS germ cell tumors treated at our institution that presented with an elevated serum or cerebrospinal fluid (CSF) tumor marker at the time of diagnosis. We then identified those who had a tumor recurrence after having been in remission and whether each recurrence was detected via MRI changes, elevated tumor markers, or both. Four patients suffered a tumor recurrence. Only one patient had simultaneously elevated tumor markers and MRI evidence of recurrence. Two patients had evidence of recurrence on MRI without corresponding elevations in serum or CSF tumor markers. One patient had abnormal tumor markers with no evidence of recurrence on MRI until 6 months later. We conclude that in patients with marker-positive CNS germ cell tumors who achieve complete remission, continued surveillance imaging in addition to measurement of tumor markers is indicated to detect recurrences.

Clinical utility of resting-state functional connectivity magnetic resonance imaging for mood and cognitive disorders.

PubMed

Takamura, T; Hanakawa, T

2017-07-01

Although functional magnetic resonance imaging (fMRI) has long been used to assess task-related brain activity in neuropsychiatric disorders, it has not yet become a widely available clinical tool. Resting-state fMRI (rs-fMRI) has been the subject of recent attention in the fields of basic and clinical neuroimaging research. This method enables investigation of the functional organization of the brain and alterations of resting-state networks (RSNs) in patients with neuropsychiatric disorders. Rs-fMRI does not require participants to perform a demanding task, in contrast to task fMRI, which often requires participants to follow complex instructions. Rs-fMRI has a number of advantages over task fMRI for application with neuropsychiatric patients, for example, although applications of task fMR to participants for healthy are easy. However, it is difficult to apply these applications to patients with psychiatric and neurological disorders, because they may have difficulty in performing demanding cognitive task. Here, we review the basic methodology and analysis techniques relevant to clinical studies, and the clinical applications of the technique for examining neuropsychiatric disorders, focusing on mood disorders (major depressive disorder and bipolar disorder) and dementia (Alzheimer's disease and mild cognitive impairment).

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.

Utility of Magnetic Resonance Imaging for the Diagnosis of Appendicitis During Pregnancy: A Canadian Experience.

PubMed

Burns, Michael; Hague, Cameron J; Vos, Patrick; Tiwari, Pari; Wiseman, Sam M

2017-11-01

The objective of the study was to evaluate the performance of magnetic resonance imaging (MRI) for the diagnosis of appendicitis during pregnancy. We conducted a retrospective review of all MRI scans performed at our institution, between 2006 and 2012, for the evaluation of suspected appendicitis in pregnant women. Details of the MRI scans performed were obtained from the radiology information system as well as details of any ultrasounds carried out for the same indication. Clinical and pathological data were obtained by retrospective chart review. The study population comprised 63 patients, and 8 patients underwent a second MRI scan during the same pregnancy. A total of 71 MRI scans were reviewed. The appendix was identified on 40 scans (56.3%). Sensitivity of MRI was 75% and specificity was 100% for the diagnosis of appendicitis in pregnant women. When cases with right lower quadrant inflammatory fat stranding or focal fluid, without appendix visualization, were classified as positive for appendicitis, MRI sensitivity increased to 81.3% but specificity decreased to 96.4%. MRI is sensitive and highly specific for the diagnosis of appendicitis during pregnancy and should be considered as a first line imaging study for this clinical presentation. Copyright © 2017 Canadian Association of Radiologists. Published by Elsevier Inc. All rights reserved.

Targeting Accuracy, Procedure Times and User Experience of 240 Experimental MRI Biopsies Guided by a Clinical Add-On Navigation System.

PubMed

Busse, Harald; Riedel, Tim; Garnov, Nikita; Thörmer, Gregor; Kahn, Thomas; Moche, Michael

2015-01-01

MRI is of great clinical utility for the guidance of special diagnostic and therapeutic interventions. The majority of such procedures are performed iteratively ("in-and-out") in standard, closed-bore MRI systems with control imaging inside the bore and needle adjustments outside the bore. The fundamental limitations of such an approach have led to the development of various assistance techniques, from simple guidance tools to advanced navigation systems. The purpose of this work was to thoroughly assess the targeting accuracy, workflow and usability of a clinical add-on navigation solution on 240 simulated biopsies by different medical operators. Navigation relied on a virtual 3D MRI scene with real-time overlay of the optically tracked biopsy needle. Smart reference markers on a freely adjustable arm ensured proper registration. Twenty-four operators - attending (AR) and resident radiologists (RR) as well as medical students (MS) - performed well-controlled biopsies of 10 embedded model targets (mean diameter: 8.5 mm, insertion depths: 17-76 mm). Targeting accuracy, procedure times and 13 Likert scores on system performance were determined (strong agreement: 5.0). Differences in diagnostic success rates (AR: 93%, RR: 88%, MS: 81%) were not significant. In contrast, between-group differences in biopsy times (AR: 4:15, RR: 4:40, MS: 5:06 min:sec) differed significantly (p<0.01). Mean overall rating was 4.2. The average operator would use the system again (4.8) and stated that the outcome justifies the extra effort (4.4). Lowest agreement was reported for the robustness against external perturbations (2.8). The described combination of optical tracking technology with an automatic MRI registration appears to be sufficiently accurate for instrument guidance in a standard (closed-bore) MRI environment. High targeting accuracy and usability was demonstrated on a relatively large number of procedures and operators. Between groups with different expertise there were significant differences in experimental procedure times but not in the number of successful biopsies.

Mapping (and modeling) physiological movements during EEG-fMRI recordings: the added value of the video acquired simultaneously.

PubMed

Ruggieri, Andrea; Vaudano, Anna Elisabetta; Benuzzi, Francesca; Serafini, Marco; Gessaroli, Giuliana; Farinelli, Valentina; Nichelli, Paolo Frigio; Meletti, Stefano

2015-01-15

During resting-state EEG-fMRI studies in epilepsy, patients' spontaneous head-face movements occur frequently. We tested the usefulness of synchronous video recording to identify and model the fMRI changes associated with non-epileptic movements to improve sensitivity and specificity of fMRI maps related to interictal epileptiform discharges (IED). Categorization of different facial/cranial movements during EEG-fMRI was obtained for 38 patients [with benign epilepsy with centro-temporal spikes (BECTS, n=16); with idiopathic generalized epilepsy (IGE, n=17); focal symptomatic/cryptogenic epilepsy (n=5)]. We compared at single subject- and at group-level the IED-related fMRI maps obtained with and without additional regressors related to spontaneous movements. As secondary aim, we considered facial movements as events of interest to test the usefulness of video information to obtain fMRI maps of the following face movements: swallowing, mouth-tongue movements, and blinking. Video information substantially improved the identification and classification of the artifacts with respect to the EEG observation alone (mean gain of 28 events per exam). Inclusion of physiological activities as additional regressors in the GLM model demonstrated an increased Z-score and number of voxels of the global maxima and/or new BOLD clusters in around three quarters of the patients. Video-related fMRI maps for swallowing, mouth-tongue movements, and blinking were comparable to the ones obtained in previous task-based fMRI studies. Video acquisition during EEG-fMRI is a useful source of information. Modeling physiological movements in EEG-fMRI studies for epilepsy will lead to more informative IED-related fMRI maps in different epileptic conditions. Copyright © 2014 Elsevier B.V. All rights reserved.

MRI: are you playing your system like a fiddle or a Stradivarius? Where we are headed and how to keep up.

PubMed

Carroll-Callahan, Catherine M; Andersson, Lars A

2004-01-01

Dr. Raymond Damadian performed the first human magnetic resonance imaging (MRI) scan in 1977. Unveiled from behind the research curtain, MRI technology was introduced to the clinical environment by the mid 1980s. Most academic and largehospitals lined up right away and purchased their first scanners as soon as they became available. The race began, and the MRI learning process at radiology departments all over the world started. As with any growing technology, came a surge of competition--manufacturers as well as imaging facilities. MRI technology flooded the medical community, since it provided enormous benefits for patients and doctors. It was like a rocket launching with scientists and original equipment manufacturers (OEMs) researching, creating and contributing to the advancement of clinical science and forever improved diagnoses. Radiologists at UCLA predict that most of today's procedures currently falling under research will flourish in the clinical setting within the next 5 years. The rise of PET technology and the ability to fuse metabolic images with an anatomical MRI map will undoubtedly prove invaluable for staging of pathology, treatment planning and tracking, especially when the disease is present within soft tissue, like the brain. Another sign that MRI is a healthy addition to medical imaging is the increasing number of MRI reimbursement codes. However, Medicare, Medicaid and private insurance companies are also scrutinizing more and paying less today than they did yesterday. There will always be certain myths about how bigger is always better. That's not to say system enhancements and advancements are not essential to medical imaging, but the needs and budgets differ for each facility. Regardless of site needs or budget, it is imperative that all facilities utilize the equipment they have to their maximum potential. The new "bells and whistles" might not be needed to stay competitive. Innovative technology continues to be available as long as there is a need. However, buying bigger and better doesn't always mean you will utilize what's been bought to its full potential.

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.

In-Bore MR-Guided Biopsy Systems and Utility of PI-RADS.

PubMed

Fütterer, Jurgen J; Moche, Michael; Busse, Harald; Yakar, Derya

2016-06-01

A diagnostic dilemma exists in cases wherein a patient with clinical suspicion for prostate cancer has a negative transrectal ultrasound-guided biopsy session. Although transrectal ultrasound-guided biopsy is the standard of care, a paradigm shift is being observed. In biopsy-naive patients and patients with at least 1 negative biopsy session, multiparametric magnetic resonance imaging (MRI) is being utilized for tumor detection and subsequent targeting. Several commercial devices are now available for targeted prostate biopsy ranging from transrectal ultrasound-MR fusion biopsy to in bore MR-guided biopsy. In this review, we will give an update on the current status of in-bore MRI-guided biopsy systems and discuss value of prostate imaging-reporting and data system (PIRADS).

Impact of preoperative functional magnetic resonance imaging during awake craniotomy procedures for intraoperative guidance and complication avoidance.

PubMed

Trinh, Victoria T; Fahim, Daniel K; Maldaun, Marcos V C; Shah, Komal; McCutcheon, Ian E; Rao, Ganesh; Lang, Frederick; Weinberg, Jeffrey; Sawaya, Raymond; Suki, Dima; Prabhu, Sujit S

2014-01-01

We wanted to study the role of functional MRI (fMRI) in preventing neurological injury in awake craniotomy patients as this has not been previously studied. To examine the role of fMRI as an intraoperative adjunct during awake craniotomy procedures. Preoperative fMRI was carried out routinely in 214 patients undergoing awake craniotomy with direct cortical stimulation (DCS). In 40% of our cases (n = 85) fMRI was utilized for the intraoperative localization of the eloquent cortex. In the other 129 cases significant noise distortion, poor task performance and nonspecific BOLD activation precluded the surgeon from using the fMRI data. Compared with DCS, fMRI had a sensitivity and specificity, respectively, of 91 and 64% in Broca's area, 93 and 18% in Wernicke's area and 100 and 100% in motor areas. A new intraoperative neurological deficit during subcortical dissection was predictive of a worsened deficit following surgery (p < 0.001). The use of fMRI for intraoperative localization was, however, not significant in preventing worsened neurological deficits, both in the immediate postoperative period (p = 1.00) and at the 3-month follow-up (p = 0.42). The routine use of fMRI was not useful in identifying language sites as performed and, more importantly, practiced tasks failed to prevent neurological deficits following awake craniotomy procedures. © 2014 S. Karger AG, Basel.

Evaluation of expert criteria for preoperative magnetic resonance imaging of newly diagnosed breast cancer.

PubMed

Behrendt, Carolyn E; Tumyan, Lusine; Gonser, Laura; Shaw, Sara L; Vora, Lalit; Paz, I Benjamin; Ellenhorn, Joshua D I; Yim, John H

2014-08-01

Despite 2 randomized trials reporting no reduction in operations or local recurrence at 1 year, preoperative magnetic resonance imaging (MRI) is increasingly used in diagnostic workup of breast cancer. We evaluated 5 utilization criteria recently proposed by experts. Of women (n = 340) newly diagnosed with unilateral breast cancer who underwent bilateral MRI, most (69.4%) met at least 1 criterion before MRI: mammographic density (44.4%), under consideration for partial breast irradiation (PBI) (19.7%), genetic-familial risk (12.9%), invasive lobular carcinoma (11.8%), and multifocal/multicentric disease (10.6%). MRI detected occult malignant lesion or extension of index lesion in 21.2% of index, 3.3% of contralateral, breasts. No expert criterion was associated with MRI-detected malignant lesion, which associated instead with pre-MRI plan of lumpectomy without PBI (48.2% of subjects): Odds Ratio 3.05, 95% CI 1.57-5.91 (p adjusted for multiple hypothesis testing = 0.007, adjusted for index-vs-contralateral breast and covariates). The expert guidelines were not confirmed by clinical evidence. Copyright © 2014 Elsevier Ltd. All rights reserved.

R1 dispersion contrast at high field with fast field-cycling MRI.

PubMed

Bödenler, Markus; Basini, Martina; Casula, Maria Francesca; Umut, Evrim; Gösweiner, Christian; Petrovic, Andreas; Kruk, Danuta; Scharfetter, Hermann

2018-05-01

Contrast agents with a strong R 1 dispersion have been shown to be effective in generating target-specific contrast in MRI. The utilization of this R 1 field dependence requires the adaptation of an MRI scanner for fast field-cycling (FFC). Here, we present the first implementation and validation of FFC-MRI at a clinical field strength of 3 T. A field-cycling range of ±100 mT around the nominal B 0 field was realized by inserting an additional insert coil into an otherwise conventional MRI system. System validation was successfully performed with selected iron oxide magnetic nanoparticles and comparison to FFC-NMR relaxometry measurements. Furthermore, we show proof-of-principle R 1 dispersion imaging and demonstrate the capability of generating R 1 dispersion contrast at high field with suppressed background signal. With the presented ready-to-use hardware setup it is possible to investigate MRI contrast agents with a strong R 1 dispersion at a field strength of 3 T. Copyright © 2018 Elsevier Inc. All rights reserved.

Correlation of brain Magnetic Resonance Imaging of spontaneously lead poisoned bald eagles (Haliaeetus leucocephalus) with histological lesions: A pilot study.

PubMed

de Francisco, Olga Nicolas; Feeney, Daniel; Armién, Anibal G; Wuenschmann, Arno; Redig, Patrick T

2016-04-01

Six bald eagles with severe, acute lead poisoning based on blood lead values were analyzed by Magnetic Resonance Imaging (MRI) of the brain and histopathology. The aims of the study were to use MRI to locate brain lesions and correlate the changes in MRI signal with the histological character of the lesions at necropsy. All of the bald eagles presented with neurologic and non-neurologic signs suggestive of severe lead poisoning and had blood lead levels in excess of 1.0 ppm. Areas of change in image intensity in the brainstem, midbrain and cerebellum were detected in the MRI scans. Histopathology confirmed the presence of all suspected lesions. The character of the lesions suggested vascular damage as the primary insult. MRI was useful for detecting lesions and defining their three-dimensional distribution and extent. Future studies are needed to evaluate the utility of MRI for detection of lesions in less severely lead poisoned eagles and determining prognosis for treatment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Current whole-body MRI applications in the neurofibromatoses: NF1, NF2, and schwannomatosis.

PubMed

Ahlawat, Shivani; Fayad, Laura M; Khan, Muhammad Shayan; Bredella, Miriam A; Harris, Gordon J; Evans, D Gareth; Farschtschi, Said; Jacobs, Michael A; Chhabra, Avneesh; Salamon, Johannes M; Wenzel, Ralph; Mautner, Victor F; Dombi, Eva; Cai, Wenli; Plotkin, Scott R; Blakeley, Jaishri O

2016-08-16

The Response Evaluation in Neurofibromatosis and Schwannomatosis (REiNS) International Collaboration Whole-Body MRI (WB-MRI) Working Group reviewed the existing literature on WB-MRI, an emerging technology for assessing disease in patients with neurofibromatosis type 1 (NF1), neurofibromatosis type 2 (NF2), and schwannomatosis (SWN), to recommend optimal image acquisition and analysis methods to enable WB-MRI as an endpoint in NF clinical trials. A systematic process was used to review all published data about WB-MRI in NF syndromes to assess diagnostic accuracy, feasibility and reproducibility, and data about specific techniques for assessment of tumor burden, characterization of neoplasms, and response to therapy. WB-MRI at 1.5T or 3.0T is feasible for image acquisition. Short tau inversion recovery (STIR) sequence is used in all investigations to date, suggesting consensus about the utility of this sequence for detection of WB tumor burden in people with NF. There are insufficient data to support a consensus statement about the optimal imaging planes (axial vs coronal) or 2D vs 3D approaches. Functional imaging, although used in some NF studies, has not been systematically applied or evaluated. There are no comparative studies between regional vs WB-MRI or evaluations of WB-MRI reproducibility. WB-MRI is feasible for identifying tumors using both 1.5T and 3.0T systems. The STIR sequence is a core sequence. Additional investigation is needed to define the optimal approach for volumetric analysis, the reproducibility of WB-MRI in NF, and the diagnostic performance of WB-MRI vs regional MRI. © 2016 American Academy of Neurology.

ICN_Atlas: Automated description and quantification of functional MRI activation patterns in the framework of intrinsic connectivity networks.

PubMed

Kozák, Lajos R; van Graan, Louis André; Chaudhary, Umair J; Szabó, Ádám György; Lemieux, Louis

2017-12-01

Generally, the interpretation of functional MRI (fMRI) activation maps continues to rely on assessing their relationship to anatomical structures, mostly in a qualitative and often subjective way. Recently, the existence of persistent and stable brain networks of functional nature has been revealed; in particular these so-called intrinsic connectivity networks (ICNs) appear to link patterns of resting state and task-related state connectivity. These networks provide an opportunity of functionally-derived description and interpretation of fMRI maps, that may be especially important in cases where the maps are predominantly task-unrelated, such as studies of spontaneous brain activity e.g. in the case of seizure-related fMRI maps in epilepsy patients or sleep states. Here we present a new toolbox (ICN_Atlas) aimed at facilitating the interpretation of fMRI data in the context of ICN. More specifically, the new methodology was designed to describe fMRI maps in function-oriented, objective and quantitative way using a set of 15 metrics conceived to quantify the degree of 'engagement' of ICNs for any given fMRI-derived statistical map of interest. We demonstrate that the proposed framework provides a highly reliable quantification of fMRI activation maps using a publicly available longitudinal (test-retest) resting-state fMRI dataset. The utility of the ICN_Atlas is also illustrated on a parametric task-modulation fMRI dataset, and on a dataset of a patient who had repeated seizures during resting-state fMRI, confirmed on simultaneously recorded EEG. The proposed ICN_Atlas toolbox is freely available for download at http://icnatlas.com and at http://www.nitrc.org for researchers to use in their fMRI investigations. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Correlated gene expression and anatomical communication support synchronized brain activity in the mouse functional connectome.

PubMed

Mills, Brian D; Grayson, David S; Shunmugavel, Anandakumar; Miranda-Dominguez, Oscar; Feczko, Eric; Earl, Eric; Neve, Kim; Fair, Damien A

2018-05-22

Cognition and behavior depend on synchronized intrinsic brain activity that is organized into functional networks across the brain. Research has investigated how anatomical connectivity both shapes and is shaped by these networks, but not how anatomical connectivity interacts with intra-areal molecular properties to drive functional connectivity. Here, we present a novel linear model to explain functional connectivity by integrating systematically obtained measurements of axonal connectivity, gene expression, and resting state functional connectivity MRI in the mouse brain. The model suggests that functional connectivity arises from both anatomical links and inter-areal similarities in gene expression. By estimating these effects, we identify anatomical modules in which correlated gene expression and anatomical connectivity support functional connectivity. Along with providing evidence that not all genes equally contribute to functional connectivity, this research establishes new insights regarding the biological underpinnings of coordinated brain activity measured by BOLD fMRI. SIGNIFICANCE STATEMENT Efforts at characterizing the functional connectome with fMRI have risen exponentially over the last decade. Yet despite this rise, the biological underpinnings of these functional measurements are still largely unknown. The current report begins to fill this void by investigating the molecular underpinnings of the functional connectome through an integration of systematically obtained structural information and gene expression data throughout the rodent brain. We find that both white matter connectivity and similarity in regional gene expression relate to resting state functional connectivity. The current report furthers our understanding of the biological underpinnings of the functional connectome and provides a linear model that can be utilized to streamline preclinical animal studies of disease. Copyright © 2018 the authors.

Cerebrospinal and Interstitial Fluid Transport via the Glymphatic Pathway Modeled by Optimal Mass Transport

PubMed Central

Ratner, Vadim; Gao, Yi; Lee, Hedok; Elkin, Rena; Nedergaard, Maiken; Benveniste, Helene; Tannenbaum, Allen

2017-01-01

The glymphatic pathway is a system which facilitates continuous cerebrospinal fluid (CSF) and interstitial fluid (ISF) exchange and plays a key role in removing waste products from the rodent brain. Dysfunction of the glymphatic pathway may be implicated in the pathophysiology of Alzheimer's disease. Intriguingly, the glymphatic system is most active during deep wave sleep general anesthesia. By using paramagnetic tracers administered into CSF of rodents, we previously showed the utility of MRI in characterizing a macroscopic whole brain view of glymphatic transport but we have yet to define and visualize the specific flow patterns. Here we have applied an alternative mathematical analysis approach to a dynamic time series of MRI images acquired every 4 min over ∼3 hrs in anesthetized rats, following administration of a small molecular weight paramagnetic tracer into the CSF reservoir of the cisterna magna. We use Optimal Mass Transport (OMT) to model the glymphatic flow vector field, and then analyze the flow to find the network of CSF-ISF flow channels. We use 3D visualization computational tools to visualize the OMT defined network of CSF-ISF flow channels in relation to anatomical and vascular key landmarks from the live rodent brain. The resulting OMT model of the glymphatic transport network agrees largely with the current understanding of the glymphatic transport patterns defined by dynamic contrast-enhanced MRI revealing key CSF transport pathways along the ventral surface of the brain with a trajectory towards the pineal gland, cerebellum, hypothalamus and olfactory bulb. In addition, the OMT analysis also revealed some interesting previously unnoticed behaviors regarding CSF transport involving parenchymal streamlines moving from ventral reservoirs towards the surface of the brain, olfactory bulb and large central veins. PMID:28323163

Cerebrospinal and interstitial fluid transport via the glymphatic pathway modeled by optimal mass transport.

PubMed

Ratner, Vadim; Gao, Yi; Lee, Hedok; Elkin, Rena; Nedergaard, Maiken; Benveniste, Helene; Tannenbaum, Allen

2017-05-15

The glymphatic pathway is a system which facilitates continuous cerebrospinal fluid (CSF) and interstitial fluid (ISF) exchange and plays a key role in removing waste products from the rodent brain. Dysfunction of the glymphatic pathway may be implicated in the pathophysiology of Alzheimer's disease. Intriguingly, the glymphatic system is most active during deep wave sleep general anesthesia. By using paramagnetic tracers administered into CSF of rodents, we previously showed the utility of MRI in characterizing a macroscopic whole brain view of glymphatic transport but we have yet to define and visualize the specific flow patterns. Here we have applied an alternative mathematical analysis approach to a dynamic time series of MRI images acquired every 4min over ∼3h in anesthetized rats, following administration of a small molecular weight paramagnetic tracer into the CSF reservoir of the cisterna magna. We use Optimal Mass Transport (OMT) to model the glymphatic flow vector field, and then analyze the flow to find the network of CSF-ISF flow channels. We use 3D visualization computational tools to visualize the OMT defined network of CSF-ISF flow channels in relation to anatomical and vascular key landmarks from the live rodent brain. The resulting OMT model of the glymphatic transport network agrees largely with the current understanding of the glymphatic transport patterns defined by dynamic contrast-enhanced MRI revealing key CSF transport pathways along the ventral surface of the brain with a trajectory towards the pineal gland, cerebellum, hypothalamus and olfactory bulb. In addition, the OMT analysis also revealed some interesting previously unnoticed behaviors regarding CSF transport involving parenchymal streamlines moving from ventral reservoirs towards the surface of the brain, olfactory bulb and large central veins. Copyright © 2017. Published by Elsevier Inc.

Study of ocular transport of drugs released from an intravitreal implant using magnetic resonance imaging.

PubMed

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

2005-02-01

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

Cardiac and pericardial tumors: A potential application of positron emission tomography-magnetic resonance imaging.

PubMed

Fathala, Ahmed; Abouzied, Mohei; AlSugair, Abdul-Aziz

2017-07-26

Cardiac and pericardial masses may be neoplastic, benign and malignant, non-neoplastic such as thrombus or simple pericardial cysts, or normal variants cardiac structure can also be a diagnostic challenge. Currently, there are several imaging modalities for diagnosis of cardiac masses; each technique has its inherent advantages and disadvantages. Echocardiography, is typically the initial test utilizes in such cases, Echocardiography is considered the test of choice for evaluation and detection of cardiac mass, it is widely available, portable, with no ionizing radiation and provides comprehensive evaluation of cardiac function and valves, however, echocardiography is not very helpful in many cases such as evaluation of extracardiac extension of mass, poor tissue characterization, and it is non diagnostic in some cases. Cross sectional imaging with cardiac computed tomography provides a three dimensional data set with excellent spatial resolution but utilizes ionizing radiation, intravenous iodinated contrast and relatively limited functional evaluation of the heart. Cardiac magnetic resonance imaging (CMR) has excellent contrast resolution that allows superior soft tissue characterization. CMR offers comprehensive evaluation of morphology, function, tissue characterization. The great benefits of CMR make CMR a highly useful tool in the assessment of cardiac masses. (Fluorine 18) fluorodeoxygluocse (FDG) positron emission tomography (PET) has become a corner stone in several oncological application such as tumor staging, restaging, treatment efficiency, FDG is a very useful imaging modality in evaluation of cardiac masses. A recent advance in the imaging technology has been the development of integrated PET-MRI system that utilizes the advantages of PET and MRI in a single examination. FDG PET-MRI provides complementary information on evaluation of cardiac masses. The purpose of this review is to provide several clinical scenarios on the incremental value of PET and MRI in the evaluation of cardiac masses.

Modeling fMRI signals can provide insights into neural processing in the cerebral cortex

PubMed Central

Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo

2015-01-01

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

Modeling fMRI signals can provide insights into neural processing in the cerebral cortex.

PubMed

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

2015-08-01

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

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.

PSNet: prostate segmentation on MRI based on a convolutional neural network.

PubMed

Tian, Zhiqiang; Liu, Lizhi; Zhang, Zhenfeng; Fei, Baowei

2018-04-01

Automatic segmentation of the prostate on magnetic resonance images (MRI) has many applications in prostate cancer diagnosis and therapy. We proposed a deep fully convolutional neural network (CNN) to segment the prostate automatically. Our deep CNN model is trained end-to-end in a single learning stage, which uses prostate MRI and the corresponding ground truths as inputs. The learned CNN model can be used to make an inference for pixel-wise segmentation. Experiments were performed on three data sets, which contain prostate MRI of 140 patients. The proposed CNN model of prostate segmentation (PSNet) obtained a mean Dice similarity coefficient of [Formula: see text] as compared to the manually labeled ground truth. Experimental results show that the proposed model could yield satisfactory segmentation of the prostate on MRI.

Ultrasound-based logistic regression model LR2 versus magnetic resonance imaging for discriminating between benign and malignant adnexal masses: a prospective study.

PubMed

Shimada, Kanane; Matsumoto, Koji; Mimura, Takashi; Ishikawa, Tetsuya; Munechika, Jiro; Ohgiya, Yoshimitsu; Kushima, Miki; Hirose, Yusuke; Asami, Yuka; Iitsuka, Chiaki; Miyamoto, Shingo; Onuki, Mamiko; Tsunoda, Hajime; Matsuoka, Ryu; Ichizuka, Kiyotake; Sekizawa, Akihiko

2018-06-01

The diagnostic performances of the International Ovarian Tumor Analysis (IOTA) ultrasound-based logistic regression model (LR2) and magnetic resonance imaging (MRI) in discriminating between benign and malignant adnexal masses have not been directly compared in a single study. Using the IOTA LR2 model and subjective interpretation of MRI findings by experienced radiologists, 265 consecutive patients with adnexal masses were preoperatively evaluated in two hospitals between February 2014 and December 2015. Definitive histological diagnosis of excised tissues was used as a gold standard. From the 265 study subjects, 54 (20.4%) tumors were histologically diagnosed as malignant (including 11 borderline and 3 metastatic tumors). Preoperative diagnoses of malignant tumors showed 91.7% total agreement between IOTA LR2 and MRI, with a kappa value of 0.77 [95% confidence interval (CI), 0.68-0.86]. Sensitivity of IOTA LR2 (0.94, 95% CI, 0.85-0.98) for predicting malignant tumors was similar to that of MRI (0.96, 95% CI, 0.87-0.99; P = 0.99), whereas specificity of IOTA LR2 (0.98, 95% CI, 0.95-0.99) was significantly higher than that of MRI (0.91, 95% CI, 0.87-0.95; P = 0.002). Combined IOTA LR2 and MRI results gave the greatest sensitivity (1.00, 95% CI, 0.93-1.00) and had similar specificity (0.91, 95% CI, 0.86-0.94) to MRI. The IOTA LR2 model had a similar sensitivity to MRI for discriminating between benign and malignant tumors and a higher specificity compared with MRI. Our findings suggest that the IOTA LR2 model, either alone or in conjunction with MRI, should be included in preoperative evaluation of adnexal masses.

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

PubMed Central

2013-01-01

Background 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. Methods 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. Results 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. Conclusion 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. PMID:24564961

Longitudinal assessment of mouse renal injury using high-resolution anatomic and magnetization transfer MR imaging.

PubMed

Wang, Feng; Jiang, Rosie; Takahashi, Keiko; Gore, John; Harris, Raymond C; Takahashi, Takamune; Quarles, C Chad

2014-11-01

The purpose of this study is to evaluate the utility of high-resolution non-invasive endogenous high-field MRI methods for the longitudinal structural and quantitative assessments of mouse kidney disease using the model of unilateral ureter obstruction (UUO). T1-weighted, T2-weighted and magnetization transfer (MT) imaging protocols were optimized to improve the regional contrast in mouse kidney. Conventional T1 and T2 weighted images were collected in UUO mice on day 0 (~3h), day 1, day 3 and day 6 after injury, on a 7 T small animal MRI system. Cortical and medullary thickness, corticomedullary contrast and Magnetization Transfer Ratio (MTR) were assessed longitudinally. Masson trichrome staining was used to histologically assess changes in tissue microstructure. Over the course of UUO progression there were significant (p<0.05) changes in thickness of cortex and outer medulla, and regional changes in T2 signal intensity and MTR values. Histological changes included tubular cell death, tubular dilation, urine retention, and interstitial fibrosis, assessed by histology. The MRI measures of renal cortical and medullary atrophy, cortical-medullary differentiation and MTR changes provide an endogenous, non-invasive and quantitative evaluation of renal morphology and tissue composition during UUO progression. Copyright © 2014 Elsevier Inc. All rights reserved.

MRI measurement of the temporal evolution of relative CMRO(2) during rat forepaw stimulation.

PubMed

Mandeville, J B; Marota, J J; Ayata, C; Moskowitz, M A; Weisskoff, R M; Rosen, B R

1999-11-01

This study reports the first measurement of the relative cerebral metabolic rate of oxygen utilization (rCMRO(2)) during functional brain activation with sufficient temporal resolution to address the dynamics of blood oxygen level-dependent (BOLD) MRI signal. During rat forepaw stimulation, rCMRO(2) was determined in somatosensory cortex at 3-sec intervals, using a model of BOLD signal and measurements of the change in BOLD transverse relaxation rate, the resting state BOLD transverse relaxation rate, relative cerebral blood flow (rCBF), and relative cerebral blood volume (rCBV). Average percentage changes from 10 to 30 sec after onset of forepaw stimulation for rCBF, rCBV, rCMRO(2), and BOLD relaxation rate were 62 +/- 16, 17 +/- 2, 19 +/- 17, and -26 +/- 12, respectively. A poststimulus undershoot in BOLD signal was quantitatively attributed to the temporal mismatch between changes in blood flow and volume, and not to the role of oxygen metabolism. Magn Reson Med 42:944-951, 1999. Copyright 1999 Wiley-Liss, Inc.

Simulation of spatiotemporal CT data sets using a 4D MRI-based lung motion model.

PubMed

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

2014-05-01

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

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.

Correction for partial volume effect in PET blood flow images

NASA Astrophysics Data System (ADS)

Gage, Howard D.; Fahey, Fredrick H.; Santago, Peter, II; Harkness, Beth A.; Keyes, J. W.

1996-04-01

Current positron emission tomography techniques for the measurement of cerebral blood flow assume that voxels represent pure material regions. In this work, a method is presented which utilizes anatomical information from a high resolution modality such as MRI in conjunction with a multicompartment extension of the Kety model to obtain intravoxel, tissue specific blood flow values. In order to evaluate the proposed method, noisy time activity curves (TACs) were simulated representing different combinations of gray matter, white matter and CSF, and ratios of gray to white matter blood flow. In all experiments it was assumed that registered MR data supplied the number of materials and the fraction of each present. For each TAC, three experiments were run. In the first it was assumed that the fraction of each material determined by MRI was correct, and, in the second two, that the value was either too high or too low. Using the tree annealing method, material flows were determined which gave the best fit of the model to the simulated TAC data. The results indicate that the accuracy of the method is approximately linearly related to the error in material fraction estimated for a voxel.

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

NASA Astrophysics Data System (ADS)

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

2005-04-01

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

Dielectric properties of 3D-printed materials for anatomy specific 3D-printed MRI coils

NASA Astrophysics Data System (ADS)

Behzadnezhad, Bahareh; Collick, Bruce D.; Behdad, Nader; McMillan, Alan B.

2018-04-01

Additive manufacturing provides a low-cost and rapid means to translate 3D designs into the construction of a prototype. For MRI, this type of manufacturing can be used to construct various components including the structure of RF coils. In this paper, we characterize the material properties (dielectric constant and loss tangent) of several common 3D-printed polymers in the MRI frequency range of 63-300 MHz (for MRI magnetic field strengths of 1.5-7 T), and utilize these material properties in full-wave electromagnetic simulations to design and construct a very low-cost subject/anatomy-specific 3D-printed receive-only RF coil that fits close to the body. We show that the anatomy-specific coil exhibits higher signal-to-noise ratio compared to a conventional flat surface coil.

Cardiac CT and MRI for congenital heart disease in Asian countries: recent trends in publication based on a scientific database.

PubMed

Tsai, I-Chen; Goo, Hyun Woo

2013-06-01

In the past 12 years, during the process of imaging congenital heart disease (CHD), Asian doctors have not only made every effort to adhere to established magnetic resonance imaging (MRI) protocols as in Western countries, but also have developed Computed tomography (CT) as an alternative problem-solving technique. Databases have shown that Asian doctors were more inclined to utilize CT than MRI in evaluating CHD. Articles in the literature focusing on CT have been cited more frequently than articles on MRI. Additionally, several repeatedly cited CT articles have become seminal papers in this field. The database reflects a trend suggesting that Asian doctors actively adapt to new techniques and flexibly develop unique strategies to overcome limitations caused by the relatively limited resources often available to them.

Diagnosis and management of transfusion iron overload: The role of imaging

PubMed Central

Wood, John C.

2010-01-01

The characterization of iron stores is important to prevent and treat iron overload. Serum markers such as ferritin, serum iron, iron binding capacity, transferrin saturation, and nontransferrin-bound iron can be used to follow trends in iron status; however, variability in these markers limits predictive power for any given individual. Liver iron represents the best single marker of total iron balance. Measures of liver iron include biopsy, superconducting quantum interference device, computer tomography, and magnetic resonance imaging (MRI). MRI is the most accurate and widely available noninvasive tool to assess liver iron. The main advantages of MRI include a low-rate of variability between measurements and the ability to assess iron loading in endocrine tissues, the heart and the liver. This manuscript describes the principles, validation, and clinical utility of MRI for tissue iron estimation. PMID:17963249

Comparison of Dynamic Contrast Enhanced MRI and Quantitative SPECT in a Rat Glioma Model

PubMed Central

Skinner, Jack T.; Yankeelov, Thomas E.; Peterson, Todd E.; Does, Mark D.

2012-01-01

Pharmacokinetic modeling of dynamic contrast enhanced (DCE)-MRI data provides measures of the extracellular volume fraction (ve) and the volume transfer constant (Ktrans) in a given tissue. These parameter estimates may be biased, however, by confounding issues such as contrast agent and tissue water dynamics, or assumptions of vascularization and perfusion made by the commonly used model. In contrast to MRI, radiotracer imaging with SPECT is insensitive to water dynamics. A quantitative dual-isotope SPECT technique was developed to obtain an estimate of ve in a rat glioma model for comparison to the corresponding estimates obtained using DCE-MRI with a vascular input function (VIF) and reference region model (RR). Both DCE-MRI methods produced consistently larger estimates of ve in comparison to the SPECT estimates, and several experimental sources were postulated to contribute to these differences. PMID:22991315

MRI versus breast-specific gamma imaging (BSGI) in newly diagnosed ductal cell carcinoma-in-situ: a prospective head-to-head trial.

PubMed

Keto, Jessica L; Kirstein, Laurie; Sanchez, Diana P; Fulop, Tamara; McPartland, Laura; Cohen, Ilona; Boolbol, Susan K

2012-01-01

Mammography remains the standard imaging technique for the diagnosis of ductal carcinoma-in-situ (DCIS). Functional breast imaging, including breast magnetic resonance imaging (MRI), has known limitations in evaluating DCIS. To date, there are limited data on the utility of breast-specific gamma imaging (BSGI) in DCIS. We sought to prospectively compare the sensitivity of BSGI to MRI in newly diagnosed DCIS patients. Patients with newly diagnosed DCIS from June 1, 2009, through May 31, 2010, underwent a protocol with both breast MRI and BSGI. Each imaging study was read by a separate dedicated breast radiologist. Patients were excluded if excisional biopsy was performed for diagnosis, if their MRI was performed at an outside facility, or if final pathology revealed invasive carcinoma. There were 18 patients enrolled onto the study that had both MRI and BSGI for newly diagnosed DCIS. The sensitivity for MRI was 94% and for BSGI was 89% (P > 0.5, NS). There was one index tumor not seen on either MRI or BSGI, and one index tumor seen on MRI but not visualized on BSGI. Although BSGI has previously been shown to be as sensitive as MRI for detecting known invasive breast carcinoma, this study shows that BSGI is equally as sensitive as MRI at detecting newly diagnosed DCIS. As a result of the limited number of patients enrolled onto the study, larger prospective studies need to be performed to determine the true sensitivity and specificity of BSGI.

Development and preliminary evaluation of an ultrasonic motor actuated needle guide for 3T MRI-guided transperineal prostate interventions

NASA Astrophysics Data System (ADS)

Song, Sang-Eun; Tokuda, Junichi; Tuncali, Kemal; Tempany, Clare; Hata, Nobuhiko

2012-02-01

Image guided prostate interventions have been accelerated by Magnetic Resonance Imaging (MRI) and robotic technologies in the past few years. However, transrectal ultrasound (TRUS) guided procedure still remains as vast majority in clinical practice due to engineering and clinical complexity of the MRI-guided robotic interventions. Subsequently, great advantages and increasing availability of MRI have not been utilized at its maximum capacity in clinic. To benefit patients from the advantages of MRI, we developed an MRI-compatible motorized needle guide device "Smart Template" that resembles a conventional prostate template to perform MRI-guided prostate interventions with minimal changes in the clinical procedure. The requirements and specifications of the Smart Template were identified from our latest MRI-guided intervention system that has been clinically used in manual mode for prostate biopsy. Smart Template consists of vertical and horizontal crossbars that are driven by two ultrasonic motors via timing-belt and mitergear transmissions. Navigation software that controls the crossbar position to provide needle insertion positions was also developed. The software can be operated independently or interactively with an open-source navigation software, 3D Slicer, that has been developed for prostate intervention. As preliminary evaluation, MRI distortion and SNR test were conducted. Significant MRI distortion was found close to the threaded brass alloy components of the template. However, the affected volume was limited outside the clinical region of interest. SNR values over routine MRI scan sequences for prostate biopsy indicated insignificant image degradation during the presence of the robotic system and actuation of the ultrasonic motors.

A comparison of the diagnostic accuracy of magnetic resonance imaging to axillary ultrasound in the detection of axillary nodal metastases in newly diagnosed breast cancer.

PubMed

Assing, Matthew A; Patel, Bhavika K; Karamsadkar, Neel; Weinfurtner, Jared; Usmani, Omar; Kiluk, John V; Drukteinis, Jennifer S

2017-11-01

Patients with a diagnosis of invasive breast cancer are increasingly undergoing breast magnetic resonance imaging (MRI) for preoperative staging including evaluation of axillary lymph node metastases (ALNM). This retrospective study aims to evaluate the utility of adding axillary ultrasound (AUS) in the preoperative setting when an MRI is planned or has already been performed. This IRB approved, HIPAA compliant study reviewed a total of 271 patients with a new diagnosis of invasive breast cancer at a single institution, between June 1, 2010 and June 30, 2013. The study included patients who received both AUS and MRI for preoperative staging. Data were divided into two cohorts, patients who underwent MRI prior to AUS and those who underwent AUS prior to MRI. AUS and MRI reports were categorized according to BI-RADS criteria as "suspicious" or "not suspicious" for ALNM. In the setting of a negative MRI and subsequent positive AUS, only one out of 25 cases (4%) were positive for metastases after correlating with histologic pathology. MRI detected metastatic disease in four out of 27 (15%) patients who had false-negative AUS performed prior to MRI. Our results indicate the addition of AUS after preoperative MRI does not contribute significantly to increased detection of missed disease. MRI could serve as the initial staging imaging method of the axilla in the setting that AUS is not initially performed and may be valuable in identification of lymph nodes not identified on AUS. © 2017 Wiley Periodicals, Inc.

Potential of PET-MRI for imaging of non-oncologic musculoskeletal disease.

PubMed

Kogan, Feliks; Fan, Audrey P; Gold, Garry E

2016-12-01

Early detection of musculoskeletal disease leads to improved therapies and patient outcomes, and would benefit greatly from imaging at the cellular and molecular level. As it becomes clear that assessment of multiple tissues and functional processes are often necessary to study the complex pathogenesis of musculoskeletal disorders, the role of multi-modality molecular imaging becomes increasingly important. New positron emission tomography-magnetic resonance imaging (PET-MRI) systems offer to combine high-resolution MRI with simultaneous molecular information from PET to study the multifaceted processes involved in numerous musculoskeletal disorders. In this article, we aim to outline the potential clinical utility of hybrid PET-MRI to these non-oncologic musculoskeletal diseases. We summarize current applications of PET molecular imaging in osteoarthritis (OA), rheumatoid arthritis (RA), metabolic bone diseases and neuropathic peripheral pain. Advanced MRI approaches that reveal biochemical and functional information offer complementary assessment in soft tissues. Additionally, we discuss technical considerations for hybrid PET-MR imaging including MR attenuation correction, workflow, radiation dose, and quantification.

Utility of fetal cardiac magnetic resonance imaging to assess fetuses with right aortic arch and right ductus arteriosus.

PubMed

Dong, Su-Zhen; Zhu, Ming

2018-06-01

To evaluate the utility of fetal cardiac magnetic resonance imaging (MRI) to diagnose right aortic arch (RAA) with right ductus arteriosus. This retrospective study included six fetuses with right aortic arch and right ductus arteriosus. The six fetal cases were examined using a 1.5-T magnetic resonance unit. The steady-state free precession (SSFP) and single-shot turbo spin echo (SSTSE) sequences were used to evaluate the fetal heart and airway. The gestational age of the six fetuses ranged from 22 to 35 weeks (mean, 26.5 weeks). The age of the pregnant women ranged from 23 to 40 years (mean 31 years). Fetal cardiac MRI diagnosed the six fetal cases with RAA with right ductus arteriosus correctly. Among the six fetuses, four were associated with other congenital heart defects. In three of six cases, the diagnoses established using prenatal echocardiography (echo) was correct when compared with postnatal diagnosis. Fetal cardiac MRI is a useful complementary tool to assess fetuses with RAA and right ductus arteriosus.

Anti-CEA-functionalized superparamagnetic iron oxide nanoparticles for examining colorectal tumors in vivo

NASA Astrophysics Data System (ADS)

Huang, Kai-Wen; Chieh, Jen-Jie; Lin, In-Tsang; Horng, Herng-Er; Yang, Hong-Chang; Hong, Chin-Yih

2013-10-01

Although the biomarker carcinoembryonic antigen (CEA) is expressed in colorectal tumors, the utility of an anti-CEA-functionalized image medium is powerful for in vivo positioning of colorectal tumors. With a risk of superparamagnetic iron oxide nanoparticles (SPIONPs) that is lower for animals than other material carriers, anti-CEA-functionalized SPIONPs were synthesized in this study for labeling colorectal tumors by conducting different preoperatively and intraoperatively in vivo examinations. In magnetic resonance imaging (MRI), the image variation of colorectal tumors reached the maximum at approximately 24 h. However, because MRI requires a nonmetal environment, it was limited to preoperative imaging. With the potentiality of in vivo screening and intraoperative positioning during surgery, the scanning superconducting-quantum-interference-device biosusceptometry (SSB) was adopted, showing the favorable agreement of time-varied intensity with MRI. Furthermore, biological methodologies of different tissue staining methods and inductively coupled plasma (ICP) yielded consistent results, proving that the obtained in vivo results occurred because of targeted anti-CEA SPIONPs. This indicates that developed anti-CEA SPIONPs owe the utilities as an image medium of these in vivo methodologies.

Real-Time MRI-Guided Endovascular Recanalization of Chronic Total Arterial Occlusion in a Swine Model

PubMed Central

Raval, Amish N.; Karmarkar, Parag V.; Guttman, Michael A.; Ozturk, Cengizhan; Sampath, Smita; DeSilva, Ranil; Aviles, Ronnier J.; Xu, Minnan; Wright, Victor J.; Schenke, William H.; Kocaturk, Ozgur; Dick, Alexander J.; Raman, Venkatesh K.; Atalar, Ergin; McVeigh, Elliot R.; Lederman, Robert J.

2006-01-01

Background Endovascular recanalization (guidewire traversal) of peripheral artery chronic total occlusion (CTO) can be challenging. X-Ray angiography resolves CTO poorly. Virtually “blind” device advancement during X-ray-guided interventions can lead to procedure failure, perforation and hemorrhage. Alternatively, magnetic resonance imaging (MRI) may delineate the artery within the occluded segment to enhance procedural safety and success. We hypothesized that real-time MRI (rtMRI) guided CTO recanalization can be accomplished in an animal model. Methods and Results Carotid artery CTO was created by balloon injury in 19 lipid overfed swine. After 6–8 weeks, two underwent direct necropsy analysis for histology, three underwent primary X-ray-guided CTO recanalization attempts, and the remaining 14 underwent rtMRI-guided recanalization attempts in a 1.5T interventional MRI system. rtMRI intervention used custom CTO catheters and guidewires that incorporated MRI receiver antennae to enhance device visibility. The mean length of the occluded segments was 13.3 ± 1.6cm. rtMRI-guided CTO recanalization was successful in 11/14 swine and only 1/3 swine using X-ray alone. After unsuccessful rtMRI (n = 3), X-ray-guided attempts also were all unsuccessful. Conclusions Recanalization of long CTO is feasible entirely using rtMRI guidance. Low profile clinical-grade devices will be required to translate this experience to humans. Endovascular recanalization of chronic total arterial occlusion (CTO) is challenging under conventional X-ray guidance because devices are advanced almost blindly. MRI can image CTO borders and luminal contents, and could potentially guide these procedures. We test the feasibility of real-time MRI guided wire traversal in a swine model of peripheral artery CTO using custom active MRI catheters. PMID:16490819

Learning Computational Models of Video Memorability from fMRI Brain Imaging.

PubMed

Han, Junwei; Chen, Changyuan; Shao, Ling; Hu, Xintao; Han, Jungong; Liu, Tianming

2015-08-01

Generally, various visual media are unequally memorable by the human brain. This paper looks into a new direction of modeling the memorability of video clips and automatically predicting how memorable they are by learning from brain functional magnetic resonance imaging (fMRI). We propose a novel computational framework by integrating the power of low-level audiovisual features and brain activity decoding via fMRI. Initially, a user study experiment is performed to create a ground truth database for measuring video memorability and a set of effective low-level audiovisual features is examined in this database. Then, human subjects' brain fMRI data are obtained when they are watching the video clips. The fMRI-derived features that convey the brain activity of memorizing videos are extracted using a universal brain reference system. Finally, due to the fact that fMRI scanning is expensive and time-consuming, a computational model is learned on our benchmark dataset with the objective of maximizing the correlation between the low-level audiovisual features and the fMRI-derived features using joint subspace learning. The learned model can then automatically predict the memorability of videos without fMRI scans. Evaluations on publically available image and video databases demonstrate the effectiveness of the proposed framework.

Utility and Scope of Rapid Prototyping in Patients with Complex Muscular Ventricular Septal Defects or Double-Outlet Right Ventricle: Does it Alter Management Decisions?

PubMed

Bhatla, Puneet; Tretter, Justin T; Ludomirsky, Achi; Argilla, Michael; Latson, Larry A; Chakravarti, Sujata; Barker, Piers C; Yoo, Shi-Joon; McElhinney, Doff B; Wake, Nicole; Mosca, Ralph S

2017-01-01

Rapid prototyping facilitates comprehension of complex cardiac anatomy. However, determining when this additional information proves instrumental in patient management remains a challenge. We describe our experience with patient-specific anatomic models created using rapid prototyping from various imaging modalities, suggesting their utility in surgical and interventional planning in congenital heart disease (CHD). Virtual and physical 3-dimensional (3D) models were generated from CT or MRI data, using commercially available software for patients with complex muscular ventricular septal defects (CMVSD) and double-outlet right ventricle (DORV). Six patients with complex anatomy and uncertainty of the optimal management strategy were included in this study. The models were subsequently used to guide management decisions, and the outcomes reviewed. 3D models clearly demonstrated the complex intra-cardiac anatomy in all six patients and were utilized to guide management decisions. In the three patients with CMVSD, one underwent successful endovascular device closure following a prior failed attempt at transcatheter closure, and the other two underwent successful primary surgical closure with the aid of 3D models. In all three cases of DORV, the models provided better anatomic delineation and additional information that altered or confirmed the surgical plan. Patient-specific 3D heart models show promise in accurately defining intra-cardiac anatomy in CHD, specifically CMVSD and DORV. We believe these models improve understanding of the complex anatomical spatial relationships in these defects and provide additional insight for pre/intra-interventional management and surgical planning.

A review of MRI evaluation of demyelination in cuprizone murine model

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

Krutenkova, E., E-mail: len--k@yandex.ru; Pan, E.; Khodanovich, M., E-mail: khodanovich@mail.tsu.ru

The cuprizone mouse model of non-autoimmune demyelination reproduces some phenomena of multiple sclerosis and is appropriate for validation and specification of a new method of non-invasive diagnostics. In the review new data which are collected using the new MRI method are compared with one or more conventional MRI tools. Also the paper reviewed the validation of MRI approaches using histological or immunohistochemical methods. Luxol fast blue histological staining and myelin basic protein immunostaining is widespread. To improve the accuracy of non-invasive conventional MRI, multimodal scanning could be applied. The new quantitative MRI method of fast mapping of the macromolecular protonmore » fraction is a reliable biomarker of myelin in the brain and can be used for research of demyelination in animals. To date, a validation of MPF method on the CPZ mouse model of demyelination is not performed, although this method is probably the best way to evaluate demyelination using MRI.« less

MR thermometry characterization of a hyperthermia ultrasound array designed using the k-space computational method

PubMed Central

Al-Bataineh, Osama M; Collins, Christopher M; Park, Eun-Joo; Lee, Hotaik; Smith, Nadine Barrie

2006-01-01

Background Ultrasound induced hyperthermia is a useful adjuvant to radiation therapy in the treatment of prostate cancer. A uniform thermal dose (43°C for 30 minutes) is required within the targeted cancerous volume for effective therapy. This requires specific ultrasound phased array design and appropriate thermometry method. Inhomogeneous, acoustical, three-dimensional (3D) prostate models and economical computational methods provide necessary tools to predict the appropriate shape of hyperthermia phased arrays for better focusing. This research utilizes the k-space computational method and a 3D human prostate model to design an intracavitary ultrasound probe for hyperthermia treatment of prostate cancer. Evaluation of the probe includes ex vivo and in vivo controlled hyperthermia experiments using the noninvasive magnetic resonance imaging (MRI) thermometry. Methods A 3D acoustical prostate model was created using photographic data from the Visible Human Project®. The k-space computational method was used on this coarse grid and inhomogeneous tissue model to simulate the steady state pressure wavefield of the designed phased array using the linear acoustic wave equation. To ensure the uniformity and spread of the pressure in the length of the array, and the focusing capability in the width of the array, the equally-sized elements of the 4 × 20 elements phased array were 1 × 14 mm. A probe was constructed according to the design in simulation using lead zerconate titanate (PZT-8) ceramic and a Delrin® plastic housing. Noninvasive MRI thermometry and a switching feedback controller were used to accomplish ex vivo and in vivo hyperthermia evaluations of the probe. Results Both exposimetry and k-space simulation results demonstrated acceptable agreement within 9%. With a desired temperature plateau of 43.0°C, ex vivo and in vivo controlled hyperthermia experiments showed that the MRI temperature at the steady state was 42.9 ± 0.38°C and 43.1 ± 0.80°C, respectively, for 20 minutes of heating. Conclusion Unlike conventional computational methods, the k-space method provides a powerful tool to predict pressure wavefield in large scale, 3D, inhomogeneous and coarse grid tissue models. Noninvasive MRI thermometry supports the efficacy of this probe and the feedback controller in an in vivo hyperthermia treatment of canine prostate. PMID:17064421

MR thermometry characterization of a hyperthermia ultrasound array designed using the k-space computational method.

PubMed

Al-Bataineh, Osama M; Collins, Christopher M; Park, Eun-Joo; Lee, Hotaik; Smith, Nadine Barrie

2006-10-25

Ultrasound induced hyperthermia is a useful adjuvant to radiation therapy in the treatment of prostate cancer. A uniform thermal dose (43 degrees C for 30 minutes) is required within the targeted cancerous volume for effective therapy. This requires specific ultrasound phased array design and appropriate thermometry method. Inhomogeneous, acoustical, three-dimensional (3D) prostate models and economical computational methods provide necessary tools to predict the appropriate shape of hyperthermia phased arrays for better focusing. This research utilizes the k-space computational method and a 3D human prostate model to design an intracavitary ultrasound probe for hyperthermia treatment of prostate cancer. Evaluation of the probe includes ex vivo and in vivo controlled hyperthermia experiments using the noninvasive magnetic resonance imaging (MRI) thermometry. A 3D acoustical prostate model was created using photographic data from the Visible Human Project. The k-space computational method was used on this coarse grid and inhomogeneous tissue model to simulate the steady state pressure wavefield of the designed phased array using the linear acoustic wave equation. To ensure the uniformity and spread of the pressure in the length of the array, and the focusing capability in the width of the array, the equally-sized elements of the 4 x 20 elements phased array were 1 x 14 mm. A probe was constructed according to the design in simulation using lead zerconate titanate (PZT-8) ceramic and a Delrin plastic housing. Noninvasive MRI thermometry and a switching feedback controller were used to accomplish ex vivo and in vivo hyperthermia evaluations of the probe. Both exposimetry and k-space simulation results demonstrated acceptable agreement within 9%. With a desired temperature plateau of 43.0 degrees C, ex vivo and in vivo controlled hyperthermia experiments showed that the MRI temperature at the steady state was 42.9 +/- 0.38 degrees C and 43.1 +/- 0.80 degrees C, respectively, for 20 minutes of heating. Unlike conventional computational methods, the k-space method provides a powerful tool to predict pressure wavefield in large scale, 3D, inhomogeneous and coarse grid tissue models. Noninvasive MRI thermometry supports the efficacy of this probe and the feedback controller in an in vivo hyperthermia treatment of canine prostate.

Presurgical language fMRI: Clinical practices and patient outcomes in epilepsy surgical planning.

PubMed

Benjamin, Christopher F A; Li, Alexa X; Blumenfeld, Hal; Constable, R Todd; Alkawadri, Rafeed; Bickel, Stephan; Helmstaedter, Christoph; Meletti, Stefano; Bronen, Richard; Warfield, Simon K; Peters, Jurriaan M; Reutens, David; Połczyńska, Monika; Spencer, Dennis D; Hirsch, Lawrence J

2018-03-12

The goal of this study was to document current clinical practice and report patient outcomes in presurgical language functional MRI (fMRI) for epilepsy surgery. Epilepsy surgical programs worldwide were surveyed as to the utility, implementation, and efficacy of language fMRI in the clinic; 82 programs responded. Respondents were predominantly US (61%) academic programs (85%), and evaluated adults (44%), adults and children (40%), or children only (16%). Nearly all (96%) reported using language fMRI. Surprisingly, fMRI is used to guide surgical margins (44% of programs) as well as lateralize language (100%). Sites using fMRI for localization most often use a distance margin around activation of 10mm. While considered useful, 56% of programs reported at least one instance of disagreement with other measures. Direct brain stimulation typically confirmed fMRI findings (74%) when guiding margins, but instances of unpredicted decline were reported by 17% of programs and 54% reported unexpected preservation of function. Programs reporting unexpected decline did not clearly differ from those which did not. Clinicians using fMRI to guide surgical margins do not typically map known language-critical areas beyond Broca's and Wernicke's. This initial data shows many clinical teams are confident using fMRI not only for language lateralization but also to guide surgical margins. Reported cases of unexpected language preservation when fMRI activation is resected, and cases of language decline when it is not, emphasize a critical need for further validation. Comprehensive studies comparing commonly-used fMRI paradigms to predict stimulation mapping and post-surgical language decline remain of high importance. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

"Let's get physical": advantages of a physical model over 3D computer models and textbooks in learning imaging anatomy.

PubMed

Preece, Daniel; Williams, Sarah B; Lam, Richard; Weller, Renate

2013-01-01

Three-dimensional (3D) information plays an important part in medical and veterinary education. Appreciating complex 3D spatial relationships requires a strong foundational understanding of anatomy and mental 3D visualization skills. Novel learning resources have been introduced to anatomy training to achieve this. Objective evaluation of their comparative efficacies remains scarce in the literature. This study developed and evaluated the use of a physical model in demonstrating the complex spatial relationships of the equine foot. It was hypothesized that the newly developed physical model would be more effective for students to learn magnetic resonance imaging (MRI) anatomy of the foot than textbooks or computer-based 3D models. Third year veterinary medicine students were randomly assigned to one of three teaching aid groups (physical model; textbooks; 3D computer model). The comparative efficacies of the three teaching aids were assessed through students' abilities to identify anatomical structures on MR images. Overall mean MRI assessment scores were significantly higher in students utilizing the physical model (86.39%) compared with students using textbooks (62.61%) and the 3D computer model (63.68%) (P < 0.001), with no significant difference between the textbook and 3D computer model groups (P = 0.685). Student feedback was also more positive in the physical model group compared with both the textbook and 3D computer model groups. Our results suggest that physical models may hold a significant advantage over alternative learning resources in enhancing visuospatial and 3D understanding of complex anatomical architecture, and that 3D computer models have significant limitations with regards to 3D learning. © 2013 American Association of Anatomists.

A receptor-based model for dopamine-induced fMRI signal

PubMed Central

Mandeville, Joseph. B.; Sander, Christin Y. M.; Jenkins, Bruce G.; Hooker, Jacob M.; Catana, Ciprian; Vanduffel, Wim; Alpert, Nathaniel M.; Rosen, Bruce R.; Normandin, Marc D.

2013-01-01

This report describes a multi-receptor physiological model of the fMRI temporal response and signal magnitude evoked by drugs that elevate synaptic dopamine in basal ganglia. The model is formulated as a summation of dopamine’s effects at D1-like and D2-like receptor families, which produce functional excitation and inhibition, respectively, as measured by molecular indicators like adenylate cyclase or neuroimaging techniques like fMRI. Functional effects within the model are described in terms of relative changes in receptor occupancies scaled by receptor densities and neuro-vascular coupling constants. Using literature parameters, the model reconciles many discrepant observations and interpretations of pre-clinical data. Additionally, we present data showing that amphetamine stimulation produces fMRI inhibition at low doses and a biphasic response at higher doses in the basal ganglia of non-human primates (NHP), in agreement with model predictions based upon the respective levels of evoked dopamine. Because information about dopamine release is required to inform the fMRI model, we simultaneously acquired PET 11C-raclopride data in several studies to evaluate the relationship between raclopride displacement and assumptions about dopamine release. At high levels of dopamine release, results suggest that refinements of the model will be required to consistently describe the PET and fMRI data. Overall, the remarkable success of the model in describing a wide range of preclinical fMRI data indicate that this approach will be useful for guiding the design and analysis of basic science and clinical investigations and for interpreting the functional consequences of dopaminergic stimulation in normal subjects and in populations with dopaminergic neuroadaptations. PMID:23466936

PET/NIRF/MRI triple functional iron oxide nanoparticles.

PubMed

Xie, Jin; Chen, Kai; Huang, Jing; Lee, Seulki; Wang, Jinhua; Gao, Jinhao; Li, Xingguo; Chen, Xiaoyuan

2010-04-01

Engineered nanoparticles with theranostic functions have attracted a lot of attention for their potential role in the dawning era of personalized medicine. Iron oxide nanoparticles (IONPs), with their advantages of being non-toxic, biodegradable and inexpensive, are candidate platforms for the buildup of theranostic nanostructures; however, progress in using them has been limited largely due to inefficient drug loading and delivery. In the current study, we utilized dopamine to modify the surface of IONPs, yielding nanoconjugates that can be easily encapsulated into human serum albumin (HSA) matrices (clinically utilized drug carriers). This nanosystem is well-suited for dual encapsulation of IONPs and drug molecules, because the encapsulation is achieved in a way that is similar to common drug loading. To assess the biophysical characteristics of this novel nanosystem, the HSA coated IONPs (HSA-IONPs) were dually labeled with (64)Cu-DOTA and Cy5.5, and tested in a subcutaneous U87MG xenograft mouse model. In vivo positron emission tomography (PET)/near-infrared fluorescence (NIRF)/magnetic resonance imaging (MRI) tri-modality imaging, and ex vivo analyses and histological examinations were carefully conducted to investigate the in vivo behavior of the nanostructures. With the compact HSA coating, the HSA-IONPs manifested a prolonged circulation half-life; more impressively, they showed massive accumulation in lesions, high extravasation rate, and low uptake of the particles by macrophages at the tumor area. Published by Elsevier Ltd.

Presurgical visualization of the neurovascular relationship in trigeminal neuralgia with 3D modeling using free Slicer software.

PubMed

Han, Kai-Wei; Zhang, Dan-Feng; Chen, Ji-Gang; Hou, Li-Jun

2016-11-01

To explore whether segmentation and 3D modeling are more accurate in the preoperative detection of the neurovascular relationship (NVR) in patients with trigeminal neuralgia (TN) compared to MRI fast imaging employing steady-state acquisition (FIESTA). Segmentation and 3D modeling using 3D Slicer were conducted for 40 patients undergoing MRI FIESTA and microsurgical vascular decompression (MVD). The NVR, as well as the offending vessel determined by MRI FIESTA and 3D Slicer, was reviewed and compared with intraoperative manifestations using SPSS. The k agreement between the MRI FIESTA and operation in determining the NVR was 0.232 and that between the 3D modeling and operation was 0.6333. There was no significant difference between these two procedures (χ 2  = 8.09, P = 0.088). The k agreement between the MRI FIESTA and operation in determining the offending vessel was 0.373, and that between the 3D modeling and operation was 0.922. There were significant differences between two of them (χ 2  = 82.01, P = 0.000). The sensitivity and specificity for MRI FIESTA in determining the NVR were 87.2 % and 100 %, respectively, and for 3D modeling were both 100 %. The segmentation and 3D modeling were more accurate than MRI FIESTA in preoperative verification of the NVR and offending vessel. This was consistent with surgical manifestations and was more helpful for the preoperative decision and surgical plan.

Understanding disease processes in multiple sclerosis through magnetic resonance imaging studies in animal models

PubMed Central

Nathoo, Nabeela; Yong, V. Wee; Dunn, Jeff F.

2014-01-01

There are exciting new advances in multiple sclerosis (MS) resulting in a growing understanding of both the complexity of the disorder and the relative involvement of grey matter, white matter and inflammation. Increasing need for preclinical imaging is anticipated, as animal models provide insights into the pathophysiology of the disease. Magnetic resonance (MR) is the key imaging tool used to diagnose and to monitor disease progression in MS, and thus will be a cornerstone for future research. Although gadolinium-enhancing and T2 lesions on MRI have been useful for detecting MS pathology, they are not correlative of disability. Therefore, new MRI methods are needed. Such methods require validation in animal models. The increasing necessity for MRI of animal models makes it critical and timely to understand what research has been conducted in this area and what potential there is for use of MRI in preclinical models of MS. Here, we provide a review of MRI and magnetic resonance spectroscopy (MRS) studies that have been carried out in animal models of MS that focus on pathology. We compare the MRI phenotypes of animals and patients and provide advice on how best to use animal MR studies to increase our understanding of the linkages between MR and pathology in patients. This review describes how MRI studies of animal models have been, and will continue to be, used in the ongoing effort to understand MS. PMID:24936425

Fiducial-based fusion of 3D dental models with magnetic resonance imaging.

PubMed

Abdi, Amir H; Hannam, Alan G; Fels, Sidney

2018-04-16

Magnetic resonance imaging (MRI) is widely used in study of maxillofacial structures. While MRI is the modality of choice for soft tissues, it fails to capture hard tissues such as bone and teeth. Virtual dental models, acquired by optical 3D scanners, are becoming more accessible for dental practice and are starting to replace the conventional dental impressions. The goal of this research is to fuse the high-resolution 3D dental models with MRI to enhance the value of imaging for applications where detailed analysis of maxillofacial structures are needed such as patient examination, surgical planning, and modeling. A subject-specific dental attachment was digitally designed and 3D printed based on the subject's face width and dental anatomy. The attachment contained 19 semi-ellipsoidal concavities in predetermined positions where oil-based ellipsoidal fiducial markers were later placed. The MRI was acquired while the subject bit on the dental attachment. The spatial position of the center of mass of each fiducial in the resultant MR Image was calculated by averaging its voxels' spatial coordinates. The rigid transformation to fuse dental models to MRI was calculated based on the least squares mapping of corresponding fiducials and solved via singular-value decomposition. The target registration error (TRE) of the proposed fusion process, calculated in a leave-one-fiducial-out fashion, was estimated at 0.49 mm. The results suggest that 6-9 fiducials suffice to achieve a TRE of equal to half the MRI voxel size. Ellipsoidal oil-based fiducials produce distinguishable intensities in MRI and can be used as registration fiducials. The achieved accuracy of the proposed approach is sufficient to leverage the merged 3D dental models with the MRI data for a finer analysis of the maxillofacial structures where complete geometry models are needed.

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

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

Viruslike Nanoparticles with Maghemite Cores Allow for Enhanced MRI Contrast Agents

DOE PAGES

Malyutin, Andrey G.; Easterday, Rosemary; Lozovyy, Yaroslav; ...

2014-12-15

Here, for the first time, we demonstrate formation of virus-like nanoparticles (VNPs) utilizing gold-coated iron oxide nanoparticles as cores and capsidprotein of brome mosaic virus (BMV) or hepatitis B virus (HBV) as shells. Further, utilizing cryo-electron microscopy and single particle methods, we are able to show that the BMV coat on VNPs assembles into a structure very close to that of a native virion. This is a consequence of an optimal iron oxide NP size (~11 nm) fitting the virus cavity and an ultrathin gold layer on the maghemite cores, which allows for utilization of SH-(CH 2) 11-(CH 2-CH 2-O)more » 4-OCH 2-COOH as capping molecules to provide sufficient stability, charge density, and small form factor. MRI studies show unique relaxivity ratios that diminish only slightly with gold coating. In conclusion, a virus protein coating of a magnetic core mimicking the wild-type virus makes these VNPs a versatile platform for biomedical applications.« less

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI.

PubMed

Chu, Shu-Hsien; Parhi, Keshab K; Lenglet, Christophe

2018-03-16

A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

DCE-MRI of the prostate using shutter-speed vs. Tofts model for tumor characterization and assessment of aggressiveness.

PubMed

Hectors, Stefanie J; Besa, Cecilia; Wagner, Mathilde; Jajamovich, Guido H; Haines, George K; Lewis, Sara; Tewari, Ashutosh; Rastinehad, Ardeshir; Huang, Wei; Taouli, Bachir

2017-09-01

To quantify Tofts model (TM) and shutter-speed model (SSM) perfusion parameters in prostate cancer (PCa) and noncancerous peripheral zone (PZ) and to compare the diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to Prostate Imaging and Reporting and Data System (PI-RADS) classification for the assessment of PCa aggressiveness. Fifty PCa patients (mean age 60 years old) who underwent MRI at 3.0T followed by prostatectomy were included in this Institutional Review Board-approved retrospective study. DCE-MRI parameters (K trans , v e , k ep [TM&SSM] and intracellular water molecule lifetime τ i [SSM]) were determined in PCa and PZ. Differences in DCE-MRI parameters between PCa and PZ, and between models were assessed using Wilcoxon signed-rank tests. Receiver operating characteristic (ROC) analysis for differentiation between PCa and PZ was performed for individual and combined DCE-MRI parameters. Diagnostic performance of DCE-MRI parameters for identification of aggressive PCa (Gleason ≥8, grade group [GG] ≥3 or pathology stage pT3) was assessed using ROC analysis and compared with PI-RADSv2 scores. DCE-MRI parameters were significantly different between TM and SSM and between PZ and PCa (P < 0.037). Diagnostic performances of TM and SSM for differentiation of PCa from PZ were similar (highest AUC TM: K trans +k ep 0.76, SSM: τ i +k ep 0.80). PI-RADS outperformed TM and SSM DCE-MRI for identification of Gleason ≥8 lesions (AUC PI-RADS: 0.91, highest AUC DCE-MRI: K trans +τ i SSM 0.61, P = 0.002). The diagnostic performance of PI-RADS and DCE-MRI for identification of GG ≥3 and pT3 PCa was not significantly different (P > 0.213). SSM DCE-MRI did not increase the diagnostic performance of DCE-MRI for PCa characterization. PI-RADS outperformed both TM and SSM DCE-MRI for identification of aggressive cancer. 3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:837-849. © 2017 International Society for Magnetic Resonance in Medicine.

Prospect theory does not describe the feedback-related negativity value function.

PubMed

Sambrook, Thomas D; Roser, Matthew; Goslin, Jeremy

2012-12-01

Humans handle uncertainty poorly. Prospect theory accounts for this with a value function in which possible losses are overweighted compared to possible gains, and the marginal utility of rewards decreases with size. fMRI studies have explored the neural basis of this value function. A separate body of research claims that prediction errors are calculated by midbrain dopamine neurons. We investigated whether the prospect theoretic effects shown in behavioral and fMRI studies were present in midbrain prediction error coding by using the feedback-related negativity, an ERP component believed to reflect midbrain prediction errors. Participants' stated satisfaction with outcomes followed prospect theory but their feedback-related negativity did not, instead showing no effect of marginal utility and greater sensitivity to potential gains than losses. Copyright © 2012 Society for Psychophysiological Research.

Reconstruction of dynamic image series from undersampled MRI data using data-driven model consistency condition (MOCCO).

PubMed

Velikina, Julia V; Samsonov, Alexey A

2015-11-01

To accelerate dynamic MR imaging through development of a novel image reconstruction technique using low-rank temporal signal models preestimated from training data. We introduce the model consistency condition (MOCCO) technique, which utilizes temporal models to regularize reconstruction without constraining the solution to be low-rank, as is performed in related techniques. This is achieved by using a data-driven model to design a transform for compressed sensing-type regularization. The enforcement of general compliance with the model without excessively penalizing deviating signal allows recovery of a full-rank solution. Our method was compared with a standard low-rank approach utilizing model-based dimensionality reduction in phantoms and patient examinations for time-resolved contrast-enhanced angiography (CE-MRA) and cardiac CINE imaging. We studied the sensitivity of all methods to rank reduction and temporal subspace modeling errors. MOCCO demonstrated reduced sensitivity to modeling errors compared with the standard approach. Full-rank MOCCO solutions showed significantly improved preservation of temporal fidelity and aliasing/noise suppression in highly accelerated CE-MRA (acceleration up to 27) and cardiac CINE (acceleration up to 15) data. MOCCO overcomes several important deficiencies of previously proposed methods based on pre-estimated temporal models and allows high quality image restoration from highly undersampled CE-MRA and cardiac CINE data. © 2014 Wiley Periodicals, Inc.

RECONSTRUCTION OF DYNAMIC IMAGE SERIES FROM UNDERSAMPLED MRI DATA USING DATA-DRIVEN MODEL CONSISTENCY CONDITION (MOCCO)

PubMed Central

Velikina, Julia V.; Samsonov, Alexey A.

2014-01-01

Purpose To accelerate dynamic MR imaging through development of a novel image reconstruction technique using low-rank temporal signal models pre-estimated from training data. Theory We introduce the MOdel Consistency COndition (MOCCO) technique that utilizes temporal models to regularize the reconstruction without constraining the solution to be low-rank as performed in related techniques. This is achieved by using a data-driven model to design a transform for compressed sensing-type regularization. The enforcement of general compliance with the model without excessively penalizing deviating signal allows recovery of a full-rank solution. Methods Our method was compared to standard low-rank approach utilizing model-based dimensionality reduction in phantoms and patient examinations for time-resolved contrast-enhanced angiography (CE MRA) and cardiac CINE imaging. We studied sensitivity of all methods to rank-reduction and temporal subspace modeling errors. Results MOCCO demonstrated reduced sensitivity to modeling errors compared to the standard approach. Full-rank MOCCO solutions showed significantly improved preservation of temporal fidelity and aliasing/noise suppression in highly accelerated CE MRA (acceleration up to 27) and cardiac CINE (acceleration up to 15) data. Conclusions MOCCO overcomes several important deficiencies of previously proposed methods based on pre-estimated temporal models and allows high quality image restoration from highly undersampled CE-MRA and cardiac CINE data. PMID:25399724

Recording event-related activity under hostile magnetic resonance environment: Is multimodal EEG/ERP-MRI recording possible?

PubMed

Karakaş, H M; Karakaş, S; Ozkan Ceylan, A; Tali, E T

2009-08-01

Event-related potentials (ERPs) have high temporal resolution, but insufficient spatial resolution; the converse is true for the functional imaging techniques. The purpose of the study was to test the utility of a multimodal EEG/ERP-MRI technique which combines electroencephalography (EEG) and magnetic resonance imaging (MRI) for a simultaneously high temporal and spatial resolution. The sample consisted of 32 healthy young adults of both sexes. Auditory stimuli were delivered according to the active and passive oddball paradigms in the MRI environment (MRI-e) and in the standard conditions of the electrophysiology laboratory environment (Lab-e). Tasks were presented in a fixed order. Participants were exposed to the recording environments in a counterbalanced order. EEG data were preprocessed for MRI-related artifacts. Source localization was made using a current density reconstruction technique. The ERP waveforms for the MRI-e were morphologically similar to those for the Lab-e. The effect of the recording environment, experimental paradigm and electrode location were analyzed using a 2x2x3 analysis of variance for repeated measures. The ERP components in the two environments showed parametric variations and characteristic topographical distributions. The calculated sources were in line with the related literature. The findings indicated effortful cognitive processing in MRI-e. The study provided preliminary data on the feasibility of the multimodal EEG/ERP-MRI technique. It also indicated lines of research that are to be pursued for a decisive testing of this technique and its implementation to clinical practice.

Imaging Electric Properties of Biological Tissues by RF Field Mapping in MRI

PubMed Central

Zhang, Xiaotong; Zhu, Shanan; He, Bin

2010-01-01

The electric properties (EPs) of biological tissue, i.e., the electric conductivity and permittivity, can provide important information in the diagnosis of various diseases. The EPs also play an important role in specific absorption rate (SAR) calculation, a major concern in high-field Magnetic Resonance Imaging (MRI), as well as in non-medical areas such as wireless-telecommunications. The high-field MRI system is accompanied by significant wave propagation effects, and the radio frequency (RF) radiation is dependent on the EPs of biological tissue. Based on the measurement of the active transverse magnetic component of the applied RF field (known as B1-mapping technique), we propose a dual-excitation algorithm, which uses two sets of measured B1 data to noninvasively reconstruct the electric properties of biological tissues. The Finite Element Method (FEM) was utilized in three-dimensional (3D) modeling and B1 field calculation. A series of computer simulations were conducted to evaluate the feasibility and performance of the proposed method on a 3D head model within a transverse electromagnetic (TEM) coil and a birdcage (BC) coil. Using a TEM coil, when noise free, the reconstructed EP distribution of tissues in the brain has relative errors of 12% ∼ 28% and correlated coefficients of greater than 0.91. Compared with other B1-mapping based reconstruction algorithms, our approach provides superior performance without the need for iterative computations. The present simulation results suggest that good reconstruction of electric properties from B1 mapping can be achieved. PMID:20129847

Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data

PubMed Central

Meng, Xing; Jiang, Rongtao; Lin, Dongdong; Bustillo, Juan; Jones, Thomas; Chen, Jiayu; Yu, Qingbao; Du, Yuhui; Zhang, Yu; Jiang, Tianzi; Sui, Jing; Calhoun, Vince D.

2016-01-01

Neuroimaging techniques have greatly enhanced the understanding of neurodiversity (human brain variation across individuals) in both health and disease. The ultimate goal of using brain imaging biomarkers is to perform individualized predictions. Here we proposed a generalized framework that can predict explicit values of the targeted measures by taking advantage of joint information from multiple modalities. This framework also enables whole brain voxel-wise searching by combining multivariate techniques such as ReliefF, clustering, correlation-based feature selection and multiple regression models, which is more flexible and can achieve better prediction performance than alternative atlas-based methods. For 50 healthy controls and 47 schizophrenia patients, three kinds of features derived from resting-state fMRI (fALFF), sMRI (gray matter) and DTI (fractional anisotropy) were extracted and fed into a regression model, achieving high prediction for both cognitive scores (MCCB composite r = 0.7033, MCCB social cognition r = 0.7084) and symptomatic scores (positive and negative syndrome scale [PANSS] positive r = 0.7785, PANSS negative r = 0.7804). Moreover, the brain areas likely responsible for cognitive deficits of schizophrenia, including middle temporal gyrus, dorsolateral prefrontal cortex, striatum, cuneus and cerebellum, were located with different weights, as well as regions predicting PANSS symptoms, including thalamus, striatum and inferior parietal lobule, pinpointing the potential neuromarkers. Finally, compared to a single modality, multimodal combination achieves higher prediction accuracy and enables individualized prediction on multiple clinical measures. There is more work to be done, but the current results highlight the potential utility of multimodal brain imaging biomarkers to eventually inform clinical decision-making. PMID:27177764

Spatio-temporal texture (SpTeT) for distinguishing vulnerable from stable atherosclerotic plaque on dynamic contrast enhancement (DCE) MRI in a rabbit model

PubMed Central

Wan, Tao; Madabhushi, Anant; Phinikaridou, Alkystis; Hamilton, James A.; Hua, Ning; Pham, Tuan; Danagoulian, Jovanna; Kleiman, Ross; Buckler, Andrew J.

2014-01-01

Purpose: To develop a new spatio-temporal texture (SpTeT) based method for distinguishing vulnerable versus stable atherosclerotic plaques on DCE-MRI using a rabbit model of atherothrombosis. Methods: Aortic atherosclerosis was induced in 20 New Zealand White rabbits by cholesterol diet and endothelial denudation. MRI was performed before (pretrigger) and after (posttrigger) inducing plaque disruption with Russell's-viper-venom and histamine. Of the 30 vascular targets (segments) under histology analysis, 16 contained thrombus (vulnerable) and 14 did not (stable). A total of 352 voxel-wise computerized SpTeT features, including 192 Gabor, 36 Kirsch, 12 Sobel, 52 Haralick, and 60 first-order textural features, were extracted on DCE-MRI to capture subtle texture changes in the plaques over the course of contrast uptake. Different combinations of SpTeT feature sets, in which the features were ranked by a minimum-redundancy-maximum-relevance feature selection technique, were evaluated via a random forest classifier. A 500 iterative 2-fold cross validation was performed for discriminating the vulnerable atherosclerotic plaque and stable atherosclerotic plaque on per voxel basis. Four quantitative metrics were utilized to measure the classification results in separating between vulnerable and stable plaques. Results: The quantitative results show that the combination of five classes of SpTeT features can distinguish between vulnerable (disrupted plaques with an overlying thrombus) and stable plaques with the best AUC values of 0.9631 ± 0.0088, accuracy of 89.98% ± 0.57%, sensitivity of 83.71% ± 1.71%, and specificity of 94.55% ± 0.48%. Conclusions: Vulnerable and stable plaque can be distinguished by SpTeT based features. The SpTeT features, following validation on larger datasets, could be established as effective and reliable imaging biomarkers for noninvasively assessing atherosclerotic risk. PMID:24694153

Axillary Lymph Node Evaluation Utilizing Convolutional Neural Networks Using MRI Dataset.

PubMed

Ha, Richard; Chang, Peter; Karcich, Jenika; Mutasa, Simukayi; Fardanesh, Reza; Wynn, Ralph T; Liu, Michael Z; Jambawalikar, Sachin

2018-04-25

The aim of this study is to evaluate the role of convolutional neural network (CNN) in predicting axillary lymph node metastasis, using a breast MRI dataset. An institutional review board (IRB)-approved retrospective review of our database from 1/2013 to 6/2016 identified 275 axillary lymph nodes for this study. Biopsy-proven 133 metastatic axillary lymph nodes and 142 negative control lymph nodes were identified based on benign biopsies (100) and from healthy MRI screening patients (42) with at least 3 years of negative follow-up. For each breast MRI, axillary lymph node was identified on first T1 post contrast dynamic images and underwent 3D segmentation using an open source software platform 3D Slicer. A 32 × 32 patch was then extracted from the center slice of the segmented tumor data. A CNN was designed for lymph node prediction based on each of these cropped images. The CNN consisted of seven convolutional layers and max-pooling layers with 50% dropout applied in the linear layer. In addition, data augmentation and L2 regularization were performed to limit overfitting. Training was implemented using the Adam optimizer, an algorithm for first-order gradient-based optimization of stochastic objective functions, based on adaptive estimates of lower-order moments. Code for this study was written in Python using the TensorFlow module (1.0.0). Experiments and CNN training were done on a Linux workstation with NVIDIA GTX 1070 Pascal GPU. Two class axillary lymph node metastasis prediction models were evaluated. For each lymph node, a final softmax score threshold of 0.5 was used for classification. Based on this, CNN achieved a mean five-fold cross-validation accuracy of 84.3%. It is feasible for current deep CNN architectures to be trained to predict likelihood of axillary lymph node metastasis. Larger dataset will likely improve our prediction model and can potentially be a non-invasive alternative to core needle biopsy and even sentinel lymph node evaluation.

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

Bayesian Inference for Functional Dynamics Exploring in fMRI Data.

PubMed

Guo, Xuan; Liu, Bing; Chen, Le; Chen, Guantao; Pan, Yi; Zhang, Jing

2016-01-01

This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI) data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM), Bayesian Connectivity Change Point Model (BCCPM), and Dynamic Bayesian Variable Partition Model (DBVPM), and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come.

Practice guideline summary: Use of fMRI in the presurgical evaluation of patients with epilepsy

PubMed Central

Szaflarski, Jerzy P.; Gloss, David; Binder, Jeffrey R.; Gaillard, William D.; Golby, Alexandra J.; Holland, Scott K.; Ojemann, Jeffrey; Spencer, David C.; Swanson, Sara J.; French, Jacqueline A.; Theodore, William H.

2017-01-01

Objective: To assess the diagnostic accuracy and prognostic value of functional MRI (fMRI) in determining lateralization and predicting postsurgical language and memory outcomes. Methods: An 11-member panel evaluated and rated available evidence according to the 2004 American Academy of Neurology process. At least 2 panelists reviewed the full text of 172 articles and selected 37 for data extraction. Case reports, reports with <15 cases, meta-analyses, and editorials were excluded. Results and recommendations: The use of fMRI may be considered an option for lateralizing language functions in place of intracarotid amobarbital procedure (IAP) in patients with medial temporal lobe epilepsy (MTLE; Level C), temporal epilepsy in general (Level C), or extratemporal epilepsy (Level C). For patients with temporal neocortical epilepsy or temporal tumors, the evidence is insufficient (Level U). fMRI may be considered to predict postsurgical language deficits after anterior temporal lobe resection (Level C). The use of fMRI may be considered for lateralizing memory functions in place of IAP in patients with MTLE (Level C) but is of unclear utility in other epilepsy types (Level U). fMRI of verbal memory or language encoding should be considered for predicting verbal memory outcome (Level B). fMRI using nonverbal memory encoding may be considered for predicting visuospatial memory outcomes (Level C). Presurgical fMRI could be an adequate alternative to IAP memory testing for predicting verbal memory outcome (Level C). Clinicians should carefully advise patients of the risks and benefits of fMRI vs IAP during discussions concerning choice of specific modality in each case. PMID:28077494

Maturing Thalamocortical Functional Connectivity Across Development

PubMed Central

Fair, Damien A.; Bathula, Deepti; Mills, Kathryn L.; Dias, Taciana G. Costa; Blythe, Michael S.; Zhang, Dongyang; Snyder, Abraham Z.; Raichle, Marcus E.; Stevens, Alexander A.; Nigg, Joel T.; Nagel, Bonnie J.

2010-01-01

Recent years have witnessed a surge of investigations examining functional brain organization using resting-state functional connectivity MRI (rs-fcMRI). To date, this method has been used to examine systems organization in typical and atypical developing populations. While the majority of these investigations have focused on cortical–cortical interactions, cortical–subcortical interactions also mature into adulthood. Innovative work by Zhang et al. (2008) in adults have identified methods that utilize rs-fcMRI and known thalamo-cortical topographic segregation to identify functional boundaries in the thalamus that are remarkably similar to known thalamic nuclear grouping. However, despite thalamic nuclei being well formed early in development, the developmental trajectory of functional thalamo-cortical relations remains unexplored. Thalamic maps generated by rs-fcMRI are based on functional relationships, and should modify with the dynamic thalamo-cortical changes that occur throughout maturation. To examine this possibility, we employed a strategy as previously described by Zhang et al. to a sample of healthy children, adolescents, and adults. We found strengthening functional connectivity of the cortex with dorsal/anterior subdivisions of the thalamus, with greater connectivity observed in adults versus children. Temporal lobe connectivity with ventral/midline/posterior subdivisions of the thalamus weakened with age. Changes in sensory and motor thalamo-cortical interactions were also identified but were limited. These findings are consistent with known anatomical and physiological cortical–subcortical changes over development. The methods and developmental context provided here will be important for understanding how cortical–subcortical interactions relate to models of typically developing behavior and developmental neuropsychiatric disorders. PMID:20514143

Functional network integrity presages cognitive decline in preclinical Alzheimer disease.

PubMed

Buckley, Rachel F; Schultz, Aaron P; Hedden, Trey; Papp, Kathryn V; Hanseeuw, Bernard J; Marshall, Gad; Sepulcre, Jorge; Smith, Emily E; Rentz, Dorene M; Johnson, Keith A; Sperling, Reisa A; Chhatwal, Jasmeer P

2017-07-04

To examine the utility of resting-state functional connectivity MRI (rs-fcMRI) measurements of network integrity as a predictor of future cognitive decline in preclinical Alzheimer disease (AD). A total of 237 clinically normal older adults (aged 63-90 years, Clinical Dementia Rating 0) underwent baseline β-amyloid (Aβ) imaging with Pittsburgh compound B PET and structural and rs-fcMRI. We identified 7 networks for analysis, including 4 cognitive networks (default, salience, dorsal attention, and frontoparietal control) and 3 noncognitive networks (primary visual, extrastriate visual, motor). Using linear and curvilinear mixed models, we used baseline connectivity in these networks to predict longitudinal changes in preclinical Alzheimer cognitive composite (PACC) performance, both alone and interacting with Aβ burden. Median neuropsychological follow-up was 3 years. Baseline connectivity in the default, salience, and control networks predicted longitudinal PACC decline, unlike connectivity in the dorsal attention and all noncognitive networks. Default, salience, and control network connectivity was also synergistic with Aβ burden in predicting decline, with combined higher Aβ and lower connectivity predicting the steepest curvilinear decline in PACC performance. In clinically normal older adults, lower functional connectivity predicted more rapid decline in PACC scores over time, particularly when coupled with increased Aβ burden. Among examined networks, default, salience, and control networks were the strongest predictors of rate of change in PACC scores, with the inflection point of greatest decline beyond the fourth year of follow-up. These results suggest that rs-fcMRI may be a useful predictor of early, AD-related cognitive decline in clinical research settings. © 2017 American Academy of Neurology.

Improved spatial accuracy of functional maps in the rat olfactory bulb using supervised machine learning approach.

PubMed

Murphy, Matthew C; Poplawsky, Alexander J; Vazquez, Alberto L; Chan, Kevin C; Kim, Seong-Gi; Fukuda, Mitsuhiro

2016-08-15

Functional MRI (fMRI) is a popular and important tool for noninvasive mapping of neural activity. As fMRI measures the hemodynamic response, the resulting activation maps do not perfectly reflect the underlying neural activity. The purpose of this work was to design a data-driven model to improve the spatial accuracy of fMRI maps in the rat olfactory bulb. This system is an ideal choice for this investigation since the bulb circuit is well characterized, allowing for an accurate definition of activity patterns in order to train the model. We generated models for both cerebral blood volume weighted (CBVw) and blood oxygen level dependent (BOLD) fMRI data. The results indicate that the spatial accuracy of the activation maps is either significantly improved or at worst not significantly different when using the learned models compared to a conventional general linear model approach, particularly for BOLD images and activity patterns involving deep layers of the bulb. Furthermore, the activation maps computed by CBVw and BOLD data show increased agreement when using the learned models, lending more confidence to their accuracy. The models presented here could have an immediate impact on studies of the olfactory bulb, but perhaps more importantly, demonstrate the potential for similar flexible, data-driven models to improve the quality of activation maps calculated using fMRI data. Copyright © 2016 Elsevier Inc. All rights reserved.

Role of eNOS in water exchange index maintenance-MRI studies

NASA Astrophysics Data System (ADS)

Atochin, D.; Litvak, M.; Huang, S.; Kim, Y. R.; Huang, P.

2017-08-01

Stroke studies employ experimental models of cerebral ischemic and reperfusion injury in rodents. MRI provides valuable supravital data of cerebral blood flow and brain tissue damage. This paper presents MRI applications for cerebral blood flow research in mice lines with impaired nitric oxide production by endothelial nitric oxide synthase. Our data demonstrates that specific modifications of MRI methodology in transgenic mouse models help to evaluate the role of eNOS in the brain-blood barrier function.

Resting-State Functional Connectivity in Autism Spectrum Disorders: A Review

PubMed Central

Hull, Jocelyn V.; Jacokes, Zachary J.; Torgerson, Carinna M.; Irimia, Andrei; Van Horn, John Darrell

2017-01-01

Ongoing debate exists within the resting-state functional MRI (fMRI) literature over how intrinsic connectivity is altered in the autistic brain, with reports of general over-connectivity, under-connectivity, and/or a combination of both. Classifying autism using brain connectivity is complicated by the heterogeneous nature of the condition, allowing for the possibility of widely variable connectivity patterns among individuals with the disorder. Further differences in reported results may be attributable to the age and sex of participants included, designs of the resting-state scan, and to the analysis technique used to evaluate the data. This review systematically examines the resting-state fMRI autism literature to date and compares studies in an attempt to draw overall conclusions that are presently challenging. We also propose future direction for rs-fMRI use to categorize individuals with autism spectrum disorder, serve as a possible diagnostic tool, and best utilize data-sharing initiatives. PMID:28101064

Automated modification and fusion of voxel models to construct body phantoms with heterogeneous breast tissue: Application to MRI simulations.

PubMed

Rispoli, Joseph V; Wright, Steven M; Malloy, Craig R; McDougall, Mary P

2017-01-01

Human voxel models incorporating detailed anatomical features are vital tools for the computational evaluation of electromagnetic (EM) fields within the body. Besides whole-body human voxel models, phantoms representing smaller heterogeneous anatomical features are often employed; for example, localized breast voxel models incorporating fatty and fibroglandular tissues have been developed for a variety of EM applications including mammography simulation and dosimetry, magnetic resonance imaging (MRI), and ultra-wideband microwave imaging. However, considering wavelength effects, electromagnetic modeling of the breast at sub-microwave frequencies necessitates detailed breast phantoms in conjunction with whole-body voxel models. Heterogeneous breast phantoms are sized to fit within radiofrequency coil hardware, modified by voxel-wise extrusion, and fused to whole-body models using voxel-wise, tissue-dependent logical operators. To illustrate the utility of this method, finite-difference time-domain simulations are performed using a whole-body model integrated with a variety of available breast phantoms spanning the standard four tissue density classifications representing the majority of the population. The software library uses a combination of voxel operations to seamlessly size, modify, and fuse eleven breast phantoms to whole-body voxel models. The software is publicly available on GitHub and is linked to the file exchange at MATLAB ® Central. Simulations confirm the proportions of fatty and fibroglandular tissues in breast phantoms have significant yet predictable implications on projected power deposition in tissue. Breast phantoms may be modified and fused to whole-body voxel models using the software presented in this work; user considerations for the open-source software and resultant phantoms are discussed. Furthermore, results indicate simulating breast models as predominantly fatty tissue can considerably underestimate the potential for tissue heating in women with substantial fibroglandular tissue.

Automated modification and fusion of voxel models to construct body phantoms with heterogeneous breast tissue: Application to MRI simulations

PubMed Central

Rispoli, Joseph V.; Wright, Steven M.; Malloy, Craig R.; McDougall, Mary P.

2017-01-01

Background Human voxel models incorporating detailed anatomical features are vital tools for the computational evaluation of electromagnetic (EM) fields within the body. Besides whole-body human voxel models, phantoms representing smaller heterogeneous anatomical features are often employed; for example, localized breast voxel models incorporating fatty and fibroglandular tissues have been developed for a variety of EM applications including mammography simulation and dosimetry, magnetic resonance imaging (MRI), and ultra-wideband microwave imaging. However, considering wavelength effects, electromagnetic modeling of the breast at sub-microwave frequencies necessitates detailed breast phantoms in conjunction with whole-body voxel models. Methods Heterogeneous breast phantoms are sized to fit within radiofrequency coil hardware, modified by voxel-wise extrusion, and fused to whole-body models using voxel-wise, tissue-dependent logical operators. To illustrate the utility of this method, finite-difference time-domain simulations are performed using a whole-body model integrated with a variety of available breast phantoms spanning the standard four tissue density classifications representing the majority of the population. Results The software library uses a combination of voxel operations to seamlessly size, modify, and fuse eleven breast phantoms to whole-body voxel models. The software is publicly available on GitHub and is linked to the file exchange at MATLAB® Central. Simulations confirm the proportions of fatty and fibroglandular tissues in breast phantoms have significant yet predictable implications on projected power deposition in tissue. Conclusions Breast phantoms may be modified and fused to whole-body voxel models using the software presented in this work; user considerations for the open-source software and resultant phantoms are discussed. Furthermore, results indicate simulating breast models as predominantly fatty tissue can considerably underestimate the potential for tissue heating in women with substantial fibroglandular tissue. PMID:28798837

Defining active sacroiliitis on MRI for classification of axial spondyloarthritis: update by the ASAS MRI working group.

PubMed

Lambert, Robert G W; Bakker, Pauline A C; van der Heijde, Désirée; Weber, Ulrich; Rudwaleit, Martin; Hermann, K G; Sieper, Joachim; Baraliakos, Xenofon; Bennett, Alex; Braun, Jürgen; Burgos-Vargas, Rubén; Dougados, Maxime; Pedersen, Susanne Juhl; Jurik, Anne Grethe; Maksymowych, Walter P; Marzo-Ortega, Helena; Østergaard, Mikkel; Poddubnyy, Denis; Reijnierse, Monique; van den Bosch, Filip; van der Horst-Bruinsma, Irene; Landewé, Robert

2016-11-01

To review and update the existing definition of a positive MRI for classification of axial spondyloarthritis (SpA). The Assessment in SpondyloArthritis International Society (ASAS) MRI working group conducted a consensus exercise to review the definition of a positive MRI for inclusion in the ASAS classification criteria of axial SpA. Existing definitions and new data relevant to the MRI diagnosis and classification of sacroiliitis and spondylitis in axial SpA, published since the ASAS definition first appeared in print in 2009, were reviewed and discussed. The precise wording of the existing definition was examined in detail and the data and a draft proposal were presented to and voted on by the ASAS membership. The clear presence of bone marrow oedema on MRI in subchondral bone is still considered to be the defining observation that determines the presence of active sacroiliitis. Structural damage lesions seen on MRI may contribute to a decision by the observer that inflammatory lesions are genuinely due to SpA but are not required to meet the definition. The existing definition was clarified adding guidelines and images to assist in the application of the definition. The definition of a positive MRI for classification of axial SpA should continue to primarily depend on the imaging features of 'active sacroiliitis' until more data are available regarding MRI features of structural damage in the sacroiliac joint and MRI features in the spine and their utility when used for classification purposes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Enhanced control of dorsolateral prefrontal cortex neurophysiology with real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback training and working memory practice.

PubMed

Sherwood, Matthew S; Kane, Jessica H; Weisend, Michael P; Parker, Jason G

2016-01-01

Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback can be used to train localized, conscious regulation of blood oxygen level-dependent (BOLD) signals. As a therapeutic technique, rt-fMRI neurofeedback reduces the symptoms of a variety of neurologic disorders. To date, few studies have investigated the use of self-regulation training using rt-fMRI neurofeedback to enhance cognitive performance. This work investigates the utility of rt-fMRI neurofeedback as a tool to enhance human cognition by training healthy individuals to consciously control activity in the left dorsolateral prefrontal cortex (DLPFC). A cohort of 18 healthy participants in the experimental group underwent rt-fMRI neurofeedback from the left DLPFC in five training sessions across two weeks while 7 participants in the control group underwent similar training outside the MRI and without rt-fMRI neurofeedback. Working memory (WM) performance was evaluated on two testing days separated by the five rt-fMRI neurofeedback sessions using two computerized tests. We investigated the ability to control the BOLD signal across training sessions and WM performance across the two testing days. The group with rt-fMRI neurofeedback demonstrated a significant increase in the ability to self-regulate the BOLD signal in the left DLPFC across sessions. WM performance showed differential improvement between testing days one and two across the groups with the highest increases observed in the rt-fMRI neurofeedback group. These results provide evidence that individuals can quickly gain the ability to consciously control the left DLPFC, and this training results in improvements of WM performance beyond that of training alone. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

PREDICTION OF MALIGNANT BREAST LESIONS FROM MRI FEATURES: A COMPARISON OF ARTIFICIAL NEURAL NETWORK AND LOGISTIC REGRESSION TECHNIQUES

PubMed Central

McLaren, Christine E.; Chen, Wen-Pin; Nie, Ke; Su, Min-Ying

2009-01-01

Rationale and Objectives Dynamic contrast enhanced MRI (DCE-MRI) is a clinical imaging modality for detection and diagnosis of breast lesions. Analytical methods were compared for diagnostic feature selection and performance of lesion classification to differentiate between malignant and benign lesions in patients. Materials and Methods The study included 43 malignant and 28 benign histologically-proven lesions. Eight morphological parameters, ten gray level co-occurrence matrices (GLCM) texture features, and fourteen Laws’ texture features were obtained using automated lesion segmentation and quantitative feature extraction. Artificial neural network (ANN) and logistic regression analysis were compared for selection of the best predictors of malignant lesions among the normalized features. Results Using ANN, the final four selected features were compactness, energy, homogeneity, and Law_LS, with area under the receiver operating characteristic curve (AUC) = 0.82, and accuracy = 0.76. The diagnostic performance of these 4-features computed on the basis of logistic regression yielded AUC = 0.80 (95% CI, 0.688 to 0.905), similar to that of ANN. The analysis also shows that the odds of a malignant lesion decreased by 48% (95% CI, 25% to 92%) for every increase of 1 SD in the Law_LS feature, adjusted for differences in compactness, energy, and homogeneity. Using logistic regression with z-score transformation, a model comprised of compactness, NRL entropy, and gray level sum average was selected, and it had the highest overall accuracy of 0.75 among all models, with AUC = 0.77 (95% CI, 0.660 to 0.880). When logistic modeling of transformations using the Box-Cox method was performed, the most parsimonious model with predictors, compactness and Law_LS, had an AUC of 0.79 (95% CI, 0.672 to 0.898). Conclusion The diagnostic performance of models selected by ANN and logistic regression was similar. The analytic methods were found to be roughly equivalent in terms of predictive ability when a small number of variables were chosen. The robust ANN methodology utilizes a sophisticated non-linear model, while logistic regression analysis provides insightful information to enhance interpretation of the model features. PMID:19409817

Removal of intensity bias in magnitude spin-echo MRI images by nonlinear diffusion filtering

NASA Astrophysics Data System (ADS)

Samsonov, Alexei A.; Johnson, Chris R.

2004-05-01

MRI data analysis is routinely done on the magnitude part of complex images. While both real and imaginary image channels contain Gaussian noise, magnitude MRI data are characterized by Rice distribution. However, conventional filtering methods often assume image noise to be zero mean and Gaussian distributed. Estimation of an underlying image using magnitude data produces biased result. The bias may lead to significant image errors, especially in areas of low signal-to-noise ratio (SNR). The incorporation of the Rice PDF into a noise filtering procedure can significantly complicate the method both algorithmically and computationally. In this paper, we demonstrate that inherent image phase smoothness of spin-echo MRI images could be utilized for separate filtering of real and imaginary complex image channels to achieve unbiased image denoising. The concept is demonstrated with a novel nonlinear diffusion filtering scheme developed for complex image filtering. In our proposed method, the separate diffusion processes are coupled through combined diffusion coefficients determined from the image magnitude. The new method has been validated with simulated and real MRI data. The new method has provided efficient denoising and bias removal in conventional and black-blood angiography MRI images obtained using fast spin echo acquisition protocols.

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

PubMed

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

2006-01-01

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

A decomposition model and voxel selection framework for fMRI analysis to predict neural response of visual stimuli.

PubMed

Raut, Savita V; Yadav, Dinkar M

2018-03-28

This paper presents an fMRI signal analysis methodology using geometric mean curve decomposition (GMCD) and mutual information-based voxel selection framework. Previously, the fMRI signal analysis has been conducted using empirical mean curve decomposition (EMCD) model and voxel selection on raw fMRI signal. The erstwhile methodology loses frequency component, while the latter methodology suffers from signal redundancy. Both challenges are addressed by our methodology in which the frequency component is considered by decomposing the raw fMRI signal using geometric mean rather than arithmetic mean and the voxels are selected from EMCD signal using GMCD components, rather than raw fMRI signal. The proposed methodologies are adopted for predicting the neural response. Experimentations are conducted in the openly available fMRI data of six subjects, and comparisons are made with existing decomposition models and voxel selection frameworks. Subsequently, the effect of degree of selected voxels and the selection constraints are analyzed. The comparative results and the analysis demonstrate the superiority and the reliability of the proposed methodology.

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

Lee, D; Pollock, S; Keall, P

Purpose: Audiovisual biofeedback breath-hold (AVBH) was employed to reproduce tumor position on inhale and exhale breath-holds for 4D tumor information. We hypothesize that lung tumor position will be more consistent using AVBH compared with conventional breath-hold (CBH). Methods: Lung tumor positions were determined for seven lung cancer patients (age: 25 – 74) during to two separate 3T MRI sessions. A breathhold training session was performed prior to the MRI sessions to allow patients to become comfortable with AVBH and their exhale and inhale target positions. CBH and AVBH 4D image datasets were obtained in the first MRI session (pre-treatment) andmore » the second MRI session (midtreatment) within six weeks of the first session. Audio-instruction (MRI: Siemens Skyra) in CBH and verbal-instruction (radiographer) in AVBH were used. A radiation oncologist contoured the lung tumor using Eclipse (Varian Medical Systems); tumor position was quantified as the centroid of the contoured tumor after rigid registration based on vertebral anatomy across two MRI sessions. CBH and AVBH were compared in terms of the reproducibility assessed via (1) the difference between the two exhale positions for the two sessions and the two inhale positions for the sessions. (2) The difference in amplitude (exhale to inhale) between the two sessions. Results: Compared to CBH, AVBH improved the reproducibility of two exhale (or inhale) lung tumor positions relative to each other by 33%, from 6.4±5.3 mm to 4.3±3.0 mm (p=0.005). Compared to CBH, AVBH improved the reproducibility of exhale and inhale amplitude by 66%, from 5.6±5.9 mm to 1.9±1.4 mm (p=0.005). Conclusions: This study demonstrated that audiovisual biofeedback can be utilized for improving the reproducibility of breath-hold lung tumor position. These results are advantageous towards achieving more accurate emerging radiation treatment planning methods, in addition to imaging and treatment modalities utilizing breath-hold procedures.« less

Clinical utility of flumazenil-PET versus [18F]fluorodeoxyglucose-PET and MRI in refractory partial epilepsy. A prospective study in 100 patients.

PubMed

Ryvlin, P; Bouvard, S; Le Bars, D; De Lamérie, G; Grégoire, M C; Kahane, P; Froment, J C; Mauguière, F

1998-11-01

We assessed the clinical utility of [11C]flumazenil-PET (FMZ-PET) prospectively in 100 epileptic patients undergoing a pre-surgical evaluation, and defined the specific contribution of this neuro-imaging technique with respect to those of MRI and [18F]fluorodeoxyglucose-PET (FDG-PET). All patients benefited from a long term video-EEG monitoring, whereas an intracranial EEG investigation was performed in 40 cases. Most of our patients (73%) demonstrated a FMZ-PET abnormality; this hit rate was significantly higher in temporal lobe epilepsy (94%) than in other types of epilepsy (50%) (P < 0.001). Most FMZ-PET findings coexisted with a MRI abnormality (81%), including hippocampal atrophy (35%) and focal hypometabolism on FDG-PET (89%). The area of decreased FMZ binding was often smaller than that of glucose hypometabolism (48%) or larger than that of the MRI abnormality (28%). FMZ-PET did not prove superior to FDG-PET in assessing the extent of the ictal onset zone, as defined by intracranial EEG recordings. However, it provided useful data which were complementary to those of MRI and FDG-PET in three situations: (i) in temporal lobe epilepsy associated with MRI signs of hippocampal sclerosis, FMZ-PET abnormalities delineated the site of seizure onset precisely, whenever they were coextensive with FDG-PET abnormalities; (ii) in bi-temporal epilepsy, FMZ-PET helped to confirm the bilateral origin of seizures by showing a specific pattern of decreased FMZ binding in both temporal lobes in 33% of cases; (iii) in patients with a unilateral cryptogenic frontal lobe epilepsy, FMZ-PET provided further evidence of the side and site of seizure onset in 55% of cases. Thus, FMZ-PET deserves to be included in the pre-surgical evaluation of these specific categories of epileptic patients, representing approximately half of the population considered for epilepsy surgery.

Image-Based Computational Fluid Dynamics in Blood Vessel Models: Toward Developing a Prognostic Tool to Assess Cardiovascular Function Changes in Prolonged Space Flights

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

Evaluation of PET and MR datasets in integrated 18F-FDG PET/MRI: A comparison of different MR sequences for whole-body restaging of breast cancer patients.

PubMed

Grueneisen, Johannes; Sawicki, Lino Morris; Wetter, Axel; Kirchner, Julian; Kinner, Sonja; Aktas, Bahriye; Forsting, Michael; Ruhlmann, Verena; Umutlu, Lale

2017-04-01

To investigate the diagnostic value of different MR sequences and 18F-FDG PET data for whole-body restaging of breast cancer patients utilizing PET/MRI. A total of 36 patients with suspected tumor recurrence of breast cancer based on clinical follow-up or abnormal findings in follow-up examinations (e.g. CT, MRI) were prospectively enrolled in this study. All patients underwent a PET/CT and subsequently an additional PET/MR scan. Two readers were instructed to identify the occurrence of a tumor relapse in subsequent MR and PET/MR readings, utilizing different MR sequence constellations for each session. The diagnostic confidence for the determination of a malignant or benign lesion was qualitatively rated (3-point ordinal scale) for each lesion in the different reading sessions and the lesion conspicuity (4-point ordinal scale) for the three different MR sequences was additionally evaluated. Tumor recurrence was present in 25/36 (69%) patients. All three PET/MRI readings showed a significantly higher accuracy as well as higher confidence levels for the detection of recurrent breast cancer lesions when compared to MRI alone (p<0.05). Furthermore, all three PET/MR sequence constellations showed comparable diagnostic accuracy for the identification of a breast cancer recurrence (p>0.05), yet the highest confidence levels were obtained, when all three MR sequences were used for image interpretation. Moreover, contrast-enhanced T1-weighted VIBE imaging showed significantly higher values for the delineation of malignant and benign lesions when compared to T2w HASTE and diffusion-weighted imaging. Integrated PET/MRI provides superior restaging of breast cancer patients over MRI alone. Facing the need for appropriate and efficient whole-body PET/MR protocols, our results show the feasibility of fast and morphologically adequate PET/MR protocols. However, considering an equivalent accuracy for the detection of breast cancer recurrences in the three PET/MR readings, the application of contrast-agent and the inclusion of DWI in the study protocol seems to be debatable. Copyright © 2017 Elsevier B.V. All rights reserved.

Magnetic resonance imaging correlates of bee sting induced multiple organ dysfunction syndrome: A case report.

PubMed

Das, Sushant K; Zeng, Li-Chuan; Li, Bing; Niu, Xiang-Ke; Wang, Jing-Liang; Bhetuwal, Anup; Yang, Han-Feng

2014-09-28

Occasionally systemic complications with high risk of death, such as multiple organ dysfunction syndrome (MODS), can occur following multiple bee stings. This case study reports a patient who presented with MODS, i.e., acute kidney injury, hepatic and cardiac dysfunction, after multiple bee stings. The standard clinical findings were then correlated with magnetic resonance imaging (MRI) findings, which demonstrates that MRI may be utilized as a simpler tool to use than other multiple diagnostics.

Working memory, reasoning, and expertise in medicine-insights into their relationship using functional neuroimaging.

PubMed

Hruska, Pam; Krigolson, Olav; Coderre, Sylvain; McLaughlin, Kevin; Cortese, Filomeno; Doig, Christopher; Beran, Tanya; Wright, Bruce; Hecker, Kent G

2016-12-01

Clinical reasoning is dependent upon working memory (WM). More precisely, during the clinical reasoning process stored information within long-term memory is brought into WM to facilitate the internal deliberation that affords a clinician the ability to reason through a case. In the present study, we examined the relationship between clinical reasoning and WM while participants read clinical cases with functional magnetic resonance imaging (fMRI). More specifically, we examined the impact of clinical case difficulty (easy, hard) and clinician level of expertise (2nd year medical students, senior gastroenterologists) on neural activity within regions of cortex associated with WM (i.e., the prefrontal cortex) during the reasoning process. fMRI was used to scan ten second-year medical students and ten practicing gastroenterologists while they reasoned through sixteen clinical cases [eight straight forward (easy) and eight complex (hard)] during a single 1-h scanning session. Within-group analyses contrasted the easy and hard cases which were then subsequently utilized for a between-group analysis to examine effects of expertise (novice > expert, expert > novice). Reading clinical cases evoked multiple neural activations in occipital, prefrontal, parietal, and temporal cortical regions in both groups. Importantly, increased activation in the prefrontal cortex in novices for both easy and hard clinical cases suggests novices utilize WM more so than experts during clinical reasoning. We found that clinician level of expertise elicited differential activation of regions of the human prefrontal cortex associated with WM during clinical reasoning. This suggests there is an important relationship between clinical reasoning and human WM. As such, we suggest future models of clinical reasoning take into account that the use of WM is not consistent throughout all clinical reasoning tasks, and that memory structure may be utilized differently based on level of expertise.

Using fMRI to study reward processing in humans: past, present, and future

PubMed Central

Wang, Kainan S.; Smith, David V.

2016-01-01

Functional magnetic resonance imaging (fMRI) is a noninvasive tool used to probe cognitive and affective processes. Although fMRI provides indirect measures of neural activity, the advent of fMRI has allowed for 1) the corroboration of significant animal findings in the human brain, and 2) the expansion of models to include more common human attributes that inform behavior. In this review, we briefly consider the neural basis of the blood oxygenation level dependent signal to set up a discussion of how fMRI studies have applied it in examining cognitive models in humans and the promise of using fMRI to advance such models. Specifically, we illustrate the contribution that fMRI has made to the study of reward processing, focusing on the role of the striatum in encoding reward-related learning signals that drive anticipatory and consummatory behaviors. For instance, we discuss how fMRI can be used to link neural signals (e.g., striatal responses to rewards) to individual differences in behavior and traits. While this functional segregation approach has been constructive to our understanding of reward-related functions, many fMRI studies have also benefitted from a functional integration approach that takes into account how interconnected regions (e.g., corticostriatal circuits) contribute to reward processing. We contend that future work using fMRI will profit from using a multimodal approach, such as combining fMRI with noninvasive brain stimulation tools (e.g., transcranial electrical stimulation), that can identify causal mechanisms underlying reward processing. Consequently, advancements in implementing fMRI will promise new translational opportunities to inform our understanding of psychopathologies. PMID:26740530

Methods and utility of EEG-fMRI in epilepsy

PubMed Central

Lemieux, Louis; Chaudhary, Umair Javaid

2015-01-01

Brain activity data in general and more specifically in epilepsy can be represented as a matrix that includes measures of electrophysiology, anatomy and behaviour. Each of these sub-matrices has a complex interaction depending upon the brain state i.e., rest, cognition, seizures and interictal periods. This interaction presents significant challenges for interpretation but also potential for developing further insights into individual event types. Successful treatments in epilepsy hinge on unravelling these complexities, and also on the sensitivity and specificity of methods that characterize the nature and localization of underlying physiological and pathological networks. Limitations of pharmacological and surgical treatments call for refinement and elaboration of methods to improve our capability to localise the generators of seizure activity and our understanding of the neurobiology of epilepsy. Simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI), by potentially circumventing some of the limitations of EEG in terms of sensitivity, can allow the mapping of haemodynamic networks over the entire brain related to specific spontaneous and triggered epileptic events in humans, and thereby provide new localising information. In this work we review the published literature, and discuss the methods and utility of EEG-fMRI in localising the generators of epileptic activity. We draw on our experience and that of other groups, to summarise the spectrum of information provided by an increasing number of EEG-fMRI case-series, case studies and group studies in patients with epilepsy, for its potential role to elucidate epileptic generators and networks. We conclude that EEG-fMRI provides a multidimensional view that contributes valuable clinical information to localize the epileptic focus with potential important implications for the surgical treatment of some patients with drug-resistant epilepsy, and insights into the resting state and cognitive network dynamics. PMID:25853087

Pharmacological MRI in animal models: a useful tool for 5-HT research?

PubMed

Martin, Chris; Sibson, Nicola R

2008-11-01

Pharmacological magnetic resonance imaging (phMRI) offers the potential to provide novel insights into the functioning of neurotransmitter systems and drug action in the central nervous system. To date, much of the neuropharmacological research that has applied phMRI techniques has focused on the dopaminergic system with relatively few studies into serotonergic function. In this article, we discuss the current capabilities of, and future potential for phMRI to address fundamental questions in serotonergic research using animal models. Firstly we review existing literature on the application of phMRI to the serotonergic system by exploring 3 broad research themes: (i) the functional anatomy of the serotonergic system; (ii) drug-receptor targeting and distribution; and (iii) disease models and drug development. Subsequently, we discuss the interpretation of phMRI data in terms of neuropharmacological action with a focus on issues specific to neuroimaging studies of the serotonergic system. Unlike other neuroimaging approaches such as positron emission tomography, phMRI methods do not currently offer sensitivity to markers of specific pharmacological action. However, they can provide in vivo markers of the neuropharmacological modulation of neuronal activity across the whole brain with unparalleled spatial and temporal resolution. Furthermore, due to the non-invasive nature of MRI, these markers are readily translatable to human studies. Whilst there are a number of constraints and limitations to phMRI methods that necessitate careful data interpretation, we argue that phMRI could become a valuable research tool in neuropharmacological studies of the serotonergic system.

Multiparametric Magnetic Resonance Imaging for Active Surveillance of Prostate Cancer.

PubMed

An, Julie Y; Sidana, Abhinav; Choyke, Peter L; Wood, Bradford J.; Pinto, Peter A; Türkbey, İsmail Barış

2017-09-29

Active surveillance has gained popularity as an acceptable management option for men with low-risk prostate cancer. Successful utilization of this strategy can delay or prevent unnecessary interventions - thereby reducing morbidity associated with overtreatment. The usefulness of active surveillance primarily depends on correct identification of patients with low-risk disease. However, current population-wide algorithms and tools do not adequately exclude high-risk disease, thereby limiting the confidence of clinicians and patients to go on active surveillance. Novel imaging tools such as mpMRI provide information about the size and location of potential cancers enabling more informed treatment decisions. The term "multiparametric" in prostate mpMRI refers to the summation of several MRI series into one examination whose initial goal is to identify potential clinically-significant lesions suitable for targeted biopsy. The main advantages of MRI are its superior anatomic resolution and the lack of ionizing radiation. Recently, the Prostate Imaging-Reporting and Data System has been instituted as an international standard for unifying mpMRI results. The imaging sequences in mpMRI defined by Prostate Imaging Reporting and Data System version 2 includes: T2-weighted MRI, diffusion-weighted MRI, derived apparent-diffusion coefficient from diffusion-weighted MRI, and dynamic contrast-enhanced MRI. The use of mpMRI prior to starting active surveillance could prevent those with missed, high-grade lesions from going on active surveillance, and reassure those with minimal disease who may be hesitant to take part in active surveillance. Although larger validation studies are still necessary, preliminary results suggest mpMRI has a role in selecting patients for active surveillance. Less certain is the role of mpMRI in monitoring patients on active surveillance, as data on this will take a long time to mature. The biggest obstacles to routine use of prostate MRI are quality control, cost, reproducibility, and access. Nevertheless, there is great a potential for mpMRI to improve outcomes and quality of treatment. The major roles of MRI will continue to expand and its emerging use in standard of care approaches becomes more clearly defined and supported by increasing levels of data.

NAPR: a Cloud-Based Framework for Neuroanatomical Age Prediction.

PubMed

Pardoe, Heath R; Kuzniecky, Ruben

2018-01-01

The availability of cloud computing services has enabled the widespread adoption of the "software as a service" (SaaS) approach for software distribution, which utilizes network-based access to applications running on centralized servers. In this paper we apply the SaaS approach to neuroimaging-based age prediction. Our system, named "NAPR" (Neuroanatomical Age Prediction using R), provides access to predictive modeling software running on a persistent cloud-based Amazon Web Services (AWS) compute instance. The NAPR framework allows external users to estimate the age of individual subjects using cortical thickness maps derived from their own locally processed T1-weighted whole brain MRI scans. As a demonstration of the NAPR approach, we have developed two age prediction models that were trained using healthy control data from the ABIDE, CoRR, DLBS and NKI Rockland neuroimaging datasets (total N = 2367, age range 6-89 years). The provided age prediction models were trained using (i) relevance vector machines and (ii) Gaussian processes machine learning methods applied to cortical thickness surfaces obtained using Freesurfer v5.3. We believe that this transparent approach to out-of-sample evaluation and comparison of neuroimaging age prediction models will facilitate the development of improved age prediction models and allow for robust evaluation of the clinical utility of these methods.

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.

Patterns of Breast Magnetic Resonance Imaging Use in Community Practice

PubMed Central

Wernli, Karen J.; DeMartini, Wendy B.; Ichikawa, Laura; Lehman, Constance D.; Onega, Tracy; Kerlikowske, Karla; Henderson, Louise M.; Geller, Berta M.; Hofmann, Mike; Yankaskas, Bonnie C.

2014-01-01

Importance Breast magnetic resonance imaging (MRI) is increasingly used for breast cancer screening, diagnostic evaluation, and surveillance However, we lack data on national patterns of breast MRI use in community practice. Objective To describe 2005–2009 patterns of breast magnetic resonance imaging (MRI) use in U.S. community practice. Design Observational cohort study Setting Data collected from 2005–2009 on breast MRI and mammography from five national Breast Cancer Surveillance Consortium registries. Participants Data included 8931 breast MRI examinations and 1,288,924 screening mammograms from women aged 18–79 years. Main measures We calculated the rate of breast MRI examinations per 1000 women with breast imaging within the same year and described the clinical indications for the breast MRI examinations by year and age. We compared women screened with breast MRI to women screened with mammography alone for patient characteristics and lifetime breast cancer risk. Results The overall rate of breast MRI from 2005 through 2009 nearly tripled from 4.2 to 11.5 examinations per 1000 women with the most rapid rise from 2005–2007 (p=0.02). The most common clinical indication was diagnostic evaluation (40.3%), followed by screening (31.7%). Compared to women who received screening mammography alone, women who underwent screening breast MRI were more likely to be <50 years, white non-Hispanic, nulliparous, and have extremely dense breast tissue, a family history of breast cancer, and a personal history of breast cancer. The proportion of women screened by breast MRI at high lifetime risk for breast cancer (>20%) increased during the study period from 9% in 2005 to 29% in 2009. Conclusions and relevance Use of breast MRI for screening in high-risk women is increasing. However, our findings suggest there is a need to improve appropriate utilization, including among women who may benefit from screening breast MRI. PMID:24247555

Potential pitfalls when denoising resting state fMRI data using nuisance regression.

PubMed

Bright, Molly G; Tench, Christopher R; Murphy, Kevin

2017-07-01

In resting state fMRI, it is necessary to remove signal variance associated with noise sources, leaving cleaned fMRI time-series that more accurately reflect the underlying intrinsic brain fluctuations of interest. This is commonly achieved through nuisance regression, in which the fit is calculated of a noise model of head motion and physiological processes to the fMRI data in a General Linear Model, and the "cleaned" residuals of this fit are used in further analysis. We examine the statistical assumptions and requirements of the General Linear Model, and whether these are met during nuisance regression of resting state fMRI data. Using toy examples and real data we show how pre-whitening, temporal filtering and temporal shifting of regressors impact model fit. Based on our own observations, existing literature, and statistical theory, we make the following recommendations when employing nuisance regression: pre-whitening should be applied to achieve valid statistical inference of the noise model fit parameters; temporal filtering should be incorporated into the noise model to best account for changes in degrees of freedom; temporal shifting of regressors, although merited, should be achieved via optimisation and validation of a single temporal shift. We encourage all readers to make simple, practical changes to their fMRI denoising pipeline, and to regularly assess the appropriateness of the noise model used. By negotiating the potential pitfalls described in this paper, and by clearly reporting the details of nuisance regression in future manuscripts, we hope that the field will achieve more accurate and precise noise models for cleaning the resting state fMRI time-series. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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.

Classification of clinical significance of MRI prostate findings using 3D convolutional neural networks

NASA Astrophysics Data System (ADS)

Mehrtash, Alireza; Sedghi, Alireza; Ghafoorian, Mohsen; Taghipour, Mehdi; Tempany, Clare M.; Wells, William M.; Kapur, Tina; Mousavi, Parvin; Abolmaesumi, Purang; Fedorov, Andriy

2017-03-01

Prostate cancer (PCa) remains a leading cause of cancer mortality among American men. Multi-parametric magnetic resonance imaging (mpMRI) is widely used to assist with detection of PCa and characterization of its aggressiveness. Computer-aided diagnosis (CADx) of PCa in MRI can be used as clinical decision support system to aid radiologists in interpretation and reporting of mpMRI. We report on the development of a convolution neural network (CNN) model to support CADx in PCa based on the appearance of prostate tissue in mpMRI, conducted as part of the SPIE-AAPM-NCI PROSTATEx challenge. The performance of different combinations of mpMRI inputs to CNN was assessed and the best result was achieved using DWI and DCE-MRI modalities together with the zonal information of the finding. On the test set, the model achieved an area under the receiver operating characteristic curve of 0.80.

High resolution, MRI-based, segmented, computerized head phantom

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

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

1999-01-01

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

Unobtrusive integration of data management with fMRI analysis.

PubMed

Poliakov, Andrew V; Hertzenberg, Xenia; Moore, Eider B; Corina, David P; Ojemann, George A; Brinkley, James F

2007-01-01

This note describes a software utility, called X-batch which addresses two pressing issues typically faced by functional magnetic resonance imaging (fMRI) neuroimaging laboratories (1) analysis automation and (2) data management. The first issue is addressed by providing a simple batch mode processing tool for the popular SPM software package (http://www.fil.ion. ucl.ac.uk/spm/; Welcome Department of Imaging Neuroscience, London, UK). The second is addressed by transparently recording metadata describing all aspects of the batch job (e.g., subject demographics, analysis parameters, locations and names of created files, date and time of analysis, and so on). These metadata are recorded as instances of an extended version of the Protégé-based Experiment Lab Book ontology created by the Dartmouth fMRI Data Center. The resulting instantiated ontology provides a detailed record of all fMRI analyses performed, and as such can be part of larger systems for neuroimaging data management, sharing, and visualization. The X-batch system is in use in our own fMRI research, and is available for download at http://X-batch.sourceforge.net/.

Gas Phase UTE MRI of Propane and Propene

PubMed Central

Kovtunov, Kirill V.; Romanov, Alexey S.; Salnikov, Oleg G.; Barskiy, Danila A.; Chekmenev, Eduard Y.; Koptyug, Igor V.

2016-01-01

1H MRI of gases can potentially enable functional lung imaging to probe gas ventilation and other functions. In this work, 1H MR images of hyperpolarized and thermally polarized propane gas were obtained using UTE (ultrashort echo time) pulse sequence. A 2D image of thermally polarized propane gas with ~0.9×0.9 mm2 spatial resolution was obtained in less than 2 seconds, demonstrating that even non-hyperpolarized hydrocarbon gases can be successfully utilized for conventional proton MRI. The experiments were also performed with hyperpolarized propane gas and demonstrated acquisition of high-resolution multi-slice FLASH 2D images in ca. 510 s and non slice-selective 2D UTE MRI images in ca. 2 s. The UTE approach adopted in this study can be potentially used for medical lung imaging. Furthermore, the possibility to combine UTE with selective suppression of 1H signals from one of the two gases in a mixture is demonstrated in this MRI study. The latter can be useful for visualizing industrially important processes where several gases may be present, e.g., gas-solid catalytic reactions. PMID:27478870

Imaging of Groin Pain: Magnetic Resonance and Ultrasound Imaging Features

PubMed Central

Lee, Susan C.; Endo, Yoshimi; Potter, Hollis G.

2017-01-01

Context: Evaluation of groin pain in athletes may be challenging as pain is typically poorly localized and the pubic symphyseal region comprises closely approximated tendons and muscles. As such, magnetic resonance imaging (MRI) and ultrasound (US) may help determine the etiology of groin pain. Evidence Acquisition: A PubMed search was performed using the following search terms: ultrasound, magnetic resonance imaging, sports hernia, athletic pubalgia, and groin pain. Date restrictions were not placed on the literature search. Study Design: Clinical review. Level of Evidence: Level 4. Results: MRI is sensitive in diagnosing pathology in groin pain. Not only can MRI be used to image rectus abdominis/adductor longus aponeurosis and pubic bone pathology, but it can also evaluate other pathology within the hip and pelvis. MRI is especially helpful when groin pain is poorly localized. Real-time capability makes ultrasound useful in evaluating the pubic symphyseal region, as it can be used for evaluation and treatment. Conclusion: MRI and US are valuable in diagnosing pathology in athletes with groin pain, with the added utility of treatment using US-guided intervention. Strength-of Recommendation Taxonomy: C PMID:28850315

Towards Single Biomolecule Imaging via Optical Nanoscale Magnetic Resonance Imaging.

PubMed

Boretti, Alberto; Rosa, Lorenzo; Castelletto, Stefania

2015-09-09

Nuclear magnetic resonance (NMR) spectroscopy is a physical marvel in which electromagnetic radiation is charged and discharged by nuclei in a magnetic field. In conventional NMR, the specific nuclei resonance frequency depends on the strength of the magnetic field and the magnetic properties of the isotope of the atoms. NMR is routinely utilized in clinical tests by converting nuclear spectroscopy in magnetic resonance imaging (MRI) and providing 3D, noninvasive biological imaging. While this technique has revolutionized biomedical science, measuring the magnetic resonance spectrum of single biomolecules is still an intangible aspiration, due to MRI resolution being limited to tens of micrometers. MRI and NMR have, however, recently greatly advanced, with many breakthroughs in nano-NMR and nano-MRI spurred by using spin sensors based on an atomic impurities in diamond. These techniques rely on magnetic dipole-dipole interactions rather than inductive detection. Here, novel nano-MRI methods based on nitrogen vacancy centers in diamond are highlighted, that provide a solution to the imaging of single biomolecules with nanoscale resolution in-vivo and in ambient conditions. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Parallel group independent component analysis for massive fMRI data sets.

PubMed

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

2017-01-01

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

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.

An MRI-compatible hand sensory vibrotactile system.

PubMed

Wang, Fa; Lakshminarayanan, Kishor; Slota, Gregory P; Seo, Na Jin; Webster, John G

2015-01-01

Recently, the application of vibrotactile noise to the wrist or back of the hand has been shown to enhance fingertip tactile sensory perception (Enders et al 2013), supporting the potential for an assistive device worn at the wrist, that generates minute vibrations to help the elderly or patients with sensory deficit. However, knowledge regarding the detailed physiological mechanism behind this sensory improvement in the central nervous system, especially in the human brain, is limited, hindering progress in development and use of such assistive devices. To enable investigation of the impact of vibrotactile noise on sensorimotor brain activity in humans, a magnetic resonance imaging (MRI)-compatible vibrotactile system was developed to provide vibrotactile noise during an MRI of the brain. The vibrotactile system utilizes a remote (outside the MR room) signal amplifier which provides a voltage from -40 to +40 V to drive a 12 mm diameter piezoelectric vibrator (inside the MR room). It is portable and is found to be MRI-compatible which enables its use for neurologic investigation with MRI. The system was also found to induce an improvement in fingertip tactile sensation, consistent with the previous study.

Imaging of Groin Pain: Magnetic Resonance and Ultrasound Imaging Features.

PubMed

Lee, Susan C; Endo, Yoshimi; Potter, Hollis G

Evaluation of groin pain in athletes may be challenging as pain is typically poorly localized and the pubic symphyseal region comprises closely approximated tendons and muscles. As such, magnetic resonance imaging (MRI) and ultrasound (US) may help determine the etiology of groin pain. A PubMed search was performed using the following search terms: ultrasound, magnetic resonance imaging, sports hernia, athletic pubalgia, and groin pain. Date restrictions were not placed on the literature search. Clinical review. Level 4. MRI is sensitive in diagnosing pathology in groin pain. Not only can MRI be used to image rectus abdominis/adductor longus aponeurosis and pubic bone pathology, but it can also evaluate other pathology within the hip and pelvis. MRI is especially helpful when groin pain is poorly localized. Real-time capability makes ultrasound useful in evaluating the pubic symphyseal region, as it can be used for evaluation and treatment. MRI and US are valuable in diagnosing pathology in athletes with groin pain, with the added utility of treatment using US-guided intervention. Strength-of Recommendation Taxonomy: C.

A simple anaesthetic and monitoring system for magnetic resonance imaging.

PubMed

Rejger, V S; Cohn, B F; Vielvoye, G J; de Raadt, F B

1989-09-01

Clinical magnetic resonance imaging (MRI) is a digital tomographic technique which utilizes radio waves emitted by hydrogen protons in a powerful magnetic field to form an image of soft-tissue structures and abnormalities within the body. Unfortunately, because of the relatively long scanning time required and the narrow deep confines of the MRI tunnel and Faraday cage, some patients cannot be examined without the use of heavy sedation or general anaesthesia. Due to poor access to the patient and the strong magnetic field, several problems arise in monitoring and administering anaesthesia during this procedure. In this presentation these problems and their solutions, as resolved by our institution, are discussed. Of particular interest is the anaesthesia circuit specifically adapted for use during MRI scanning.

Augmented reality for breast imaging.

PubMed

Rancati, Alberto; Angrigiani, Claudio; Nava, Maurizio B; Catanuto, Giuseppe; Rocco, Nicola; Ventrice, Fernando; Dorr, Julio

2018-06-01

Augmented reality (AR) enables the superimposition of virtual reality reconstructions onto clinical images of a real patient, in real time. This allows visualization of internal structures through overlying tissues, thereby providing a virtual transparency vision of surgical anatomy. AR has been applied to neurosurgery, which utilizes a relatively fixed space, frames, and bony references; the application of AR facilitates the relationship between virtual and real data. Augmented breast imaging (ABI) is described. Breast MRI studies for breast implant patients with seroma were performed using a Siemens 3T system with a body coil and a four-channel bilateral phased-array breast coil as the transmitter and receiver, respectively. Gadolinium was injected as a contrast agent (0.1 mmol/kg at 2 mL/s) using a programmable power injector. Dicom formatted images data from 10 MRI cases of breast implant seroma and 10 MRI cases with T1-2 N0 M0 breast cancer, were imported and transformed into augmented reality images. ABI demonstrated stereoscopic depth perception, focal point convergence, 3D cursor use, and joystick fly-through. ABI can improve clinical outcomes, providing an enhanced view of the structures to work on. It should be further studied to determine its utility in clinical practice.

Nonvisualization of the ovaries on pelvic ultrasound: does MRI add anything?

PubMed

Lisanti, Christopher J; Wood, Jonathan R; Schwope, Ryan B

2014-02-01

The purpose of our study is to assess the utility of pelvic magnetic resonance imaging (MRI) in the event that either one or both ovaries are not visualized by pelvic ultrasound. This HIPAA-compliant retrospective study was approved by our local institutional review board and informed consent waived. 1926 pelvic MRI examinations between March 2007 and December 2011 were reviewed and included if a combined transabdominal and endovaginal pelvic ultrasound had been performed in the preceding 6 months with at least one ovary nonvisualized. Ovaries not visualized on pelvic ultrasound were assumed to be normal and compared with the pelvic MRI findings. MRI findings were categorized as concordant or discordant. Discordant findings were divided into malignant, non-malignant physiologic or non-malignant non-physiologic. The modified Wald, the "rule of thirds", and the binomial distribution probability tests were performed. 255 pelvic ultrasounds met inclusion criteria with 364 ovaries not visualized. 0 malignancies were detected on MRI. 6.9% (25/364) of nonvisualized ovaries had non-malignant discordant findings on MRI: 5.2% (19/364) physiologic, 1.6% (6/364) non-physiologic. Physiologic findings included: 16 functional cysts and 3 hemorrhagic cysts. Non-physiologic findings included: 3 cysts in post-menopausal women, 1 hydrosalpinx, and 2 broad ligament fibroids. The theoretical risk of detecting an ovarian carcinoma on pelvic MRI when an ovary is not visualized on ultrasound ranges from 0 to 1.3%. If an ovary is not visualized on pelvic ultrasound, it can be assumed to be without carcinoma and MRI rarely adds additional information.

Planning magnetic resonance imaging for prostate cancer intensity-modulated radiation therapy: Impact on target volumes, radiotherapy dose and androgen deprivation administration.

PubMed

Horsley, Patrick J; Aherne, Noel J; Edwards, Grace V; Benjamin, Linus C; Wilcox, Shea W; McLachlan, Craig S; Assareh, Hassan; Welshman, Richard; McKay, Michael J; Shakespeare, Thomas P

2015-03-01

Magnetic resonance imaging (MRI) scans are increasingly utilized for radiotherapy planning to contour the primary tumors of patients undergoing intensity-modulated radiation therapy (IMRT). These scans may also demonstrate cancer extent and may affect the treatment plan. We assessed the impact of planning MRI detection of extracapsular extension, seminal vesicle invasion, or adjacent organ invasion on the staging, target volume delineation, doses, and hormonal therapy of patients with prostate cancer undergoing IMRT. The records of 509 consecutive patients with planning MRI scans being treated with IMRT for prostate cancer between January 2010 and July 2012 were retrospectively reviewed. Tumor staging and treatment plans before and after MRI were compared. Of the 509 patients, 103 (20%) were upstaged and 44 (9%) were migrated to a higher risk category as a result of findings at MRI. In 94 of 509 patients (18%), the MRI findings altered management. Ninety-four of 509 patients (18%) had a change to their clinical target volume (CTV) or treatment technique, and in 41 of 509 patients (8%) the duration of hormone therapy was changed because of MRI findings. The use of radiotherapy planning MRI altered CTV design, dose and/or duration of androgen deprivation in 18% of patients in this large, single institution series of men planned for dose-escalated prostate IMRT. This has substantial implications for radiotherapy target volumes and doses, as well as duration of androgen deprivation. Further research is required to investigate whether newer MRI techniques can simultaneously fulfill staging and radiotherapy contouring roles. © 2014 Wiley Publishing Asia Pty Ltd.

T2-weighted MRI-derived textural features reflect prostate cancer aggressiveness: preliminary results.

PubMed

Nketiah, Gabriel; Elschot, Mattijs; Kim, Eugene; Teruel, Jose R; Scheenen, Tom W; Bathen, Tone F; Selnæs, Kirsten M

2017-07-01

To evaluate the diagnostic relevance of T2-weighted (T2W) MRI-derived textural features relative to quantitative physiological parameters derived from diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI in Gleason score (GS) 3+4 and 4+3 prostate cancers. 3T multiparametric-MRI was performed on 23 prostate cancer patients prior to prostatectomy. Textural features [angular second moment (ASM), contrast, correlation, entropy], apparent diffusion coefficient (ADC), and DCE pharmacokinetic parameters (K trans and V e ) were calculated from index tumours delineated on the T2W, DW, and DCE images, respectively. The association between the textural features and prostatectomy GS and the MRI-derived parameters, and the utility of the parameters in differentiating between GS 3+4 and 4+3 prostate cancers were assessed statistically. ASM and entropy correlated significantly (p < 0.05) with both GS and median ADC. Contrast correlated moderately with median ADC. The textural features correlated insignificantly with K trans and V e . GS 4+3 cancers had significantly lower ASM and higher entropy than 3+4 cancers, but insignificant differences in median ADC, K trans , and V e . The combined texture-MRI parameters yielded higher classification accuracy (91%) than the individual parameter sets. T2W MRI-derived textural features could serve as potential diagnostic markers, sensitive to the pathological differences in prostate cancers. • T2W MRI-derived textural features correlate significantly with Gleason score and ADC. • T2W MRI-derived textural features differentiate Gleason score 3+4 from 4+3 cancers. • T2W image textural features could augment tumour characterization.

Passive fMRI mapping of language function for pediatric epilepsy surgical planning: validation using Wada, ECS, and FMAER.

PubMed

Suarez, Ralph O; Taimouri, Vahid; Boyer, Katrina; Vega, Clemente; Rotenberg, Alexander; Madsen, Joseph R; Loddenkemper, Tobias; Duffy, Frank H; Prabhu, Sanjay P; Warfield, Simon K

2014-12-01

In this study we validate passive language fMRI protocols designed for clinical application in pediatric epilepsy surgical planning as they do not require overt participation from patients. We introduced a set of quality checks that assess reliability of noninvasive fMRI mappings utilized for clinical purposes. We initially compared two fMRI language mapping paradigms, one active in nature (requiring participation from the patient) and the other passive in nature (requiring no participation from the patient). Group-level analysis in a healthy control cohort demonstrated similar activation of the putative language centers of the brain in the inferior frontal (IFG) and temporoparietal (TPG) regions. Additionally, we showed that passive language fMRI produced more left-lateralized activation in TPG (LI=+0.45) compared to the active task; with similarly robust left-lateralized IFG (LI=+0.24) activations using the passive task. We validated our recommended fMRI mapping protocols in a cohort of 15 pediatric epilepsy patients by direct comparison against the invasive clinical gold-standards. We found that language-specific TPG activation by fMRI agreed to within 9.2mm to subdural localizations by invasive functional mapping in the same patients, and language dominance by fMRI agreed with Wada test results at 80% congruency in TPG and 73% congruency in IFG. Lastly, we tested the recommended passive language fMRI protocols in a cohort of very young patients and confirmed reliable language-specific activation patterns in that challenging cohort. We concluded that language activation maps can be reliably achieved using the passive language fMRI protocols we proposed even in very young (average 7.5 years old) or sedated pediatric epilepsy patients. Copyright © 2014 Elsevier B.V. All rights reserved.

Magnetic resonance imaging in evaluating workers' compensation patients.

PubMed

Babbel, Daniel; Rayan, Ghazi

2012-04-01

We studied the utility of magnetic resonance imaging (MRI) studies for workers' compensation patients with hand conditions in which the referring doctor obtained the images. We compared the MRI findings with the eventual clinical findings. We also investigated the approximate cost of these MRI studies. We retrospectively reviewed the charts of all workers' compensation patients seen in a hand and upper extremity practice over the course of 3 years. We selected patients who had MRI studies of the affected upper extremities before referral to the senior author (G.R.). We reviewed the charts for information regarding demographics, referral diagnoses, MRI diagnoses made by the radiologist, the area of the upper extremity studied, and eventual clinical diagnoses by the senior author. We made a determination as to whether a hand surgeon could have adequately diagnosed and treated the patients' conditions without the imaging studies. We also investigated the cost associated with these MRIs. We included 62 patients with a total of 67 MRI scans in this study. The MRI studies did not contribute to clinically diagnosing the patients' conditions in any of the cases we reviewed. The hand surgeon's clinical diagnosis disagreed with the radiologist's MRI diagnosis in 63% of patients. The MRI was unnecessary to arrive at the clinical diagnosis and did not influence the treatment offered for any of the 62 patients. The total cost for the 67 non-contrast MRI studies was approximately $53,000. Costly imaging studies are frequently done to determine the validity of a patient's reported problems; unfortunately, these tests are frequently unnecessary and waste resources. Magnetic resonance imaging scans may not be the standard for accurate diagnosis and can misdirect care. Therapeutic III. Copyright © 2012 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

Practice guideline summary: Use of fMRI in the presurgical evaluation of patients with epilepsy: Report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology.

PubMed

Szaflarski, Jerzy P; Gloss, David; Binder, Jeffrey R; Gaillard, William D; Golby, Alexandra J; Holland, Scott K; Ojemann, Jeffrey; Spencer, David C; Swanson, Sara J; French, Jacqueline A; Theodore, William H

2017-01-24

To assess the diagnostic accuracy and prognostic value of functional MRI (fMRI) in determining lateralization and predicting postsurgical language and memory outcomes. An 11-member panel evaluated and rated available evidence according to the 2004 American Academy of Neurology process. At least 2 panelists reviewed the full text of 172 articles and selected 37 for data extraction. Case reports, reports with <15 cases, meta-analyses, and editorials were excluded. The use of fMRI may be considered an option for lateralizing language functions in place of intracarotid amobarbital procedure (IAP) in patients with medial temporal lobe epilepsy (MTLE; Level C), temporal epilepsy in general (Level C), or extratemporal epilepsy (Level C). For patients with temporal neocortical epilepsy or temporal tumors, the evidence is insufficient (Level U). fMRI may be considered to predict postsurgical language deficits after anterior temporal lobe resection (Level C). The use of fMRI may be considered for lateralizing memory functions in place of IAP in patients with MTLE (Level C) but is of unclear utility in other epilepsy types (Level U). fMRI of verbal memory or language encoding should be considered for predicting verbal memory outcome (Level B). fMRI using nonverbal memory encoding may be considered for predicting visuospatial memory outcomes (Level C). Presurgical fMRI could be an adequate alternative to IAP memory testing for predicting verbal memory outcome (Level C). Clinicians should carefully advise patients of the risks and benefits of fMRI vs IAP during discussions concerning choice of specific modality in each case. © 2017 American Academy of Neurology.

Clinical utility of magnetic resonance imaging radiographs for suspected organic syndromes in adult psychiatry.

PubMed

Erhart, Stephen M; Young, Alexander S; Marder, Stephen R; Mintz, Jim

2005-08-01

In psychiatric practice, adult patients are most commonly referred for magnetic resonance imaging (MRI) to screen for suspected organic medical diseases of the central nervous system that can mimic psychiatric syndromes. We identified the most common signs and symptoms prompting MRIs to establish the predictive value of these signs and symptoms for clinically pertinent organic syndromes. This study was a retrospective chart review of psychiatric patients at the Veterans Affairs Greater Los Angeles Health Care Center (Los Angeles, Calif.) who were referred for MRI of the brain between 1996 and 2002. Patients referred for evaluation of dementia were excluded. The specific indications leading clinicians to obtain MRI were identified and grouped. In order to offset the uncertain significance of many MRI findings, for this study, the predictive value of each indication was calculated based on the percentage of patients in whom clinical management changed in response to MRI findings rather than on the percentage with any abnormal MRI results. Of 253 patients who had MRIs, 38 (15%) incurred some degree of treatment modification as a result of MRI findings, including 6 patients in whom MRI identified a medical condition that became the focus of treatment. Six indications appeared most likely to prompt clinicians to obtain MRIs. Because pertinent results were associated with each of these indications, statistical evaluation did not reveal significant differences in their predictive values (chi(2) = 4.32, df = 5, p = .505). Unlike prior studies showing no value to screening radioimaging, this study shows MRI can be a useful screening test among patients suspected of having organic psychiatric disorders and that the common indications for MRI employed at one institution were predictive.

Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands.

PubMed

Deligianni, Fani; Centeno, Maria; Carmichael, David W; Clayden, Jonathan D

2014-01-01

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity.

Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands

PubMed Central

Deligianni, Fani; Centeno, Maria; Carmichael, David W.; Clayden, Jonathan D.

2014-01-01

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity. PMID:25221467

Functional magnetic resonance imaging in a low-field intraoperative scanner.

PubMed

Schulder, Michael; Azmi, Hooman; Biswal, Bharat

2003-01-01

Functional magnetic resonance imaging (fMRI) has been used for preoperative planning and intraoperative surgical navigation. However, most experience to date has been with preoperative images acquired on high-field echoplanar MRI units. We explored the feasibility of acquiring fMRI of the motor cortex with a dedicated low-field intraoperative MRI (iMRI). Five healthy volunteers were scanned with the 0.12-tesla PoleStar N-10 iMRI (Odin Medical Technologies, Israel). A finger-tapping motor paradigm was performed with sequential scans, acquired alternately at rest and during activity. In addition, scans were obtained during breath holding alternating with normal breathing. The same paradigms were repeated using a 3-tesla MRI (Siemens Corp., Allandale, N.J., USA). Statistical analysis was performed offline using cross-correlation and cluster techniques. Data were resampled using the 'jackknife' process. The location, number of activated voxels and degrees of statistical significance between the two scanners were compared. With both the 0.12- and 3-tesla imagers, motor cortex activation was seen in all subjects to a significance of p < 0.02 or greater. No clustered pixels were seen outside the sensorimotor cortex. The resampled correlation coefficients were normally distributed, with a mean of 0.56 for both the 0.12- and 3-tesla scanners (standard deviations 0.11 and 0.08, respectively). The breath holding paradigm confirmed that the expected diffuse activation was seen on 0.12- and 3-tesla scans. Accurate fMRI with a low-field iMRI is feasible. Such data could be acquired immediately before or even during surgery. This would increase the utility of iMRI and allow for updated intraoperative functional imaging, free of the limitations of brain shift. Copyright 2003 S. Karger AG, Basel

An Abbreviated Protocol for High-Risk Screening Breast MRI Saves Time and Resources.

PubMed

Harvey, Susan C; Di Carlo, Phillip A; Lee, Bonmyong; Obadina, Eniola; Sippo, Dorothy; Mullen, Lisa

2016-04-01

To review the ability of an abbreviated, high-risk, screening, breast MRI protocol to detect cancer and save resources. High-risk screening breast MR images were reviewed, from both an abbreviated protocol and a full diagnostic protocol. Differences in cancer detection, scanner utilization, interpretation times, and need for additional imaging were recorded in an integrated data form, and reviewed and compared. A total of 568 MRI cases were reviewed, with the abbreviated and full protocols. No difference was found in the number of cancers detected. Scan times were decreased by 18.8 minutes per case, for a total of 10,678 minutes (178 hours). Interpretation time, on average, was 1.55 minutes for the abbreviated protocol, compared with 6.43 minutes for the full protocol. Review of the full protocol led to a significant change in the final BI-RADS(®) assessment in 12 of 568 (2.1%) cases. Abbreviated MRI is as effective as full-protocol MRI for demonstration of cancers in the high-risk screening setting, with only 12 (2.1%) cases recommended for additional MRI evaluation. The efficiency and resource savings of an abbreviated protocol would be significant, and would allow for opportunities to provide MRI for additional patients, as well as improved radiologist time management and workflow, with the potential to add real-time MRI interpretation or double reading. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

An Abbreviated Protocol for High-Risk Screening Breast MRI Saves Time and Resources.

PubMed

Harvey, Susan C; Di Carlo, Phillip A; Lee, Bonmyong; Obadina, Eniola; Sippo, Dorothy; Mullen, Lisa

2016-11-01

To review the ability of an abbreviated, high-risk, screening, breast MRI protocol to detect cancer and save resources. High-risk screening breast MR images were reviewed, from both an abbreviated protocol and a full diagnostic protocol. Differences in cancer detection, scanner utilization, interpretation times, and need for additional imaging were recorded in an integrated data form, and reviewed and compared. A total of 568 MRI cases were reviewed, with the abbreviated and full protocols. No difference was found in the number of cancers detected. Scan times were decreased by 18.8 minutes per case, for a total of 10,678 minutes (178 hours). Interpretation time, on average, was 1.55 minutes for the abbreviated protocol, compared with 6.43 minutes for the full protocol. Review of the full protocol led to a significant change in the final BI-RADS ® assessment in 12 of 568 (2.1%) cases. Abbreviated MRI is as effective as full-protocol MRI for demonstration of cancers in the high-risk screening setting, with only 12 (2.1 %) cases recommended for additional MRI evaluation. The efficiency and resource savings of an abbreviated protocol would be significant, and would allow for opportunities to provide MRI for additional patients, as well as improved radiologist time management and workflow, with the potential to add real-time MRI interpretation or double reading. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Radio-frequency energy quantification in magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Alon, Leeor

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

MRI-based hip cartilage measures in osteoarthritic and non-osteoarthritic individuals: a systematic review

PubMed Central

Aguilar, Hector N; Battié, Michele C

2017-01-01

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

Constructing Carbon Fiber Motion-Detection Loops for Simultaneous EEG–fMRI

PubMed Central

Abbott, David F.; Masterton, Richard A. J.; Archer, John S.; Fleming, Steven W.; Warren, Aaron E. L.; Jackson, Graeme D.

2015-01-01

One of the most significant impediments to high-quality EEG recorded in an MRI scanner is subject motion. Availability of motion artifact sensors can substantially improve the quality of the recorded EEG. In the study of epilepsy, it can also dramatically increase the confidence that one has in discriminating true epileptiform activity from artifact. This is due both to the reduction in artifact and the ability to visually inspect the motion sensor signals when reading the EEG, revealing whether or not head motion is present. We have previously described the use of carbon fiber loops for detecting and correcting artifact in EEG acquired simultaneously with MRI. The loops, attached to the subject’s head, are electrically insulated from the scalp. They provide a simple and direct measure of specific artifact that is contaminating the EEG, including both subject motion and residual artifact arising from magnetic field gradients applied during MRI. Our previous implementation was used together with a custom-built EEG–fMRI system that differs substantially from current commercially available EEG–fMRI systems. The present technical note extends this work, describing in more detail how to construct the carbon fiber motion-detection loops, and how to interface them with a commercially available simultaneous EEG–fMRI system. We hope that the information provided may help those wishing to utilize a motion-detection/correction solution to improve the quality of EEG recorded within an MRI scanner. PMID:25601852

Multimodal imaging guided preclinical trials of vascular targeting in prostate cancer

PubMed Central

Kalmuk, James; Folaron, Margaret; Buchinger, Julian; Pili, Roberto; Seshadri, Mukund

2015-01-01

The high mortality rate associated with castration-resistant prostate cancer (CRPC) underscores the need for improving therapeutic options for this patient population. The purpose of this study was to examine the potential of vascular targeting in prostate cancer. Experimental studies were carried out in subcutaneous and orthotopic Myc-CaP prostate tumors implanted into male FVB mice to examine the efficacy of a novel microtubule targeted vascular disrupting agent (VDA), EPC2407 (Crolibulin™). A non-invasive multimodality imaging approach based on magnetic resonance imaging (MRI), bioluminescence imaging (BLI), and ultrasound (US) was utilized to guide preclinical trial design and monitor tumor response to therapy. Imaging results were correlated with histopathologic assessment, tumor growth and survival analysis. Contrast-enhanced MRI revealed potent antivascular activity of EPC2407 against subcutaneous and orthotopic Myc-CaP tumors. Longitudinal BLI of Myc-CaP tumors expressing luciferase under the androgen response element (Myc-CaP/ARE-luc) revealed changes in AR signaling and reduction in intratumoral delivery of luciferin substrate following castration suggestive of reduced blood flow. This reduction in blood flow was validated by US and MRI. Combination treatment resulted in sustained vascular suppression, inhibition of tumor regrowth and conferred a survival benefit in both models. These results demonstrate the therapeutic potential of vascular targeting in combination with androgen deprivation against prostate cancer. PMID:26203773

Feasibility of studying brain morphology in major depressive disorder with structural magnetic resonance imaging and clinical data from the electronic medical record: A pilot study

PubMed Central

Hoogenboom, Wouter S.; Perlis, Roy H.; Smoller, Jordan W.; Zeng-Treitler, Qing; Gainer, Vivian S.; Murphy, Shawn N.; Churchill, Susanne E.; Kohane, Isaac S.; Shenton, Martha E.; Iosifescu, Dan V.

2012-01-01

For certain research questions related to long-term outcomes or to rare disorders, designing prospective studies is impractical or prohibitively expensive. Such studies could instead utilize clinical and magnetic resonance imaging data (MRI) collected as part of routine clinical care, stored in the electronic medical record (EMR). Using major depressive disorder (MDD) as a disease model, we examined the feasibility of studying brain morphology and associations with remission using clinical and MRI data exclusively drawn from the EMR. Advanced automated tools were used to select MDD patients and controls from the EMR who had brain MRI data, but no diagnosed brain pathology. MDD patients were further assessed for remission status by review of clinical charts. Twenty MDD patients (eight full-remitters, six partial-remitters, and six non-remitters), and fifteen healthy control subjects met all study criteria for advanced morphometric analyses. Compared to controls, MDD patients had significantly smaller right rostral-anterior cingulate volume, and level of non-remission was associated with smaller left hippocampus and left rostral-middle frontal gyrus volume. The use of EMR data for psychiatric research may provide a timely and cost-effective approach with the potential to generate large study samples reflective of the real population with the illness studied. PMID:23149041

Normalization of white matter intensity on T1-weighted images of patients with acquired central nervous system demyelination.

PubMed

Ghassemi, Rezwan; Brown, Robert; Narayanan, Sridar; Banwell, Brenda; Nakamura, Kunio; Arnold, Douglas L

2015-01-01

Intensity variation between magnetic resonance images (MRI) hinders comparison of tissue intensity distributions in multicenter MRI studies of brain diseases. The available intensity normalization techniques generally work well in healthy subjects but not in the presence of pathologies that affect tissue intensity. One such disease is multiple sclerosis (MS), which is associated with lesions that prominently affect white matter (WM). To develop a T1-weighted (T1w) image intensity normalization method that is independent of WM intensity, and to quantitatively evaluate its performance. We calculated median intensity of grey matter and intraconal orbital fat on T1w images. Using these two reference tissue intensities we calculated a linear normalization function and applied this to the T1w images to produce normalized T1w (NT1) images. We assessed performance of our normalization method for interscanner, interprotocol, and longitudinal normalization variability, and calculated the utility of the normalization method for lesion analyses in clinical trials. Statistical modeling showed marked decreases in T1w intensity differences after normalization (P < .0001). We developed a WM-independent T1w MRI normalization method and tested its performance. This method is suitable for longitudinal multicenter clinical studies for the assessment of the recovery or progression of disease affecting WM. Copyright © 2014 by the American Society of Neuroimaging.

Encoding of marginal utility across time in the human brain

PubMed Central

Pine, Alex; Seymour, Ben; Roiser, Jonathan P; Bossaerts, Peter; Friston, Karl J.; Curran, H. Valerie; Dolan, Raymond J.

2010-01-01

Marginal utility theory prescribes the relationship between the objective property of the magnitude of rewards and their subjective value. Despite its pervasive influence, however, there is remarkably little direct empirical evidence for such a theory of value, let alone of its neurobiological basis. We show that human preferences in an inter-temporal choice task are best described by a model that integrates marginally diminishing utility with temporal discounting. Using functional magnetic resonance imaging (fMRI), we show that activity in the dorsal striatum encodes both the marginal utility of rewards, over and above that which can be described by their magnitude alone, and the discounting associated with increasing time. In addition, our data show that dorsal striatum may be involved in integrating subjective valuation systems inherent to time and magnitude, thereby providing an overall metric of value used to guide choice behaviour. Furthermore, during choice we show that anterior cingulate activity correlates with the degree of difficulty associated with dissonance between value and time. Our data support an integrative architecture for decision-making, revealing the neural representation of distinct subcomponents of value that may contribute to impulsivity and decisiveness. PMID:19641120

Evaluation of left ventricular scar identification from contrast enhanced magnetic resonance imaging for guidance of ventricular catheter ablation therapy

NASA Astrophysics Data System (ADS)

Rettmann, M. E.; Lehmann, H. I.; Johnson, S. B.; Packer, D. L.

2016-03-01

Patients with ventricular arrhythmias typically exhibit myocardial scarring, which is believed to be an important anatomic substrate for reentrant circuits, thereby making these regions a key target in catheter ablation therapy. In ablation therapy, a catheter is guided into the left ventricle and radiofrequency energy is delivered into the tissue to interrupt arrhythmic electrical pathways. Low bipolar voltage regions are typically localized during the procedure through point-by-point construction of an electroanatomic map by sampling the endocardial surface with the ablation catheter and are used as a surrogate for myocardial scar. This process is time consuming, requires significant skill, and has the potential to miss low voltage sites. This has led to efforts to quantify myocardial scar preoperatively using delayed, contrast-enhanced MRI. In this paper, we evaluate the utility of left ventricular scar identification from delayed contrast enhanced magnetic resonance imaging for guidance of catheter ablation of ventricular arrhythmias. Myocardial infarcts were created in three canines followed by a delayed, contrast enhanced MRI scan and electroanatomic mapping. The left ventricle and myocardial scar is segmented from preoperative MRI images and sampled points from the procedural electroanatomical map are registered to the segmented endocardial surface. Sampled points with low bipolar voltage points visually align with the segmented scar regions. This work demonstrates the potential utility of using preoperative delayed, enhanced MRI to identify myocardial scarring for guidance of ventricular catheter ablation therapy.

A Kernel-Based Low-Rank (KLR) Model for Low-Dimensional Manifold Recovery in Highly Accelerated Dynamic MRI.

PubMed

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

2017-11-01

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

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 ...

Annual Screening Strategies in BRCA1 and BRCA2 Gene Mutation Carriers: A Comparative Effectiveness Analysis

PubMed Central

Lowry, Kathryn P.; Lee, Janie M.; Kong, Chung Y.; McMahon, Pamela M.; Gilmore, Michael E.; Cott Chubiz, Jessica E.; Pisano, Etta D.; Gatsonis, Constantine; Ryan, Paula D.; Ozanne, Elissa M.; Gazelle, G. Scott

2011-01-01

Background While breast cancer screening with mammography and MRI is recommended for BRCA mutation carriers, there is no current consensus on the optimal screening regimen. Methods We used a computer simulation model to compare six annual screening strategies [film mammography (FM), digital mammography (DM), FM and magnetic resonance imaging (MRI) or DM and MRI contemporaneously, and alternating FM/MRI or DM/MRI at six-month intervals] beginning at ages 25, 30, 35, and 40, and two strategies of annual MRI with delayed alternating DM/FM to clinical surveillance alone. Strategies were evaluated without and with mammography-induced breast cancer risk, using two models of excess relative risk. Input parameters were obtained from the medical literature, publicly available databases, and calibration. Results Without radiation risk effects, alternating DM/MRI starting at age 25 provided the highest life expectancy (BRCA1: 72.52 years, BRCA2: 77.63 years). When radiation risk was included, a small proportion of diagnosed cancers were attributable to radiation exposure (BRCA1: <2%, BRCA2: <4%). With radiation risk, alternating DM/MRI at age 25 or annual MRI at age 25/delayed alternating DM at age 30 were most effective, depending on the radiation risk model used. Alternating DM/MRI starting at age 25 also had the highest number of false-positive screens/person (BRCA1: 4.5, BRCA2: 8.1). Conclusions Annual MRI at 25/delayed alternating DM at age 30 is likely the most effective screening strategy in BRCA mutation carriers. Screening benefits, associated risks and personal acceptance of false-positive results, should be considered in choosing the optimal screening strategy for individual women. PMID:21935911

Left ventricular hypertrophy by ECG versus cardiac MRI as a predictor for heart failure.

PubMed

Oseni, Abdullahi O; Qureshi, Waqas T; Almahmoud, Mohamed F; Bertoni, Alain G; Bluemke, David A; Hundley, William G; Lima, Joao A C; Herrington, David M; Soliman, Elsayed Z

2017-01-01

To determine if there is a significant difference in the predictive abilities of left ventricular hypertrophy (LVH) detected by ECG-LVH versus LVH ascertained by cardiac MRI-LVH in a model similar to the Framingham Heart Failure Risk Score (FHFRS). This study included 4745 (mean age 61±10 years, 53.5% women, 61.7% non-whites) participants in the Multi-Ethnic Study of Atherosclerosis. ECG-LVH was defined using Cornell voltage product while MRI-LVH was derived from left ventricular mass. Cox proportional hazard regression was used to examine the association between ECG-LVH and MRI-LVH with incident heart failure (HF). Harrell's concordance C-index was used to estimate the predictive ability of the model when either ECG-LVH or MRI-LVH was included as one of its components. ECG-LVH was present in 291 (6.1%), while MRI-LVH was present in 499 (10.5%) of the participants. Both ECG-LVH (HR 2.25, 95% CI 1.38 to 3.69) and MRI-LVH (HR 3.80, 95% CI 1.56 to 5.63) were predictive of HF. The absolute risk of developing HF was 8.81% for MRI-LVH versus 2.26% for absence of MRI-LVH with a relative risk of 3.9. With ECG-LVH, the absolute risk of developing HF 6.87% compared with 2.69% for absence of ECG-LVH with a relative risk of 2.55. The ability of the model to predict HF was better with MRI-LVH (C-index 0.871, 95% CI 0.842 to 0.899) than with ECG-LVH (C-index 0.860, 95% CI 0.833 to 0.888) (p<0.0001). ECG-LVH and MRI-LVH are predictive of HF. Substituting MRI-LVH for ECG-LVH improves the predictive ability of a model similar to the FHFRS. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Advanced Imaging Utilization Trends in Privately Insured Patients From 2007 to 2013.

PubMed

Horný, Michal; Burgess, James F; Cohen, Alan B

2015-12-01

The aim of the study was to investigate whether the increase in utilization of advanced diagnostic imaging for privately insured patients in 2011 was the beginning of a new trend in imaging utilization growth, or an isolated deviation from the declining trend that began in 2008. We extracted outpatient and inpatient CT, diagnostic ultrasound, MRI, and PET procedures from databases, for the years 2007 to 2013. This study extended previous work, covering 2012 to 2013, using the same methodology. For every year of the study period, we calculated the following: number of procedures per person-year covered by private health insurance; proportion of office and emergency visits that resulted in an imaging session; average payments per procedure; and total payments per person-year covered by private health insurance. Outpatient utilization of CT and PET decreased in both 2012 and 2013; outpatient utilization of MRI mildly increased in 2012, but then decreased in 2013. Outpatient utilization of diagnostic ultrasound showed a very different pattern, increasing throughout the study period. Inpatient utilization of all imaging modalities except PET decreased in both 2012 and 2013. Adjusted payments for all imaging modalities increased in 2012, and then dropped substantially in 2013, except the adjusted payments for diagnostic ultrasound that increased in 2013 again. The trend of increasing utilization of advanced diagnostic imaging seems to be over for some, but not all, imaging modalities. A combination of policy (eg, breast density notification laws), technologic advancement, and wider access seems to be responsible for at least part of an increasing utilization of diagnostic ultrasound. Copyright © 2015 American College of Radiology. All rights reserved.

Reducing Field Distortion in Magnetic Resonance Imaging

NASA Technical Reports Server (NTRS)

Eom, Byeong Ho; Penanen, Konstantin; Hahn, Inseob

2010-01-01

A concept for a magnetic resonance imaging (MRI) system that would utilize a relatively weak magnetic field provides for several design features that differ significantly from the corresponding features of conventional MRI systems. Notable among these features are a magnetic-field configuration that reduces (relative to the conventional configuration) distortion and blurring of the image, the use of a superconducting quantum interference device (SQUID) magnetometer as the detector, and an imaging procedure suited for the unconventional field configuration and sensor. In a typical application of MRI, a radio-frequency pulse is used to excite precession of the magnetic moments of protons in an applied magnetic field, and the decaying precession is detected for a short time following the pulse. The precession occurs at a resonance frequency proportional to the strengths of the magnetic field and the proton magnetic moment. The magnetic field is configured to vary with position in a known way; hence, by virtue of the aforesaid proportionality, the resonance frequency varies with position in a known way. In other words, position is encoded as resonance frequency. MRI using magnetic fields weaker than those of conventional MRI offers several advantages, including cheaper and smaller equipment, greater compatibility with metallic objects, and higher image quality because of low susceptibility distortion and enhanced spin-lattice-relaxation- time contrast. SQUID MRI is being developed into a practical MRI method for applied magnetic flux densities of the order of only 100 T

Comparison among T1-weighted magnetic resonance imaging, modified dixon method, and magnetic resonance spectroscopy in measuring bone marrow fat.

PubMed

Shen, Wei; Gong, Xiuqun; Weiss, Jessica; Jin, Ye

2013-01-01

An increasing number of studies are utilizing different magnetic resonance (MR) methods to quantify bone marrow fat due to its potential role in osteoporosis. Our aim is to compare the measurements of bone marrow fat among T1-weighted magnetic resonance imaging (MRI), modified Dixon method (also called fat fraction MRI (FFMRI)), and magnetic resonance spectroscopy (MRS). Contiguous MRI scans were acquired in 27 Caucasian postmenopausal women with a modified Dixon method (i.e., FFMRI). Bone marrow adipose tissue (BMAT) of T1-weighted MRI and bone marrow fat fraction of the L3 vertebra and femoral necks were quantified using SliceOmatic and Matlab. MRS was also acquired at the L3 vertebra. Correlation among the three MR methods measured bone marrow fat fraction and BMAT ranges from 0.78 to 0.88 (P < 0.001) in the L3 vertebra. Correlation between BMAT measured by T1-weighted MRI and bone marrow fat fraction measured by modified FFMRI is 0.86 (P < 0.001) in femoral necks. There are good correlations among T1-weighted MRI, FFMRI, and MRS for bone marrow fat quantification. The inhomogeneous distribution of bone marrow fat, the threshold segmentation of the T1-weighted MRI, and the ambiguity of the FFMRI may partially explain the difference among the three methods.

Comparison among T1-Weighted Magnetic Resonance Imaging, Modified Dixon Method, and Magnetic Resonance Spectroscopy in Measuring Bone Marrow Fat

PubMed Central

Shen, Wei; Gong, Xiuqun; Weiss, Jessica; Jin, Ye

2013-01-01

Introduction. An increasing number of studies are utilizing different magnetic resonance (MR) methods to quantify bone marrow fat due to its potential role in osteoporosis. Our aim is to compare the measurements of bone marrow fat among T1-weighted magnetic resonance imaging (MRI), modified Dixon method (also called fat fraction MRI (FFMRI)), and magnetic resonance spectroscopy (MRS). Methods. Contiguous MRI scans were acquired in 27 Caucasian postmenopausal women with a modified Dixon method (i.e., FFMRI). Bone marrow adipose tissue (BMAT) of T1-weighted MRI and bone marrow fat fraction of the L3 vertebra and femoral necks were quantified using SliceOmatic and Matlab. MRS was also acquired at the L3 vertebra. Results. Correlation among the three MR methods measured bone marrow fat fraction and BMAT ranges from 0.78 to 0.88 (P < 0.001) in the L3 vertebra. Correlation between BMAT measured by T1-weighted MRI and bone marrow fat fraction measured by modified FFMRI is 0.86 (P < 0.001) in femoral necks. Conclusion. There are good correlations among T1-weighted MRI, FFMRI, and MRS for bone marrow fat quantification. The inhomogeneous distribution of bone marrow fat, the threshold segmentation of the T1-weighted MRI, and the ambiguity of the FFMRI may partially explain the difference among the three methods. PMID:23606951

An eigenvalue approach for the automatic scaling of unknowns in model-based reconstructions: Application to real-time phase-contrast flow MRI.

PubMed

Tan, Zhengguo; Hohage, Thorsten; Kalentev, Oleksandr; Joseph, Arun A; Wang, Xiaoqing; Voit, Dirk; Merboldt, K Dietmar; Frahm, Jens

2017-12-01

The purpose of this work is to develop an automatic method for the scaling of unknowns in model-based nonlinear inverse reconstructions and to evaluate its application to real-time phase-contrast (RT-PC) flow magnetic resonance imaging (MRI). Model-based MRI reconstructions of parametric maps which describe a physical or physiological function require the solution of a nonlinear inverse problem, because the list of unknowns in the extended MRI signal equation comprises multiple functional parameters and all coil sensitivity profiles. Iterative solutions therefore rely on an appropriate scaling of unknowns to numerically balance partial derivatives and regularization terms. The scaling of unknowns emerges as a self-adjoint and positive-definite matrix which is expressible by its maximal eigenvalue and solved by power iterations. The proposed method is applied to RT-PC flow MRI based on highly undersampled acquisitions. Experimental validations include numerical phantoms providing ground truth and a wide range of human studies in the ascending aorta, carotid arteries, deep veins during muscular exercise and cerebrospinal fluid during deep respiration. For RT-PC flow MRI, model-based reconstructions with automatic scaling not only offer velocity maps with high spatiotemporal acuity and much reduced phase noise, but also ensure fast convergence as well as accurate and precise velocities for all conditions tested, i.e. for different velocity ranges, vessel sizes and the simultaneous presence of signals with velocity aliasing. In summary, the proposed automatic scaling of unknowns in model-based MRI reconstructions yields quantitatively reliable velocities for RT-PC flow MRI in various experimental scenarios. Copyright © 2017 John Wiley & Sons, Ltd.

Cardiac re-entry dynamics and self-termination in DT-MRI based model of Human Foetal Heart

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Analysis of EEG-fMRI data in focal epilepsy based on automated spike classification and Signal Space Projection.

PubMed

Liston, Adam D; De Munck, Jan C; Hamandi, Khalid; Laufs, Helmut; Ossenblok, Pauly; Duncan, John S; Lemieux, Louis

2006-07-01

Simultaneous acquisition of EEG and fMRI data enables the investigation of the hemodynamic correlates of interictal epileptiform discharges (IEDs) during the resting state in patients with epilepsy. This paper addresses two issues: (1) the semi-automation of IED classification in statistical modelling for fMRI analysis and (2) the improvement of IED detection to increase experimental fMRI efficiency. For patients with multiple IED generators, sensitivity to IED-correlated BOLD signal changes can be improved when the fMRI analysis model distinguishes between IEDs of differing morphology and field. In an attempt to reduce the subjectivity of visual IED classification, we implemented a semi-automated system, based on the spatio-temporal clustering of EEG events. We illustrate the technique's usefulness using EEG-fMRI data from a subject with focal epilepsy in whom 202 IEDs were visually identified and then clustered semi-automatically into four clusters. Each cluster of IEDs was modelled separately for the purpose of fMRI analysis. This revealed IED-correlated BOLD activations in distinct regions corresponding to three different IED categories. In a second step, Signal Space Projection (SSP) was used to project the scalp EEG onto the dipoles corresponding to each IED cluster. This resulted in 123 previously unrecognised IEDs, the inclusion of which, in the General Linear Model (GLM), increased the experimental efficiency as reflected by significant BOLD activations. We have also shown that the detection of extra IEDs is robust in the face of fluctuations in the set of visually detected IEDs. We conclude that automated IED classification can result in more objective fMRI models of IEDs and significantly increased sensitivity.

Brain magnetic resonance imaging CO2 stress testing in adolescent postconcussion syndrome.

PubMed

Mutch, W Alan C; Ellis, Michael J; Ryner, Lawrence N; Ruth Graham, M; Dufault, Brenden; Gregson, Brian; Hall, Thomas; Bunge, Martin; Essig, Marco; Fisher, Joseph A; Duffin, James; Mikulis, David J

2016-09-01

OBJECT A neuroimaging assessment tool to visualize global and regional impairments in cerebral blood flow (CBF) and cerebrovascular responsiveness in individual patients with concussion remains elusive. Here the authors summarize the safety, feasibility, and results of brain CO2 stress testing in adolescents with postconcussion syndrome (PCS) and healthy controls. METHODS This study was approved by the Biomedical Research Ethics Board at the University of Manitoba. Fifteen adolescents with PCS and 17 healthy control subjects underwent anatomical MRI, pseudo-continuous arterial spin labeling MRI, and brain stress testing using controlled CO2 challenge and blood oxygen level-dependent (BOLD) MRI. Post hoc processing was performed using statistical parametric mapping to determine voxel-by-voxel regional resting CBF and cerebrovascular responsiveness of the brain to the CO2 stimulus (increase in BOLD signal) or the inverse (decrease in BOLD signal). Receiver operating characteristic (ROC) curves were generated to compare voxel counts categorized by control (0) or PCS (1). RESULTS Studies were well tolerated without any serious adverse events. Anatomical MRI was normal in all study participants. No differences in CO2 stimuli were seen between the 2 participant groups. No group differences in global mean CBF were detected between PCS patients and healthy controls. Patient-specific differences in mean regional CBF and CO2 BOLD responsiveness were observed in all PCS patients. The ROC curve analysis for brain regions manifesting a voxel response greater than and less than the control atlas (that is, abnormal voxel counts) produced an area under the curve of 0.87 (p < 0.0001) and 0.80 (p = 0.0003), respectively, consistent with a clinically useful predictive model. CONCLUSIONS Adolescent PCS is associated with patient-specific abnormalities in regional mean CBF and BOLD cerebrovascular responsiveness that occur in the setting of normal global resting CBF. Future prospective studies are warranted to examine the utility of brain MRI CO2 stress testing in the longitudinal assessment of acute sports-related concussion and PCS.

Anisotropic smoothing regularization (AnSR) in Thirion's Demons registration evaluates brain MRI tissue changes post-laser ablation.

PubMed

Hwuang, Eileen; Danish, Shabbar; Rusu, Mirabela; Sparks, Rachel; Toth, Robert; Madabhushi, Anant

2013-01-01

MRI-guided laser-induced interstitial thermal therapy (LITT) is a form of laser ablation and a potential alternative to craniotomy in treating glioblastoma multiforme (GBM) and epilepsy patients, but its effectiveness has yet to be fully evaluated. One way of assessing short-term treatment of LITT is by evaluating changes in post-treatment MRI as a measure of response. Alignment of pre- and post-LITT MRI in GBM and epilepsy patients via nonrigid registration is necessary to detect subtle localized treatment changes on imaging, which can then be correlated with patient outcome. A popular deformable registration scheme in the context of brain imaging is Thirion's Demons algorithm, but its flexibility often introduces artifacts without physical significance, which has conventionally been corrected by Gaussian smoothing of the deformation field. In order to prevent such artifacts, we instead present the Anisotropic smoothing regularizer (AnSR) which utilizes edge-detection and denoising within the Demons framework to regularize the deformation field at each iteration of the registration more aggressively in regions of homogeneously oriented displacements while simultaneously regularizing less aggressively in areas containing heterogeneous local deformation and tissue interfaces. In contrast, the conventional Gaussian smoothing regularizer (GaSR) uniformly averages over the entire deformation field, without carefully accounting for transitions across tissue boundaries and local displacements in the deformation field. In this work we employ AnSR within the Demons algorithm and perform pairwise registration on 2D synthetic brain MRI with and without noise after inducing a deformation that models shrinkage of the target region expected from LITT. We also applied Demons with AnSR for registering clinical T1-weighted MRI for one epilepsy and one GBM patient pre- and post-LITT. Our results demonstrate that by maintaining select displacements in the deformation field, AnSR outperforms both GaSR and no regularizer (NoR) in terms of normalized sum of squared differences (NSSD) with values such as 0.743, 0.807, and 1.000, respectively, for GBM.

Targeting Accuracy, Procedure Times and User Experience of 240 Experimental MRI Biopsies Guided by a Clinical Add-On Navigation System

PubMed Central

Busse, Harald; Riedel, Tim; Garnov, Nikita; Thörmer, Gregor; Kahn, Thomas; Moche, Michael

2015-01-01

Objectives MRI is of great clinical utility for the guidance of special diagnostic and therapeutic interventions. The majority of such procedures are performed iteratively ("in-and-out") in standard, closed-bore MRI systems with control imaging inside the bore and needle adjustments outside the bore. The fundamental limitations of such an approach have led to the development of various assistance techniques, from simple guidance tools to advanced navigation systems. The purpose of this work was to thoroughly assess the targeting accuracy, workflow and usability of a clinical add-on navigation solution on 240 simulated biopsies by different medical operators. Methods Navigation relied on a virtual 3D MRI scene with real-time overlay of the optically tracked biopsy needle. Smart reference markers on a freely adjustable arm ensured proper registration. Twenty-four operators – attending (AR) and resident radiologists (RR) as well as medical students (MS) – performed well-controlled biopsies of 10 embedded model targets (mean diameter: 8.5 mm, insertion depths: 17-76 mm). Targeting accuracy, procedure times and 13 Likert scores on system performance were determined (strong agreement: 5.0). Results Differences in diagnostic success rates (AR: 93%, RR: 88%, MS: 81%) were not significant. In contrast, between-group differences in biopsy times (AR: 4:15, RR: 4:40, MS: 5:06 min:sec) differed significantly (p<0.01). Mean overall rating was 4.2. The average operator would use the system again (4.8) and stated that the outcome justifies the extra effort (4.4). Lowest agreement was reported for the robustness against external perturbations (2.8). Conclusions The described combination of optical tracking technology with an automatic MRI registration appears to be sufficiently accurate for instrument guidance in a standard (closed-bore) MRI environment. High targeting accuracy and usability was demonstrated on a relatively large number of procedures and operators. Between groups with different expertise there were significant differences in experimental procedure times but not in the number of successful biopsies. PMID:26222443

Thoracic respiratory motion estimation from MRI using a statistical model and a 2-D image navigator.

PubMed

King, A P; Buerger, C; Tsoumpas, C; Marsden, P K; Schaeffter, T

2012-01-01

Respiratory motion models have potential application for estimating and correcting the effects of motion in a wide range of applications, for example in PET-MR imaging. Given that motion cycles caused by breathing are only approximately repeatable, an important quality of such models is their ability to capture and estimate the intra- and inter-cycle variability of the motion. In this paper we propose and describe a technique for free-form nonrigid respiratory motion correction in the thorax. Our model is based on a principal component analysis of the motion states encountered during different breathing patterns, and is formed from motion estimates made from dynamic 3-D MRI data. We apply our model using a data-driven technique based on a 2-D MRI image navigator. Unlike most previously reported work in the literature, our approach is able to capture both intra- and inter-cycle motion variability. In addition, the 2-D image navigator can be used to estimate how applicable the current motion model is, and hence report when more imaging data is required to update the model. We also use the motion model to decide on the best positioning for the image navigator. We validate our approach using MRI data acquired from 10 volunteers and demonstrate improvements of up to 40.5% over other reported motion modelling approaches, which corresponds to 61% of the overall respiratory motion present. Finally we demonstrate one potential application of our technique: MRI-based motion correction of real-time PET data for simultaneous PET-MRI acquisition. Copyright © 2011 Elsevier B.V. All rights reserved.

Evaluation of three inverse problem models to quantify skin microcirculation using diffusion-weighted MRI

NASA Astrophysics Data System (ADS)

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

2008-11-01

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

Multi-Domain Transfer Learning for Early Diagnosis of Alzheimer's Disease.

PubMed

Cheng, Bo; Liu, Mingxia; Shen, Dinggang; Li, Zuoyong; Zhang, Daoqiang

2017-04-01

Recently, transfer learning has been successfully applied in early diagnosis of Alzheimer's Disease (AD) based on multi-domain data. However, most of existing methods only use data from a single auxiliary domain, and thus cannot utilize the intrinsic useful correlation information from multiple domains. Accordingly, in this paper, we consider the joint learning of tasks in multi-auxiliary domains and the target domain, and propose a novel Multi-Domain Transfer Learning (MDTL) framework for early diagnosis of AD. Specifically, the proposed MDTL framework consists of two key components: 1) a multi-domain transfer feature selection (MDTFS) model that selects the most informative feature subset from multi-domain data, and 2) a multi-domain transfer classification (MDTC) model that can identify disease status for early AD detection. We evaluate our method on 807 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database using baseline magnetic resonance imaging (MRI) data. The experimental results show that the proposed MDTL method can effectively utilize multi-auxiliary domain data for improving the learning performance in the target domain, compared with several state-of-the-art methods.

The correlation between emotional intelligence and gray matter volume in university students.

PubMed

Tan, Yafei; Zhang, Qinglin; Li, Wenfu; Wei, Dongtao; Qiao, Lei; Qiu, Jiang; Hitchman, Glenn; Liu, Yijun

2014-11-01

A number of recent studies have investigated the neurological substrates of emotional intelligence (EI), but none of them have considered the neural correlates of EI that are measured using the Schutte Self-Report Emotional Intelligence Scale (SSREIS). This scale was developed based on the EI model of Salovey and Mayer (1990). In the present study, SSREIS was adopted to estimate EI. Meanwhile, magnetic resonance imaging (MRI) and voxel-based morphometry (VBM) were used to evaluate the gray matter volume (GMV) of 328 university students. Results found positive correlations between Monitor of Emotions and VBM measurements in the insula and orbitofrontal cortex. In addition, Utilization of Emotions was positively correlated with the GMV in the parahippocampal gyrus, but was negatively correlated with the VBM measurements in the fusiform gyrus and middle temporal gyrus. Furthermore, Social Ability had volume correlates in the vermis. These findings indicate that the neural correlates of the EI model, which primarily focuses on the abilities of individuals to appraise and express emotions, can also regulate and utilize emotions to solve problems. Copyright © 2014 Elsevier Inc. All rights reserved.

Multi-Domain Transfer Learning for Early Diagnosis of Alzheimer’s Disease

PubMed Central

Cheng, Bo; Liu, Mingxia; Li, Zuoyong

2017-01-01

Recently, transfer learning has been successfully applied in early diagnosis of Alzheimer’s Disease (AD) based on multi-domain data. However, most of existing methods only use data from a single auxiliary domain, and thus cannot utilize the intrinsic useful correlation information from multiple domains. Accordingly, in this paper, we consider the joint learning of tasks in multi-auxiliary domains and the target domain, and propose a novel Multi-Domain Transfer Learning (MDTL) framework for early diagnosis of AD. Specifically, the proposed MDTL framework consists of two key components: 1) a multi-domain transfer feature selection (MDTFS) model that selects the most informative feature subset from multi-domain data, and 2) a multidomain transfer classification (MDTC) model that can identify disease status for early AD detection. We evaluate our method on 807 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using baseline magnetic resonance imaging (MRI) data. The experimental results show that the proposed MDTL method can effectively utilize multi-auxiliary domain data for improving the learning performance in the target domain, compared with several state-of-the-art methods. PMID:27928657

Modeling Dynamic Contrast-Enhanced MRI Data with a Constrained Local AIF.

PubMed

Duan, Chong; Kallehauge, Jesper F; Pérez-Torres, Carlos J; Bretthorst, G Larry; Beeman, Scott C; Tanderup, Kari; Ackerman, Joseph J H; Garbow, Joel R

2018-02-01

This study aims to develop a constrained local arterial input function (cL-AIF) to improve quantitative analysis of dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) data by accounting for the contrast-agent bolus amplitude error in the voxel-specific AIF. Bayesian probability theory-based parameter estimation and model selection were used to compare tracer kinetic modeling employing either the measured remote-AIF (R-AIF, i.e., the traditional approach) or an inferred cL-AIF against both in silico DCE-MRI data and clinical, cervical cancer DCE-MRI data. When the data model included the cL-AIF, tracer kinetic parameters were correctly estimated from in silico data under contrast-to-noise conditions typical of clinical DCE-MRI experiments. Considering the clinical cervical cancer data, Bayesian model selection was performed for all tumor voxels of the 16 patients (35,602 voxels in total). Among those voxels, a tracer kinetic model that employed the voxel-specific cL-AIF was preferred (i.e., had a higher posterior probability) in 80 % of the voxels compared to the direct use of a single R-AIF. Maps of spatial variation in voxel-specific AIF bolus amplitude and arrival time for heterogeneous tissues, such as cervical cancer, are accessible with the cL-AIF approach. The cL-AIF method, which estimates unique local-AIF amplitude and arrival time for each voxel within the tissue of interest, provides better modeling of DCE-MRI data than the use of a single, measured R-AIF. The Bayesian-based data analysis described herein affords estimates of uncertainties for each model parameter, via posterior probability density functions, and voxel-wise comparison across methods/models, via model selection in data modeling.

Geographic Distribution of Radiologists and Utilization of Teleradiology in Japan: A Longitudinal Analysis Based on National Census Data.

PubMed

Matsumoto, Masatoshi; Koike, Soichi; Kashima, Saori; Awai, Kazuo

2015-01-01

Japan has the most CT and MRI scanners per unit population in the world, and as these technologies spread, their geographic distribution is becoming equalized. In contrast, the number of radiologists per unit population in Japan is the lowest among OECD countries and their geographic distribution is unknown. Likewise, little is known about the use of teleradiology, which can compensate for the uneven distribution of radiologists. Based on the Survey of Physicians, Dentists and Pharmacists and the Static Survey of Medical Institutions by the Ministry of Health, Labour and Welfare, a dataset of radiologists and CT and MRI utilizations in each of Japan's 1811 municipalities was created. The inter-municipality equity of the number of radiologists was evaluated using Gini coefficient. Logistic regression analysis, based on Static Survey data, was performed to evaluate the association between hospital location and teleradiology use. Between 2006 and 2012 the number of radiologists increased by 21.7%, but the Gini coefficient remained unchanged. The number of radiologists per 1,000 CT (MRI) utilizations decreased by 17.9% (1.0%); the number was highest in metropolis and lowest in town/village and the disparity has widened from 1.9 to 2.2 (1.6 to 2.0) times. The number of hospitals and clinics using teleradiology has increased (by 69.6% and 18.1%, respectively). Hospitals located in towns/villages (odds ratio 1.61; 95% confidence interval 1.26-2.07) were more likely to use teleradiology than those in metropolises. Contrary to the CT and MRI distributions, radiologist distribution has not been evened out by the increase in their number; in other words, the distribution of radiologists was not affected by market-derived spatial competition force. As a consequence, the gap of the radiologist shortage between urban and rural areas is increasing. Teleradiology, which is one way to ameliorate this gap, should be encouraged.

Neuroaxonal ion dyshomeostasis of the normal-appearing corpus callosum in experimental autoimmune encephalomyelitis.

PubMed

Chen, Chiao-Chi V; Zechariah, Anil; Hsu, Yi-Hua; Chen, Hsiao-Wen; Yang, Li-Chuan; Chang, Chen

2008-04-01

Atrophy of the corpus callosum (CC) is a well-documented observation in clinically definite multiple sclerosis (MS) patients. One recent hypothesis for the neurodegeneration that occurs in MS is that ion dyshomeostasis leads to neuroaxonal damage. To examine whether ion dyshomeostasis occurs in the CC during MS onset, experimental autoimmune encephalomyelitis (EAE) was utilized as an animal MS model to induce autoimmunity-mediated responses. To date, in vivo investigations of neuronal ion homeostasis has not been feasible using traditional neuroscience techniques. Therefore, the current study employed an emerging MRI method, called Mn2+-enhanced MRI (MEMRI). Mn2+ dynamics is closely associated with important neuronal activity events, and is also considered to be a Ca2+ surrogate. Furthermore, when injected intracranially, Mn2+ can be used as a multisynaptic tracer. These features enable MEMRI to detect neuronal ion homeostasis within a multisynaptic circuit that is connected to the injection site. Mn2+ was injected into the visual cortex to trace the CC, and T1-weighted imaging was utilized to observe temporal changes in Mn2+-induced signals in the traced pathways. The results showed that neuroaxonal functional changes associated with ion dyshomeostasis occurred in the CC during an acute EAE attack. In addition, the pathway appeared normal, although EAE-induced immune-cell infiltration was visible around the CC. The findings suggest that ion dyshomeostasis is a major neuronal aberration underlying the deterioration of normal-appearing brain tissues in MS, supporting its involvement in neuroaxonal functioning in MS.

Theranostic multimodal potential of magnetic nanoparticles actuated by non-heating low frequency magnetic field in the new-generation nanomedicine

NASA Astrophysics Data System (ADS)

Golovin, Yuri I.; Klyachko, Natalia L.; Majouga, Alexander G.; Sokolsky, Marina; Kabanov, Alexander V.

2017-02-01

The scope of this review involves one of the most promising branches of new-generation biomedicine, namely magnetic nanotheranostics using remote control of functionalized magnetic nanoparticles (f-MNPs) by means of alternating magnetic fields (AMFs). The review is mainly focused on new approach which utilizes non-heating low frequency magnetic fields (LFMFs) for nanomechanical actuation of f-MNPs. This approach is compared to such traditional ones as magnetic resonance imaging (MRI) and radio-frequency (RF) magnetic hyperthermia (MH) which utilize high frequency heating AMF. The innovative principles and specific models of non-thermal magnetomechanical actuation of biostructures by MNP rotational oscillations in LFMF are described. The discussed strategy allows biodistribution monitoring in situ, delivering drugs to target tissues and releasing them with controlled rate, controlling biocatalytic reaction kinetics, inducing malignant cell apoptosis, and more. Optimization of both LFMF and f-MNP parameters may lead to dramatic improvement of treatment efficiency, locality, and selectivity on molecular or cellular levels and allow implementing both drug and drugless, i.e., pure nanomechanical therapy, in particular cancer therapy. The optimal parameters within this approach differ significantly from those used in MH or MRI because of the principal difference in the f-MNP actuation modes. It is shown that specifically designed high gradient, steady magnetic field enables diagnostic and therapeutic LFMF impact localization in the deep tissues within the area ranging from a millimeter to a few centimeters and 3D scanning of affected region, if necessary.

Virtual 3-dimensional preoperative planning with the dextroscope for excision of a 4th ventricular ependymoma.

PubMed

Anil, S M; Kato, Y; Hayakawa, M; Yoshida, K; Nagahisha, S; Kanno, T

2007-04-01

Advances in computer imaging and technology have facilitated enhancement in surgical planning with a 3-dimensional model of the surgical plan of action utilizing advanced visualization tools in order to plan individual interactive operations with the aid of the dextroscope. This provides a proper 3-dimensional imaging insight to the pathological anatomy and sets a new dimension in collaboration for training and education. The case of a seventeen-year-old female, being operated with the aid of a preoperative 3-dimensional virtual reality planning and the practical application of the neurosurgical operation, is presented. This young lady presented with a two-year history of recurrent episodes of severe, global, throbbing headache with episodes of projectile vomiting associated with shoulder pain which progressively worsened. She had no obvious neurological deficits on clinical examination. CT and MRI showed a contrast-enhancing midline posterior fossa space-occupying lesion. Utilizing virtual imaging technology with the aid of a dextroscope which generates stereoscopic images, a 3-dimensional image was produced with the CT and MRI images. A preoperative planning for excision of the lesion was made and a real-time 3-dimensional volume was produced and surgical planning with the dextroscope was made and the lesion excised. Virtual reality has brought new proportions in 3-dimensional planning and management of various complex neuroanatomical problems that are faced during various operations. Integration of 3-dimensional imaging with stereoscopic vision makes understanding the complex anatomy easier and helps improve decision making in patient management.

A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data

PubMed Central

Calhoun, Vince D.; Liu, Jingyu; Adalı, Tülay

2009-01-01

Independent component analysis (ICA) has become an increasingly utilized approach for analyzing brain imaging data. In contrast to the widely used general linear model (GLM) that requires the user to parameterize the data (e.g. the brain's response to stimuli), ICA, by relying upon a general assumption of independence, allows the user to be agnostic regarding the exact form of the response. In addition, ICA is intrinsically a multivariate approach, and hence each component provides a grouping of brain activity into regions that share the same response pattern thus providing a natural measure of functional connectivity. There are a wide variety of ICA approaches that have been proposed, in this paper we focus upon two distinct methods. The first part of this paper reviews the use of ICA for making group inferences from fMRI data. We provide an overview of current approaches for utilizing ICA to make group inferences with a focus upon the group ICA approach implemented in the GIFT software. In the next part of this paper, we provide an overview of the use of ICA to combine or fuse multimodal data. ICA has proven particularly useful for data fusion of multiple tasks or data modalities such as single nucleotide polymorphism (SNP) data or event-related potentials. As demonstrated by a number of examples in this paper, ICA is a powerful and versatile data-driven approach for studying the brain. PMID:19059344

A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data.

PubMed

Calhoun, Vince D; Liu, Jingyu; Adali, Tülay

2009-03-01

Independent component analysis (ICA) has become an increasingly utilized approach for analyzing brain imaging data. In contrast to the widely used general linear model (GLM) that requires the user to parameterize the data (e.g. the brain's response to stimuli), ICA, by relying upon a general assumption of independence, allows the user to be agnostic regarding the exact form of the response. In addition, ICA is intrinsically a multivariate approach, and hence each component provides a grouping of brain activity into regions that share the same response pattern thus providing a natural measure of functional connectivity. There are a wide variety of ICA approaches that have been proposed, in this paper we focus upon two distinct methods. The first part of this paper reviews the use of ICA for making group inferences from fMRI data. We provide an overview of current approaches for utilizing ICA to make group inferences with a focus upon the group ICA approach implemented in the GIFT software. In the next part of this paper, we provide an overview of the use of ICA to combine or fuse multimodal data. ICA has proven particularly useful for data fusion of multiple tasks or data modalities such as single nucleotide polymorphism (SNP) data or event-related potentials. As demonstrated by a number of examples in this paper, ICA is a powerful and versatile data-driven approach for studying the brain.

Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping

PubMed Central

Robinson, Jennifer; Calhoun, Vince

2018-01-01

Purpose To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping. Methods A brain functional activity is represented in terms of magnetic source by a perturbation model: χ = χ0 +δχ, with δχ for BOLD magnetic perturbations and χ0 for background. A brain fMRI experiment produces a timeseries of complex-valued images (T2* images), whereby we extract the BOLD phase signals (denoted by δP) by a complex division. By solving an inverse problem, we reconstruct the BOLD δχ dataset from the δP dataset, and the brain χ distribution from a (unwrapped) T2* phase image. Given a 4D dataset of task BOLD fMRI, we implement brain functional mapping by temporal correlation analysis. Results Through a high-field (7T) and high-resolution (0.5mm in plane) task fMRI experiment, we demonstrated in detail the BOLD perturbation model for fMRI phase signal separation (P + δP) and reconstructing intrinsic brain magnetic source (χ and δχ). We also provided to a low-field (3T) and low-resolution (2mm) task fMRI experiment in support of single-subject fMRI study. Our experiments show that the δχ-depicted functional map reveals bidirectional BOLD χ perturbations during the task performance. Conclusions The BOLD perturbation model allows us to separate fMRI phase signal (by complex division) and to perform inverse mapping for pure BOLD δχ reconstruction for intrinsic functional χ mapping. The full brain χ reconstruction (from unwrapped fMRI phase) provides a new brain tissue image that allows to scrutinize the brain tissue idiosyncrasy for the pure BOLD δχ response through an automatic function/structure co-localization. PMID:29351339

Black blood MRI in suspected large artery primary angiitis of the central nervous system.

PubMed

Pfefferkorn, Thomas; Linn, Jennifer; Habs, Maximilian; Opherk, Christina; Cyran, Clemens; Ottomeyer, Caroline; Straube, Andreas; Dichgans, Martin; Nikolaou, Konstantin; Saam, Tobias

2013-07-01

Single case reports suggest that black blood MRI (T1-weighted fat and blood suppressed sequences with and without contrast injection; BB-MRI) may visualize intracranial vessel wall contrast enhancement (CE) in primary angiitis of the central nervous system (PACNS). In this single-center observational pilot study we prospectively investigated the value of BB-MRI in the diagnosis of large artery PACNS. Patients with suspected large artery PACNS received a standardized diagnostic program including BB-MRI. Vessel wall CE was graded (grade 0-2) by two experienced readers blinded to clinical data and correlated to the final diagnosis. Four of 12 included patients received a final diagnosis of PACNS. All of them showed moderate (grade 1) to strong (grade 2) vessel wall CE at the sites of stenosis. A moderate (grade 1) vessel wall CE grade was also observed in 6 of the remaining 8 patients in whom alternative diagnoses were made: arteriosclerotic disease (n = 4), intracranial dissection (n = 1), and Moyamoya disease (n = 1). Our pilot study demonstrates that vessel wall CE is a frequent finding in PACNS and its mimics. Larger trials will be necessary to evaluate the utility of BB-MRI in the diagnostic workup of PACNS. Copyright © 2012 by the American Society of Neuroimaging.

Daily Tracking of Glioblastoma Resection Cavity, Cerebral Edema, and Tumor Volume with MRI-Guided Radiation Therapy.

PubMed

Mehta, Shahil; Gajjar, Shefali R; Padgett, Kyle R; Asher, David; Stoyanova, Radka; Ford, John C; Mellon, Eric A

2018-03-19

Radiation therapy (RT) plays a critical role in the treatment of glioblastoma. Studies of brain imaging during RT for glioblastoma have demonstrated changes in the brain during RT. However, frequent or daily utilization of standalone magnetic resonance imaging (MRI) scans during RT have limited feasibility. The recent release of the tri-cobalt-60 MRI-guided RT (MR-IGRT) device (ViewRay MRIdian, Cleveland, OH) allows for daily brain MRI for the RT setup. Daily MRI of three postoperative patients undergoing RT and temozolomide for glioblastoma over a six-week course allowed for the identification of changes to the cavity, edema, and visible tumor on a daily basis. The volumes and dimensions of the resection cavities, edema, and T2-hyperintense tumor were measured. A general trend of daily decreases in cavity measurements was observed in all patients. For the one patient with edema, a trend of daily increases followed by a trend of daily decreases were observed. These results suggest that daily MRI could be used for onboard resimulation and adaptive RT for future fluctuations in the sizes of brain tumors, cavities, or cystic components. This could improve tumor targeting and reduce RT of healthy brain tissue.

Daily Tracking of Glioblastoma Resection Cavity, Cerebral Edema, and Tumor Volume with MRI-Guided Radiation Therapy

PubMed Central

Mehta, Shahil; Gajjar, Shefali R; Padgett, Kyle R; Asher, David; Stoyanova, Radka; Ford, John C

2018-01-01

Radiation therapy (RT) plays a critical role in the treatment of glioblastoma. Studies of brain imaging during RT for glioblastoma have demonstrated changes in the brain during RT. However, frequent or daily utilization of standalone magnetic resonance imaging (MRI) scans during RT have limited feasibility. The recent release of the tri-cobalt-60 MRI-guided RT (MR-IGRT) device (ViewRay MRIdian, Cleveland, OH) allows for daily brain MRI for the RT setup. Daily MRI of three postoperative patients undergoing RT and temozolomide for glioblastoma over a six-week course allowed for the identification of changes to the cavity, edema, and visible tumor on a daily basis. The volumes and dimensions of the resection cavities, edema, and T2-hyperintense tumor were measured. A general trend of daily decreases in cavity measurements was observed in all patients. For the one patient with edema, a trend of daily increases followed by a trend of daily decreases were observed. These results suggest that daily MRI could be used for onboard resimulation and adaptive RT for future fluctuations in the sizes of brain tumors, cavities, or cystic components. This could improve tumor targeting and reduce RT of healthy brain tissue. PMID:29796358

Multimodal Fusion with Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia

PubMed Central

Qi, Shile; Calhoun, Vince D.; van Erp, Theo G. M.; Bustillo, Juan; Damaraju, Eswar; Turner, Jessica A.; Du, Yuhui; Chen, Jiayu; Yu, Qingbao; Mathalon, Daniel H.; Ford, Judith M.; Voyvodic, James; Mueller, Bryon A.; Belger, Aysenil; Ewen, Sarah Mc; Potkin, Steven G.; Preda, Adrian; Jiang, Tianzi

2017-01-01

Multimodal fusion is an effective approach to take advantage of cross-information among multiple imaging data to better understand brain diseases. However, most current fusion approaches are blind, without adopting any prior information. To date, there is increasing interest to uncover the neurocognitive mapping of specific behavioral measurement on enriched brain imaging data; hence, a supervised, goal-directed model that enables a priori information as a reference to guide multimodal data fusion is in need and a natural option. Here we proposed a fusion with reference model, called “multi-site canonical correlation analysis with reference plus joint independent component analysis” (MCCAR+jICA), which can precisely identify co-varying multimodal imaging patterns closely related to reference information, such as cognitive scores. In a 3-way fusion simulation, the proposed method was compared with its alternatives on estimation accuracy of both target component decomposition and modality linkage detection. MCCAR+jICA outperforms others with higher precision. In human imaging data, working memory performance was utilized as a reference to investigate the covarying functional and structural brain patterns among 3 modalities and how they are impaired in schizophrenia. Two independent cohorts (294 and 83 subjects respectively) were used. Interestingly, similar brain maps were identified between the two cohorts, with substantial overlap in the executive control networks in fMRI, salience network in sMRI, and major white matter tracts in dMRI. These regions have been linked with working memory deficits in schizophrenia in multiple reports, while MCCAR+jICA further verified them in a repeatable, joint manner, demonstrating the potential of such results to identify potential neuromarkers for mental disorders. PMID:28708547

Advice Taking from Humans and Machines: An fMRI and Effective Connectivity Study.

PubMed

Goodyear, Kimberly; Parasuraman, Raja; Chernyak, Sergey; Madhavan, Poornima; Deshpande, Gopikrishna; Krueger, Frank

2016-01-01

With new technological advances, advice can come from different sources such as machines or humans, but how individuals respond to such advice and the neural correlates involved need to be better understood. We combined functional MRI and multivariate Granger causality analysis with an X-ray luggage-screening task to investigate the neural basis and corresponding effective connectivity involved with advice utilization from agents framed as experts. Participants were asked to accept or reject good or bad advice from a human or machine agent with low reliability (high false alarm rate). We showed that unreliable advice decreased performance overall and participants interacting with the human agent had a greater depreciation of advice utilization during bad advice compared to the machine agent. These differences in advice utilization can be perceivably due to reevaluation of expectations arising from association of dispositional credibility for each agent. We demonstrated that differences in advice utilization engaged brain regions that may be associated with evaluation of personal characteristics and traits (precuneus, posterior cingulate cortex, temporoparietal junction) and interoception (posterior insula). We found that the right posterior insula and left precuneus were the drivers of the advice utilization network that were reciprocally connected to each other and also projected to all other regions. Our behavioral and neuroimaging results have significant implications for society because of progressions in technology and increased interactions with machines.

Advice Taking from Humans and Machines: An fMRI and Effective Connectivity Study

PubMed Central

Goodyear, Kimberly; Parasuraman, Raja; Chernyak, Sergey; Madhavan, Poornima; Deshpande, Gopikrishna; Krueger, Frank

2016-01-01

With new technological advances, advice can come from different sources such as machines or humans, but how individuals respond to such advice and the neural correlates involved need to be better understood. We combined functional MRI and multivariate Granger causality analysis with an X-ray luggage-screening task to investigate the neural basis and corresponding effective connectivity involved with advice utilization from agents framed as experts. Participants were asked to accept or reject good or bad advice from a human or machine agent with low reliability (high false alarm rate). We showed that unreliable advice decreased performance overall and participants interacting with the human agent had a greater depreciation of advice utilization during bad advice compared to the machine agent. These differences in advice utilization can be perceivably due to reevaluation of expectations arising from association of dispositional credibility for each agent. We demonstrated that differences in advice utilization engaged brain regions that may be associated with evaluation of personal characteristics and traits (precuneus, posterior cingulate cortex, temporoparietal junction) and interoception (posterior insula). We found that the right posterior insula and left precuneus were the drivers of the advice utilization network that were reciprocally connected to each other and also projected to all other regions. Our behavioral and neuroimaging results have significant implications for society because of progressions in technology and increased interactions with machines. PMID:27867351

Short-term memory deficits correlate with hippocampal-thalamic functional connectivity alterations following acute sleep restriction.

PubMed

Chengyang, Li; Daqing, Huang; Jianlin, Qi; Haisheng, Chang; Qingqing, Meng; Jin, Wang; Jiajia, Liu; Enmao, Ye; Yongcong, Shao; Xi, Zhang

2017-08-01

Acute sleep restriction heavily influences cognitive function, affecting executive processes such as attention, response inhibition, and memory. Previous neuroimaging studies have suggested a link between hippocampal activity and short-term memory function. However, the specific contribution of the hippocampus to the decline of short-term memory following sleep restriction has yet to be established. In the current study, we utilized resting-state functional magnetic resonance imaging (fMRI) to examine the association between hippocampal functional connectivity (FC) and the decline of short-term memory following total sleep deprivation (TSD). Twenty healthy adult males aged 20.9 ± 2.3 years (age range, 18-24 years) were enrolled in a within-subject crossover study. Short-term memory and FC were assessed using a Delay-matching short-term memory test and a resting-state fMRI scan before and after TSD. Seed-based correlation analysis was performed using fMRI data for the left and right hippocampus to identify differences in hippocampal FC following TSD. Subjects demonstrated reduced alertness and a decline in short-term memory performance following TSD. Moreover, fMRI analysis identified reduced hippocampal FC with the superior frontal gyrus (SFG), temporal regions, and supplementary motor area. In addition, an increase in FC between the hippocampus and bilateral thalamus was observed, the extent of which correlated with short-term memory performance following TSD. Our findings indicate that the disruption of hippocampal-cortical connectivity is linked to the decline in short-term memory observed after acute sleep restriction. Such results provide further evidence that support the cognitive impairment model of sleep deprivation.

Monitoring Blood-Brain Barrier Integrity Following Amyloid-β Immunotherapy Using Gadolinium-Enhanced MRI in a PDAPP Mouse Model.

PubMed

Blockx, Ines; Einstein, Steve; Guns, Pieter-Jan; Van Audekerke, Johan; Guglielmetti, Caroline; Zago, Wagner; Roose, Dimitri; Verhoye, Marleen; Van der Linden, Annemie; Bard, Frederique

2016-09-06

Amyloid-related imaging abnormalities (ARIA) have been reported with some anti-amyloid-β (Aβ) immunotherapy trials. They are detected with magnetic resonance imaging (MRI) and thought to represent transient accumulation of fluid/edema (ARIA-E) or microhemorrhages (ARIA-H). Although the clinical significance and pathophysiology are unknown, it has been proposed that anti-Aβimmunotherapy may affect blood-brain barrier (BBB) integrity. To examine vascular integrity in aged (12-16 months) PDAPP and wild type mice (WT), we performed a series of longitudinal in vivo MRI studies. Mice were treated on a weekly basis using anti-Aβimmunotherapy (3D6) and follow up was done longitudinally from 1-12 weeks after treatment. BBB-integrity was assessed using both visual assessment of T1-weighted scans and repeated T1 mapping in combination with gadolinium (Gd-DOTA). A subset of 3D6 treated PDAPP mice displayed numerous BBB disruptions, whereas WT and saline-treated PDAPP mice showed intact BBB integrity under the conditions tested. In addition, the contrast induced decrease in T1 value was observed in the meningeal and midline area. BBB disruption events occurred early during treatment (between 1 and 5 weeks), were transient, and resolved quickly. Finally, BBB-leakages associated with microhemorrhages were confirmed by Perls'Prussian blue histopathological analysis. Our preclinical findings support the hypothesis that 3D6 leads to transient leakage from amyloid-positive vessels. The current study has provided valuable insights on the time course of vascular alterations during immunization treatment and supports further research in relation to the nature of ARIA and the utility of in vivo repeated T1 MRI as a translational tool.

A Heavy Tailed Expectation Maximization Hidden Markov Random Field Model with Applications to Segmentation of MRI

PubMed Central

Castillo-Barnes, Diego; Peis, Ignacio; Martínez-Murcia, Francisco J.; Segovia, Fermín; Illán, Ignacio A.; Górriz, Juan M.; Ramírez, Javier; Salas-Gonzalez, Diego

2017-01-01

A wide range of segmentation approaches assumes that intensity histograms extracted from magnetic resonance images (MRI) have a distribution for each brain tissue that can be modeled by a Gaussian distribution or a mixture of them. Nevertheless, intensity histograms of White Matter and Gray Matter are not symmetric and they exhibit heavy tails. In this work, we present a hidden Markov random field model with expectation maximization (EM-HMRF) modeling the components using the α-stable distribution. The proposed model is a generalization of the widely used EM-HMRF algorithm with Gaussian distributions. We test the α-stable EM-HMRF model in synthetic data and brain MRI data. The proposed methodology presents two main advantages: Firstly, it is more robust to outliers. Secondly, we obtain similar results than using Gaussian when the Gaussian assumption holds. This approach is able to model the spatial dependence between neighboring voxels in tomographic brain MRI. PMID:29209194

Simultaneous quantification of hepatic MRI-PDFF and R2* in a rabbit model with nonalcoholic fatty liver disease.

PubMed

Wang, Xiaomin; Zhang, Xiaojing; Ma, Lin; Li, Shengli

2018-06-20

Quantification of hepatic fat and iron content is important for early detection and monitoring of nonalcoholic fatty liver disease (NAFLD) patients. This study evaluated quantification efficiency of hepatic proton density fat fraction (PDFF) by MRI using NAFLD rabbits. R2* was also measured to investigate whether it correlates with fat levels in NAFLD. NAFLD rabbit model was successfully established by high fat and cholesterol diet. Rabbits underwent MRI examination for fat and iron analyses, compared with liver histological findings. MR examinations were performed on a 3.0T MR system using multi-echo 3D gradient recalled echo (GRE) sequence. MRI-PDFF showed significant differences between different steatosis grades with medians of 3.72% (normal), 5.43% (mild), 9.11% (moderate) and 11.17% (severe), whereas this was not observed in R2*. Close correlation between MRI-PDFF and histological steatosis was observed (r=0.78, P=0.000). Hepatic iron deposit was not found in any rabbits. There was no correlation between R2* and either liver MRI-PDFF or histological steatosis. MR measuring MRI-PDFF and R2* simultaneously provides promising quantification of steatosis and iron. Rabbit NAFLD model confirmed accuracy of MRI-PDFF for liver fat quantification. R2* measurement and relationship between fat and iron of NAFLD liver need further experimental investigation.

A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI.

PubMed

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2015-10-01

In this paper, we propose a novel method for modelling functional dynamics in resting-state fMRI (rs-fMRI) for Mild Cognitive Impairment (MCI) identification. Specifically, we devise a hybrid architecture by combining Deep Auto-Encoder (DAE) and Hidden Markov Model (HMM). The roles of DAE and HMM are, respectively, to discover hierarchical non-linear relations among features, by which we transform the original features into a lower dimension space, and to model dynamic characteristics inherent in rs-fMRI, i.e. , internal state changes. By building a generative model with HMMs for each class individually, we estimate the data likelihood of a test subject as MCI or normal healthy control, based on which we identify the clinical label. In our experiments, we achieved the maximal accuracy of 81.08% with the proposed method, outperforming state-of-the-art methods in the literature.

A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI

PubMed Central

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2015-01-01

In this paper, we propose a novel method for modelling functional dynamics in resting-state fMRI (rs-fMRI) for Mild Cognitive Impairment (MCI) identification. Specifically, we devise a hybrid architecture by combining Deep Auto-Encoder (DAE) and Hidden Markov Model (HMM). The roles of DAE and HMM are, respectively, to discover hierarchical non-linear relations among features, by which we transform the original features into a lower dimension space, and to model dynamic characteristics inherent in rs-fMRI, i.e., internal state changes. By building a generative model with HMMs for each class individually, we estimate the data likelihood of a test subject as MCI or normal healthy control, based on which we identify the clinical label. In our experiments, we achieved the maximal accuracy of 81.08% with the proposed method, outperforming state-of-the-art methods in the literature. PMID:27054199

Regression and statistical shape model based substitute CT generation for MRI alone external beam radiation therapy from standard clinical MRI sequences.

PubMed

Ghose, Soumya; Greer, Peter B; Sun, Jidi; Pichler, Peter; Rivest-Henault, David; Mitra, Jhimli; Richardson, Haylea; Wratten, Chris; Martin, Jarad; Arm, Jameen; Best, Leah; Dowling, Jason A

2017-10-27

In MR only radiation therapy planning, generation of the tissue specific HU map directly from the MRI would eliminate the need of CT image acquisition and may improve radiation therapy planning. The aim of this work is to generate and validate substitute CT (sCT) scans generated from standard T2 weighted MR pelvic scans in prostate radiation therapy dose planning. A Siemens Skyra 3T MRI scanner with laser bridge, flat couch and pelvic coil mounts was used to scan 39 patients scheduled for external beam radiation therapy for localized prostate cancer. For sCT generation a whole pelvis MRI (1.6 mm 3D isotropic T2w SPACE sequence) was acquired. Patients received a routine planning CT scan. Co-registered whole pelvis CT and T2w MRI pairs were used as training images. Advanced tissue specific non-linear regression models to predict HU for the fat, muscle, bladder and air were created from co-registered CT-MRI image pairs. On a test case T2w MRI, the bones and bladder were automatically segmented using a novel statistical shape and appearance model, while other soft tissues were separated using an Expectation-Maximization based clustering model. The CT bone in the training database that was most 'similar' to the segmented bone was then transformed with deformable registration to create the sCT component of the test case T2w MRI bone tissue. Predictions for the bone, air and soft tissue from the separate regression models were successively combined to generate a whole pelvis sCT. The change in monitor units between the sCT-based plans relative to the gold standard CT plan for the same IMRT dose plan was found to be [Formula: see text] (mean  ±  standard deviation) for 39 patients. The 3D Gamma pass rate was [Formula: see text] (2 mm/2%). The novel hybrid model is computationally efficient, generating an sCT in 20 min from standard T2w images for prostate cancer radiation therapy dose planning and DRR generation.

Regression and statistical shape model based substitute CT generation for MRI alone external beam radiation therapy from standard clinical MRI sequences

NASA Astrophysics Data System (ADS)

Ghose, Soumya; Greer, Peter B.; Sun, Jidi; Pichler, Peter; Rivest-Henault, David; Mitra, Jhimli; Richardson, Haylea; Wratten, Chris; Martin, Jarad; Arm, Jameen; Best, Leah; Dowling, Jason A.

2017-11-01

In MR only radiation therapy planning, generation of the tissue specific HU map directly from the MRI would eliminate the need of CT image acquisition and may improve radiation therapy planning. The aim of this work is to generate and validate substitute CT (sCT) scans generated from standard T2 weighted MR pelvic scans in prostate radiation therapy dose planning. A Siemens Skyra 3T MRI scanner with laser bridge, flat couch and pelvic coil mounts was used to scan 39 patients scheduled for external beam radiation therapy for localized prostate cancer. For sCT generation a whole pelvis MRI (1.6 mm 3D isotropic T2w SPACE sequence) was acquired. Patients received a routine planning CT scan. Co-registered whole pelvis CT and T2w MRI pairs were used as training images. Advanced tissue specific non-linear regression models to predict HU for the fat, muscle, bladder and air were created from co-registered CT-MRI image pairs. On a test case T2w MRI, the bones and bladder were automatically segmented using a novel statistical shape and appearance model, while other soft tissues were separated using an Expectation-Maximization based clustering model. The CT bone in the training database that was most ‘similar’ to the segmented bone was then transformed with deformable registration to create the sCT component of the test case T2w MRI bone tissue. Predictions for the bone, air and soft tissue from the separate regression models were successively combined to generate a whole pelvis sCT. The change in monitor units between the sCT-based plans relative to the gold standard CT plan for the same IMRT dose plan was found to be 0.3%+/-0.9% (mean  ±  standard deviation) for 39 patients. The 3D Gamma pass rate was 99.8+/-0.00 (2 mm/2%). The novel hybrid model is computationally efficient, generating an sCT in 20 min from standard T2w images for prostate cancer radiation therapy dose planning and DRR generation.

3D polymer gel dosimetry using a 3D (DESS) and a 2D MultiEcho SE (MESE) sequence

NASA Astrophysics Data System (ADS)

Maris, Thomas G.; Pappas, Evangelos; Karolemeas, Kostantinos; Papadakis, Antonios E.; Zacharopoulou, Fotini; Papanikolaou, Nickolas; Gourtsoyiannis, Nicholas

2006-12-01

The utilization of 3D techniques in Magnetic Resonance Imaging data aquisition and post-processing analysis is a prerequisite especially when modern radiotherapy techniques (conformal RT, IMRT, Stereotactic RT) are to be used. The aim of this work is to compare a 3D Double Echo Steady State (DESS) and a 2D Multiple Echo Spin Echo (MESE) sequence in 3D MRI radiation dosimetry using two different MRI scanners and utilising N-VInylPyrrolidone (VIPAR) based polymer gels.

Reproducibility of Brain Morphometry from Short-Term Repeat Clinical MRI Examinations: A Retrospective Study

PubMed Central

Liu, Hon-Man; Chen, Shan-Kai; Chen, Ya-Fang; Lee, Chung-Wei; Yeh, Lee-Ren

2016-01-01

Purpose To assess the inter session reproducibility of automatic segmented MRI-derived measures by FreeSurfer in a group of subjects with normal-appearing MR images. Materials and Methods After retrospectively reviewing a brain MRI database from our institute consisting of 14,758 adults, those subjects who had repeat scans and had no history of neurodegenerative disorders were selected for morphometry analysis using FreeSurfer. A total of 34 subjects were grouped by MRI scanner model. After automatic segmentation using FreeSurfer, label-wise comparison (involving area, thickness, and volume) was performed on all segmented results. An intraclass correlation coefficient was used to estimate the agreement between sessions. Wilcoxon signed rank test was used to assess the population mean rank differences across sessions. Mean-difference analysis was used to evaluate the difference intervals across scanners. Absolute percent difference was used to estimate the reproducibility errors across the MRI models. Kruskal-Wallis test was used to determine the across-scanner effect. Results The agreement in segmentation results for area, volume, and thickness measurements of all segmented anatomical labels was generally higher in Signa Excite and Verio models when compared with Sonata and TrioTim models. There were significant rank differences found across sessions in some labels of different measures. Smaller difference intervals in global volume measurements were noted on images acquired by Signa Excite and Verio models. For some brain regions, significant MRI model effects were observed on certain segmentation results. Conclusions Short-term scan-rescan reliability of automatic brain MRI morphometry is feasible in the clinical setting. However, since repeatability of software performance is contingent on the reproducibility of the scanner performance, the scanner performance must be calibrated before conducting such studies or before using such software for retrospective reviewing. PMID:26812647

Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2.

PubMed

Jack, Clifford R; Barnes, Josephine; Bernstein, Matt A; Borowski, Bret J; Brewer, James; Clegg, Shona; Dale, Anders M; Carmichael, Owen; Ching, Christopher; DeCarli, Charles; Desikan, Rahul S; Fennema-Notestine, Christine; Fjell, Anders M; Fletcher, Evan; Fox, Nick C; Gunter, Jeff; Gutman, Boris A; Holland, Dominic; Hua, Xue; Insel, Philip; Kantarci, Kejal; Killiany, Ron J; Krueger, Gunnar; Leung, Kelvin K; Mackin, Scott; Maillard, Pauline; Malone, Ian B; Mattsson, Niklas; McEvoy, Linda; Modat, Marc; Mueller, Susanne; Nosheny, Rachel; Ourselin, Sebastien; Schuff, Norbert; Senjem, Matthew L; Simonson, Alix; Thompson, Paul M; Rettmann, Dan; Vemuri, Prashanthi; Walhovd, Kristine; Zhao, Yansong; Zuk, Samantha; Weiner, Michael

2015-07-01

Alzheimer's Disease Neuroimaging Initiative (ADNI) is now in its 10th year. The primary objective of the magnetic resonance imaging (MRI) core of ADNI has been to improve methods for clinical trials in Alzheimer's disease (AD) and related disorders. We review the contributions of the MRI core from present and past cycles of ADNI (ADNI-1, -Grand Opportunity and -2). We also review plans for the future-ADNI-3. Contributions of the MRI core include creating standardized acquisition protocols and quality control methods; examining the effect of technical features of image acquisition and analysis on outcome metrics; deriving sample size estimates for future trials based on those outcomes; and piloting the potential utility of MR perfusion, diffusion, and functional connectivity measures in multicenter clinical trials. Over the past decade the MRI core of ADNI has fulfilled its mandate of improving methods for clinical trials in AD and will continue to do so in the future. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Molecular fMRI of Serotonin Transport.

PubMed

Hai, Aviad; Cai, Lili X; Lee, Taekwan; Lelyveld, Victor S; Jasanoff, Alan

2016-11-23

Reuptake of neurotransmitters from the brain interstitium shapes chemical signaling processes and is disrupted in several pathologies. Serotonin reuptake in particular is important for mood regulation and is inhibited by first-line drugs for treatment of depression. Here we introduce a molecular-level fMRI technique for micron-scale mapping of serotonin transport in live animals. Intracranial injection of an MRI-detectable serotonin sensor complexed with serotonin, together with serial imaging and compartmental analysis, permits neurotransmitter transport to be quantified as serotonin dissociates from the probe. Application of this strategy to much of the striatum and surrounding areas reveals widespread nonsaturating serotonin removal with maximal rates in the lateral septum. The serotonin reuptake inhibitor fluoxetine selectively suppresses serotonin removal in septal subregions, whereas both fluoxetine and a dopamine transporter blocker depress reuptake in striatum. These results highlight promiscuous pharmacological influences on the serotonergic system and demonstrate the utility of molecular fMRI for characterization of neurochemical dynamics. Copyright © 2016 Elsevier Inc. All rights reserved.

Biological and Health Effects of Electromagnetic Fields Related to the Operation of MRI/TMS

NASA Astrophysics Data System (ADS)

Shigemitsu, Tsukasa; Ueno, Shoogo

This paper reviews issues of biological effects and safety aspects of the electromagnetic fields related to both Magnetic Resonance Imaging (MRI) and Transcranial Magnetic Stimulation (TMS) as a diagnostic technique. The noninvasive character of these diagnostic techniques is based on the utilization of the electromagnetic fields such as the static magnetic field, time-varying magnetic field, and radiofrequency electromagnetic field. Following the short view of the history and the principle of these noninvasive techniques, we review the biological effects of the electromagnetic fields, the health effects and safety issues related to MRI/TMS environments. Through a discussion of biological and health effects, it shows briefly guidelines which provide a consideration in human risk for both patients and medical staff. Finally, safety issues related to MRI/TMS are discussed with the highlighting of the guideline such as the International Commission on NonIonizing Radiation Protection (ICNIRP) and EMF Directive (Directve2013/35/EU) of European Union.

Quantitative Imaging Biomarkers of NAFLD

PubMed Central

Kinner, Sonja; Reeder, Scott B.

2016-01-01

Conventional imaging modalities, including ultrasonography (US), computed tomography (CT), and magnetic resonance (MR), play an important role in the diagnosis and management of patients with nonalcoholic fatty liver disease (NAFLD) by allowing noninvasive diagnosis of hepatic steatosis. However, conventional imaging modalities are limited as biomarkers of NAFLD for various reasons. Multi-parametric quantitative MRI techniques overcome many of the shortcomings of conventional imaging and allow comprehensive and objective evaluation of NAFLD. MRI can provide unconfounded biomarkers of hepatic fat, iron, and fibrosis in a single examination—a virtual biopsy has become a clinical reality. In this article, we will review the utility and limitation of conventional US, CT, and MR imaging for the diagnosis NAFLD. Recent advances in imaging biomarkers of NAFLD are also discussed with an emphasis in multi-parametric quantitative MRI. PMID:26848588

[Joint correction for motion artifacts and off-resonance artifacts in multi-shot diffusion magnetic resonance imaging].

PubMed

Wu, Wenchuan; Fang, Sheng; Guo, Hua

2014-06-01

Aiming at motion artifacts and off-resonance artifacts in multi-shot diffusion magnetic resonance imaging (MRI), we proposed a joint correction method in this paper to correct the two kinds of artifacts simultaneously without additional acquisition of navigation data and field map. We utilized the proposed method using multi-shot variable density spiral sequence to acquire MRI data and used auto-focusing technique for image deblurring. We also used direct method or iterative method to correct motion induced phase errors in the process of deblurring. In vivo MRI experiments demonstrated that the proposed method could effectively suppress motion artifacts and off-resonance artifacts and achieve images with fine structures. In addition, the scan time was not increased in applying the proposed method.

The representation of order information in auditory-verbal short-term memory.

PubMed

Kalm, Kristjan; Norris, Dennis

2014-05-14

Here we investigate how order information is represented in auditory-verbal short-term memory (STM). We used fMRI and a serial recall task to dissociate neural activity patterns representing the phonological properties of the items stored in STM from the patterns representing their order. For this purpose, we analyzed fMRI activity patterns elicited by different item sets and different orderings of those items. These fMRI activity patterns were compared with the predictions made by positional and chaining models of serial order. The positional models encode associations between items and their positions in a sequence, whereas the chaining models encode associations between successive items and retain no position information. We show that a set of brain areas in the postero-dorsal stream of auditory processing store associations between items and order as predicted by a positional model. The chaining model of order representation generates a different pattern similarity prediction, which was shown to be inconsistent with the fMRI data. Our results thus favor a neural model of order representation that stores item codes, position codes, and the mapping between them. This study provides the first fMRI evidence for a specific model of order representation in the human brain. Copyright © 2014 the authors 0270-6474/14/346879-08$15.00/0.

Passive Ventricular Mechanics Modelling Using MRI of Structure and Function

PubMed Central

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

2009-01-01

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

A Combined Pharmacokinetic and Radiologic Assessment of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Predicts Response to Chemoradiation in Locally Advanced Cervical Cancer

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

Semple, Scott; Harry, Vanessa N. MRCOG.; Parkin, David E.

2009-10-01

Purpose: To investigate the combination of pharmacokinetic and radiologic assessment of dynamic contrast-enhanced magnetic resonance imaging (MRI) as an early response indicator in women receiving chemoradiation for advanced cervical cancer. Methods and Materials: Twenty women with locally advanced cervical cancer were included in a prospective cohort study. Dynamic contrast-enhanced MRI was carried out before chemoradiation, after 2 weeks of therapy, and at the conclusion of therapy using a 1.5-T MRI scanner. Radiologic assessment of uptake parameters was obtained from resultant intensity curves. Pharmacokinetic analysis using a multicompartment model was also performed. General linear modeling was used to combine radiologic andmore » pharmacokinetic parameters and correlated with eventual response as determined by change in MRI tumor size and conventional clinical response. A subgroup of 11 women underwent repeat pretherapy MRI to test pharmacokinetic reproducibility. Results: Pretherapy radiologic parameters and pharmacokinetic K{sup trans} correlated with response (p < 0.01). General linear modeling demonstrated that a combination of radiologic and pharmacokinetic assessments before therapy was able to predict more than 88% of variance of response. Reproducibility of pharmacokinetic modeling was confirmed. Conclusions: A combination of radiologic assessment with pharmacokinetic modeling applied to dynamic MRI before the start of chemoradiation improves the predictive power of either by more than 20%. The potential improvements in therapy response prediction using this type of combined analysis of dynamic contrast-enhanced MRI may aid in the development of more individualized, effective therapy regimens for this patient group.« less

Adaptive cyclic physiologic noise modeling and correction in functional MRI.

PubMed

Beall, Erik B

2010-03-30

Physiologic noise in BOLD-weighted MRI data is known to be a significant source of the variance, reducing the statistical power and specificity in fMRI and functional connectivity analyses. We show a dramatic improvement on current noise correction methods in both fMRI and fcMRI data that avoids overfitting. The traditional noise model is a Fourier series expansion superimposed on the periodicity of parallel measured breathing and cardiac cycles. Correction using this model results in removal of variance matching the periodicity of the physiologic cycles. Using this framework allows easy modeling of noise. However, using a large number of regressors comes at the cost of removing variance unrelated to physiologic noise, such as variance due to the signal of functional interest (overfitting the data). It is our hypothesis that there are a small variety of fits that describe all of the significantly coupled physiologic noise. If this is true, we can replace a large number of regressors used in the model with a smaller number of the fitted regressors and thereby account for the noise sources with a smaller reduction in variance of interest. We describe these extensions and demonstrate that we can preserve variance in the data unrelated to physiologic noise while removing physiologic noise equivalently, resulting in data with a higher effective SNR than with current corrections techniques. Our results demonstrate a significant improvement in the sensitivity of fMRI (up to a 17% increase in activation volume for fMRI compared with higher order traditional noise correction) and functional connectivity analyses. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Passive ventricular mechanics modelling using MRI of structure and function.

PubMed

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

2008-01-01

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

Patch-based generation of a pseudo CT from conventional MRI sequences for MRI-only radiotherapy of the brain

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

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

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

Enhanced Thalamic Functional Connectivity with No fMRI Responses to Affected Forelimb Stimulation in Stroke-Recovered Rats.

PubMed

Shim, Woo H; Suh, Ji-Yeon; Kim, Jeong K; Jeong, Jaeseung; Kim, Young R

2016-01-01

Neurological recovery after stroke has been extensively investigated to provide better understanding of neurobiological mechanism, therapy, and patient management. Recent advances in neuroimaging techniques, particularly functional MRI (fMRI), have widely contributed to unravel the relationship between the altered neural function and stroke-affected brain areas. As results of previous investigations, the plastic reorganization and/or gradual restoration of the hemodynamic fMRI responses to neural stimuli have been suggested as relevant mechanisms underlying the stroke recovery process. However, divergent study results and modality-dependent outcomes have clouded the proper interpretation of variable fMRI signals. Here, we performed both evoked and resting state fMRI (rs-fMRI) to clarify the link between the fMRI phenotypes and post-stroke functional recovery. The experiments were designed to examine the altered neural activity within the contra-lesional hemisphere and other undamaged brain regions using rat models with large unilateral stroke, which despite the severe injury, exhibited nearly full recovery at ∼6 months after stroke. Surprisingly, both blood oxygenation level-dependent and blood volume-weighted (CBVw) fMRI activities elicited by electrical stimulation of the stroke-affected forelimb were completely absent, failing to reveal the neural origin of the behavioral recovery. In contrast, the functional connectivity maps showed highly robust rs-fMRI activity concentrated in the contra-lesional ventromedial nucleus of thalamus (VM). The negative finding in the stimuli-induced fMRI study using the popular rat middle cerebral artery model denotes weak association between the fMRI hemodynamic responses and neurological improvement. The results strongly caution the indiscreet interpretation of stroke-affected fMRI signals and demonstrate rs-fMRI as a complementary tool for efficiently characterizing stroke recovery.

Improving fMRI reliability in presurgical mapping for brain tumours.

PubMed

Stevens, M Tynan R; Clarke, David B; Stroink, Gerhard; Beyea, Steven D; D'Arcy, Ryan Cn

2016-03-01

Functional MRI (fMRI) is becoming increasingly integrated into clinical practice for presurgical mapping. Current efforts are focused on validating data quality, with reliability being a major factor. In this paper, we demonstrate the utility of a recently developed approach that uses receiver operating characteristic-reliability (ROC-r) to: (1) identify reliable versus unreliable data sets; (2) automatically select processing options to enhance data quality; and (3) automatically select individualised thresholds for activation maps. Presurgical fMRI was conducted in 16 patients undergoing surgical treatment for brain tumours. Within-session test-retest fMRI was conducted, and ROC-reliability of the patient group was compared to a previous healthy control cohort. Individually optimised preprocessing pipelines were determined to improve reliability. Spatial correspondence was assessed by comparing the fMRI results to intraoperative cortical stimulation mapping, in terms of the distance to the nearest active fMRI voxel. The average ROC-r reliability for the patients was 0.58±0.03, as compared to 0.72±0.02 in healthy controls. For the patient group, this increased significantly to 0.65±0.02 by adopting optimised preprocessing pipelines. Co-localisation of the fMRI maps with cortical stimulation was significantly better for more reliable versus less reliable data sets (8.3±0.9 vs 29±3 mm, respectively). We demonstrated ROC-r analysis for identifying reliable fMRI data sets, choosing optimal postprocessing pipelines, and selecting patient-specific thresholds. Data sets with higher reliability also showed closer spatial correspondence to cortical stimulation. ROC-r can thus identify poor fMRI data at time of scanning, allowing for repeat scans when necessary. ROC-r analysis provides optimised and automated fMRI processing for improved presurgical mapping. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Understanding Patient Preference in Female Pelvic Imaging: Transvaginal Ultrasound and MRI.

PubMed

Sakala, Michelle D; Carlos, Ruth C; Mendiratta-Lala, Mishal; Quint, Elisabeth H; Maturen, Katherine E

2018-04-01

Women with pelvic pain or abnormal uterine bleeding may undergo diagnostic imaging. This study evaluates patient experience in transvaginal ultrasound (TVUS) and magnetic resonance imaging (MRI) and explores correlations between preference and symptom severity. Institutional review board approval was obtained for this Health Insurance Portability and Accountability Act-compliant prospective study. Fifty premenopausal women with pelvic symptoms evaluated by recent TVUS and MRI and without history of gynecologic cancer or hysterectomy were included. A phone questionnaire used validated survey instruments including Uterine Fibroid Symptoms Quality of Life index, Testing Morbidities Index, and Wait Trade Off for TVUS and MRI examinations. Using Wait Trade Off, patients preferred TVUS over MRI (3.58 vs 2.80 weeks, 95% confidence interval [CI] -1.63, 0.12; P = .08). Summary test utility of Testing Morbidities Index for MRI was worse than for TVUS (81.64 vs 87.42, 95%CI 0.41, 11.15; P = .03). Patients reported greater embarrassment during TVUS than during MRI (P <.0001), but greater fear and anxiety both before (P <.0001) and during (P <.001) MRI, and greater mental (P = .02) and physical (P = .02) problems after MRI versus TVUS. Subscale correlations showed physically inactive women rated TVUS more negatively (R = -0.32, P = .03), whereas women with more severe symptoms of loss of control of health (R = -0.28, P = .04) and sexual dysfunction (R = -0.30, P = .03) rated MRI more negatively. Women with pelvic symptoms had a slight but significant preference for TVUS over MRI. Identifying specific distressing aspects of each test and patient factors contributing to negative perceptions can direct improvement in both test environment and patient preparation. Improved patient experience may increase imaging value. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

The utility of conductive plastic electrodes in prolonged ICU EEG monitoring.

PubMed

Das, Rohit R; Lucey, Brendan P; Chou, Sherry H-Y; Espinosa, Patricio S; Zamani, Amir A; Dworetzky, Barbara A; Bromfield, Edward B; Lee, Jong Woo

2009-01-01

We investigated the feasibility and utilization of conductive plastic electrodes (CPEs) in patients undergoing continuous video-electroencephalographic (EEG) monitoring in the intensive care unit (ICU), and assessed the quality of brain magnetic resonance imaging (MRI) and computed tomography (CT) images obtained during this period. A total of 54 patients were monitored. Seizures were recorded in 16 patients. Twenty-five patients had neuroimaging performed with electrodes in place; 15 MRI and 23 CT scans were performed. All patients had excellent quality anatomical images without clinically significant artifacts, and without any signs or symptoms that raised safety concerns. Recording quality of the EEG was indistinguishable to that achieved with standard gold electrodes. The use of CPEs allowed for uninterrupted EEG recording of patients who required urgent neuroimaging, and decreased the amount of time spent by the technologists required to remove and reattach leads.

fMRI Validation of fNIRS Measurements During a Naturalistic Task

PubMed Central

Noah, J. Adam; Ono, Yumie; Nomoto, Yasunori; Shimada, Sotaro; Tachibana, Atsumichi; Zhang, Xian; Bronner, Shaw; Hirsch, Joy

2015-01-01

We present a method to compare brain activity recorded with near-infrared spectroscopy (fNIRS) in a dance video game task to that recorded in a reduced version of the task using fMRI (functional magnetic resonance imaging). Recently, it has been shown that fNIRS can accurately record functional brain activities equivalent to those concurrently recorded with functional magnetic resonance imaging for classic psychophysical tasks and simple finger tapping paradigms. However, an often quoted benefit of fNIRS is that the technique allows for studying neural mechanisms of complex, naturalistic behaviors that are not possible using the constrained environment of fMRI. Our goal was to extend the findings of previous studies that have shown high correlation between concurrently recorded fNIRS and fMRI signals to compare neural recordings obtained in fMRI procedures to those separately obtained in naturalistic fNIRS experiments. Specifically, we developed a modified version of the dance video game Dance Dance Revolution (DDR) to be compatible with both fMRI and fNIRS imaging procedures. In this methodology we explain the modifications to the software and hardware for compatibility with each technique as well as the scanning and calibration procedures used to obtain representative results. The results of the study show a task-related increase in oxyhemoglobin in both modalities and demonstrate that it is possible to replicate the findings of fMRI using fNIRS in a naturalistic task. This technique represents a methodology to compare fMRI imaging paradigms which utilize a reduced-world environment to fNIRS in closer approximation to naturalistic, full-body activities and behaviors. Further development of this technique may apply to neurodegenerative diseases, such as Parkinson’s disease, late states of dementia, or those with magnetic susceptibility which are contraindicated for fMRI scanning. PMID:26132365

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

Kowalchik, Kristin V.; Vallow, Laura A., E-mail: vallow.laura@mayo.edu; McDonough, Michelle

Purpose: To study the utility of preoperative breast MRI for partial breast irradiation (PBI) patient selection, using multivariable analysis of significant risk factors to create a classification rule. Methods and Materials: Between 2002 and 2009, 712 women with newly diagnosed breast cancer underwent preoperative bilateral breast MRI at Mayo Clinic Florida. Of this cohort, 566 were retrospectively deemed eligible for PBI according to the National Surgical Adjuvant Breast and Bowel Project Protocol B-39 inclusion criteria using physical examination, mammogram, and/or ultrasound. Magnetic resonance images were then reviewed to determine their impact on patient eligibility. The patient and tumor characteristics weremore » evaluated to determine risk factors for altered PBI eligibility after MRI and to create a classification rule. Results: Of the 566 patients initially eligible for PBI, 141 (25%) were found ineligible because of pathologically proven MRI findings. Magnetic resonance imaging detected additional ipsilateral breast cancer in 118 (21%). Of these, 62 (11%) had more extensive disease than originally noted before MRI, and 64 (11%) had multicentric disease. Contralateral breast cancer was detected in 28 (5%). Four characteristics were found to be significantly associated with PBI ineligibility after MRI on multivariable analysis: premenopausal status (P=.021), detection by palpation (P<.001), first-degree relative with a history of breast cancer (P=.033), and lobular histology (P=.002). Risk factors were assigned a score of 0-2. The risk of altered PBI eligibility from MRI based on number of risk factors was 0:18%; 1:22%; 2:42%; 3:65%. Conclusions: Preoperative bilateral breast MRI altered the PBI recommendations for 25% of women. Women who may undergo PBI should be considered for breast MRI, especially those with lobular histology or with 2 or more of the following risk factors: premenopausal, detection by palpation, and first-degree relative with a history of breast cancer.« less