O'Connell, Caitlin; Ho, Leon C; Murphy, Matthew C; Conner, Ian P; Wollstein, Gadi; Cham, Rakie; Chan, Kevin C
2016-11-09
Human visual performance has been observed to show superiority in localized regions of the visual field across many classes of stimuli. However, the underlying neural mechanisms remain unclear. This study aims to determine whether the visual information processing in the human brain is dependent on the location of stimuli in the visual field and the corresponding neuroarchitecture using blood-oxygenation-level-dependent functional MRI (fMRI) and diffusion kurtosis MRI, respectively, in 15 healthy individuals at 3 T. In fMRI, visual stimulation to the lower hemifield showed stronger brain responses and larger brain activation volumes than the upper hemifield, indicative of the differential sensitivity of the human brain across the visual field. In diffusion kurtosis MRI, the brain regions mapping to the lower visual field showed higher mean kurtosis, but not fractional anisotropy or mean diffusivity compared with the upper visual field. These results suggested the different distributions of microstructural organization across visual field brain representations. There was also a strong positive relationship between diffusion kurtosis and fMRI responses in the lower field brain representations. In summary, this study suggested the structural and functional brain involvements in the asymmetry of visual field responses in humans, and is important to the neurophysiological and psychological understanding of human visual information processing.
Diffusion MRI at 25: Exploring brain tissue structure and function
Bihan, Denis Le; Johansen-Berg, Heidi
2013-01-01
Diffusion MRI (or dMRI) came into existence in the mid-1980s. During the last 25 years, diffusion MRI has been extraordinarily successful (with more than 300,000 entries on Google Scholar for diffusion MRI). Its main clinical domain of application has been neurological disorders, especially for the management of patients with acute stroke. It is also rapidly becoming a standard for white matter disorders, as diffusion tensor imaging (DTI) can reveal abnormalities in white matter fiber structure and provide outstanding maps of brain connectivity. The ability to visualize anatomical connections between different parts of the brain, non-invasively and on an individual basis, has emerged as a major breakthrough for neurosciences. The driving force of dMRI is to monitor microscopic, natural displacements of water molecules that occur in brain tissues as part of the physical diffusion process. Water molecules are thus used as a probe that can reveal microscopic details about tissue architecture, either normal or in a diseased state. PMID:22120012
PANDA: a pipeline toolbox for analyzing brain diffusion images.
Cui, Zaixu; Zhong, Suyu; Xu, Pengfei; He, Yong; Gong, Gaolang
2013-01-01
Diffusion magnetic resonance imaging (dMRI) is widely used in both scientific research and clinical practice in in-vivo studies of the human brain. While a number of post-processing packages have been developed, fully automated processing of dMRI datasets remains challenging. Here, we developed a MATLAB toolbox named "Pipeline for Analyzing braiN Diffusion imAges" (PANDA) for fully automated processing of brain diffusion images. The processing modules of a few established packages, including FMRIB Software Library (FSL), Pipeline System for Octave and Matlab (PSOM), Diffusion Toolkit and MRIcron, were employed in PANDA. Using any number of raw dMRI datasets from different subjects, in either DICOM or NIfTI format, PANDA can automatically perform a series of steps to process DICOM/NIfTI to diffusion metrics [e.g., fractional anisotropy (FA) and mean diffusivity (MD)] that are ready for statistical analysis at the voxel-level, the atlas-level and the Tract-Based Spatial Statistics (TBSS)-level and can finish the construction of anatomical brain networks for all subjects. In particular, PANDA can process different subjects in parallel, using multiple cores either in a single computer or in a distributed computing environment, thus greatly reducing the time cost when dealing with a large number of datasets. In addition, PANDA has a friendly graphical user interface (GUI), allowing the user to be interactive and to adjust the input/output settings, as well as the processing parameters. As an open-source package, PANDA is freely available at http://www.nitrc.org/projects/panda/. This novel toolbox is expected to substantially simplify the image processing of dMRI datasets and facilitate human structural connectome studies.
PANDA: a pipeline toolbox for analyzing brain diffusion images
Cui, Zaixu; Zhong, Suyu; Xu, Pengfei; He, Yong; Gong, Gaolang
2013-01-01
Diffusion magnetic resonance imaging (dMRI) is widely used in both scientific research and clinical practice in in-vivo studies of the human brain. While a number of post-processing packages have been developed, fully automated processing of dMRI datasets remains challenging. Here, we developed a MATLAB toolbox named “Pipeline for Analyzing braiN Diffusion imAges” (PANDA) for fully automated processing of brain diffusion images. The processing modules of a few established packages, including FMRIB Software Library (FSL), Pipeline System for Octave and Matlab (PSOM), Diffusion Toolkit and MRIcron, were employed in PANDA. Using any number of raw dMRI datasets from different subjects, in either DICOM or NIfTI format, PANDA can automatically perform a series of steps to process DICOM/NIfTI to diffusion metrics [e.g., fractional anisotropy (FA) and mean diffusivity (MD)] that are ready for statistical analysis at the voxel-level, the atlas-level and the Tract-Based Spatial Statistics (TBSS)-level and can finish the construction of anatomical brain networks for all subjects. In particular, PANDA can process different subjects in parallel, using multiple cores either in a single computer or in a distributed computing environment, thus greatly reducing the time cost when dealing with a large number of datasets. In addition, PANDA has a friendly graphical user interface (GUI), allowing the user to be interactive and to adjust the input/output settings, as well as the processing parameters. As an open-source package, PANDA is freely available at http://www.nitrc.org/projects/panda/. This novel toolbox is expected to substantially simplify the image processing of dMRI datasets and facilitate human structural connectome studies. PMID:23439846
q-Space Deep Learning: Twelve-Fold Shorter and Model-Free Diffusion MRI Scans.
Golkov, Vladimir; Dosovitskiy, Alexey; Sperl, Jonathan I; Menzel, Marion I; Czisch, Michael; Samann, Philipp; Brox, Thomas; Cremers, Daniel
2016-05-01
Numerous scientific fields rely on elaborate but partly suboptimal data processing pipelines. An example is diffusion magnetic resonance imaging (diffusion MRI), a non-invasive microstructure assessment method with a prominent application in neuroimaging. Advanced diffusion models providing accurate microstructural characterization so far have required long acquisition times and thus have been inapplicable for children and adults who are uncooperative, uncomfortable, or unwell. We show that the long scan time requirements are mainly due to disadvantages of classical data processing. We demonstrate how deep learning, a group of algorithms based on recent advances in the field of artificial neural networks, can be applied to reduce diffusion MRI data processing to a single optimized step. This modification allows obtaining scalar measures from advanced models at twelve-fold reduced scan time and detecting abnormalities without using diffusion models. We set a new state of the art by estimating diffusion kurtosis measures from only 12 data points and neurite orientation dispersion and density measures from only 8 data points. This allows unprecedentedly fast and robust protocols facilitating clinical routine and demonstrates how classical data processing can be streamlined by means of deep learning.
Mekkaoui, Choukri; Reese, Timothy G.; Jackowski, Marcel P.; Bhat, Himanshu
2015-01-01
Diffusion MRI provides unique information on the structure, organization, and integrity of the myocardium without the need for exogenous contrast agents. Diffusion MRI in the heart, however, has proven technically challenging because of the intrinsic non‐rigid deformation during the cardiac cycle, displacement of the myocardium due to respiratory motion, signal inhomogeneity within the thorax, and short transverse relaxation times. Recently developed accelerated diffusion‐weighted MR acquisition sequences combined with advanced post‐processing techniques have improved the accuracy and efficiency of diffusion MRI in the myocardium. In this review, we describe the solutions and approaches that have been developed to enable diffusion MRI of the heart in vivo, including a dual‐gated stimulated echo approach, a velocity‐ (M 1) or an acceleration‐ (M 2) compensated pulsed gradient spin echo approach, and the use of principal component analysis filtering. The structure of the myocardium and the application of these techniques in ischemic heart disease are also briefly reviewed. The advent of clinical MR systems with stronger gradients will likely facilitate the translation of cardiac diffusion MRI into clinical use. The addition of diffusion MRI to the well‐established set of cardiovascular imaging techniques should lead to new and complementary approaches for the diagnosis and evaluation of patients with heart disease. © 2015 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd. PMID:26484848
Weerakoon, Bimali Sanjeevani; Osuga, Toshiaki
2017-03-01
The observation of molecular diffusion by means of magnetic resonance imaging (MRI) is significant in the evaluation of the metabolic activity of living tissues. Series of MRI examinations were conducted on a diffusion model to study the behaviour of the diffusion process of different-molecular-weight (MW) paramagnetic MRI contrast agents in an isotropic agar hydrogel medium. The model consisted of a solidified 1 % agar gel with an initial concentration of 0.5 mmol/L contrast solution layered on top of the gel. The diffusion process was monitored at pre-determined time intervals of immediately, 1, 6, 9, 23, and 48 h after introduction of the contrast agents onto the agar gel with a T1-weighted spin-echo (SE) pulse sequence. Three types of paramagnetic contrast agents, Gd-DTPA with a MW of 547.57 g/mol, Prohance with a MW of 558.69 g/mol and MnCl 2 with a MW of 125.84 g/mol, resulted in an approximate average diffusional displacement ratio of 1:1:2 per hour, respectively, within 48 h of the experiment. Therefore, the results of this study supported the hypothesis that the rate of the diffusion process of MRI contrast agents in the agar hydrogel medium is inversely related to their MWs. However, more repetitions are necessary under various types of experimental conditions and also with various types of contrast media of different MWs for further confirmation and validation of these results.
Özarslan, Evren; Koay, Cheng Guan; Shepherd, Timothy M; Komlosh, Michal E; İrfanoğlu, M Okan; Pierpaoli, Carlo; Basser, Peter J
2013-09-01
Diffusion-weighted magnetic resonance (MR) signals reflect information about underlying tissue microstructure and cytoarchitecture. We propose a quantitative, efficient, and robust mathematical and physical framework for representing diffusion-weighted MR imaging (MRI) data obtained in "q-space," and the corresponding "mean apparent propagator (MAP)" describing molecular displacements in "r-space." We also define and map novel quantitative descriptors of diffusion that can be computed robustly using this MAP-MRI framework. We describe efficient analytical representation of the three-dimensional q-space MR signal in a series expansion of basis functions that accurately describes diffusion in many complex geometries. The lowest order term in this expansion contains a diffusion tensor that characterizes the Gaussian displacement distribution, equivalent to diffusion tensor MRI (DTI). Inclusion of higher order terms enables the reconstruction of the true average propagator whose projection onto the unit "displacement" sphere provides an orientational distribution function (ODF) that contains only the orientational dependence of the diffusion process. The representation characterizes novel features of diffusion anisotropy and the non-Gaussian character of the three-dimensional diffusion process. Other important measures this representation provides include the return-to-the-origin probability (RTOP), and its variants for diffusion in one- and two-dimensions-the return-to-the-plane probability (RTPP), and the return-to-the-axis probability (RTAP), respectively. These zero net displacement probabilities measure the mean compartment (pore) volume and cross-sectional area in distributions of isolated pores irrespective of the pore shape. MAP-MRI represents a new comprehensive framework to model the three-dimensional q-space signal and transform it into diffusion propagators. Experiments on an excised marmoset brain specimen demonstrate that MAP-MRI provides several novel, quantifiable parameters that capture previously obscured intrinsic features of nervous tissue microstructure. This should prove helpful for investigating the functional organization of normal and pathologic nervous tissue. Copyright © 2013 Elsevier Inc. All rights reserved.
Mekkaoui, Choukri; Reese, Timothy G; Jackowski, Marcel P; Bhat, Himanshu; Sosnovik, David E
2017-03-01
Diffusion MRI provides unique information on the structure, organization, and integrity of the myocardium without the need for exogenous contrast agents. Diffusion MRI in the heart, however, has proven technically challenging because of the intrinsic non-rigid deformation during the cardiac cycle, displacement of the myocardium due to respiratory motion, signal inhomogeneity within the thorax, and short transverse relaxation times. Recently developed accelerated diffusion-weighted MR acquisition sequences combined with advanced post-processing techniques have improved the accuracy and efficiency of diffusion MRI in the myocardium. In this review, we describe the solutions and approaches that have been developed to enable diffusion MRI of the heart in vivo, including a dual-gated stimulated echo approach, a velocity- (M 1 ) or an acceleration- (M 2 ) compensated pulsed gradient spin echo approach, and the use of principal component analysis filtering. The structure of the myocardium and the application of these techniques in ischemic heart disease are also briefly reviewed. The advent of clinical MR systems with stronger gradients will likely facilitate the translation of cardiac diffusion MRI into clinical use. The addition of diffusion MRI to the well-established set of cardiovascular imaging techniques should lead to new and complementary approaches for the diagnosis and evaluation of patients with heart disease. © 2015 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd. © 2015 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.
Dipy, a library for the analysis of diffusion MRI data.
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
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
Varadarajan, Divya; Haldar, Justin P
2017-11-01
The data measured in diffusion MRI can be modeled as the Fourier transform of the Ensemble Average Propagator (EAP), a probability distribution that summarizes the molecular diffusion behavior of the spins within each voxel. This Fourier relationship is potentially advantageous because of the extensive theory that has been developed to characterize the sampling requirements, accuracy, and stability of linear Fourier reconstruction methods. However, existing diffusion MRI data sampling and signal estimation methods have largely been developed and tuned without the benefit of such theory, instead relying on approximations, intuition, and extensive empirical evaluation. This paper aims to address this discrepancy by introducing a novel theoretical signal processing framework for diffusion MRI. The new framework can be used to characterize arbitrary linear diffusion estimation methods with arbitrary q-space sampling, and can be used to theoretically evaluate and compare the accuracy, resolution, and noise-resilience of different data acquisition and parameter estimation techniques. The framework is based on the EAP, and makes very limited modeling assumptions. As a result, the approach can even provide new insight into the behavior of model-based linear diffusion estimation methods in contexts where the modeling assumptions are inaccurate. The practical usefulness of the proposed framework is illustrated using both simulated and real diffusion MRI data in applications such as choosing between different parameter estimation methods and choosing between different q-space sampling schemes. Copyright © 2017 Elsevier Inc. All rights reserved.
O’Connell, Caitlin; Ho, Leon C.; Murphy, Matthew C.; Conner, Ian P.; Wollstein, Gadi; Cham, Rakie; Chan, Kevin C.
2016-01-01
Human visual performance has been observed to exhibit superiority in localized regions of the visual field across many classes of stimuli. However, the underlying neural mechanisms remain unclear. This study aims to determine if the visual information processing in the human brain is dependent on the location of stimuli in the visual field and the corresponding neuroarchitecture using blood-oxygenation-level-dependent functional MRI (fMRI) and diffusion kurtosis MRI (DKI), respectively in 15 healthy individuals at 3 Tesla. In fMRI, visual stimulation to the lower hemifield showed stronger brain responses and larger brain activation volumes than the upper hemifield, indicative of the differential sensitivity of the human brain across the visual field. In DKI, the brain regions mapping to the lower visual field exhibited higher mean kurtosis but not fractional anisotropy or mean diffusivity when compared to the upper visual field. These results suggested the different distributions of microstructural organization across visual field brain representations. There was also a strong positive relationship between diffusion kurtosis and fMRI responses in the lower field brain representations. In summary, this study suggested the structural and functional brain involvements in the asymmetry of visual field responses in humans, and is important to the neurophysiological and psychological understanding of human visual information processing. PMID:27631541
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.
Andersson, Jesper L.R.; Sotiropoulos, Stamatios N.
2015-01-01
Diffusion MRI offers great potential in studying the human brain microstructure and connectivity. However, diffusion images are marred by technical problems, such as image distortions and spurious signal loss. Correcting for these problems is non-trivial and relies on having a mechanism that predicts what to expect. In this paper we describe a novel way to represent and make predictions about diffusion MRI data. It is based on a Gaussian process on one or several spheres similar to the Geostatistical method of “Kriging”. We present a choice of covariance function that allows us to accurately predict the signal even from voxels with complex fibre patterns. For multi-shell data (multiple non-zero b-values) the covariance function extends across the shells which means that data from one shell is used when making predictions for another shell. PMID:26236030
NASA Astrophysics Data System (ADS)
Ginsburger, Kévin; Poupon, Fabrice; Beaujoin, Justine; Estournet, Delphine; Matuschke, Felix; Mangin, Jean-François; Axer, Markus; Poupon, Cyril
2018-02-01
White matter is composed of irregularly packed axons leading to a structural disorder in the extra-axonal space. Diffusion MRI experiments using oscillating gradient spin echo sequences have shown that the diffusivity transverse to axons in this extra-axonal space is dependent on the frequency of the employed sequence. In this study, we observe the same frequency-dependence using 3D simulations of the diffusion process in disordered media. We design a novel white matter numerical phantom generation algorithm which constructs biomimicking geometric configurations with few design parameters, and enables to control the level of disorder of the generated phantoms. The influence of various geometrical parameters present in white matter, such as global angular dispersion, tortuosity, presence of Ranvier nodes, beading, on the extra-cellular perpendicular diffusivity frequency dependence was investigated by simulating the diffusion process in numerical phantoms of increasing complexity and fitting the resulting simulated diffusion MR signal attenuation with an adequate analytical model designed for trapezoidal OGSE sequences. This work suggests that angular dispersion and especially beading have non-negligible effects on this extracellular diffusion metrics that may be measured using standard OGSE DW-MRI clinical protocols.
The connectome mapper: an open-source processing pipeline to map connectomes with MRI.
Daducci, Alessandro; Gerhard, Stephan; Griffa, Alessandra; Lemkaddem, Alia; Cammoun, Leila; Gigandet, Xavier; Meuli, Reto; Hagmann, Patric; Thiran, Jean-Philippe
2012-01-01
Researchers working in the field of global connectivity analysis using diffusion magnetic resonance imaging (MRI) can count on a wide selection of software packages for processing their data, with methods ranging from the reconstruction of the local intra-voxel axonal structure to the estimation of the trajectories of the underlying fibre tracts. However, each package is generally task-specific and uses its own conventions and file formats. In this article we present the Connectome Mapper, a software pipeline aimed at helping researchers through the tedious process of organising, processing and analysing diffusion MRI data to perform global brain connectivity analyses. Our pipeline is written in Python and is freely available as open-source at www.cmtk.org.
Advances in diffusion MRI acquisition and processing in the Human Connectome Project
Sotiropoulos, Stamatios N; Jbabdi, Saad; Xu, Junqian; Andersson, Jesper L; Moeller, Steen; Auerbach, Edward J; Glasser, Matthew F; Hernandez, Moises; Sapiro, Guillermo; Jenkinson, Mark; Feinberg, David A; Yacoub, Essa; Lenglet, Christophe; Ven Essen, David C; Ugurbil, Kamil; Behrens, Timothy EJ
2013-01-01
The Human Connectome Project (HCP) is a collaborative 5-year effort to map human brain connections and their variability in healthy adults. A consortium of HCP investigators will study a population of 1200 healthy adults using multiple imaging modalities, along with extensive behavioral and genetic data. In this overview, we focus on diffusion MRI (dMRI) and the structural connectivity aspect of the project. We present recent advances in acquisition and processing that allow us to obtain very high-quality in-vivo MRI data, while enabling scanning of a very large number of subjects. These advances result from 2 years of intensive efforts in optimising many aspects of data acquisition and processing during the piloting phase of the project. The data quality and methods described here are representative of the datasets and processing pipelines that will be made freely available to the community at quarterly intervals, beginning in 2013. PMID:23702418
Froeling, Martijn; Tax, Chantal M W; Vos, Sjoerd B; Luijten, Peter R; Leemans, Alexander
2017-05-01
In this work, we present the MASSIVE (Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation) brain dataset of a single healthy subject, which is intended to facilitate diffusion MRI (dMRI) modeling and methodology development. MRI data of one healthy subject (female, 25 years) were acquired on a clinical 3 Tesla system (Philips Achieva) with an eight-channel head coil. In total, the subject was scanned on 18 different occasions with a total acquisition time of 22.5 h. The dMRI data were acquired with an isotropic resolution of 2.5 mm 3 and distributed over five shells with b-values up to 4000 s/mm 2 and two Cartesian grids with b-values up to 9000 s/mm 2 . The final dataset consists of 8000 dMRI volumes, corresponding B 0 field maps and noise maps for subsets of the dMRI scans, and ten three-dimensional FLAIR, T 1 -, and T 2 -weighted scans. The average signal-to-noise-ratio of the non-diffusion-weighted images was roughly 35. This unique set of in vivo MRI data will provide a robust framework to evaluate novel diffusion processing techniques and to reliably compare different approaches for diffusion modeling. The MASSIVE dataset is made publically available (both unprocessed and processed) on www.massive-data.org. Magn Reson Med 77:1797-1809, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.
Morozov, Darya; Tal, Iris; Pisanty, Odelia; Shani, Eilon
2017-01-01
Abstract As sessile organisms, plants must respond to the environment by adjusting their growth and development. Most of the plant body is formed post-embryonically by continuous activity of apical and lateral meristems. The development of lateral adventitious roots is a complex process, and therefore the development of methods that can visualize, non-invasively, the plant microstructure and organ initiation that occur during growth and development is of paramount importance. In this study, relaxation-based and advanced diffusion magnetic resonance imaging (MRI) methods including diffusion tensor (DTI), q-space diffusion imaging (QSI), and double-pulsed-field-gradient (d-PFG) MRI, at 14.1 T, were used to characterize the hypocotyl microstructure and the microstructural changes that occurred during the development of lateral adventitious roots in tomato. Better contrast was observed in relaxation-based MRI using higher in-plane resolution but this also resulted in a significant reduction in the signal-to-noise ratio of the T2-weighted MR images. Diffusion MRI revealed that water diffusion is highly anisotropic in the vascular cylinder. QSI and d-PGSE MRI showed that in the vascular cylinder some of the cells have sizes in the range of 6–10 μm. The MR images captured cell reorganization during adventitious root formation in the periphery of the primary vascular bundles, adjacent to the xylem pole that broke through the cortex and epidermis layers. This study demonstrates that MRI and diffusion MRI methods allow the non-invasive study of microstructural features of plants, and enable microstructural changes associated with adventitious root formation to be followed. PMID:28398563
Vellmer, Sebastian; Tonoyan, Aram S; Suter, Dieter; Pronin, Igor N; Maximov, Ivan I
2018-02-01
Diffusion magnetic resonance imaging (dMRI) is a powerful tool in clinical applications, in particular, in oncology screening. dMRI demonstrated its benefit and efficiency in the localisation and detection of different types of human brain tumours. Clinical dMRI data suffer from multiple artefacts such as motion and eddy-current distortions, contamination by noise, outliers etc. In order to increase the image quality of the derived diffusion scalar metrics and the accuracy of the subsequent data analysis, various pre-processing approaches are actively developed and used. In the present work we assess the effect of different pre-processing procedures such as a noise correction, different smoothing algorithms and spatial interpolation of raw diffusion data, with respect to the accuracy of brain glioma differentiation. As a set of sensitive biomarkers of the glioma malignancy grades we chose the derived scalar metrics from diffusion and kurtosis tensor imaging as well as the neurite orientation dispersion and density imaging (NODDI) biophysical model. Our results show that the application of noise correction, anisotropic diffusion filtering, and cubic-order spline interpolation resulted in the highest sensitivity and specificity for glioma malignancy grading. Thus, these pre-processing steps are recommended for the statistical analysis in brain tumour studies. Copyright © 2017. Published by Elsevier GmbH.
Arab, Anas; Wojna-Pelczar, Anna; Khairnar, Amit; Szabó, Nikoletta; Ruda-Kucerova, Jana
2018-05-01
Pathology of neurodegenerative diseases can be correlated with intra-neuronal as well as extracellular changes which lead to neuronal degeneration. The central nervous system (CNS) is a complex structure comprising of many biological barriers. These microstructural barriers might be affected by a variety of pathological processes. Specifically, changes in the brain tissue's microstructure affect the diffusion of water which can be assessed non-invasively by diffusion weighted (DW) magnetic resonance imaging (MRI) techniques. Diffusion tensor imaging (DTI) is a diffusion MRI technique that considers diffusivity as a Gaussian process, i.e. does not account for any diffusion hindrance. However, environment of the brain tissues is characterized by a non-Gaussian diffusion. Therefore, diffusion kurtosis imaging (DKI) was developed as an extension of DTI method in order to quantify the non-Gaussian distribution of water diffusion. This technique represents a promising approach for early diagnosis of neurodegenerative diseases when the neurodegenerative process starts. Hence, the purpose of this article is to summarize the ongoing clinical and preclinical research on Parkinson's, Alzheimer's and Huntington diseases, using DKI and to discuss the role of this technique as an early stage biomarker of neurodegenerative conditions. Copyright © 2018 Elsevier Inc. All rights reserved.
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.
Modifications of pancreatic diffusion MRI by tissue characteristics: what are we weighting for?
Nissan, Noam
2017-08-01
Diffusion-weighted imaging holds the potential to improve the diagnosis and biological characterization of pancreatic disease, and in particular pancreatic cancer, which exhibits decreased values of the apparent diffusion coefficient (ADC). Yet, variable and overlapping ADC values have been reported for the healthy and the pathological pancreas, including for cancer and other benign conditions. This controversy reflects the complexity of probing the water-diffusion process in the pancreas, which is dependent upon multiple biological factors within this organ's unique physiological environment. In recent years, extensive studies have investigated the correlation between tissue properties including cellularity, vascularity, fibrosis, secretion and microstructure and pancreatic diffusivity. Understanding how the various physiological and pathological features and the underlying functional processes affect the diffusion measurement may serve to optimize the method for improved diagnostic gain. Therefore, the aim of the present review article is to elucidate the relationship between pancreatic tissue characteristics and diffusion MRI measurement. Copyright © 2017 John Wiley & Sons, Ltd.
The Potential for an Enhanced Role for MRI in Radiation-therapy Treatment Planning
Metcalfe, P.; Liney, G. P.; Holloway, L.; Walker, A.; Barton, M.; Delaney, G. P.; Vinod, S.; Tomé, W.
2013-01-01
The exquisite soft-tissue contrast of magnetic resonance imaging (MRI) has meant that the technique is having an increasing role in contouring the gross tumor volume (GTV) and organs at risk (OAR) in radiation therapy treatment planning systems (TPS). MRI-planning scans from diagnostic MRI scanners are currently incorporated into the planning process by being registered to CT data. The soft-tissue data from the MRI provides target outline guidance and the CT provides a solid geometric and electron density map for accurate dose calculation on the TPS computer. There is increasing interest in MRI machine placement in radiotherapy clinics as an adjunct to CT simulators. Most vendors now offer 70 cm bores with flat couch inserts and specialised RF coil designs. We would refer to these devices as MR-simulators. There is also research into the future application of MR-simulators independent of CT and as in-room image-guidance devices. It is within the background of this increased interest in the utility of MRI in radiotherapy treatment planning that this paper is couched. The paper outlines publications that deal with standard MRI sequences used in current clinical practice. It then discusses the potential for using processed functional diffusion maps (fDM) derived from diffusion weighted image sequences in tracking tumor activity and tumor recurrence. Next, this paper reviews publications that describe the use of MRI in patient-management applications that may, in turn, be relevant to radiotherapy treatment planning. The review briefly discusses the concepts behind functional techniques such as dynamic contrast enhanced (DCE), diffusion-weighted (DW) MRI sequences and magnetic resonance spectroscopic imaging (MRSI). Significant applications of MR are discussed in terms of the following treatment sites: brain, head and neck, breast, lung, prostate and cervix. While not yet routine, the use of apparent diffusion coefficient (ADC) map analysis indicates an exciting future application for functional MRI. Although DW-MRI has not yet been routinely used in boost adaptive techniques, it is being assessed in cohort studies for sub-volume boosting in prostate tumors. PMID:23617289
Bible, Ellen; Dell’Acqua, Flavio; Solanky, Bhavana; Balducci, Anthony; Crapo, Peter; Badylak, Stephen F.; Ahrens, Eric T.; Modo, Michel
2012-01-01
Transplantation of human neural stem cells (hNSCs) is emerging as a viable treatment for stroke related brain injury. However, intraparenchymal grafts do not regenerate lost tissue, but rather integrate into the host parenchyma without significantly affecting the lesion cavity. Providing a structural support for the delivered cells appears important for cell based therapeutic approaches. The non-invasive monitoring of therapeutic methods would provide valuable information regarding therapeutic strategies but remains a challenge. Labeling transplanted cells with metal-based 1H-magnetic resonance imaging (MRI) contrast agents affects the visualization of the lesion cavity. Herein, we demonstrate that a 19F-MRI contrast agent can adequately monitor the distribution of transplanted cells, whilst allowing an evaluation of the lesion cavity and the formation of new tissue on 1H-MRI scans. Twenty percent of cells labeled with the 19F-agent were of host origin, potentially reflecting the re-uptake of label from dead transplanted cells. Both T2- and diffusion-weighted MRI scans indicated that transplantation of hNSCs suspended in a gel form of a xenogeneic extracellular matrix (ECM) bioscaffold resulted in uniformly distributed cells throughout the lesion cavity. However, diffusion MRI indicated that the injected materials did not yet establish diffusion barriers (i.e. cellular network, fiber tracts) normally found within striatal tissue. The ECM bioscaffold therefore provides an important support to hNSCs for the creation of de novo tissue and multi-nuclei MRI represents an adept method for the visualization of some aspects of this process. However, significant developments of both the transplantation paradigm, as well as regenerative imaging, are required to successfully create new tissue in the lesion cavity and to monitor this process non-invasively. PMID:22244696
Mass diffusion coefficient measurement for vitreous humor using FEM and MRI
NASA Astrophysics Data System (ADS)
Rattanakijsuntorn, Komsan; Penkova, Anita; Sadha, Satwindar S.
2018-01-01
In early studies, the ‘contour method’ for determining the diffusion coefficient of the vitreous humor was developed. This technique relied on careful injection of an MRI contrast agent (surrogate drug) into the vitreous humor of fresh bovine eyes, and tracking the contours of the contrast agent in time. In addition, an analytical solution was developed for the theoretical contours built on point source model for the injected surrogate drug. The match between theoretical and experimental contours as a least square fit, while floating the diffusion coefficient, led to the value of the diffusion coefficient. This method had its limitation that the initial injection of the surrogate had to be spherical or ellipsoidal because of the analytical result based on the point-source model. With a new finite element model for the analysis in this study, the technique is much less restrictive and handles irregular shapes of the initial bolus. The fresh bovine eyes were used for drug diffusion study in the vitreous and three contrast agents of different molecular masses: gadolinium-diethylenetriaminepentaacetic acid (Gd-DTPA, 938 Da), non-ionic gadoteridol (Prohance, 559 Da), and bovine albumin conjugated with gadolinium (Galbumin, 74 kDa) were used as drug surrogates to visualize the diffusion process by MRI. The 3D finite element model was developed to determine the diffusion coefficients of these surrogates with the images from MRI. This method can be used for other types of bioporous media provided the concentration profile can be visualized (by methods such as MRI or fluorescence).
MRI diffusion tensor reconstruction with PROPELLER data acquisition.
Cheryauka, Arvidas B; Lee, James N; Samsonov, Alexei A; Defrise, Michel; Gullberg, Grant T
2004-02-01
MRI diffusion imaging is effective in measuring the diffusion tensor in brain, cardiac, liver, and spinal tissue. Diffusion tensor tomography MRI (DTT MRI) method is based on reconstructing the diffusion tensor field from measurements of projections of the tensor field. Projections are obtained by appropriate application of rotated diffusion gradients. In the present paper, the potential of a novel data acquisition scheme, PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction), is examined in combination with DTT MRI for its capability and sufficiency for diffusion imaging. An iterative reconstruction algorithm is used to reconstruct the diffusion tensor field from rotated diffusion weighted blades by appropriate rotated diffusion gradients. DTT MRI with PROPELLER data acquisition shows significant potential to reduce the number of weighted measurements, avoid ambiguity in reconstructing diffusion tensor parameters, increase signal-to-noise ratio, and decrease the influence of signal distortion.
Nicolas, R; Gros-Dagnac, H; Aubry, F; Celsis, P
2017-06-01
The blood oxygen level-dependent (BOLD) effect is extensively used for functional MRI (fMRI) but presents some limitations. Diffusion-weighted fMRI (DfMRI) has been proposed as a method more tightly linked to neuronal activity. This work proposes a protocol of DfMRI acquired for several b-values and diffusion directions that is compared to gradient-echo BOLD (GE-BOLD) and to repeated spin-echo BOLD (SE-BOLD, acquisitions performed with b=0s/mm 2 ), which was also used to ensure the reproducibility of the response. A block stimulation paradigm of the primary visual system (V1) was performed in 12 healthy subjects with checkerboard alternations (2Hz frequency). DfMRI was performed at 3T with 5 b-values (b=1500, 1000, 500, 250, 0s/mm 2 ) with TR/TE=1004/93ms, Δ/δ=45.4ms/30ms, and 6 spatial directions for diffusion measures. GE-BOLD was performed with a similar block stimulation design timing. Apparent Diffusion Coefficient (ADC)-fMRI was computed with all b-values used. An identical Z-score level was used for all fMRI modalities for the comparison of volumes of activation. ADC-fMRI and SE-BOLD fMRI activation locations were compared in a voxel-based analysis to a cytoarchitectural probability map of V1. SE-BOLD activation volumes represented only 55% of the GE-BOLD activation volumes (P<0.0001). DfMRI activation volumes averaged for all b-values acquired represented only 12% of GE-BOLD (P<0.0001) and only 22% of SE-BOLD activation volumes (P<0.005). Compared to SE-BOLD-fMRI, ADC-fMRI activations showed fewer pixels outside of V1 and a higher average probability of belonging to V1. DfMRI and ADC-fMRI acquisition at 3T could be easily post-processed with common neuro-imaging software. DfMRI and ADC-fMRI activation volumes were significantly smaller than those obtained with SE-BOLD. ADC-fMRI activations were more precisely localized in V1 than those of SE-BOLD-fMRI. This validated the increased capability of ADC-fMRI compared to BOLD to enhance the precision of localizing an fMRI activation in the cyto-architectural zone V1, thereby justifying the use of ADC-fMRI for neuro-scientific studies. Copyright © 2017 Elsevier Inc. All rights reserved.
Loh, K B; Ramli, N; Tan, L K; Roziah, M; Rahmat, K; Ariffin, H
2012-07-01
The degree and status of white matter myelination can be sensitively monitored using diffusion tensor imaging (DTI). This study looks at the measurement of fractional anistropy (FA) and mean diffusivity (MD) using an automated ROI with an existing DTI atlas. Anatomical MRI and structural DTI were performed cross-sectionally on 26 normal children (newborn to 48 months old), using 1.5-T MRI. The automated processing pipeline was implemented to convert diffusion-weighted images into the NIfTI format. DTI-TK software was used to register the processed images to the ICBM DTI-81 atlas, while AFNI software was used for automated atlas-based volumes of interest (VOIs) and statistical value extraction. DTI exhibited consistent grey-white matter contrast. Triphasic temporal variation of the FA and MD values was noted, with FA increasing and MD decreasing rapidly early in the first 12 months. The second phase lasted 12-24 months during which the rate of FA and MD changes was reduced. After 24 months, the FA and MD values plateaued. DTI is a superior technique to conventional MR imaging in depicting WM maturation. The use of the automated processing pipeline provides a reliable environment for quantitative analysis of high-throughput DTI data. Diffusion tensor imaging outperforms conventional MRI in depicting white matter maturation. • DTI will become an important clinical tool for diagnosing paediatric neurological diseases. • DTI appears especially helpful for developmental abnormalities, tumours and white matter disease. • An automated processing pipeline assists quantitative analysis of high throughput DTI data.
Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project.
Bastiani, Matteo; Andersson, Jesper L R; Cordero-Grande, Lucilio; Murgasova, Maria; Hutter, Jana; Price, Anthony N; Makropoulos, Antonios; Fitzgibbon, Sean P; Hughes, Emer; Rueckert, Daniel; Victor, Suresh; Rutherford, Mary; Edwards, A David; Smith, Stephen M; Tournier, Jacques-Donald; Hajnal, Joseph V; Jbabdi, Saad; Sotiropoulos, Stamatios N
2018-05-28
The developing Human Connectome Project is set to create and make available to the scientific community a 4-dimensional map of functional and structural cerebral connectivity from 20 to 44 weeks post-menstrual age, to allow exploration of the genetic and environmental influences on brain development, and the relation between connectivity and neurocognitive function. A large set of multi-modal MRI data from fetuses and newborn infants is currently being acquired, along with genetic, clinical and developmental information. In this overview, we describe the neonatal diffusion MRI (dMRI) image processing pipeline and the structural connectivity aspect of the project. Neonatal dMRI data poses specific challenges, and standard analysis techniques used for adult data are not directly applicable. We have developed a processing pipeline that deals directly with neonatal-specific issues, such as severe motion and motion-related artefacts, small brain sizes, high brain water content and reduced anisotropy. This pipeline allows automated analysis of in-vivo dMRI data, probes tissue microstructure, reconstructs a number of major white matter tracts, and includes an automated quality control framework that identifies processing issues or inconsistencies. We here describe the pipeline and present an exemplar analysis of data from 140 infants imaged at 38-44 weeks post-menstrual age. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Pullens, Pim; Bladt, Piet; Sijbers, Jan; Maas, Andrew I R; Parizel, Paul M
2017-03-01
Since Diffusion Weighted Imaging (DWI) data acquisition and processing are not standardized, substantial differences in DWI derived measures such as Apparent Diffusion Coefficient (ADC) may arise which are related to the acquisition or MRI processing method, but not to the sample under study. Quality assurance using a standardized test object, or phantom, is a key factor in standardizing DWI across scanners. Current diffusion phantoms are either complex to use, not available in larger quantities, contain substances unwanted in a clinical environment, or are expensive. A diffusion phantom based on a polyvinylpyrrolidone (PVP) solution, together with a phantom holder, is presented and compared to existing diffusion phantoms for use in clinical DWI scans. An ADC vs. temperature calibration curve was obtained. ADC of the phantom (808 to 857 ± 0.2 mm 2 /s) is in the same range as ADC values found in brain tissue. ADC measurements are highly reproducible across time with an intra-class correlation coefficient of > 0.8. ADC as function of temperature (in Kelvin) can be estimated as ADCm(T)=[exp(-7.09)·exp-2903.81T-1293.55] with a total uncertainty (95% confidence limit) of ± 1.7%. We present an isotropic diffusion MRI phantom, together with its temperature calibration curve, that is easy-to-use in a clinical environment, cost-effective, reproducible to produce, and that contains no harmful substances. © 2017 American Association of Physicists in Medicine.
NASA Astrophysics Data System (ADS)
Cao, Ning; Liang, Xuwei; Zhuang, Qi; Zhang, Jun
2009-02-01
Magnetic Resonance Imaging (MRI) techniques have achieved much importance in providing visual and quantitative information of human body. Diffusion MRI is the only non-invasive tool to obtain information of the neural fiber networks of the human brain. The traditional Diffusion Tensor Imaging (DTI) is only capable of characterizing Gaussian diffusion. High Angular Resolution Diffusion Imaging (HARDI) extends its ability to model more complex diffusion processes. Spherical harmonic series truncated to a certain degree is used in recent studies to describe the measured non-Gaussian Apparent Diffusion Coefficient (ADC) profile. In this study, we use the sampling theorem on band-limited spherical harmonics to choose a suitable degree to truncate the spherical harmonic series in the sense of Signal-to-Noise Ratio (SNR), and use Monte Carlo integration to compute the spherical harmonic transform of human brain data obtained from icosahedral schema.
Bible, Ellen; Dell'Acqua, Flavio; Solanky, Bhavana; Balducci, Anthony; Crapo, Peter M; Badylak, Stephen F; Ahrens, Eric T; Modo, Michel
2012-04-01
Transplantation of human neural stem cells (hNSCs) is emerging as a viable treatment for stroke related brain injury. However, intraparenchymal grafts do not regenerate lost tissue, but rather integrate into the host parenchyma without significantly affecting the lesion cavity. Providing a structural support for the delivered cells appears important for cell based therapeutic approaches. The non-invasive monitoring of therapeutic methods would provide valuable information regarding therapeutic strategies but remains a challenge. Labeling transplanted cells with metal-based (1)H-magnetic resonance imaging (MRI) contrast agents affects the visualization of the lesion cavity. Herein, we demonstrate that a (19)F-MRI contrast agent can adequately monitor the distribution of transplanted cells, whilst allowing an evaluation of the lesion cavity and the formation of new tissue on (1)H-MRI scans. Twenty percent of cells labeled with the (19)F agent were of host origin, potentially reflecting the re-uptake of label from dead transplanted cells. Both T(2)- and diffusion-weighted MRI scans indicated that transplantation of hNSCs suspended in a gel form of a xenogeneic extracellular matrix (ECM) bioscaffold resulted in uniformly distributed cells throughout the lesion cavity. However, diffusion MRI indicated that the injected materials did not yet establish diffusion barriers (i.e. cellular network, fiber tracts) normally found within striatal tissue. The ECM bioscaffold therefore provides an important support to hNSCs for the creation of de novo tissue and multi-nuclei MRI represents an adept method for the visualization of some aspects of this process. However, significant developments of both the transplantation paradigm, as well as regenerative imaging, are required to successfully create new tissue in the lesion cavity and to monitor this process non-invasively. Copyright © 2011 Elsevier Ltd. All rights reserved.
Image formation in diffusion MRI: A review of recent technical developments
Miller, Karla L.
2017-01-01
Diffusion magnetic resonance imaging (MRI) is a standard imaging tool in clinical neurology, and is becoming increasingly important for neuroscience studies due to its ability to depict complex neuroanatomy (eg, white matter connectivity). Single‐shot echo‐planar imaging is currently the predominant formation method for diffusion MRI, but suffers from blurring, distortion, and low spatial resolution. A number of methods have been proposed to address these limitations and improve diffusion MRI acquisition. Here, the recent technical developments for image formation in diffusion MRI are reviewed. We discuss three areas of advance in diffusion MRI: improving image fidelity, accelerating acquisition, and increasing the signal‐to‐noise ratio. Level of Evidence: 5 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:646–662 PMID:28194821
Diffusion-Weighted Imaging Outside the Brain: Consensus Statement From an ISMRM-Sponsored Workshop
Taouli, Bachir; Beer, Ambros J.; Chenevert, Thomas; Collins, David; Lehman, Constance; Matos, Celso; Padhani, Anwar R.; Rosenkrantz, Andrew B.; Shukla-Dave, Amita; Sigmund, Eric; Tanenbaum, Lawrence; Thoeny, Harriet; Thomassin-Naggara, Isabelle; Barbieri, Sebastiano; Corcuera-Solano, Idoia; Orton, Matthew; Partridge, Savannah C.; Koh, Dow-Mu
2016-01-01
The significant advances in magnetic resonance imaging (MRI) hardware and software, sequence design, and postprocessing methods have made diffusion-weighted imaging (DWI) an important part of body MRI protocols and have fueled extensive research on quantitative diffusion outside the brain, particularly in the oncologic setting. In this review, we summarize the most up-to-date information on DWI acquisition and clinical applications outside the brain, as discussed in an ISMRM-sponsored symposium held in April 2015. We first introduce recent advances in acquisition, processing, and quality control; then review scientific evidence in major organ systems; and finally describe future directions. PMID:26892827
Cong, Fengyu; Puoliväli, Tuomas; Alluri, Vinoo; Sipola, Tuomo; Burunat, Iballa; Toiviainen, Petri; Nandi, Asoke K; Brattico, Elvira; Ristaniemi, Tapani
2014-02-15
Independent component analysis (ICA) has been often used to decompose fMRI data mostly for the resting-state, block and event-related designs due to its outstanding advantage. For fMRI data during free-listening experiences, only a few exploratory studies applied ICA. For processing the fMRI data elicited by 512-s modern tango, a FFT based band-pass filter was used to further pre-process the fMRI data to remove sources of no interest and noise. Then, a fast model order selection method was applied to estimate the number of sources. Next, both individual ICA and group ICA were performed. Subsequently, ICA components whose temporal courses were significantly correlated with musical features were selected. Finally, for individual ICA, common components across majority of participants were found by diffusion map and spectral clustering. The extracted spatial maps (by the new ICA approach) common across most participants evidenced slightly right-lateralized activity within and surrounding the auditory cortices. Meanwhile, they were found associated with the musical features. Compared with the conventional ICA approach, more participants were found to have the common spatial maps extracted by the new ICA approach. Conventional model order selection methods underestimated the true number of sources in the conventionally pre-processed fMRI data for the individual ICA. Pre-processing the fMRI data by using a reasonable band-pass digital filter can greatly benefit the following model order selection and ICA with fMRI data by naturalistic paradigms. Diffusion map and spectral clustering are straightforward tools to find common ICA spatial maps. Copyright © 2013 Elsevier B.V. All rights reserved.
Classification of fMRI resting-state maps using machine learning techniques: A comparative study
NASA Astrophysics Data System (ADS)
Gallos, Ioannis; Siettos, Constantinos
2017-11-01
We compare the efficiency of Principal Component Analysis (PCA) and nonlinear learning manifold algorithms (ISOMAP and Diffusion maps) for classifying brain maps between groups of schizophrenia patients and healthy from fMRI scans during a resting-state experiment. After a standard pre-processing pipeline, we applied spatial Independent component analysis (ICA) to reduce (a) noise and (b) spatial-temporal dimensionality of fMRI maps. On the cross-correlation matrix of the ICA components, we applied PCA, ISOMAP and Diffusion Maps to find an embedded low-dimensional space. Finally, support-vector-machines (SVM) and k-NN algorithms were used to evaluate the performance of the algorithms in classifying between the two groups.
Diffusion MRI and its role in neuropsychology
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
Continuous diffusion signal, EAP and ODF estimation via Compressive Sensing in diffusion MRI.
Merlet, Sylvain L; Deriche, Rachid
2013-07-01
In this paper, we exploit the ability of Compressed Sensing (CS) to recover the whole 3D Diffusion MRI (dMRI) signal from a limited number of samples while efficiently recovering important diffusion features such as the Ensemble Average Propagator (EAP) and the Orientation Distribution Function (ODF). Some attempts to use CS in estimating diffusion signals have been done recently. However, this was mainly an experimental insight of CS capabilities in dMRI and the CS theory has not been fully exploited. In this work, we also propose to study the impact of the sparsity, the incoherence and the RIP property on the reconstruction of diffusion signals. We show that an efficient use of the CS theory enables to drastically reduce the number of measurements commonly used in dMRI acquisitions. Only 20-30 measurements, optimally spread on several b-value shells, are shown to be necessary, which is less than previous attempts to recover the diffusion signal using CS. This opens an attractive perspective to measure the diffusion signals in white matter within a reduced acquisition time and shows that CS holds great promise and opens new and exciting perspectives in diffusion MRI (dMRI). Copyright © 2013 Elsevier B.V. All rights reserved.
Bural, Gonca G; Torigian, Drew A; Burke, Anne; Houseni, Mohamed; Alkhawaldeh, Khaled; Cucchiara, Andrew; Basu, Sandip; Alavi, Abass
2010-06-01
The aim of this study was to compare hepatic standardized uptake values (SUVs) and hepatic metabolic volumetric products (HMVP) between patients of diffuse hepatic steatosis and control subjects with normal livers. Twenty-seven subjects were included in the study (13 men and 14 women; age range, 34-72 years). All had 18F-2-fluoro-2-D-deoxyglucose-positron emission tomography (FDG-PET) and magnetic resonance imaging (MRI) scans with an interscan interval of 0-5 months. Twelve of 27 subjects had diffuse hepatic steatosis on MRI. The remaining 15 were selected as age-matched controls based on normal liver parenchyma on MRI. Mean and maximum hepatic SUVs were calculated for both patient groups on FDG-PET images. Hepatic volumes were measured from MRI. HMVP in each subject was subsequently calculated by multiplication of hepatic volume by mean hepatic SUV. HMVPs as well as mean and maximum hepatic SUVs were compared between the two study groups. HMVPs, mean hepatic SUVs, and maximum hepatic SUVs were greater (statistically significant, p < 0.05) in subjects with diffuse hepatic steatosis compared to those in the control group. The increase in HMVP is the result of increased hepatic metabolic activity likely related to the diffuse hepatic steatosis. The active inflammatory process related to the diffuse hepatic steatosis is the probable explanation for the increase in hepatic metabolic activity on FDG-PET study.
Imaging laminar structures in the gray matter with diffusion MRI.
Assaf, Yaniv
2018-01-05
The cortical layers define the architecture of the gray matter and its neuroanatomical regions and are essential for brain function. Abnormalities in cortical layer development, growth patterns, organization, or size can affect brain physiology and cognition. Unfortunately, while large population studies are underway that will greatly increase our knowledge about these processes, current non-invasive techniques for characterizing the cortical layers remain inadequate. For decades, high-resolution T1 and T2 Weighted Magnetic Resonance Imaging (MRI) have been the method-of-choice for gray matter and layer characterization. In the past few years, however, diffusion MRI has shown increasing promise for its unique insights into the fine structure of the cortex. Several different methods, including surface analysis, connectivity exploration, and sub-voxel component modeling, are now capable of exploring the diffusion characteristics of the cortex. In this review, we will discuss current advances in the application of diffusion imaging for cortical characterization and its unique features, with a particular emphasis on its spatial resolution, arguably its greatest limitation. In addition, we will explore the relationship between the diffusion MRI signal and the cellular components of the cortex, as visualized by histology. While the obstacles facing the widespread application of cortical diffusion imaging remain daunting, the information it can reveal may prove invaluable. Within the next few years, we predict a surge in the application of this technique and a concomitant expansion of our knowledge of cortical layers. Copyright © 2018 Elsevier Inc. All rights reserved.
Symmetric Positive 4th Order Tensors & Their Estimation from Diffusion Weighted MRI⋆
Barmpoutis, Angelos; Jian, Bing; Vemuri, Baba C.; Shepherd, Timothy M.
2009-01-01
In Diffusion Weighted Magnetic Resonance Image (DW-MRI) processing a 2nd order tensor has been commonly used to approximate the diffusivity function at each lattice point of the DW-MRI data. It is now well known that this 2nd-order approximation fails to approximate complex local tissue structures, such as fibers crossings. In this paper we employ a 4th order symmetric positive semi-definite (PSD) tensor approximation to represent the diffusivity function and present a novel technique to estimate these tensors from the DW-MRI data guaranteeing the PSD property. There have been several published articles in literature on higher order tensor approximations of the diffusivity function but none of them guarantee the positive semi-definite constraint, which is a fundamental constraint since negative values of the diffusivity coefficients are not meaningful. In our methods, we parameterize the 4th order tensors as a sum of squares of quadratic forms by using the so called Gram matrix method from linear algebra and its relation to the Hilbert’s theorem on ternary quartics. This parametric representation is then used in a nonlinear-least squares formulation to estimate the PSD tensors of order 4 from the data. We define a metric for the higher-order tensors and employ it for regularization across the lattice. Finally, performance of this model is depicted on synthetic data as well as real DW-MRI from an isolated rat hippocampus. PMID:17633709
Real Diffusion-Weighted MRI Enabling True Signal Averaging and Increased Diffusion Contrast
Eichner, Cornelius; Cauley, Stephen F; Cohen-Adad, Julien; Möller, Harald E; Turner, Robert; Setsompop, Kawin; Wald, Lawrence L
2015-01-01
This project aims to characterize the impact of underlying noise distributions on diffusion-weighted imaging. The noise floor is a well-known problem for traditional magnitude-based diffusion-weighted MRI (dMRI) data, leading to biased diffusion model fits and inaccurate signal averaging. Here, we introduce a total-variation-based algorithm to eliminate shot-to-shot phase variations of complex-valued diffusion data with the intention to extract real-valued dMRI datasets. The obtained real-valued diffusion data are no longer superimposed by a noise floor but instead by a zero-mean Gaussian noise distribution, yielding dMRI data without signal bias. We acquired high-resolution dMRI data with strong diffusion weighting and, thus, low signal-to-noise ratio. Both the extracted real-valued and traditional magnitude data were compared regarding signal averaging, diffusion model fitting and accuracy in resolving crossing fibers. Our results clearly indicate that real-valued diffusion data enables idealized conditions for signal averaging. Furthermore, the proposed method enables unbiased use of widely employed linear least squares estimators for model fitting and demonstrates an increased sensitivity to detect secondary fiber directions with reduced angular error. The use of phase-corrected, real-valued data for dMRI will therefore help to clear the way for more detailed and accurate studies of white matter microstructure and structural connectivity on a fine scale. PMID:26241680
NASA Astrophysics Data System (ADS)
Mériaux, Sébastien; Conti, Allegra; Larrat, Benoît
2018-05-01
The characterization of extracellular space (ECS) architecture represents valuable information for the understanding of transport mechanisms occurring in brain parenchyma. ECS tortuosity reflects the hindrance imposed by cell membranes to molecular diffusion. Numerous strategies have been proposed to measure the diffusion through ECS and to estimate its tortuosity. The first method implies the perfusion for several hours of a radiotracer which effective diffusion coefficient D* is determined after post mortem processing. The most well-established techniques are real-time iontophoresis that measures the concentration of a specific ion at known distance from its release point, and integrative optical imaging that relies on acquiring microscopy images of macromolecules labelled with fluorophore. After presenting these methods, we focus on a recent Magnetic Resonance Imaging (MRI)-based technique that consists in acquiring concentration maps of a contrast agent diffusing within ECS. Thanks to MRI properties, molecular diffusion and tortuosity can be estimated in 3D for deep brain regions. To further discuss the reliability of this technique, we point out the influence of the delivery method on the estimation of D*. We compare the value of D* for a contrast agent intracerebrally injected, with its value when the agent is delivered to the brain after an ultrasound-induced blood-brain barrier (BBB) permeabilization. Several studies have already shown that tortuosity may be modified in pathological conditions. Therefore, we believe that MRI-based techniques could be useful in a clinical context for characterizing the diffusion properties of pathological ECS and thus predicting the drug biodistribution into the targeted area.
A Simulation Tool for Dynamic Contrast Enhanced MRI
Mauconduit, Franck; Christen, Thomas; Barbier, Emmanuel Luc
2013-01-01
The quantification of bolus-tracking MRI techniques remains challenging. The acquisition usually relies on one contrast and the analysis on a simplified model of the various phenomena that arise within a voxel, leading to inaccurate perfusion estimates. To evaluate how simplifications in the interstitial model impact perfusion estimates, we propose a numerical tool to simulate the MR signal provided by a dynamic contrast enhanced (DCE) MRI experiment. Our model encompasses the intrinsic and relaxations, the magnetic field perturbations induced by susceptibility interfaces (vessels and cells), the diffusion of the water protons, the blood flow, the permeability of the vessel wall to the the contrast agent (CA) and the constrained diffusion of the CA within the voxel. The blood compartment is modeled as a uniform compartment. The different blocks of the simulation are validated and compared to classical models. The impact of the CA diffusivity on the permeability and blood volume estimates is evaluated. Simulations demonstrate that the CA diffusivity slightly impacts the permeability estimates ( for classical blood flow and CA diffusion). The effect of long echo times is investigated. Simulations show that DCE-MRI performed with an echo time may already lead to significant underestimation of the blood volume (up to 30% lower for brain tumor permeability values). The potential and the versatility of the proposed implementation are evaluated by running the simulation with realistic vascular geometry obtained from two photons microscopy and with impermeable cells in the extravascular environment. In conclusion, the proposed simulation tool describes DCE-MRI experiments and may be used to evaluate and optimize acquisition and processing strategies. PMID:23516414
Hernández-Martin, Estefania; Marcano, Francisco; Casanova, Oscar; Modroño, Cristian; Plata-Bello, Julio; González-Mora, Jose Luis
2017-01-01
Abstract. Diffuse optical tomography (DOT) measures concentration changes in both oxy- and deoxyhemoglobin providing three-dimensional images of local brain activations. A pilot study, which compares both DOT and functional magnetic resonance imaging (fMRI) volumes through t-maps given by canonical statistical parametric mapping (SPM) processing for both data modalities, is presented. The DOT series were processed using a method that is based on a Bayesian filter application on raw DOT data to remove physiological changes and minimum description length application index to select a number of singular values, which reduce the data dimensionality during image reconstruction and adaptation of DOT volume series to normalized standard space. Therefore, statistical analysis is performed with canonical SPM software in the same way as fMRI analysis is done, accepting DOT volumes as if they were fMRI volumes. The results show the reproducibility and ruggedness of the method to process DOT series on group analysis using cognitive paradigms on the prefrontal cortex. Difficulties such as the fact that scalp–brain distances vary between subjects or cerebral activations are difficult to reproduce due to strategies used by the subjects to solve arithmetic problems are considered. T-images given by fMRI and DOT volume series analyzed in SPM show that at the functional level, both DOT and fMRI measures detect the same areas, although DOT provides complementary information to fMRI signals about cerebral activity. PMID:28386575
Hoffman, Matthew P; Taylor, Erik N; Aninwene, George E; Sadayappan, Sakthivel; Gilbert, Richard J
2018-02-01
Contraction of muscular tissue requires the synchronized shortening of myofibers arrayed in complex geometrical patterns. Imaging such myofiber patterns with diffusion-weighted MRI reveals architectural ensembles that underlie force generation at the organ scale. Restricted proton diffusion is a stochastic process resulting from random translational motion that may be used to probe the directionality of myofibers in whole tissue. During diffusion-weighted MRI, magnetic field gradients are applied to determine the directional dependence of proton diffusion through the analysis of a diffusional probability distribution function (PDF). The directions of principal (maximal) diffusion within the PDF are associated with similarly aligned diffusion maxima in adjacent voxels to derive multivoxel tracts. Diffusion-weighted MRI with tractography thus constitutes a multiscale method for depicting patterns of cellular organization within biological tissues. We provide in this review, details of the method by which generalized Q-space imaging is used to interrogate multidimensional diffusion space, and thereby to infer the organization of muscular tissue. Q-space imaging derives the lowest possible angular separation of diffusion maxima by optimizing the conditions by which magnetic field gradients are applied to a given tissue. To illustrate, we present the methods and applications associated with Q-space imaging of the multiscale myoarchitecture associated with the human and rodent tongues. These representations emphasize the intricate and continuous nature of muscle fiber organization and suggest a method to depict structural "blueprints" for skeletal and cardiac muscle tissue. © 2016 Wiley Periodicals, Inc.
Jeurissen, Ben; Leemans, Alexander; Sijbers, Jan
2014-10-01
Ensuring one is using the correct gradient orientations in a diffusion MRI study can be a challenging task. As different scanners, file formats and processing tools use different coordinate frame conventions, in practice, users can end up with improperly oriented gradient orientations. Using such wrongly oriented gradient orientations for subsequent diffusion parameter estimation will invalidate all rotationally variant parameters and fiber tractography results. While large misalignments can be detected by visual inspection, small rotations of the gradient table (e.g. due to angulation of the acquisition plane), are much more difficult to detect. In this work, we propose an automated method to align the coordinate frame of the gradient orientations with that of the corresponding diffusion weighted images, using a metric based on whole brain fiber tractography. By transforming the gradient table and measuring the average fiber trajectory length, we search for the transformation that results in the best global 'connectivity'. To ensure a fast calculation of the metric we included a range of algorithmic optimizations in our tractography routine. To make the optimization routine robust to spurious local maxima, we use a stochastic optimization routine that selects a random set of seed points on each evaluation. Using simulations, we show that our method can recover the correct gradient orientations with high accuracy and precision. In addition, we demonstrate that our technique can successfully recover rotated gradient tables on a wide range of clinically realistic data sets. As such, our method provides a practical and robust solution to an often overlooked pitfall in the processing of diffusion MRI. Copyright © 2014 Elsevier B.V. All rights reserved.
Ramanan, B.; Holmes, W. M.; Sloan, W. T.; Phoenix, V. R.
2010-01-01
Molecules become readily visible by magnetic resonance imaging (MRI) when labeled with a paramagnetic tag. Consequently, MRI can be used to image their transport through porous media. In this study, we demonstrated that this method could be applied to image mass transport processes in biofilms. The transport of a complex of gadolinium and diethylenetriamine pentaacetic acid (Gd-DTPA), a commercially available paramagnetic molecule, was imaged both in agar (as a homogeneous test system) and in a phototrophic biofilm. The images collected were T1 weighted, where T1 is an MRI property of the biofilm and is dependent on Gd-DTPA concentration. A calibration protocol was applied to convert T1 parameter maps into concentration maps, thus revealing the spatially resolved concentrations of this tracer at different time intervals. Comparing the data obtained from the agar experiment with data from a one-dimensional diffusion model revealed that transport of Gd-DTPA in agar was purely via diffusion, with a diffusion coefficient of 7.2 × 10−10 m2 s−1. In contrast, comparison of data from the phototrophic biofilm experiment with data from a two-dimensional diffusion model revealed that transport of Gd-DTPA inside the biofilm was by both diffusion and advection, equivalent to a diffusion coefficient of 1.04 × 10−9 m2 s−1. This technology can be used to further explore mass transport processes in biofilms, either by using the wide range of commercially available paramagnetically tagged molecules and nanoparticles or by using bespoke tagged molecules. PMID:20435773
Assessing the sensitivity of diffusion MRI to detect neuronal activity directly.
Bai, Ruiliang; Stewart, Craig V; Plenz, Dietmar; Basser, Peter J
2016-03-22
Functional MRI (fMRI) is widely used to study brain function in the neurosciences. Unfortunately, conventional fMRI only indirectly assesses neuronal activity via hemodynamic coupling. Diffusion fMRI was proposed as a more direct and accurate fMRI method to detect neuronal activity, yet confirmative findings have proven difficult to obtain. Given that the underlying relation between tissue water diffusion changes and neuronal activity remains unclear, the rationale for using diffusion MRI to monitor neuronal activity has yet to be clearly established. Here, we studied the correlation between water diffusion and neuronal activity in vitro by simultaneous calcium fluorescence imaging and diffusion MR acquisition. We used organotypic cortical cultures from rat brains as a biological model system, in which spontaneous neuronal activity robustly emerges free of hemodynamic and other artifacts. Simultaneous fluorescent calcium images of neuronal activity are then directly correlated with diffusion MR signals now free of confounds typically encountered in vivo. Although a simultaneous increase of diffusion-weighted MR signals was observed together with the prolonged depolarization of neurons induced by pharmacological manipulations (in which cell swelling was demonstrated to play an important role), no evidence was found that diffusion MR signals directly correlate with normal spontaneous neuronal activity. These results suggest that, whereas current diffusion MR methods could monitor pathological conditions such as hyperexcitability, e.g., those seen in epilepsy, they do not appear to be sensitive or specific enough to detect or follow normal neuronal activity.
Assessing the sensitivity of diffusion MRI to detect neuronal activity directly
Bai, Ruiliang; Stewart, Craig V.; Plenz, Dietmar; Basser, Peter J.
2016-01-01
Functional MRI (fMRI) is widely used to study brain function in the neurosciences. Unfortunately, conventional fMRI only indirectly assesses neuronal activity via hemodynamic coupling. Diffusion fMRI was proposed as a more direct and accurate fMRI method to detect neuronal activity, yet confirmative findings have proven difficult to obtain. Given that the underlying relation between tissue water diffusion changes and neuronal activity remains unclear, the rationale for using diffusion MRI to monitor neuronal activity has yet to be clearly established. Here, we studied the correlation between water diffusion and neuronal activity in vitro by simultaneous calcium fluorescence imaging and diffusion MR acquisition. We used organotypic cortical cultures from rat brains as a biological model system, in which spontaneous neuronal activity robustly emerges free of hemodynamic and other artifacts. Simultaneous fluorescent calcium images of neuronal activity are then directly correlated with diffusion MR signals now free of confounds typically encountered in vivo. Although a simultaneous increase of diffusion-weighted MR signals was observed together with the prolonged depolarization of neurons induced by pharmacological manipulations (in which cell swelling was demonstrated to play an important role), no evidence was found that diffusion MR signals directly correlate with normal spontaneous neuronal activity. These results suggest that, whereas current diffusion MR methods could monitor pathological conditions such as hyperexcitability, e.g., those seen in epilepsy, they do not appear to be sensitive or specific enough to detect or follow normal neuronal activity. PMID:26941239
Sahara, Naruhiko; Perez, Pablo D.; Lin, Wen-Lang; Dickson, Dennis W.; Ren, Yan; Zeng, Huadong; Lewis, Jada; Febo, Marcelo
2016-01-01
Elevated expression of human hyperphosphorylated tau is associated with neuronal loss and white matter (WM) pathology in Alzheimer’s disease (AD) and related neurodegenerative disorders. Using in vivo diffusion tensor magnetic resonance imaging (DT-MRI) at 11.1 Tesla we measured age-related alterations in WM diffusion anisotropy indices in a mouse model of human tauopathy (rTg4510) and nontransgenic (nonTg) control mice at the age of 2.5, 4.5, and 8 months. Similar to previous DT-MRI studies in AD subjects, 8-month-old rTg4510 mice showed lower fractional anisotropy (FA) values in WM structures than nonTg. The low WM FA in rTg4510 mice was observed in the genu and splenium of the corpus callosum, anterior commissure, fimbria, and internal capsule and was associated with a higher radial diffusivity than nonTg. Interestingly, rTg4510 mice showed lower estimates for the mode of anisotropy than controls at 2.5 months suggesting that changes in this diffusivity metric are detectable at an early stage preceding severe tauopathy. Immunogold electron microscopy partly supports our diffusion tensor imaging findings. At the age of 4 months, rTg4510 mice show axonal tau inclusions and unmyelinated processes. At later ages (12 months and 14 months) we observed inclusions in myelin sheath, axons, and unmyelinated processes, and a “disorganized” pattern of myelinated fiber arrangement with enlarged inter-axonal spaces in rTg4510 but not in nonTg mice. Our data support a role for the progression of tau pathology in reduced WM integrity measured by DT-MRI. Further in vivo DT-MRI studies in the rTg4510 mouse should help better discern the detailed mechanisms of reduced FA and anisotropy mode, and the specific role of tau during neurodegeneration. PMID:24411290
Khachaturian, Mark Haig
2010-01-01
Awake monkey fMRI and diffusion MRI combined with conventional neuroscience techniques has the potential to study the structural and functional neural network. The majority of monkey fMRI and diffusion MRI experiments are performed with single coils which suffer from severe EPI distortions which limit resolution. By constructing phased array coils for monkey MRI studies, gains in SNR and anatomical accuracy (i.e., reduction of EPI distortions) can be achieved using parallel imaging. The major challenges associated with constructing phased array coils for monkeys are the variation in head size and space constraints. Here, we apply phased array technology to a 4-channel phased array coil capable of improving the resolution and image quality of full brain awake monkey fMRI and diffusion MRI experiments. The phased array coil is that can adapt to different rhesus monkey head sizes (ages 4-8) and fits in the limited space provided by monkey stereotactic equipment and provides SNR gains in primary visual cortex and anatomical accuracy in conjunction with parallel imaging and improves resolution in fMRI experiments by a factor of 2 (1.25 mm to 1.0 mm isotropic) and diffusion MRI experiments by a factor of 4 (1.5 mm to 0.9 mm isotropic).
Khachaturian, Mark Haig
2010-01-01
Awake monkey fMRI and diffusion MRI combined with conventional neuroscience techniques has the potential to study the structural and functional neural network. The majority of monkey fMRI and diffusion MRI experiments are performed with single coils which suffer from severe EPI distortions which limit resolution. By constructing phased array coils for monkey MRI studies, gains in SNR and anatomical accuracy (i.e., reduction of EPI distortions) can be achieved using parallel imaging. The major challenges associated with constructing phased array coils for monkeys are the variation in head size and space constraints. Here, we apply phased array technology to a 4-channel phased array coil capable of improving the resolution and image quality of full brain awake monkey fMRI and diffusion MRI experiments. The phased array coil is that can adapt to different rhesus monkey head sizes (ages 4–8) and fits in the limited space provided by monkey stereotactic equipment and provides SNR gains in primary visual cortex and anatomical accuracy in conjunction with parallel imaging and improves resolution in fMRI experiments by a factor of 2 (1.25 mm to 1.0 mm isotropic) and diffusion MRI experiments by a factor of 4 (1.5 mm to 0.9 mm isotropic). PMID:21243106
NASA Astrophysics Data System (ADS)
Song, Yongchen; Hao, Min; Zhao, Yuechao; Zhang, Liang
2014-12-01
In this study, the dual-chamber pressure decay method and magnetic resonance imaging (MRI) were used to dynamically visualize the gas diffusion process in liquid-saturated porous media, and the relationship of concentration-distance for gas diffusing into liquid-saturated porous media at different times were obtained by MR images quantitative analysis. A non-iterative finite volume method was successfully applied to calculate the local gas diffusion coefficient in liquid-saturated porous media. The results agreed very well with the conventional pressure decay method, thus it demonstrates that the method was feasible of determining the local diffusion coefficient of gas in liquid-saturated porous media at different times during diffusion process.
Clinical utility for diffusion MRI sequence in emergency and inpatient spine protocols.
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.
Single-shot turbo spin echo acquisition for in vivo cardiac diffusion MRI.
Edalati, Masoud; Lee, Gregory R; Hui Wang; Taylor, Michael D; Li, Yu Y
2016-08-01
Diffusion MRI offers the ability to noninvasively characterize the microstructure of myocardium tissue and detect disease related pathology in cardiovascular examination. This study investigates the feasibility of in vivo cardiac diffusion MRI under free-breathing condition. A high-speed imaging technique, correlation imaging, is used to enable single-shot turbo spin echo for free-breathing cardiac data acquisition. The obtained in vivo cardiac diffusion-weighted images illustrate robust image quality and minor geometry distortions. The resultant diffusion scalar maps show reliable quantitative values consistent with those previously published in the literature. It is demonstrated that this technique has the potential for in vivo free-breathing cardiac diffusion MRI.
Distortion correction for diffusion-weighted MRI tractography and fMRI in the temporal lobes.
Embleton, Karl V; Haroon, Hamied A; Morris, David M; Ralph, Matthew A Lambon; Parker, Geoff J M
2010-10-01
Single shot echo-planar imaging (EPI) sequences are currently the most commonly used sequences for diffusion-weighted imaging (DWI) and functional magnetic resonance imaging (fMRI) as they allow relatively high signal to noise with rapid acquisition time. A major drawback of EPI is the substantial geometric distortion and signal loss that can occur due to magnetic field inhomogeneities close to air-tissue boundaries. If DWI-based tractography and fMRI are to be applied to these regions, then the distortions must be accurately corrected to achieve meaningful results. We describe robust acquisition and processing methods for correcting such distortions in spin echo (SE) EPI using a variant of the reversed direction k space traversal method with a number of novel additions. We demonstrate that dual direction k space traversal with maintained diffusion-encoding gradient strength and direction results in correction of the great majority of eddy current-associated distortions in DWI, in addition to those created by variations in magnetic susceptibility. We also provide examples to demonstrate that the presence of severe distortions cannot be ignored if meaningful tractography results are desired. The distortion correction routine was applied to SE-EPI fMRI acquisitions and allowed detection of activation in the temporal lobe that had been previously found using PET but not conventional fMRI. © 2010 Wiley-Liss, Inc.
Diffusion imaging quality control via entropy of principal direction distribution.
Farzinfar, Mahshid; Oguz, Ipek; Smith, Rachel G; Verde, Audrey R; Dietrich, Cheryl; Gupta, Aditya; Escolar, Maria L; Piven, Joseph; Pujol, Sonia; Vachet, Clement; Gouttard, Sylvain; Gerig, Guido; Dager, Stephen; McKinstry, Robert C; Paterson, Sarah; Evans, Alan C; Styner, Martin A
2013-11-15
Diffusion MR imaging has received increasing attention in the neuroimaging community, as it yields new insights into the microstructural organization of white matter that are not available with conventional MRI techniques. While the technology has enormous potential, diffusion MRI suffers from a unique and complex set of image quality problems, limiting the sensitivity of studies and reducing the accuracy of findings. Furthermore, the acquisition time for diffusion MRI is longer than conventional MRI due to the need for multiple acquisitions to obtain directionally encoded Diffusion Weighted Images (DWI). This leads to increased motion artifacts, reduced signal-to-noise ratio (SNR), and increased proneness to a wide variety of artifacts, including eddy-current and motion artifacts, "venetian blind" artifacts, as well as slice-wise and gradient-wise inconsistencies. Such artifacts mandate stringent Quality Control (QC) schemes in the processing of diffusion MRI data. Most existing QC procedures are conducted in the DWI domain and/or on a voxel level, but our own experiments show that these methods often do not fully detect and eliminate certain types of artifacts, often only visible when investigating groups of DWI's or a derived diffusion model, such as the most-employed diffusion tensor imaging (DTI). Here, we propose a novel regional QC measure in the DTI domain that employs the entropy of the regional distribution of the principal directions (PD). The PD entropy quantifies the scattering and spread of the principal diffusion directions and is invariant to the patient's position in the scanner. High entropy value indicates that the PDs are distributed relatively uniformly, while low entropy value indicates the presence of clusters in the PD distribution. The novel QC measure is intended to complement the existing set of QC procedures by detecting and correcting residual artifacts. Such residual artifacts cause directional bias in the measured PD and here called dominant direction artifacts. Experiments show that our automatic method can reliably detect and potentially correct such artifacts, especially the ones caused by the vibrations of the scanner table during the scan. The results further indicate the usefulness of this method for general quality assessment in DTI studies. Copyright © 2013 Elsevier Inc. All rights reserved.
Diffusion imaging quality control via entropy of principal direction distribution
Oguz, Ipek; Smith, Rachel G.; Verde, Audrey R.; Dietrich, Cheryl; Gupta, Aditya; Escolar, Maria L.; Piven, Joseph; Pujol, Sonia; Vachet, Clement; Gouttard, Sylvain; Gerig, Guido; Dager, Stephen; McKinstry, Robert C.; Paterson, Sarah; Evans, Alan C.; Styner, Martin A.
2013-01-01
Diffusion MR imaging has received increasing attention in the neuroimaging community, as it yields new insights into the microstructural organization of white matter that are not available with conventional MRI techniques. While the technology has enormous potential, diffusion MRI suffers from a unique and complex set of image quality problems, limiting the sensitivity of studies and reducing the accuracy of findings. Furthermore, the acquisition time for diffusion MRI is longer than conventional MRI due to the need for multiple acquisitions to obtain directionally encoded Diffusion Weighted Images (DWI). This leads to increased motion artifacts, reduced signal-to-noise ratio (SNR), and increased proneness to a wide variety of artifacts, including eddy-current and motion artifacts, “venetian blind” artifacts, as well as slice-wise and gradient-wise inconsistencies. Such artifacts mandate stringent Quality Control (QC) schemes in the processing of diffusion MRI data. Most existing QC procedures are conducted in the DWI domain and/or on a voxel level, but our own experiments show that these methods often do not fully detect and eliminate certain types of artifacts, often only visible when investigating groups of DWI's or a derived diffusion model, such as the most-employed diffusion tensor imaging (DTI). Here, we propose a novel regional QC measure in the DTI domain that employs the entropy of the regional distribution of the principal directions (PD). The PD entropy quantifies the scattering and spread of the principal diffusion directions and is invariant to the patient's position in the scanner. High entropy value indicates that the PDs are distributed relatively uniformly, while low entropy value indicates the presence of clusters in the PD distribution. The novel QC measure is intended to complement the existing set of QC procedures by detecting and correcting residual artifacts. Such residual artifacts cause directional bias in the measured PD and here called dominant direction artifacts. Experiments show that our automatic method can reliably detect and potentially correct such artifacts, especially the ones caused by the vibrations of the scanner table during the scan. The results further indicate the usefulness of this method for general quality assessment in DTI studies. PMID:23684874
Structural network efficiency is associated with cognitive impairment in small-vessel disease.
Lawrence, Andrew J; Chung, Ai Wern; Morris, Robin G; Markus, Hugh S; Barrick, Thomas R
2014-07-22
To characterize brain network connectivity impairment in cerebral small-vessel disease (SVD) and its relationship with MRI disease markers and cognitive impairment. A cross-sectional design applied graph-based efficiency analysis to deterministic diffusion tensor tractography data from 115 patients with lacunar infarction and leukoaraiosis and 50 healthy individuals. Structural connectivity was estimated between 90 cortical and subcortical brain regions and efficiency measures of resulting graphs were analyzed. Networks were compared between SVD and control groups, and associations between efficiency measures, conventional MRI disease markers, and cognitive function were tested. Brain diffusion tensor tractography network connectivity was significantly reduced in SVD: networks were less dense, connection weights were lower, and measures of network efficiency were significantly disrupted. The degree of brain network disruption was associated with MRI measures of disease severity and cognitive function. In multiple regression models controlling for confounding variables, associations with cognition were stronger for network measures than other MRI measures including conventional diffusion tensor imaging measures. A total mediation effect was observed for the association between fractional anisotropy and mean diffusivity measures and executive function and processing speed. Brain network connectivity in SVD is disturbed, this disturbance is related to disease severity, and within a mediation framework fully or partly explains previously observed associations between MRI measures and SVD-related cognitive dysfunction. These cross-sectional results highlight the importance of network disruption in SVD and provide support for network measures as a disease marker in treatment studies. © 2014 American Academy of Neurology.
Structural network efficiency is associated with cognitive impairment in small-vessel disease
Chung, Ai Wern; Morris, Robin G.; Markus, Hugh S.; Barrick, Thomas R.
2014-01-01
Objective: To characterize brain network connectivity impairment in cerebral small-vessel disease (SVD) and its relationship with MRI disease markers and cognitive impairment. Methods: A cross-sectional design applied graph-based efficiency analysis to deterministic diffusion tensor tractography data from 115 patients with lacunar infarction and leukoaraiosis and 50 healthy individuals. Structural connectivity was estimated between 90 cortical and subcortical brain regions and efficiency measures of resulting graphs were analyzed. Networks were compared between SVD and control groups, and associations between efficiency measures, conventional MRI disease markers, and cognitive function were tested. Results: Brain diffusion tensor tractography network connectivity was significantly reduced in SVD: networks were less dense, connection weights were lower, and measures of network efficiency were significantly disrupted. The degree of brain network disruption was associated with MRI measures of disease severity and cognitive function. In multiple regression models controlling for confounding variables, associations with cognition were stronger for network measures than other MRI measures including conventional diffusion tensor imaging measures. A total mediation effect was observed for the association between fractional anisotropy and mean diffusivity measures and executive function and processing speed. Conclusions: Brain network connectivity in SVD is disturbed, this disturbance is related to disease severity, and within a mediation framework fully or partly explains previously observed associations between MRI measures and SVD-related cognitive dysfunction. These cross-sectional results highlight the importance of network disruption in SVD and provide support for network measures as a disease marker in treatment studies. PMID:24951477
Joint 6D k-q Space Compressed Sensing for Accelerated High Angular Resolution Diffusion MRI.
Cheng, Jian; Shen, Dinggang; Basser, Peter J; Yap, Pew-Thian
2015-01-01
High Angular Resolution Diffusion Imaging (HARDI) avoids the Gaussian. diffusion assumption that is inherent in Diffusion Tensor Imaging (DTI), and is capable of characterizing complex white matter micro-structure with greater precision. However, HARDI methods such as Diffusion Spectrum Imaging (DSI) typically require significantly more signal measurements than DTI, resulting in prohibitively long scanning times. One of the goals in HARDI research is therefore to improve estimation of quantities such as the Ensemble Average Propagator (EAP) and the Orientation Distribution Function (ODF) with a limited number of diffusion-weighted measurements. A popular approach to this problem, Compressed Sensing (CS), affords highly accurate signal reconstruction using significantly fewer (sub-Nyquist) data points than required traditionally. Existing approaches to CS diffusion MRI (CS-dMRI) mainly focus on applying CS in the q-space of diffusion signal measurements and fail to take into consideration information redundancy in the k-space. In this paper, we propose a framework, called 6-Dimensional Compressed Sensing diffusion MRI (6D-CS-dMRI), for reconstruction of the diffusion signal and the EAP from data sub-sampled in both 3D k-space and 3D q-space. To our knowledge, 6D-CS-dMRI is the first work that applies compressed sensing in the full 6D k-q space and reconstructs the diffusion signal in the full continuous q-space and the EAP in continuous displacement space. Experimental results on synthetic and real data demonstrate that, compared with full DSI sampling in k-q space, 6D-CS-dMRI yields excellent diffusion signal and EAP reconstruction with low root-mean-square error (RMSE) using 11 times less samples (3-fold reduction in k-space and 3.7-fold reduction in q-space).
Joint reconstruction of PET-MRI by exploiting structural similarity
NASA Astrophysics Data System (ADS)
Ehrhardt, Matthias J.; Thielemans, Kris; Pizarro, Luis; Atkinson, David; Ourselin, Sébastien; Hutton, Brian F.; Arridge, Simon R.
2015-01-01
Recent advances in technology have enabled the combination of positron emission tomography (PET) with magnetic resonance imaging (MRI). These PET-MRI scanners simultaneously acquire functional PET and anatomical or functional MRI data. As function and anatomy are not independent of one another the images to be reconstructed are likely to have shared structures. We aim to exploit this inherent structural similarity by reconstructing from both modalities in a joint reconstruction framework. The structural similarity between two modalities can be modelled in two different ways: edges are more likely to be at similar positions and/or to have similar orientations. We analyse the diffusion process generated by minimizing priors that encapsulate these different models. It turns out that the class of parallel level set priors always corresponds to anisotropic diffusion which is sometimes forward and sometimes backward diffusion. We perform numerical experiments where we jointly reconstruct from blurred Radon data with Poisson noise (PET) and under-sampled Fourier data with Gaussian noise (MRI). Our results show that both modalities benefit from each other in areas of shared edge information. The joint reconstructions have less artefacts and sharper edges compared to separate reconstructions and the ℓ2-error can be reduced in all of the considered cases of under-sampling.
Recovery of White Matter following Pediatric Traumatic Brain Injury Depends on Injury Severity.
Genc, Sila; Anderson, Vicki; Ryan, Nicholas P; Malpas, Charles B; Catroppa, Cathy; Beauchamp, Miriam H; Silk, Timothy J
2017-02-15
Previous studies in pediatric traumatic brain injury (TBI) have been variable in describing the effects of injury severity on white-matter development. The present study used diffusion tensor imaging to investigate prospective sub-acute and longitudinal relationships between early clinical indicators of injury severity, diffusion metrics, and neuropsychological outcomes. Pediatric patients with TBI underwent magnetic resonance imaging (MRI) (n = 78, mean [M] = 10.56, standard deviation [SD] = 2.21 years) at the sub-acute stage after injury (M = 5.55, SD = 3.05 weeks), and typically developing children were also included and imaged (n = 30, M = 10.60, SD = 2.88 years). A sub-set of the patients with TBI (n = 15) was followed up with MRI 2 years post-injury. Diffusion MRI images were acquired at sub-acute and 2-year follow-up time points and analyzed using Tract-Based Spatial Statistics. At the sub-acute stage, mean diffusivity and axial diffusivity were significantly higher in the TBI group compared with matched controls (p < 0.05). TBI severity significantly predicted diffusion profiles at the sub-acute and 2-year post-injury MRI. Patients with more severe TBI also exhibited poorer information processing speed at 6-months post-injury, which in turn correlated with their diffusion metrics. These findings highlight that the severity of the injury not only has an impact on white-matter microstructure, it also impacts its recovery over time. Moreover, findings suggest that sub-acute microstructural changes may represent a useful prognostic marker to identify children at elevated risk for longer term deficits.
The use of Polyvinyl Pyrrolidone (PVP) solutions of varying concentrations as phantoms for diffusion MRI calibration and quality control is disclosed. This diffusion MRI phantom material is already being adopted by radiologists for quality control and assurance in clinical studies.
Song, G; Luo, T; Dong, L; Liu, Q
2017-07-03
Solution reflux and edema hamper the convection-enhanced delivery of the standard treatment for glioma. Therefore, a real-time magnetic resonance imaging (MRI) method was developed to monitor the dosing process, but a quantitative analysis of local diffusion and clearance parameters has not been assessed. The objective of this study was to compare diffusion into the extracellular space (ECS) at different stages of rat C6 gliomas, and analyze the effects of the extracellular matrix (ECM) on the diffusion process. At 10 and 20 days, after successful glioma modeling, gadolinium-diethylenetriamine pentaacetic acid (Gd-DTPA) was introduced into the ECS of rat C6 gliomas. Diffusion parameters and half-life of the reagent were then detected using MRI, and quantified according to the mathematical model of diffusion. The main ECM components [chondroitin sulfate proteoglycans (CSPGs), collagen IV, and tenascin C] were detected by immunohistochemical and immunoblot analyses. In 20-day gliomas, Gd-DTPA diffused more slowly and derived higher tortuosity, with lower clearance rate and longer half-life compared to 10-day gliomas. The increased glioma ECM was associated with different diffusion and clearance parameters in 20-day rat gliomas compared to 10-day gliomas. ECS parameters were altered with C6 glioma progression from increased ECM content. Our study might help better understand the glioma microenvironment and provide benefits for interstitial drug delivery to treat brain gliomas.
The Weakly Nonlinear Magnetorotational Instability in a Local Geometry
DOE Office of Scientific and Technical Information (OSTI.GOV)
Clark, S. E.; Oishi, Jeffrey S., E-mail: seclark@astro.columbia.edu
2017-05-20
The magnetorotational instability (MRI) is a fundamental process of accretion disk physics, but its saturation mechanism remains poorly understood despite considerable theoretical and computational effort. We present a multiple-scales analysis of the non-ideal MRI in the weakly nonlinear regime—that is, when the most unstable MRI mode has a growth rate asymptotically approaching zero from above. Here, we develop our theory in a local, Cartesian channel. Our results confirm the finding by Umurhan et al. that the perturbation amplitude follows a Ginzburg–Landau equation. We further find that the Ginzburg–Landau equation will arise for the local MRI system with shear-periodic boundary conditions,more » when the effects of ambipolar diffusion are considered. A detailed force balance for the saturated azimuthal velocity and vertical magnetic field demonstrates that, even when diffusive effects are important, the bulk flow saturates via the combined processes of reducing the background shear and rearranging and strengthening the background vertical magnetic field. We directly simulate the Ginzburg–Landau amplitude evolution for our system, and demonstrate the pattern formation our model predicts on long scales of length- and timescales. We compare the weakly nonlinear theory results to a direct numerical simulation of the MRI in a thin-gap Taylor Couette flow.« less
Can we develop pathology-specific MRI contrast for "MR-negative" epilepsy?
Feindel, Kirk W
2013-05-01
Recent improvements in magnetic resonance imaging (MRI) hardware, software, and analysis routines are helping to put cases of "MR-negative" epilepsy on the decline. However, most standard-of-care MRI relies on careful manipulation and presentation of T1, T2, and diffusion-weighted contrast, which characterize the behavior of water in "bulk" tissue rather than providing pathology-specific contrast. Research efforts in MR physics continue to identify and develop novel theory, and methods such as diffusional kurtosis imaging (DKI) and temporal diffusion spectroscopy that can better characterize tissue substructure, and chemical exchange saturation transfer (CEST) that can target underlying biochemical processes. The potential role of each technique in targeting pathologies implicated in "MR-negative" epilepsy is outlined herein. Wiley Periodicals, Inc. © 2013 International League Against Epilepsy.
Perspectives on Porous Media MR in Clinical MRI
NASA Astrophysics Data System (ADS)
Sigmund, E. E.
2011-03-01
Many goals and challenges of research in natural or synthetic porous media are mirrored in quantitative medical MRI. This review will describe examples where MR techniques used in porous media (particularly diffusion-weighted imaging (DWI)) are applied to physiological pathologies. Tissue microstructure is one area with great overlap with porous media science. Diffusion-weighting (esp. in neurological tissue) has motivated models with explicit physical dimensions, statistical parameters, empirical descriptors, or hybrids thereof. Another clinically relevant microscopic process is active flow. Renal (kidney) tissue possesses significant active vascular / tubular transport that manifests as "pseudodiffusion." Cancerous lesions involve anomalies in both structure and flow. The tools of magnetic resonance and their interpretation in porous media has had great impact on clinical MRI, and continued cross-fertilization of ideas can only enhance the progress of both fields.
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.
Traumatic Brain Injury Diffusion Magnetic Resonance Imaging Research Roadmap Development Project
2011-10-01
promising technology on the horizon is the Diffusion Tensor Imaging ( DTI ). Diffusion tensor imaging ( DTI ) is a magnetic resonance imaging (MRI)-based...in the brain. The potential for DTI to improve our understanding of TBI has not been fully explored and challenges associated with non-existent...processing tools, quality control standards, and a shared image repository. The recommendations will be disseminated and pilot tested. A DTI of TBI
Whole-body MR imaging, bone diffusion imaging: how and why?
Jaramillo, Diego
2010-06-01
Whole-body MRI (W-B MRI) and diffusion-weighted imaging (DWI) are two novel techniques that greatly facilitate the evaluation of many disorders of childhood. In the musculoskeletal system, these techniques primarily aid in the evaluation of the marrow, although there is increasing interest in the study of soft-tissue abnormalities with W-B MRI and of cartilage with DWI.The normal pattern of marrow transformation affects both modalities throughout childhood. Haematopoietic marrow has a much higher signal intensity than fatty marrow on W-B MRI short tau inversion recovery (STIR) images (Darge et al. Eur J Radiol 68:289-298, 2008). Diffusion is greater in haematopoietic marrow than in fatty marrow and decreases in the skeleton with age (Jaramillo et al. Pediatr Radiol 34:S48, 2004). It is important therefore to remember that the entire skeleton is haematopoietic at birth and that there is a process of marrow transformation to fatty marrow. Marrow conversion proceeds from the fingers to the shoulders and from the toes to the hips. Within each bone, fatty marrow transformation begins in the epiphyses, and within the shaft of the long bones fatty marrow transformation begins at the diaphysis and proceeds towards the metaphyses.
Williams, Rebecca J; Reutens, David C; Hocking, Julia
2015-11-01
Decreased water displacement following increased neural activity has been observed using diffusion-weighted functional MRI (DfMRI) at high b-values. The physiological mechanisms underlying the diffusion signal change may be unique from the standard blood oxygenation level-dependent (BOLD) contrast and closer to the source of neural activity. Whether DfMRI reflects neural activity more directly than BOLD outside the primary cerebral regions remains unclear. Colored and achromatic Mondrian visual stimuli were statistically contrasted to functionally localize the human color center Area V4 in neurologically intact adults. Spatial and temporal properties of DfMRI and BOLD activation were examined across regions of the visual cortex. At the individual level, DfMRI activation patterns showed greater spatial specificity to V4 than BOLD. The BOLD activation patterns were more prominent in the primary visual cortex than DfMRI, where activation was localized to the ventral temporal lobe. Temporally, the diffusion signal change in V4 and V1 both preceded the corresponding hemodynamic response, however the early diffusion signal change was more evident in V1. DfMRI may be of use in imaging applications implementing cognitive subtraction paradigms, and where highly precise individual functional localization is required.
Diffusion tensor tracking of neuronal fiber pathways in the living human brain
NASA Astrophysics Data System (ADS)
Lori, Nicolas Francisco
2001-11-01
The technique of diffusion tensor tracking (DTT) is described, in which diffusion tensor magnetic resonance imaging (DT-MRI) data are processed to allow the visualization of white matter (WM) tracts in a living human brain. To illustrate the methods, a detailed description is given of the physics of DT-MRI, the structure of the DT-MRI experiment, the computer tools that were developed to visualize WM tracts, the anatomical consistency of the obtained WM tracts, and the accuracy and precision of DTT using computer simulations. When presenting the physics of DT-MRI, a completely quantum-mechanical view of DT-MRI is given where some of the results are new. Examples of anatomical tracts viewed using DTT are presented, including the genu and the splenium of the corpus callosum, the ventral pathway with its amygdala connection highlighted, the geniculo- calcarine tract separated into anterior and posterior parts, the geniculo-calcarine tract defined using functional magnetic resonance imaging (MRI), and U- fibers. In the simulation, synthetic DT-MRI data were constructed that would be obtained for a cylindrical WM tract with a helical trajectory surrounded by gray matter. Noise was then added to the synthetic DT-MRI data, and DTT trajectories were calculated using the noisy data (realistic tracks). Simulated DTT errors were calculated as the vector distance between the realistic tracks and the ideal trajectory. The simulation tested the effects of a comprehensive set of experimental conditions, including voxel size, data sampling, data averaging, type of tract tissue, tract diameter and type of tract trajectory. Simulated DTT accuracy and precision were typically below the voxel dimension, and precision was compatible with the experimental results.
MR Scanner Systems Should Be Adequately Characterized in Diffusion-MRI of the Breast
Giannelli, Marco; Sghedoni, Roberto; Iacconi, Chiara; Iori, Mauro; Traino, Antonio Claudio; Guerrisi, Maria; Mascalchi, Mario; Toschi, Nicola; Diciotti, Stefano
2014-01-01
Breast imaging represents a relatively recent and promising field of application of quantitative diffusion-MRI techniques. In view of the importance of guaranteeing and assessing its reliability in clinical as well as research settings, the aim of this study was to specifically characterize how the main MR scanner system-related factors affect quantitative measurements in diffusion-MRI of the breast. In particular, phantom acquisitions were performed on three 1.5 T MR scanner systems by different manufacturers, all equipped with a dedicated multi-channel breast coil as well as acquisition sequences for diffusion-MRI of the breast. We assessed the accuracy, inter-scan and inter-scanner reproducibility of the mean apparent diffusion coefficient measured along the main orthogonal directions (
2010-01-01
Objective Uncontrolled proliferation of health technologies (HT) is one contributor to the increasing pressure on health systems to adopt new technologies. With limited resources, policy-makers encounter difficulties in fulfilling their responsibility to meet the healthcare needs of the population. The aim of this study is to explore how policy-makers' reason about the diffusion and utilization of health technologies in Iran using magnetic resonance imaging (MRI) and interferon beta as tracers. Method This qualitative exploration complements quantitative data generated in a research project investigating the diffusion and utilization of MRI and interferon beta in Iran. Qualitative semi-structured interviews were conducted with 13 informants in different positions and levels of authority in the Ministry of Health (MOH), University of Medical Sciences, Health Insurance Organizations, and Parliament. The data was analysed using the framework approach. Findings Although policy-makers appeared to be positive to health technology assessment (HTA), the processes of policy-making described by the interviewees did not seem to be based on a full understanding of this (discipline). Several obstacles to applying knowledge about HT and HTA were described. The current official plan for MRI adoption and diffusion in the country was said not to be followed, and no such plan was described for interferon beta. Instead, market forces such as advertising, and physician and consumer demand, appear to have strong influence on HT diffusion and use. Dual practice may have increased the induced demand and also reduced the supervision of the private sector by the MOH. Conclusion Management instability and lack of coordination in the MOH were found to be important obstacles to accumulation of knowledge and experience which, in turn, could have led to suboptimal managerial and policy-making processes. Furthermore marketing should be controlled in order to avoid creating unnecessary patient demands and negative influences on physicians' behavior. PMID:20370906
Palesh, Mohammad; Tishelman, Carol; Fredrikson, Sten; Jamshidi, Hamidreza; Tomson, Göran; Emami, Azita
2010-04-06
Uncontrolled proliferation of health technologies (HT) is one contributor to the increasing pressure on health systems to adopt new technologies. With limited resources, policy-makers encounter difficulties in fulfilling their responsibility to meet the healthcare needs of the population. The aim of this study is to explore how policy-makers' reason about the diffusion and utilization of health technologies in Iran using magnetic resonance imaging (MRI) and interferon beta as tracers. This qualitative exploration complements quantitative data generated in a research project investigating the diffusion and utilization of MRI and interferon beta in Iran. Qualitative semi-structured interviews were conducted with 13 informants in different positions and levels of authority in the Ministry of Health (MOH), University of Medical Sciences, Health Insurance Organizations, and Parliament. The data was analysed using the framework approach. Although policy-makers appeared to be positive to health technology assessment (HTA), the processes of policy-making described by the interviewees did not seem to be based on a full understanding of this (discipline). Several obstacles to applying knowledge about HT and HTA were described. The current official plan for MRI adoption and diffusion in the country was said not to be followed, and no such plan was described for interferon beta. Instead, market forces such as advertising, and physician and consumer demand, appear to have strong influence on HT diffusion and use. Dual practice may have increased the induced demand and also reduced the supervision of the private sector by the MOH. Management instability and lack of coordination in the MOH were found to be important obstacles to accumulation of knowledge and experience which, in turn, could have led to suboptimal managerial and policy-making processes. Furthermore marketing should be controlled in order to avoid creating unnecessary patient demands and negative influences on physicians' behavior.
Brain structural changes in spasmodic dysphonia: A multimodal magnetic resonance imaging study.
Kostic, Vladimir S; Agosta, Federica; Sarro, Lidia; Tomić, Aleksandra; Kresojević, Nikola; Galantucci, Sebastiano; Svetel, Marina; Valsasina, Paola; Filippi, Massimo
2016-04-01
The pathophysiology of spasmodic dysphonia is poorly understood. This study evaluated patterns of cortical morphology, basal ganglia, and white matter microstructural alterations in patients with spasmodic dysphonia relative to healthy controls. T1-weighted and diffusion tensor magnetic resonance imaging (MRI) scans were obtained from 13 spasmodic dysphonia patients and 30 controls. Tract-based spatial statistics was applied to compare diffusion tensor MRI indices (i.e., mean, radial and axial diffusivities, and fractional anisotropy) between groups on a voxel-by-voxel basis. Cortical measures were analyzed using surface-based morphometry. Basal ganglia were segmented on T1-weighted images, and volumes and diffusion tensor MRI metrics of nuclei were measured. Relative to controls, patients with spasmodic dysphonia showed increased cortical surface area of the primary somatosensory cortex bilaterally in a region consistent with the buccal sensory representation, as well as right primary motor cortex, left superior temporal, supramarginal and superior frontal gyri. A decreased cortical area was found in the rolandic operculum bilaterally, left superior/inferior parietal and lingual gyri, as well as in the right angular gyrus. Compared to controls, spasmodic dysphonia patients showed increased diffusivities and decreased fractional anisotropy of the corpus callosum and major white matter tracts, in the right hemisphere. Altered diffusion tensor MRI measures were found in the right caudate and putamen nuclei with no volumetric changes. Multi-level alterations in voice-controlling networks, that included regions devoted not only to sensorimotor integration, motor preparation and motor execution, but also processing of auditory and visual information during speech, might have a role in the pathophysiology of spasmodic dysphonia. Copyright © 2016 Elsevier Ltd. All rights reserved.
Nitkunan, Arani; Barrick, Tom R; Charlton, Rebecca A; Clark, Chris A; Markus, Hugh S
2008-07-01
Cerebral small vessel disease is the most common cause of vascular dementia. Interest in using MRI parameters as surrogate markers of disease to assess therapies is increasing. In patients with symptomatic sporadic small vessel disease, we determined which MRI parameters best correlated with cognitive function on cross-sectional analysis and which changed over a period of 1 year. Thirty-five patients with lacunar stroke and leukoaraiosis were recruited. They underwent multimodal MRI (brain volume, fluid-attenuated inversion recovery lesion load, lacunar infarct number, fractional anisotropy, and mean diffusivity from diffusion tensor imaging) and neuropsychological testing. Twenty-seven agreed to reattend for repeat MRI and neuropsychology at 1 year. An executive function score correlated most strongly with diffusion tensor imaging (fractional anisotropy histogram, r=-0.640, P=0.004) and brain volume (r=0.501, P=0.034). Associations with diffusion tensor imaging were stronger than with all other MRI parameters. On multiple regression of all imaging parameters, a model that contained brain volume and fractional anisotropy, together with age, gender, and premorbid IQ, explained 74% of the variance of the executive function score (P=0.0001). Changes in mean diffusivity and fractional anisotropy were detectable over the 1-year follow-up; in contrast, no change in other MRI parameters was detectable over this time period. A multimodal MRI model explains a large proportion of the variation in executive function in cerebral small vessel disease. In particular, diffusion tensor imaging correlates best with executive function and is the most sensitive to change. This supports the use of MRI, in particular diffusion tensor imaging, as a surrogate marker in treatment trials.
[From Brownian motion to mind imaging: diffusion MRI].
Le Bihan, Denis
2006-11-01
The success of diffusion MRI, which was introduced in the mid 1980s is deeply rooted in the powerful concept that during their random, diffusion-driven movements water molecules probe tissue structure at a microscopic scale well beyond the usual image resolution. The observation of these movements thus provides valuable information on the structure and the geometric organization of tissues. The most successful application of diffusion MRI has been in brain ischemia, following the discovery that water diffusion drops at a very early stage of the ischemic event. Diffusion MRI provides some patients with the opportunity to receive suitable treatment at a very acute stage when brain tissue might still be salvageable. On the other hand, diffusion is modulated by the spatial orientation of large bundles of myelinated axons running in parallel through in brain white matter. This feature can be exploited to map out the orientation in space of the white matter tracks and to visualize the connections between different parts of the brain on an individual basis. Furthermore, recent data suggest that diffusion MRI may also be used to visualize rapid dynamic tissue changes, such as neuronal swelling, associated with cortical activation, offering a new and direct approach to brain functional imaging.
Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank.
Alfaro-Almagro, Fidel; Jenkinson, Mark; Bangerter, Neal K; Andersson, Jesper L R; Griffanti, Ludovica; Douaud, Gwenaëlle; Sotiropoulos, Stamatios N; Jbabdi, Saad; Hernandez-Fernandez, Moises; Vallee, Emmanuel; Vidaurre, Diego; Webster, Matthew; McCarthy, Paul; Rorden, Christopher; Daducci, Alessandro; Alexander, Daniel C; Zhang, Hui; Dragonu, Iulius; Matthews, Paul M; Miller, Karla L; Smith, Stephen M
2018-02-01
UK Biobank is a large-scale prospective epidemiological study with all data accessible to researchers worldwide. It is currently in the process of bringing back 100,000 of the original participants for brain, heart and body MRI, carotid ultrasound and low-dose bone/fat x-ray. The brain imaging component covers 6 modalities (T1, T2 FLAIR, susceptibility weighted MRI, Resting fMRI, Task fMRI and Diffusion MRI). Raw and processed data from the first 10,000 imaged subjects has recently been released for general research access. To help convert this data into useful summary information we have developed an automated processing and QC (Quality Control) pipeline that is available for use by other researchers. In this paper we describe the pipeline in detail, following a brief overview of UK Biobank brain imaging and the acquisition protocol. We also describe several quantitative investigations carried out as part of the development of both the imaging protocol and the processing pipeline. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Individual classification of Alzheimer's disease with diffusion magnetic resonance imaging.
Schouten, Tijn M; Koini, Marisa; Vos, Frank de; Seiler, Stephan; Rooij, Mark de; Lechner, Anita; Schmidt, Reinhold; Heuvel, Martijn van den; Grond, Jeroen van der; Rombouts, Serge A R B
2017-05-15
Diffusion magnetic resonance imaging (MRI) is a powerful non-invasive method to study white matter integrity, and is sensitive to detect differences in Alzheimer's disease (AD) patients. Diffusion MRI may be able to contribute towards reliable diagnosis of AD. We used diffusion MRI to classify AD patients (N=77), and controls (N=173). We use different methods to extract information from the diffusion MRI data. First, we use the voxel-wise diffusion tensor measures that have been skeletonised using tract based spatial statistics. Second, we clustered the voxel-wise diffusion measures with independent component analysis (ICA), and extracted the mixing weights. Third, we determined structural connectivity between Harvard Oxford atlas regions with probabilistic tractography, as well as graph measures based on these structural connectivity graphs. Classification performance for voxel-wise measures ranged between an AUC of 0.888, and 0.902. The ICA-clustered measures ranged between an AUC of 0.893, and 0.920. The AUC for the structural connectivity graph was 0.900, while graph measures based upon this graph ranged between an AUC of 0.531, and 0.840. All measures combined with a sparse group lasso resulted in an AUC of 0.896. Overall, fractional anisotropy clustered into ICA components was the best performing measure. These findings may be useful for future incorporation of diffusion MRI into protocols for AD classification, or as a starting point for early detection of AD using diffusion MRI. Copyright © 2017 Elsevier Inc. All rights reserved.
Complementary aspects of diffusion imaging and fMRI; I: structure and function.
Mulkern, Robert V; Davis, Peter E; Haker, Steven J; Estepar, Raul San Jose; Panych, Lawrence P; Maier, Stephan E; Rivkin, Michael J
2006-05-01
Studying the intersection of brain structure and function is an important aspect of modern neuroscience. The development of magnetic resonance imaging (MRI) over the last 25 years has provided new and powerful tools for the study of brain structure and function. Two tools in particular, diffusion imaging and functional MRI (fMRI), are playing increasingly important roles in elucidating the complementary aspects of brain structure and function. In this work, we review basic technical features of diffusion imaging and fMRI for studying the integrity of white matter structural components and for determining the location and extent of cortical activation in gray matter, respectively. We then review a growing body of literature in which the complementary aspects of diffusion imaging and fMRI, applied as separate examinations but analyzed in tandem, have been exploited to enhance our knowledge of brain structure and function.
Hagberg, Gisela E; Mamedov, Ilgar; Power, Anthony; Beyerlein, Michael; Merkle, Hellmut; Kiselev, Valerij G; Dhingra, Kirti; Kubìček, Vojtĕch; Angelovski, Goran; Logothetis, Nikos K
2014-01-01
Calcium-sensitive MRI contrast agents can only yield quantitative results if the agent concentration in the tissue is known. The agent concentration could be determined by diffusion modeling, if relevant parameters were available. We have established an MRI-based method capable of determining diffusion properties of conventional and calcium-sensitive agents. Simulations and experiments demonstrate that the method is applicable both for conventional contrast agents with a fixed relaxivity value and for calcium-sensitive contrast agents. The full pharmacokinetic time-course of gadolinium concentration estimates was observed by MRI before, during and after intracerebral administration of the agent, and the effective diffusion coefficient D* was determined by voxel-wise fitting of the solution to the diffusion equation. The method yielded whole brain coverage with a high spatial and temporal sampling. The use of two types of MRI sequences for sampling of the diffusion time courses was investigated: Look-Locker-based quantitative T(1) mapping, and T(1) -weighted MRI. The observation times of the proposed MRI method is long (up to 20 h) and consequently the diffusion distances covered are also long (2-4 mm). Despite this difference, the D* values in vivo were in agreement with previous findings using optical measurement techniques, based on observation times of a few minutes. The effective diffusion coefficient determined for the calcium-sensitive contrast agents may be used to determine local tissue concentrations and to design infusion protocols that maintain the agent concentration at a steady state, thereby enabling quantitative sensing of the local calcium concentration. Copyright © 2014 John Wiley & Sons, Ltd.
Advanced magnetic resonance imaging in glioblastoma: a review.
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.
Sparse and optimal acquisition design for diffusion MRI and beyond
Koay, Cheng Guan; Özarslan, Evren; Johnson, Kevin M.; Meyerand, M. Elizabeth
2012-01-01
Purpose: Diffusion magnetic resonance imaging (MRI) in combination with functional MRI promises a whole new vista for scientists to investigate noninvasively the structural and functional connectivity of the human brain—the human connectome, which had heretofore been out of reach. As with other imaging modalities, diffusion MRI data are inherently noisy and its acquisition time-consuming. Further, a faithful representation of the human connectome that can serve as a predictive model requires a robust and accurate data-analytic pipeline. The focus of this paper is on one of the key segments of this pipeline—in particular, the development of a sparse and optimal acquisition (SOA) design for diffusion MRI multiple-shell acquisition and beyond. Methods: The authors propose a novel optimality criterion for sparse multiple-shell acquisition and quasimultiple-shell designs in diffusion MRI and a novel and effective semistochastic and moderately greedy combinatorial search strategy with simulated annealing to locate the optimum design or configuration. The goal of the optimality criteria is threefold: first, to maximize uniformity of the diffusion measurements in each shell, which is equivalent to maximal incoherence in angular measurements; second, to maximize coverage of the diffusion measurements around each radial line to achieve maximal incoherence in radial measurements for multiple-shell acquisition; and finally, to ensure maximum uniformity of diffusion measurement directions in the limiting case when all the shells are coincidental as in the case of a single-shell acquisition. The approach taken in evaluating the stability of various acquisition designs is based on the condition number and the A-optimal measure of the design matrix. Results: Even though the number of distinct configurations for a given set of diffusion gradient directions is very large in general—e.g., in the order of 10232 for a set of 144 diffusion gradient directions, the proposed search strategy was found to be effective in finding the optimum configuration. It was found that the square design is the most robust (i.e., with stable condition numbers and A-optimal measures under varying experimental conditions) among many other possible designs of the same sample size. Under the same performance evaluation, the square design was found to be more robust than the widely used sampling schemes similar to that of 3D radial MRI and of diffusion spectrum imaging (DSI). Conclusions: A novel optimality criterion for sparse multiple-shell acquisition and quasimultiple-shell designs in diffusion MRI and an effective search strategy for finding the best configuration have been developed. The results are very promising, interesting, and practical for diffusion MRI acquisitions. PMID:22559620
Fan, Qiuyun; Nummenmaa, Aapo; Wichtmann, Barbara; Witzel, Thomas; Mekkaoui, Choukri; Schneider, Walter; Wald, Lawrence L; Huang, Susie Y
2018-06-01
We provide a comprehensive diffusion MRI dataset acquired with a novel biomimetic phantom mimicking human white matter. The fiber substrates in the diffusion phantom were constructed from hollow textile axons ("taxons") with an inner diameter of 11.8±1.2 µm and outer diameter of 33.5±2.3 µm. Data were acquired on the 3 T CONNECTOM MRI scanner with multiple diffusion times and multiple q-values per diffusion time, which is a dedicated acquisition for validation of microstructural imaging methods, such as compartment size and volume fraction mapping. Minimal preprocessing was performed to correct for susceptibility and eddy current distortions. Data were deposited in the XNAT Central database (project ID: dMRI_Phant_MGH).
Iima, Mami; Kataoka, Masako; Kanao, Shotaro; Kawai, Makiko; Onishi, Natsuko; Koyasu, Sho; Murata, Katsutoshi; Ohashi, Akane; Sakaguchi, Rena; Togashi, Kaori
2018-01-01
We prospectively examined the variability of non-Gaussian diffusion magnetic resonance imaging (MRI) and intravoxel incoherent motion (IVIM) measurements with different numbers of b-values and excitations in normal breast tissue and breast lesions. Thirteen volunteers and fourteen patients with breast lesions (seven malignant, eight benign; one patient had bilateral lesions) were recruited in this prospective study (approved by the Internal Review Board). Diffusion-weighted MRI was performed with 16 b-values (0-2500 s/mm2 with one number of excitations [NEX]) and five b-values (0-2500 s/mm2, 3 NEX), using a 3T breast MRI. Intravoxel incoherent motion (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion (theoretical apparent diffusion coefficient [ADC] at b value of 0 sec/mm2 [ADC0] and kurtosis [K]) parameters were estimated from IVIM and Kurtosis models using 16 b-values, and synthetic apparent diffusion coefficient (sADC) values were obtained from two key b-values. The variabilities between and within subjects and between different diffusion acquisition methods were estimated. There were no statistical differences in ADC0, K, or sADC values between the different b-values or NEX. A good agreement of diffusion parameters was observed between 16 b-values (one NEX), five b-values (one NEX), and five b-values (three NEX) in normal breast tissue or breast lesions. Insufficient agreement was observed for IVIM parameters. There were no statistical differences in the non-Gaussian diffusion MRI estimated values obtained from a different number of b-values or excitations in normal breast tissue or breast lesions. These data suggest that a limited MRI protocol using a few b-values might be relevant in a clinical setting for the estimation of non-Gaussian diffusion MRI parameters in normal breast tissue and breast lesions.
Kataoka, Masako; Kanao, Shotaro; Kawai, Makiko; Onishi, Natsuko; Koyasu, Sho; Murata, Katsutoshi; Ohashi, Akane; Sakaguchi, Rena; Togashi, Kaori
2018-01-01
We prospectively examined the variability of non-Gaussian diffusion magnetic resonance imaging (MRI) and intravoxel incoherent motion (IVIM) measurements with different numbers of b-values and excitations in normal breast tissue and breast lesions. Thirteen volunteers and fourteen patients with breast lesions (seven malignant, eight benign; one patient had bilateral lesions) were recruited in this prospective study (approved by the Internal Review Board). Diffusion-weighted MRI was performed with 16 b-values (0–2500 s/mm2 with one number of excitations [NEX]) and five b-values (0–2500 s/mm2, 3 NEX), using a 3T breast MRI. Intravoxel incoherent motion (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion (theoretical apparent diffusion coefficient [ADC] at b value of 0 sec/mm2 [ADC0] and kurtosis [K]) parameters were estimated from IVIM and Kurtosis models using 16 b-values, and synthetic apparent diffusion coefficient (sADC) values were obtained from two key b-values. The variabilities between and within subjects and between different diffusion acquisition methods were estimated. There were no statistical differences in ADC0, K, or sADC values between the different b-values or NEX. A good agreement of diffusion parameters was observed between 16 b-values (one NEX), five b-values (one NEX), and five b-values (three NEX) in normal breast tissue or breast lesions. Insufficient agreement was observed for IVIM parameters. There were no statistical differences in the non-Gaussian diffusion MRI estimated values obtained from a different number of b-values or excitations in normal breast tissue or breast lesions. These data suggest that a limited MRI protocol using a few b-values might be relevant in a clinical setting for the estimation of non-Gaussian diffusion MRI parameters in normal breast tissue and breast lesions. PMID:29494639
Irfanoglu, M. Okan; Walker, Lindsay; Sarlls, Joelle; Marenco, Stefano; Pierpaoli, Carlo
2013-01-01
In this work we investigate the effects of echo planar imaging (EPI) distortions on diffusion tensor imaging (DTI) based fiber tractography results. We propose a simple experimental framework that would enable assessing the effects of EPI distortions on the accuracy and reproducibility of fiber tractography from a pilot study on a few subjects. We compare trajectories computed from two diffusion datasets collected on each subject that are identical except for the orientation of phase encode direction, either right–left (RL) or anterior–posterior (AP). We define metrics to assess potential discrepancies between RL and AP trajectories in association, commissural, and projection pathways. Results from measurements on a 3 Tesla clinical scanner indicated that the effects of EPI distortions on computed fiber trajectories are statistically significant and large in magnitude, potentially leading to erroneous inferences about brain connectivity. The correction of EPI distortion using an image-based registration approach showed a significant improvement in tract consistency and accuracy. Although obtained in the context of a DTI experiment, our findings are generally applicable to all EPI-based diffusion MRI tractography investigations, including high angular resolution (HARDI) methods. On the basis of our findings, we recommend adding an EPI distortion correction step to the diffusion MRI processing pipeline if the output is to be used for fiber tractography. PMID:22401760
Hernández, Moisés; Guerrero, Ginés D.; Cecilia, José M.; García, José M.; Inuggi, Alberto; Jbabdi, Saad; Behrens, Timothy E. J.; Sotiropoulos, Stamatios N.
2013-01-01
With the performance of central processing units (CPUs) having effectively reached a limit, parallel processing offers an alternative for applications with high computational demands. Modern graphics processing units (GPUs) are massively parallel processors that can execute simultaneously thousands of light-weight processes. In this study, we propose and implement a parallel GPU-based design of a popular method that is used for the analysis of brain magnetic resonance imaging (MRI). More specifically, we are concerned with a model-based approach for extracting tissue structural information from diffusion-weighted (DW) MRI data. DW-MRI offers, through tractography approaches, the only way to study brain structural connectivity, non-invasively and in-vivo. We parallelise the Bayesian inference framework for the ball & stick model, as it is implemented in the tractography toolbox of the popular FSL software package (University of Oxford). For our implementation, we utilise the Compute Unified Device Architecture (CUDA) programming model. We show that the parameter estimation, performed through Markov Chain Monte Carlo (MCMC), is accelerated by at least two orders of magnitude, when comparing a single GPU with the respective sequential single-core CPU version. We also illustrate similar speed-up factors (up to 120x) when comparing a multi-GPU with a multi-CPU implementation. PMID:23658616
Cunnington, Ross; Boyd, Roslyn N.; Rose, Stephen E.
2016-01-01
Diffusion MRI (dMRI) tractography analyses are difficult to perform in the presence of brain pathology. Automated methods that rely on cortical parcellation for structural connectivity studies often fail, while manually defining regions is extremely time consuming and can introduce human error. Both methods also make assumptions about structure-function relationships that may not hold after cortical reorganisation. Seeding tractography with functional-MRI (fMRI) activation is an emerging method that reduces these confounds, but inherent smoothing of fMRI signal may result in the inclusion of irrelevant pathways. This paper describes a novel fMRI-seeded dMRI-analysis pipeline based on surface-meshes that reduces these issues and utilises machine-learning to generate task specific white matter pathways, minimising the requirement for manually-drawn ROIs. We directly compared this new strategy to a standard voxelwise fMRI-dMRI approach, by investigating correlations between clinical scores and dMRI metrics of thalamocortical and corticomotor tracts in 31 children with unilateral cerebral palsy. The surface-based approach successfully processed more participants (87%) than the voxel-based approach (65%), and provided significantly more-coherent tractography. Significant correlations between dMRI metrics and five clinical scores of function were found for the more superior regions of these tracts. These significant correlations were stronger and more frequently found with the surface-based method (15/20 investigated were significant; R2 = 0.43–0.73) than the voxelwise analysis (2 sig. correlations; 0.38 & 0.49). More restricted fMRI signal, better-constrained tractography, and the novel track-classification method all appeared to contribute toward these differences. PMID:27487011
Advanced magnetic resonance imaging of neurodegenerative diseases.
Agosta, Federica; Galantucci, Sebastiano; Filippi, Massimo
2017-01-01
Magnetic resonance imaging (MRI) is playing an increasingly important role in the study of neurodegenerative diseases, delineating the structural and functional alterations determined by these conditions. Advanced MRI techniques are of special interest for their potential to characterize the signature of each neurodegenerative condition and aid both the diagnostic process and the monitoring of disease progression. This aspect will become crucial when disease-modifying (personalized) therapies will be established. MRI techniques are very diverse and go from the visual inspection of MRI scans to more complex approaches, such as manual and automatic volume measurements, diffusion tensor MRI, and functional MRI. All these techniques allow us to investigate the different features of neurodegeneration. In this review, we summarize the most recent advances concerning the use of MRI in some of the most important neurodegenerative conditions, putting an emphasis on the advanced techniques.
Fundamentals of diffusion MRI physics.
Kiselev, Valerij G
2017-03-01
Diffusion MRI is commonly considered the "engine" for probing the cellular structure of living biological tissues. The difficulty of this task is threefold. First, in structurally heterogeneous media, diffusion is related to structure in quite a complicated way. The challenge of finding diffusion metrics for a given structure is equivalent to other problems in physics that have been known for over a century. Second, in most cases the MRI signal is related to diffusion in an indirect way dependent on the measurement technique used. Third, finding the cellular structure given the MRI signal is an ill-posed inverse problem. This paper reviews well-established knowledge that forms the basis for responding to the first two challenges. The inverse problem is briefly discussed and the reader is warned about a number of pitfalls on the way. Copyright © 2017 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Russell, Greg
The work described in this dissertation was motivated by a desire to better understand the cellular pathology of ischemic stroke. Two of the three bodies of research presented herein address and issue directly related to the investigation of ischemic stroke through the use of diffusion weighted magnetic resonance imaging (DWMRI) methods. The first topic concerns the development of a computationally efficient finite difference method, designed to evaluate the impact of microscopic tissue properties on the formation of DWMRI signal. For the second body of work, the effect of changing the intrinsic diffusion coefficient of a restricted sample on clinical DWMRI experiments is explored. The final body of work, while motivated by the desire to understand stroke, addresses the issue of acquiring large amounts of MRI data well suited for quantitative analysis in reduced scan time. In theory, the method could be used to generate quantitative parametric maps, including those depicting information gleaned through the use of DWMRI methods. Chapter 1 provides an introduction to several topics. A description of the use of DWMRI methods in the study of ischemic stroke is covered. An introduction to the fundamental physical principles at work in MRI is also provided. In this section the means by which magnetization is created in MRI experiments, how MRI signal is induced, as well as the influence of spin-spin and spin-lattice relaxation are discussed. Attention is also given to describing how MRI measurements can be sensitized to diffusion through the use of qualitative and quantitative descriptions of the process. Finally, the reader is given a brief introduction to the use of numerical methods for solving partial differential equations. In Chapters 2, 3 and 4, three related bodies of research are presented in terms of research papers. In Chapter 2, a novel computational method is described. The method reduces the computation resources required to simulate DWMRI experiments. In Chapter 3, a detailed study on how changes in the intrinsic intracellular diffusion coefficient may influence clinical DWMRI experiments is described. In Chapter 4, a novel, non-steady state quantitative MRI method is described.
Various diffusion magnetic resonance imaging techniques for pancreatic cancer
Tang, Meng-Yue; Zhang, Xiao-Ming; Chen, Tian-Wu; Huang, Xiao-Hua
2015-01-01
Pancreatic cancer is one of the most common malignant tumors and remains a treatment-refractory cancer with a poor prognosis. Currently, the diagnosis of pancreatic neoplasm depends mainly on imaging and which methods are conducive to detecting small lesions. Compared to the other techniques, magnetic resonance imaging (MRI) has irreplaceable advantages and can provide valuable information unattainable with other noninvasive or minimally invasive imaging techniques. Advances in MR hardware and pulse sequence design have particularly improved the quality and robustness of MRI of the pancreas. Diffusion MR imaging serves as one of the common functional MRI techniques and is the only technique that can be used to reflect the diffusion movement of water molecules in vivo. It is generally known that diffusion properties depend on the characterization of intrinsic features of tissue microdynamics and microstructure. With the improvement of the diffusion models, diffusion MR imaging techniques are increasingly varied, from the simplest and most commonly used technique to the more complex. In this review, the various diffusion MRI techniques for pancreatic cancer are discussed, including conventional diffusion weighted imaging (DWI), multi-b DWI based on intra-voxel incoherent motion theory, diffusion tensor imaging and diffusion kurtosis imaging. The principles, main parameters, advantages and limitations of these techniques, as well as future directions for pancreatic diffusion imaging are also discussed. PMID:26753059
Basic concepts of MR imaging, diffusion MR imaging, and diffusion tensor imaging.
de Figueiredo, Eduardo H M S G; Borgonovi, Arthur F N G; Doring, Thomas M
2011-02-01
MR image contrast is based on intrinsic tissue properties and specific pulse sequences and parameter adjustments. A growing number of MRI imaging applications are based on diffusion properties of water. To better understand MRI diffusion-weighted imaging, a brief overview of MR physics is presented in this article followed by physics of the evolving techniques of diffusion MR imaging and diffusion tensor imaging. Copyright © 2011. Published by Elsevier Inc.
Jovicich, Jorge; Marizzoni, Moira; Bosch, Beatriz; Bartrés-Faz, David; Arnold, Jennifer; Benninghoff, Jens; Wiltfang, Jens; Roccatagliata, Luca; Picco, Agnese; Nobili, Flavio; Blin, Oliver; Bombois, Stephanie; Lopes, Renaud; Bordet, Régis; Chanoine, Valérie; Ranjeva, Jean-Philippe; Didic, Mira; Gros-Dagnac, Hélène; Payoux, Pierre; Zoccatelli, Giada; Alessandrini, Franco; Beltramello, Alberto; Bargalló, Núria; Ferretti, Antonio; Caulo, Massimo; Aiello, Marco; Ragucci, Monica; Soricelli, Andrea; Salvadori, Nicola; Tarducci, Roberto; Floridi, Piero; Tsolaki, Magda; Constantinidis, Manos; Drevelegas, Antonios; Rossini, Paolo Maria; Marra, Camillo; Otto, Josephin; Reiss-Zimmermann, Martin; Hoffmann, Karl-Titus; Galluzzi, Samantha; Frisoni, Giovanni B
2014-11-01
Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by the reproducibility of repeated measures acquired during different sessions. At present, there is limited quantitative knowledge about the across-session reproducibility of standard diffusion metrics in 3T multi-centric studies on subjects in stable conditions, in particular when using tract based spatial statistics and with elderly people. In this study we implemented a multi-site brain diffusion protocol in 10 clinical 3T MRI sites distributed across 4 countries in Europe (Italy, Germany, France and Greece) using vendor provided sequences from Siemens (Allegra, Trio Tim, Verio, Skyra, Biograph mMR), Philips (Achieva) and GE (HDxt) scanners. We acquired DTI data (2 × 2 × 2 mm(3), b = 700 s/mm(2), 5 b0 and 30 diffusion weighted volumes) of a group of healthy stable elderly subjects (5 subjects per site) in two separate sessions at least a week apart. For each subject and session four scalar diffusion metrics were considered: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial (AD) diffusivity. The diffusion metrics from multiple subjects and sessions at each site were aligned to their common white matter skeleton using tract-based spatial statistics. The reproducibility at each MRI site was examined by looking at group averages of absolute changes relative to the mean (%) on various parameters: i) reproducibility of the signal-to-noise ratio (SNR) of the b0 images in centrum semiovale, ii) full brain test-retest differences of the diffusion metric maps on the white matter skeleton, iii) reproducibility of the diffusion metrics on atlas-based white matter ROIs on the white matter skeleton. Despite the differences of MRI scanner configurations across sites (vendors, models, RF coils and acquisition sequences) we found good and consistent test-retest reproducibility. White matter b0 SNR reproducibility was on average 7 ± 1% with no significant MRI site effects. Whole brain analysis resulted in no significant test-retest differences at any of the sites with any of the DTI metrics. The atlas-based ROI analysis showed that the mean reproducibility errors largely remained in the 2-4% range for FA and AD and 2-6% for MD and RD, averaged across ROIs. Our results show reproducibility values comparable to those reported in studies using a smaller number of MRI scanners, slightly different DTI protocols and mostly younger populations. We therefore show that the acquisition and analysis protocols used are appropriate for multi-site experimental scenarios. Copyright © 2014 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Schilling, Kurt G.; Nath, Vishwesh; Blaber, Justin; Harrigan, Robert L.; Ding, Zhaohua; Anderson, Adam W.; Landman, Bennett A.
2017-02-01
High-angular-resolution diffusion-weighted imaging (HARDI) MRI acquisitions have become common for use with higher order models of diffusion. Despite successes in resolving complex fiber configurations and probing microstructural properties of brain tissue, there is no common consensus on the optimal b-value and number of diffusion directions to use for these HARDI methods. While this question has been addressed by analysis of the diffusion-weighted signal directly, it is unclear how this translates to the information and metrics derived from the HARDI models themselves. Using a high angular resolution data set acquired at a range of b-values, and repeated 11 times on a single subject, we study how the b-value and number of diffusion directions impacts the reproducibility and precision of metrics derived from Q-ball imaging, a popular HARDI technique. We find that Q-ball metrics associated with tissue microstructure and white matter fiber orientation are sensitive to both the number of diffusion directions and the spherical harmonic representation of the Q-ball, and often are biased when under sampled. These results can advise researchers on appropriate acquisition and processing schemes, particularly when it comes to optimizing the number of diffusion directions needed for metrics derived from Q-ball imaging.
Quantitative body DW-MRI biomarkers uncertainty estimation using unscented wild-bootstrap.
Freiman, M; Voss, S D; Mulkern, R V; Perez-Rossello, J M; Warfield, S K
2011-01-01
We present a new method for the uncertainty estimation of diffusion parameters for quantitative body DW-MRI assessment. Diffusion parameters uncertainty estimation from DW-MRI is necessary for clinical applications that use these parameters to assess pathology. However, uncertainty estimation using traditional techniques requires repeated acquisitions, which is undesirable in routine clinical use. Model-based bootstrap techniques, for example, assume an underlying linear model for residuals rescaling and cannot be utilized directly for body diffusion parameters uncertainty estimation due to the non-linearity of the body diffusion model. To offset this limitation, our method uses the Unscented transform to compute the residuals rescaling parameters from the non-linear body diffusion model, and then applies the wild-bootstrap method to infer the body diffusion parameters uncertainty. Validation through phantom and human subject experiments shows that our method identify the regions with higher uncertainty in body DWI-MRI model parameters correctly with realtive error of -36% in the uncertainty values.
White Matter Development during Adolescence as Shown by Diffusion MRI
ERIC Educational Resources Information Center
Schmithorst, Vincent J.; Yuan, Weihong
2010-01-01
Previous volumetric developmental MRI studies of the brain have shown white matter development continuing through adolescence and into adulthood. This review presents current findings regarding white matter development and organization from diffusion MRI studies. The general trend during adolescence (age 12-18 years) is towards increasing…
NASA Astrophysics Data System (ADS)
Qin, Shanlin; Liu, Fawang; Turner, Ian W.
2018-03-01
The consideration of diffusion processes in magnetic resonance imaging (MRI) signal attenuation is classically described by the Bloch-Torrey equation. However, many recent works highlight the distinct deviation in MRI signal decay due to anomalous diffusion, which motivates the fractional order generalization of the Bloch-Torrey equation. In this work, we study the two-dimensional multi-term time and space fractional diffusion equation generalized from the time and space fractional Bloch-Torrey equation. By using the Galerkin finite element method with a structured mesh consisting of rectangular elements to discretize in space and the L1 approximation of the Caputo fractional derivative in time, a fully discrete numerical scheme is derived. A rigorous analysis of stability and error estimation is provided. Numerical experiments in the square and L-shaped domains are performed to give an insight into the efficiency and reliability of our method. Then the scheme is applied to solve the multi-term time and space fractional Bloch-Torrey equation, which shows that the extra time derivative terms impact the relaxation process.
Cortical fibers orientation mapping using in-vivo whole brain 7 T diffusion MRI.
Gulban, Omer F; De Martino, Federico; Vu, An T; Yacoub, Essa; Uğurbil, Kamil; Lenglet, Christophe
2018-05-10
Diffusion MRI of the cortical gray matter is challenging because the micro-environment probed by water molecules is much more complex than within the white matter. High spatial and angular resolutions are therefore necessary to uncover anisotropic diffusion patterns and laminar structures, which provide complementary (e.g. to anatomical and functional MRI) microstructural information about the cortex architectonic. Several ex-vivo and in-vivo MRI studies have recently addressed this question, however predominantly with an emphasis on specific cortical areas. There is currently no whole brain in-vivo data leveraging multi-shell diffusion MRI acquisition at high spatial resolution, and depth dependent analysis, to characterize the complex organization of cortical fibers. Here, we present unique in-vivo human 7T diffusion MRI data, and a dedicated cortical depth dependent analysis pipeline. We leverage the high spatial (1.05 mm isotropic) and angular (198 diffusion gradient directions) resolution of this whole brain dataset to improve cortical fiber orientations mapping, and study neurites (axons and/or dendrites) trajectories across cortical depths. Tangential fibers in superficial cortical depths and crossing fiber configurations in deep cortical depths are identified. Fibers gradually inserting into the gyral walls are visualized, which contributes to mitigating the gyral bias effect. Quantitative radiality maps and histograms in individual subjects and cortex-based aligned datasets further support our results. Copyright © 2018 Elsevier Inc. All rights reserved.
Cumulant expansions for measuring water exchange using diffusion MRI
NASA Astrophysics Data System (ADS)
Ning, Lipeng; Nilsson, Markus; Lasič, Samo; Westin, Carl-Fredrik; Rathi, Yogesh
2018-02-01
The rate of water exchange across cell membranes is a parameter of biological interest and can be measured by diffusion magnetic resonance imaging (dMRI). In this work, we investigate a stochastic model for the diffusion-and-exchange of water molecules. This model provides a general solution for the temporal evolution of dMRI signal using any type of gradient waveform, thereby generalizing the signal expressions for the Kärger model. Moreover, we also derive a general nth order cumulant expansion of the dMRI signal accounting for water exchange, which has not been explored in earlier studies. Based on this analytical expression, we compute the cumulant expansion for dMRI signals for the special case of single diffusion encoding (SDE) and double diffusion encoding (DDE) sequences. Our results provide a theoretical guideline on optimizing experimental parameters for SDE and DDE sequences, respectively. Moreover, we show that DDE signals are more sensitive to water exchange at short-time scale but provide less attenuation at long-time scale than SDE signals. Our theoretical analysis is also validated using Monte Carlo simulations on synthetic structures.
Hayakawa, Katsumi; Koshino, Sachiko; Tanda, Koichi; Nishimura, Akira; Sato, Osamu; Morishita, Hiroyuki; Ito, Takaaki
2018-06-01
Pseudonormalization of diffusion-weighted magnetic resonance imaging (MRI) can lead to underestimation of brain injury in newborns with hypoxic-ischemic encephalopathy (HIE), posing a significant problem. We have noticed that some neonates show pseudonormalization negativity on diffusion-weighted imaging. To compare pseudonormalization negativity with clinical outcomes. Seventeen term neonates with moderate or severe HIE underwent therapeutic hypothermia. They were examined by MRI twice at mean ages of 3 days and 10 days. We evaluated the presence of restricted diffusion, and also the presence or absence of pseudonormalization, by diffusion-weighted imaging at the time of the second MRI, and correlated the results with clinical outcome. DWI demonstrated no abnormality in seven neonates. Among the 10 neonates with abnormal diffusion-weighted imaging findings, 2 were positive for pseudonormalization and 8 were negative. Among neonates with normal diffusion-weighted imaging findings and with positivity for pseudonormalization, none had major disability. Among the eight neonates with pseudonormalization negativity, all but one, who was lost to follow-up, had major disability. Abnormal diffusion-weighted imaging with pseudonormalization negativity might be predictive of severe brain injury and major disability. The second-week MRI is important for the judgment of pseudonormalization.
Parametric dictionary learning for modeling EAP and ODF in diffusion MRI.
Merlet, Sylvain; Caruyer, Emmanuel; Deriche, Rachid
2012-01-01
In this work, we propose an original and efficient approach to exploit the ability of Compressed Sensing (CS) to recover diffusion MRI (dMRI) signals from a limited number of samples while efficiently recovering important diffusion features such as the ensemble average propagator (EAP) and the orientation distribution function (ODF). Some attempts to sparsely represent the diffusion signal have already been performed. However and contrarly to what has been presented in CS dMRI, in this work we propose and advocate the use of a well adapted learned dictionary and show that it leads to a sparser signal estimation as well as to an efficient reconstruction of very important diffusion features. We first propose to learn and design a sparse and parametric dictionary from a set of training diffusion data. Then, we propose a framework to analytically estimate in closed form two important diffusion features: the EAP and the ODF. Various experiments on synthetic, phantom and human brain data have been carried out and promising results with reduced number of atoms have been obtained on diffusion signal reconstruction, thus illustrating the added value of our method over state-of-the-art SHORE and SPF based approaches.
Ning, Lipeng; Özarslan, Evren; Westin, Carl-Fredrik; Rathi, Yogesh
2017-01-01
Inferring the microstructure of complex media from the diffusive motion of molecules is a challenging problem in diffusion physics. In this paper, we introduce a novel representation of diffusion MRI (dMRI) signal from tissue with spatially-varying diffusivity using a diffusion disturbance function. This disturbance function contains information about the (intra-voxel) spatial fluctuations in diffusivity due to restrictions, hindrances and tissue heterogeneity of the underlying tissue substrate. We derive the short- and long-range disturbance coefficients from this disturbance function to characterize the tissue structure and organization. Moreover, we provide an exact relation between the disturbance coefficients and the time-varying moments of the diffusion propagator, as well as their relation to specific tissue microstructural information such as the intra-axonal volume fraction and the apparent axon radius. The proposed approach is quite general and can model dMRI signal for any type of gradient sequence (rectangular, oscillating, etc.) without using the Gaussian phase approximation. The relevance of the proposed PICASO model is explored using Monte-Carlo simulations and in-vivo dMRI data. The results show that the estimated disturbance coefficients can distinguish different types of microstructural organization of axons. PMID:27751940
Ning, Lipeng; Özarslan, Evren; Westin, Carl-Fredrik; Rathi, Yogesh
2017-02-01
Inferring the microstructure of complex media from the diffusive motion of molecules is a challenging problem in diffusion physics. In this paper, we introduce a novel representation of diffusion MRI (dMRI) signal from tissue with spatially-varying diffusivity using a diffusion disturbance function. This disturbance function contains information about the (intra-voxel) spatial fluctuations in diffusivity due to restrictions, hindrances and tissue heterogeneity of the underlying tissue substrate. We derive the short- and long-range disturbance coefficients from this disturbance function to characterize the tissue structure and organization. Moreover, we provide an exact relation between the disturbance coefficients and the time-varying moments of the diffusion propagator, as well as their relation to specific tissue microstructural information such as the intra-axonal volume fraction and the apparent axon radius. The proposed approach is quite general and can model dMRI signal for any type of gradient sequence (rectangular, oscillating, etc.) without using the Gaussian phase approximation. The relevance of the proposed PICASO model is explored using Monte-Carlo simulations and in-vivo dMRI data. The results show that the estimated disturbance coefficients can distinguish different types of microstructural organization of axons. Copyright © 2016 Elsevier Inc. All rights reserved.
Imširović, Bilal; Zerem, Enver; Efendić, Alma; Mekić Abazović, Alma; Zerem, Omar; Djedović, Muhamed
2018-08-01
Aim To determine capabilities and potential of contrast enhanced magnetic resonance imaging (MRI) enterography in order to establish the diagnosis and to evaluate severity and activity of intestinal inflammation. Methods Fifty-five patients with suspicion for presence of Crohn's disease were evaluated. All patients underwent contrast enhanced MRI enterography and diffusion weighted imaging (DWI), and subsequently endoscopic examination or surgical treatment. Four parameters were analysed: thickening of the bowel wall, and presence of abscess, fistula and lymphadenopathy. Results Comparing results of DWI and contrast enhanced MRI enterography a significant difference between results given through diffusion and histopathological test was found, e.g. a significant difference between results obtained through diffusion and MRI enterography was found. MRI enterography sensitiveness for bowel wall thickening was 97.7% and specificity 70%, whilst DWI sensitivity for bowel wall thickening was 84% and specificity 100%. The diagnostics of abscess and fistula showed no significant difference between DWI and MRI, while in lymphadenopathy significant difference between contrast enhanced MRI enterography and DWI was found. Conclusion Contrast enhanced MRI enterography in combination with DWI allows for excellent evaluation of disease activity, but also problems or complications following it. The examination can be repeated, controlled, and it can contribute to monitoring of patients with this disease. Copyright© by the Medical Assotiation of Zenica-Doboj Canton.
Tax, Chantal M. W.; Duits, Remco; Vilanova, Anna; ter Haar Romeny, Bart M.; Hofman, Paul; Wagner, Louis; Leemans, Alexander; Ossenblok, Pauly
2014-01-01
Diffusion MRI and tractography allow for investigation of the architectural configuration of white matter in vivo, offering new avenues for applications like presurgical planning. Despite the promising outlook, there are many pitfalls that complicate its use for (clinical) application. Amongst these are inaccuracies in the geometry of the diffusion profiles on which tractography is based, and poor alignment with neighboring profiles. Recently developed contextual processing techniques, including enhancement and well-posed geometric sharpening, have shown to result in sharper and better aligned diffusion profiles. However, the research that has been conducted up to now is mainly of theoretical nature, and so far these techniques have only been evaluated by visual inspection of the diffusion profiles. In this work, the method is evaluated in a clinically relevant application: the reconstruction of the optic radiation for epilepsy surgery. For this evaluation we have developed a framework in which we incorporate a novel scoring procedure for individual pathways. We demonstrate that, using enhancement and sharpening, the extraction of an anatomically plausible reconstruction of the optic radiation from a large amount of probabilistic pathways is greatly improved in three healthy controls, where currently used methods fail to do so. Furthermore, challenging reconstructions of the optic radiation in three epilepsy surgery candidates with extensive brain lesions demonstrate that it is beneficial to integrate these methods in surgical planning. PMID:25077946
Tax, Chantal M W; Duits, Remco; Vilanova, Anna; ter Haar Romeny, Bart M; Hofman, Paul; Wagner, Louis; Leemans, Alexander; Ossenblok, Pauly
2014-01-01
Diffusion MRI and tractography allow for investigation of the architectural configuration of white matter in vivo, offering new avenues for applications like presurgical planning. Despite the promising outlook, there are many pitfalls that complicate its use for (clinical) application. Amongst these are inaccuracies in the geometry of the diffusion profiles on which tractography is based, and poor alignment with neighboring profiles. Recently developed contextual processing techniques, including enhancement and well-posed geometric sharpening, have shown to result in sharper and better aligned diffusion profiles. However, the research that has been conducted up to now is mainly of theoretical nature, and so far these techniques have only been evaluated by visual inspection of the diffusion profiles. In this work, the method is evaluated in a clinically relevant application: the reconstruction of the optic radiation for epilepsy surgery. For this evaluation we have developed a framework in which we incorporate a novel scoring procedure for individual pathways. We demonstrate that, using enhancement and sharpening, the extraction of an anatomically plausible reconstruction of the optic radiation from a large amount of probabilistic pathways is greatly improved in three healthy controls, where currently used methods fail to do so. Furthermore, challenging reconstructions of the optic radiation in three epilepsy surgery candidates with extensive brain lesions demonstrate that it is beneficial to integrate these methods in surgical planning.
Yang, Yingli; Cao, Minsong; Sheng, Ke; Gao, Yu; Chen, Allen; Kamrava, Mitch; Lee, Percy; Agazaryan, Nzhde; Lamb, James; Thomas, David; Low, Daniel; Hu, Peng
2016-03-01
To demonstrate the preliminary feasibility of a longitudinal diffusion magnetic resonance imaging (MRI) strategy for assessing patient response to radiotherapy at 0.35 T using an MRI-guided radiotherapy system (ViewRay). Six patients (three head and neck cancer, three sarcoma) who underwent fractionated radiotherapy were enrolled in this study. A 2D multislice spin echo single-shot echo planar imaging diffusion pulse sequence was implemented on the ViewRay system and tested in phantom studies. The same pulse sequence was used to acquire longitudinal diffusion data (every 2-5 fractions) on the six patients throughout the entire course of radiotherapy. The reproducibility of the apparent diffusion coefficient (ADC) measurements was assessed using reference regions and the temporal variations of the tumor ADC values were evaluated. In diffusion phantom studies, the ADC values measured on the ViewRay system matched well with reference ADC values with <5% error for a range of ground truth diffusion coefficients of 0.4-1.1 × 10(-3) mm(2)/s. The remote reference regions (i.e., brainstem in head and neck patients) had consistent ADC values throughout the therapy for all three head and neck patients, indicating acceptable reproducibility of the diffusion imaging sequence. The tumor ADC values changed throughout therapy, with the change differing between patients, ranging from a 40% drop in ADC within the first week of therapy to gradually increasing throughout therapy. For larger tumors, intratumoral heterogeneity was observed. For one sarcoma patient, postradiotherapy biopsy showed less than 10% necrosis score, which correlated with the observed 40% decrease in ADC from the fifth fraction to the eighth treatment fraction. This pilot study demonstrated that longitudinal diffusion MRI is feasible using the 0.35 T ViewRay MRI. Larger patient cohort studies are warranted to correlate the longitudinal diffusion measurements to patient outcomes. Such an approach may enable response-guided adaptive radiotherapy.
Novel Diffusion-Weighted MRI for High-Grade Prostate Cancer Detection
2017-10-01
AWARD NUMBER: W81XWH-15-1-0346 TITLE: Novel Diffusion-Weighted MRI for High -Grade Prostate Cancer Detection PRINCIPAL INVESTIGATOR: Michael Abern...Unlimited The views, opinions and/or findings contained in this report are those of the author(s) and should not be construed as an official Department of...Diffusion-Weighted MRI for High -Grade Prostate Cancer Detection 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-15-1-0346 5c. PROGRAM ELEMENT NUMBER 6
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.
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
NASA Astrophysics Data System (ADS)
Freidlin, R. Z.; Kakareka, J. W.; Pohida, T. J.; Komlosh, M. E.; Basser, P. J.
2012-08-01
In vivo MRI data can be corrupted by motion. Motion artifacts are particularly troublesome in Diffusion Weighted MRI (DWI), since the MR signal attenuation due to Brownian motion can be much less than the signal loss due to dephasing from other types of complex tissue motion, which can significantly degrade the estimation of self-diffusion coefficients, diffusion tensors, etc. This paper describes a snapshot DWI sequence, which utilizes a novel single-sided bipolar diffusion sensitizing gradient pulse within a spin echo sequence. The proposed method shortens the diffusion time by applying a single refocused bipolar diffusion gradient on one side of a refocusing RF pulse, instead of a set of diffusion sensitizing gradients, separated by a refocusing RF pulse, while reducing the impact of magnetic field inhomogeneity by using a spin echo sequence. A novel MRI phantom that can exhibit a range of complex motions was designed to demonstrate the robustness of the proposed DWI sequence.
[Gastric magnetic resonance study (methods, semiotics)].
Stashuk, G A
2003-01-01
The paper shows the potentialities of gastric study by magnetic resonance imaging (MRI). The methodic aspects of gastric study have been worked out. The MRI-semiotics of the unchanged and tumor-affected wall of the stomach and techniques in examining patients with gastric cancer of various sites are described. Using the developed procedure, MRI was performed in 199 patients, including 154 patients with gastric pathology and 45 control individuals who had no altered gastric wall. Great emphasis is placed on the role of MRI in the diagnosis of endophytic (diffuse) gastric cancer that is of priority value in its morphological structure. MRI was found to play a role in the diagnosis of the spread of a tumorous process both along the walls of the stomach and to its adjacent anatomic structures.
[Imaging and quantitative measurement of brain extracellular space using MRI Gd-DTPA tracer method].
He, Qing-yuan; Han, Hong-bin; Xu, Fang-jing-wei; Yan, Jun-hao; Zeng, Jin-jin; Li, Xiao-gang; Fu, Yu; Peng, Yun; Chen, He; Hou, Chao; Xu, Xiao-juan
2010-04-18
To observe the diffusion of Gd-DTPA in brain extracellular space (ECS) by magnetic resonance imaging(MRI) and investigate the feasibility of ECS measurement by using MRI tracer method in vivo. 2 microL Gd-DTPA was introduced into ECS by caudate nucleus according to stereotaxic atlas in 8 Sprague Dawley(SD) rats (male, 280-320 g). The MRI scans were performed at 1 h, 3 h, 6 h, 9 h and 12 h respectively after administration. MRI appearances of Gd-DTPA diffusion and distribution was observed and compared. The MRI signal enhancement was measured at each time point. The neuroethology assessment was performed after MRI scanning at 12 h. The injection was accurate at the center of the caudate nucleus in 6 rats, while, at the capsula externa in other 2 rats. Gd-DTPA diffused isotropically after it was introduced into caudate nucleus, which spread into lateral cortex at 3 h. The MRI signal enhancement distributed mainly in the middle cerebral artery territory. A significant difference was found between the signal enhancement ratio at 1 h and that at 3 h in the original point of caudate nucleus (t=95.63, P<0.01), and the signal enhancement attenuated following the exponential power function y=1.7886x(-0.1776) (R2=0.94). In 2 rats with the injection point at capsula externa, Gd-DTPA diffused anisotropically along the fiber track of white matter during 1 h to 3 h, and spread into the lateral cortex at 6 h. The diffusion and clearance of Gd-DTPA in brain ECS could be monitored and measured quantitatively in vivo by MRI tracer method.
Nissan, Noam; Furman-Haran, Edna; Shapiro-Feinberg, Myra; Grobgeld, Dov; Degani, Hadassa
2017-09-01
Lactation and the return to the pre-conception state during post-weaning are regulated by hormonal induced processes that modify the microstructure of the mammary gland, leading to changes in the features of the ductal / glandular tissue, the stroma and the fat tissue. These changes create a challenge in the radiological workup of breast disorder during lactation and early post-weaning. Here we present non-invasive MRI protocols designed to record in vivo high spatial resolution, T 2 -weighted images and diffusion tensor images of the entire mammary gland. Advanced imaging processing tools enabled tracking the changes in the anatomical and microstructural features of the mammary gland from the time of lactation to post-weaning. Specifically, by using diffusion tensor imaging (DTI) it was possible to quantitatively distinguish between the ductal / glandular tissue distention during lactation and the post-weaning involution. The application of the T 2 -weighted imaging and DTI is completely safe, non-invasive and uses intrinsic contrast based on differences in transverse relaxation rates and water diffusion rates in various directions, respectively. This study provides a basis for further in-vivo monitoring of changes during the mammary developmental stages, as well as identifying changes due to malignant transformation in patients with pregnancy associated breast cancer (PABC).
Driessen, Juliette P; van Bemmel, Alexander J M; van Kempen, Pauline M W; Janssen, Luuk M; Terhaard, Chris H J; Pameijer, Frank A; Willems, Stefan M; Stegeman, Inge; Grolman, Wilko; Philippens, Marielle E P
2016-04-01
Identification of prognostic patient characteristics in head and neck squamous cell carcinoma (HNSCC) is of great importance. Human papillomavirus (HPV)-positive HNSCCs have favorable response to (chemo)radiotherapy. Apparent diffusion coefficient, derived from diffusion-weighted MRI, has also shown to predict treatment response. The purpose of this study was to evaluate the correlation between HPV status and apparent diffusion coefficient. Seventy-three patients with histologically proven HNSCC were retrospectively analyzed. Mean pretreatment apparent diffusion coefficient was calculated by delineation of total tumor volume on diffusion-weighted MRI. HPV status was analyzed and correlated to apparent diffusion coefficient. Six HNSCCs were HPV-positive. HPV-positive HNSCC showed significantly lower apparent diffusion coefficient compared to HPV-negative. This correlation was independent of other patient characteristics. In HNSCC, positive HPV status correlates with low mean apparent diffusion coefficient. The favorable prognostic value of low pretreatment apparent diffusion coefficient might be partially attributed to patients with a positive HPV status. © 2015 Wiley Periodicals, Inc. Head Neck 38: E613-E618, 2016. © 2015 Wiley Periodicals, Inc.
Advanced magnetic resonance imaging of the physical processes in human glioblastoma.
Kalpathy-Cramer, Jayashree; Gerstner, Elizabeth R; Emblem, Kyrre E; Andronesi, Ovidiu; Rosen, Bruce
2014-09-01
The most common malignant primary brain tumor, glioblastoma multiforme (GBM) is a devastating disease with a grim prognosis. Patient survival is typically less than two years and fewer than 10% of patients survive more than five years. Magnetic resonance imaging (MRI) can have great utility in the diagnosis, grading, and management of patients with GBM as many of the physical manifestations of the pathologic processes in GBM can be visualized and quantified using MRI. Newer MRI techniques such as dynamic contrast enhanced and dynamic susceptibility contrast MRI provide functional information about the tumor hemodynamic status. Diffusion MRI can shed light on tumor cellularity and the disruption of white matter tracts in the proximity of tumors. MR spectroscopy can be used to study new tumor tissue markers such as IDH mutations. MRI is helping to noninvasively explore the link between the molecular basis of gliomas and the imaging characteristics of their physical processes. We, here, review several approaches to MR-based imaging and discuss the potential for these techniques to quantify the physical processes in glioblastoma, including tumor cellularity and vascularity, metabolite expression, and patterns of tumor growth and recurrence. We conclude with challenges and opportunities for further research in applying physical principles to better understand the biologic process in this deadly disease. See all articles in this Cancer Research section, "Physics in Cancer Research." ©2014 American Association for Cancer Research.
Miao, Wen; Man, Fengyuan; Wu, Shaoqin; Lv, Bin; Wang, Zhenchang; Xian, Junfang; Sabel, Bernhard A; He, Huiguang; Jiao, Yonghong
2015-01-01
To explore the possible brain structural and functional alterations in congenital fibrosis of extraocular muscles type 1 (CFEOM1) patients using multimodal MRI imaging. T1-weighted, diffusion tensor images and functional MRI data were obtained from 9 KIF21A positive patients and 19 age- and gender-matched healthy controls. Voxel based morphometry and tract based spatial statistics were applied to the T1-weighted and diffusion tensor images, respectively. Amplitude of low frequency fluctuations and regional homogeneity were used to process the functional MRI data. We then compared these multimodal characteristics between CFEOM1 patients and healthy controls. Compared with healthy controls, CFEOM1 patients demonstrated increased grey matter volume in bilateral frontal orbital cortex and in the right temporal pole. No diffusion indices changes were detected, indicating unaffected white matter microstructure. In addition, from resting state functional MRI data, trend of amplitude of low-frequency fluctuations increases were noted in the right inferior parietal lobe and in the right frontal cortex, and a trend of ReHo increase (p<0.001 uncorrected) in the left precentral gyrus, left orbital frontal cortex, temporal pole and cingulate gyrus. CFEOM1 patients had structural and functional changes in grey matter, but the white matter was unaffected. These alterations in the brain may be due to the abnormality of extraocular muscles and their innervating nerves. Future studies should consider the possible correlations between brain morphological/functional findings and clinical data, especially pertaining to eye movements, to obtain more precise answers about the role of brain area changes and their functional consequence in CFEOM1.
Diffusion fMRI detects white-matter dysfunction in mice with acute optic neuritis
Lin, Tsen-Hsuan; Spees, William M.; Chiang, Chia-Wen; Trinkaus, Kathryn; Cross, Anne H.; Song, Sheng-Kwei
2014-01-01
Optic neuritis is a frequent and early symptom of multiple sclerosis (MS). Conventional magnetic resonance (MR) techniques provide means to assess multiple MS-related pathologies, including axonal injury, demyelination, and inflammation. A method to directly and non-invasively probe white-matter function could further elucidate the interplay of underlying pathologies and functional impairments. Previously, we demonstrated a significant 27% activation-associated decrease in the apparent diffusion coefficient of water perpendicular to the axonal fibers (ADC⊥) in normal C57BL/6 mouse optic nerve with visual stimulation using diffusion fMRI. Here we apply this approach to explore the relationship between visual acuity, optic nerve pathology, and diffusion fMRI in the experimental autoimmune encephalomyelitis (EAE) mouse model of optic neuritis. Visual stimulation produced a significant 25% (vs. baseline) ADC⊥ decrease in sham EAE optic nerves, while only a 7% (vs. baseline) ADC⊥ decrease was seen in EAE mice with acute optic neuritis. The reduced activation-associated ADC⊥ response correlated with post-MRI immunohistochemistry determined pathologies (including inflammation, demyelination, and axonal injury). The negative correlation between activation-associated ADC⊥ response and visual acuity was also found when pooling EAE-affected and sham groups under our experimental criteria. Results suggest that reduction in diffusion fMRI directly reflects impaired axonal-activation in EAE mice with optic neuritis. Diffusion fMRI holds promise for directly gauging in vivo white-matter dysfunction or therapeutic responses in MS patients. PMID:24632420
The potential of multiparametric MRI of the breast
Pinker, Katja; Helbich, Thomas H
2017-01-01
MRI is an essential tool in breast imaging, with multiple established indications. Dynamic contrast-enhanced MRI (DCE-MRI) is the backbone of any breast MRI protocol and has an excellent sensitivity and good specificity for breast cancer diagnosis. DCE-MRI provides high-resolution morphological information, as well as some functional information about neoangiogenesis as a tumour-specific feature. To overcome limitations in specificity, several other functional MRI parameters have been investigated and the application of these combined parameters is defined as multiparametric MRI (mpMRI) of the breast. MpMRI of the breast can be performed at different field strengths (1.5–7 T) and includes both established (diffusion-weighted imaging, MR spectroscopic imaging) and novel MRI parameters (sodium imaging, chemical exchange saturation transfer imaging, blood oxygen level-dependent MRI), as well as hybrid imaging with positron emission tomography (PET)/MRI and different radiotracers. Available data suggest that multiparametric imaging using different functional MRI and PET parameters can provide detailed information about the underlying oncogenic processes of cancer development and progression and can provide additional specificity. This article will review the current and emerging functional parameters for mpMRI of the breast for improved diagnostic accuracy in breast cancer. PMID:27805423
Comparison of block and event-related experimental designs in diffusion-weighted functional MRI.
Williams, Rebecca J; McMahon, Katie L; Hocking, Julia; Reutens, David C
2014-08-01
To compare diffusion-weighted functional magnetic resonance imaging (DfMRI), a novel alternative to the blood oxygenation level-dependent (BOLD) contrast, in a functional MRI experiment. Nine participants viewed contrast reversing (7.5 Hz) black-and-white checkerboard stimuli using block and event-related paradigms. DfMRI (b = 1800 mm/s(2)) and BOLD sequences were acquired. Four parameters describing the observed signal were assessed: percent signal change, spatial extent of the activation, the Euclidean distance between peak voxel locations, and the time-to-peak of the best fitting impulse response for different paradigms and sequences. The BOLD conditions showed a higher percent signal change relative to DfMRI; however, event-related DfMRI showed the strongest group activation (t = 21.23, P < 0.0005). Activation was more diffuse and spatially closer to the BOLD response for DfMRI when the block design was used. DfMRIevent showed the shortest TTP (4.4 ± 0.88 sec). The hemodynamic contribution to DfMRI may increase with the use of block designs. © 2013 Wiley Periodicals, Inc.
Pajevic, Sinisa; Aldroubi, Akram; Basser, Peter J
2002-01-01
The effective diffusion tensor of water, D, measured by diffusion tensor MRI (DT-MRI), is inherently a discrete, noisy, voxel-averaged sample of an underlying macroscopic effective diffusion tensor field, D(x). Within fibrous tissues this field is presumed to be continuous and smooth at a gross anatomical length scale. Here a new, general mathematical framework is proposed that uses measured DT-MRI data to produce a continuous approximation to D(x). One essential finding is that the continuous tensor field representation can be constructed by repeatedly performing one-dimensional B-spline transforms of the DT-MRI data. The fidelity and noise-immunity of this approximation are tested using a set of synthetically generated tensor fields to which background noise is added via Monte Carlo methods. Generally, these tensor field templates are reproduced faithfully except at boundaries where diffusion properties change discontinuously or where the tensor field is not microscopically homogeneous. Away from such regions, the tensor field approximation does not introduce bias in useful DT-MRI parameters, such as Trace(D(x)). It also facilitates the calculation of several new parameters, particularly differential quantities obtained from the tensor of spatial gradients of D(x). As an example, we show that they can identify tissue boundaries across which diffusion properties change rapidly using in vivo human brain data. One important application of this methodology is to improve the reliability and robustness of DT-MRI fiber tractography.
Suo-Palosaari, M; Rantala, H; Lehtinen, S; Kumpulainen, T; Salokorpi, N
2016-06-01
We describe a unique case of expansive diffuse brainstem lesion diagnosed prenatally by magnetic resonance imaging (MRI) with long-term survival. Findings of fetal and postpartum MRI were highly consistent with the characteristics of diffuse brainstem glioma. Diagnosis was based on the features of MRI, and histopathology was not confirmed by biopsy. Although the prognosis of diffuse brainstem tumor is usually poor, this child was asymptomatic at birth and the neurological condition is still normal at 4 years of age without any treatment. During routine imaging follow-up, diameters of the expansion have remained stable, while the size of the lesion compared to the posterior fossa size has diminished. In addition to brainstem tumor, a skin lesion of the back was observed and MRI of the thoracic spine showed a large asymptomatic extradural cystic lesion suggesting an arachnoid cyst. The pontine tumor of this infant, in agreement with a few previously reported cases, suggests a subgroup of beneficial outcome of expansive diffuse brainstem lesions, particularly in the neonatal period. In this article, we discuss the prognosis and characteristics of pediatric brainstem tumors and differential diagnosis of neonatal brainstem lesions.
Mulkern, Robert V; Haker, Steven J; Maier, Stephan E
2007-07-01
Tissue water molecules reside in different biophysical compartments. For example, water molecules in the vasculature reside for variable periods of time within arteries, arterioles, capillaries, venuoles and veins, and may be within blood cells or blood plasma. Water molecules outside of the vasculature, in the extravascular space, reside, for a time, either within cells or within the interstitial space between cells. Within these different compartments, different types of microscopic motion that water molecules may experience have been identified and discussed. These range from Brownian diffusion to more coherent flow over the time scales relevant to functional magnetic resonance imaging (fMRI) experiments, on the order of several 10s of milliseconds. How these different types of motion are reflected in magnetic resonance imaging (MRI) methods developed for "diffusion" imaging studies has been an ongoing and active area of research. Here we briefly review the ideas that have developed regarding these motions within the context of modern "diffusion" imaging techniques and, in particular, how they have been accessed in attempts to further our understanding of the various contributions to the fMRI signal changes sought in studies of human brain activation.
Magnetic resonance imaging of granular materials
NASA Astrophysics Data System (ADS)
Stannarius, Ralf
2017-05-01
Magnetic Resonance Imaging (MRI) has become one of the most important tools to screen humans in medicine; virtually every modern hospital is equipped with a Nuclear Magnetic Resonance (NMR) tomograph. The potential of NMR in 3D imaging tasks is by far greater, but there is only "a handful" of MRI studies of particulate matter. The method is expensive, time-consuming, and requires a deep understanding of pulse sequences, signal acquisition, and processing. We give a short introduction into the physical principles of this imaging technique, describe its advantages and limitations for the screening of granular matter, and present a number of examples of different application purposes, from the exploration of granular packing, via the detection of flow and particle diffusion, to real dynamic measurements. Probably, X-ray computed tomography is preferable in most applications, but fast imaging of single slices with modern MRI techniques is unmatched, and the additional opportunity to retrieve spatially resolved flow and diffusion profiles without particle tracking is a unique feature.
Marrale, M; Collura, G; Brai, M; Toschi, N; Midiri, F; La Tona, G; Lo Casto, A; Gagliardo, C
2016-12-01
In recent years many papers about diagnostic applications of diffusion tensor imaging (DTI) have been published. This is because DTI allows to evaluate in vivo and in a non-invasive way the process of diffusion of water molecules in biological tissues. However, the simplified description of the diffusion process assumed in DTI does not permit to completely map the complex underlying cellular components and structures, which hinder and restrict the diffusion of water molecules. These limitations can be partially overcome by means of diffusion kurtosis imaging (DKI). The aim of this paper is the description of the theory of DKI, a new topic of growing interest in radiology. DKI is a higher order diffusion model that is a straightforward extension of the DTI model. Here, we analyze the physics underlying this method, we report our MRI acquisition protocol with the preprocessing pipeline used and the DKI parametric maps obtained on a 1.5 T scanner, and we review the most relevant clinical applications of this technique in various neurological diseases.
Ho, Leon C.; Wang, Bo; Conner, Ian P.; van der Merwe, Yolandi; Bilonick, Richard A.; Kim, Seong-Gi; Wu, Ed X.; Sigal, Ian A.; Wollstein, Gadi; Schuman, Joel S.; Chan, Kevin C.
2015-01-01
Purpose. Excitotoxicity has been linked to the pathogenesis of ocular diseases and injuries and may involve early degeneration of both anterior and posterior visual pathways. However, their spatiotemporal relationships remain unclear. We hypothesized that the effects of excitotoxic retinal injury (ERI) on the visual system can be revealed in vivo by diffusion tensor magnetic resonance imagining (DTI), manganese-enhanced magnetic resonance imagining (MRI), and optical coherence tomography (OCT). Methods. Diffusion tensor MRI was performed at 9.4 Tesla to monitor white matter integrity changes after unilateral N-methyl-D-aspartate (NMDA)-induced ERI in six Sprague-Dawley rats and six C57BL/6J mice. Additionally, four rats and four mice were intravitreally injected with saline to compare with NMDA-injected animals. Optical coherence tomography of the retina and manganese-enhanced MRI of anterograde transport were evaluated and correlated with DTI parameters. Results. In the rat optic nerve, the largest axial diffusivity decrease and radial diffusivity increase occurred within the first 3 and 7 days post ERI, respectively, suggestive of early axonal degeneration and delayed demyelination. The optic tract showed smaller directional diffusivity changes and weaker DTI correlations with retinal thickness compared with optic nerve, indicative of anterograde degeneration. The splenium of corpus callosum was also reorganized at 4 weeks post ERI. The DTI profiles appeared comparable between rat and mouse models. Furthermore, the NMDA-injured visual pathway showed reduced anterograde manganese transport, which correlated with diffusivity changes along but not perpendicular to optic nerve. Conclusions. Diffusion tensor MRI, manganese-enhanced MRI, and OCT provided an in vivo model system for characterizing the spatiotemporal changes in white matter integrity, the eye–brain relationships and structural–physiological relationships in the visual system after ERI. PMID:26066747
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Y; Cao, M; Kamrava, M
Purpose: Diffusion weighted MRI (DWI) is a promising imaging technique for early prediction of tumor response to radiation therapy. A recently proposed longitudinal DWI strategy using a Co-60 MRI guided RT system (MRIgRT) may bring functional MRI guided adaptive radiation therapy closer to clinical utility. We report our preliminary results of using this longitudinal DWI approach performed on the MRIgRT system for predicting the response of sarcoma patient to preop RT. Methods: Three sarcoma patients who underwent fractionated IMRT were recruited in this study. For all three patients DWI images were acquired immediately following his/her treatment. For each imaging session,more » ten slices were acquired interleaved with the b values covering the gross tumor volume (GTV). The diffusion images were processed to obtain the ADC maps using standard exponential fitting for each voxel. Regions of interest were drawn in the tumor on the diffusion images based on each patient’s clinical GTV contours. Each patient subsequently underwent surgery and the tumor necrosis score was available from standard pathology. The ADC values for each patient were compared to the necrosis scores to assess the predictive value of our longitudinal DWI for tumor response. Results: Each patient underwent 3 to 5 diffusion MRI scans depending on their treatment length. Patient 1 had a relatively unchanged ADC during the course of RT and a necrosis score of 30% at surgery. For patient 2, the mean ADC values decreased from 1.56 × 10-3 to 1.12 × 10-3 mm2/s and the patient’s necrosis score was less than 10%. Patient 3 had a slight increase in the ADC values from 0.59 × 10-3 to 0.71 × 10-3 mm2/s and patient’s necrosis score was 50%. Conclusion: Based on limited data from 3 patients, our longitudinal changes in tumor ADC assessed using the MRIgRT system correlated well with pathology results.« less
Model-free and analytical EAP reconstruction via spherical polar Fourier diffusion MRI.
Cheng, Jian; Ghosh, Aurobrata; Jiang, Tianzi; Deriche, Rachid
2010-01-01
How to estimate the diffusion Ensemble Average Propagator (EAP) from the DWI signals in q-space is an open problem in diffusion MRI field. Many methods were proposed to estimate the Orientation Distribution Function (ODF) that is used to describe the fiber direction. However, ODF is just one of the features of the EAP. Compared with ODF, EAP has the full information about the diffusion process which reflects the complex tissue micro-structure. Diffusion Orientation Transform (DOT) and Diffusion Spectrum Imaging (DSI) are two important methods to estimate the EAP from the signal. However, DOT is based on mono-exponential assumption and DSI needs a lot of samplings and very large b values. In this paper, we propose Spherical Polar Fourier Imaging (SPFI), a novel model-free fast robust analytical EAP reconstruction method, which almost does not need any assumption of data and does not need too many samplings. SPFI naturally combines the DWI signals with different b-values. It is an analytical linear transformation from the q-space signal to the EAP profile represented by Spherical Harmonics (SH). We validated the proposed methods in synthetic data, phantom data and real data. It works well in all experiments, especially for the data with low SNR, low anisotropy, and non-exponential decay.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gao, Y; Yang, Y; Rangwala, N
Purpose: To develop a reliable, 3D distortion-free diffusion MRI technique for longitudinal tumor response assessment and MRI-guided adaptive radiotherapy(RT). Methods: A diffusion prepared 3D turbo spin echo readout (DP-TSE) sequence was developed and compared with the conventional diffusion-weighted single-shot echo-planar-imaging (DW-ssEPI) sequence in a commercially available diffusion phantom, and one head-and-neck and one brain cancer patient on an MRI-guided RT system (ViewRay). In phantom study, the geometric fidelity was quantified as the ratio between the left-right (RL) and anterior-posterior (AP) dimension. Ten slices were measured on DP-TSE, DW-ssEPI and standard TSE images where the later was used as the geometricmore » reference. ADC accuracy was verified at both 0°C (reference ADC available) and room temperature with a range of diffusivity between 0.35 and 2.0*10{sup −3}mm{sup 2}/s. The ADC reproducibility was assessed based on 8 room-temperature measurements on 6 different days. In the pilot single-slice in-vivo study, CT images were used as the geometric reference, and ADC maps from both diffusion sequences were compared. Results: Distortion and susceptive-related artifact were severe in DW-ssEPI, with significantly lower RL/AP ratio (0.9579±0.0163) than DP-TSE (0.9990±0.0031) and TSE (0.9995±0.0031). ADCs from the two diffusion sequences both matched well with the vendor-provided values at 0°C; however DW-ssEPI fails to provide accurate ADC for high diffusivity vials at room temperature due to high noise level (10 times higher than DP-TSE). The DP-TSE sequence had excellent ADC reproducibility with <4% ADC variation among 8 separate measurements. In patient study, DP-TSE exhibited substantially improved geometric reliability. ROI analysis in ADC maps generated from DP-TSE and DW-ssEPI showed <5% difference where high b-value images were excluded from the latter approach due to excessive noise level. Conclusion: A diffusion MRI sequence with excellent geometric fidelity, accurate and highly reproducible ADC measurements was proposed for longitudinal tumor response assessment using an MRI-guided RT system. Yu Gao acknowledges research support from ViewRay.« less
MGH-USC Human Connectome Project Datasets with Ultra-High b-Value Diffusion MRI
Fan, Qiuyun; Witzel, Thomas; Nummenmaa, Aapo; Van Dijk, Koene R.A.; Van Horn, John D.; Drews, Michelle K.; Somerville, Leah H.; Sheridan, Margaret A.; Santillana, Rosario M.; Snyder, Jenna; Hedden, Trey; Shaw, Emily E.; Hollinshead, Marisa O.; Renvall, Ville; Zanzonico, Roberta; Keil, Boris; Cauley, Stephen; Polimeni, Jonathan R.; Tisdall, Dylan; Buckner, Randy L.; Wedeen, Van J.; Wald, Lawrence L.; Toga, Arthur W.; Rosen, Bruce R.
2015-01-01
The MGH-USC CONNECTOM MRI scanner housed at the Massachusetts General Hospital (MGH) is a major hardware innovation of the Human Connectome Project (HCP). The 3T CONNECTOM scanner is capable of producing magnetic field gradient of up to 300 mT/m strength for in vivo human brain imaging, which greatly shortens the time spent on diffusion encoding, and decreases the signal loss due to T2 decay. To demonstrate the capability of the novel gradient system, data of healthy adult participants were acquired for this MGH-USC Adult Diffusion Dataset (N=35), minimally preprocessed, and shared through the Laboratory of Neuro Imaging Image Data Archive (LONI IDA) and the WU-Minn Connectome Database (ConnecomeDB). Another purpose of sharing the data is to facilitate methodological studies of diffusion MRI (dMRI) analyses utilizing high diffusion contrast, which perhaps is not easily feasible with standard MR gradient system. In addition, acquisition of the MGH-Harvard-USC Lifespan Dataset is currently underway to include 120 healthy participants ranging from 8 to 90 years old, which will also be shared through LONI IDA and ConnectomeDB. Here we describe the efforts of the MGH-USC HCP consortium in acquiring and sharing the ultra-high b-value diffusion MRI data and provide a report on data preprocessing and access. We conclude with a demonstration of the example data, along with results of standard diffusion analyses, including q-ball Orientation Distribution Function (ODF) reconstruction and tractography. PMID:26364861
Walker, Lindsay; Chang, Lin-Ching; Nayak, Amritha; Irfanoglu, M Okan; Botteron, Kelly N; McCracken, James; McKinstry, Robert C; Rivkin, Michael J; Wang, Dah-Jyuu; Rumsey, Judith; Pierpaoli, Carlo
2016-01-01
The NIH MRI Study of normal brain development sought to characterize typical brain development in a population of infants, toddlers, children and adolescents/young adults, covering the socio-economic and ethnic diversity of the population of the United States. The study began in 1999 with data collection commencing in 2001 and concluding in 2007. The study was designed with the final goal of providing a controlled-access database; open to qualified researchers and clinicians, which could serve as a powerful tool for elucidating typical brain development and identifying deviations associated with brain-based disorders and diseases, and as a resource for developing computational methods and image processing tools. This paper focuses on the DTI component of the NIH MRI study of normal brain development. In this work, we describe the DTI data acquisition protocols, data processing steps, quality assessment procedures, and data included in the database, along with database access requirements. For more details, visit http://www.pediatricmri.nih.gov. This longitudinal DTI dataset includes raw and processed diffusion data from 498 low resolution (3 mm) DTI datasets from 274 unique subjects, and 193 high resolution (2.5 mm) DTI datasets from 152 unique subjects. Subjects range in age from 10 days (from date of birth) through 22 years. Additionally, a set of age-specific DTI templates are included. This forms one component of the larger NIH MRI study of normal brain development which also includes T1-, T2-, proton density-weighted, and proton magnetic resonance spectroscopy (MRS) imaging data, and demographic, clinical and behavioral data. Published by Elsevier Inc.
[Language Functions in the Frontal Association Area: Brain Mechanisms That Create Language].
Yamamoto, Kayako; Sakai, Kuniyoshi L
2016-11-01
Broca's area is known to be critically involved in language processing for more than 150 years. Recent neuroimaging techniques, including functional magnetic resonance imaging (fMRI) and diffusion MRI, enabled the subdivision of Broca's area based on both functional and anatomical aspects. Networks among the frontal association areas, especially the left inferior frontal gyrus (IFG), and other cortical regions in the temporal/parietal association areas, are also important for language-related information processing. Here, we review how neuroimaging studies, combined with research paradigms based on theoretical linguistics, have contributed to clarifying the critical roles of the left IFG in syntactic processing and those of language-related networks, including cortical and cerebellar regions.
Efficient gradient calibration based on diffusion MRI.
Teh, Irvin; Maguire, Mahon L; Schneider, Jürgen E
2017-01-01
To propose a method for calibrating gradient systems and correcting gradient nonlinearities based on diffusion MRI measurements. The gradient scaling in x, y, and z were first offset by up to 5% from precalibrated values to simulate a poorly calibrated system. Diffusion MRI data were acquired in a phantom filled with cyclooctane, and corrections for gradient scaling errors and nonlinearity were determined. The calibration was assessed with diffusion tensor imaging and independently validated with high resolution anatomical MRI of a second structured phantom. The errors in apparent diffusion coefficients along orthogonal axes ranged from -9.2% ± 0.4% to + 8.8% ± 0.7% before calibration and -0.5% ± 0.4% to + 0.8% ± 0.3% after calibration. Concurrently, fractional anisotropy decreased from 0.14 ± 0.03 to 0.03 ± 0.01. Errors in geometric measurements in x, y and z ranged from -5.5% to + 4.5% precalibration and were likewise reduced to -0.97% to + 0.23% postcalibration. Image distortions from gradient nonlinearity were markedly reduced. Periodic gradient calibration is an integral part of quality assurance in MRI. The proposed approach is both accurate and efficient, can be setup with readily available materials, and improves accuracy in both anatomical and diffusion MRI to within ±1%. Magn Reson Med 77:170-179, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. © 2016 Wiley Periodicals, Inc.
Efficient gradient calibration based on diffusion MRI
Teh, Irvin; Maguire, Mahon L.
2016-01-01
Purpose To propose a method for calibrating gradient systems and correcting gradient nonlinearities based on diffusion MRI measurements. Methods The gradient scaling in x, y, and z were first offset by up to 5% from precalibrated values to simulate a poorly calibrated system. Diffusion MRI data were acquired in a phantom filled with cyclooctane, and corrections for gradient scaling errors and nonlinearity were determined. The calibration was assessed with diffusion tensor imaging and independently validated with high resolution anatomical MRI of a second structured phantom. Results The errors in apparent diffusion coefficients along orthogonal axes ranged from −9.2% ± 0.4% to + 8.8% ± 0.7% before calibration and −0.5% ± 0.4% to + 0.8% ± 0.3% after calibration. Concurrently, fractional anisotropy decreased from 0.14 ± 0.03 to 0.03 ± 0.01. Errors in geometric measurements in x, y and z ranged from −5.5% to + 4.5% precalibration and were likewise reduced to −0.97% to + 0.23% postcalibration. Image distortions from gradient nonlinearity were markedly reduced. Conclusion Periodic gradient calibration is an integral part of quality assurance in MRI. The proposed approach is both accurate and efficient, can be setup with readily available materials, and improves accuracy in both anatomical and diffusion MRI to within ±1%. Magn Reson Med 77:170–179, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. PMID:26749277
Hofstetter, Shir; Friedmann, Naama; Assaf, Yaniv
2017-04-01
Human brain imaging revealed that the brain can undergo structural plasticity following new learning experiences. Most magnetic resonance imaging (MRI) uncovered morphometric alternation in cortical density after the long-term training of weeks to months. A recent diffusion tensor imaging (DTI) study has found changes in diffusion indices after 2 h of training, primarily in the hippocampus. However, whether a short learning experience can induce microstructural changes in the neocortex is still unclear. Here, we used diffusion MRI, a method sensitive to tissue microstructure, to study cortical plasticity. To attain cortical involvement, we used a short language task (under 1 h) of introducing new lexical items (flower names) to the lexicon. We have found significant changes in diffusivity in cortical regions involved in language and reading (inferior frontal gyrus, middle temporal gyrus, and inferior parietal lobule). In addition, the difference in the values of diffusivity correlated with the lexical learning rate in the task. Moreover, significant changes were found in white matter tracts near the cortex, and the extent of change correlated with behavioral measures of lexical learning rate. These findings provide first evidence of short-term cortical plasticity in the human brain after a short language learning task. It seems that short training of less than an hour of high cognitive demand can induce microstructural changes in the cortex, suggesting a rapid time scale of neuroplasticity and providing additional evidence of the power of MRI to investigate the temporal and spatial progressions of this process.
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
Modeling fluid diffusion in cerebral white matter with random walks in complex environments
NASA Astrophysics Data System (ADS)
Levy, Amichai; Cwilich, Gabriel; Buldyrev, Sergey V.; Weeden, Van J.
2012-02-01
Recent studies with diffusion MRI have shown new aspects of geometric order in the brain, including complex path coherence within the cerebral cortex, and organization of cerebral white matter and connectivity across multiple scales. The main assumption of these studies is that water molecules diffuse along myelin sheaths of neuron axons in the white matter and thus the anisotropy of their diffusion tensor observed by MRI can provide information about the direction of the axons connecting different parts of the brain. We model the diffusion of particles confined in the space of between the bundles of cylindrical obstacles representing fibrous structures of various orientations. We have investigated the directional properties of the diffusion, by studying the angular distribution of the end point of the random walks as a function of their length, to understand the scale over which the distribution randomizes. We will show evidence of qualitative change in the behavior of the diffusion for different volume fractions of obstacles. Comparisons with three-dimensional MRI images will be illustrated.
Design of Multishell Sampling Schemes with Uniform Coverage in Diffusion MRI
Caruyer, Emmanuel; Lenglet, Christophe; Sapiro, Guillermo; Deriche, Rachid
2017-01-01
Purpose In diffusion MRI, a technique known as diffusion spectrum imaging reconstructs the propagator with a discrete Fourier transform, from a Cartesian sampling of the diffusion signal. Alternatively, it is possible to directly reconstruct the orientation distribution function in q-ball imaging, providing so-called high angular resolution diffusion imaging. In between these two techniques, acquisitions on several spheres in q-space offer an interesting trade-off between the angular resolution and the radial information gathered in diffusion MRI. A careful design is central in the success of multishell acquisition and reconstruction techniques. Methods The design of acquisition in multishell is still an open and active field of research, however. In this work, we provide a general method to design multishell acquisition with uniform angular coverage. This method is based on a generalization of electrostatic repulsion to multishell. Results We evaluate the impact of our method using simulations, on the angular resolution in one and two bundles of fiber configurations. Compared to more commonly used radial sampling, we show that our method improves the angular resolution, as well as fiber crossing discrimination. Discussion We propose a novel method to design sampling schemes with optimal angular coverage and show the positive impact on angular resolution in diffusion MRI. PMID:23625329
Diffusion MRI: literature review in salivary gland tumors.
Attyé, A; Troprès, I; Rouchy, R-C; Righini, C; Espinoza, S; Kastler, A; Krainik, A
2017-07-01
Surgical resection is currently the best treatment for salivary gland tumors. A reliable magnetic resonance imaging mapping, encompassing tumor grade, location, and extension may assist safe and effective tumor resection and provide better information for patients regarding potential risks and morbidity after surgical intervention. However, direct examination of the tumor grade and extension using conventional morphological MRI remains difficult, often requiring contrast media injection and complex algorithms on perfusion imaging to estimate the degree of malignancy. In addition, contrast-enhanced MRI technique may be problematic due to the recently demonstrated gadolinium accumulation in the dentate nucleus of the cerebellum. Significant developments in magnetic resonance diffusion imaging, involving voxel-based quantitative analysis through the measurement of the apparent diffusion coefficient, have enhanced our knowledge on the different histopathological salivary tumor grades. Other diffusion imaging-derived techniques, including high-order tractography models, have recently demonstrated their usefulness in assessing the facial nerve location in parotid tumor context. All of these imaging techniques do not require contrast media injection. Our review starts by outlining the physical basis of diffusion imaging, before discussing findings from diagnostic studies testing its usefulness in assessing salivary glands tumors with diffusion MRI. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
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.
NASA Astrophysics Data System (ADS)
Hirai, K.; Katoh, Y.; Terada, N.; Kawai, S.
2016-12-01
In accretion disks, magneto-rotational instability (MRI; Balbus & Hawley, 1991) makes the disk gas in the magnetic turbulent state and drives efficient mass accretion into a central star. MRI drives turbulence through the evolution of the parasitic instability (PI; Goodman & Xu, 1994), which is related to both Kelvin-Helmholtz (K-H) instability and magnetic reconnection. The wave number vector of PI is strongly affected by both magnetic diffusivity and fluid viscosity (Pessah, 2010). This fact makes MHD simulation of MRI difficult, because we need to employ the numerical diffusivity for treating discontinuities in compressible MHD simulation schemes. Therefore, it is necessary to use an MHD scheme that has both high-order accuracy so as to resolve MRI driven turbulence and small numerical diffusivity enough to treat discontinuities. We have originally developed an MHD code by employing the scheme proposed by Kawai (2013). This scheme focuses on resolving turbulence accurately by using a high-order compact difference scheme (Lele, 1992), and meanwhile, the scheme treats discontinuities by using the localized artificial diffusivity method (Kawai, 2013). Our code also employs the pipeline algorithm (Matsuura & Kato, 2007) for MPI parallelization without diminishing the accuracy of the compact difference scheme. We carry out a 3-dimensional ideal MHD simulation with a net vertical magnetic field in the local shearing box disk model. We use 256x256x128 grids. Simulation results show that the spatially averaged turbulent stress induced by MRI linearly grows until around 2.8 orbital periods, and decreases after the saturation. We confirm the strong enhancement of the K-H mode PI at a timing just before the saturation, identified by the enhancement of its anisotropic wavenumber spectra in the 2-dimensional wavenumber space. The wave number of the maximum growth of PI reproduced in the simulation result is larger than the linear analysis. This discrepancy is explained by the simulation result that a shear flow created by MRI locally becomes thinner and faster due to interactions between antiparallel vortices induced by K-H mode PI, and this structure induces small scale waves which break the shear flow itself. We report the results of the simulation, and discuss how the saturation amplitude of MRI is determined.
Spurious group differences due to head motion in a diffusion MRI study
Yendiki, Anastasia; Koldewyn, Kami; Kakunoori, Sita; Kanwisher, Nancy; Fischl, Bruce
2014-01-01
Diffusion-weighted MRI (DW-MRI) has become a popular imaging modality for probing the microstructural properties of white matter and comparing them between populations in vivo. However, the contrast in DW-MRI arises from the microscopic random motion of water molecules in brain tissues, which makes it particularly sensitive to macroscopic head motion. Although this has been known since the introduction of DW-MRI, most studies that use this modality for group comparisons do not report measures of head motion for each group and rely on registration-based correction methods that cannot eliminate the full effects of head motion on the DW-MRI contrast. In this work we use data from children with autism and typically developing children to investigate the effects of head motion on differences in anisotropy and diffusivity measures between groups. We show that group differences in head motion can induce group differences in DW-MRI measures, and that this is the case even when comparing groups that include control subjects only, where no anisotropy or diffusivity differences are expected. We also show that such effects can be more prominent in some white-matter pathways than others, and that they can be ameliorated by including motion as a nuisance regressor in the analyses. Our results demonstrate the importance of taking head motion into account in any population study where one group might exhibit more head motion than the other. PMID:24269273
Cereda, Maurizio; Xin, Yi; Kadlecek, Stephen; Hamedani, Hooman; Rajaei, Jennia; Clapp, Justin; Rizi, Rahim R
2014-12-01
Considerable uncertainty remains about the best ventilator strategies for the mitigation of atelectasis and associated airspace stretch in patients with acute respiratory distress syndrome (ARDS). In addition to several immediate physiological effects, atelectasis increases the risk of ventilator-associated lung injury, which has been shown to significantly worsen ARDS outcomes. A number of lung imaging techniques have made substantial headway in clarifying the mechanisms of atelectasis. This paper reviews the contributions of computed tomography, positron emission tomography, and conventional MRI to understanding this phenomenon. In doing so, it also reveals several important shortcomings inherent to each of these approaches. Once these shortcomings have been made apparent, we describe how hyperpolarized (HP) gas MRI--a technique that is uniquely able to assess responses to mechanical ventilation and lung injury in peripheral airspaces--is poised to fill several of these knowledge gaps. The HP-MRI-derived apparent diffusion coefficient (ADC) quantifies the restriction of (3) He diffusion by peripheral airspaces, thereby obtaining pulmonary structural information at an extremely small scale. Lastly, this paper reports the results of a series of experiments that measured ADC in mechanically ventilated rats in order to investigate (i) the effect of atelectasis on ventilated airspaces, (ii) the relationship between positive end-expiratory pressure (PEEP), hysteresis, and the dimensions of peripheral airspaces, and (iii) the ability of PEEP and surfactant to reduce airspace dimensions after lung injury. An increase in ADC was found to be a marker of atelectasis-induced overdistension. With recruitment, higher airway pressures were shown to reduce stretch rather than worsen it. Moving forward, HP MRI has significant potential to shed further light on the atelectatic processes that occur during mechanical ventilation. Copyright © 2014 John Wiley & Sons, Ltd.
Wu, Shaoqin; Lv, Bin; Wang, Zhenchang; Xian, Junfang; Sabel, Bernhard A.; He, Huiguang; Jiao, Yonghong
2015-01-01
Purpose To explore the possible brain structural and functional alterations in congenital fibrosis of extraocular muscles type 1 (CFEOM1) patients using multimodal MRI imaging. Methods T1-weighted, diffusion tensor images and functional MRI data were obtained from 9 KIF21A positive patients and 19 age- and gender- matched healthy controls. Voxel based morphometry and tract based spatial statistics were applied to the T1-weighted and diffusion tensor images, respectively. Amplitude of low frequency fluctuations and regional homogeneity were used to process the functional MRI data. We then compared these multimodal characteristics between CFEOM1 patients and healthy controls. Results Compared with healthy controls, CFEOM1 patients demonstrated increased grey matter volume in bilateral frontal orbital cortex and in the right temporal pole. No diffusion indices changes were detected, indicating unaffected white matter microstructure. In addition, from resting state functional MRI data, trend of amplitude of low-frequency fluctuations increases were noted in the right inferior parietal lobe and in the right frontal cortex, and a trend of ReHo increase (p<0.001 uncorrected) in the left precentral gyrus, left orbital frontal cortex, temporal pole and cingulate gyrus. Conclusions CFEOM1 patients had structural and functional changes in grey matter, but the white matter was unaffected. These alterations in the brain may be due to the abnormality of extraocular muscles and their innervating nerves. Future studies should consider the possible correlations between brain morphological/functional findings and clinical data, especially pertaining to eye movements, to obtain more precise answers about the role of brain area changes and their functional consequence in CFEOM1. PMID:26186732
Cereda, Maurizio; Xin, Yi; Kadlecek, Stephen; Hamedani, Hooman; Rajaei, Jennia; Clapp, Justin; Rizi, Rahim R.
2014-01-01
Considerable uncertainty remains about the best ventilator strategies for the mitigation of atelectasis and associated airspace stretch in patients with acute respiratory distress syndrome (ARDS). In addition to several immediate physiological effects, atelectasis increases the risk of ventilator-associated lung injury (VALI), which has been shown to significantly worsen ARDS outcomes. A number of lung imaging techniques have made substantial headway in clarifying the mechanisms of atelectasis. This paper reviews the contributions of CT, PET, and conventional MRI to understanding this phenomenon. In doing so, it also reveals several important shortcomings inherent to each of these approaches. Once these shortcomings have been made apparent, we describe how hyperpolarized gas magnetic resonance imaging (HP MRI)—a technique that is uniquely able to assess responses to mechanical ventilation and lung injury in peripheral airspaces—is poised to fill several of these knowledge gaps. The HP-MRI-derived apparent diffusion coefficient (ADC) quantifies the restriction of 3He diffusion by peripheral airspaces, thereby obtaining pulmonary structural information at an extremely small scale. Lastly, this paper reports the results of a series of experiments that measured ADC in mechanically ventilated rats in order to investigate (i) the effect of atelectasis on ventilated airspaces; (ii) the relationship between positive end-expiratory pressure (PEEP), hysteresis, and the dimensions of peripheral airspaces; and (iii) the ability of PEEP and surfactant to reduce airspace dimensions after lung injury. An increase in ADC was found to be a marker of atelectasis-induced overdistension. With recruitment, higher airway pressures were shown to reduce stretch rather than worsen it. Moving forward, HP MRI has significant potential to shed further light on the atelectatic processes that occur during mechanical ventilation. PMID:24920074
Diffusion-weighted MRI in intrahepatic bile duct adenoma arising from the cirrhotic liver.
An, Chansik; Park, Sumi; Choi, Yoon Jung
2013-01-01
A 64-year-old male patient with liver cirrhosis underwent a CT study for hepatocellular carcinoma surveillance, which demonstrated a 1.4-cm hypervascular subcapsular tumor in the liver. On gadoxetic acid-enhanced MRI, the tumor showed brisk arterial enhancement and persistent hyperenhancement in the portal phase, but hypointensity in the hepatobiliary phase. On diffusion-weighted MRI, the tumor showed an apparent diffusion coefficient twofold greater than that of the background liver parenchyma, which suggested that the lesion was benign. The histologic diagnosis was intrahepatic bile duct adenoma with alcoholic liver cirrhosis.
Theilmann, Rebecca J; Borders, Rebecca; Trouard, Theodore P; Xia, Guowei; Outwater, Eric; Ranger-Moore, James; Gillies, Robert J; Stopeck, Alison
2004-01-01
Abstract A goal of oncology is the individualization of patient care to optimize therapeutic responses and minimize toxicities. Achieving this will require noninvasive, quantifiable, and early markers of tumor response. Preclinical data from xenografted tumors using a variety of antitumor therapies have shown that magnetic resonance imaging (MRI)-measured mobility of tissue water (apparent diffusion coefficient of water, or ADCw) is a biomarker presaging cell death in the tumor. This communication tests the hypothesis that changes in water mobility will quantitatively presage tumor responses in patients with metastatic liver lesions from breast cancer. A total of 13 patients with metastatic breast cancer and 60measurable liver lesionsweremonitored by diffusion MRI after initiation of new courses of chemotherapy. MR images were obtained prior to, and at 4, 11, and 39 days following the initiation of therapy for determination of volumes and ADCw values. The data indicate that diffusion MRI can predict response by 4 or 11 days after commencement of therapy, depending on the analytic method. The highest concordance was observed in tumor lesions that were less than 8 cm3 in volume at presentation. These results suggest that diffusion MRI can be useful to predict the response of liver metastases to effective chemotherapy. PMID:15720810
Noristani, Harun N.; Boukhaddaoui, Hassan; Saint-Martin, Guillaume; Auzer, Pauline; Sidiboulenouar, Rahima; Lonjon, Nicolas; Alibert, Eric; Tricaud, Nicolas; Goze-Bac, Christophe; Coillot, Christophe; Perrin, Florence E.
2017-01-01
Central nervous system (CNS) injury has been observed to lead to microglia activation and monocytes infiltration at the lesion site. Ex vivo diffusion magnetic resonance imaging (diffusion MRI or DWI) allows detailed examination of CNS tissues, and recent advances in clearing procedures allow detailed imaging of fluorescent-labeled cells at high resolution. No study has yet combined ex vivo diffusion MRI and clearing procedures to establish a possible link between microglia/monocytes response and diffusion coefficient in the context of spinal cord injury (SCI). We carried out ex vivo MRI of the spinal cord at different time-points after spinal cord transection followed by tetrahydrofuran based clearing and examined the density and morphology of microglia/monocytes using two-photon microscopy. Quantitative analysis revealed an early marked increase in microglial/monocytes density that is associated with an increase in the extension of the lesion measured using diffusion MRI. Morphological examination of microglia/monocytes somata at the lesion site revealed a significant increase in their surface area and volume as early as 72 hours post-injury. Time-course analysis showed differential microglial/monocytes response rostral and caudal to the lesion site. Microglia/monocytes showed a decrease in reactivity over time caudal to the lesion site, but an increase was observed rostrally. Direct comparison of microglia/monocytes morphology, obtained through multiphoton, and the longitudinal apparent diffusion coefficient (ADC), measured with diffusion MRI, highlighted that axonal integrity does not correlate with the density of microglia/monocytes or their somata morphology. We emphasize that differential microglial/monocytes reactivity rostral and caudal to the lesion site may thus coincide, at least partially, with reported temporal differences in debris clearance. Our study demonstrates that the combination of ex vivo diffusion MRI and two-photon microscopy may be used to follow structural tissue alteration. Lesion extension coincides with microglia/monocytes density; however, a direct relationship between ADC and microglia/monocytes density and morphology was not observed. We highlighted a differential rostro-caudal microglia/monocytes reactivity that may correspond to a temporal difference in debris clearance and axonal integrity. Thus, potential therapeutic strategies targeting microglia/monocytes after SCI may need to be adjusted not only with the time after injury but also relative to the location to the lesion site. PMID:28769787
Milchenko, Mikhail; Snyder, Abraham Z; LaMontagne, Pamela; Shimony, Joshua S; Benzinger, Tammie L; Fouke, Sarah Jost; Marcus, Daniel S
2016-07-01
Neuroimaging research often relies on clinically acquired magnetic resonance imaging (MRI) datasets that can originate from multiple institutions. Such datasets are characterized by high heterogeneity of modalities and variability of sequence parameters. This heterogeneity complicates the automation of image processing tasks such as spatial co-registration and physiological or functional image analysis. Given this heterogeneity, conventional processing workflows developed for research purposes are not optimal for clinical data. In this work, we describe an approach called Heterogeneous Optimization Framework (HOF) for developing image analysis pipelines that can handle the high degree of clinical data non-uniformity. HOF provides a set of guidelines for configuration, algorithm development, deployment, interpretation of results and quality control for such pipelines. At each step, we illustrate the HOF approach using the implementation of an automated pipeline for Multimodal Glioma Analysis (MGA) as an example. The MGA pipeline computes tissue diffusion characteristics of diffusion tensor imaging (DTI) acquisitions, hemodynamic characteristics using a perfusion model of susceptibility contrast (DSC) MRI, and spatial cross-modal co-registration of available anatomical, physiological and derived patient images. Developing MGA within HOF enabled the processing of neuro-oncology MR imaging studies to be fully automated. MGA has been successfully used to analyze over 160 clinical tumor studies to date within several research projects. Introduction of the MGA pipeline improved image processing throughput and, most importantly, effectively produced co-registered datasets that were suitable for advanced analysis despite high heterogeneity in acquisition protocols.
Miyazaki, Keiko; Jerome, Neil P; Collins, David J; Orton, Matthew R; d'Arcy, James A; Wallace, Toni; Moreno, Lucas; Pearson, Andrew D J; Marshall, Lynley V; Carceller, Fernando; Leach, Martin O; Zacharoulis, Stergios; Koh, Dow-Mu
2015-09-01
The objectives are to examine the reproducibility of functional MR imaging in children with solid tumours using quantitative parameters derived from diffusion-weighted (DW-) and dynamic contrast enhanced (DCE-) MRI. Patients under 16-years-of age with confirmed diagnosis of solid tumours (n = 17) underwent free-breathing DW-MRI and DCE-MRI on a 1.5 T system, repeated 24 hours later. DW-MRI (6 b-values, 0-1000 sec/mm(2)) enabled monoexponential apparent diffusion coefficient estimation using all (ADC0-1000) and only ≥100 sec/mm(2) (ADC100-1000) b-values. DCE-MRI was used to derive the transfer constant (K(trans)), the efflux constant (kep), the extracellular extravascular volume (ve), and the plasma fraction (vp), using a study cohort arterial input function (AIF) and the extended Tofts model. Initial area under the gadolinium enhancement curve and pre-contrast T1 were also calculated. Percentage coefficients of variation (CV) of all parameters were calculated. The most reproducible cohort parameters were ADC100-1000 (CV = 3.26%), pre-contrast T1 (CV = 6.21%), and K(trans) (CV = 15.23%). The ADC100-1000 was more reproducible than ADC0-1000, especially extracranially (CV = 2.40% vs. 2.78%). The AIF (n = 9) derived from this paediatric population exhibited sharper and earlier first-pass and recirculation peaks compared with the literature's adult population average. Free-breathing functional imaging protocols including DW-MRI and DCE-MRI are well-tolerated in children aged 6 - 15 with good to moderate measurement reproducibility. • Diffusion MRI protocol is feasible and well-tolerated in a paediatric oncology population. • DCE-MRI for pharmacokinetic evaluation is feasible and well tolerated in a paediatric oncology population. • Paediatric arterial input function (AIF) shows systematic differences from the adult population-average AIF. • Variation of quantitative parameters from paired functional MRI measurements were within 20%.
Passive Ventricular Mechanics Modelling Using MRI of Structure and Function
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
Delineation of early brain development from fetuses to infants with diffusion MRI and beyond.
Ouyang, Minhui; Dubois, Jessica; Yu, Qinlin; Mukherjee, Pratik; Huang, Hao
2018-04-12
Dynamic macrostructural and microstructural changes take place from the mid-fetal stage to 2 years after birth. Delineating structural changes of the brain during early development provides new insights into the complicated processes of both typical development and the pathological mechanisms underlying various psychiatric and neurological disorders including autism, attention deficit hyperactivity disorder and schizophrenia. Decades of histological studies have identified strong spatial and functional maturation gradients in human brain gray and white matter. The recent improvements in magnetic resonance imaging (MRI) techniques, especially diffusion MRI (dMRI), relaxometry imaging, and magnetization transfer imaging (MTI) have provided unprecedented opportunities to non-invasively quantify and map the early developmental changes at whole brain and regional levels. Here, we review the recent advances in understanding early brain structural development during the second half of gestation and the first two postnatal years using modern MR techniques. Specifically, we review studies that delineate the emergence and microstructural maturation of white matter tracts, as well as dynamic mapping of inhomogeneous cortical microstructural organization unique to fetuses and infants. These imaging studies converge into maturational curves of MRI measurements that are distinctive across different white matter tracts and cortical regions. Furthermore, contemporary models offering biophysical interpretations of the dMRI-derived measurements are illustrated to infer the underlying microstructural changes. Collectively, this review summarizes findings that contribute to charting spatiotemporally heterogeneous gray and white matter structural development, offering MRI-based biomarkers of typical brain development and setting the stage for understanding aberrant brain development in neurodevelopmental disorders. Copyright © 2018 Elsevier Inc. All rights reserved.
Passive ventricular mechanics modelling using MRI of structure and function.
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.
MGH-USC Human Connectome Project datasets with ultra-high b-value diffusion MRI.
Fan, Qiuyun; Witzel, Thomas; Nummenmaa, Aapo; Van Dijk, Koene R A; Van Horn, John D; Drews, Michelle K; Somerville, Leah H; Sheridan, Margaret A; Santillana, Rosario M; Snyder, Jenna; Hedden, Trey; Shaw, Emily E; Hollinshead, Marisa O; Renvall, Ville; Zanzonico, Roberta; Keil, Boris; Cauley, Stephen; Polimeni, Jonathan R; Tisdall, Dylan; Buckner, Randy L; Wedeen, Van J; Wald, Lawrence L; Toga, Arthur W; Rosen, Bruce R
2016-01-01
The MGH-USC CONNECTOM MRI scanner housed at the Massachusetts General Hospital (MGH) is a major hardware innovation of the Human Connectome Project (HCP). The 3T CONNECTOM scanner is capable of producing a magnetic field gradient of up to 300 mT/m strength for in vivo human brain imaging, which greatly shortens the time spent on diffusion encoding, and decreases the signal loss due to T2 decay. To demonstrate the capability of the novel gradient system, data of healthy adult participants were acquired for this MGH-USC Adult Diffusion Dataset (N=35), minimally preprocessed, and shared through the Laboratory of Neuro Imaging Image Data Archive (LONI IDA) and the WU-Minn Connectome Database (ConnectomeDB). Another purpose of sharing the data is to facilitate methodological studies of diffusion MRI (dMRI) analyses utilizing high diffusion contrast, which perhaps is not easily feasible with standard MR gradient system. In addition, acquisition of the MGH-Harvard-USC Lifespan Dataset is currently underway to include 120 healthy participants ranging from 8 to 90 years old, which will also be shared through LONI IDA and ConnectomeDB. Here we describe the efforts of the MGH-USC HCP consortium in acquiring and sharing the ultra-high b-value diffusion MRI data and provide a report on data preprocessing and access. We conclude with a demonstration of the example data, along with results of standard diffusion analyses, including q-ball Orientation Distribution Function (ODF) reconstruction and tractography. Copyright © 2015 Elsevier Inc. All rights reserved.
Mazzoli, Valentina; Oudeman, Jos; Nicolay, Klaas; Maas, Mario; Verdonschot, Nico; Sprengers, Andre M; Nederveen, Aart J; Froeling, Martijn; Strijkers, Gustav J
2016-12-01
In this study we investigated the changes in fiber length and diffusion parameters as a consequence of passive lengthening and stretching of the calf muscles. We hypothesized that changes in radial diffusivity (RD) are caused by changes in the muscle fiber cross sectional area (CSA) as a consequence of lengthening and shortening of the muscle. Diffusion Tensor MRI (DT-MRI) measurements were made twice in five healthy volunteers, with the foot in three different positions (30° plantarflexion, neutral position and 15° dorsiflexion). The muscles of the calf were manually segmented on co-registered high resolution anatomical scans, and maps of RD and axial diffusivity (AD) were reconstructed from the DT-MRI data. Fiber tractography was performed and mean fiber length was calculated for each muscle group. Significant negative correlations were found between the changes in RD and changes in fiber length in the dorsiflexed and plantarflexed positions, compared with the neutral foot position. Changes in AD did not correlate with changes in fiber length. Assuming a simple cylindrical model with constant volume for the muscle fiber, the changes in the muscle fiber CSA were calculated from the changes in fiber length. In line with our hypothesis, we observed a significant positive correlation of the CSA with the measured changes in RD. In conclusion, we showed that changes in diffusion coefficients induced by passive muscle stretching and lengthening can be explained by changes in muscle CSA, advancing the physiological interpretation of parameters derived from skeletal muscle DT-MRI. Copyright © 2016 John Wiley & Sons, Ltd.
Jabeen, S A; Cherukuri, Pavankumar; Mridula, Rukmini; Harshavardhana, K R; Gaddamanugu, Padmaja; Sarva, Sailaja; Meena, A K; Borgohain, Rupam; Jyotsna Rani, Y
2017-04-01
To study the frequency, imaging characteristics, and clinical predictors for development of periictal diffusion weighted MRI abnormalities. We prospectively analyzed electro clinical and imaging characteristic of adult patients with cluster of seizures or status epilepticus between November 2013 and November 2015, in whom the diffusion weighted imaging was done within 24h after the end of last seizure (clinical or electrographic). There were thirty patients who fulfilled the inclusion and exclusion criteria. Twenty patients (66%) had periictal MRI abnormalities. Nine patients (34%) did not have any MRI abnormality. All the patients with PMA had abnormalities on diffusion weighted imaging (DWI). Hippocampal abnormalities were seen in nine (53%), perisylvian in two (11.7%), thalamic in five (30%), splenium involvement in two (11.7%) and cortical involvement (temporo-occipital, parieto-occipital, temporo-parietal, fronto-parietal and fronto-temporal) in sixteen (94.1%) patients. Complete reversal of DWI changes was noted in sixteen (80%) patients and four (20%) patients showed partial resolution of MRI abnormalities. Mean duration of seizures was significantly higher among patients with PMA (59.11+20.97h) compared to those without MRI changes (27.33+9.33h) (p<0.001). Diffusion abnormalities on MRI are common in patients with cluster of seizures and status epilepticus and were highly concordant with clinical semiology and EEG activity. Patients with longer duration of seizures/status were more likely to have PMA. Copyright © 2017 Elsevier B.V. All rights reserved.
Idiopathic granulomatous mastitis: magnetic resonance imaging findings with diffusion MRI.
Aslan, Hulya; Pourbagher, Aysin; Colakoglu, Tamer
2016-07-01
Idiopathic granulomatous mastitis (IGM) is a rare benign breast disease with unknown etiology which can mimic breast carcinoma, both clinically and radiologically. Magnetic resonance imaging (MRI) findings of IGM have been previously described; however there is no study evaluating diffusion-weighted MRI findings of IGM. To analyze conventional, dynamic contrast-enhanced, and diffusion-weighted MRI signal characteristics of IGM by comparing it with the contralateral normal breast parenchyma. A total of 39 patients were included in the study. On dynamic contrast-enhanced MRI, the distribution and enhancement patterns of the lesions were evaluated. We also detected the frequencies of involving quadrants, retroareolar involvement, accompanying abscess, and skin edema. T2-weighted (T2W) and STIR signal intensities and both mean and minimum apparent diffusion coefficient (ADC) values were compared with the contralateral normal parenchyma. IGM showed significantly lower mean and minimum ADC values when compared with the normal parenchyma. Signal intensities on T2W and STIR sequences of the lesion were significantly higher than the normal parenchyma. On dynamic contrast-enhanced MRI, 7.7% of the patients had mass-like contrast enhancement, 92.3% of the patients had non-mass-like contrast enhancement. Abscess was positive in 33.3% of the patients. As a result, IGM showed commonly non-mass-like lesions with restricted diffusion. Although it is a benign pathology, it may show clustered ring-like enhancement like malignant lesions. © The Foundation Acta Radiologica 2015.
Transcortical Sensory Aphasia after Left Frontal Lobe Infarction: Loss of Functional Connectivity.
Kwon, Miseon; Shim, Woo Hyun; Kim, Sang-Joon; Kim, Jong S
2017-01-01
The underlying mechanism of transcortical sensory aphasia (TSA) caused by lesions occurring in the left frontal lobe remains unclear. We attempted to investigate the mechanism with the use of functional MRI (fMRI). We studied 2 patients with TSA after a left frontal infarction identified by diffusion-weighted MRI. As control subjects, a patient with transcortical motor aphasia and a healthy normal adult were chosen. The Korean version of Western Aphasia Battery was performed initially and at 3 months post stroke. We performed fMRI using verb generation and sentence completion tasks. Resting-state fMRI (rs-fMRI) was also obtained for network-level analysis initially and at 3 months post stroke. The results of diffusion- and perfusion-weighted MRI revealed no diffusion-perfusion mismatch. Initial fMRI in patients with TSA showed no reversed inter-/intrahemispheric activation patterns. rs-fMRI showed significantly decreased resting-state functional connectivity in the language network in patients with TSA compared with the control subjects. Follow-up rs-fMRI studies showed improvement in functional connectivity along with the recovery of patients' language function. Our data showed that the auditory comprehension deficits in patients with frontal lobe infarcts is attributed to difficulty accessing the posterior language area due to functional disconnection between language centers in the acute stage of stroke. © 2017 S. Karger AG, Basel.
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.
Detailed magnetic resonance imaging features of a case series of primary gliosarcoma.
Sampaio, Luísa; Linhares, Paulo; Fonseca, José
2017-12-01
Objective We aimed to characterise the magnetic resonance imaging (MRI) features of a case series of primary gliosarcoma, with the inclusion of diffusion-weighted imaging and perfusion imaging with dynamic susceptibility contrast MRI. Materials and methods We conducted a retrospective study of cases of primary gliosarcoma from the Pathology Department database from January 2006 to December 2014. Clinical and demographic data were obtained. Two neuroradiologists, blinded to diagnosis, assessed tumour location, signal intensity in T1 and T2-weighted images, pattern of enhancement, diffusion-weighted imaging and dynamic susceptibility contrast MRI studies on preoperative MRI. Results Seventeen patients with primary gliosarcomas had preoperative MRI study: seven men and 10 women, with a mean age of 59 years (range 27-74). All lesions were well demarcated, supratentorial and solitary (frontal n = 5, temporal n = 4, parietal n = 3); 13 tumours abutted the dural surface (8/13 with dural enhancement); T1 and T2-weighted imaging patterns were heterogeneous and the majority of lesions (12/17) showed a rim-like enhancement pattern with focal nodularities/irregular thickness. Restricted diffusion (mean apparent diffusion coefficient values 0.64 × 10 -3 mm 2 /s) in the more solid/thick components was present in eight out of 11 patients with diffusion-weighted imaging study. Dynamic susceptibility contrast MRI study ( n = 8) consistently showed hyperperfusion in non-necrotic/cystic components on relative cerebral volume maps. Conclusions The main distinguishing features of primary gliosarcoma are supratentorial and peripheral location, well-defined boundaries and a rim-like pattern of enhancement with an irregular thick wall. Diffusion-weighted imaging and relative cerebral volume map analysis paralleled primary gliosarcoma with high-grade gliomas, thus proving helpful in differential diagnosis.
Diffusion-weighted Breast MRI: Clinical Applications and Emerging Techniques
Partridge, Savannah C.; Nissan, Noam; Rahbar, Habib; Kitsch, Averi E.; Sigmund, Eric E.
2016-01-01
Diffusion weighted MRI (DWI) holds potential to improve the detection and biological characterization of breast cancer. DWI is increasingly being incorporated into breast MRI protocols to address some of the shortcomings of routine clinical breast MRI. Potential benefits include improved differentiation of benign and malignant breast lesions, assessment and prediction of therapeutic efficacy, and non-contrast detection of breast cancer. The breast presents a unique imaging environment with significant physiologic and inter-subject variations, as well as specific challenges to achieving reliable high quality diffusion weighted MR images. Technical innovations are helping to overcome many of the image quality issues that have limited widespread use of DWI for breast imaging. Advanced modeling approaches to further characterize tissue perfusion, complexity, and glandular organization may expand knowledge and yield improved diagnostic tools. PMID:27690173
Multistability of the Brain Network for Self-other Processing
Chen, Yi-An; Huang, Tsung-Ren
2017-01-01
Early fMRI studies suggested that brain areas processing self-related and other-related information were highly overlapping. Hypothesising functional localisation of the cortex, researchers have tried to locate “self-specific” and “other-specific” regions within these overlapping areas by subtracting suspected confounding signals in task-based fMRI experiments. Inspired by recent advances in whole-brain dynamic modelling, we instead explored an alternative hypothesis that similar spatial activation patterns could be associated with different processing modes in the form of different synchronisation patterns. Combining an automated synthesis of fMRI data with a presumption-free diffusion spectrum image (DSI) fibre-tracking algorithm, we isolated a network putatively composed of brain areas and white matter tracts involved in self-other processing. We sampled synchronisation patterns from the dynamical systems of this network using various combinations of physiological parameters. Our results showed that the self-other processing network, with simulated gamma-band activity, tended to stabilise at a number of distinct synchronisation patterns. This phenomenon, termed “multistability,” could serve as an alternative model in theorising the mechanism of processing self-other information. PMID:28256520
Marcuzzo, Stefania; Bonanno, Silvia; Padelli, Francesco; Moreno-Manzano, Victoria; García-Verdugo, José Manuel; Bernasconi, Pia; Mantegazza, Renato; Bruzzone, Maria Grazia; Zucca, Ileana
2016-01-01
Diffusion-weighted Magnetic Resonance Imaging (dMRI) has relevant applications in the microstructural characterization of the spinal cord, especially in neurodegenerative diseases. Animal models have a pivotal role in the study of such diseases; however, in vivo spinal dMRI of small animals entails additional challenges that require a systematical investigation of acquisition parameters. The purpose of this study is to compare three acquisition protocols and identify the scanning parameters allowing a robust estimation of the main diffusion quantities and a good sensitivity to neurodegeneration in the mouse spinal cord. For all the protocols, the signal-to-noise and contrast-to noise ratios and the mean value and variability of Diffusion Tensor metrics were evaluated in healthy controls. For the estimation of fractional anisotropy less variability was provided by protocols with more diffusion directions, for the estimation of mean, axial and radial diffusivity by protocols with fewer diffusion directions and higher diffusion weighting. Intermediate features (12 directions, b = 1200 s/mm2) provided the overall minimum inter- and intra-subject variability in most cases. In order to test the diagnostic sensitivity of the protocols, 7 G93A-SOD1 mice (model of amyotrophic lateral sclerosis) at 10 and 17 weeks of age were scanned and the derived diffusion parameters compared with those estimated in age-matched healthy animals. The protocols with an intermediate or high number of diffusion directions provided the best differentiation between the two groups at week 17, whereas only few local significant differences were highlighted at week 10. According to our results, a dMRI protocol with an intermediate number of diffusion gradient directions and a relatively high diffusion weighting is optimal for spinal cord imaging. Further work is needed to confirm these results and for a finer tuning of acquisition parameters. Nevertheless, our findings could be important for the optimization of acquisition protocols for preclinical and clinical dMRI studies on the spinal cord. PMID:27560686
Nilsson, Markus; van Westen, Danielle; Ståhlberg, Freddy; Sundgren, Pia C; Lätt, Jimmy
2013-08-01
Biophysical models that describe the outcome of white matter diffusion MRI experiments have various degrees of complexity. While the simplest models assume equal-sized and parallel axons, more elaborate ones may include distributions of axon diameters and axonal orientation dispersions. These microstructural features can be inferred from diffusion-weighted signal attenuation curves by solving an inverse problem, validated in several Monte Carlo simulation studies. Model development has been paralleled by microscopy studies of the microstructure of excised and fixed nerves, confirming that axon diameter estimates from diffusion measurements agree with those from microscopy. However, results obtained in vivo are less conclusive. For example, the amount of slowly diffusing water is lower than expected, and the diffusion-encoded signal is apparently insensitive to diffusion time variations, contrary to what may be expected. Recent understandings of the resolution limit in diffusion MRI, the rate of water exchange, and the presence of microscopic axonal undulation and axonal orientation dispersions may, however, explain such apparent contradictions. Knowledge of the effects of biophysical mechanisms on water diffusion in tissue can be used to predict the outcome of diffusion tensor imaging (DTI) and of diffusion kurtosis imaging (DKI) studies. Alterations of DTI or DKI parameters found in studies of pathologies such as ischemic stroke can thus be compared with those predicted by modelling. Observations in agreement with the predictions strengthen the credibility of biophysical models; those in disagreement could provide clues of how to improve them. DKI is particularly suited for this purpose; it is performed using higher b-values than DTI, and thus carries more information about the tissue microstructure. The purpose of this review is to provide an update on the current understanding of how various properties of the tissue microstructure and the rate of water exchange between microenvironments are reflected in diffusion MRI measurements. We focus on the use of biophysical models for extracting tissue-specific parameters from data obtained with single PGSE sequences on clinical MRI scanners, but results obtained with animal MRI scanners are also considered. While modelling of white matter is the central theme, experiments on model systems that highlight important aspects of the biophysical models are also reviewed.
MRI in multiple sclerosis: current status and future prospects
Bakshi, Rohit; Thompson, Alan J; Rocca, Maria A; Pelletier, Daniel; Dousset, Vincent; Barkhof, Frederik; Inglese, Matilde; Guttmann, Charles R G; Horsfield, Mark A; Filippi, Massimo
2008-01-01
Many promising MRI approaches for research or clinical management of multiple sclerosis (MS) have recently emerged, or are under development or refinement. Advanced MRI methods need to be assessed to determine whether they allow earlier diagnosis or better identification of phenotypes. Improved post-processing should allow more efficient and complete extraction of information from images. Magnetic resonance spectroscopy should improve in sensitivity and specificity with higher field strengths and should enable the detection of a wider array of metabolites. Diffusion imaging is moving closer to the goal of defining structural connectivity and, thereby, determining the functional significance of lesions at specific locations. Cell-specific imaging now seems feasible with new magnetic resonance contrast agents. The imaging of myelin water fraction brings the hope of providing a specific measure of myelin content. Ultra-high-field MRI increases sensitivity, but also presents new technical challenges. Here, we review these recent developments in MRI for MS, and also look forward to refinements in spinal-cord imaging, optic-nerve imaging, perfusion MRI, and functional MRI. Advances in MRI should improve our ability to diagnose, monitor, and understand the pathophysiology of MS. PMID:18565455
Mapping immune cell infiltration using restricted diffusion MRI.
Yeh, Fang-Cheng; Liu, Li; Hitchens, T Kevin; Wu, Yijen L
2017-02-01
Diffusion MRI provides a noninvasive way to assess tissue microstructure. Based on diffusion MRI, we propose a model-free method called restricted diffusion imaging (RDI) to quantify restricted diffusion and correlate it with cellularity. An analytical relation between q-space signals and the density of restricted spins was derived to quantify restricted diffusion. A phantom study was conducted to investigate the performance of RDI, and RDI was applied to an animal study to assess immune cell infiltration in myocardial tissues with ischemia-reperfusion injury. Our phantom study showed a correlation coefficient of 0.998 between cell density and the restricted diffusion quantified by RDI. The animal study also showed that the high-value regions in RDI matched well with the macrophage infiltration areas in the H&E stained slides. In comparison with diffusion tensor imaging (DTI), RDI exhibited its outperformance to detect macrophage infiltration and delineate inflammatory myocardium. RDI can be used to reveal cell density and detect immune cell infiltration. RDI exhibits better specificity than the diffusivity measurement derived from DTI. Magn Reson Med 77:603-612, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.
Novel Diffusion-Weighted MRI for High-Grade Prostate Cancer Detection
2016-10-01
in image resolution and scale.This process is critical for evaluating new imaging modalities.Our initial findings illustrate the potential of the...eligible for analysis as determined by adequate pathologic processing and MR images deemed to be of adequate quality by the study team. The...histology samples have been requested from the UIC biorepository for digitization All MR images have been collected and prepared for image processing
NASA Astrophysics Data System (ADS)
Nakamura, Takako; Ohana, Tsuguyori; Yabuno, Hajime; Kasai, Rumiko; Suzuki, Tetsuya; Hasebe, Terumitsu
2013-01-01
We have developed a simple and useful process for fabricating nanodiamond (ND) particles modified with an organogadolinium moiety by chemical modification for their use as a magnetic resonance imaging (MRI) contrast agent. The introduction of the organogadolinium moiety on the surface of the ND particles was performed by the condensation of ND and diethylenetriaminepentaacetic acid (DTPA) followed by treatment with GdCl3. The modified surfaces were evaluated by X-ray photoelectron spectroscopy, diffuse reflectance Fourier transform infrared spectroscopy, mass spectroscopy, and inductively coupled plasma atomic emission spectroscopy analyses. MRI experiments on the Gd-DTPA-ND particles indicated their high signal intensity on T1-weighted images.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thompson, Scott M., E-mail: Thompson.scott@mayo.edu; Gorny, Krzysztof R.; Jondal, Danielle E.
A 17-year-old previously healthy female presented with a progressive soft tissue infiltrative process involving the neck and thorax. Extensive diagnostic evaluation including multiple imaging, laboratory, and biopsy studies was nondiagnostic. Due to an urgent need to establish a diagnosis and several previous nondiagnostic biopsies, she was referred to interventional radiology for MRI-guided wire localization immediately prior to open surgical biopsy. Under general anesthesia, wires were placed in the areas of increased T2 signal within the bilateral splenius capitis muscles using intermittent MRI-guidance followed by immediate surgical biopsy down to the wires. Pathology confirmed the diagnosis of diffuse large B-cell lymphoma.
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.
Diffusion MRI in early cancer therapeutic response assessment
Galbán, C. J.; Hoff, B. A.; Chenevert, T. L.; Ross, B. D.
2016-01-01
Imaging biomarkers for the predictive assessment of treatment response in patients with cancer earlier than standard tumor volumetric metrics would provide new opportunities to individualize therapy. Diffusion-weighted MRI (DW-MRI), highly sensitive to microenvironmental alterations at the cellular level, has been evaluated extensively as a technique for the generation of quantitative and early imaging biomarkers of therapeutic response and clinical outcome. First demonstrated in a rodent tumor model, subsequent studies have shown that DW-MRI can be applied to many different solid tumors for the detection of changes in cellularity as measured indirectly by an increase in the apparent diffusion coefficient (ADC) of water molecules within the lesion. The introduction of quantitative DW-MRI into the treatment management of patients with cancer may aid physicians to individualize therapy, thereby minimizing unnecessary systemic toxicity associated with ineffective therapies, saving valuable time, reducing patient care costs and ultimately improving clinical outcome. This review covers the theoretical basis behind the application of DW-MRI to monitor therapeutic response in cancer, the analytical techniques used and the results obtained from various clinical studies that have demonstrated the efficacy of DW-MRI for the prediction of cancer treatment response. PMID:26773848
Terada, Yukinori; Toda, Hiroki; Okumura, Ryosuke; Ikeda, Naokado; Yuba, Yoshiaki; Katayama, Toshiro; Iwasaki, Koichi
2018-03-01
Microcystic meningioma, a rare meningioma subtype, can present diagnostic difficulty. We aimed to investigate the historadiological properties of microcystic meningioma using conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) analysis. We retrospectively analyzed conventional MRI and DWI results of six microcystic meningioma cases by examining their appearance and determining their apparent diffusion coefficient (ADC) values. The ADC values of the intratumoral components were normalized with ADC values of the cerebrospinal fluid in the lateral ventricle (ADC ratios). As cystic formations are frequently associated with microcystic meningiomas, their MRI characteristics were compared with the imaging data from 11 cystic meningiomas of non-microcystic subtypes. We found that cysts in microcystic meningioma tended to have a reticular appearance on DWI, as they did on gadolinium-enhanced T1-weighted imaging. Additionally, these reticular cysts had significantly lower ADC ratios than microcystic non-reticular and non-microcystic cysts. These DWI characteristics likely reflect the histological properties of microcystic meningioma. A reticular appearance on gadolinium-enhanced T1-weighted MRI and DWI, and cyst formation with relatively low ADC values can be diagnostic markers of microcystic meningiomas.
Measurement tensors in diffusion MRI: generalizing the concept of diffusion encoding.
Westin, Carl-Fredrik; Szczepankiewicz, Filip; Pasternak, Ofer; Ozarslan, Evren; Topgaard, Daniel; Knutsson, Hans; Nilsson, Markus
2014-01-01
In traditional diffusion MRI, short pulsed field gradients (PFG) are used for the diffusion encoding. The standard Stejskal-Tanner sequence uses one single pair of such gradients, known as single-PFG (sPFG). In this work we describe how trajectories in q-space can be used for diffusion encoding. We discuss how such encoding enables the extension of the well-known scalar b-value to a tensor-valued entity we call the diffusion measurement tensor. The new measurements contain information about higher order diffusion propagator covariances not present in sPFG. As an example analysis, we use this new information to estimate a Gaussian distribution over diffusion tensors in each voxel, described by its mean (a diffusion tensor) and its covariance (a 4th order tensor).
Characteristics of early MRI in children and adolescents with vanishing white matter.
van der Lei, Hannemieke D; Steenweg, Marjan E; Barkhof, Frederik; de Grauw, Ton; d'Hooghe, Marc; Morton, Richard; Shah, Siddharth; Wolf, Nicole; van der Knaap, Marjo S
2012-02-01
MRI in vanishing white matter typically shows diffuse abnormality of the cerebral white matter, which becomes increasingly rarefied and cystic. We investigated the MRI characteristics preceding this stage. In a retrospective observational study, we evaluated all available MRIs in our database of DNA-confirmed VWM patients and selected MRIs without diffuse cerebral white matter abnormalities and without signs of rarefaction or cystic degeneration in patients below 20 years of age. A previously established scoring list was used to evaluate the MRIs. An MRI of seven patients fulfilled the criteria. All had confluent and symmetrical abnormalities in the periventricular and bordering deep white matter. In young patients, myelination was delayed. The inner rim of the corpus callosum was affected in all patients. In early stages of VWM, MRI does not necessarily display diffuse cerebral white matter involvement and rarefaction or cystic degeneration. If the MRI abnormalities do not meet the criteria for VWM, it helps to look at the corpus callosum. If the inner rim (the callosal-septal interface) is affected, VWM should be considered. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.
Director Field Analysis (DFA): Exploring Local White Matter Geometric Structure in Diffusion MRI.
Cheng, Jian; Basser, Peter J
2018-01-01
In Diffusion Tensor Imaging (DTI) or High Angular Resolution Diffusion Imaging (HARDI), a tensor field or a spherical function field (e.g., an orientation distribution function field), can be estimated from measured diffusion weighted images. In this paper, inspired by the microscopic theoretical treatment of phases in liquid crystals, we introduce a novel mathematical framework, called Director Field Analysis (DFA), to study local geometric structural information of white matter based on the reconstructed tensor field or spherical function field: (1) We propose a set of mathematical tools to process general director data, which consists of dyadic tensors that have orientations but no direction. (2) We propose Orientational Order (OO) and Orientational Dispersion (OD) indices to describe the degree of alignment and dispersion of a spherical function in a single voxel or in a region, respectively; (3) We also show how to construct a local orthogonal coordinate frame in each voxel exhibiting anisotropic diffusion; (4) Finally, we define three indices to describe three types of orientational distortion (splay, bend, and twist) in a local spatial neighborhood, and a total distortion index to describe distortions of all three types. To our knowledge, this is the first work to quantitatively describe orientational distortion (splay, bend, and twist) in general spherical function fields from DTI or HARDI data. The proposed DFA and its related mathematical tools can be used to process not only diffusion MRI data but also general director field data, and the proposed scalar indices are useful for detecting local geometric changes of white matter for voxel-based or tract-based analysis in both DTI and HARDI acquisitions. The related codes and a tutorial for DFA will be released in DMRITool. Copyright © 2017 Elsevier B.V. All rights reserved.
Small-Animal Imaging Using Diffuse Fluorescence Tomography.
Davis, Scott C; Tichauer, Kenneth M
2016-01-01
Diffuse fluorescence tomography (DFT) has been developed to image the spatial distribution of fluorescence-tagged tracers in living tissue. This capability facilitates the recovery of any number of functional parameters, including enzymatic activity, receptor density, blood flow, and gene expression. However, deploying DFT effectively is complex and often requires years of know-how, especially for newer mutlimodal systems that combine DFT with conventional imaging systems. In this chapter, we step through the process of using MRI-DFT imaging of a receptor-targeted tracer in small animals.
Multiparametric Breast MRI of Breast Cancer
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
Lober, Robert M; Cho, Yoon-Jae; Tang, Yujie; Barnes, Patrick D; Edwards, Michael S; Vogel, Hannes; Fisher, Paul G; Monje, Michelle; Yeom, Kristen W
2014-03-01
While pediatric diffuse intrinsic pontine gliomas (DIPG) remain fatal, recent data have shown subgroups with distinct molecular biology and clinical behavior. We hypothesized that diffusion-weighted MRI can be used as a prognostic marker to stratify DIPG subsets with distinct clinical behavior. Apparent diffusion coefficient (ADC) values derived from diffusion-weighted MRI were computed in 20 consecutive children with treatment-naïve DIPG tumors. The median ADC for the cohort was used to stratify the tumors into low and high ADC groups. Survival, gender, therapy, and potential steroid effects were compared between the ADC groups. Median age at diagnosis was 6.6 (range 2.3-13.2) years, with median follow-up seven (range 1-36) months. There were 14 boys and six girls. Seventeen patients received radiotherapy, five received chemotherapy, and six underwent cerebrospinal fluid diversion. The median ADC of 1,295 × 10(-6) mm(2)/s for the cohort partitioned tumors into low or high diffusion groups, which had distinct median survivals of 3 and 13 months, respectively (log-rank p < 0.001). Low ADC tumors were found only in boys, whereas high ADC tumors were found in both boys and girls. Available tissue specimens in three low ADC tumors demonstrated high-grade histology, whereas one high ADC tumor demonstrated low-grade histology with a histone H3.1 K27M mutation and high-grade metastatic lesion at autopsy. ADC derived from diffusion-weighted MRI may identify prognostically distinct subgroups of pediatric DIPG.
Klenk, Christopher; Gawande, Rakhee; Uslu, Lebriz; Khurana, Aman; Qiu, Deqiang; Quon, Andrew; Donig, Jessica; Rosenberg, Jarrett; Luna-Fineman, Sandra; Moseley, Michael; Daldrup-Link, Heike E
2014-03-01
Imaging tests are essential for staging of children with cancer. However, CT and radiotracer-based imaging procedures are associated with substantial exposure to ionising radiation and risk of secondary cancer development later in life. Our aim was to create a highly effective, clinically feasible, ionising radiation-free staging method based on whole-body diffusion-weighted MRI and the iron supplement ferumoxytol, used off-label as a contrast agent. We compared whole-body diffusion-weighted MRI with standard clinical (18)F-fluorodeoxyglucose ((18)F-FDG) PET/CT scans in children and young adults with malignant lymphomas and sarcomas. Whole-body diffusion-weighted magnetic resonance images were generated by coregistration of colour-encoded ferumoxytol-enhanced whole-body diffusion-weighted MRI scans for tumour detection with ferumoxytol-enhanced T1-weighted MRI scans for anatomical orientation, similar to the concept of integrated (18)F-FDG PET/CT scans. Tumour staging results were compared using Cohen's κ statistics. Histopathology and follow-up imaging served as the standard of reference. Data was assessed in the per-protocol population. This study is registered with ClinicalTrials.gov, number NCT01542879. 22 of 23 recruited patients were analysed because one patient discontinued before completion of the whole-body scan. Mean exposure to ionising radiation was 12·5 mSv (SD 4·1) for (18)F-FDG PET/CT compared with zero for whole-body diffusion-weighted MRI. (18)F-FDG PET/CT detected 163 of 174 malignant lesions at 1325 anatomical regions and whole-body diffusion-weighted MRI detected 158. Comparing (18)F-FDG PET/CT to whole-body diffusion-weighted MRI, sensitivities were 93·7% (95% CI 89·0-96·8) versus 90·8% (85·5-94·7); specificities 97·7% (95% CI 96·7-98·5) versus 99·5% (98·9-99·8); and diagnostic accuracies 97·2% (93·6-99·4) versus 98·3% (97·4-99·2). Tumour staging results showed very good agreement between both imaging modalities with a κ of 0·93 (0·81-1·00). No adverse events after administration of ferumoxytol were recorded. Ferumoxytol-enhanced whole-body diffusion-weighted MRI could be an alternative to (18)F-FDG PET/CT for staging of children and young adults with cancer that is free of ionising radiation. This new imaging test might help to prevent long-term side-effects from radiographic staging procedures. Thrasher Research Fund and Clinical Health Research Institute at Stanford University. Copyright © 2014 Elsevier Ltd. All rights reserved.
Farrar, Danielle; Budson, Andrew E
2017-04-01
While the relationship between diffusion tensor imaging (DTI) measurements and training effects is explored by Voelker et al. (this issue), a cursory discussion of functional magnetic resonance imaging (fMRI) measurements categorizes increased activation with findings of greater white matter integrity. Evidence of the relationship between fMRI activation and white matter integrity is conflicting, as is the relationship between fMRI activation and training effects. An examination of the changes in fMRI activation in response to training is helpful, but the relationship between DTI and fMRI activation, particularly in the context of white matter changes, must be examined further before general conclusions can be drawn.
Kikuchi, Shingo; Onuki, Yoshinori; Kuribayashi, Hideto; Takayama, Kozo
2012-01-01
We reported previously that sustained release matrix tablets showed zero-order drug release without being affected by pH change. To understand drug release mechanisms more fully, we monitored the swelling and erosion of hydrating tablets using magnetic resonance imaging (MRI). Three different types of tablets comprised of polyion complex-forming materials and a hydroxypropyl methylcellulose (HPMC) were used. Proton density- and diffusion-weighted images of the hydrating tablets were acquired at intervals. Furthermore, apparent self-diffusion coefficient maps were generated from diffusion-weighted imaging to evaluate the state of hydrating tablets. Our findings indicated that water penetration into polyion complex tablets was faster than that into HPMC matrix tablets. In polyion complex tablets, water molecules were dispersed homogeneously and their diffusivity was relatively high, whereas in HPMC matrix tablets, water molecule movement was tightly restricted within the gel. An optimal tablet formulation determined in a previous study had water molecule penetration and diffusivity properties that appeared intermediate to those of polyion complex and HPMC matrix tablets; water molecules were capable of penetrating throughout the tablets and relatively high diffusivity was similar to that in the polyion complex tablet, whereas like the HPMC matrix tablet, it was well swollen. This study succeeded in characterizing the tablet hydration process. MRI provides profound insight into the state of water molecules in hydrating tablets; thus, it is a useful tool for understanding drug release mechanisms at a molecular level.
Zhang, Guangwen; Wang, Shuangshuang; Wen, Didi; Zhang, Jing; Wei, Xiaocheng; Ma, Wanling; Zhao, Weiwei; Wang, Mian; Wu, Guosheng; Zhang, Jinsong
2016-12-09
Water molecular diffusion in vivo tissue is much more complicated. We aimed to compare non-Gaussian diffusion models of diffusion-weighted imaging (DWI) including intra-voxel incoherent motion (IVIM), stretched-exponential model (SEM) and Gaussian diffusion model at 3.0 T MRI in patients with rectal cancer, and to determine the optimal model for investigating the water diffusion properties and characterization of rectal carcinoma. Fifty-nine consecutive patients with pathologically confirmed rectal adenocarcinoma underwent DWI with 16 b-values at a 3.0 T MRI system. DWI signals were fitted to the mono-exponential and non-Gaussian diffusion models (IVIM-mono, IVIM-bi and SEM) on primary tumor and adjacent normal rectal tissue. Parameters of standard apparent diffusion coefficient (ADC), slow- and fast-ADC, fraction of fast ADC (f), α value and distributed diffusion coefficient (DDC) were generated and compared between the tumor and normal tissues. The SEM exhibited the best fitting results of actual DWI signal in rectal cancer and the normal rectal wall (R 2 = 0.998, 0.999 respectively). The DDC achieved relatively high area under the curve (AUC = 0.980) in differentiating tumor from normal rectal wall. Non-Gaussian diffusion models could assess tissue properties more accurately than the ADC derived Gaussian diffusion model. SEM may be used as a potential optimal model for characterization of rectal cancer.
Kanmaz, Lutfi; Karavas, Erdal
2018-05-29
The purpose of this study was to evaluate the value of diffusion-weighted MRI (DW-MRI) in differentiating benign and malignant head and neck masses by comparing their apparent diffusion coefficient (ADC) values. The study included 32 patients with a neck mass >1 cm in diameter who were examined with echo planar DW-MRI. Two different diffusion gradients (b values of b = 0 and b = 1000 s/mm²) were applied. DWI and ADC maps of 32 neck masses in 32 patients were obtained. Mean ADC values of benign and malignant neck lesions were measured and compared statistically. A total of 15 (46.9%) malignant masses and 17 (53.1%) benign masses were determined. Of all the neck masses, the ADC value of cystic masses was the highest and that of lymphomas was the lowest. The mean ADC values of benign and malignant neck masses were 1.57 × 10 -3 mm²/s and 0.90 × 10 -3 mm²/s, respectively. The difference between mean ADC values of benign and malignant neck masses was significant ( p < 0.01). Diffusion-weighted MRI with ADC measurements can be useful in the differential diagnosis of neck masses.
Diffusion tensor imaging, white matter lesions, the corpus callosum, and gait in the elderly
USDA-ARS?s Scientific Manuscript database
Gait impairment is common in the elderly, especially affected by stroke and white matter hyper intensities found in conventional brain magnetic resonance imaging (MRI). Diffusion tensor imaging (DTI) is more sensitive to white matter damage than conventional MRI. The relationship between DTI measure...
Kim, Dong Gyu; Kim, Seong Ho; Kim, Oh Lyong; Cho, Yun Woo; Son, Su Min; Jang, Sung Ho
2009-01-01
There have been no studies on motor recovery in severe quadriplegic patients with traumatic brain injury (TBI) resulting from combined causes of weakness; this type of patient is often seen in rehabilitation clinics. We report on a quadriplegic patient who showed long-term motor recovery from severe weakness caused by a diffuse axonal injury (DAI) on the brainstem and a traumatic intracerebral hemorrhage (ICH) on left cerebral peduncle, as evaluated by diffuse tensor imaging (DTI) and functional MRI (fMRI). A 17-year-old male patient presented with quadriparesis at the onset of TBI. Over the 28-month period following the onset of the injury, the motor function of the four extremities slowly recovered to a range that was nearly normal. Two longitudinal DTIs (at 11 and 28 months from onset) and fMRI (at 28 months) were performed. Fractional anisotropy and an apparent diffusion coefficient were measured using the region of interest method, and diffusion tensor tractography was conducted using a DTI/fMRI combination. Fractional anisotrophy values in the brainstem, which were markedly decreased on the 11-month DTI, were increased on the 28-month DTI. On the fMRI performed at 28 months, the contralateral primary sensori-motor cortex was activated by the movement of either the right or left hand. Diffusion tensor tractography showed that fiber tracts originating from the motor-sensory cortex passed through the known corticospinal tract pathway to the pons. It seems that the weakness of this patient recovered due to the recovery of the damaged corticospinal tracts.
Pitfalls of diffusion-weighted imaging of the female pelvis
Duarte, Ana Luisa; Dias, João Lopes; Cunha, Teresa Margarida
2018-01-01
Diffusion-weighted imaging (DWI) is widely used in protocols for magnetic resonance imaging (MRI) of the female pelvis. It provides functional and structural information about biological tissues, without the use of ionizing radiation or intravenous administration of contrast medium. High signal intensity on DWI with simultaneous low signal intensity on apparent diffusion coefficient maps is usually associated with malignancy. However, that pattern can also be seen in many benign lesions, a fact that should be recognized by radiologists. Correlating DWI findings with those of conventional (T1- and T2-weighted) MRI sequences and those of contrast-enhanced MRI sequences is mandatory in order to avoid potential pitfalls. The aim of this review article is the description of the most relevant physiological and benign pathological conditions of the female pelvis that can show restricted diffusion on DWI. PMID:29559764
Barnea-Goraly, Naama; Weinzimer, Stuart A.; Mauras, Nelly; Beck, Roy W.; Marzelli, Matt J.; Mazaika, Paul K.; Aye, Tandy; White, Neil H.; Tsalikian, Eva; Fox, Larry; Kollman, Craig; Cheng, Peiyao; Reiss, Allan L.
2013-01-01
Background The ability to lie still in an MRI scanner is essential for obtaining usable image data. To reduce motion, young children are often sedated, adding significant cost and risk. Objective We assessed the feasibility of using a simple and affordable behavioral desensitization program to yield high-quality brain MRI scans in sedation-free children. Materials and methods 222 children (4–9.9 years), 147 with type 1 diabetes and 75 age-matched non-diabetic controls, participated in a multi-site study focused on effects of type 1 diabetes on the developing brain. T1-weighted and diffusion-weighted imaging (DWI) MRI scans were performed. All children underwent behavioral training and practice MRI sessions using either a commercial MRI simulator or an inexpensive mock scanner consisting of a toy tunnel, vibrating mat, and video player to simulate the sounds and feel of the MRI scanner. Results 205 children (92.3%), mean age 7±1.7 years had high-quality T1-W scans and 174 (78.4%) had high-quality diffusion-weighted scans after the first scan session. With a second scan session, success rates were 100% and 92.5% for T1-and diffusion-weighted scans, respectively. Success rates did not differ between children with type 1 diabetes and children without diabetes, or between centers using a commercial MRI scan simulator and those using the inexpensive mock scanner. Conclusion Behavioral training can lead to a high success rate for obtaining high-quality T1-and diffusion-weighted brain images from a young population without sedation. PMID:24096802
NASA Astrophysics Data System (ADS)
Murase, Kenya; Yamazaki, Youichi; Shinohara, Masaaki; Kawakami, Kazunori; Kikuchi, Keiichi; Miki, Hitoshi; Mochizuki, Teruhito; Ikezoe, Junpei
2001-10-01
The purpose of this study was to present an application of a novel denoising technique for improving the accuracy of cerebral blood flow (CBF) images generated from dynamic susceptibility contrast-enhanced magnetic resonance imaging (DSC-MRI). The method presented in this study was based on anisotropic diffusion (AD). The usefulness of this method was firstly investigated using computer simulations. We applied this method to patient data acquired using a 1.5 T MR system. After a bolus injection of Gd-DTPA, we obtained 40-50 dynamic images with a 1.32-2.08 s time resolution in 4-6 slices. The dynamic images were processed using the AD method, and then the CBF images were generated using pixel-by-pixel deconvolution analysis. For comparison, the CBF images were also generated with or without processing the dynamic images using a median or Gaussian filter. In simulation studies, the standard deviation of the CBF values obtained after processing by the AD method was smaller than that of the CBF values obtained without any processing, while the mean value agreed well with the true CBF value. Although the median and Gaussian filters also reduced image noise, the mean CBF values were considerably underestimated compared with the true values. Clinical studies also suggested that the AD method was capable of reducing the image noise while preserving the quantitative accuracy of CBF images. In conclusion, the AD method appears useful for denoising DSC-MRI, which will make the CBF images generated from DSC-MRI more reliable.
Studholme, Colin; Frias, Antonio E.
2017-01-01
Altered macroscopic anatomical characteristics of the cerebral cortex have been identified in individuals affected by various neurodevelopmental disorders. However, the cellular developmental mechanisms that give rise to these abnormalities are not understood. Previously, advances in image reconstruction of diffusion magnetic resonance imaging (MRI) have made possible high-resolution in utero measurements of water diffusion anisotropy in the fetal brain. Here, diffusion anisotropy within the developing fetal cerebral cortex is longitudinally characterized in the rhesus macaque, focusing on gestation day (G85) through G135 of the 165 d term. Additionally, for subsets of animals characterized at G90 and G135, immunohistochemical staining was performed, and 3D structure tensor analyses were used to identify the cellular processes that most closely parallel changes in water diffusion anisotropy with cerebral cortical maturation. Strong correlations were found between maturation of dendritic arbors on the cellular level and the loss of diffusion anisotropy with cortical development. In turn, diffusion anisotropy changes were strongly associated both regionally and temporally with cortical folding. Notably, the regional and temporal dependence of diffusion anisotropy and folding were distinct from the patterns observed for cerebral cortical surface area expansion. These findings strengthen the link proposed in previous studies between cellular-level changes in dendrite morphology and noninvasive diffusion MRI measurements of the developing cerebral cortex and support the possibility that, in gyroencephalic species, structural differentiation within the cortex is coupled to the formation of gyri and sulci. SIGNIFICANCE STATEMENT Abnormal brain morphology has been found in populations with neurodevelopmental disorders. However, the mechanisms linking cellular level and macroscopic maturation are poorly understood, even in normal brains. This study contributes new understanding to this subject using serial in utero MRI measurements of rhesus macaque fetuses, from which macroscopic and cellular information can be derived. We found that morphological differentiation of dendrites was strongly associated both regionally and temporally with folding of the cerebral cortex. Interestingly, parallel associations were not observed with cortical surface area expansion. These findings support the possibility that perturbed morphological differentiation of cells within the cortex may underlie abnormal macroscopic characteristics of individuals affected by neurodevelopmental disorders. PMID:28069920
Tóth, Eszter; Szabó, Nikoletta; Csete, Gergõ; Király, András; Faragó, Péter; Spisák, Tamás; Bencsik, Krisztina; Vécsei, László; Kincses, Zsigmond T
2017-01-01
Objective: Cortical pathology, periventricular demyelination, and lesion formation in multiple sclerosis (MS) are related (Hypothesis 1). Factors in the cerebrospinal fluid close to these compartments could possibly drive the parallel processes. Alternatively, the cortical atrophy could be caused by remote axonal transection (Hypothesis 2). Since MRI can differentiate between demyelination and axon loss, we used this imaging modality to investigate the correlation between the pattern of diffusion parameter changes in the periventricular- and deep white matter and the gray matter atrophy. Methods: High-resolution T1-weighted, FLAIR, and diffusion MRI images were acquired in 52 RRMS patients and 50 healthy, age-matched controls. We used EDSS to estimate the clinical disability. We used Tract Based Spatial Statistics to compare diffusion parameters (fractional anisotropy, mean, axial, and radial diffusivity) between groups. We evaluated global brain, white, and gray matter atrophy with SIENAX. Averaged, standard diffusion parameters were calculated in four compartment: periventricular lesioned and normal appearing white matter, non-periventricular lesioned and normal appearing white matter. PLS regression was used to identify which diffusion parameter and in which compartment best predicts the brain atrophy and clinical disability. Results: In our diffusion tensor imaging study compared to controls we found extensive alterations of fractional anisotropy, mean and radial diffusivity and smaller changes of axial diffusivity (maximal p > 0.0002) in patients that suggested demyelination in the lesioned and in the normal appearing white matter. We found significant reduction in total brain, total white, and gray matter (patients: 718.764 ± 14.968, 323.237 ± 7.246, 395.527 ± 8.050 cm 3 , controls: 791.772 ± 22.692, 355.350 ± 10.929, 436.422 ± 12.011 cm 3 ; mean ± SE), ( p < 0.015; p < 0.0001; p < 0.009; respectively) of patients compared to controls. The PLS analysis revealed a combination of demyelination-like diffusion parameters (higher mean and radial diffusivity in patients) in the lesions and in the non-lesioned periventricular white matter, which best predicted the gray matter atrophy ( p < 0.001). Similarly, EDSS was best predicted by the radial diffusivity of the lesions and the non-lesioned periventricular white matter, but axial diffusivity of the periventricular lesions also contributed significantly ( p < 0.0001). Interpretation: Our investigation showed that gray matter atrophy and white matter demyelination are related in MS but white matter axonal loss does not significantly contribute to the gray matter pathology.
Steventon, Jessica J.; Trueman, Rebecca C.; Rosser, Anne E.; Jones, Derek K.
2016-01-01
Background Huge advances have been made in understanding and addressing confounds in diffusion MRI data to quantify white matter microstructure. However, there has been a lag in applying these advances in clinical research. Some confounds are more pronounced in HD which impedes data quality and interpretability of patient-control differences. This study presents an optimised analysis pipeline and addresses specific confounds in a HD patient cohort. Method 15 HD gene-positive and 13 matched control participants were scanned on a 3T MRI system with two diffusion MRI sequences. An optimised post processing pipeline included motion, eddy current and EPI correction, rotation of the B matrix, free water elimination (FWE) and tractography analysis using an algorithm capable of reconstructing crossing fibres. The corpus callosum was examined using both a region-of-interest and a deterministic tractography approach, using both conventional diffusion tensor imaging (DTI)-based and spherical deconvolution analyses. Results Correcting for CSF contamination significantly altered microstructural metrics and the detection of group differences. Reconstructing the corpus callosum using spherical deconvolution produced a more complete reconstruction with greater sensitivity to group differences, compared to DTI-based tractography. Tissue volume fraction (TVF) was reduced in HD participants and was more sensitive to disease burden compared to DTI metrics. Conclusion Addressing confounds in diffusion MR data results in more valid, anatomically faithful white matter tract reconstructions with reduced within-group variance. TVF is recommended as a complementary metric, providing insight into the relationship with clinical symptoms in HD not fully captured by conventional DTI metrics. PMID:26335798
Steventon, Jessica J; Trueman, Rebecca C; Rosser, Anne E; Jones, Derek K
2016-05-30
Huge advances have been made in understanding and addressing confounds in diffusion MRI data to quantify white matter microstructure. However, there has been a lag in applying these advances in clinical research. Some confounds are more pronounced in HD which impedes data quality and interpretability of patient-control differences. This study presents an optimised analysis pipeline and addresses specific confounds in a HD patient cohort. 15 HD gene-positive and 13 matched control participants were scanned on a 3T MRI system with two diffusion MRI sequences. An optimised post processing pipeline included motion, eddy current and EPI correction, rotation of the B matrix, free water elimination (FWE) and tractography analysis using an algorithm capable of reconstructing crossing fibres. The corpus callosum was examined using both a region-of-interest and a deterministic tractography approach, using both conventional diffusion tensor imaging (DTI)-based and spherical deconvolution analyses. Correcting for CSF contamination significantly altered microstructural metrics and the detection of group differences. Reconstructing the corpus callosum using spherical deconvolution produced a more complete reconstruction with greater sensitivity to group differences, compared to DTI-based tractography. Tissue volume fraction (TVF) was reduced in HD participants and was more sensitive to disease burden compared to DTI metrics. Addressing confounds in diffusion MR data results in more valid, anatomically faithful white matter tract reconstructions with reduced within-group variance. TVF is recommended as a complementary metric, providing insight into the relationship with clinical symptoms in HD not fully captured by conventional DTI metrics. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.
The grey matter correlates of impaired decision-making in multiple sclerosis
Muhlert, Nils; Sethi, Varun; Cipolotti, Lisa; Haroon, Hamied; Parker, Geoff J M; Yousry, Tarek; Wheeler-Kingshott, Claudia; Miller, David; Ron, Maria; Chard, Declan
2015-01-01
Objective People with multiple sclerosis (MS) have difficulties with decision-making but it is unclear if this is due to changes in impulsivity, risk taking, deliberation or risk adjustment, and how this relates to brain pathology. Methods We assessed these aspects of decision-making in 105 people with MS and 43 healthy controls. We used a novel diffusion MRI method, diffusion orientational complexity (DOC), as an index of grey matter pathology in regions associated with decision-making and also measured grey matter tissue volumes and white matter lesion volumes. Results People with MS showed less adjustment to risk and slower decision-making than controls. Moreover, impaired decision-making correlated with reduced executive function, memory and processing speed. Decision-making impairments were most prevalent in people with secondary progressive MS. They were seen in patients with cognitive impairment and those without cognitive impairment. On diffusion MRI, people with MS showed DOC changes in all regions except the occipital cortex, relative to controls. Risk adjustment correlated with DOC in the hippocampi and deliberation time with DOC in the medial prefrontal, middle frontal gyrus, anterior cingulate and caudate parcellations and with white matter lesion volumes. Conclusions These data clarify the features of decision-making deficits in MS, and provide the first evidence that they relate to grey and white matter abnormalities seen using MRI. PMID:25006208
Kretzschmar, M; Bieri, O; Miska, M; Wiewiorski, M; Hainc, N; Valderrabano, V; Studler, U
2015-04-01
The purpose of this study was to characterize the collagen component of repair tissue (RT) of the talus after autologous matrix-induced chondrogenesis (AMIC) using quantitative T2 and diffusion-weighted imaging. Mean T2 values and diffusion coefficients of AMIC-RT and normal cartilage of the talus of 25 patients with posttraumatic osteochondral lesions and AMIC repair were compared in a cross-sectional design using partially spoiled steady-state free precession (pSSFP) for T2 quantification, and diffusion-weighted double-echo steady-state (dwDESS) for diffusion measurement. RT and cartilage were graded with modified Noyes and MOCART scores on morphological sequences. An association between follow-up interval and quantitative MRI measures was assessed using multivariate regression, after stratifying the cohort according to time interval between surgery and MRI. Mean T2 of the AMIC-RT and cartilage were 43.1 ms and 39.1 ms, respectively (p = 0.26). Mean diffusivity of the RT (1.76 μm(2)/ms) was significantly higher compared to normal cartilage (1.46 μm(2)/ms) (p = 0.0092). No correlation was found between morphological and quantitative parameters. RT diffusivity was lowest in the subgroup with follow-up >28 months (p = 0.027). Compared to T2-mapping, dwDESS demonstrated greater sensitivity in detecting differences in the collagen matrix between AMIC-RT and cartilage. Decreased diffusivity in patients with longer follow-up times may indicate an increased matrix organization of RT. • MRI is used to assess morphology of the repair tissue during follow-up. • Quantitative MRI allows an estimation of biochemical properties of the repair tissue. • Differences between repair tissue and cartilage were more significant with dwDESS than T2 mapping.
[See the thinking brain: a story about water].
Le Bihan, D
2008-01-01
Among the astonishing Einstein's papers from 1905, there is one which unexpectedly gave birth to a powerful method to explore the brain. Molecular diffusion was explained by Einstein on the basis of the random translational motion of molecules which results from their thermal energy. In the mid 1980s it was shown that water diffusion in the brain could be imaged using MRI. During their random displacements water molecules probe tissue structure at a microscopic scale, interacting with cell membranes and, thus, providing unique information on the functional architecture of tissues. A dramatic application of diffusion MRI has been brain ischemia, following the discovery that water diffusion drops immediately after the onset of an ischemic event, when brain cells undergo swelling through cytotoxic edema. On the other hand, water diffusion is anisotropic in white matter, because axon membranes limit molecular movement perpendicularly to the fibers. This feature can be exploited to map out the orientation in space of the white matter tracks and image brain connections. More recently, it has been shown that diffusion MRI could accurately detect cortical activation. As the diffusion response precedes by several seconds the hemodynamic response captured by BOLD fMRI, it has been suggested that water diffusion could reflect early neuronal events, such as the transient swelling of activated cortical cells. If confirmed, this discovery will represent a significant breakthrough, allowing non invasive access to a direct physiological marker of brain activation. This approach will bridge the gap between invasive optical imaging techniques in neuronal cell cultures, and current functional neuroimaging approaches in humans, which are based on indirect and remote blood flow changes.
NASA Astrophysics Data System (ADS)
Luk, Alex T.; Lin, Yuting; Grimmond, Brian; Sood, Anup; Uzgiris, Egidijus E.; Nalcioglu, Orhan; Gulsen, Gultekin
2013-03-01
Since diffuse optical tomography (DOT) is a low spatial resolution modality, it is desirable to validate its quantitative accuracy with another well-established imaging modality, such as magnetic resonance imaging (MRI). In this work, we have used a polymer based bi-functional MRI-optical contrast agent (Gd-DTPA-polylysine-IR800) in collaboration with GE Global Research. This multi-modality contrast agent provided not only co-localization but also the same kinetics, to cross-validate two imaging modalities. Bi-functional agents are injected to the rats and pharmacokinetics at the bladder are recovered using both optical and MR imaging. DOT results are validated using MRI results as "gold standard"
Morawski, Markus; Kirilina, Evgeniya; Scherf, Nico; Jäger, Carsten; Reimann, Katja; Trampel, Robert; Gavriilidis, Filippos; Geyer, Stefan; Biedermann, Bernd; Arendt, Thomas; Weiskopf, Nikolaus
2017-11-28
Recent breakthroughs in magnetic resonance imaging (MRI) enabled quantitative relaxometry and diffusion-weighted imaging with sub-millimeter resolution. Combined with biophysical models of MR contrast the emerging methods promise in vivo mapping of cyto- and myelo-architectonics, i.e., in vivo histology using MRI (hMRI) in humans. The hMRI methods require histological reference data for model building and validation. This is currently provided by MRI on post mortem human brain tissue in combination with classical histology on sections. However, this well established approach is limited to qualitative 2D information, while a systematic validation of hMRI requires quantitative 3D information on macroscopic voxels. We present a promising histological method based on optical 3D imaging combined with a tissue clearing method, Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging compatible Tissue hYdrogel (CLARITY), adapted for hMRI validation. Adapting CLARITY to the needs of hMRI is challenging due to poor antibody penetration into large sample volumes and high opacity of aged post mortem human brain tissue. In a pilot experiment we achieved transparency of up to 8 mm-thick and immunohistochemical staining of up to 5 mm-thick post mortem brain tissue by a combination of active and passive clearing, prolonged clearing and staining times. We combined 3D optical imaging of the cleared samples with tailored image processing methods. We demonstrated the feasibility for quantification of neuron density, fiber orientation distribution and cell type classification within a volume with size similar to a typical MRI voxel. The presented combination of MRI, 3D optical microscopy and image processing is a promising tool for validation of MRI-based microstructure estimates. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Wada, Masae; Hasegawa, Daisuke; Hamamoto, Yuji; Yu, Yoshihiko; Fujiwara-Igarashi, Aki; Fujita, Michio
2017-07-01
Although MRI has become widely used in small animal practice, little is known about the validity of advanced MRI techniques such as diffusion-weighted imaging and diffusion tensor imaging. The aim of this retrospective analytical observational study was to investigate the characteristics of diffusion parameters, that is the apparent diffusion coefficient and fractional anisotropy, in dogs with a solitary intracranial meningioma or histiocytic sarcoma. Dogs were included based on the performance of diffusion MRI and histological confirmation. Statistical analyses were performed to compare apparent diffusion coefficient and fractional anisotropy for the two types of tumor in the intra- and peritumoral regions. Eleven cases with meningioma and six with histiocytic sarcoma satisfied the inclusion criteria. Significant differences in apparent diffusion coefficient value (× 10 -3 mm 2 /s) between meningioma vs. histiocytic sarcoma were recognized in intratumoral small (1.07 vs. 0.76) and large (1.04 vs. 0.77) regions of interest, in the peritumoral margin (0.93 vs. 1.08), and in the T2 high region (1.21 vs. 1.41). Significant differences in fractional anisotropy values were found in the peritumoral margin (0.29 vs. 0.24) and the T2 high region (0.24 vs. 0.17). The current study identified differences in measurements of apparent diffusion coefficient and fractional anisotropy for meningioma and histiocytic sarcoma in a small sample of dogs. In addition, we observed that all cases of intracranial histiocytic sarcoma showed leptomeningeal enhancement and/or mass formation invading into the sulci in the contrast study. Future studies are needed to determine the sensitivity of these imaging characteristics for differentiating between these tumor types. © 2017 American College of Veterinary Radiology.
Hurley, Samuel A.; Samsonov, Alexey A.; Adluru, Nagesh; Hosseinbor, Ameer Pasha; Mossahebi, Pouria; Tromp, Do P.M.; Zakszewski, Elizabeth; Field, Aaron S.
2011-01-01
Abstract The image contrast in magnetic resonance imaging (MRI) is highly sensitive to several mechanisms that are modulated by the properties of the tissue environment. The degree and type of contrast weighting may be viewed as image filters that accentuate specific tissue properties. Maps of quantitative measures of these mechanisms, akin to microstructural/environmental-specific tissue stains, may be generated to characterize the MRI and physiological properties of biological tissues. In this article, three quantitative MRI (qMRI) methods for characterizing white matter (WM) microstructural properties are reviewed. All of these measures measure complementary aspects of how water interacts with the tissue environment. Diffusion MRI, including diffusion tensor imaging, characterizes the diffusion of water in the tissues and is sensitive to the microstructural density, spacing, and orientational organization of tissue membranes, including myelin. Magnetization transfer imaging characterizes the amount and degree of magnetization exchange between free water and macromolecules like proteins found in the myelin bilayers. Relaxometry measures the MRI relaxation constants T1 and T2, which in WM have a component associated with the water trapped in the myelin bilayers. The conduction of signals between distant brain regions occurs primarily through myelinated WM tracts; thus, these methods are potential indicators of pathology and structural connectivity in the brain. This article provides an overview of the qMRI stain mechanisms, acquisition and analysis strategies, and applications for these qMRI stains. PMID:22432902
Sepehrband, Farshid; Clark, Kristi A.; Ullmann, Jeremy F.P.; Kurniawan, Nyoman D.; Leanage, Gayeshika; Reutens, David C.; Yang, Zhengyi
2015-01-01
We examined whether quantitative density measures of cerebral tissue consistent with histology can be obtained from diffusion magnetic resonance imaging (MRI). By incorporating prior knowledge of myelin and cell membrane densities, absolute tissue density values were estimated from relative intra-cellular and intra-neurite density values obtained from diffusion MRI. The NODDI (neurite orientation distribution and density imaging) technique, which can be applied clinically, was used. Myelin density estimates were compared with the results of electron and light microscopy in ex vivo mouse brain and with published density estimates in a healthy human brain. In ex vivo mouse brain, estimated myelin densities in different sub-regions of the mouse corpus callosum were almost identical to values obtained from electron microscopy (Diffusion MRI: 42±6%, 36±4% and 43±5%; electron microscopy: 41±10%, 36±8% and 44±12% in genu, body and splenium, respectively). In the human brain, good agreement was observed between estimated fiber density measurements and previously reported values based on electron microscopy. Estimated density values were unaffected by crossing fibers. PMID:26096639
Clinical applications of advanced magnetic resonance imaging techniques for arthritis evaluation
Martín Noguerol, Teodoro; Luna, Antonio; Gómez Cabrera, Marta; Riofrio, Alexie D
2017-01-01
Magnetic resonance imaging (MRI) has allowed a comprehensive evaluation of articular disease, increasing the detection of early cartilage involvement, bone erosions, and edema in soft tissue and bone marrow compared to other imaging techniques. In the era of functional imaging, new advanced MRI sequences are being successfully applied for articular evaluation in cases of inflammatory, infectious, and degenerative arthropathies. Diffusion weighted imaging, new fat suppression techniques such as DIXON, dynamic contrast enhanced-MRI, and specific T2 mapping cartilage sequences allow a better understanding of the physiopathological processes that underlie these different arthropathies. They provide valuable quantitative information that aids in their differentiation and can be used as potential biomarkers of articular disease course and treatment response. PMID:28979849
Tu, Zhanhai; Xiao, Zebin; Zheng, Yingyan; Huang, Hongjie; Yang, Libin; Cao, Dairong
2018-01-01
Background Little is known about the value of computed tomography (CT) and magnetic resonance imaging (MRI) combined with diffusion-weighted imaging (DWI) in distinguishing malignant from benign skull-involved lesions. Purpose To evaluate the discriminative value of DWI combined with conventional CT and MRI for differentiating between benign and malignant skull-involved lesions. Material and Methods CT and MRI findings of 58 patients with pathologically proven skull-involved lesions (43 benign and 15 malignant) were retrospectively reviewed. Conventional CT and MRI characteristics and apparent diffusion coefficient (ADC) value of the two groups were evaluated and compared. Multivariate logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the differential performance of each parameter separately and together. Results The presence of cortical defects or break-through and ill-defined margins were associated with malignant skull-involved lesions (both P < 0.05). Malignant skull-involved lesions demonstrated a significantly lower ADC ( P = 0.016) than benign lesions. ROC curve analyses indicated that a combination of CT, MRI, and DWI with an ADC ≤ 0.703 × 10 -3 mm 2 /s showed optimal sensitivity, while DWI along showed optimal specificity of 88.4% in differentiating between benign and malignant skull-involved lesions. Conclusion The combination of CT, MRI, and DWI can help to differentiate malignant from benign skull-involved lesions. CT + MRI + DWI offers optimal sensitivity, while DWI offers optimal specificity.
Bayesian uncertainty quantification in linear models for diffusion MRI.
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.
Bajpai, Jyoti; Gamnagatti, Shivanand; Kumar, Rakesh; Sreenivas, Vishnubhatla; Sharma, Mehar Chand; Khan, Shah Alam; Rastogi, Shishir; Malhotra, Arun; Safaya, Rajni; Bakhshi, Sameer
2011-04-01
Histological necrosis, the current standard for response evaluation in osteosarcoma, is attainable after neoadjuvant chemotherapy. To establish the role of surrogate markers of response prediction and evaluation using MRI in the early phases of the disease. Thirty-one treatment-naïve osteosarcoma patients received three cycles of neoadjuvant chemotherapy followed by surgery during 2006-2008. All patients underwent baseline and post-chemotherapy conventional, diffusion-weighted and dynamic contrast-enhanced MRI. Taking histological response (good response ≥90% necrosis) as the reference standard, various parameters of MRI were compared to it. A tumor was considered ellipsoidal; volume, average tumor plane and its relative value (average tumor plane relative/body surface area) was calculated using the standard formula for ellipse. Receiver operating characteristic curves were generated to assess best threshold and predictability. After deriving thresholds for each parameter in univariable analysis, multivariable analysis was carried out. Both pre-and post-chemotherapy absolute and relative-size parameters correlated well with necrosis. Apparent diffusion coefficient did not correlate with necrosis; however, on adjusting for volume, significant correlation was found. Thus, we could derive a new parameter: diffusion per unit volume. In osteosarcoma, chemotherapy response can be predicted and evaluated by conventional and diffusion-weighted MRI early in the disease course and it correlates well with necrosis. Further, newly derived parameter diffusion per unit volume appears to be a sensitive substitute for response evaluation in osteosarcoma.
In vivo high-resolution 7 Tesla MRI shows early and diffuse cortical alterations in CADASIL.
De Guio, François; Reyes, Sonia; Vignaud, Alexandre; Duering, Marco; Ropele, Stefan; Duchesnay, Edouard; Chabriat, Hugues; Jouvent, Eric
2014-01-01
Recent data suggest that early symptoms may be related to cortex alterations in CADASIL (Cerebral Autosomal-Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy), a monogenic model of cerebral small vessel disease (SVD). The aim of this study was to investigate cortical alterations using both high-resolution T2* acquisitions obtained with 7 Tesla MRI and structural T1 images with 3 Tesla MRI in CADASIL patients with no or only mild symptomatology (modified Rankin's scale ≤1 and Mini Mental State Examination (MMSE) ≥24). Complete reconstructions of the cortex using 7 Tesla T2* acquisitions with 0.7 mm isotropic resolution were obtained in 11 patients (52.1±13.2 years, 36% male) and 24 controls (54.8±11.0 years, 42% male). Seven Tesla T2* within the cortex and cortical thickness and morphology obtained from 3 Tesla images were compared between CADASIL and control subjects using general linear models. MMSE, brain volume, cortical thickness and global sulcal morphology did not differ between groups. By contrast, T2* measured by 7 Tesla MRI was significantly increased in frontal, parietal, occipital and cingulate cortices in patients after correction for multiple testing. These changes were not related to white matter lesions, lacunes or microhemorrhages in patients having no brain atrophy compared to controls. Seven Tesla MRI, by contrast to state of the art post-processing of 3 Tesla acquisitions, shows diffuse T2* alterations within the cortical mantle in CADASIL whose origin remains to be determined.
Mardor, Yael; Roth, Yiftach; Ocherashvilli, Aharon; Spiegelmann, Roberto; Tichler, Thomas; Daniels, Dianne; Maier, Stephan E; Nissim, Ouzi; Ram, Zvi; Baram, Jacob; Orenstein, Arie; Pfeffer, Raphael
2004-01-01
Abstract Diffusion-weighted magnetic resonance imaging (DWMRI) is sensitive to tissues' biophysical characteristics, including apparent diffusion coefficients (ADCs) and volume fractions of water in different populations. In this work, we evaluate the clinical efficacy of DWMRI and high diffusion-weighted magnetic resonance imaging (HDWMRI), acquired up to b = 4000 sec/mm2 to amplify sensitivity to water diffusion properties, in pretreatment prediction of brain tumors' response to radiotherapy. Twelve patients with 20 brain lesions were studied. Six ring-enhancing lesions were excluded due to their distinct diffusion characteristics. Conventional and DWMRI were acquired on a 0.5-T MRI. Response to therapy was determined from relative changes in tumor volumes calculated from contrast-enhanced T1-weighted MRI, acquired before and a mean of 46 days after beginning therapy. ADCs and a diffusion index, RD, reflecting tissue viability based on water diffusion were calculated from DWMRIs. Pretreatment values of ADC and RD were found to correlate significantly with later tumor response/nonresponse (r = 0.76, P < .002 and r = 0.77, P < .001). This correlation implies that tumors with low pretreatment diffusion values, indicating high viability, will respond better to radiotherapy than tumors with high diffusion values, indicating necrosis. These results demonstrate the feasibility of using DWMRI for pretreatment prediction of response to therapy in patients with brain tumors undergoing radiotherapy. PMID:15140402
Mardor, Yael; Roth, Yiftach; Ochershvilli, Aharon; Spiegelmann, Roberto; Tichler, Thomas; Daniels, Dianne; Maier, Stephan E; Nissim, Ouzi; Ram, Zvi; Baram, Jacob; Orenstein, Arie; Pfeffer, Raphael
2004-01-01
Diffusion-weighted magnetic resonance imaging (DWMRI) is sensitive to tissues' biophysical characteristics, including apparent diffusion coefficients (ADCs) and volume fractions of water in different populations. In this work, we evaluate the clinical efficacy of DWMRI and high diffusion-weighted magnetic resonance imaging (HDWMRI), acquired up to b = 4000 sec/mm(2) to amplify sensitivity to water diffusion properties, in pretreatment prediction of brain tumors' response to radiotherapy. Twelve patients with 20 brain lesions were studied. Six ring-enhancing lesions were excluded due to their distinct diffusion characteristics. Conventional and DWMRI were acquired on a 0.5-T MRI. Response to therapy was determined from relative changes in tumor volumes calculated from contrast-enhanced T1-weighted MRI, acquired before and a mean of 46 days after beginning therapy. ADCs and a diffusion index, R(D), reflecting tissue viability based on water diffusion were calculated from DWMRIs. Pretreatment values of ADC and R(D) were found to correlate significantly with later tumor response/nonresponse (r = 0.76, P <.002 and r = 0.77, P <.001). This correlation implies that tumors with low pretreatment diffusion values, indicating high viability, will respond better to radiotherapy than tumors with high diffusion values, indicating necrosis. These results demonstrate the feasibility of using DWMRI for pretreatment prediction of response to therapy in patients with brain tumors undergoing radiotherapy.
Reid, Lee B; Sale, Martin V; Cunnington, Ross; Mattingley, Jason B; Rose, Stephen E
2017-09-01
We have reported reliable changes in behavior, brain structure, and function in 24 healthy right-handed adults who practiced a finger-thumb opposition sequence task with their left hand for 10 min daily, over 4 weeks. Here, we extend these findings by using diffusion MRI to investigate white-matter changes in the corticospinal tract, basal-ganglia, and connections of the dorsolateral prefrontal cortex. Twenty-three participant datasets were available with pre-training and post-training scans. Task performance improved in all participants (mean: 52.8%, SD: 20.0%; group P < 0.01 FWE) and widespread microstructural changes were detected across the motor system of the "trained" hemisphere. Specifically, region-of-interest-based analyses of diffusion MRI (n = 22) revealed significantly increased fractional anisotropy (FA) in the right caudate nucleus (4.9%; P < 0.05 FWE), and decreased mean diffusivity in the left nucleus accumbens (-1.3%; P < 0.05 FWE). Diffusion MRI tractography (n = 22), seeded by sensorimotor cortex fMRI activation, also revealed increased FA in the right corticospinal tract (mean 3.28%; P < 0.05 FWE) predominantly reflecting decreased radial diffusivity. These changes were consistent throughout the entire length of the tract. The left corticospinal tract did not show any changes. FA also increased in white matter connections between the right middle frontal gyrus and both right caudate nucleus (17/22 participants; P < 0.05 FWE) and right supplementary motor area (18/22 participants; P < 0.05 FWE). Equivalent changes in FA were not seen in the left (non-trained) hemisphere. In combination with our functional and structural findings, this study provides detailed, multifocal evidence for widespread neuroplastic changes in the human brain resulting from motor training. Hum Brain Mapp 38:4302-4312, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Newcombe, Virginia F J; Williams, Guy B; Scoffings, Daniel; Cross, Justin; Carpenter, T Adrian; Pickard, John D; Menon, David K
2010-05-01
An improved in vivo understanding of variations in neuropathology in the vegetative state (VS) may aid diagnosis, improve prognostication and help refine the selection of patients for particular treatment regimes. The authors have used diffusion tensor imaging (DTI) to characterise the extent and location of white matter loss in VS secondary to traumatic brain injury (TBI) and ischaemic-hypoxic injury. Twelve patients with VS (seven TBI, five ischaemic/hypoxic injuries) underwent MRI including DTI at a minimum of 3 months postinjury. Mean apparent diffusion coefficient, fractional anisotropy and eigenvalues were obtained for whole-brain grey and white matter, the pons, thalamus, ventral midbrain, dorsal midbrain and the corpus callosum. DTI measures of supratentorial damage were compared with a summed measure from the JFK modified Coma Recovery Scale (CRS-R) and with a three-point scale of functional magnetic resonance imaging (fMRI) response to an auditory paradigm to assess whether residual integrity of supratentorial white matter connectivity correlated with cortical processing. Conventional radiological approaches did not detect lesions in regions where quantitative DTI demonstrated abnormalities. There was evidence of marked, broadly similar, abnormalities in the supratentorial grey- and white-matter compartments from both aetiologies. In contrast, discordant findings were found in the infratentorial compartment, with DTI abnormalities in the brainstem confined to the TBI group. Supratentorial DTI abnormalities correlated with the CRS-R as well as responses to an fMRI paradigm that detected convert cognitive processing. DTI may help to characterise differences in patients in VS. These findings may have implications for response to therapies, and should be taken into account in trials of interventions aimed at arousal in VS.
Holleran, Laurena; Kim, Joong Hee; Gangolli, Mihika; Stein, Thor; Alvarez, Victor; McKee, Ann; Brody, David L
2017-03-01
Chronic traumatic encephalopathy (CTE) is a progressive degenerative disorder associated with repetitive traumatic brain injury. One of the primary defining neuropathological lesions in CTE, based on the first consensus conference, is the accumulation of hyperphosphorylated tau in gray matter sulcal depths. Post-mortem CTE studies have also reported myelin loss, axonal injury and white matter degeneration. Currently, the diagnosis of CTE is restricted to post-mortem neuropathological analysis. We hypothesized that high spatial resolution advanced diffusion MRI might be useful for detecting white matter microstructural changes directly adjacent to gray matter tau pathology. To test this hypothesis, formalin-fixed post-mortem tissue blocks from the superior frontal cortex of ten individuals with an established diagnosis of CTE were obtained from the Veterans Affairs-Boston University-Concussion Legacy Foundation brain bank. Advanced diffusion MRI data was acquired using an 11.74 T MRI scanner at Washington University with 250 × 250 × 500 µm 3 spatial resolution. Diffusion tensor imaging, diffusion kurtosis imaging and generalized q-sampling imaging analyses were performed in a blinded fashion. Following MRI acquisition, tissue sections were tested for phosphorylated tau immunoreactivity in gray matter sulcal depths. Axonal disruption in underlying white matter was assessed using two-dimensional Fourier transform analysis of myelin black gold staining. A robust image co-registration method was applied to accurately quantify the relationship between diffusion MRI parameters and histopathology. We found that white matter underlying sulci with high levels of tau pathology had substantially impaired myelin black gold Fourier transform power coherence, indicating axonal microstructural disruption (r = -0.55, p = 0.0015). Using diffusion tensor MRI, we found that fractional anisotropy (FA) was modestly (r = 0.53) but significantly (p = 0.0012) correlated with axonal disruption, where lower FA was associated with greater axonal disruption in white matter directly adjacent to hyperphosphorylated tau positive sulci. In summary, our findings indicate that axonal disruption and tau pathology are closely associated, and high spatial resolution ex vivo diffusion MRI has the potential to detect microstructural alterations observed in CTE tissue. Future studies will be required to determine whether this approach can be applied to living people.
Notohamiprodjo, Mike; Staehler, Michael; Steiner, Nicole; Schwab, Felix; Sourbron, Steven P; Michaely, Henrik J; Helck, Andreas D; Reiser, Maximilian F; Nikolaou, Konstantin
2013-06-01
To investigate a multiparametric magnetic resonance imaging (MRI) approach comprising diffusion-weighted imaging (DWI), blood oxygen-dependent (BOLD), and dynamic contrast-enhanced (DCE) MRI for characterization and differentiation of primary renal cell carcinoma (RCC). Fourteen patients with clear-cell carcinoma and four patients with papillary RCC were examined with DWI, BOLD MRI, and DCE MRI at 1.5T. The apparent diffusion coefficient (ADC) was calculated with a monoexponential decay. The spin-dephasing rate R2* was derived from parametric R2* maps. DCE-MRI was analyzed using a two-compartment exchange model allowing separation of perfusion (plasma flow [FP] and plasma volume [VP]), permeability (permeability surface area product [PS]), and extravascular extracellular volume (VE). Statistical analysis was performed with Wilcoxon signed-rank test, Pearson's correlation coefficient, and receiver operating characteristic curve analysis. Clear-cell RCC showed higher ADC and lower R2* compared to papillary subtypes, but differences were not significant. FP of clear-cell subtypes was significantly higher than in papillary RCC. Perfusion parameters showed moderate but significant inverse correlation with R2*. VE showed moderate inverse correlation with ADC. Fp and Vp showed best sensitivity for histological differentiation. Multiparametric MRI comprising DWI, BOLD, and DCE MRI is feasible for assessment of primary RCC. BOLD moderately correlates to DCE MRI-derived perfusion. ADC shows moderate correlation to the extracellular volume, but does not correlate to tumor oxygenation or perfusion. In this preliminary study DCE-MRI appeared superior to BOLD and DWI for histological differentiation. Copyright © 2013 AUR. Published by Elsevier Inc. All rights reserved.
Heusch, Philipp; Köhler, Jens; Wittsack, Hans-Joerg; Heusner, Till A; Buchbender, Christian; Poeppel, Thorsten D; Nensa, Felix; Wetter, Axel; Gauler, Thomas; Hartung, Verena; Lanzman, Rotem S
2013-11-01
To assess the feasibility of non-Gaussian DWI as part of a FDG-PET/MRI protocol in patients with histologically proven non-small cell lung cancer. 15 consecutive patients with histologically proven NSCLC (mean age 61 ± 11 years) were included in this study and underwent whole-body FDG-PET/MRI following whole-body FDG-PET/CT. As part of the whole-body FDG-PET/MRI protocol, an EPI-sequence with 5 b-values (0, 100, 500, 1000 and 2000 s/mm(2)) was acquired for DWI of the thorax during free-breathing. Volume of interest (VOI) measurements were performed to determine the maximum and mean standardized uptake value (SUV(max); SUV(mean)). A region of interest (ROI) was manually drawn around the tumor on b=0 images and then transferred to the corresponding parameter maps to assess ADC(mono), D(app) and K(app). To assess the goodness of the mathematical fit R(2) was calculated for monoexponential and non-Gaussian analysis. Spearman's correlation coefficients were calculated to compare SUV values and diffusion coefficients. A Student's t-test was performed to compare the monoexponential and non-Gaussian diffusion fitting (R(2)). T staging was equal between FDG-PET/CT and FDG-PET/MRI in 12 of 15 patients. For NSCLC, mean ADC(mono) was 2.11 ± 1.24 × 10(-3) mm(2)/s, Dapp was 2.46 ± 1.29 × 10(-3) mm(2)/s and mean Kapp was 0.70 ± 0.21. The non-Gaussian diffusion analysis (R(2)=0.98) provided a significantly better mathematical fitting to the DWI signal decay than the monoexponetial analysis (R(2)=0.96) (p<0.001). SUV(max) and SUV(mean) of NSCLC was 13.5 ± 7.6 and 7.9 ± 4.3 for FDG-PET/MRI. ADC(mono) as well as Dapp exhibited a significant inverse correlation with the SUV(max) (ADC(mono): R=-0.67; p<0.01; Dapp: R=-0.69; p<0.01) as well as with SUV(mean) assessed by FDG-PET/MRI (ADC(mono): R=-0.66; p<0.01; Dapp: R=-0.69; p<0.01). Furthermore, Kapp exhibited a significant correlation with SUV(max) (R=0.72; p<0.05) and SUV(mean) as assessed by FDG-PET/MRI (R=0.71; p<0.005). Simultaneous PET and non-Gaussian diffusion acquisitions are feasible. Non-Gaussian diffusion parameters show a good correlation with SUV and might provide additional information beyond monoexponential ADC, especially as non-Gaussian diffusion exhibits better mathematical fitting to the decay of the diffusion signal than monoexponential DWI. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Diffuse myelitis after treatment of cerebral aspergillosis in an immune competent patient.
Mollahoseini, Reza; Nikoobakht, Mahdi
2011-01-01
Presentation of an unusual case of cerebral aspergillosis in an immune competent patient who was treated successfully but symptoms and signs of a demyelinating process following initial recovery has been occurred. A 29-year-old male with focal seizure. Brain MRI revealed small multiple hemispheric and dural lesions. An open biopsy was conducted. Histological evaluation revealed hyphe-like structure in the necrotic area, within vessel walls, and lumina, suggestive aspergillus fumigatus . Furthermore, brancheal hyphae in potassium hydrxide 15% and colonies on sabourud dextrose agar were observed. Based of the above findings the patient underwent anti fungal therapy. The patient recovered and continued a normal life however a follow up MRI was performed after 3 months from recovery. No significant abnormality was observed from the MRI procedure. One month later the patient developed signs and symptoms of spinal cord involvement which seemed to be the result of myelitis. A brain MR showed no abnormalities .Therefore it seemed reasonable to administer corticosteroid as a treatment for suspected active demyelinating process. During the above treatment, signs and symptoms of myelopathy disappeared and a whole spine MRI showed remarkable improvement.
Henry, Roland G; Berman, Jeffrey I; Nagarajan, Srikantan S; Mukherjee, Pratik; Berger, Mitchel S
2004-02-01
The combination of mapping functional cortical neurons by intraoperative cortical stimulation and axonal architecture by diffusion tensor MRI fiber tracking can be used to delineate the pathways between functional regions. In this study the authors investigated the feasibility of combining these techniques to yield connectivity associated with motor speech and naming. Diffusion tensor MRI fiber tracking provides maps of axonal bundles and was combined with intraoperative mapping of eloquent cortex for a patient undergoing brain tumor surgery. Tracks from eight stimulated sites in the inferior frontal cortex including mouth motor, speech arrest, and anomia were generated from the diffusion tensor MRI data. The regions connected by the fiber tracking were compared to foci from previous functional imaging reports on language tasks. Connections were found between speech arrest, mouth motor, and anomia sites and the SMA proper and cerebral peduncle. The speech arrest and a mouth motor site were also seen to connect to the putamen via the external capsule. This is the first demonstration of delineation of subcortical pathways using diffusion tensor MRI fiber tracking with intraoperative cortical stimulation. The combined techniques may provide improved preservation of eloquent regions during neurological surgery, and may provide access to direct connectivity information between functional regions of the brain.
Henry, Roland G.; Berman, Jeffrey I.; Nagarajan, Srikantan S.; Mukherjee, Pratik; Berger, Mitchel S.
2014-01-01
The combination of mapping functional cortical neurons by intraoperative cortical stimulation and axonal architecture by diffusion tensor MRI fiber tracking can be used to delineate the pathways between functional regions. In this study the authors investigated the feasibility of combining these techniques to yield connectivity associated with motor speech and naming. Diffusion tensor MRI fiber tracking provides maps of axonal bundles and was combined with intraoperative mapping of eloquent cortex for a patient undergoing brain tumor surgery. Tracks from eight stimulated sites in the inferior frontal cortex including mouth motor, speech arrest, and anomia were generated from the diffusion tensor MRI data. The regions connected by the fiber tracking were compared to foci from previous functional imaging reports on language tasks. Connections were found between speech arrest, mouth motor, and anomia sites and the SMA proper and cerebral peduncle. The speech arrest and a mouth motor site were also seen to connect to the putamen via the external capsule. This is the first demonstration of delineation of subcortical pathways using diffusion tensor MRI fiber tracking with intraoperative cortical stimulation. The combined techniques may provide improved preservation of eloquent regions during neurological surgery, and may provide access to direct connectivity information between functional regions of the brain. PMID:14980564
Chen, Tai-Yuan; Wu, Te-Chang; Tsui, Yu-Kun; Chen, Hou-Hsun; Lin, Chien-Jen; Lee, Huey-Jen; Wu, Tai-Ching
2015-01-01
Though diffusion-weighted (DW) magnetic resonance imaging (MRI) is useful for diagnosing many pathologies, its use in infectious spondylodiscitis is unclear. We aimed to evaluate the use of DW MRI and apparent diffusion coefficient (ADC) mapping for the diagnosis of infectious spondylodiscitis. In this retrospective study, 17 patients with confirmed infectious spondylodiscitis were matched by age and level of infected disc with 17 patients with degenerative disc disease (DDD) and 17 healthy controls. All patients received conventional MRI and diffusion-weighted imaging (DWI) in the same imaging session. ADC values of the 3 groups of patients were compared. The mean age of each group was 67.4 ± 11.6 years. The mean ADCs of the normal control, DDD, and infectious spondylodiscitis groups were 1.76 ± 0.19 × 10(-3) , 1.12 ± 0.22 × 10(-3) , and 1.27 ± 0.38 × 10(-3) mm2 /second, respectively. The ADCs of the DDD and infectious spondylodiscitis groups were both significantly lower than that of the normal control group (both, P < 0.001). These data suggest that DWI/ADC MRI may be useful in the early diagnosis of infectious spondylodiscitis. © 2014 The Authors. Journal of Neuroimaging published by Wiley Periodicals, Inc. on behalf of American Society of Neuroimaging.
NASA Astrophysics Data System (ADS)
Lützkendorf, Ralf; Hertel, Frank; Heidemann, Robin; Thiel, Andreas; Luchtmann, Michael; Plaumann, Markus; Stadler, Jörg; Baecke, Sebastian; Bernarding, Johannes
2013-03-01
Diffusion tensor imaging (DTI) allows characterizing and exploiting diffusion anisotropy effects, thereby providing important details about tissue microstructure. A major application in neuroimaging is the so-called fiber tracking where neuronal connections between brain regions are determined non-invasively by DTI. Combining these neural pathways within the human brain with the localization of activated brain areas provided by functional MRI offers important information about functional connectivity of brain regions. However, DTI suffers from severe signal reduction due to the diffusion-weighting. Ultra-high field (UHF) magnetic resonance imaging (MRI) should therefore be advantageous to increase the intrinsic signal-to-noise ratio (SNR). This in turn enables to acquire high quality data with increased resolution, which is beneficial for tracking more complex fiber structures. However, UHF MRI imposes some difficulties mainly due to the larger B1 inhomogeneity compared to 3T MRI. We therefore optimized the parameters to perform DTI at a 7 Tesla whole body MR scanner equipped with a high performance gradient system and a 32-channel head receive coil. A Stesjkal Tanner spin-echo EPI sequence was used, to acquire 110 slices with an isotropic voxel-size of 1.2 mm covering the whole brain. 60 diffusion directions were scanned which allows calculating the principal direction components of the diffusion vector in each voxel. The results prove that DTI can be performed with high quality at UHF and that it is possible to explore the SNT benefit of the higher field strength. Combining UHF fMRI data with UHF DTI results will therefore be a major step towards better neuroimaging methods.
Statistical evaluation of manual segmentation of a diffuse low-grade glioma MRI dataset.
Ben Abdallah, Meriem; Blonski, Marie; Wantz-Mezieres, Sophie; Gaudeau, Yann; Taillandier, Luc; Moureaux, Jean-Marie
2016-08-01
Software-based manual segmentation is critical to the supervision of diffuse low-grade glioma patients and to the optimal treatment's choice. However, manual segmentation being time-consuming, it is difficult to include it in the clinical routine. An alternative to circumvent the time cost of manual segmentation could be to share the task among different practitioners, providing it can be reproduced. The goal of our work is to assess diffuse low-grade gliomas' manual segmentation's reproducibility on MRI scans, with regard to practitioners, their experience and field of expertise. A panel of 13 experts manually segmented 12 diffuse low-grade glioma clinical MRI datasets using the OSIRIX software. A statistical analysis gave promising results, as the practitioner factor, the medical specialty and the years of experience seem to have no significant impact on the average values of the tumor volume variable.
Change-point analysis data of neonatal diffusion tensor MRI in preterm and term-born infants.
Wu, Dan; Chang, Linda; Akazawa, Kentaro; Oishi, Kumiko; Skranes, Jon; Ernst, Thomas; Oishi, Kenichi
2017-06-01
The data presented in this article are related to the research article entitled "Mapping the Critical Gestational Age at Birth that Alters Brain Development in Preterm-born Infants using Multi-Modal MRI" (Wu et al., 2017) [1]. Brain immaturity at birth poses critical neurological risks in the preterm-born infants. We used a novel change-point model to analyze the critical gestational age at birth (GAB) that could affect postnatal development, based on diffusion tensor MRI (DTI) acquired from 43 preterm and 43 term-born infants in 126 brain regions. In the corresponding research article, we presented change-point analysis of fractional anisotropy (FA) and mean diffusivities (MD) measurements in these infants. In this article, we offered the relative changes of axonal and radial diffusivities (AD and RD) in relation to the change of FA and FA-based change-points, and we also provided the AD- and RD-based change-point results.
Ream, Justin M; Dillman, Jonathan R; Adler, Jeremy; Khalatbari, Shokoufeh; McHugh, Jonathan B; Strouse, Peter J; Dhanani, Muhammad; Shpeen, Benjamin; Al-Hawary, Mahmoud M
2013-09-01
Restricted diffusion on diffusion-weighted imaging (DWI) sequences during magnetic resonance enterography (MRE) has been shown in segments of bowel affected by Crohn disease. However, the exact meaning of this finding, particularly within the pediatric Crohn disease population, is poorly understood. The purpose of this study was to determine the significance of bowel wall restricted diffusion in children with small bowel Crohn disease by correlating apparent diffusion coefficient (ADC) values with other MRI markers of disease activity. A retrospective review of pediatric patients (≤ 18 years of age) with Crohn disease terminal ileitis who underwent MRE with DWI at our institution between May 1, 2009 and May 31, 2011 was undertaken. All of the children had either biopsy-proven Crohn disease terminal ileitis or clinically diagnosed Crohn disease, including terminal ileal involvement by imaging. The mean minimum ADC value within the wall of the terminal ileum was determined for each examination. ADC values were tested for correlation/association with other MRI findings to determine whether a relationship exists between bowel wall restricted diffusion and disease activity. Forty-six MRE examinations with DWI in children with terminal ileitis were identified (23 girls and 23 boys; mean age, 14.3 years). There was significant negative correlation or association between bowel wall minimum ADC value and established MRI markers of disease activity, including degree of bowel wall thickening (R = (-)0.43; P = 0.003), striated pattern of arterial enhancement (P = 0.01), degree of arterial enhancement (P = 0.01), degree of delayed enhancement (P = 0.045), amount of mesenteric inflammatory changes (P < 0.0001) and presence of a stricture (P = 0.02). ADC values were not significantly associated with bowel wall T2-weighted signal intensity, length of disease involvement or mesenteric fibrofatty proliferation. Increasing bowel wall restricted diffusion (lower ADC values) is associated with multiple MRI findings that are traditionally associated with active inflammation in pediatric small bowel Crohn disease.
A Hough Transform Global Probabilistic Approach to Multiple-Subject Diffusion MRI Tractography
2010-04-01
distribution unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT A global probabilistic fiber tracking approach based on the voting process provided by...umn.edu 2 ABSTRACT A global probabilistic fiber tracking approach based on the voting process provided by the Hough transform is introduced in...criteria for aligning curves and particularly tracts. In this work, we present a global probabilistic approach inspired by the voting procedure provided
Skeletal muscle metastases on magnetic resonance imaging: analysis of 31 cases.
Li, Qi; Wang, Lei; Pan, Shinong; Shu, Hong; Ma, Ying; Lu, Zaiming; Fu, Xihu; Jiang, Bo; Guo, Qiyong
2016-01-01
To investigate the magnetic resonance imaging (MRI) features of skeletal muscle metastases (SMM). The records of 31 patients with proven SMM were retrospectively reviewed. Clinical history, type of primary malignancy, location of metastases, and MRI features of SMM were evaluated. Based on MRI findings, SMM were divided into three MRI types. The correlation between MRI types with ages and pathology category, between MRI types of SMM and ages, as well as MRI types of SMM and pathology category were analysed with Spearman's rho. The most common primary tumour was genital tumour (25.8%) and bronchial carcinoma (19.4%), and the most common cell type was adenocarcinoma (58.1%). SMM were located in the iliopsoas muscle (26.3%), paravertebral muscles (21.1%), and upper extremity muscles (18.4%). MRI features: (1) Type-I localised lesions (12.90%), round-like mass limited to local regions with heterogeneous iso-signal intensity in T1WI and heterogeneous hyper-intensity in T2WI; (2) Type-II diffuse lesions without bone destruction (35.48%), abnormal diffuse swelling of the muscle with irregular boundaries and slightly hypo- to iso-intensity in T1WI and hyper-intensity in T2WI; and (3) Type-III diffuse lesions with bone destruction (51.61%), distinct irregular lump with iso-intensity in T1WI and heterogeneous hyper-intensity in T2WI with adjacent bone invasion. There was positive correlation between MRI types and ages (r = 0.431, p < 0.05). There were no significant differences of MRI types with pathology category (p > 0.05). SMM features on MRI can be broadly used to classify lesions, which is beneficial for SMM diagnosis.
Skeletal muscle metastases on magnetic resonance imaging: analysis of 31 cases
Li, Qi; Wang, Lei; Shu, Hong; Ma, Ying; Lu, Zaiming; Fu, Xihu; Jiang, Bo; Guo, Qiyong
2016-01-01
Aim of the study To investigate the magnetic resonance imaging (MRI) features of skeletal muscle metastases (SMM). Material and methods The records of 31 patients with proven SMM were retrospectively reviewed. Clinical history, type of primary malignancy, location of metastases, and MRI features of SMM were evaluated. Based on MRI findings, SMM were divided into three MRI types. The correlation between MRI types with ages and pathology category, between MRI types of SMM and ages, as well as MRI types of SMM and pathology category were analysed with Spearman's rho. Results The most common primary tumour was genital tumour (25.8%) and bronchial carcinoma (19.4%), and the most common cell type was adenocarcinoma (58.1%). SMM were located in the iliopsoas muscle (26.3%), paravertebral muscles (21.1%), and upper extremity muscles (18.4%). MRI features: (1) Type-I localised lesions (12.90%), round-like mass limited to local regions with heterogeneous iso-signal intensity in T1WI and heterogeneous hyper-intensity in T2WI; (2) Type-II diffuse lesions without bone destruction (35.48%), abnormal diffuse swelling of the muscle with irregular boundaries and slightly hypo- to iso-intensity in T1WI and hyper-intensity in T2WI; and (3) Type-III diffuse lesions with bone destruction (51.61%), distinct irregular lump with iso-intensity in T1WI and heterogeneous hyper-intensity in T2WI with adjacent bone invasion. There was positive correlation between MRI types and ages (r = 0.431, p < 0.05). There were no significant differences of MRI types with pathology category (p > 0.05). Conclusions SMM features on MRI can be broadly used to classify lesions, which is beneficial for SMM diagnosis. PMID:27647989
Gorgolewski, Krzysztof J; Auer, Tibor; Calhoun, Vince D; Craddock, R Cameron; Das, Samir; Duff, Eugene P; Flandin, Guillaume; Ghosh, Satrajit S; Glatard, Tristan; Halchenko, Yaroslav O; Handwerker, Daniel A; Hanke, Michael; Keator, David; Li, Xiangrui; Michael, Zachary; Maumet, Camille; Nichols, B Nolan; Nichols, Thomas E; Pellman, John; Poline, Jean-Baptiste; Rokem, Ariel; Schaefer, Gunnar; Sochat, Vanessa; Triplett, William; Turner, Jessica A; Varoquaux, Gaël; Poldrack, Russell A
2016-06-21
The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations.
Gorgolewski, Krzysztof J.; Auer, Tibor; Calhoun, Vince D.; Craddock, R. Cameron; Das, Samir; Duff, Eugene P.; Flandin, Guillaume; Ghosh, Satrajit S.; Glatard, Tristan; Halchenko, Yaroslav O.; Handwerker, Daniel A.; Hanke, Michael; Keator, David; Li, Xiangrui; Michael, Zachary; Maumet, Camille; Nichols, B. Nolan; Nichols, Thomas E.; Pellman, John; Poline, Jean-Baptiste; Rokem, Ariel; Schaefer, Gunnar; Sochat, Vanessa; Triplett, William; Turner, Jessica A.; Varoquaux, Gaël; Poldrack, Russell A.
2016-01-01
The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations. PMID:27326542
High-fidelity meshes from tissue samples for diffusion MRI simulations.
Panagiotaki, Eleftheria; Hall, Matt G; Zhang, Hui; Siow, Bernard; Lythgoe, Mark F; Alexander, Daniel C
2010-01-01
This paper presents a method for constructing detailed geometric models of tissue microstructure for synthesizing realistic diffusion MRI data. We construct three-dimensional mesh models from confocal microscopy image stacks using the marching cubes algorithm. Random-walk simulations within the resulting meshes provide synthetic diffusion MRI measurements. Experiments optimise simulation parameters and complexity of the meshes to achieve accuracy and reproducibility while minimizing computation time. Finally we assess the quality of the synthesized data from the mesh models by comparison with scanner data as well as synthetic data from simple geometric models and simplified meshes that vary only in two dimensions. The results support the extra complexity of the three-dimensional mesh compared to simpler models although sensitivity to the mesh resolution is quite robust.
Orczyk, C; Rusinek, H; Rosenkrantz, A B; Mikheev, A; Deng, F-M; Melamed, J; Taneja, S S
2013-12-01
To assess a novel method of three-dimensional (3D) co-registration of prostate cancer digital histology and in-vivo multiparametric magnetic resonance imaging (mpMRI) image sets for clinical usefulness. A software platform was developed to achieve 3D co-registration. This software was prospectively applied to three patients who underwent radical prostatectomy. Data comprised in-vivo mpMRI [T2-weighted, dynamic contrast-enhanced weighted images (DCE); apparent diffusion coefficient (ADC)], ex-vivo T2-weighted imaging, 3D-rebuilt pathological specimen, and digital histology. Internal landmarks from zonal anatomy served as reference points for assessing co-registration accuracy and precision. Applying a method of deformable transformation based on 22 internal landmarks, a 1.6 mm accuracy was reached to align T2-weighted images and the 3D-rebuilt pathological specimen, an improvement over rigid transformation of 32% (p = 0.003). The 22 zonal anatomy landmarks were more accurately mapped using deformable transformation than rigid transformation (p = 0.0008). An automatic method based on mutual information, enabled automation of the process and to include perfusion and diffusion MRI images. Evaluation of co-registration accuracy using the volume overlap index (Dice index) met clinically relevant requirements, ranging from 0.81-0.96 for sequences tested. Ex-vivo images of the specimen did not significantly improve co-registration accuracy. This preliminary analysis suggests that deformable transformation based on zonal anatomy landmarks is accurate in the co-registration of mpMRI and histology. Including diffusion and perfusion sequences in the same 3D space as histology is essential further clinical information. The ability to localize cancer in 3D space may improve targeting for image-guided biopsy, focal therapy, and disease quantification in surveillance protocols. Copyright © 2013 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
Treit, Sarah; Chen, Zhang; Zhou, Dongming; Baugh, Lauren; Rasmussen, Carmen; Andrew, Gail; Pei, Jacqueline; Beaulieu, Christian
2017-01-01
Quantitative magnetic resonance imaging (MRI) has revealed abnormalities in brain volumes, cortical thickness and white matter microstructure in fetal alcohol spectrum disorders (FASD); however, no study has reported all three measures within the same cohort to assess the relative magnitude of deficits, and few studies have examined sex differences. Participants with FASD (n = 70; 30 females; 5-32 years) and healthy controls (n = 74; 35 females; 5-32 years) underwent cognitive testing and MRI to assess cortical thickness, regional brain volumes and fractional anisotropy (FA)/mean diffusivity (MD) of white matter tracts. A significant effect of group, age-by-group, or sex-by-group was found for 9/9 volumes, 7/39 cortical thickness regions, 3/9 white matter tracts, and 9/10 cognitive tests, indicating group differences that in some cases differ by age or sex. Volume reductions for several structures were larger in males than females, despite similar deficits of cognition in both sexes. Correlations between brain structure and cognitive scores were found in females of both groups, but were notably absent in males. Correlations within a given MRI modality (e.g. total brain volume and caudate volume) were prevalent in both the control and FASD groups, and were more numerous than correlations between measurement types (e.g. volumes and diffusion tensor imaging) in either cohort. This multi-modal MRI study finds widespread differences of brain structure in participants with prenatal alcohol exposure, and to a greater extent in males than females which may suggest attenuation of the expected process of sexual dimorphism of brain structure during typical development.
Bickelhaupt, Sebastian; Paech, Daniel; Kickingereder, Philipp; Steudle, Franziska; Lederer, Wolfgang; Daniel, Heidi; Götz, Michael; Gählert, Nils; Tichy, Diana; Wiesenfarth, Manuel; Laun, Frederik B; Maier-Hein, Klaus H; Schlemmer, Heinz-Peter; Bonekamp, David
2017-08-01
To assess radiomics as a tool to determine how well lesions found suspicious on breast cancer screening X-ray mammography can be categorized into malignant and benign with unenhanced magnetic resonance (MR) mammography with diffusion-weighted imaging and T 2 -weighted sequences. From an asymptomatic screening cohort, 50 women with mammographically suspicious findings were examined with contrast-enhanced breast MRI (ceMRI) at 1.5T. Out of this protocol an unenhanced, abbreviated diffusion-weighted imaging protocol (ueMRI) including T 2 -weighted, (T 2 w), diffusion-weighted imaging (DWI), and DWI with background suppression (DWIBS) sequences and corresponding apparent diffusion coefficient (ADC) maps were extracted. From ueMRI-derived radiomic features, three Lasso-supervised machine-learning classifiers were constructed and compared with the clinical performance of a highly experienced radiologist: 1) univariate mean ADC model, 2) unconstrained radiomic model, 3) constrained radiomic model with mandatory inclusion of mean ADC. The unconstrained and constrained radiomic classifiers consisted of 11 parameters each and achieved differentiation of malignant from benign lesions with a .632 + bootstrap receiver operating characteristics (ROC) area under the curve (AUC) of 84.2%/85.1%, compared to 77.4% for mean ADC and 95.9%/95.9% for the experienced radiologist using ceMRI/ueMRI. In this pilot study we identified two ueMRI radiomics classifiers that performed well in the differentiation of malignant from benign lesions and achieved higher performance than the mean ADC parameter alone. Classification was lower than the almost perfect performance of a highly experienced breast radiologist. The potential of radiomics to provide a training-independent diagnostic decision tool is indicated. A performance reaching the human expert would be highly desirable and based on our results is considered possible when the concept is extended in larger cohorts with further development and validation of the technique. 1 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:604-616. © 2017 International Society for Magnetic Resonance in Medicine.
Gao, Yu; Han, Fei; Zhou, Ziwu; Cao, Minsong; Kaprealian, Tania; Kamrava, Mitchell; Wang, Chenyang; Neylon, John; Low, Daniel A; Yang, Yingli; Hu, Peng
2017-10-01
Monitoring tumor response during the course of treatment and adaptively modifying treatment plan based on tumor biological feedback may represent a new paradigm for radiotherapy. Diffusion MRI has shown great promises in assessing and predicting tumor response to radiotherapy. However, the conventional diffusion-weighted single-shot echo-planar-imaging (DW-ssEPI) technique suffers from limited resolution, severe distortion, and possibly inaccurate ADC at low field strength. The purpose of this work was to develop a reliable, accurate and distortion-free diffusion MRI technique that is practicable for longitudinal tumor response evaluation and adaptive radiotherapy on a 0.35 T MRI-guided radiotherapy system. A diffusion-prepared turbo spin echo readout (DP-TSE) sequence was developed and compared with the conventional diffusion-weighted single-shot echo-planar-imaging sequence on a 0.35 T MRI-guided radiotherapy system (ViewRay). A spatial integrity phantom was used to quantitate and compare the geometric accuracy of the two diffusion sequences for three orthogonal orientations. The apparent diffusion coefficient (ADC) accuracy was evaluated on a diffusion phantom under both 0 °C and room temperature to cover a diffusivity range between 0.40 × 10 -3 and 2.10 × 10 -3 mm 2 /s. Ten room temperature measurements repeated on five different days were conducted to assess the ADC reproducibility of DP-TSE. Two glioblastoma (GBM) and six sarcoma patients were included to examine the in vivo feasibility. The target registration error (TRE) was calculated to quantitate the geometric accuracy where structural CT or MR images were co-registered to the diffusion images as references. ADC maps from DP-TSE and DW-ssEPI were calculated and compared. A tube phantom was placed next to patients not treated on ViewRay, and ADCs of this reference tube were also compared. The proposed DP-TSE passed the spatial integrity test (< 1 mm within 100 mm radius and < 2 mm within 175 mm radius) under the three orthogonal orientations. The detected errors were 0.474 ± 0.355 mm, 0.475 ± 0.287 mm, and 0.546 ± 0.336 mm in the axial, coronal, and sagittal plane. DW-ssEPI, however, failed the tests due to severe distortion and low signal intensity. Noise correction must be performed for the DW-ssEPI to avoid ADC quantitation errors, whereas it is optional for DP-TSE. At 0 °C, the two sequences provided accurate quantitation with < 3% variation with the reference. In the room temperature study, discrepancies between ADCs from DP-TSE and the reference were within 4%, but could be as high as 8% for DW-ssEPI after the noise correction. Excellent ADC reproducibility with a coefficient of variation < 5% was observed among the 10 measurements of DP-TSE, indicating desirable robustness for ADC-based tumor response assessment. In vivo TRE in DP-TSE was less than 1.6 mm overall, whereas it could be greater than 12 mm in DW-ssEPI. For GBM patients, the CSF and brain tissue ADCs from DP-TSE were within the ranges found in literature. ADC differences between the two techniques were within 8% among the six sarcoma patients. For the reference tube that had a relatively low diffusivity, the two diffusion sequences provided matched measurements. A diffusion technique with excellent geometric fidelity, accurate, and reproducible ADC measurement was demonstrated for longitudinal tumor response assessment using a low-field MRI-guided radiotherapy system. © 2017 American Association of Physicists in Medicine.
NASA Astrophysics Data System (ADS)
Marrale, Maurizio; Collura, Giorgio; Gallo, Salvatore; Nici, Stefania; Tranchina, Luigi; Abbate, Boris Federico; Marineo, Sandra; Caracappa, Santo; d'Errico, Francesco
2017-04-01
This work focused on the analysis of the temporal diffusion of ferric ions through PVA-GTA gel dosimeters. PVA-GTA gel samples, partly exposed with 6 MV X-rays in order to create an initial steep gradient, were mapped using magnetic resonance imaging on a 7T MRI scanner for small animals. Multiple images of the gels were acquired over several hours after irradiation and were analyzed to quantitatively extract the signal profile. The spatial resolution achieved is 200 μm and this makes this technique particularly suitable for the analysis of steep gradients of ferric ion concentration. The results obtained with PVA-GTA gels were compared with those achieved with agarose gels, which is a standard dosimetric gel formulation. The analysis showed that the diffusion process is much slower (more than five times) for PVA-GTA gels than for agarose ones. Furthermore, it is noteworthy that the diffusion coefficient value obtained through MRI analysis is significantly consistent with that obtained in separate study Marini et al. (Submitted for publication) using a totally independent method such as spectrophotometry. This is a valuable result highlighting that the good dosimetric features of this gel matrix not only can be reproduced but also can be measured through independent experimental techniques based on different physical principles.
Rotationally invariant clustering of diffusion MRI data using spherical harmonics
NASA Astrophysics Data System (ADS)
Liptrot, Matthew; Lauze, François
2016-03-01
We present a simple approach to the voxelwise classification of brain tissue acquired with diffusion weighted MRI (DWI). The approach leverages the power of spherical harmonics to summarise the diffusion information, sampled at many points over a sphere, using only a handful of coefficients. We use simple features that are invariant to the rotation of the highly orientational diffusion data. This provides a way to directly classify voxels whose diffusion characteristics are similar yet whose primary diffusion orientations differ. Subsequent application of machine-learning to the spherical harmonic coefficients therefore may permit classification of DWI voxels according to their inferred underlying fibre properties, whilst ignoring the specifics of orientation. After smoothing apparent diffusion coefficients volumes, we apply a spherical harmonic transform, which models the multi-directional diffusion data as a collection of spherical basis functions. We use the derived coefficients as voxelwise feature vectors for classification. Using a simple Gaussian mixture model, we examined the classification performance for a range of sub-classes (3-20). The results were compared against existing alternatives for tissue classification e.g. fractional anisotropy (FA) or the standard model used by Camino.1 The approach was implemented on both two publicly-available datasets: an ex-vivo pig brain and in-vivo human brain from the Human Connectome Project (HCP). We have demonstrated how a robust classification of DWI data can be performed without the need for a model reconstruction step. This avoids the potential confounds and uncertainty that such models may impose, and has the benefit of being computable directly from the DWI volumes. As such, the method could prove useful in subsequent pre-processing stages, such as model fitting, where it could inform about individual voxel complexities and improve model parameter choice.
Sreedharan, Ruma Madhu; Menon, Amitha C; James, Jija S; Kesavadas, Chandrasekharan; Thomas, Sanjeev V
2015-03-01
Language lateralization is unique to humans. Functional MRI (fMRI) and diffusion tensor imaging (DTI) enable the study of language areas and white matter fibers involved in language, respectively. The objective of this study was to correlate arcuate fasciculus (AF) laterality by diffusion tensor imaging with that by fMRI in preadolescent children which has not yet been reported. Ten children between 8 and 12 years were subjected to fMRI and DTI imaging using Siemens 1.5 T MRI. Two language fMRI paradigms--visual verb generation and word pair task--were used. Analysis was done using SPM8 software. In DTI, the fiber volume of the arcuate fasciculus (AFV) and fractional anisotropy (FA) was measured. The fMRI Laterality Index (fMRI-LI) and DTI Laterality Index (DTI-LI) were calculated and their correlation assessed using the Pearson Correlation Index. Of ten children, mean age 10.6 years, eight showed left lateralization while bilateral language lateralization was seen in two. AFV by DTI was more on the left side in seven of the eight children who had left lateralization by fMRI. DTI could not trace the AF in one child. Of the two with bilateral language lateralization on fMRI, one showed larger AFV on the right side while the other did not show any asymmetry. There was a significant correlation (p < 0.02) between fMRI-LI and DTI-LI. Group mean of AFV by DTI was higher on the left side (2659.89 ± 654.75 mm(3)) as compared to the right (1824.11 ± 582.81 mm(3)) (p < 0.01). Like fMRI, DTI also reveals language laterality in children with a high degree of correlation between the two imaging modalities.
The visual white matter: The application of diffusion MRI and fiber tractography to vision science
Rokem, Ariel; Takemura, Hiromasa; Bock, Andrew S.; Scherf, K. Suzanne; Behrmann, Marlene; Wandell, Brian A.; Fine, Ione; Bridge, Holly; Pestilli, Franco
2017-01-01
Visual neuroscience has traditionally focused much of its attention on understanding the response properties of single neurons or neuronal ensembles. The visual white matter and the long-range neuronal connections it supports are fundamental in establishing such neuronal response properties and visual function. This review article provides an introduction to measurements and methods to study the human visual white matter using diffusion MRI. These methods allow us to measure the microstructural and macrostructural properties of the white matter in living human individuals; they allow us to trace long-range connections between neurons in different parts of the visual system and to measure the biophysical properties of these connections. We also review a range of findings from recent studies on connections between different visual field maps, the effects of visual impairment on the white matter, and the properties underlying networks that process visual information supporting visual face recognition. Finally, we discuss a few promising directions for future studies. These include new methods for analysis of MRI data, open datasets that are becoming available to study brain connectivity and white matter properties, and open source software for the analysis of these data. PMID:28196374
Complete fourier direct magnetic resonance imaging (CFD-MRI) for diffusion MRI
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
Bi, Qiu; Xiao, Zhibo; Lv, Fajin; Liu, Yao; Zou, Chunxia; Shen, Yiqing
2018-02-05
The objective of this study was to find clinical parameters and qualitative and quantitative magnetic resonance imaging (MRI) features for differentiating uterine sarcoma from atypical leiomyoma (ALM) preoperatively and to calculate predictive values for uterine sarcoma. Data from 60 patients with uterine sarcoma and 88 patients with ALM confirmed by surgery and pathology were collected. Clinical parameters, qualitative MRI features, diffusion-weighted imaging with apparent diffusion coefficient values, and quantitative parameters of dynamic contrast-enhanced MRI of these two tumor types were compared. Predictive values for uterine sarcoma were calculated using multivariable logistic regression. Patient clinical manifestations, tumor locations, margins, T2-weighted imaging signals, mean apparent diffusion coefficient values, minimum apparent diffusion coefficient values, and time-signal intensity curves of solid tumor components were obvious significant parameters for distinguishing between uterine sarcoma and ALM (all P <.001). Abnormal vaginal bleeding, tumors located mainly in the uterine cavity, ill-defined tumor margins, and mean apparent diffusion coefficient values of <1.272 × 10 -3 mm 2 /s were significant preoperative predictors of uterine sarcoma. When the overall scores of these four predictors were greater than or equal to 7 points, the sensitivity, the specificity, the accuracy, and the positive and negative predictive values were 88.9%, 99.9%, 95.7%, 97.0%, and 95.1%, respectively. The use of clinical parameters and multiparametric MRI as predictive factors was beneficial for diagnosing uterine sarcoma preoperatively. These findings could be helpful for guiding treatment decisions. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Salman Shahid, Syed; Gaul, Robert T.; Kerskens, Christian; Flamini, Vittoria; Lally, Caitríona
2017-12-01
Diffusion magnetic resonance imaging (dMRI) can provide insights into the microstructure of intact arterial tissue. The current study employed high magnetic field MRI to obtain ultra-high resolution dMRI at an isotropic voxel resolution of 117 µm3 in less than 2 h of scan time. A parameter selective single shell (128 directions) diffusion-encoding scheme based on Stejskel-Tanner sequence with echo-planar imaging (EPI) readout was used. EPI segmentation was used to reduce the echo time (TE) and to minimise the susceptibility-induced artefacts. The study utilised the dMRI analysis with diffusion tensor imaging (DTI) framework to investigate structural heterogeneity in intact arterial tissue and to quantify variations in tissue composition when the tissue is cut open and flattened. For intact arterial samples, the region of interest base comparison showed significant differences in fractional anisotropy and mean diffusivity across the media layer (p < 0.05). For open cut flat samples, DTI based directionally invariant indices did not show significant differences across the media layer. For intact samples, fibre tractography based indices such as calculated helical angle and fibre dispersion showed near circumferential alignment and a high degree of fibre dispersion, respectively. This study demonstrates the feasibility of fast dMRI acquisition with ultra-high spatial and angular resolution at 7 T. Using the optimised sequence parameters, this study shows that DTI based markers are sensitive to local structural changes in intact arterial tissue samples and these markers may have clinical relevance in the diagnosis of atherosclerosis and aneurysm.
Park, Hyun Jeong; Kim, Seong Hyun; Jang, Kyung Mi; Choi, Seo-youn; Lee, Soon Jin; Choi, Dongil
2014-04-01
To assess the added value of diffusion-weighted imaging (DWI) to conventional magnetic resonance imaging (MRI) for differentiating benign from malignant bile duct strictures. Twenty-seven patients with a benign stricture and 42 patients with a malignant stricture who had undergone gadoxetic acid-enhanced MRI with DWI were enrolled. Qualitative (signal intensity, dynamic enhancement pattern) and quantitative (wall thickness and length) analyses were performed. Two observers independently reviewed a set of conventional MRI and a combined set of conventional MRI and DWI, and receiver operating characteristic (ROC) curve analysis was assessed. Benign strictures showed isointensity (18.5-70.4 %) and a similar enhancement pattern (22.2 %) to that of normal bile duct more frequently than malignant strictures (0-40.5 % and 0 %) on conventional MRI (P < 0.05). Malignant strictures (90.5-92.9 %) showed hypervascularity on arterial and portal venous phase images more frequently than benign strictures (37.0-70.4 %) (P < 0.01) On DWI, all malignant strictures showed hyperintensity compared with benign cases (70.4 %) (P < 0.001). Malignant strictures were significantly thicker and longer than benign strictures (P < 0.001). The diagnostic performance of both observers improved significantly after additional review of DWI. Adding DWI to conventional MRI is more helpful for differentiating benign from malignant bile duct strictures than conventional MRI alone. • Accurate diagnosis and exclusion of benign strictures of bile duct are important. • Diffusion-weighted MRI helps to distinguish benign from malignant bile duct strictures. • DWI plus conventional MRI provides superior diagnostic accuracy to conventional MRI alone.
Albayrak, Eda; Sonmezgoz, Fitnet; Ozmen, Zafer; Aktas, Fatma; Altunkas, Aysegul
2017-01-01
A 26-year-old female patient with Type 1 Gaucher’s disease (GD) was admitted to our clinic with complaints of stomachache and signs of anemia. The patient underwent ultrasonography (US), computerised tomography (CT), and magnetic resonance imaging (MRI) scan. Imaging studies revealed massive hepatosplenomegaly, choledocolithiasis, and six nodules in the spleen with a mean size of 14 mm. The nodules appeared hyperechoic, hypoechoic, and of mixed echogenicity on the US and hypodense on the CT. While the nodules were observed to be iso-hypointense in T1-weighted (T1WI) images, they appeared to be hyperintense in the T2-weighted (T2WI) images. There were no diffusion restrictions in these nodules that appeared on the diffusion-weighted magnetic resonance imaging (DWI). A nodule located at the lower pole was observed to be hypointense in the T2WI images. The nodule located at the lower pole, which appeared hypointense in T2WI series, had restricted diffusion upon DWI. In this study, we aimed to present the properties of splenic GD nodules using US, CT, and conventional MRI, together with DWI. This case report is the first to apply US, CT, and conventional MRI, together with DWI, to the splenic nodules associated with Gaucher’s disease. PMID:29386979
NASA Astrophysics Data System (ADS)
Skare, Stefan; Hedehus, Maj; Moseley, Michael E.; Li, Tie-Qiang
2000-12-01
Diffusion tensor mapping with MRI can noninvasively track neural connectivity and has great potential for neural scientific research and clinical applications. For each diffusion tensor imaging (DTI) data acquisition scheme, the diffusion tensor is related to the measured apparent diffusion coefficients (ADC) by a transformation matrix. With theoretical analysis we demonstrate that the noise performance of a DTI scheme is dependent on the condition number of the transformation matrix. To test the theoretical framework, we compared the noise performances of different DTI schemes using Monte-Carlo computer simulations and experimental DTI measurements. Both the simulation and the experimental results confirmed that the noise performances of different DTI schemes are significantly correlated with the condition number of the associated transformation matrices. We therefore applied numerical algorithms to optimize a DTI scheme by minimizing the condition number, hence improving the robustness to experimental noise. In the determination of anisotropic diffusion tensors with different orientations, MRI data acquisitions using a single optimum b value based on the mean diffusivity can produce ADC maps with regional differences in noise level. This will give rise to rotational variances of eigenvalues and anisotropy when diffusion tensor mapping is performed using a DTI scheme with a limited number of diffusion-weighting gradient directions. To reduce this type of artifact, a DTI scheme with not only a small condition number but also a large number of evenly distributed diffusion-weighting gradients in 3D is preferable.
Neurocognitive Effects of Radiotherapy
2014-10-01
patients have completed a 4-5 hour neurocognitive testing assessment at baseline by Dr. Carol Armstrong. In addition , all patients have completed a 1...hour standard MRI as well as additional testing including diffuse tensor imaging (DTI), perfusion and diffusion. The majority of patients have...completed baseline and at least two additional time-points in regards to both neurocognitive testing and MRI. Eight patients have completed
Evaluating Kurtosis-based Diffusion MRI Tissue Models for White Matter with Fiber Ball Imaging
Jensen, Jens H.; McKinnon, Emilie T.; Glenn, G. Russell; Helpern, Joseph A.
2018-01-01
In order to quantify well-defined microstructural properties of brain tissue from diffusion MRI (dMRI) data, tissue models are typically employed that relate biological features, such as cell morphology and cell membrane permeability, to the diffusion dynamics. A variety of such models have been proposed for white matter, and their validation is a topic of active interest. In this paper, three different tissue models are tested by comparing their predictions for a specific microstructural parameter to the value measured independently with a recently proposed dMRI method known as fiber ball imaging (FBI). The three tissue models are all constructed with the diffusion and kurtosis tensors, and they are hence compatible with diffusional kurtosis imaging (DKI). Nevertheless, the models differ significantly in their details and predictions. For voxels with fractional anisotropies (FA) exceeding 0.5, all three are reasonably consistent with FBI. However, for lower FA values, one of these, called the white matter tract integrity (WMTI) model, is found to be in much better accord with FBI than the other two, suggesting that the WMTI model has a broader range of applicability. PMID:28085211
Sone, Daichi; Sato, Noriko; Kimura, Yukio; Watanabe, Yutaka; Okazaki, Mitsutoshi; Matsuda, Hiroshi
2018-06-01
Although epilepsy in the elderly has attracted attention recently, there are few systematic studies of neuroimaging in such patients. In this study, we used structural MRI and diffusion tensor imaging (DTI) to investigate the morphological and microstructural features of the brain in late-onset temporal lobe epilepsy (TLE). We recruited patients with TLE and an age of onset > 50 years (late-TLE group) and age- and sex-matched healthy volunteers (control group). 3-Tesla MRI scans, including 3D T1-weighted images and 15-direction DTI, showed normal findings on visual assessment in both groups. We used Statistical Parametric Mapping 12 (SPM12) for gray and white matter structural normalization and comparison and used Tract-Based Spatial Statistics (TBSS) for fractional anisotropy and mean diffusivity comparisons of DTI. In both methods, p < 0.05 (family-wise error) was considered statistically significant. In total, 30 patients with late-onset TLE (mean ± SD age, 66.8 ± 8.4; mean ± SD age of onset, 63.0 ± 7.6 years) and 40 healthy controls (mean ± SD age, 66.6 ± 8.5 years) were enrolled. The late-onset TLE group showed significant gray matter volume increases in the bilateral amygdala and anterior hippocampus and significantly reduced mean diffusivity in the left temporofrontal lobe, internal capsule, and brainstem. No significant changes were evident in white matter volume or fractional anisotropy. Our findings may reflect some characteristics or mechanisms of cryptogenic TLE in the elderly, such as inflammatory processes.
Conventions and nomenclature for double diffusion encoding NMR and MRI.
Shemesh, Noam; Jespersen, Sune N; Alexander, Daniel C; Cohen, Yoram; Drobnjak, Ivana; Dyrby, Tim B; Finsterbusch, Jurgen; Koch, Martin A; Kuder, Tristan; Laun, Fredrik; Lawrenz, Marco; Lundell, Henrik; Mitra, Partha P; Nilsson, Markus; Özarslan, Evren; Topgaard, Daniel; Westin, Carl-Fredrik
2016-01-01
Stejskal and Tanner's ingenious pulsed field gradient design from 1965 has made diffusion NMR and MRI the mainstay of most studies seeking to resolve microstructural information in porous systems in general and biological systems in particular. Methods extending beyond Stejskal and Tanner's design, such as double diffusion encoding (DDE) NMR and MRI, may provide novel quantifiable metrics that are less easily inferred from conventional diffusion acquisitions. Despite the growing interest on the topic, the terminology for the pulse sequences, their parameters, and the metrics that can be derived from them remains inconsistent and disparate among groups active in DDE. Here, we present a consensus of those groups on terminology for DDE sequences and associated concepts. Furthermore, the regimes in which DDE metrics appear to provide microstructural information that cannot be achieved using more conventional counterparts (in a model-free fashion) are elucidated. We highlight in particular DDE's potential for determining microscopic diffusion anisotropy and microscopic fractional anisotropy, which offer metrics of microscopic features independent of orientation dispersion and thus provide information complementary to the standard, macroscopic, fractional anisotropy conventionally obtained by diffusion MR. Finally, we discuss future vistas and perspectives for DDE. © 2015 Wiley Periodicals, Inc.
Clarke, Sharon E; Mistry, Dipan; AlThubaiti, Talal; Khan, M Naeem; Morris, David; Bance, Manohar
2017-05-01
The purpose of this study was to evaluate the sensitivity, specificity, and positive and negative predictive values of the diffusion-weighted periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) technique in the detection of cholesteatoma at our institution with surgical confirmation in all cases. A retrospective review of 21 consecutive patients who underwent diffusion-weighted PROPELLER magnetic resonance imaging (MRI) on a 1.5T MRI scanner prior to primary or revision/second-look surgery for suspected cholesteatoma from 2009-2012 was performed. Diffusion-weighted PROPELLER had a sensitivity of 75%, specificity of 60%, positive predictive value of 86%, and negative predictive value of 43%. In the 15 patients for whom the presence or absence of cholesteatoma was correctly predicted, there were 2 cases where the reported locations of diffusion restriction did not correspond to the location of the cholesteatoma observed at surgery. On the basis of our retrospective study, we conclude that diffusion-weighted PROPELLER MRI is not sufficiently accurate to replace second look surgery at our institution. Copyright © 2016 Canadian Association of Radiologists. Published by Elsevier Inc. All rights reserved.
Beer, Anton L.; Plank, Tina; Meyer, Georg; Greenlee, Mark W.
2013-01-01
Functional magnetic resonance imaging (MRI) showed that the superior temporal and occipital cortex are involved in multisensory integration. Probabilistic fiber tracking based on diffusion-weighted MRI suggests that multisensory processing is supported by white matter connections between auditory cortex and the temporal and occipital lobe. Here, we present a combined functional MRI and probabilistic fiber tracking study that reveals multisensory processing mechanisms that remained undetected by either technique alone. Ten healthy participants passively observed visually presented lip or body movements, heard speech or body action sounds, or were exposed to a combination of both. Bimodal stimulation engaged a temporal-occipital brain network including the multisensory superior temporal sulcus (msSTS), the lateral superior temporal gyrus (lSTG), and the extrastriate body area (EBA). A region-of-interest (ROI) analysis showed multisensory interactions (e.g., subadditive responses to bimodal compared to unimodal stimuli) in the msSTS, the lSTG, and the EBA region. Moreover, sounds elicited responses in the medial occipital cortex. Probabilistic tracking revealed white matter tracts between the auditory cortex and the medial occipital cortex, the inferior occipital cortex (IOC), and the superior temporal sulcus (STS). However, STS terminations of auditory cortex tracts showed limited overlap with the msSTS region. Instead, msSTS was connected to primary sensory regions via intermediate nodes in the temporal and occipital cortex. Similarly, the lSTG and EBA regions showed limited direct white matter connections but instead were connected via intermediate nodes. Our results suggest that multisensory processing in the STS is mediated by separate brain areas that form a distinct network in the lateral temporal and inferior occipital cortex. PMID:23407860
Multiparametric Magnetic Resonance Imaging for Active Surveillance of Prostate Cancer.
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.
Assili, S.; Fathi Kazerooni, A.; Aghaghazvini, L.; Saligheh Rad, H.R.; Pirayesh Islamian, J.
2015-01-01
Background Salivary gland tumors form nearly 3% of head and neck tumors. Due to their large histological variety and vicinity to facial nerves, pre-operative diagnosis and differentiation of benign and malignant parotid tumors are a major challenge for radiologists. Objective The majority of these tumors are benign; however, sometimes they tend to transform into a malignant form. Functional MRI techniques, namely dynamic contrast enhanced (DCE-) MRI and diffusion-weighted MRI (DWI) can indicate the characteristics of tumor tissue. Methods DCE-MRI analysis is based on the parameters of time intensity curve (TIC) before and after contrast agent injection. This method has the potential to identify the angiogenesis of tumors. DWI analysis is performed according to diffusion of water molecules in a tissue for determination of the cellularity of tumors. Conclusion According to the literature, these methods cannot be used individually to differentiate benign from malignant salivary gland tumors. An effective approach could be to combine the aforementioned methods to increase the accuracy of discrimination between different tumor types. The main objective of this study is to explore the application of DCE-MRI and DWI for assessment of salivary gland tumor types. PMID:26688794
Islim, Filiz; Salik, Aysun Erbahceci; Bayramoglu, Sibel; Guven, Koray; Alis, Halil; Turhan, Ahmet Nuray
2014-06-01
The purpose of this study was to evaluate the contribution of diffusion-weighted magnetic resonance imaging (DW-MRI) to the detection of infection in acute pancreatitis-related collections. A total of 21 DW-MRI, and computed tomography (CT) were performed on 20 patients diagnosed as acute pancreatitis with acute peri-pancreatic fluid or necrotic collections. Collections were classified as infected or sterile according to the culture and follow-up results. Collections with gas bubbles on CT images were considered to be infected. Collections with peripheral bright signals on DW-MRI images were considered to be positive, whereas those without signals were considered to be negative. Apparent diffusion coefficient (ADC) values of the peripheral and central parts of the collections were measured. Student's t test was used to compare the means of ADC values of independent groups. Apart from one false positive result, the presence of infection was detected by DW-MRI with 95.2% accuracy. The sensitivity and accuracy of DW-MRI were higher than CT for the detection of infection. The ADC values in the central parts of the collections were significantly different between the infected and sterile groups. DW-MRI can be used as a non-invasive technique for the detection of infection in acute pancreatitis-associated collections.
Brunelle, S.; Bertucci, F.; Chetaille, B.; Lelong, B.; Piana, G.; Sarran, A.
2013-01-01
Introduction Aggressive angiomyxoma (AA) is a rare benign soft tissue tumour usually affecting the pelvis and perineum of young women. Magnetic resonance imaging (MRI) is crucial in the management of AA patients for its diagnostic contribution and for the preoperative assessment of the actual tumour extension. Given the current development of less aggressive therapeutics associated with a higher risk of recurrence, close follow-up with MRI is fundamental after treatment. In this context, diffusion-weighted (DW) imaging has already shown high efficacy in the detection of early small relapses in prostate or rectal cancer. Case Report We report here a case of pelvic AA in a 51-year-old woman examined with dynamic contrast enhancement and DW-MRI, including apparent diffusion coefficient mapping and calculation. Conclusion To our knowledge, this is the first description of DW-MRI in AA reported in the literature. Here, knowledge about imaging features of AA will be reviewed and expanded. PMID:23904848
Brunelle, S; Bertucci, F; Chetaille, B; Lelong, B; Piana, G; Sarran, A
2013-05-01
Aggressive angiomyxoma (AA) is a rare benign soft tissue tumour usually affecting the pelvis and perineum of young women. Magnetic resonance imaging (MRI) is crucial in the management of AA patients for its diagnostic contribution and for the preoperative assessment of the actual tumour extension. Given the current development of less aggressive therapeutics associated with a higher risk of recurrence, close follow-up with MRI is fundamental after treatment. In this context, diffusion-weighted (DW) imaging has already shown high efficacy in the detection of early small relapses in prostate or rectal cancer. We report here a case of pelvic AA in a 51-year-old woman examined with dynamic contrast enhancement and DW-MRI, including apparent diffusion coefficient mapping and calculation. To our knowledge, this is the first description of DW-MRI in AA reported in the literature. Here, knowledge about imaging features of AA will be reviewed and expanded.
NASA Astrophysics Data System (ADS)
Jensen, Jens H.; Helpern, Joseph A.
2011-06-01
Hardware constraints typically require the use of extended gradient pulse durations for clinical applications of diffusion-weighted magnetic resonance imaging (DW-MRI), which can potentially influence the estimation of diffusion metrics. Prior studies have examined this effect for the apparent diffusion coefficient. This study employs a two-compartment exchange model in order to assess the gradient pulse duration sensitivity of the apparent diffusional kurtosis (ADK), a quantitative index of diffusional non-Gaussianity. An analytic expression is derived and numerically evaluated for parameter ranges relevant to DW-MRI of brain. It is found that the ADK differs from the true diffusional kurtosis by at most a few percent. This suggests that ADK estimates for brain may be robust with respect to changes in pulse gradient duration.
Technique of diffusion weighted imaging and its application in stroke
NASA Astrophysics Data System (ADS)
Li, Enzhong; Tian, Jie; Han, Ying; Wang, Huifang; Li, Wu; He, Huiguang
2003-05-01
To study the application of diffusion weighted imaging and image post processing in the diagnosis of stroke, especially in acute stroke, 205 patients were examined by 1.5 T or 1.0 T MRI scanner and the images such as T1, T2 and diffusion weighted images were obtained. Image post processing was done with "3D Med System" developed by our lab to analyze data and acquire the apparent diffusion coefficient (ADC) map. In acute and subacute stage of stroke, the signal in cerebral infarction areas changed to hyperintensity in T2- and diffusion-weighted images, normal or hypointensity in T1-weighted images. In hyperacute stage, however, the signal was hyperintense just in the diffusion weighted imaes; others were normal. In the chronic stage, the signal in T1- and diffusion-weighted imaging showed hypointensity and hyperintensity in T2 weighted imaging. Because ADC declined obviously in acute and subacute stage of stroke, the lesion area was hypointensity in ADC map. With the development of the disease, ADC gradually recovered and then changed to hyperintensity in ADC map in chronic stage. Using diffusion weighted imaging and ADC mapping can make a diagnosis of stroke, especially in the hyperacute stage of stroke, and can differentiate acute and chronic stroke.
Lodygensky, Gregory A; Kunz, Nicolas; Perroud, Elodie; Somm, Emmanuel; Mlynarik, Vladimir; Hüppi, Petra S; Gruetter, Rolf; Sizonenko, Stéphane V
2014-03-01
Lipopolysaccharide (LPS) injection in the corpus callosum (CC) of rat pups results in diffuse white matter injury similar to the main neuropathology of preterm infants. The aim of this study was to characterize the structural and metabolic markers of acute inflammatory injury by high-field magnetic resonance imaging (MRI) magnetic resonance spectroscopy (MRS) in vivo. Twenty-four hours after a 1-mg/kg injection of LPS in postnatal day 3 rat pups, diffusion tensor imaging and proton nuclear magnetic spectroscopy ((1)H NMR) were analyzed in conjunction to determine markers of cell death and inflammation using immunohistochemistry and gene expression. MRI and MRS in the CC revealed an increase in lactate and free lipids and a decrease of the apparent diffusion coefficient. Detailed evaluation of the CC showed a marked apoptotic response assessed by fractin expression. Interestingly, the degree of reduction in the apparent diffusion coefficient correlated strongly with the natural logarithm of fractin expression, in the same region of interest. LPS injection further resulted in increased activated microglia clustered in the cingulum, widespread astrogliosis, and increased expression of genes for interleukin (IL)-1, IL-6, and tumor necrosis factor. This model was able to reproduce the typical MRI hallmarks of acute diffuse white matter injury seen in preterm infants and allowed the evaluation of in vivo biomarkers of acute neuropathology after inflammatory challenge.
In Vivo High-Resolution 7 Tesla MRI Shows Early and Diffuse Cortical Alterations in CADASIL
De Guio, François; Reyes, Sonia; Vignaud, Alexandre; Duering, Marco; Ropele, Stefan; Duchesnay, Edouard; Chabriat, Hugues; Jouvent, Eric
2014-01-01
Background and Purpose Recent data suggest that early symptoms may be related to cortex alterations in CADASIL (Cerebral Autosomal-Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy), a monogenic model of cerebral small vessel disease (SVD). The aim of this study was to investigate cortical alterations using both high-resolution T2* acquisitions obtained with 7 Tesla MRI and structural T1 images with 3 Tesla MRI in CADASIL patients with no or only mild symptomatology (modified Rankin’s scale ≤1 and Mini Mental State Examination (MMSE) ≥24). Methods Complete reconstructions of the cortex using 7 Tesla T2* acquisitions with 0.7 mm isotropic resolution were obtained in 11 patients (52.1±13.2 years, 36% male) and 24 controls (54.8±11.0 years, 42% male). Seven Tesla T2* within the cortex and cortical thickness and morphology obtained from 3 Tesla images were compared between CADASIL and control subjects using general linear models. Results MMSE, brain volume, cortical thickness and global sulcal morphology did not differ between groups. By contrast, T2* measured by 7 Tesla MRI was significantly increased in frontal, parietal, occipital and cingulate cortices in patients after correction for multiple testing. These changes were not related to white matter lesions, lacunes or microhemorrhages in patients having no brain atrophy compared to controls. Conclusions Seven Tesla MRI, by contrast to state of the art post-processing of 3 Tesla acquisitions, shows diffuse T2* alterations within the cortical mantle in CADASIL whose origin remains to be determined. PMID:25165824
Langs, Georg; Sweet, Andrew; Lashkari, Danial; Tie, Yanmei; Rigolo, Laura; Golby, Alexandra J; Golland, Polina
2014-12-01
In this paper we construct an atlas that summarizes functional connectivity characteristics of a cognitive process from a population of individuals. The atlas encodes functional connectivity structure in a low-dimensional embedding space that is derived from a diffusion process on a graph that represents correlations of fMRI time courses. The functional atlas is decoupled from the anatomical space, and thus can represent functional networks with variable spatial distribution in a population. In practice the atlas is represented by a common prior distribution for the embedded fMRI signals of all subjects. We derive an algorithm for fitting this generative model to the observed data in a population. Our results in a language fMRI study demonstrate that the method identifies coherent and functionally equivalent regions across subjects. The method also successfully maps functional networks from a healthy population used as a training set to individuals whose language networks are affected by tumors. Copyright © 2014. Published by Elsevier Inc.
Avram, Alexandru V; Sarlls, Joelle E; Barnett, Alan S; Özarslan, Evren; Thomas, Cibu; Irfanoglu, M Okan; Hutchinson, Elizabeth; Pierpaoli, Carlo; Basser, Peter J
2016-02-15
Diffusion tensor imaging (DTI) is the most widely used method for characterizing noninvasively structural and architectural features of brain tissues. However, the assumption of a Gaussian spin displacement distribution intrinsic to DTI weakens its ability to describe intricate tissue microanatomy. Consequently, the biological interpretation of microstructural parameters, such as fractional anisotropy or mean diffusivity, is often equivocal. We evaluate the clinical feasibility of assessing brain tissue microstructure with mean apparent propagator (MAP) MRI, a powerful analytical framework that efficiently measures the probability density function (PDF) of spin displacements and quantifies useful metrics of this PDF indicative of diffusion in complex microstructure (e.g., restrictions, multiple compartments). Rotation invariant and scalar parameters computed from the MAP show consistent variation across neuroanatomical brain regions and increased ability to differentiate tissues with distinct structural and architectural features compared with DTI-derived parameters. The return-to-origin probability (RTOP) appears to reflect cellularity and restrictions better than MD, while the non-Gaussianity (NG) measures diffusion heterogeneity by comprehensively quantifying the deviation between the spin displacement PDF and its Gaussian approximation. Both RTOP and NG can be decomposed in the local anatomical frame for reference determined by the orientation of the diffusion tensor and reveal additional information complementary to DTI. The propagator anisotropy (PA) shows high tissue contrast even in deep brain nuclei and cortical gray matter and is more uniform in white matter than the FA, which drops significantly in regions containing crossing fibers. Orientational profiles of the propagator computed analytically from the MAP MRI series coefficients allow separation of different fiber populations in regions of crossing white matter pathways, which in turn improves our ability to perform whole-brain fiber tractography. Reconstructions from subsampled data sets suggest that MAP MRI parameters can be computed from a relatively small number of DWIs acquired with high b-value and good signal-to-noise ratio in clinically achievable scan durations of less than 10min. The neuroanatomical consistency across healthy subjects and reproducibility in test-retest experiments of MAP MRI microstructural parameters further substantiate the robustness and clinical feasibility of this technique. The MAP MRI metrics could potentially provide more sensitive clinical biomarkers with increased pathophysiological specificity compared to microstructural measures derived using conventional diffusion MRI techniques. Published by Elsevier Inc.
Diffusion Entropy: A Potential Neuroimaging Biomarker of Bipolar Disorder in the Temporal Pole.
Spuhler, Karl; Bartlett, Elizabeth; Ding, Jie; DeLorenzo, Christine; Parsey, Ramin; Huang, Chuan
2018-02-01
Despite much research, bipolar depression remains poorly understood, with no clinically useful biomarkers for its diagnosis. The paralimbic system has become a target for biomarker research, with paralimbic structural connectivity commonly reported to distinguish bipolar patients from controls in tractography-based diffusion MRI studies, despite inconsistent findings in voxel-based studies. The purpose of this analysis was to validate existing findings with traditional diffusion MRI metrics and investigate the utility of a novel diffusion MRI metric, entropy of diffusion, in the search for bipolar depression biomarkers. We performed group-level analysis on 9 un-medicated (6 medication-naïve; 3 medication-free for at least 33 days) bipolar patients in a major depressive episode and 9 matched healthy controls to compare: (1) average mean diffusivity (MD) and fractional anisotropy (FA) and; (2) MD and FA histogram entropy-a statistical measure of distribution homogeneity-in the amygdala, hippocampus, orbitofrontal cortex and temporal pole. We also conducted classification analyses with leave-one-out and separate testing dataset (N = 11) approaches. We did not observe statistically significant differences in average MD or FA between the groups in any region. However, in the temporal pole, we observed significantly lower MD entropy in bipolar patients; this finding suggests a regional difference in MD distributions in the absence of an average difference. This metric allowed us to accurately characterize bipolar patients from controls in leave-one-out (accuracy = 83%) and prediction (accuracy = 73%) analyses. This novel application of diffusion MRI yielded not only an interesting separation between bipolar patients and healthy controls, but also accurately classified bipolar patients from controls. © 2017 Wiley Periodicals, Inc.
Xu, Xiao Quan; Choi, Young Jun; Sung, Yu Sub; Yoon, Ra Gyoung; Jang, Seung Won; Park, Ji Eun; Heo, Young Jin; Baek, Jung Hwan; Lee, Jeong Hyun
2016-01-01
To investigate the correlation between perfusion- and diffusion-related parameters from intravoxel incoherent motion (IVIM) and those from dynamic contrast-enhanced MR imaging (DCE-MRI) and diffusion-weighted imaging in tumors and normal muscles of the head and neck. We retrospectively enrolled 20 consecutive patients with head and neck tumors with MR imaging performed using a 3T MR scanner. Tissue diffusivity (D), pseudo-diffusion coefficient (D(*)), and perfusion fraction (f) were derived from bi-exponential fitting of IVIM data obtained with 14 different b-values in three orthogonal directions. We investigated the correlation between D, f, and D(*) and model-free parameters from the DCE-MRI (wash-in, Tmax, Emax, initial AUC60, whole AUC) and the apparent diffusion coefficient (ADC) value in the tumor and normal masseter muscle using a whole volume-of-interest approach. Pearson's correlation test was used for statistical analysis. No correlation was found between f or D(*) and any of the parameters from the DCE-MRI in all patients or in patients with squamous cell carcinoma (p > 0.05). The ADC was significantly correlated with D values in the tumors (p < 0.001, r = 0.980) and muscles (p = 0.013, r = 0.542), despite its significantly higher value than D. The difference between ADC and D showed significant correlation with f values in the tumors (p = 0.017, r = 0.528) and muscles (p = 0.003, r = 0.630), but no correlation with D(*) (p > 0.05, respectively). Intravoxel incoherent motion shows no significant correlation with model-free perfusion parameters derived from the DCE-MRI but is feasible for the analysis of diffusivity in both tumors and normal muscles of the head and neck.
MRI-negative refractory partial epilepsy: role for diffusion tensor imaging in high field MRI.
Chen, Qin; Lui, Su; Li, Chun-Xiao; Jiang, Li-Jun; Ou-Yang, Luo; Tang, He-Han; Shang, Hui-Fang; Huang, Xiao-Qi; Gong, Qi-Yong; Zhou, Dong
2008-07-01
Our aim is to use the high field MR scanner (3T) to verify whether diffusion tensor imaging (DTI) could help in locating the epileptogenic zone in patients with MRI-negative refractory partial epilepsy. Fifteen patients with refractory partial epilepsy who had normal conventional MRI, and 40 healthy volunteers were recruited for the study. DTI was performed on a 3T MR scanner, individual maps of mean diffusivity (MD) and fractional anisotropy (FA) were calculated, and Voxel-Based Analysis (VBA) was performed for individual comparison between patients and controls. Voxel-based analysis revealed significant MD increase in variant regions in 13 patients. The electroclinical seizure localization was concurred to seven patients. No patient exhibited regions of significant decreased MD. Regions of significant reduced FA were observed in five patients, with two of these concurring with electroclinical seizure localization. Two patients had regions of significant increase in FA, which were distinct from electroclinical seizure localization. Our study's results revealed that DTI is a responsive neuroradiologic technique that provides information about the epileptogenic areas in patients with MRI-negative refractory partial epilepsy. This technique may also helpful in pre-surgical evaluation.
Increased working memory related fMRI signal in children following Tick Borne Encephalitis.
Henrik, Ullman; Åsa, Fowler; Ronny, Wickström
2016-01-01
Tick Borne Encephalitis (TBE) is a viral infection in the central nervous system endemic in Europe and Asia. While pediatric infection may carry a lower risk for serious neurological sequelae compared to adults, a large proportion of children experience long term cognitive problems, most markedly decreased working memory capacity. We explored whether task related functional magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) could reveal a biological correlate of status-post TBE in children. We examined 11 serologically verified pediatric TBE patients with central nervous system involvement with 55 healthy controls with working memory tests and MRI. The TBE patients showed a prominent deficit in working memory capacity and an increased task related functional MRI signal in working memory related cortical areas during a spatial working memory task performed without sedation. No diffusion differences could be found with DTI, in line with the reported paucity of anatomical abnormalities. This study is the first to demonstrate functional MRI abnormalities in TBE patients that bears similarity to other patient groups with diffuse neuronal damage. Copyright © 2015 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.
MRI of chemical reactions and processes.
Britton, Melanie M
2017-08-01
As magnetic resonance imaging (MRI) can spatially resolve a wealth of molecular information available from nuclear magnetic resonance (NMR), it is able to non-invasively visualise the composition, properties and reactions of a broad range of spatially-heterogeneous molecular systems. Hence, MRI is increasingly finding applications in the study of chemical reactions and processes in a diverse range of environments and technologies. This article will explain the basic principles of MRI and how it can be used to visualise chemical composition and molecular properties, providing an overview of the variety of information available. Examples are drawn from the disciplines of chemistry, chemical engineering, environmental science, physics, electrochemistry and materials science. The review introduces a range of techniques used to produce image contrast, along with the chemical and molecular insight accessible through them. Methods for mapping the distribution of chemical species, using chemical shift imaging or spatially-resolved spectroscopy, are reviewed, as well as methods for visualising physical state, temperature, current density, flow velocities and molecular diffusion. Strategies for imaging materials with low signal intensity, such as those containing gases or low sensitivity nuclei, using compressed sensing, para-hydrogen or polarisation transfer, are discussed. Systems are presented which encapsulate the diversity of chemical and physical parameters observable by MRI, including one- and two-phase flow in porous media, chemical pattern formation, phase transformations and hydrodynamic (fingering) instabilities. Lastly, the emerging area of electrochemical MRI is discussed, with studies presented on the visualisation of electrochemical deposition and dissolution processes during corrosion and the operation of batteries, supercapacitors and fuel cells. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.
Diffusion Lung Imaging with Hyperpolarized Gas MRI
Yablonskiy, Dmitriy A; Sukstanskii, Alexander L; Quirk, James D
2015-01-01
Lung imaging using conventional 1H MRI presents great challenges due to low density of lung tissue, lung motion and very fast lung tissue transverse relaxation (typical T2* is about 1-2 ms). MRI with hyperpolarized gases (3He and 129Xe) provides a valuable alternative due to a very strong signal originated from inhaled gas residing in the lung airspaces and relatively slow gas T2* relaxation (typical T2* is about 20-30 ms). Though in vivo human experiments should be done very fast – usually during a single breath-hold. In this review we describe the recent developments in diffusion lung MRI with hyperpolarized gases. We show that a combination of modeling results of gas diffusion in lung airspaces and diffusion measurements with variable diffusion-sensitizing gradients allows extracting quantitative information on the lung microstructure at the alveolar level. This approach, called in vivo lung morphometry, allows from a less than 15-second MRI scan, providing quantitative values and spatial distributions of the same physiological parameters as are measured by means of the “standard” invasive stereology (mean linear intercept, surface-to-volume ratio, density of alveoli, etc.). Besides, the approach makes it possible to evaluate some advanced Weibel parameters characterizing lung microstructure - average radii of alveolar sacs and ducts, as well as the depth of their alveolar sleeves. Such measurements, providing in vivo information on the integrity of pulmonary acinar airways and their changes in different diseases, are of great importance and interest to a broad range of physiologists and clinicians. We also discuss a new type of experiments that are based on the in vivo lung morphometry technique combined with quantitative CT measurements as well as with the Gradient Echo MRI measurements of hyperpolarized gas transverse relaxation in the lung airspaces. Such experiments provide additional information on the blood vessel volume fraction, specific gas volume, the length of acinar airways, and allows evaluation of lung parenchymal and non-parenchymal tissue. PMID:26676342
NASA Astrophysics Data System (ADS)
Mahmood, Faisal; Johannesen, Helle H.; Geertsen, Poul; Hansen, Rasmus H.
2017-04-01
An imaging biomarker for early prediction of treatment response potentially provides a non-invasive tool for better prognostics and individualized management of the disease. Radiotherapy (RT) response is generally related to changes in gross tumor volume manifesting months later. In this prospective study we investigated the apparent diffusion coefficient (ADC), perfusion fraction and pseudo diffusion coefficient derived from diffusion weighted MRI as potential early biomarkers for radiotherapy response of brain metastases. It was a particular aim to assess the optimal time point for acquiring the DW-MRI scan during the course of treatment, since to our knowledge this important question has not been addressed directly in previous studies. Twenty-nine metastases (N = 29) from twenty-one patients, treated with whole-brain fractionated external beam RT were analyzed. Patients were scanned with a 1 T MRI system to acquire DW-, T2*W-, T2W- and T1W scans, before start of RT, at each fraction and at follow up two to three months after RT. The DW-MRI parameters were derived using regions of interest based on high b-value images (b = 800 s mm-2). Both volumetric and RECIST criteria were applied for response evaluation. It was found that in non-responding metastases the mean ADC decreased and in responding metastases it increased. The volume based response proved to be far more consistently predictable by the ADC change found at fraction number 7 and later, compared to the linear response (RECIST). The perfusion fraction and pseudo diffusion coefficient did not show sufficient prognostic value with either response assessment criteria. In conclusion this study shows that the ADC derived using high b-values may be a reliable biomarker for early assessment of radiotherapy response for brain metastases patients. The earliest response stratification can be achieved using two DW-MRI scans, one pre-treatment and one at treatment day 7-9 (equivalent to 21 Gy).
2015-10-01
that includes physical and neuropsychological evaluations, neuroimaging (MRI, fMRI , DTI), adrenal function tests, and diverse immune, inflammatory...characterized by a profile of concurrent symptoms that typically includes persistent headaches, memory and cognitive difficulties, widespread pain, unexplained...includes physical examinations, neuroimaging (MRI volumetric assessments, fMRI , diffusion tensor imaging), neuropsychological evaluations, assessment
Jeon, Ji Young; Lee, Min Hee; Lee, Sang Hoon; Shin, Myung Jin
2016-01-01
Objective: To evaluate the usefulness of adding diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping to conventional 3.0-T MRI to differentiate between benign and malignant superficial soft-tissue masses (SSTMs). Methods: The institutional review board approved this study and informed consent was waived. The authors retrospectively analyzed conventional MR images including diffusion-weighted images (b-values: 0, 400, 800 s mm−2) in 60 histologically proven SSTMs (35 benign and 25 malignant) excluding lipomas. Two radiologists independently evaluated the conventional MRI alone and again with the additional DWI for the evaluation of malignant masses. The mean ADC values measured within an entire mass and the contrast-enhancing solid portion were used for quantitative analysis. Diagnostic performances were compared using receiver-operating characteristic analysis. Results: For an inexperienced reader, using only conventional MRI, the sensitivity, specificity and accuracy were 84%, 80% and 81.6%, respectively. When combining conventional MRI and DWI, the sensitivity, specificity and accuracy were 96%, 85.7% and 90%, respectively. Additional DWI influenced the improvement of the rate of correct diagnosis by 8.3% (5/60). For an experienced reader, additional DWI revealed the same accuracy of 86.7% without added value on the correct diagnosis. The group mean ADCs of malignant SSTMs were significantly lower than that of benign SSTMs (p < 0.001). The best diagnostic performance with respect to differentiation of SSTMs could be obtained when conventional MRI was assessed in combination with DWI. Conclusion: Adding qualitative and quantitative DWI to conventional MRI can improve the diagnostic performance for the differentiation between benign and malignant SSTMs. Advances in knowledge: Because the imaging characteristics of many malignant superficial soft-tissue lesions overlap with those of benign ones, inadequate surgical resection due to misinterpretation of MRI often occurs. Adding DWI to conventional MRI yields greater diagnostic performances [area under the receiver-operating characteristic curve (AUC), 0.83–0.99] than does the use of conventional MRI alone (AUC, 0.71–0.93) in the evaluation of malignant superficial masses by inexperienced readers. PMID:26892266
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xie, Y; Wang, C; Horton, J
Purpose: To investigate the feasibility of using classic textural feature extraction in radiotherapy response assessment, we studied a unique cohort of early stage breast cancer patients with paired pre - and post-radiation Diffusion Weighted MRI (DWI-MRI) and Dynamic Contrast Enhanced MRI (DCE-MRI). Methods: 15 female patients from our prospective phase I trial evaluating preoperative radiotherapy were included in this retrospective study. Each patient received a single-fraction radiation treatment, and DWI and DCE scans were conducted before and after the radiotherapy. DWI scans were acquired using a spin-echo EPI sequence with diffusion weighting factors of b = 0 and b =more » 500 mm{sup 2} /s, and the apparent diffusion coefficient (ADC) maps were calculated. DCE-MRI scans were acquired using a T{sub 1}-weighted 3D SPGR sequence with a temporal resolution of about 1 minute. The contrast agent (CA) was intravenously injected with a 0.1 mmol/kg bodyweight dose at 2 ml/s. Two parameters, volume transfer constant (K{sup trans} ) and k{sub ep} were analyzed using the two-compartment Tofts kinetic model. For DCE parametric maps and ADC maps, 33 textural features were generated from the clinical target volume (CTV) in a 3D fashion using the classic gray level co-occurrence matrix (GLCOM) and gray level run length matrix (GLRLM). Wilcoxon signed-rank test was used to determine the significance of each texture feature’s change after the radiotherapy. The significance was set to 0.05 with Bonferroni correction. Results: For ADC maps calculated from DWI-MRI, 24 out of 33 CTV features changed significantly after the radiotherapy. For DCE-MRI pharmacokinetic parameters, all 33 CTV features of K{sup trans} and 33 features of k{sub ep} changed significantly. Conclusion: Initial results indicate that those significantly changed classic texture features are sensitive to radiation-induced changes and can be used for assessment of radiotherapy response in breast cancer.« less
Lessard, Eric; Young, Heather M; Bhalla, Anurag; Pike, Damien; Sheikh, Khadija; McCormack, David G; Ouriadov, Alexei; Parraga, Grace
2017-11-01
Thoracic x-ray computed tomography (CT) and hyperpolarized 3 He magnetic resonance imaging (MRI) provide quantitative measurements of airspace enlargement in patients with emphysema. For patients with panlobular emphysema due to alpha-1 antitrypsin deficiency (AATD), sensitive biomarkers of disease progression and response to therapy have been difficult to develop and exploit, especially those biomarkers that correlate with outcomes like quality of life. Here, our objective was to generate and compare CT and diffusion-weighted inhaled-gas MRI measurements of emphysema including apparent diffusion coefficient (ADC) and MRI-derived mean linear intercept (L m ) in patients with AATD, chronic obstructive pulmonary disease (COPD) ex-smokers, and elderly never-smokers. We enrolled patients with AATD (n = 8; 57 ± 7 years), ex-smokers with COPD (n = 8; 77 ± 6 years), and a control group of never-smokers (n = 5; 64 ± 2 years) who underwent thoracic CT, MRI, spirometry, plethysmography, the St. George's Respiratory Questionnaire, and the 6-minute walk test during a single 2-hour visit. MRI-derived ADC, L m , surface-to-volume ratio, and ventilation defect percent were generated for the apical, basal, and whole lung as was CT lung area ≤-950 Hounsfield units (RA 950 ), low attenuating clusters, and airway count. In patients with AATD, there was a significantly different MRI-derived ADC (P = .03), L m (P < .0001), and surface-to-volume ratio (P < .0001), but not diffusing capacity of carbon monoxide, residual volume or total lung capacity, or CT RA 950 (P > .05) compared to COPD ex-smokers with a significantly different St. George's Respiratory Questionnaire. In this proof-of-concept demonstration, we evaluated CT and MRI lung emphysema measurements and observed significantly worse MRI biomarkers of emphysema in patients with AATD compared to patients with COPD, although CT RA 950 and diffusing capacity of carbon monoxide were not significantly different, underscoring the sensitivity of MRI measurements of AATD emphysema. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
Beaujoin, Justine; Palomero-Gallagher, Nicola; Boumezbeur, Fawzi; Axer, Markus; Bernard, Jeremy; Poupon, Fabrice; Schmitz, Daniel; Mangin, Jean-François; Poupon, Cyril
2018-06-01
The human hippocampus plays a key role in memory management and is one of the first structures affected by Alzheimer's disease. Ultra-high magnetic resonance imaging provides access to its inner structure in vivo. However, gradient limitations on clinical systems hinder access to its inner connectivity and microstructure. A major target of this paper is the demonstration of diffusion MRI potential, using ultra-high field (11.7 T) and strong gradients (750 mT/m), to reveal the extra- and intra-hippocampal connectivity in addition to its microstructure. To this purpose, a multiple-shell diffusion-weighted acquisition protocol was developed to reach an ultra-high spatio-angular resolution with a good signal-to-noise ratio. The MRI data set was analyzed using analytical Q-Ball Imaging, Diffusion Tensor Imaging (DTI), and Neurite Orientation Dispersion and Density Imaging models. High Angular Resolution Diffusion Imaging estimates allowed us to obtain an accurate tractography resolving more complex fiber architecture than DTI models, and subsequently provided a map of the cross-regional connectivity. The neurite density was akin to that found in the histological literature, revealing the three hippocampal layers. Moreover, a gradient of connectivity and neurite density was observed between the anterior and the posterior part of the hippocampus. These results demonstrate that ex vivo ultra-high field/ultra-high gradients diffusion-weighted MRI allows the mapping of the inner connectivity of the human hippocampus, its microstructure, and to accurately reconstruct elements of the polysynaptic intra-hippocampal pathway using fiber tractography techniques at very high spatial/angular resolutions.
Taimouri, Vahid; Afacan, Onur; Perez-Rossello, Jeannette M.; Callahan, Michael J.; Mulkern, Robert V.; Warfield, Simon K.; Freiman, Moti
2015-01-01
Purpose: To evaluate the effect of the spatially constrained incoherent motion (SCIM) method on improving the precision and robustness of fast and slow diffusion parameter estimates from diffusion-weighted MRI in liver and spleen in comparison to the independent voxel-wise intravoxel incoherent motion (IVIM) model. Methods: We collected diffusion-weighted MRI (DW-MRI) data of 29 subjects (5 healthy subjects and 24 patients with Crohn’s disease in the ileum). We evaluated parameters estimates’ robustness against different combinations of b-values (i.e., 4 b-values and 7 b-values) by comparing the variance of the estimates obtained with the SCIM and the independent voxel-wise IVIM model. We also evaluated the improvement in the precision of parameter estimates by comparing the coefficient of variation (CV) of the SCIM parameter estimates to that of the IVIM. Results: The SCIM method was more robust compared to IVIM (up to 70% in liver and spleen) for different combinations of b-values. Also, the CV values of the parameter estimations using the SCIM method were significantly lower compared to repeated acquisition and signal averaging estimated using IVIM, especially for the fast diffusion parameter in liver (CVIV IM = 46.61 ± 11.22, CVSCIM = 16.85 ± 2.160, p < 0.001) and spleen (CVIV IM = 95.15 ± 19.82, CVSCIM = 52.55 ± 1.91, p < 0.001). Conclusions: The SCIM method characterizes fast and slow diffusion more precisely compared to the independent voxel-wise IVIM model fitting in the liver and spleen. PMID:25832079
Schouten, Tijn M; Koini, Marisa; de Vos, Frank; Seiler, Stephan; van der Grond, Jeroen; Lechner, Anita; Hafkemeijer, Anne; Möller, Christiane; Schmidt, Reinhold; de Rooij, Mark; Rombouts, Serge A R B
2016-01-01
Magnetic resonance imaging (MRI) is sensitive to structural and functional changes in the brain caused by Alzheimer's disease (AD), and can therefore be used to help in diagnosing the disease. Improving classification of AD patients based on MRI scans might help to identify AD earlier in the disease's progress, which may be key in developing treatments for AD. In this study we used an elastic net classifier based on several measures derived from the MRI scans of mild to moderate AD patients (N = 77) from the prospective registry on dementia study and controls (N = 173) from the Austrian Stroke Prevention Family Study. We based our classification on measures from anatomical MRI, diffusion weighted MRI and resting state functional MRI. Our unimodal classification performance ranged from an area under the curve (AUC) of 0.760 (full correlations between functional networks) to 0.909 (grey matter density). When combining measures from multiple modalities in a stepwise manner, the classification performance improved to an AUC of 0.952. This optimal combination consisted of grey matter density, white matter density, fractional anisotropy, mean diffusivity, and sparse partial correlations between functional networks. Classification performance for mild AD as well as moderate AD also improved when using this multimodal combination. We conclude that different MRI modalities provide complementary information for classifying AD. Moreover, combining multiple modalities can substantially improve classification performance over unimodal classification.
Koh, D-M; Collins, D J; Wallace, T; Chau, I; Riddell, A M
2012-07-01
To compare the diagnostic accuracy of gadolinium-ethoxybenzyl-diethylenetriaminepentaacetic acid (Gd-EOB-DTPA)-enhanced MRI, diffusion-weighted MRI (DW-MRI) and a combination of both techniques for the detection of colorectal hepatic metastases. 72 patients with suspected colorectal liver metastases underwent Gd-EOB-DTPA MRI and DW-MRI. Images were retrospectively reviewed with unenhanced T(1) and T(2) weighted images as Gd-EOB-DTPA image set, DW-MRI image set and combined image set by two independent radiologists. Each lesion detected was scored for size, location and likelihood of metastasis, and compared with surgery and follow-up imaging. Diagnostic accuracy was compared using receiver operating characteristics and interobserver agreement by kappa statistics. 417 lesions (310 metastases, 107 benign) were found in 72 patients. For both readers, diagnostic accuracy using the combined image set was higher [area under the curve (Az)=0.96, 0.97] than Gd-EOB-DTPA image set (Az=0.86, 0.89) or DW-MRI image set (Az=0.93, 0.92). Using combined image set improved identification of liver metastases compared with Gd-EOB-DTPA image set (p<0.001) or DW-MRI image set (p<0.001). There was very good interobserver agreement for lesion classification (κ=0.81-0.88). Combining DW-MRI with Gd-EOB-DTPA-enhanced T(1) weighted MRI significantly improved the detection of colorectal liver metastases.
Li, Xiulei; Wang, Ling; Li, Yong; Song, Peiji
2017-10-01
This study aimed to investigate the value of diffusion-weighted imaging (DWI) in combination with conventional magnetic resonance imaging (MRI) for improving tumor detection in young patients treated with fertility-sparing surgery because of early cervical carcinoma. Fifty-four patients with stage Ia or Ib1 cervical carcinoma were enrolled into this study. Magnetic resonance examinations were performed for these patients using conventional MRI (including T1-weighted imaging, T2-weighted imaging, and dynamic contrast-enhanced MRI) and DWI. The apparent diffusion coefficient (ADC) values of cervical carcinoma were analyzed quantitatively and compared with that of adjacent epithelium. Sensitivity, positive predictive value, and accuracy of 2 sets of MRI sequences were calculated on the basis of histologic results, and the diagnostic ability of conventional MRI/DWI combinations was compared with that of conventional MRI. The mean ADC value from cervical carcinoma (mean, 786 × 10 mm/s ± 100) was significantly lower than that from adjacent epithelium (mean, 1352 × 10 mm/s ± 147) (P = 0.01). When the threshold ADC value set as 1010 × 10 mm/s, the sensitivity and specificity for differentiating cervical carcinoma from nontumor epithelium were 78.2% and 67.2%, respectively. The sensitivity and accuracy of conventional MRI for tumor detection were 76.0% and 70.4%, whereas the sensitivity and accuracy of conventional MRI/DWI combinations were 91.7% and 90.7%, respectively. Conventional MRI/DWI combinations revealed a positive predictive value of 97.8% and only 4 false-negative findings. The addition of DWI to conventional MRI considerably improves the sensitivity and accuracy of tumor detection in young patients treated with fertility-sparing surgery, which supports the inclusion quantitative analysis of ADC value in routine MRI protocol before fertility-sparing surgery.
Magnetic Resonance Imaging of Liver Metastasis.
Karaosmanoglu, Ali Devrim; Onur, Mehmet Ruhi; Ozmen, Mustafa Nasuh; Akata, Deniz; Karcaaltincaba, Musturay
2016-12-01
Liver magnetic resonance imaging (MRI) is becoming the gold standard in liver metastasis detection and treatment response assessment. The most sensitive magnetic resonance sequences are diffusion-weighted images and hepatobiliary phase images after Gd-EOB-DTPA. Peripheral ring enhancement, diffusion restriction, and hypointensity on hepatobiliary phase images are hallmarks of liver metastases. In patients with normal ultrasonography, computed tomography (CT), and positron emission tomography (PET)-CT findings and high clinical suspicion of metastasis, MRI should be performed for diagnosis of unseen metastasis. In melanoma, colon cancer, and neuroendocrine tumor metastases, MRI allows confident diagnosis of treatment-related changes in liver and enables differential diagnosis from primary liver tumors. Focal nodular hyperplasia-like nodules in patients who received platinum-based chemotherapy, hypersteatosis, and focal fat can mimic metastasis. In cancer patients with fatty liver, MRI should be preferred to CT. Although the first-line imaging for metastases is CT, MRI can be used as a problem-solving method. MRI may be used as the first-line method in patients who would undergo curative surgery or metastatectomy. Current limitation of MRI is low sensitivity for metastasis smaller than 3mm. MRI fingerprinting, glucoCEST MRI, and PET-MRI may allow simpler and more sensitive diagnosis of liver metastasis. Copyright © 2016 Elsevier Inc. All rights reserved.
A possible application of magnetic resonance imaging for pharmaceutical research.
Kowalczuk, Joanna; Tritt-Goc, Jadwiga
2011-03-18
Magnetic resonance imaging (MRI) is a non-destructive and non-invasive method, the experiment can be conducted in situ and allows the studying of the sample and the different processes in vitro or in vivo. 1D, 2D or 3D imaging can be undertaken. MRI is nowadays most widely used in medicine as a clinical diagnostic tool, but has still seen limited application in the food and pharmaceutical sciences. The different imaging pulse sequences of MRI allow to image the processes that take place in a wide scale range from ms (dissolution of compact tablets) to hours (hydration of drug delivery systems) for mobile as well as for rigid spins, usually protons. The paper gives examples of MRI application of in vitro imaging of pharmaceutical dosage based on hydroxypropyl methylcellulose which have focused on water-penetration, diffusion, polymer swelling, and drug release, characterized with respect to other physical parameters such as pH and the molecular weight of polymer. Tetracycline hydrochloride was used as a model drug. NMR imaging of density distributions and fast kinetics of the dissolution behavior of compact tablets is presented for paracetamol tablets. Copyright © 2010 Elsevier B.V. All rights reserved.
Abascal, Juan F P J; Desco, Manuel; Parra-Robles, Juan
2018-02-01
Diffusion MRI data are generally acquired using hyperpolarized gases during patient breath-hold, which yields a compromise between achievable image resolution, lung coverage, and number of -values. In this paper, we propose a novel method that accelerates the acquisition of diffusion MRI data by undersampling in both the spatial and -value dimensions and incorporating knowledge about signal decay into the reconstruction (SIDER). SIDER is compared with total variation (TV) reconstruction by assessing its effect on both the recovery of ventilation images and the estimated mean alveolar dimensions (MADs). Both methods are assessed by retrospectively undersampling diffusion data sets ( =8) of healthy volunteers and patients with Chronic Obstructive Pulmonary Disease (COPD) for acceleration factors between x2 and x10. TV led to large errors and artifacts for acceleration factors equal to or larger than x5. SIDER improved TV, with a lower solution error and MAD histograms closer to those obtained from fully sampled data for acceleration factors up to x10. SIDER preserved image quality at all acceleration factors, although images were slightly smoothed and some details were lost at x10. In conclusion, we developed and validated a novel compressed sensing method for lung MRI imaging and achieved high acceleration factors, which can be used to increase the amount of data acquired during breath-hold. This methodology is expected to improve the accuracy of estimated lung microstructure dimensions and provide more options in the study of lung diseases with MRI.
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.
Quantitative characterization of the imaging limits of diffuse low-grade oligodendrogliomas.
Gerin, Chloé; Pallud, Johan; Deroulers, Christophe; Varlet, Pascale; Oppenheim, Catherine; Roux, Francois-Xavier; Chrétien, Fabrice; Thomas, Stephen R; Grammaticos, Basile; Badoual, Mathilde
2013-10-01
Supratentorial diffuse low-grade gliomas in adults extend beyond maximal visible MRI-defined abnormalities, and a gap exists between the imaging signal changes and the actual tumor margins. Direct quantitative comparisons between imaging and histological analyses are lacking to date. However, they are of the utmost importance if one wishes to develop realistic models for diffuse glioma growth. In this study, we quantitatively compared the cell concentration and the edema fraction from human histological biopsy samples (BSs) performed inside and outside imaging abnormalities during serial imaging-based stereotactic biopsy of diffuse low-grade gliomas. The cell concentration was significantly higher in BSs located inside (1189 ± 378 cell/mm(2)) than outside (740 ± 124 cell/mm(2)) MRI-defined abnormalities (P = .0003). The edema fraction was significantly higher in BSs located inside (mean, 45% ± 23%) than outside (mean, 5 %± 9%) MRI-defined abnormalities (P < .0001). At borders of the MRI-defined abnormalities, 20% of the tissue surface area was occupied by edema and only 3% by tumor cells. The cycling cell concentration was significantly higher in BSs located inside (10 ± 12 cell/mm(2)), compared with outside (0.5 ± 0.9 cell/mm(2)), MRI-defined abnormalities (P = .0001). We showed that the margins of T2-weighted signal changes are mainly correlated with the edema fraction. In 62.5% of patients, the cycling tumor cell fraction (defined as the ratio of the cycling tumor cell concentration to the total number of tumor cells) was higher at the limits of the MRI-defined abnormalities than closer to the center of the tumor. In the remaining patients, the cycling tumor cell fraction increased towards the center of the tumor.
Iannicelli, Elsa; Di Pietropaolo, Marco; Pilozzi, Emanuela; Osti, Mattia Falchetto; Valentino, Maria; Masoni, Luigi; Ferri, Mario
2016-10-01
The aim of our study was to assess the performance value of magnetic resonance imaging (MRI) in the restaging of locally advanced rectal cancer after neoadjuvant chemoradiotherapy (CRT) and in the identification of good vs. poor responders to neoadjuvant therapy. A total of 34 patients with locally advanced rectal cancer underwent MRI prior to and after CRT. T stage and tumor regression grade (TRG) on post-CRT MRI was compared with the pathological staging ypT and TRG. Tumor volume and the apparent diffusion coefficient (ADC) were measured using diffusion-weighted imaging (DWI) before and after neoadjuvant CRT; the percentage of tumor volume reduction and the change of ADC (ΔADC) was also calculated. ADC parameters and the percentage of tumor volume reduction were correlated to histopathological results. The diagnostic performance of ADC and volume reduction to assess tumor response was evaluated by calculating the area under the ROC curve and the optimal cut-off values. A significant correlation between the T stage and the TRG defined in DW-MRI after CRT and the ypT and the TRG observed on the surgical specimens was found (p = 0.001; p < 0.001). The mean post-CRT ADC and ΔADC in responder patients was significantly higher compared to non-responder ones (p = 0.001; p = 0.01). Furthermore, the mean post-CRT ADC values were significantly higher in tumors with T-downstage (p = 0.01). DW-MRI may have a significant role in the restaging and in the evaluation of post-CRT response of locally advanced rectal cancer. Quantitative analysis of DWI through ADC map may result in a promising noninvasive tool to evaluate the response to therapy.
Ma, Wanling; Li, Na; Zhao, Weiwei; Ren, Jing; Wei, Mengqi; Yang, Yong; Wang, Yingmei; Fu, Xin; Zhang, Zhuoli; Larson, Andrew C; Huan, Yi
2016-01-01
To clarify diffusion and perfusion abnormalities and evaluate correlation between apparent diffusion coefficient (ADC), MR perfusion and histopathologic parameters of pancreatic cancer (PC). Eighteen patients with PC underwent diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Parameters of DCE-MRI and ADC of cancer and non-cancerous tissue were compared. Correlation between the rate constant that represents transfer of contrast agent from the arterial blood into the extravascular extracellular space (K, volume of the extravascular extracellular space per unit volume of tissue (Ve), and ADC of PC and histopathologic parameters were analyzed. The rate constant that represents transfer of contrast agent from the extravascular extracellular space into blood plasma, K, tissue volume fraction occupied by vascular space, and ADC of PC were significantly lower than nontumoral pancreases. Ve of PC was significantly higher than that of nontumoral pancreas. Apparent diffusion coefficient and K values of PC were negatively correlated to fibrosis content and fibroblast activation protein staining score. Fibrosis content was positively correlated to Ve. Apparent diffusion coefficient values and parameters of DCE-MRI can differentiate PC from nontumoral pancreases. There are correlations between ADC, K, Ve, and fibrosis content of PC. Fibroblast activation protein staining score of PC is negatively correlated to ADC and K. Apparent diffusion coefficient, K, and Ve may be feasible to predict prognosis of PC.
Lung Morphometry with Hyperpolarized 129Xe: Theoretical Background
Sukstanskii, A.L.; Yablonskiy, D.A.
2011-01-01
The 3He lung morphometry technique, based on MRI measurements of hyperpolarized 3He gas diffusion in lung airspaces, provides unique information on the lung microstructure at the alveolar level. In vivo 3D tomographic images of standard morphological parameters (airspace chord length, lung parenchyma surface-to-volume ratio, number of alveoli per unit volume) can be generated from a rather short (several seconds) MRI scan. The technique is based on a theory of gas diffusion in lung acinar airways and experimental measurements of diffusion attenuated MRI signal. The present work aims at developing the theoretical background of a similar technique based on hyperpolarized 129Xe gas. As the diffusion coefficient and gyromagnetic ratio of 129Xe gas are substantially different from those of 3He gas, the specific details of the theory and experimental measurements with 129Xe should be amended. We establish phenomenological relationships between acinar airway geometrical parameters and the diffusion attenuated MR signal for human and small animal lungs, both normal lungs and lungs with mild emphysema. Optimal diffusion times are shown to be about 5 ms for human and 1.3 ms for small animals. The expected uncertainties in measuring main morphometrical parameters of the lungs are estimated in the framework of Bayesian probability theory. PMID:21713985
[Effect of vibration caused by time-varying magnetic fields on diffusion-weighted MRI].
Ogura, Akio; Maeda, Fumie; Miyai, Akira; Hayashi, Kohji; Hongoh, Takaharu
2006-04-20
Diffusion-weighted images (DWIs) with high b-factor in the body are often used to detect and diagnose cancer at MRI. The echo planar imaging (EPI) sequence and high motion probing gradient pulse are used at diffusion weighted imaging, causing high table vibration. The purpose of this study was to assess whether the diffusion signal and apparent diffusion coefficient (ADC) values are influenced by this vibration because of time-varying magnetic fields. Two DWIs were compared. In one, phantoms were fixed on the MRI unit's table transmitting the vibration. In the other, phantoms were supported in air, in the absence of vibration. The phantoms called "solution phantoms" were made from agarose of a particular density. The phantoms called "jelly phantoms" were made from agarose that was heated. The diffusion signal and ADC value of each image were compared. The results showed that the signal of DWI units using the solution phantom was not affected by vibration. However, the signal of DWI and ADC were increased in the low-density jelly phantom as a result of vibration, causing the jelly phantom to vibrate. The DWIs of vibrating regions such as the breast maybe be subject to error. A countermeasure seems to be to support the region adequately.
Focal Cortical Dysplasia (FCD) lesion analysis with complex diffusion approach.
Rajan, Jeny; Kannan, K; Kesavadas, C; Thomas, Bejoy
2009-10-01
Identification of Focal Cortical Dysplasia (FCD) can be difficult due to the subtle MRI changes. Though sequences like FLAIR (fluid attenuated inversion recovery) can detect a large majority of these lesions, there are smaller lesions without signal changes that can easily go unnoticed by the naked eye. The aim of this study is to improve the visibility of focal cortical dysplasia lesions in the T1 weighted brain MRI images. In the proposed method, we used a complex diffusion based approach for calculating the FCD affected areas. Based on the diffused image and thickness map, a complex map is created. From this complex map; FCD areas can be easily identified. MRI brains of 48 subjects selected by neuroradiologists were given to computer scientists who developed the complex map for identifying the cortical dysplasia. The scientists were blinded to the MRI interpretation result of the neuroradiologist. The FCD could be identified in all the patients in whom surgery was done, however three patients had false positive lesions. More lesions were identified in patients in whom surgery was not performed and lesions were seen in few of the controls. These were considered as false positive. This computer aided detection technique using complex diffusion approach can help detect focal cortical dysplasia in patients with epilepsy.
Ultra-high field upper extremity peripheral nerve and non-contrast enhanced vascular imaging
Raval, Shailesh B.; Britton, Cynthia A.; Zhao, Tiejun; Krishnamurthy, Narayanan; Santini, Tales; Gorantla, Vijay S.; Ibrahim, Tamer S.
2017-01-01
Objective The purpose of this study was to explore the efficacy of Ultra-high field [UHF] 7 Tesla [T] MRI as compared to 3T MRI in non-contrast enhanced [nCE] imaging of structural anatomy in the elbow, forearm, and hand [upper extremity]. Materials and method A wide range of sequences including T1 weighted [T1] volumetric interpolate breath-hold exam [VIBE], T2 weighted [T2] double-echo steady state [DESS], susceptibility weighted imaging [SWI], time-of-flight [TOF], diffusion tensor imaging [DTI], and diffusion spectrum imaging [DSI] were optimized and incorporated with a radiofrequency [RF] coil system composed of a transverse electromagnetic [TEM] transmit coil combined with an 8-channel receive-only array for 7T upper extremity [UE] imaging. In addition, Siemens optimized protocol/sequences were used on a 3T scanner and the resulting images from T1 VIBE and T2 DESS were compared to that obtained at 7T qualitatively and quantitatively [SWI was only qualitatively compared]. DSI studio was utilized to identify nerves based on analysis of diffusion weighted derived fractional anisotropy images. Images of forearm vasculature were extracted using a paint grow manual segmentation method based on MIPAV [Medical Image Processing, Analysis, and Visualization]. Results High resolution and high quality signal-to-noise ratio [SNR] and contrast-to-noise ratio [CNR]—images of the hand, forearm, and elbow were acquired with nearly homogeneous 7T excitation. Measured [performed on the T1 VIBE and T2 DESS sequences] SNR and CNR values were almost doubled at 7T vs. 3T. Cartilage, synovial fluid and tendon structures could be seen with higher clarity in the 7T T1 and T2 weighted images. SWI allowed high resolution and better quality imaging of large and medium sized arteries and veins, capillary networks and arteriovenous anastomoses at 7T when compared to 3T. 7T diffusion weighted sequence [not performed at 3T] demonstrates that the forearm nerves are clearly delineated by fiber tractography. The proper digital palmar arteries and superficial palmar arch could also be clearly visualized using TOF nCE 7T MRI. Conclusion Ultra-high resolution neurovascular imaging in upper extremities is possible at 7T without use of renal toxic intravenous contrast. 7T MRI can provide superior peripheral nerve [based on fiber anisotropy and diffusion coefficient parameters derived from diffusion tensor/spectrum imaging] and vascular [nCE MRA and vessel segmentation] imaging. PMID:28662061
Robust and fast nonlinear optimization of diffusion MRI microstructure models.
Harms, R L; Fritz, F J; Tobisch, A; Goebel, R; Roebroeck, A
2017-07-15
Advances in biophysical multi-compartment modeling for diffusion MRI (dMRI) have gained popularity because of greater specificity than DTI in relating the dMRI signal to underlying cellular microstructure. A large range of these diffusion microstructure models have been developed and each of the popular models comes with its own, often different, optimization algorithm, noise model and initialization strategy to estimate its parameter maps. Since data fit, accuracy and precision is hard to verify, this creates additional challenges to comparability and generalization of results from diffusion microstructure models. In addition, non-linear optimization is computationally expensive leading to very long run times, which can be prohibitive in large group or population studies. In this technical note we investigate the performance of several optimization algorithms and initialization strategies over a few of the most popular diffusion microstructure models, including NODDI and CHARMED. We evaluate whether a single well performing optimization approach exists that could be applied to many models and would equate both run time and fit aspects. All models, algorithms and strategies were implemented on the Graphics Processing Unit (GPU) to remove run time constraints, with which we achieve whole brain dataset fits in seconds to minutes. We then evaluated fit, accuracy, precision and run time for different models of differing complexity against three common optimization algorithms and three parameter initialization strategies. Variability of the achieved quality of fit in actual data was evaluated on ten subjects of each of two population studies with a different acquisition protocol. We find that optimization algorithms and multi-step optimization approaches have a considerable influence on performance and stability over subjects and over acquisition protocols. The gradient-free Powell conjugate-direction algorithm was found to outperform other common algorithms in terms of run time, fit, accuracy and precision. Parameter initialization approaches were found to be relevant especially for more complex models, such as those involving several fiber orientations per voxel. For these, a fitting cascade initializing or fixing parameter values in a later optimization step from simpler models in an earlier optimization step further improved run time, fit, accuracy and precision compared to a single step fit. This establishes and makes available standards by which robust fit and accuracy can be achieved in shorter run times. This is especially relevant for the use of diffusion microstructure modeling in large group or population studies and in combining microstructure parameter maps with tractography results. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Characterization of diffuse orbital mass using Apparent diffusion coefficient in 3-tesla MRI.
ElKhamary, Sahar M; Galindo-Ferreiro, Alicia; AlGhafri, Laila; Khandekar, Rajiv; Schellini, Silvana Artioli
2018-01-01
To evaluate if the apparent diffusion coefficient (ADC) value in diffusion-weighted magnetic resonance imaging (DW-MRI) improves the diagnostic accuracy of diffuse orbital masses. ADC DW-MRI was used to evaluate cases of diffuse orbital masses at our institution from 2000 to 2015. Lesions were grouped according to histopathologic diagnosis as, benign, pre-malignant and malignant. Lymphoproliferative lesions were further subgrouped as lymphoma or other lymphoproliferative lesions. The validity of the ADC value for the diffuse orbital mass was compared between groups. The area under curve (AUC) was also calculated. Thirty-nine cases of diffuse orbital masses were evaluated. The median ADC was 0.58 (25% quartile 0.48; minimum: 0.45; maximum: 1.72 × 10 (-3) ) for the malignant tumors and 1.19 (25% quartile 0.7; minimum: 0.5; maximum: 1.95 × 10 (-3) mm (2) s (-1) ) for benign lesions. This difference in ADC between lesions was statistically significant (Mann Whitney U test P < 0.001). The median ADC was 0.51 (25% quartile 0.48) for lymphomas and 0.9 (25% quartile 0.7) for other lymphoproliferative lesions. This difference in ADC was statistically significant (Mann Whitney U test P = 0.02). An ADC value of 0.8 × 10 (-3) mm (2) s (-1) was noted as the ideal threshold value for differentiating malignant from benign diffuse orbital masses. The validity of ADC in predicting a malignant or benign diffuse orbital mass had a sensitivity of 87%, specificity of 67% and accuracy of 88%. ADC is a promising imaging metric to characterize malignant and benign diffuse orbital masses and to distinguish lymphomas from other non-lymphoproliferative lesions.
Neural and Behavioral Sequelae of Blast-Related Traumatic Brain Injury
2012-11-01
testing and advanced MRI techniques [task-activated functional MRI (fMRI) and diffusion tensor imaging ( DTI )] to gain a comprehensive understanding of... DTI fiber tracking) and neurobehavioral testing (computerized assessment and standard neuropsychological testing) on 60 chronic trauma patients: 15...data analysis. 15. SUBJECT TERMS Blast-related traumatic brain injury (TBI), fMRI, DTI , cognition 16. SECURITY CLASSIFICATION OF: 17. LIMITATION
Jones, D K; Alexander, D C; Bowtell, R; Cercignani, M; Dell'Acqua, F; McHugh, D J; Miller, K L; Palombo, M; Parker, G J M; Rudrapatna, U S; Tax, C M W
2018-05-22
The key component of a microstructural diffusion MRI 'super-scanner' is a dedicated high-strength gradient system that enables stronger diffusion weightings per unit time compared to conventional gradient designs. This can, in turn, drastically shorten the time needed for diffusion encoding, increase the signal-to-noise ratio, and facilitate measurements at shorter diffusion times. This review, written from the perspective of the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure, an initiative to establish a shared 300 mT/m-gradient facility amongst the microstructural imaging community, describes ten advantages of ultra-strong gradients for microstructural imaging. Specifically, we will discuss how the increase of the accessible measurement space compared to a lower-gradient systems (in terms of Δ, b-value, and TE) can accelerate developments in the areas of 1) axon diameter distribution mapping; 2) microstructural parameter estimation; 3) mapping micro-vs macroscopic anisotropy features with gradient waveforms beyond a single pair of pulsed-gradients; 4) multi-contrast experiments, e.g. diffusion-relaxometry; 5) tractography and high-resolution imaging in vivo and 6) post mortem; 7) diffusion-weighted spectroscopy of metabolites other than water; 8) tumour characterisation; 9) functional diffusion MRI; and 10) quality enhancement of images acquired on lower-gradient systems. We finally discuss practical barriers in the use of ultra-strong gradients, and provide an outlook on the next generation of 'super-scanners'. Copyright © 2018. Published by Elsevier Inc.
Impact of time-of-day on diffusivity measures of brain tissue derived from diffusion tensor imaging.
Thomas, Cibu; Sadeghi, Neda; Nayak, Amrita; Trefler, Aaron; Sarlls, Joelle; Baker, Chris I; Pierpaoli, Carlo
2018-06-01
Diurnal fluctuations in MRI measures of structural and functional properties of the brain have been reported recently. These fluctuations may have a physiological origin, since they have been detected using different MRI modalities, and cannot be explained by factors that are typically known to confound MRI measures. While preliminary evidence suggests that measures of structural properties of the brain based on diffusion tensor imaging (DTI) fluctuate as a function of time-of-day (TOD), the underlying mechanism has not been investigated. Here, we used a longitudinal within-subjects design to investigate the impact of time-of-day on DTI measures. In addition to using the conventional monoexponential tensor model to assess TOD-related fluctuations, we used a dual compartment tensor model that allowed us to directly assess if any change in DTI measures is due to an increase in CSF/free-water volume fraction or due to an increase in water diffusivity within the parenchyma. Our results show that Trace or mean diffusivity, as measured using the conventional monoexponential tensor model tends to increase systematically from morning to afternoon scans at the interface of grey matter/CSF, most prominently in the major fissures and the sulci of the brain. Interestingly, in a recent study of the glymphatic system, these same regions were found to show late enhancement after intrathecal injection of a CSF contrast agent. The increase in Trace also impacts DTI measures of diffusivity such as radial and axial diffusivity, but does not affect fractional anisotropy. The dual compartment analysis revealed that the increase in diffusivity measures from PM to AM was driven by an increase in the volume fraction of CSF-like free-water. Taken together, our findings provide important insight into the likely physiological origins of diurnal fluctuations in MRI measurements of structural properties of the brain. Published by Elsevier Inc.
Ianuş, Andrada; Shemesh, Noam
2018-04-01
Diffusion MRI is confounded by the need to acquire at least two images separated by a repetition time, thereby thwarting the detection of rapid dynamic microstructural changes. The issue is exacerbated when diffusivity variations are accompanied by rapid changes in T 2 . The purpose of the present study is to accelerate diffusion MRI acquisitions such that both reference and diffusion-weighted images necessary for quantitative diffusivity mapping are acquired in a single-shot experiment. A general methodology termed incomplete initial nutation diffusion imaging (INDI), capturing two diffusion contrasts in a single shot, is presented. This methodology creates a longitudinal magnetization reservoir that facilitates the successive acquisition of two images separated by only a few milliseconds. The theory behind INDI is presented, followed by proof-of-concept studies in water phantom, ex vivo, and in vivo experiments at 16.4 and 9.4 T. Mean diffusivities extracted from INDI were comparable with diffusion tensor imaging and the two-shot isotropic diffusion encoding in the water phantom. In ex vivo mouse brain tissues, as well as in the in vivo mouse brain, mean diffusivities extracted from conventional isotropic diffusion encoding and INDI were in excellent agreement. Simulations for signal-to-noise considerations identified the regimes in which INDI is most beneficial. The INDI method accelerates diffusion MRI acquisition to single-shot mode, which can be of great importance for mapping dynamic microstructural properties in vivo without T 2 bias. Magn Reson Med 79:2198-2204, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
Comparison of cumulant expansion and q-space imaging estimates for diffusional kurtosis in brain.
Mohanty, Vaibhav; McKinnon, Emilie T; Helpern, Joseph A; Jensen, Jens H
2018-05-01
To compare estimates for the diffusional kurtosis in brain as obtained from a cumulant expansion (CE) of the diffusion MRI (dMRI) signal and from q-space (QS) imaging. For the CE estimates of the kurtosis, the CE was truncated to quadratic order in the b-value and fit to the dMRI signal for b-values from 0 up to 2000s/mm 2 . For the QS estimates, b-values ranging from 0 up to 10,000s/mm 2 were used to determine the diffusion displacement probability density function (dPDF) via Stejskal's formula. The kurtosis was then calculated directly from the second and fourth order moments of the dPDF. These two approximations were studied for in vivo human data obtained on a 3T MRI scanner using three orthogonal diffusion encoding directions. The whole brain mean values for the CE and QS kurtosis estimates differed by 16% or less in each of the considered diffusion encoding directions, and the Pearson correlation coefficients all exceeded 0.85. Nonetheless, there were large discrepancies in many voxels, particularly those with either very high or very low kurtoses relative to the mean values. Estimates of the diffusional kurtosis in brain obtained using CE and QS approximations are strongly correlated, suggesting that they encode similar information. However, for the choice of b-values employed here, there may be substantial differences, depending on the properties of the diffusion microenvironment in each voxel. Copyright © 2018 Elsevier Inc. All rights reserved.
Single-shot ADC imaging for fMRI.
Song, Allen W; Guo, Hua; Truong, Trong-Kha
2007-02-01
It has been suggested that apparent diffusion coefficient (ADC) contrast can be sensitive to cerebral blood flow (CBF) changes during brain activation. However, current ADC imaging techniques have an inherently low temporal resolution due to the requirement of multiple acquisitions with different b-factors, as well as potential confounds from cross talk between the deoxyhemoglobin-induced background gradients and the externally applied diffusion-weighting gradients. In this report a new method is proposed and implemented that addresses these two limitations. Specifically, a single-shot pulse sequence that sequentially acquires one gradient-echo (GRE) and two diffusion-weighted spin-echo (SE) images was developed. In addition, the diffusion-weighting gradient waveform was numerically optimized to null the cross terms with the deoxyhemoglobin-induced background gradients to fully isolate the effect of diffusion weighting from that of oxygenation-level changes. The experimental results show that this new single-shot method can acquire ADC maps with sufficient signal-to-noise ratio (SNR), and establish its practical utility in functional MRI (fMRI) to complement the blood oxygenation level-dependent (BOLD) technique and provide differential sensitivity for different vasculatures to better localize neural activity originating from the small vessels. Copyright (c) 2007 Wiley-Liss, Inc.
A brain MRI atlas of the common squirrel monkey, Saimiri sciureus
NASA Astrophysics Data System (ADS)
Gao, Yurui; Schilling, Kurt G.; Khare, Shweta P.; Panda, Swetasudha; Choe, Ann S.; Stepniewska, Iwona; Li, Xia; Ding, Zhoahua; Anderson, Adam; Landman, Bennett A.
2014-03-01
The common squirrel monkey, Saimiri sciureus, is a New World monkey with functional and microstructural organization of central nervous system similar to that of humans. It is one of the most commonly used South American primates in biomedical research. Unlike its Old World macaque cousins, no digital atlases have described the organization of the squirrel monkey brain. Here, we present a multi-modal magnetic resonance imaging (MRI) atlas constructed from the brain of an adult female squirrel monkey. In vivo MRI acquisitions include high resolution T2 structural imaging and low resolution diffusion tensor imaging. Ex vivo MRI acquisitions include high resolution T2 structural imaging and high resolution diffusion tensor imaging. Cortical regions were manually annotated on the co-registered volumes based on published histological sections.
Unilateral or bilateral punctate hippocampal hyperintensities on DW-MRI: seizures, amnesia, or both?
Bocos-Portillo, Jone; Escalza-Cortina, Inés; Gómez-Beldarrain, Marian; Rodriguez-Sainz, Aida; Garcia-Monco, Juan Carlos
2018-06-02
The presence of small hippocampal hyperintense lesions on diffusion-weighted (DW) MRI can respond to different etiologies and represents a challenge where clinical judgment is imperative, since therapeutic approach may be quite different.We here report three patients with similar neuroradiological findings, i.e., hyperintense punctate hippocampal lesions on diffusion-weighted MRI sequences, yet of different origin. The first one presented with isolated amnesia (transient global amnesia), the second one with amnesia and seizures, and the third one with seizures.Thus, hippocampal punctate lesions appear after transient global amnesia, but the same pattern may be present after seizures, either focal-onset or generalized seizures. This peculiar radiological MRI pattern could indicate a pathogenic link between transient global amnesia (TGA) and seizures which should be further studied.
Wong, Alex M; Toh, Cheng-Hong; Lien, Reyin; Chao, An-Shine; Wong, Ho-Fai; Ng, Koon-Kwan
2006-11-01
Meconium pseudocyst results from a loculated inflammation occurring in response to spillage of meconium into the peritoneal cavity after a bowel perforation. Certain cystic lesions, such as abscesses and dermoid and epidermoid cysts, are known to show reduced water diffusion on DWI. MRI has recently become a valuable adjunct to ultrasonography for fetal gastrointestinal anomalies. Complementary to ultrasonography, prenatal MRI can help further characterize the lesion and can clearly demonstrate the anatomical relationship between the lesion and adjacent organs. We report a case of meconium pseudocyst that was prenatally imaged with ultrasonography and MRI, postnatally complicated by pneumoperitoneum, and proved by postnatal surgery and histopathology. We emphasize the MRI of the pseudocyst, particularly T1-weighted and diffusion-weighted imaging.
Zhang, Tong; Zhang, Feng; Meng, Yanfeng; Wang, Han; Le, Thomas; Wei, Baojie; Lee, Donghoon; Willis, Patrick; Shen, Baozhong; Yang, Xiaoming
2013-12-01
The aim of this study was to evaluate the feasibility of using diffusion-weighted MRI to monitor the early response of pancreatic cancers to radiofrequency heat (RFH)-enhanced chemotherapy. Human pancreatic carcinoma cells (PANC-1) in different groups and 24 mice with pancreatic cancer xenografts in four groups were treated with phosphate-buffered saline (PBS) as a control, RFH at 42 °C, gemcitabine and gemcitabine plus RFH at 42 °C. One day before and 1, 7 and 14 days after treatment, diffusion-weighted MRI and T2 -weighted imaging were applied to monitor the apparent diffusion coefficients (ADCs) of tumors and tumor growth. MRI findings were correlated with the results of tumor apoptosis analysis. In the in vitro experiments, the quantitative viability assay showed lower relative cell viabilities for treatment with gemcitabine plus RFH at 42 °C relative to treatment with RFH only and gemcitabine only (37 ± 5% versus 65 ± 4% and 58 ± 8%, respectively, p < 0.05). In the in vivo experiments, the combination therapy resulted in smaller relative tumor volumes than RFH only and chemotherapy only (0.82 ± 0.17 versus 2.23 ± 0.90 and 1.64 ± 0.44, respectively, p = 0.003). In vivo, 14-T MRI demonstrated a remarkable decrease in ADCs at day 1 and increased ADCs at days 7 and 14 in the combination therapy group. The apoptosis index in the combination therapy group was significantly higher than those in the chemotherapy-only, RFH-only and PBS treatment groups (37 ± 6% versus 20 ± 5%, 8 ± 2% and 3 ± 1%, respectively, p < 0.05). This study confirms that it is feasible to use MRI to monitor RFH-enhanced chemotherapy in pancreatic cancers, which may present new options for the efficient treatment of pancreatic malignancies using MRI/RFH-integrated local chemotherapy. Copyright © 2013 John Wiley & Sons, Ltd.
Microstructure Imaging of Crossing (MIX) White Matter Fibers from diffusion MRI
Farooq, Hamza; Xu, Junqian; Nam, Jung Who; Keefe, Daniel F.; Yacoub, Essa; Georgiou, Tryphon; Lenglet, Christophe
2016-01-01
Diffusion MRI (dMRI) reveals microstructural features of the brain white matter by quantifying the anisotropic diffusion of water molecules within axonal bundles. Yet, identifying features such as axonal orientation dispersion, density, diameter, etc., in complex white matter fiber configurations (e.g. crossings) has proved challenging. Besides optimized data acquisition and advanced biophysical models, computational procedures to fit such models to the data are critical. However, these procedures have been largely overlooked by the dMRI microstructure community and new, more versatile, approaches are needed to solve complex biophysical model fitting problems. Existing methods are limited to models assuming single fiber orientation, relevant to limited brain areas like the corpus callosum, or multiple orientations but without the ability to extract detailed microstructural features. Here, we introduce a new and versatile optimization technique (MIX), which enables microstructure imaging of crossing white matter fibers. We provide a MATLAB implementation of MIX, and demonstrate its applicability to general microstructure models in fiber crossings using synthetic as well as ex-vivo and in-vivo brain data. PMID:27982056
Cerebrovascular reactivity and white matter integrity.
Sam, Kevin; Peltenburg, Boris; Conklin, John; Sobczyk, Olivia; Poublanc, Julien; Crawley, Adrian P; Mandell, Daniel M; Venkatraghavan, Lakshmikumar; Duffin, James; Fisher, Joseph A; Black, Sandra E; Mikulis, David J
2016-11-29
To compare the diffusion and perfusion MRI metrics of normal-appearing white matter (NAWM) with and without impaired cerebrovascular reactivity (CVR). Seventy-five participants with moderate to severe leukoaraiosis underwent blood oxygen level-dependent CVR mapping using a 3T MRI system with precise carbon dioxide stimulus manipulation. Several MRI metrics were statistically compared between areas of NAWM with positive and negative CVR using one-way analysis of variance with Bonferroni correction for multiple comparisons. Areas of NAWM with negative CVR showed a significant reduction in fractional anisotropy by a mean (SD) of 3.7% (2.4), cerebral blood flow by 22.1% (8.2), regional cerebral blood volume by 22.2% (7.0), and a significant increase in mean diffusivity by 3.9% (3.1) and time to maximum by 10.9% (13.2) (p < 0.01), compared to areas with positive CVR. Impaired CVR is associated with subtle changes in the tissue integrity of NAWM, as evaluated using several quantitative diffusion and perfusion MRI metrics. These findings suggest that impaired CVR may contribute to the progression of white matter disease. © 2016 American Academy of Neurology.
Fetal MRI: A Technical Update with Educational Aspirations
Gholipour, Ali; Estroff, Judith A.; Barnewolt, Carol E.; Robertson, Richard L.; Grant, P. Ellen; Gagoski, Borjan; Warfield, Simon K.; Afacan, Onur; Connolly, Susan A.; Neil, Jeffrey J.; Wolfberg, Adam; Mulkern, Robert V.
2015-01-01
Fetal magnetic resonance imaging (MRI) examinations have become well-established procedures at many institutions and can serve as useful adjuncts to ultrasound (US) exams when diagnostic doubts remain after US. Due to fetal motion, however, fetal MRI exams are challenging and require the MR scanner to be used in a somewhat different mode than that employed for more routine clinical studies. Herein we review the techniques most commonly used, and those that are available, for fetal MRI with an emphasis on the physics of the techniques and how to deploy them to improve success rates for fetal MRI exams. By far the most common technique employed is single-shot T2-weighted imaging due to its excellent tissue contrast and relative immunity to fetal motion. Despite the significant challenges involved, however, many of the other techniques commonly employed in conventional neuro- and body MRI such as T1 and T2*-weighted imaging, diffusion and perfusion weighted imaging, as well as spectroscopic methods remain of interest for fetal MR applications. An effort to understand the strengths and limitations of these basic methods within the context of fetal MRI is made in order to optimize their use and facilitate implementation of technical improvements for the further development of fetal MR imaging, both in acquisition and post-processing strategies. PMID:26225129
Carlbom, Lina; Caballero-Corbalán, José; Granberg, Dan; Sörensen, Jens; Eriksson, Barbro; Ahlström, Håkan
2017-01-01
Aim We wanted to explore if whole-body magnetic resonance imaging (MRI) including diffusion-weighted (DW) and liver-specific contrast agent-enhanced imaging could be valuable in lesion detection of neuroendocrine tumors (NET). [11C]-5-Hydroxytryptophan positron emission tomography/computed tomography (5-HTP PET/CT) was used for comparison. Materials and methods Twenty-one patients with NET were investigated with whole-body MRI, including DW imaging (DWI) and contrast-enhanced imaging of the liver, and whole-body 5-HTP PET/CT. Seven additional patients underwent upper abdomen MRI including DWI, liver-specific contrast agent-enhanced imaging, and 5-HTP PET/CT. Results There was a patient-based concordance of 61% and a lesion-based concordance of 53% between the modalities. MRI showed good concordance with PET in detecting bone metastases but was less sensitive in detecting metastases in mediastinal lymph nodes. MRI detected more liver metastases than 5-HTP PET/CT. Conclusion Whole-body MRI with DWI did not detect all NET lesions found with whole-body 5-HTP PET/CT. Our findings indicate that MRI of the liver including liver-specific contrast agent-enhanced imaging and DWI could be a useful complement to whole-body 5-HTP PET/CT. PMID:27894208
Rosenbaum, Daniel G; Askin, Gulce; Beneck, Debra M; Kovanlikaya, Arzu
2017-10-01
The role of magnetic resonance imaging (MRI) in pediatric appendicitis is increasing; MRI findings predictive of appendiceal perforation have not been specifically evaluated. To assess the performance of MRI in differentiating perforated from non-perforated appendicitis. A retrospective review of pediatric patients undergoing contrast-enhanced MRI and subsequent appendectomy was performed, with surgicopathological confirmation of perforation. Appendiceal diameter and the following 10 MRI findings were assessed: appendiceal restricted diffusion, wall defect, appendicolith, periappendiceal free fluid, remote free fluid, restricted diffusion within free fluid, abscess, peritoneal enhancement, ileocecal wall thickening and ileus. Two-sample t-test and chi-square tests were used to analyze continuous and discrete data, respectively. Sensitivity and specificity for individual MRI findings were calculated and optimal thresholds for measures of accuracy were selected. Seventy-seven patients (mean age: 12.2 years) with appendicitis were included, of whom 22 had perforation. The perforated group had a larger mean appendiceal diameter and mean number of MRI findings than the non-perforated group (12.3 mm vs. 8.6 mm; 5.0 vs. 2.0, respectively). Abscess, wall defect and restricted diffusion within free fluid had the greatest specificity for perforation (1.00, 1.00 and 0.96, respectively) but low sensitivity (0.36, 0.25 and 0.32, respectively). The receiver operator characteristic curve for total number of MRI findings had an area under the curve of 0.92, with an optimal threshold of 3.5. A threshold of any 4 findings had the best ability to accurately discriminate between perforated and non-perforated cases, with a sensitivity of 82% and specificity of 85%. Contrast-enhanced MRI can differentiate perforated from non-perforated appendicitis. The presence of multiple findings increases diagnostic accuracy, with a threshold of any four findings optimally discriminating between perforated and non-perforated cases. These results may help guide management decisions as MRI assumes a greater role in the work-up of pediatric appendicitis.
b matrix errors in echo planar diffusion tensor imaging
Boujraf, Saïd; Luypaert, Robert; Osteaux, Michel
2001-01-01
Diffusion‐weighted magnetic resonance imaging (DW‐MRI) is a recognized tool for early detection of infarction of the human brain. DW‐MRI uses the signal loss associated with the random thermal motion of water molecules in the presence of magnetic field gradients to derive parameters that reflect the translational mobility of the water molecules in tissues. If diffusion‐weighted images with different values of b matrix are acquired during one individual investigation, it is possible to calculate apparent diffusion coefficient maps that are the elements of the diffusion tensor. The diffusion tensor elements represent the apparent diffusion coefficient of protons of water molecules in each pixel in the corresponding sample. The relation between signal intensity in the diffusion‐weighted images, diffusion tensor, and b matrix is derived from the Bloch equations. Our goal is to establish the magnitude of the error made in the calculation of the elements of the diffusion tensor when the imaging gradients are ignored. PACS number(s): 87.57. –s, 87.61.–c PMID:11602015
Ponrartana, Skorn; Andrade, Kristine E; Wren, Tishya A L; Ramos-Platt, Leigh; Hu, Houchun H; Bluml, Stefan; Gilsanz, Vicente
2014-06-01
The purpose of this study was to assess the repeatability of water-fat MRI and diffusion-tensor imaging (DTI) as quantitative biomarkers of pediatric lower extremity skeletal muscle. MRI at 3 T of a randomly selected thigh and lower leg of seven healthy children was studied using water-fat separation and DTI techniques. Muscle-fat fraction, apparent diffusion coefficient (ADC), and fractional anisotropy (FA) values were calculated. Test-retest and interrater repeatability were assessed by calculating the Pearson correlation coefficient, intraclass correlation coefficient, and Bland-Altman analysis. Bland-Altman plots show that the mean difference between test-retest and interrater measurements of muscle-fat fraction, ADC, and FA was near 0. The correlation coefficients and intraclass correlation coefficients were all between 0.88 and 0.99 (p < 0.05), suggesting excellent reliability of the measurements. Muscle-fat fraction measurements from water-fat MRI exhibited the highest intraclass correlation coefficient. Interrater agreement was consistently better than test-retest comparisons. Water-fat MRI and DTI measurements in lower extremity skeletal muscles are objective repeatable biomarkers in children. This knowledge should aid in the understanding of the number of participants needed in clinical trials when using these determinations as an outcome measure to noninvasively monitor neuromuscular disease.
Effects of cannabis on cognition in patients with MS: a psychometric and MRI study.
Pavisian, Bennis; MacIntosh, Bradley J; Szilagyi, Greg; Staines, Richard W; O'Connor, Paul; Feinstein, Anthony
2014-05-27
To determine functional and structural neuroimaging correlates of cognitive dysfunction associated with cannabis use in multiple sclerosis (MS). In a cross-sectional study, 20 subjects with MS who smoked cannabis and 19 noncannabis users with MS, matched on demographic and neurologic variables, underwent fMRI while completing a test of working memory, the N-Back. Resting-state fMRI and structural MRI data (lesion and normal-appearing brain tissue volumes, diffusion tensor imaging metrics) were also collected. Neuropsychological data pertaining to verbal (Selective Reminding Test Revised) and visual (10/36 Spatial Recall Test) memory, information processing speed (Paced Auditory Serial Addition Test [2- and 3-second versions] and Symbol Digit Modalities Test), and attention (Word List Generation) were obtained. The cannabis group performed more poorly on the more demanding of the Paced Auditory Serial Addition Test tasks (i.e., 2-second version) (p < 0.02) and the 10/36 Spatial Recall Test (p < 0.03). Cannabis users had more diffuse cerebral activation across all N-Back trials and made more errors on the 2-Back task (p < 0.006), during which they displayed increased activation relative to nonusers in parietal (p < 0.007) and anterior cingulate (p < 0.001) regions implicated in working memory. No group differences in resting-state networks or structural MRI variables were found. Patients with MS who smoke cannabis are more cognitively impaired than nonusers. Cannabis further compromises cerebral compensatory mechanisms, already faulty in MS. These imaging data boost the construct validity of the neuropsychological findings and act as a cautionary note to cannabis users and prescribers. © 2014 American Academy of Neurology.
Bucy, Daniel S; Brown, Mark S; Bielefeldt-Ohmann, Helle; Thompson, Jesse; Bachand, Annette M; Morges, Michelle; Elder, John H; Vandewoude, Sue; Kraft, Susan L
2011-08-01
HIV infection results in a highly prevalent syndrome of cognitive and motor disorders designated as HIV-associated dementia (HAD). Neurologic dysfunction resembling HAD has been documented in cats infected with strain PPR of the feline immunodeficiency virus (FIV), whereas another highly pathogenic strain (C36) has not been known to cause neurologic signs. Animals experimentally infected with equivalent doses of FIV-C36 or FIV-PPR, and uninfected controls were evaluated by magnetic resonance diffusion-weighted imaging (DW-MRI) and spectroscopy (MRS) at 17.5-18 weeks post-infection, as part of a study of viral clade pathogenesis in FIV-infected cats. The goals of the MR imaging portion of the project were to determine whether this methodology was capable of detecting early neuropathophysiology in the absence of outward manifestation of neurological signs and to compare the MR imaging results for the two viral strains expected to have differing degrees of neurologic effects. We hypothesized that there would be increased diffusion, evidenced by the apparent diffusion coefficient as measured by DW-MRI, and altered metabolite ratios measured by MRS, in the brains of FIV-PPR-infected cats relative to C36-infected cats and uninfected controls. Increased apparent diffusion coefficients were seen in the white matter, gray matter, and basal ganglia of both the PPR and C36-infected (asymptomatic) cats. Thalamic MRS metabolite ratios did not differ between groups. The equivalently increased diffusion by DW-MRI suggests similar indirect neurotoxicity mechanisms for the two viral genotypes. DW-MRI is a sensitive tool to detect neuropathophysiological changes in vivo that could be useful during longitudinal studies of FIV.
Rodriguez Gutierrez, Daniel; Manita, Muftah; Jaspan, Tim; Dineen, Robert A.; Grundy, Richard G.; Auer, Dorothee P.
2013-01-01
Background Assessment of treatment response by measuring tumor size is known to be a late and potentially confounded response index. Serial diffusion MRI has shown potential for allowing earlier and possibly more reliable response assessment in adult patients, with limited experience in clinical settings and in pediatric brain cancer. We present a retrospective study of clinical MRI data in children with high-grade brain tumors to assess and compare the values of several diffusion change metrics to predict treatment response. Methods Eighteen patients (age range, 1.9–20.6 years) with high-grade brain tumors and serial diffusion MRI (pre- and posttreatment interval range, 1–16 weeks posttreatment) were identified after obtaining parental consent. The following diffusion change metrics were compared with the clinical response status assessed at 6 months: (1) regional change in absolute and normalized apparent diffusivity coefficient (ADC), (2) voxel-based fractional volume of increased (fiADC) and decreased ADC (fdADC), and (3) a new metric based on the slope of the first principal component of functional diffusion maps (fDM). Results Responders (n = 12) differed significantly from nonresponders (n = 6) in all 3 diffusional change metrics demonstrating higher regional ADC increase, larger fiADC, and steeper slopes (P < .05). The slope method allowed the best response prediction (P < .01, η2 = 0.78) with a classification accuracy of 83% for a slope of 58° using receiver operating characteristic (ROC) analysis. Conclusions We demonstrate that diffusion change metrics are suitable response predictors for high-grade pediatric tumors, even in the presence of variable clinical diffusion imaging protocols. PMID:23585630
Sauer, Alexander; Li, Mengxia; Holl-Wieden, Annette; Pabst, Thomas; Neubauer, Henning
2017-10-12
Diffusion-weighted MRI has been proposed as a new technique for imaging synovitis without intravenous contrast application. We investigated diagnostic utility of multi-shot readout-segmented diffusion-weighted MRI (multi-shot DWI) for synovial imaging of the knee joint in patients with juvenile idiopathic arthritis (JIA). Thirty-two consecutive patients with confirmed or suspected JIA (21 girls, median age 13 years) underwent routine 1.5 T MRI with contrast-enhanced T1w imaging (contrast-enhanced MRI) and with multi-shot DWI (RESOLVE, b-values 0-50 and 800 s/mm 2 ). Contrast-enhanced MRI, representing the diagnostic standard, and diffusion-weighted images at b = 800 s/mm 2 were separately rated by three independent blinded readers at different levels of expertise for the presence and the degree of synovitis on a modified 5-item Likert scale along with the level of subjective diagnostic confidence. Fourteen (44%) patients had active synovitis and joint effusion, nine (28%) patients showed mild synovial enhancement not qualifying for arthritis and another nine (28%) patients had no synovial signal alterations on contrast-enhanced imaging. Ratings by the 1st reader on contrast-enhanced MRI and on DWI showed substantial agreement (κ = 0.74). Inter-observer-agreement was high for diagnosing, or ruling out, active arthritis of the knee joint on contrast-enhanced MRI and on DWI, showing full agreement between 1st and 2nd reader and disagreement in one case (3%) between 1st and 3rd reader. In contrast, ratings in cases of absent vs. little synovial inflammation were markedly inconsistent on DWI. Diagnostic confidence was lower on DWI, compared to contrast-enhanced imaging. Multi-shot DWI of the knee joint is feasible in routine imaging and reliably diagnoses, or rules out, active arthritis of the knee joint in paediatric patients without the need of gadolinium-based i.v. contrast injection. Possibly due to "T2w shine-through" artifacts, DWI does not reliably differentiate non-inflamed joints from knee joints with mild synovial irritation.
Duning, Thomas; Kellinghaus, Christoph; Mohammadi, Siawoosh; Schiffbauer, Hagen; Keller, Simon; Ringelstein, E Bernd; Knecht, Stefan; Deppe, Michael
2010-02-01
Conventional structural MRI fails to identify a cerebral lesion in 25% of patients with cryptogenic partial epilepsy (CPE). Diffusion tensor imaging is an MRI technique sensitive to microstructural abnormalities of cerebral white matter (WM) by quantification of fractional anisotropy (FA). The objectives of the present study were to identify focal FA abnormalities in patients with CPE who were deemed MRI negative during routine presurgical evaluation. Diffusion tensor imaging at 3 T was performed in 12 patients with CPE and normal conventional MRI and in 67 age matched healthy volunteers. WM integrity was compared between groups on the basis of automated voxel-wise statistics of FA maps using an analysis of covariance. Volumetric measurements from high resolution T1-weighted images were also performed. Significant FA reductions in WM regions encompassing diffuse areas of the brain were observed when all patients as a group were compared with controls. On an individual basis, voxel based analyses revealed widespread symmetrical FA reduction in CPE patients. Furthermore, asymmetrical temporal lobe FA reduction was consistently ipsilateral to the electroclinical focus. No significant correlations were found between FA alterations and clinical data. There were no differences in brain volumes of CPE patients compared with controls. Despite normal conventional MRI, WM integrity abnormalities in CPE patients extend far beyond the epileptogenic zone. Given that unilateral temporal lobe FA abnormalities were consistently observed ipsilateral to the seizure focus, analysis of temporal FA may provide an informative in vivo investigation into the localisation of the epileptogenic zone in MRI negative patients.
Neural and Behavioral Sequelae of Blast-Related Traumatic Brain Injury
2012-09-01
fMRI, DTI , cognition 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON USAMRMC a...techniques [task-activated functional MRI (fMRI) and diffusion tensor imaging ( DTI )] to gain a comprehensive understanding of the neural changes...orthopedic injuries. We accomplished this goal by conducting advanced neuroimaging (task-activated fMRI and DTI fiber tracking) and neurobehavioral
Razek, A A K A; Elkhamary, S
2011-01-01
We review the role of MRI in retinoblastoma and simulating lesions. Retinoblastoma is the most common paediatric intra-ocular tumour. It may be endophytic, exophytic or a diffuse infiltrating tumour. MRI can detect intra-ocular, extra-ocular and intracranial extension of the tumour. MRI is essential for monitoring patients after treatment and detection of associated second malignancies. It helps to differentiating the tumour from simulating lesions with leukocoria. PMID:21849363
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.
Magnetic resonance imaging in active surveillance—a modern approach
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
Hompland, Tord; Ellingsen, Christine; Galappathi, Kanthi; Rofstad, Einar K
2014-01-01
Abstract Background. A high fraction of stroma in malignant tissues is associated with tumor progression, metastasis, and poor prognosis. Possible correlations between the stromal and physiologic microenvironments of tumors and the potential of dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) magnetic resonance imaging (MRI) in quantification of the stromal microenvironment were investigated in this study. Material and methods. CK-160 cervical carcinoma xenografts were used as preclinical tumor model. A total of 43 tumors were included in the study, and of these tumors, 17 were used to search for correlations between the stromal and physiologic microenvironments, 11 were subjected to DCE-MRI, and 15 were subjected to DW-MRI. DCE-MRI and DW-MRI were carried out at 1.5 T with a clinical MR scanner and a slotted tube resonator transceiver coil constructed for mice. Fraction of connective tissue (CTFCol) and fraction of hypoxic tissue (HFPim) were determined by immunohistochemistry. A Millar SPC 320 catheter was used to measure tumor interstitial fluid pressure (IFP). Results. CTFCol showed a positive correlation to IFP and an inverse correlation to HFPim. The apparent diffusion coefficient assessed by DW-MRI was inversely correlated to CTFCol, whereas no correlation was found between DCE-MRI-derived parameters and CTFCol. Conclusion. DW-MRI is a potentially useful method for characterizing the stromal microenvironment of tumors.
Uğurbil, Kamil; Xu, Junqian; Auerbach, Edward J.; Moeller, Steen; Vu, An; Duarte-Carvajalino, Julio M.; Lenglet, Christophe; Wu, Xiaoping; Schmitter, Sebastian; Van de Moortele, Pierre Francois; Strupp, John; Sapiro, Guillermo; De Martino, Federico; Wang, Dingxin; Harel, Noam; Garwood, Michael; Chen, Liyong; Feinberg, David A.; Smith, Stephen M.; Miller, Karla L.; Sotiropoulos, Stamatios N; Jbabdi, Saad; Andersson, Jesper L; Behrens, Timothy EJ; Glasser, Matthew F.; Van Essen, David; Yacoub, Essa
2013-01-01
The human connectome project (HCP) relies primarily on three complementary magnetic resonance (MR) methods. These are: 1) resting state functional MR imaging (rfMRI) which uses correlations in the temporal fluctuations in an fMRI time series to deduce ‘functional connectivity’; 2) diffusion imaging (dMRI), which provides the input for tractography algorithms used for the reconstruction of the complex axonal fiber architecture; and 3) task based fMRI (tfMRI), which is employed to identify functional parcellation in the human brain in order to assist analyses of data obtained with the first two methods. We describe technical improvements and optimization of these methods as well as instrumental choices that impact speed of acquisition of fMRI and dMRI images at 3 Tesla, leading to whole brain coverage with 2 mm isotropic resolution in 0.7 second for fMRI, and 1.25 mm isotropic resolution dMRI data for tractography analysis with three-fold reduction in total data acquisition time. Ongoing technical developments and optimization for acquisition of similar data at 7 Tesla magnetic field are also presented, targeting higher resolution, specificity of functional imaging signals, mitigation of the inhomogeneous radio frequency (RF) fields and power deposition. Results demonstrate that overall, these approaches represent a significant advance in MR imaging of the human brain to investigate brain function and structure. PMID:23702417
NASA Astrophysics Data System (ADS)
Archip, Neculai; Fedorov, Andriy; Lloyd, Bryn; Chrisochoides, Nikos; Golby, Alexandra; Black, Peter M.; Warfield, Simon K.
2006-03-01
A major challenge in neurosurgery oncology is to achieve maximal tumor removal while avoiding postoperative neurological deficits. Therefore, estimation of the brain deformation during the image guided tumor resection process is necessary. While anatomic MRI is highly sensitive for intracranial pathology, its specificity is limited. Different pathologies may have a very similar appearance on anatomic MRI. Moreover, since fMRI and diffusion tensor imaging are not currently available during the surgery, non-rigid registration of preoperative MR with intra-operative MR is necessary. This article presents a translational research effort that aims to integrate a number of state-of-the-art technologies for MRI-guided neurosurgery at the Brigham and Women's Hospital (BWH). Our ultimate goal is to routinely provide the neurosurgeons with accurate information about brain deformation during the surgery. The current system is tested during the weekly neurosurgeries in the open magnet at the BWH. The preoperative data is processed, prior to the surgery, while both rigid and non-rigid registration algorithms are run in the vicinity of the operating room. The system is tested on 9 image datasets from 3 neurosurgery cases. A method based on edge detection is used to quantitatively validate the results. 95% Hausdorff distance between points of the edges is used to estimate the accuracy of the registration. Overall, the minimum error is 1.4 mm, the mean error 2.23 mm, and the maximum error 3.1 mm. The mean ratio between brain deformation estimation and rigid alignment is 2.07. It demonstrates that our results can be 2.07 times more precise then the current technology. The major contribution of the presented work is the rigid and non-rigid alignment of the pre-operative fMRI with intra-operative 0.5T MRI achieved during the neurosurgery.
XQ-NLM: Denoising Diffusion MRI Data via x-q Space Non-Local Patch Matching.
Chen, Geng; Wu, Yafeng; Shen, Dinggang; Yap, Pew-Thian
2016-10-01
Noise is a major issue influencing quantitative analysis in diffusion MRI. The effects of noise can be reduced by repeated acquisitions, but this leads to long acquisition times that can be unrealistic in clinical settings. For this reason, post-acquisition denoising methods have been widely used to improve SNR. Among existing methods, non-local means (NLM) has been shown to produce good image quality with edge preservation. However, currently the application of NLM to diffusion MRI has been mostly focused on the spatial space (i.e., the x -space), despite the fact that diffusion data live in a combined space consisting of the x -space and the q -space (i.e., the space of wavevectors). In this paper, we propose to extend NLM to both x -space and q -space. We show how patch-matching, as required in NLM, can be performed concurrently in x-q space with the help of azimuthal equidistant projection and rotation invariant features. Extensive experiments on both synthetic and real data confirm that the proposed x-q space NLM (XQ-NLM) outperforms the classic NLM.
NASA Astrophysics Data System (ADS)
Leroy, Henri-Arthur; Vermandel, Maximilien; Tétard, Marie-Charlotte; Lejeune, Jean-Paul; Mordon, Serge; Reyns, Nicolas
2015-03-01
Background Glioblastoma is a high-grade cerebral tumor with local recurrence and poor outcome. Photodynamic therapy (PDT) is a local treatment based on the light activation of a photosensitizer (PS) in the presence of oxygen to form cytotoxic species. Fractionation of light delivery may enhance treatment efficiency by restoring tissue oxygenation. Objectives To evaluate the efficiency of light fractionation using MRI imaging, including diffusion and perfusion, compared to histological data. Materials and Methods Thirty-nine "Nude" rats were grafted with human U87 cells into the right putamen. After PS precursor intake (5-ALA), an optic fiber was introduced into the tumor. The rats were randomized in three groups: without illumination, with monofractionated illumination and the third one with multifractionated light. Treatment effects were assessed with early MRI including diffusion and perfusion sequences. The animals were eventually sacrificed to perform brain histology. Results On MRI, we observed elevated diffusion values in the center of the tumor among treated animals, especially in multifractionated group. Perfusion decreased around the treatment site, all the more in the multifractionated group. Histology confirmed our MRI findings, with a more extensive necrosis and associated with a rarified angiogenic network in the treatment area, after multifractionated PDT. However, we observed more surrounding edema and neovascularization in the peripheral ring after multifractionated PDT. Conclusion Fractionated interstitial PDT induced specific tumoral lesions. The multifractionated scheme was more efficient, inducing increased tumoral necrosis, but it also caused significant peripheral edema and neovascularization. Diffusion and perfusion MRI imaging were able to predict the histological lesions.
Tao, Ran; Fletcher, P Thomas; Gerber, Samuel; Whitaker, Ross T
2009-01-01
This paper presents a method for correcting the geometric and greyscale distortions in diffusion-weighted MRI that result from inhomogeneities in the static magnetic field. These inhomogeneities may due to imperfections in the magnet or to spatial variations in the magnetic susceptibility of the object being imaged--so called susceptibility artifacts. Echo-planar imaging (EPI), used in virtually all diffusion weighted acquisition protocols, assumes a homogeneous static field, which generally does not hold for head MRI. The resulting distortions are significant, sometimes more than ten millimeters. These artifacts impede accurate alignment of diffusion images with structural MRI, and are generally considered an obstacle to the joint analysis of connectivity and structure in head MRI. In principle, susceptibility artifacts can be corrected by acquiring (and applying) a field map. However, as shown in the literature and demonstrated in this paper, field map corrections of susceptibility artifacts are not entirely accurate and reliable, and thus field maps do not produce reliable alignment of EPIs with corresponding structural images. This paper presents a new, image-based method for correcting susceptibility artifacts. The method relies on a variational formulation of the match between an EPI baseline image and a corresponding T2-weighted structural image but also specifically accounts for the physics of susceptibility artifacts. We derive a set of partial differential equations associated with the optimization, describe the numerical methods for solving these equations, and present results that demonstrate the effectiveness of the proposed method compared with field-map correction.
Exploring the multiple-hit hypothesis of preterm white matter damage using diffusion MRI.
Barnett, Madeleine L; Tusor, Nora; Ball, Gareth; Chew, Andrew; Falconer, Shona; Aljabar, Paul; Kimpton, Jessica A; Kennea, Nigel; Rutherford, Mary; David Edwards, A; Counsell, Serena J
2018-01-01
Preterm infants are at high risk of diffuse white matter injury and adverse neurodevelopmental outcome. The multiple hit hypothesis suggests that the risk of white matter injury increases with cumulative exposure to multiple perinatal risk factors. Our aim was to test this hypothesis in a large cohort of preterm infants using diffusion weighted magnetic resonance imaging (dMRI). We studied 491 infants (52% male) without focal destructive brain lesions born at < 34 weeks, who underwent structural and dMRI at a specialist Neonatal Imaging Centre. The median (range) gestational age (GA) at birth was 30 + 1 (23 + 2 -33 + 5 ) weeks and median postmenstrual age at scan was 42 + 1 (38-45) weeks. dMRI data were analyzed using tract based spatial statistics and the relationship between dMRI measures in white matter and individual perinatal risk factors was assessed. We tested the hypothesis that increased exposure to perinatal risk factors was associated with lower fractional anisotropy (FA), and higher radial, axial and mean diffusivity (RD, AD, MD) in white matter. Neurodevelopmental performance was investigated using the Bayley Scales of Infant and Toddler Development, Third Edition (BSITD-III) in a subset of 381 infants at 20 months corrected age. We tested the hypothesis that lower FA and higher RD, AD and MD in white matter were associated with poorer neurodevelopmental performance. Identified risk factors for diffuse white matter injury were lower GA at birth, fetal growth restriction, increased number of days requiring ventilation and parenteral nutrition, necrotizing enterocolitis and male sex. Clinical chorioamnionitis and patent ductus arteriosus were not associated with white matter injury. Multivariate analysis demonstrated that fetal growth restriction, increased number of days requiring ventilation and parenteral nutrition were independently associated with lower FA values. Exposure to cumulative risk factors was associated with reduced white matter FA and FA values at term equivalent age were associated with subsequent neurodevelopmental performance. This study suggests multiple perinatal risk factors have an independent association with diffuse white matter injury at term equivalent age and exposure to multiple perinatal risk factors exacerbates dMRI defined, clinically significant white matter injury. Our findings support the multiple hit hypothesis for preterm white matter injury.
The physical and biological basis of quantitative parameters derived from diffusion MRI
2012-01-01
Diffusion magnetic resonance imaging is a quantitative imaging technique that measures the underlying molecular diffusion of protons. Diffusion-weighted imaging (DWI) quantifies the apparent diffusion coefficient (ADC) which was first used to detect early ischemic stroke. However this does not take account of the directional dependence of diffusion seen in biological systems (anisotropy). Diffusion tensor imaging (DTI) provides a mathematical model of diffusion anisotropy and is widely used. Parameters, including fractional anisotropy (FA), mean diffusivity (MD), parallel and perpendicular diffusivity can be derived to provide sensitive, but non-specific, measures of altered tissue structure. They are typically assessed in clinical studies by voxel-based or region-of-interest based analyses. The increasing recognition of the limitations of the diffusion tensor model has led to more complex multi-compartment models such as CHARMED, AxCaliber or NODDI being developed to estimate microstructural parameters including axonal diameter, axonal density and fiber orientations. However these are not yet in routine clinical use due to lengthy acquisition times. In this review, I discuss how molecular diffusion may be measured using diffusion MRI, the biological and physical bases for the parameters derived from DWI and DTI, how these are used in clinical studies and the prospect of more complex tissue models providing helpful micro-structural information. PMID:23289085
Epilepsy Surgery for Individuals with TSC
... tomography (PET), single-photon emission tomography (SPECT), magnetoencephalography (MEG), Diffusion Tensor Imaging (DTI), and functional MRI (fMRI). ... sclerosis: a comparison of high resolution EEG and MEG. Epilepsia 47:108-114 Jansen FE, Huffelen ACV, ...
Stieltjes, Bram; Weikert, Thomas; Gatidis, Sergios; Wiese, Mark; Wild, Damian; Lardinois, Didier
2017-01-01
The minimum apparent diffusion coefficient (ADCmin) derived from diffusion-weighted MRI (DW-MRI) and the maximum standardized uptake value (SUVmax) of FDG-PET are markers of aggressiveness in lung cancer. The numeric correlation of the two parameters has been extensively studied, but their spatial interplay is not well understood. After FDG-PET and DW-MRI coregistration, values and location of ADCmin- and SUVmax-voxels were analyzed. The upper limit of the 95% confidence interval for registration accuracy of sequential PET/MRI was 12 mm, and the mean distance (D) between ADCmin- and SUVmax-voxels was 14.0 mm (average of two readers). Spatial mismatch (D > 12 mm) between ADCmin and SUVmax was found in 9/25 patients. A considerable number of mismatch cases (65%) was also seen in a control group that underwent simultaneous PET/MRI. In the entire patient cohort, no statistically significant correlation between SUVmax and ADCmin was seen, while a moderate negative linear relationship (r = −0.5) between SUVmax and ADCmin was observed in tumors with a spatial match (D ≤ 12 mm). In conclusion, spatial mismatch between ADCmin and SUVmax is found in a considerable percentage of patients. The spatial connection of the two parameters SUVmax and ADCmin has a crucial influence on their numeric correlation. PMID:29391862
Song, Y; Yoon, Y C; Chong, Y; Seo, S W; Choi, Y-L; Sohn, I; Kim, M-J
2017-08-01
To compare the abilities of conventional magnetic resonance imaging (MRI) and apparent diffusion coefficient (ADC) in differentiating between benign and malignant soft-tissue tumours (STT). A total of 123 patients with STT who underwent 3 T MRI, including diffusion-weighted imaging (DWI), were retrospectively analysed using variate conventional MRI parameters, ADC mean and ADC min . For the all-STT group, the correlation between the malignant STT conventional MRI parameters, except deep compartment involvement, compared to those of benign STT were statistically significant with univariate analysis. Maximum diameter of the tumour (p=0.001; odds ratio [OR], 8.97) and ADC mean (p=0.020; OR, 4.30) were independent factors with multivariate analysis. For the non-myxoid non-haemosiderin STT group, signal heterogeneity on axial T1-weighted imaging (T1WI; p=0.017), ADC mean , and ADC min (p=0.001, p=0.001), showed significant differences with univariate analysis between malignancy and benignity. Signal heterogeneity in axial T1WI (p=0.025; OR, 12.64) and ADC mean (p=0.004; OR, 33.15) were independent factors with multivariate analysis. ADC values as well as conventional MRI parameters were useful in differentiating between benign and malignant STT. The ADC mean was the most powerful diagnostic parameter in non-myxoid non-haemosiderin STT. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
Edlow, Brian L; Giacino, Joseph T; Hirschberg, Ronald E; Gerrard, Jason; Wu, Ona; Hochberg, Leigh R
2013-12-01
Prognostication in the early stage of traumatic coma is a common challenge in the neuro-intensive care unit. We report the unexpected recovery of functional milestones (i.e., consciousness, communication, and community reintegration) in a 19-year-old man who sustained a severe traumatic brain injury. The early magnetic resonance imaging (MRI) findings, at the time, suggested a poor prognosis. During the first year of the patient's recovery, MRI with diffusion tensor imaging and T2*-weighted imaging was performed on day 8 (coma), day 44 (minimally conscious state), day 198 (post-traumatic confusional state), and day 366 (community reintegration). Mean apparent diffusion coefficient (ADC) and fractional anisotropy values in the corpus callosum, cerebral hemispheric white matter, and thalamus were compared with clinical assessments using the Disability Rating Scale (DRS). Extensive diffusion restriction in the corpus callosum and bihemispheric white matter was observed on day 8, with ADC values in a range typically associated with neurotoxic injury (230-400 × 10(-6 )mm(2)/s). T2*-weighted MRI revealed widespread hemorrhagic axonal injury in the cerebral hemispheres, corpus callosum, and brainstem. Despite the presence of severe axonal injury on early MRI, the patient regained the ability to communicate and perform activities of daily living independently at 1 year post-injury (DRS = 8). MRI data should be interpreted with caution when prognosticating for patients in traumatic coma. Recovery of consciousness and community reintegration are possible even when extensive traumatic axonal injury is demonstrated by early MRI.
Fink, Ericka L; Panigrahy, A; Clark, R S B; Fitz, C R; Landsittel, D; Kochanek, P M; Zuccoli, G
2013-08-01
To assess regional brain injury on magnetic resonance imaging (MRI) after pediatric cardiac arrest (CA) and to associate regional injury with patient outcome and effects of hypothermia therapy for neuroprotection. We performed a retrospective chart review with prospective imaging analysis. Children between 1 week and 17 years of age who had a brain MRI in the first 2 weeks after CA without other acute brain injury between 2002 and 2008 were included. Brain MRI (1.5 T General Electric, Milwaukee, WI, USA) images were analyzed by 2 blinded neuroradiologists with adjudication; images were visually graded. Brain lobes, basal ganglia, thalamus, brain stem, and cerebellum were analyzed using T1, T2, and diffusion-weighted images (DWI). We examined 28 subjects with median age 1.9 years (IQR 0.4-13.0) and 19 (68 %) males. Increased intensity on T2 in the basal ganglia and restricted diffusion in the brain lobes were associated with unfavorable outcome (all P < 0.05). Therapeutic hypothermia had no effect on regional brain injury. Repeat brain MRI was infrequently performed but demonstrated evolution of lesions. Children with lesions in the basal ganglia on conventional MRI and brain lobes on DWI within the first 2 weeks after CA represent a group with increased risk of poor outcome. These findings may be important for developing neuroprotective strategies based on regional brain injury and for evaluating response to therapy in interventional clinical trials.
Sauter, Alexander W; Stieltjes, Bram; Weikert, Thomas; Gatidis, Sergios; Wiese, Mark; Klarhöfer, Markus; Wild, Damian; Lardinois, Didier; Bremerich, Jens; Sommer, Gregor
2017-01-01
The minimum apparent diffusion coefficient (ADC min ) derived from diffusion-weighted MRI (DW-MRI) and the maximum standardized uptake value (SUV max ) of FDG-PET are markers of aggressiveness in lung cancer. The numeric correlation of the two parameters has been extensively studied, but their spatial interplay is not well understood. After FDG-PET and DW-MRI coregistration, values and location of ADC min - and SUV max -voxels were analyzed. The upper limit of the 95% confidence interval for registration accuracy of sequential PET/MRI was 12 mm, and the mean distance ( D ) between ADC min - and SUV max -voxels was 14.0 mm (average of two readers). Spatial mismatch ( D > 12 mm) between ADC min and SUV max was found in 9/25 patients. A considerable number of mismatch cases (65%) was also seen in a control group that underwent simultaneous PET/MRI. In the entire patient cohort, no statistically significant correlation between SUV max and ADC min was seen, while a moderate negative linear relationship ( r = -0.5) between SUV max and ADC min was observed in tumors with a spatial match ( D ≤ 12 mm). In conclusion, spatial mismatch between ADC min and SUV max is found in a considerable percentage of patients. The spatial connection of the two parameters SUV max and ADC min has a crucial influence on their numeric correlation.
Schilling, Kurt; Gao, Yurui; Stepniewska, Iwona; Choe, Ann S; Landman, Bennett A; Anderson, Adam W
2016-01-01
Purpose Animal models are needed to better understand the relationship between diffusion MRI (dMRI) and the underlying tissue microstructure. One promising model for validation studies is the common squirrel monkey, Saimiri sciureus. This study aims to determine (1) the reproducibility of in vivo diffusion measures both within and between subjects; (2) the agreement between in vivo and ex vivo data acquired from the same specimen and (3) normal diffusion values and their variation across brain regions. Methods Data were acquired from three healthy squirrel monkeys, each imaged twice in vivo and once ex vivo. Reproducibility of fractional anisotropy (FA), mean diffusivity (MD), and principal eigenvector (PEV) was assessed, and normal values were determined both in vivo and ex vivo. Results The calculated coefficients of variation (CVs) for both intra-subject and inter-subject MD were below 10% (low variability) while FA had a wider range of CVs, 2–14% intra-subject (moderate variability), and 3–31% inter-subject (high variability). MD in ex vivo tissue was lower than in vivo (30%–50% decrease), while FA values increased in all regions (30–39% increase). The mode of angular differences between in vivo and ex vivo PEVs was 12 degrees. Conclusion This study characterizes the diffusion properties of the squirrel monkey brain and serves as the groundwork for using the squirrel monkey, both in vivo and ex vivo, as a model for diffusion MRI studies. PMID:27587226
Parsian, Sana; Giannakopoulos, Nadia V.; Rahbar, Habib; Rendi, Mara H.; Chai, Xiaoyu
2016-01-01
OBJECTIVE To determine the underlying histopathologic features influencing apparent diffusion coefficient (ADC) values of breast fibroadenomas. MATERIALS AND METHODS Biopsy proven fibroadenomas (n=26) initially identified as suspicious on breast MRI were retrospectively evaluated. Histopathological assessments of lesion cellularity and stromal type were compared with ADC measures on diffusion-weighted MRI. RESULTS Presence of epithelial hyperplasia (increased cellularity) and dense collagenous stroma were both significantly associated with lower lesion ADC values (p=0.02 and 0.004, respectively. CONCLUSION Variations in epithelial cellularity and stromal type influence breast lesion ADC values and may explain the wide range of ADC measures observed in benign fibroadenomas. PMID:27379441
Neurocognitive Effects of Radiotherapy
2013-11-05
tensor imaging ( DTI ), perfusion and diffusion. The majority of patients have completed baseline and at least two additional time-points in regards...completed a 1 hour standard MRI as well as additional testing including diffuse tensor imaging ( DTI ), perfusion and diffusion. The majority of...including diffuse tensor imaging ( DTI ), perfusion and diffusion. The majority of patients have completed baseline and at least two additional time
The importance of correcting for signal drift in diffusion MRI.
Vos, Sjoerd B; Tax, Chantal M W; Luijten, Peter R; Ourselin, Sebastien; Leemans, Alexander; Froeling, Martijn
2017-01-01
To investigate previously unreported effects of signal drift as a result of temporal scanner instability on diffusion MRI data analysis and to propose a method to correct this signal drift. We investigated the signal magnitude of non-diffusion-weighted EPI volumes in a series of diffusion-weighted imaging experiments to determine whether signal magnitude changes over time. Different scan protocols and scanners from multiple vendors were used to verify this on phantom data, and the effects on diffusion kurtosis tensor estimation in phantom and in vivo data were quantified. Scalar metrics (eigenvalues, fractional anisotropy, mean diffusivity, mean kurtosis) and directional information (first eigenvectors and tractography) were investigated. Signal drift, a global signal decrease with subsequently acquired images in the scan, was observed in phantom data on all three scanners, with varying magnitudes up to 5% in a 15-min scan. The signal drift has a noticeable effect on the estimation of diffusion parameters. All investigated quantitative parameters as well as tractography were affected by this artifactual signal decrease during the scan. By interspersing the non-diffusion-weighted images throughout the session, the signal decrease can be estimated and compensated for before data analysis; minimizing the detrimental effects on subsequent MRI analyses. Magn Reson Med 77:285-299, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
Neubauer, Henning; Pabst, Thomas; Dick, Anke; Machann, Wolfram; Evangelista, Laura; Wirth, Clemens; Köstler, Herbert; Hahn, Dietbert; Beer, Meinrad
2013-01-01
Small-bowel MRI based on contrast-enhanced T1-weighted sequences has been challenged by diffusion-weighted imaging (DWI) for detection of inflammatory bowel lesions and complications in patients with Crohn disease. To evaluate free-breathing DWI, as compared to contrast-enhanced MRI, in children, adolescents and young adults with Crohn disease. This retrospective study included 33 children and young adults with Crohn disease ages 17 ± 3 years (mean ± standard deviation) and 27 matched controls who underwent small-bowel MRI with contrast-enhanced T1-weighted sequences and DWI at 1.5 T. The detectability of Crohn manifestations was determined. Concurrent colonoscopy as reference was available in two-thirds of the children with Crohn disease. DWI and contrast-enhanced MRI correctly identified 32 and 31 patients, respectively. All 22 small-bowel lesions and all Crohn complications were detected. False-positive findings (two on DWI, one on contrast-enhanced MRI), compared to colonoscopy, were a result of large-bowel lumen collapse. Inflammatory wall thickening was comparable on DWI and contrast-enhanced MRI. DWI was superior to contrast-enhanced MRI for detection of lesions in 27% of the assessed bowel segments and equal to contrast-enhanced MRI in 71% of segments. DWI facilitates fast, accurate and comprehensive workup in Crohn disease without the need for intravenous administration of contrast medium. Contrast-enhanced MRI is superior in terms of spatial resolution and multiplanar acquisition.
Turkbey, Baris; Xu, Sheng; Kruecker, Jochen; Locklin, Julia; Pang, Yuxi; Shah, Vijay; Bernardo, Marcelino; Baccala, Angelo; Rastinehad, Ardeshir; Benjamin, Compton; Merino, Maria J; Wood, Bradford J; Choyke, Peter L; Pinto, Peter A
2011-03-29
During transrectal ultrasound (TRUS)-guided prostate biopsies, the actual location of the biopsy site is rarely documented. Here, we demonstrate the capability of TRUS-magnetic resonance imaging (MRI) image fusion to document the biopsy site and correlate biopsy results with multi-parametric MRI findings. Fifty consecutive patients (median age 61 years) with a median prostate-specific antigen (PSA) level of 5.8 ng/ml underwent 12-core TRUS-guided biopsy of the prostate. Pre-procedural T2-weighted magnetic resonance images were fused to TRUS. A disposable needle guide with miniature tracking sensors was attached to the TRUS probe to enable fusion with MRI. Real-time TRUS images during biopsy and the corresponding tracking information were recorded. Each biopsy site was superimposed onto the MRI. Each biopsy site was classified as positive or negative for cancer based on the results of each MRI sequence. Sensitivity, specificity, and receiver operating curve (ROC) area under the curve (AUC) values were calculated for multi-parametric MRI. Gleason scores for each multi-parametric MRI pattern were also evaluated. Six hundred and 5 systemic biopsy cores were analyzed in 50 patients, of whom 20 patients had 56 positive cores. MRI identified 34 of 56 positive cores. Overall, sensitivity, specificity, and ROC area values for multi-parametric MRI were 0.607, 0.727, 0.667, respectively. TRUS-MRI fusion after biopsy can be used to document the location of each biopsy site, which can then be correlated with MRI findings. Based on correlation with tracked biopsies, T2-weighted MRI and apparent diffusion coefficient maps derived from diffusion-weighted MRI are the most sensitive sequences, whereas the addition of delayed contrast enhancement MRI and three-dimensional magnetic resonance spectroscopy demonstrated higher specificity consistent with results obtained using radical prostatectomy specimens.
Yu, Xue; Lee, Elaine Yuen Phin; Lai, Vincent; Chan, Queenie
2014-07-01
To evaluate the correlation between standardized uptake value (SUV) (tissue metabolism) and apparent diffusion coefficient (ADC) (water diffusivity) in peritoneal metastases. Patients with peritoneal dissemination detected on (18)F-fluorodeoxyglucose positron emission tomography combined with computed tomography (FDG-PET/CT) were prospectively recruited for MRI examinations with informed consent and the study was approved by the local Institutional Review Board. FDG-PET/CT, diffusion-weighted imaging (DWI), MRI, and DWI/MRI images were independently reviewed by two radiologists based on visual analysis. SUVmax/SUVmean and ADCmin/ADCmean were obtained manually by drawing ROIs over the peritoneal metastases on FDG-PET/CT and DWI, respectively. Diagnostic characteristics of each technique were evaluated. Pearson's coefficient and McNemar and Kappa tests were used for statistical analysis. Eight patients were recruited for this prospective study and 34 peritoneal metastases were evaluated. ADCmean was significantly and negatively correlated with SUVmax (r = -0.528, P = 0.001) and SUVmean (r = -0.548, P = 0.001). ADCmin had similar correlation with SUVmax (r = -0.508, P = 0.002) and SUVmean (r = -0.513, P = 0.002). DWI/MRI had high diagnostic performance (accuracy = 98%) comparable to FDG-PET/CT, in peritoneal metastasis detection. Kappa values were excellent for all techniques. There was a significant inverse correlation between SUV and ADC. © 2013 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Salinas-Muciño, G.; Torres-García, E.; Hidalgo-Tobon, S.
2012-10-01
The process to produce an MR image includes nuclear alignment, RF excitation, spatial encoding, and image formation. To form an image, it is necessary to perform spatial localization of the MR signals, which is achieved using gradient coils. MRI requires the use of gradient coils that generate magnetic fields, which vary linearly with position over the imaging volume. Safety issues have been a motivation to study deeply the relation between the interaction of gradient magnetic field and the peripheral nerve stimulation. In this work is presented a numerical modeling between the concomitant magnetic fields produced by the gradient coils and the electric field induced in a cube with σ conductivity by the gradient field switching in pulse sequences as Eco planar Imaging (EPI), due to this kind of sequence is the most used in advance applications of magnetic resonance imaging as functional MRI, cardiac imaging or diffusion.
NASA Astrophysics Data System (ADS)
Ingo, Carson; Sui, Yi; Chen, Yufen; Parrish, Todd; Webb, Andrew; Ronen, Itamar
2015-03-01
In this paper, we provide a context for the modeling approaches that have been developed to describe non-Gaussian diffusion behavior, which is ubiquitous in diffusion weighted magnetic resonance imaging of water in biological tissue. Subsequently, we focus on the formalism of the continuous time random walk theory to extract properties of subdiffusion and superdiffusion through novel simplifications of the Mittag-Leffler function. For the case of time-fractional subdiffusion, we compute the kurtosis for the Mittag-Leffler function, which provides both a connection and physical context to the much-used approach of diffusional kurtosis imaging. We provide Monte Carlo simulations to illustrate the concepts of anomalous diffusion as stochastic processes of the random walk. Finally, we demonstrate the clinical utility of the Mittag-Leffler function as a model to describe tissue microstructure through estimations of subdiffusion and kurtosis with diffusion MRI measurements in the brain of a chronic ischemic stroke patient.
Stadelmann, Marc A; Maquer, Ghislain; Voumard, Benjamin; Grant, Aaron; Hackney, David B; Vermathen, Peter; Alkalay, Ron N; Zysset, Philippe K
2018-05-17
Intervertebral disc degeneration is a common disease that is often related to impaired mechanical function, herniations and chronic back pain. The degenerative process induces alterations of the disc's shape, composition and structure that can be visualized in vivo using magnetic resonance imaging (MRI). Numerical tools such as finite element analysis (FEA) have the potential to relate MRI-based information to the altered mechanical behavior of the disc. However, in terms of geometry, composition and fiber architecture, current FE models rely on observations made on healthy discs and might therefore not be well suited to study the degeneration process. To address the issue, we propose a new, more realistic FE methodology based on diffusion tensor imaging (DTI). For this study, a human disc joint was imaged in a high-field MR scanner with proton-density weighted (PD) and DTI sequences. The PD image was segmented and an anatomy-specific mesh was generated. Assuming accordance between local principal diffusion direction and local mean collagen fiber alignment, corresponding fiber angles were assigned to each element. Those element-wise fiber directions and PD intensities allowed the homogenized model to smoothly account for composition and fibrous structure of the disc. The disc's in vitro mechanical behavior was quantified under tension, compression, flexion, extension, lateral bending and rotation. The six resulting load-displacement curves could be replicated by the FE model, which supports our approach as a first proof of concept towards patient-specific disc modeling. Copyright © 2018 Elsevier Ltd. All rights reserved.
Ex vivo diffusion MRI of the human brain: Technical challenges and recent advances.
Roebroeck, Alard; Miller, Karla L; Aggarwal, Manisha
2018-06-04
This review discusses ex vivo diffusion magnetic resonance imaging (dMRI) as an important research tool for neuroanatomical investigations and the validation of in vivo dMRI techniques, with a focus on the human brain. We review the challenges posed by the properties of post-mortem tissue, and discuss state-of-the-art tissue preparation methods and recent advances in pulse sequences and acquisition techniques to tackle these. We then review recent ex vivo dMRI studies of the human brain, highlighting the validation of white matter orientation estimates and the atlasing and mapping of large subcortical structures. We also give particular emphasis to the delineation of layered gray matter structure with ex vivo dMRI, as this application illustrates the strength of its mesoscale resolution over large fields of view. We end with a discussion and outlook on future and potential directions of the field. © 2018 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.
Advanced MRI Methods for Assessment of Chronic Liver Disease
Taouli, Bachir; Ehman, Richard L.; Reeder, Scott B.
2010-01-01
MRI plays an increasingly important role for assessment of patients with chronic liver disease. MRI has numerous advantages, including lack of ionizing radiation and the possibility of performing multiparametric imaging. With recent advances in technology, advanced MRI methods such as diffusion-, perfusion-weighted MRI, MR elastography, chemical shift based fat-water separation and MR spectroscopy can now be applied to liver imaging. We will review the respective roles of these techniques for assessment of chronic liver disease. PMID:19542391
Meijer, Kim A; Muhlert, Nils; Cercignani, Mara; Sethi, Varun; Ron, Maria A; Thompson, Alan J; Miller, David H; Chard, Declan; Geurts, Jeroen Jg; Ciccarelli, Olga
2016-10-01
While our knowledge of white matter (WM) pathology underlying cognitive impairment in relapsing remitting multiple sclerosis (MS) is increasing, equivalent understanding in those with secondary progressive (SP) MS lags behind. The aim of this study is to examine whether the extent and severity of WM tract damage differ between cognitively impaired (CI) and cognitively preserved (CP) secondary progressive multiple sclerosis (SPMS) patients. Conventional magnetic resonance imaging (MRI) and diffusion MRI were acquired from 30 SPMS patients and 32 healthy controls (HC). Cognitive domains commonly affected in MS patients were assessed. Linear regression was used to predict cognition. Diffusion measures were compared between groups using tract-based spatial statistics (TBSS). A total of 12 patients were classified as CI, and processing speed was the most commonly affected domain. The final regression model including demographic variables and radial diffusivity explained the greatest variance of cognitive performance (R 2 = 0.48, p = 0.002). SPMS patients showed widespread loss of WM integrity throughout the WM skeleton when compared with HC. When compared with CP patients, CI patients showed more extensive and severe damage of several WM tracts, including the fornix, superior longitudinal fasciculus and forceps major. Loss of WM integrity assessed using TBSS helps to explain cognitive decline in SPMS patients. © The Author(s), 2016.
Andrzejewski, Piotr; Baltzer, Pascal; Polanec, Stephan H.; Sturdza, Alina; Georg, Dietmar; Helbich, Thomas H.; Karanikas, Georgios; Grimm, Christoph; Polterauer, Stephan; Poetter, Richard; Wadsak, Wolfgang; Mitterhauser, Markus; Georg, Petra
2016-01-01
Objectives To investigate fused multiparametric positron emission tomography/magnetic resonance imaging (MP PET/MRI) at 3T in patients with locally advanced cervical cancer, using high-resolution T2-weighted, contrast-enhanced MRI (CE-MRI), diffusion-weighted imaging (DWI), and the radiotracers [18F]fluorodeoxyglucose ([18F]FDG) and [18F]fluoromisonidazol ([18F]FMISO) for the non-invasive detection of tumor heterogeneity for an improved planning of chemo-radiation therapy (CRT). Materials and Methods Sixteen patients with locally advanced cervix were enrolled in this IRB approved and were examined with fused MP [18F]FDG/ [18F]FMISO PET/MRI and in eleven patients complete data sets were acquired. MP PET/MRI was assessed for tumor volume, enhancement (EH)-kinetics, diffusivity, and [18F]FDG/ [18F]FMISO-avidity. Descriptive statistics and voxel-by-voxel analysis of MRI and PET parameters were performed. Correlations were assessed using multiple correlation analysis. Results All tumors displayed imaging parameters concordant with cervix cancer, i.e. type II/III EH-kinetics, restricted diffusivity (median ADC 0.80x10-3mm2/sec), [18F]FDG- (median SUVmax16.2) and [18F]FMISO-avidity (median SUVmax3.1). In all patients, [18F]FMISO PET identified the hypoxic tumor subvolume, which was independent of tumor volume. A voxel-by-voxel analysis revealed only weak correlations between the MRI and PET parameters (0.05–0.22), indicating that each individual parameter yields independent information and the presence of tumor heterogeneity. Conclusion MP [18F]FDG/ [18F]FMISO PET/MRI in patients with cervical cancer facilitates the acquisition of independent predictive and prognostic imaging parameters. MP [18F]FDG/ [18F]FMISO PET/MRI enables insights into tumor biology on multiple levels and provides information on tumor heterogeneity, which has the potential to improve the planning of CRT. PMID:27167829
Pinker, Katja; Andrzejewski, Piotr; Baltzer, Pascal; Polanec, Stephan H; Sturdza, Alina; Georg, Dietmar; Helbich, Thomas H; Karanikas, Georgios; Grimm, Christoph; Polterauer, Stephan; Poetter, Richard; Wadsak, Wolfgang; Mitterhauser, Markus; Georg, Petra
2016-01-01
To investigate fused multiparametric positron emission tomography/magnetic resonance imaging (MP PET/MRI) at 3T in patients with locally advanced cervical cancer, using high-resolution T2-weighted, contrast-enhanced MRI (CE-MRI), diffusion-weighted imaging (DWI), and the radiotracers [18F]fluorodeoxyglucose ([18F]FDG) and [18F]fluoromisonidazol ([18F]FMISO) for the non-invasive detection of tumor heterogeneity for an improved planning of chemo-radiation therapy (CRT). Sixteen patients with locally advanced cervix were enrolled in this IRB approved and were examined with fused MP [18F]FDG/ [18F]FMISO PET/MRI and in eleven patients complete data sets were acquired. MP PET/MRI was assessed for tumor volume, enhancement (EH)-kinetics, diffusivity, and [18F]FDG/ [18F]FMISO-avidity. Descriptive statistics and voxel-by-voxel analysis of MRI and PET parameters were performed. Correlations were assessed using multiple correlation analysis. All tumors displayed imaging parameters concordant with cervix cancer, i.e. type II/III EH-kinetics, restricted diffusivity (median ADC 0.80x10-3mm2/sec), [18F]FDG- (median SUVmax16.2) and [18F]FMISO-avidity (median SUVmax3.1). In all patients, [18F]FMISO PET identified the hypoxic tumor subvolume, which was independent of tumor volume. A voxel-by-voxel analysis revealed only weak correlations between the MRI and PET parameters (0.05-0.22), indicating that each individual parameter yields independent information and the presence of tumor heterogeneity. MP [18F]FDG/ [18F]FMISO PET/MRI in patients with cervical cancer facilitates the acquisition of independent predictive and prognostic imaging parameters. MP [18F]FDG/ [18F]FMISO PET/MRI enables insights into tumor biology on multiple levels and provides information on tumor heterogeneity, which has the potential to improve the planning of CRT.
Assessment of the Focal Hepatic Lesions Using Diffusion Tensor Magnetic Resonance Imaging
Oussous, Siham Ait; Boujraf, Saïd; Kamaoui, Imane
2016-01-01
The goal is assessing the diffusion magnetic resonance imaging (dMRI) method efficiency in characterizing focal hepatic lesions (FHLs). About 28-FHL patients were studied in Radiology and Clinical Imaging Department of our University Hospital using 1.5 Tesla MRI system between January 2010 and June 2011. Patients underwent hepatic MRI consisting of dynamic T1- and T2-weighted imaging. The dMRI was performed with b-values of 200 s/mm2 and 600 s/mm2. About 42 lesions measuring more than 1 cm were studied including the variation of the signal according to the b-value and the apparent diffusion coefficient (ADC). The diagnostic imaging reference was based on standard MRI techniques data for typical lesions and on histology after surgical biopsy for atypical lesions. About 38 lesions were assessed including 13 benign lesions consisting of 1 focal nodular hyperplasia, 8 angiomas, and 4 cysts. About 25 malignant lesions included 11 hepatocellular carcinoma, 9 hepatic metastases, 1 cholangiocarcinoma, and 4 lymphomas. dMRI of soft lesions demonstrated higher ADC of 2.26 ± 0.75 mm2/s, whereas solid lesions showed lower ADC 1.19 ± 0.33 mm2/s with significant difference (P = 0.05). Discrete values collections were noticed. These results were correlated to standard MRI and histological findings. Sensitivity of 93% and specificity of 84% were found in diagnoses of malignant tumors with an ADC threshold of 1.6 × 10−3 mm2/s. dMRI is important characterization method of FHL. However, it should not be used as single criteria of hepatic lesions malignity. MRI, clinical, and biological data must be correlated. Significant difference was found between benign and solid malignant lesions without threshold ADC values. Hence, it is difficult to confirm ADC threshold differentiating the lesion classification. PMID:27186537
Zhang, Zhongwei; Yuan, Qing; Zhou, Heling; Zhao, Dawen; Li, Li; Gerberich, Jenifer L; Mason, Ralph P
2015-11-01
To assess tumor response to oxygen challenge using quantitative diffusion magnetic resonance imaging (MRI). A well-characterized Dunning R3327-AT1 rat prostate cancer line was implanted subcutaneously in the right thigh of male Copenhagen rats (n = 8). Diffusion-weighted images (DWI) with multiple b values (0, 25, 50, 100, 150, 200, 300, 500, 1000, 1500 s/mm(2) ) in three orthogonal directions were obtained using a multishot FSE-based Stejskal-Tanner DWI sequence (FSE-DWI) at 4.7T, while rats breathed medical air (21% oxygen) and with 100% oxygen challenge. Stretched-exponential and intravoxel incoherent motion (IVIM) models were used to calculate and compare quantitative diffusion parameters: diffusion heterogeneity index (α), intravoxel distribution of diffusion coefficients (DDC), tissue diffusivity (Dt), pseudo-diffusivity (Dp), and perfusion fraction (f) on a voxel-by-voxel basis. A significant increase of α (73.9 ± 4.7% in air vs. 78.1 ± 4.5% in oxygen, P = 0.0198) and a significant decrease of f (13.4 ± 3.7% in air vs. 10.4 ± 2.7% in oxygen, P = 0.0201) were observed to accompany oxygen challenge. Correlations between f and α during both air and oxygen breathing were found; the correlation coefficients (r) were -0.90 and -0.96, respectively. Positive correlations between Dt and DDC with oxygen breathing (r = 0.95, P = 0.0003), f and DDC with air breathing were also observed (r = 0.95, P = 0.0004). Quantitative diffusion MRI demonstrated changes in tumor perfusion in response to oxygen challenge. © 2015 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Jarrett, Angela M.; Hormuth, David A.; Barnes, Stephanie L.; Feng, Xinzeng; Huang, Wei; Yankeelov, Thomas E.
2018-05-01
Clinical methods for assessing tumor response to therapy are largely rudimentary, monitoring only temporal changes in tumor size. Our goal is to predict the response of breast tumors to therapy using a mathematical model that utilizes magnetic resonance imaging (MRI) data obtained non-invasively from individual patients. We extended a previously established, mechanically coupled, reaction-diffusion model for predicting tumor response initialized with patient-specific diffusion weighted MRI (DW-MRI) data by including the effects of chemotherapy drug delivery, which is estimated using dynamic contrast-enhanced (DCE-) MRI data. The extended, drug incorporated, model is initialized using patient-specific DW-MRI and DCE-MRI data. Data sets from five breast cancer patients were used—obtained before, after one cycle, and at mid-point of neoadjuvant chemotherapy. The DCE-MRI data was used to estimate spatiotemporal variations in tumor perfusion with the extended Kety–Tofts model. The physiological parameters derived from DCE-MRI were used to model changes in delivery of therapy drugs within the tumor for incorporation in the extended model. We simulated the original model and the extended model in both 2D and 3D and compare the results for this five-patient cohort. Preliminary results show reductions in the error of model predicted tumor cellularity and size compared to the experimentally-measured results for the third MRI scan when therapy was incorporated. Comparing the two models for agreement between the predicted total cellularity and the calculated total cellularity (from the DW-MRI data) reveals an increased concordance correlation coefficient from 0.81 to 0.98 for the 2D analysis and 0.85 to 0.99 for the 3D analysis (p < 0.01 for each) when the extended model was used in place of the original model. This study demonstrates the plausibility of using DCE-MRI data as a means to estimate drug delivery on a patient-specific basis in predictive models and represents a step toward the goal of achieving individualized prediction of tumor response to therapy.
NASA Astrophysics Data System (ADS)
Liang, Yingjie; Ye, Allen Q.; Chen, Wen; Gatto, Rodolfo G.; Colon-Perez, Luis; Mareci, Thomas H.; Magin, Richard L.
2016-10-01
Non-Gaussian (anomalous) diffusion is wide spread in biological tissues where its effects modulate chemical reactions and membrane transport. When viewed using magnetic resonance imaging (MRI), anomalous diffusion is characterized by a persistent or 'long tail' behavior in the decay of the diffusion signal. Recent MRI studies have used the fractional derivative to describe diffusion dynamics in normal and post-mortem tissue by connecting the order of the derivative with changes in tissue composition, structure and complexity. In this study we consider an alternative approach by introducing fractal time and space derivatives into Fick's second law of diffusion. This provides a more natural way to link sub-voxel tissue composition with the observed MRI diffusion signal decay following the application of a diffusion-sensitive pulse sequence. Unlike previous studies using fractional order derivatives, here the fractal derivative order is directly connected to the Hausdorff fractal dimension of the diffusion trajectory. The result is a simpler, computationally faster, and more direct way to incorporate tissue complexity and microstructure into the diffusional dynamics. Furthermore, the results are readily expressed in terms of spectral entropy, which provides a quantitative measure of the overall complexity of the heterogeneous and multi-scale structure of biological tissues. As an example, we apply this new model for the characterization of diffusion in fixed samples of the mouse brain. These results are compared with those obtained using the mono-exponential, the stretched exponential, the fractional derivative, and the diffusion kurtosis models. Overall, we find that the order of the fractal time derivative, the diffusion coefficient, and the spectral entropy are potential biomarkers to differentiate between the microstructure of white and gray matter. In addition, we note that the fractal derivative model has practical advantages over the existing models from the perspective of computational accuracy and efficiency.
Pisharady, Pramod Kumar; Sotiropoulos, Stamatios N; Sapiro, Guillermo; Lenglet, Christophe
2017-09-01
We propose a sparse Bayesian learning algorithm for improved estimation of white matter fiber parameters from compressed (under-sampled q-space) multi-shell diffusion MRI data. The multi-shell data is represented in a dictionary form using a non-monoexponential decay model of diffusion, based on continuous gamma distribution of diffusivities. The fiber volume fractions with predefined orientations, which are the unknown parameters, form the dictionary weights. These unknown parameters are estimated with a linear un-mixing framework, using a sparse Bayesian learning algorithm. A localized learning of hyperparameters at each voxel and for each possible fiber orientations improves the parameter estimation. Our experiments using synthetic data from the ISBI 2012 HARDI reconstruction challenge and in-vivo data from the Human Connectome Project demonstrate the improvements.
White matter integrity and processing speed in sickle cell anemia.
Stotesbury, Hanne; Kirkham, Fenella J; Kölbel, Melanie; Balfour, Philippa; Clayden, Jonathan D; Sahota, Sati; Sakaria, Simrat; Saunders, Dawn E; Howard, Jo; Kesse-Adu, Rachel; Inusa, Baba; Pelidis, Maria; Chakravorty, Subarna; Rees, David C; Awogbade, Moji; Wilkey, Olu; Layton, Mark; Clark, Christopher A; Kawadler, Jamie M
2018-05-11
The purpose of this retrospective cross-sectional study was to investigate whether changes in white matter integrity are related to slower processing speed in sickle cell anemia. Thirty-seven patients with silent cerebral infarction, 46 patients with normal MRI, and 32 sibling controls (age range 8-37 years) underwent cognitive assessment using the Wechsler scales and 3-tesla MRI. Tract-based spatial statistics analyses of diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) parameters were performed. Processing speed index (PSI) was lower in patients than controls by 9.34 points (95% confidence interval: 4.635-14.855, p = 0.0003). Full Scale IQ was lower by 4.14 scaled points (95% confidence interval: -1.066 to 9.551, p = 0.1), but this difference was abolished when PSI was included as a covariate ( p = 0.18). There were no differences in cognition between patients with and without silent cerebral infarction, and both groups had lower PSI than controls (both p < 0.001). In patients, arterial oxygen content, socioeconomic status, age, and male sex were identified as predictors of PSI, and correlations were found between PSI and DTI scalars (fractional anisotropy r = 0.614, p < 0.00001; r = -0.457, p < 0.00001; mean diffusivity r = -0.341, p = 0.0016; radial diffusivity r = -0.457, p < 0.00001) and NODDI parameters (intracellular volume fraction r = 0.364, p = 0.0007) in widespread regions. Our results extend previous reports of impairment that is independent of presence of infarction and may worsen with age. We identify processing speed as a vulnerable domain, with deficits potentially mediating difficulties across other domains, and provide evidence that reduced processing speed is related to the integrity of normal-appearing white matter using microstructure parameters from DTI and NODDI. Copyright © 2018 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.
Malyarenko, Dariya; Newitt, David; Wilmes, Lisa; Tudorica, Alina; Helmer, Karl G.; Arlinghaus, Lori R.; Jacobs, Michael A.; Jajamovich, Guido; Taouli, Bachir; Yankeelov, Thomas E.; Huang, Wei; Chenevert, Thomas L.
2015-01-01
Purpose Characterize system-specific bias across common magnetic resonance imaging (MRI) platforms for quantitative diffusion measurements in multicenter trials. Methods Diffusion weighted imaging (DWI) was performed on an ice-water phantom along the superior-inferior (SI) and right-left (RL) orientations spanning ±150 mm. The same scanning protocol was implemented on 14 MRI systems at seven imaging centers. The bias was estimated as a deviation of measured from known apparent diffusion coefficient (ADC) along individual DWI directions. The relative contributions of gradient nonlinearity, shim errors, imaging gradients and eddy currents were assessed independently. The observed bias errors were compared to numerical models. Results The measured systematic ADC errors scaled quadratically with offset from isocenter, and ranged between −55% (SI) and 25% (RL). Nonlinearity bias was dependent on system design and diffusion gradient direction. Consistent with numerical models, minor ADC errors (±5%) due to shim, imaging and eddy currents were mitigated by double echo DWI and image co-registration of individual gradient directions. Conclusion The analysis confirms gradient nonlinearity as a major source of spatial DW bias and variability in off-center ADC measurements across MRI platforms, with minor contributions from shim, imaging gradients and eddy currents. The developed protocol enables empiric description of systematic bias in multicenter quantitative DWI studies. PMID:25940607
Malyarenko, Dariya I; Newitt, David; J Wilmes, Lisa; Tudorica, Alina; Helmer, Karl G; Arlinghaus, Lori R; Jacobs, Michael A; Jajamovich, Guido; Taouli, Bachir; Yankeelov, Thomas E; Huang, Wei; Chenevert, Thomas L
2016-03-01
Characterize system-specific bias across common magnetic resonance imaging (MRI) platforms for quantitative diffusion measurements in multicenter trials. Diffusion weighted imaging (DWI) was performed on an ice-water phantom along the superior-inferior (SI) and right-left (RL) orientations spanning ± 150 mm. The same scanning protocol was implemented on 14 MRI systems at seven imaging centers. The bias was estimated as a deviation of measured from known apparent diffusion coefficient (ADC) along individual DWI directions. The relative contributions of gradient nonlinearity, shim errors, imaging gradients, and eddy currents were assessed independently. The observed bias errors were compared with numerical models. The measured systematic ADC errors scaled quadratically with offset from isocenter, and ranged between -55% (SI) and 25% (RL). Nonlinearity bias was dependent on system design and diffusion gradient direction. Consistent with numerical models, minor ADC errors (± 5%) due to shim, imaging and eddy currents were mitigated by double echo DWI and image coregistration of individual gradient directions. The analysis confirms gradient nonlinearity as a major source of spatial DW bias and variability in off-center ADC measurements across MRI platforms, with minor contributions from shim, imaging gradients and eddy currents. The developed protocol enables empiric description of systematic bias in multicenter quantitative DWI studies. © 2015 Wiley Periodicals, Inc.
Tajima, Taku; Akahane, Masaaki; Takao, Hidemasa; Akai, Hiroyuki; Kiryu, Shigeru; Imamura, Hiroshi; Watanabe, Yasushi; Kokudo, Norihiro; Ohtomo, Kuni
2012-10-01
We compared diagnostic ability for detecting hepatic metastases between gadolinium ethoxy benzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) on a 1.5-T system, and determined whether DWI is necessary in Gd-EOB-DTPA-enhanced MRI for diagnosing colorectal liver metastases. We assessed 29 consecutive prospectively enrolled patients with suspected metachronous colorectal liver metastases; all patients underwent surgery and had preoperative Gd-EOB-DTPA-enhanced MRI. Overall detection rate, sensitivity for detecting metastases and benign lesions, positive predictive value, and diagnostic accuracy (Az value) were compared among three image sets [unenhanced MRI (DWI set), Gd-EOB-DTPA-enhanced MRI excluding DWI (EOB set), and combined set]. Gd-EOB-DTPA-enhanced MRI yielded better overall detection rate (77.8-79.0 %) and sensitivity (87.1-89.4 %) for detecting metastases than the DWI set (55.9 % and 64.7 %, respectively) for one observer (P < 0.001). No statistically significant difference was seen between the EOB and combined sets, although several metastases were newly detected on additional DWI. Gd-EOB-DTPA-enhanced MRI yielded a better overall detection rate and higher sensitivity for detecting metastases compared with unenhanced MRI. Additional DWI may be able to reduce oversight of lesions in Gd-EOB-DTPA-enhanced 1.5-T MRI for detecting colorectal liver metastases.
Fusion of MRIs and CT scans for surgical treatment of cholesteatoma of the middle ear in children.
Plouin-Gaudon, Isabelle; Bossard, Denis; Ayari-Khalfallah, Sonia; Froehlich, Patrick
2010-09-01
To evaluate the efficiency of diffusion-weighted magnetic resonance imaging (MRI) and high-resolution computed tomographic (CT) scan coregistration in predicting and adequately locating primary or recurrent cholesteatoma in children. Prospective study. Tertiary care university hospital. Ten patients aged 2 to 17 years (mean age, 8.5 years) with cholesteatoma of the middle ear, some of which were previously treated, were included for follow-up with systematic CT scanning and MRI between 2007 and 2008. Computed tomographic scanning was performed on a Siemens Somaton 128 (0.5/0.2-mm slices reformatted in 0.5/0.3-mm images). Fine cuts were obtained parallel and perpendicular to the lateral semicircular canal in each ear (100 × 100-mm field of view). Magnetic resonance imaging was undertaken on a Siemens Avanto 1.5T unit, with a protocol adapted for young children. Diffusion-weighted imaging was acquired using a single-shot turbo spin-echo mode. To allow for diagnosis and localization of the cholesteatoma, CT and diffusion-weighted MRIs were fused for each case. In 10 children, fusion technique allowed for correct diagnosis and precise localization (hypotympanum, epitympanum, mastoid recess, and attical space) as confirmed by subsequent standard surgery (positive predictive value, 100%). In 3 cases, the surgical approach was adequately determined from the fusion results. Lesion sizes on the CT-MRI fusion corresponded with perioperative findings. Recent developments in imaging techniques have made diffusion-weighted MRI more effective for detecting recurrent cholesteatoma. The major drawback of this technique, however, has been its poor anatomical and spatial discrimination. Fusion imaging using high-resolution CT and diffusion-weighted MRI appears to be a promising technique for both the diagnosis and precise localization of cholesteatomas. It provides useful information for surgical planning and, furthermore, is easy to use in pediatric cases.
A new compression format for fiber tracking datasets.
Presseau, Caroline; Jodoin, Pierre-Marc; Houde, Jean-Christophe; Descoteaux, Maxime
2015-04-01
A single diffusion MRI streamline fiber tracking dataset may contain hundreds of thousands, and often millions of streamlines and can take up to several gigabytes of memory. This amount of data is not only heavy to compute, but also difficult to visualize and hard to store on disk (especially when dealing with a collection of brains). These problems call for a fiber-specific compression format that simplifies its manipulation. As of today, no fiber compression format has yet been adopted and the need for it is now becoming an issue for future connectomics research. In this work, we propose a new compression format, .zfib, for streamline tractography datasets reconstructed from diffusion magnetic resonance imaging (dMRI). Tracts contain a large amount of redundant information and are relatively smooth. Hence, they are highly compressible. The proposed method is a processing pipeline containing a linearization, a quantization and an encoding step. Our pipeline is tested and validated under a wide range of DTI and HARDI tractography configurations (step size, streamline number, deterministic and probabilistic tracking) and compression options. Similar to JPEG, the user has one parameter to select: a worst-case maximum tolerance error in millimeter (mm). Overall, we find a compression factor of more than 96% for a maximum error of 0.1mm without any perceptual change or change of diffusion statistics (mean fractional anisotropy and mean diffusivity) along bundles. This opens new opportunities for connectomics and tractometry applications. Copyright © 2014 Elsevier Inc. All rights reserved.
Schmid-Tannwald, C; Schmid-Tannwald, C M; Morelli, J N; Neumann, R; Reiser, M F; Nikolaou, K; Rist, C
2014-07-01
To evaluate the role of diffusion-weighted magnetic resonance imaging (DW-MRI) in the differentiation of hepatic abscesses from non-infected fluid collections. In this retrospective study, 22 hepatic abscesses and 27 non-infected hepatic fluid collections were examined in 27 patients who underwent abdominal MRI including DW-MRI. Two independent observers reviewed T2-weighted + DW-MRI and T2-weighted + contrast-enhanced T1-weighted (CET1W) images in two sessions. Detection rates and confidence levels were calculated and compared using McNemar's and Wilcoxon's signed rank tests, respectively. Apparent diffusion coefficient (ADC) values of abscesses and non-infected fluid collections were compared using the t-test. Receiver operating characteristic (ROC) curves were constructed. There was no statistically significant difference in the accuracy of detecting abscesses using T2-weighted + DW-MRI (both observers: 21/22, 95.5%) versus T2-weighted + CET1W images (observer 1: 21/22, 95.5%; observer 2: 22/22, 100%; p < 0.01). Mean ADC values were significantly lower with abscesses versus non-infected fluid collections (0.83 ± 0.24 versus 2.25 ± 0.61 × 10(-3) mm(2)/s; p < 0.001). With ROC analysis there was good discrimination of abscess from non-infected fluid collections at a threshold ADC value of 1.36 × 10(-3) mm(2)/s. DW-MRI allows qualitative and quantitative differentiation of abscesses from non-infected fluid collections in the liver. Copyright © 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
Brown, Anna M; Nagala, Sidhartha; McLean, Mary A; Lu, Yonggang; Scoffings, Daniel; Apte, Aditya; Gonen, Mithat; Stambuk, Hilda E; Shaha, Ashok R; Tuttle, R Michael; Deasy, Joseph O; Priest, Andrew N; Jani, Piyush; Shukla-Dave, Amita; Griffiths, John
2016-04-01
Ultrasound-guided fine needle aspirate cytology fails to diagnose many malignant thyroid nodules; consequently, patients may undergo diagnostic lobectomy. This study assessed whether textural analysis (TA) could noninvasively stratify thyroid nodules accurately using diffusion-weighted MRI (DW-MRI). This multi-institutional study examined 3T DW-MRI images obtained with spin echo echo planar imaging sequences. The training data set included 26 patients from Cambridge, United Kingdom, and the test data set included 18 thyroid cancer patients from Memorial Sloan Kettering Cancer Center (New York, New York, USA). Apparent diffusion coefficients (ADCs) were compared over regions of interest (ROIs) defined on thyroid nodules. TA, linear discriminant analysis (LDA), and feature reduction were performed using the 21 MaZda-generated texture parameters that best distinguished benign and malignant ROIs. Training data set mean ADC values were significantly different for benign and malignant nodules (P = 0.02) with a sensitivity and specificity of 70% and 63%, respectively, and a receiver operator characteristic (ROC) area under the curve (AUC) of 0.73. The LDA model of the top 21 textural features correctly classified 89/94 DW-MRI ROIs with 92% sensitivity, 96% specificity, and an AUC of 0.97. This algorithm correctly classified 16/18 (89%) patients in the independently obtained test set of thyroid DW-MRI scans. TA classifies thyroid nodules with high sensitivity and specificity on multi-institutional DW-MRI data sets. This method requires further validation in a larger prospective study. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
The VALiDATe29 MRI Based Multi-Channel Atlas of the Squirrel Monkey Brain.
Schilling, Kurt G; Gao, Yurui; Stepniewska, Iwona; Wu, Tung-Lin; Wang, Feng; Landman, Bennett A; Gore, John C; Chen, Li Min; Anderson, Adam W
2017-10-01
We describe the development of the first digital atlas of the normal squirrel monkey brain and present the resulting product, VALiDATe29. The VALiDATe29 atlas is based on multiple types of magnetic resonance imaging (MRI) contrast acquired on 29 squirrel monkeys, and is created using unbiased, nonlinear registration techniques, resulting in a population-averaged stereotaxic coordinate system. The atlas consists of multiple anatomical templates (proton density, T1, and T2* weighted), diffusion MRI templates (fractional anisotropy and mean diffusivity), and ex vivo templates (fractional anisotropy and a structural MRI). In addition, the templates are combined with histologically defined cortical labels, and diffusion tractography defined white matter labels. The combination of intensity templates and image segmentations make this atlas suitable for the fundamental atlas applications of spatial normalization and label propagation. Together, this atlas facilitates 3D anatomical localization and region of interest delineation, and enables comparisons of experimental data across different subjects or across different experimental conditions. This article describes the atlas creation and its contents, and demonstrates the use of the VALiDATe29 atlas in typical applications. The atlas is freely available to the scientific community.
Voxelwise multivariate analysis of multimodality magnetic resonance imaging
Naylor, Melissa G.; Cardenas, Valerie A.; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin
2015-01-01
Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remains a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. PMID:23408378
Tax, Chantal M.W.; Haije, Tom Dela; Fuster, Andrea; Westin, Carl-Fredrik; Viergever, Max A.; Florack, Luc; Leemans, Alexander
2017-01-01
The question whether our brain pathways adhere to a geometric grid structure has been a popular topic of debate in the diffusion imaging and neuroscience society. Wedeen et al. (2012a b) proposed that the brain’s white matter is organized like parallel sheets of interwoven pathways. Catani et al. (2012) concluded that this grid pattern is most likely an artifact, resulting from methodological biases that cause the tractography pathways to cross in orthogonal angles. To date, ambiguities in the mathematical conditions for a sheet structure to exist (e.g. its relation to orthogonal angles) combined with the lack of extensive quantitative evidence have prevented wide acceptance of the hypothesis. In this work, we formalize the relevant terminology and recapitulate the condition for a sheet structure to exist. Note that this condition is not related to the presence or absence of orthogonal crossing fibers, and that sheet structure is defined formally as a surface formed by two sets of interwoven pathways intersecting at arbitrary angles within the surface. To quantify the existence of sheet structure, we present a novel framework to compute the sheet probability index (SPI), which reflects the presence of sheet structure in discrete orientation data (e.g. fiber peaks derived from diffusion MRI). With simulation experiments we investigate the effect of spatial resolution, curvature of the fiber pathways, and measurement noise on the ability to detect sheet structure. In real diffusion MRI data experiments we can identify various regions where the data supports sheet structure (high SPI values), but also areas where the data does not support sheet structure (low SPI values) or where no reliable conclusion can be drawn. Several areas with high SPI values were found to be consistent across subjects, across multiple data sets obtained with different scanners, resolutions, and degrees of diffusion weighting, and across various modeling techniques. Under the strong assumption that the diffusion MRI peaks reflect true axons, our results would therefore indicate that pathways do not form sheet structures at every crossing fiber region but instead at well-defined locations in the brain. With this framework, sheet structure location, extent, and orientation could potentially serve as new structural features of brain tissue. The proposed method can be extended to quantify sheet structure in directional data obtained with techniques other than diffusion MRI, which is essential for further validation. PMID:27456538
DOE Office of Scientific and Technical Information (OSTI.GOV)
Emin, David, E-mail: emin@unm.edu; Akhtari, Massoud; Ellingson, B. M.
We analyze the transient-dc and frequency-dependent electrical conductivities between blocking electrodes. We extend this analysis to measurements of ions’ transport in freshly excised bulk samples of human brain tissue whose complex cellular structure produces blockages. The associated ionic charge-carrier density and diffusivity are consistent with local values for sodium cations determined non-invasively in brain tissue by MRI (NMR) and diffusion-MRI (spin-echo NMR). The characteristic separation between blockages, about 450 microns, is very much shorter than that found for sodium-doped gel proxies for brain tissue, >1 cm.
Added Value of Assessing Adnexal Masses with Advanced MRI Techniques
Thomassin-Naggara, I.; Balvay, D.; Rockall, A.; Carette, M. F.; Ballester, M.; Darai, E.; Bazot, M.
2015-01-01
This review will present the added value of perfusion and diffusion MR sequences to characterize adnexal masses. These two functional MR techniques are readily available in routine clinical practice. We will describe the acquisition parameters and a method of analysis to optimize their added value compared with conventional images. We will then propose a model of interpretation that combines the anatomical and morphological information from conventional MRI sequences with the functional information provided by perfusion and diffusion weighted sequences. PMID:26413542
Quantitative T2 mapping of white matter: applications for ageing and cognitive decline
NASA Astrophysics Data System (ADS)
Knight, Michael J.; McCann, Bryony; Tsivos, Demitra; Dillon, Serena; Coulthard, Elizabeth; Kauppinen, Risto A.
2016-08-01
In MRI, the coherence lifetime T2 is sensitive to the magnetic environment imposed by tissue microstructure and biochemistry in vivo. Here we explore the possibility that the use of T2 relaxometry may provide information complementary to that provided by diffusion tensor imaging (DTI) in ageing of healthy controls (HC), Alzheimer’s disease (AD) and mild cognitive impairment (MCI). T2 and diffusion MRI metrics were quantified in HC and patients with MCI and mild AD using multi-echo MRI and DTI. We used tract-based spatial statistics (TBSS) to evaluate quantitative MRI parameters in white matter (WM). A prolonged T2 in WM was associated with AD, and able to distinguish AD from MCI, and AD from HC. Shorter WM T2 was associated with better cognition and younger age in general. In no case was a reduction in T2 associated with poorer cognition. We also applied principal component analysis, showing that WM volume changes independently of T2, MRI diffusion indices and cognitive performance indices. Our data add to the evidence that age-related and AD-related decline in cognition is in part attributable to WM tissue state, and much less to WM quantity. These observations suggest that WM is involved in AD pathology, and that T2 relaxometry is a potential imaging modality for detecting and characterising WM in cognitive decline and dementia.
Update on the MRI Core of the Alzheimer's Disease Neuroimaging Initiative
Jack, Clifford R; Bernstein, Matt A; Borowski, Bret J; Gunter, Jeffrey L; Fox, Nick C; Thompson, Paul M; Schuff, Norbert; Krueger, Gunnar; Killiany, Ronald J; DeCarli, Charles S; Dale, Anders M; Weiner, Michael W
2010-01-01
Functions of the ADNI MRI core fall into three categories: (1) those of the central MRI core lab at Mayo Clinic, Rochester, Minnesota, needed to generate high quality MRI data in all subjects at each time point; (2) those of the funded ADNI MRI core imaging analysis groups responsible for analyzing the MRI data, and (3) the joint function of the entire MRI core in designing and problem solving MR image acquisition, pre-processing and analyses methods. The primary objective of ADNI was and continues to be improving methods for clinical trials in Alzheimer's disease. Our approach to the present (“ADNI-GO”) and future (“ADNI-2”, if funded) MRI protocol will be to maintain MRI methodological consistency in previously enrolled “ADNI-1” subjects who are followed longitudinally in ADNI-GO and ADNI-2. We will modernize and expand the MRI protocol for all newly enrolled ADNI-GO and ADNI-2 subjects. All newly enrolled subjects will be scanned at 3T with a core set of three sequence types: 3D T1-weighted volume, FLAIR, and a long TE gradient echo volumetric acquisition for micro hemorrhage detection. In addition to this core ADNI-GO and ADNI-2 protocol, we will perform vendor specific pilot sub-studies of arterial spin labeling perfusion, resting state functional connectivity and diffusion tensor imaging. One each of these sequences will be added to the core protocol on systems from each MRI vendor. These experimental sub-studies are designed to demonstrate the feasibility of acquiring useful data in a multi-center (but single vendor) setting for these three emerging MRI applications. PMID:20451869
A monte carlo study of restricted diffusion: Implications for diffusion MRI of prostate cancer.
Gilani, Nima; Malcolm, Paul; Johnson, Glyn
2017-04-01
Diffusion MRI is used frequently to assess prostate cancer. The prostate consists of cellular tissue surrounding fluid filled ducts. Here, the diffusion properties of the ductal fluid alone were studied. Monte Carlo simulations were used to investigate ductal residence times to determine whether ducts can be regarded as forming a separate compartment and whether ductal radius could determine the Apparent Diffusion Coefficient (ADC) of the ductal fluid. Random walks were simulated in cavities. Average residence times were estimated for permeable cavities. Signal reductions resulting from application of a Stejskal-Tanner pulse sequence were calculated in impermeable cavities. Simulations were repeated for cavities of different radii and different diffusion times. Residence times are at least comparable with diffusion times even in relatively high grade tumors. ADCs asymptotically approach theoretical limiting values. At large radii and short diffusion times, ADCs are similar to free diffusion. At small radii and long diffusion times, ADCs are reduced toward zero, and kurtosis approaches a value of -1.2. Restricted diffusion in cavities of similar sizes to prostate ducts may reduce ductal ADCs. This may contribute to reductions in total ADC seen in prostate cancer. Magn Reson Med 77:1671-1677, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.
Van Steenkiste, Gwendolyn; Jeurissen, Ben; Veraart, Jelle; den Dekker, Arnold J; Parizel, Paul M; Poot, Dirk H J; Sijbers, Jan
2016-01-01
Diffusion MRI is hampered by long acquisition times, low spatial resolution, and a low signal-to-noise ratio. Recently, methods have been proposed to improve the trade-off between spatial resolution, signal-to-noise ratio, and acquisition time of diffusion-weighted images via super-resolution reconstruction (SRR) techniques. However, during the reconstruction, these SRR methods neglect the q-space relation between the different diffusion-weighted images. An SRR method that includes a diffusion model and directly reconstructs high resolution diffusion parameters from a set of low resolution diffusion-weighted images was proposed. Our method allows an arbitrary combination of diffusion gradient directions and slice orientations for the low resolution diffusion-weighted images, optimally samples the q- and k-space, and performs motion correction with b-matrix rotation. Experiments with synthetic data and in vivo human brain data show an increase of spatial resolution of the diffusion parameters, while preserving a high signal-to-noise ratio and low scan time. Moreover, the proposed SRR method outperforms the previous methods in terms of the root-mean-square error. The proposed SRR method substantially increases the spatial resolution of MRI that can be obtained in a clinically feasible scan time. © 2015 Wiley Periodicals, Inc.
Bae, Min Sun; Jahng, Geon-Ho; Ryu, Chang Woo; Kim, Eui Jong; Choi, Woo Suk; Yang, Dal Mo
2009-12-01
The aim of this study was to investigate whether indices of diffusion tensor MRI (DT-MRI) are altered after contrast medium injection in patients with brain tumors. DT-MRIs at a 3-T unit before and 6 min after gadolinium-diethylenetriamine penta-acetic acid injection were obtained in nine patients (five women, four men) with histologically confirmed brain tumors (four metastases, one glioblastoma multiforme, three meningiomas, and one lymphoma). Fractional anisotropy (FA), trace and mean raw DT-MRI data without (DT_b0, b value = 0 s/mm(2)) and with (DT_b800, b value = 800 s/mm(2)) diffusion-encoded gradients were calculated. Regions of interest (ROIs) were placed in the tumor, peritumoral edema, and normal-appearing symmetric contralateral brain tissue for each patient. The Kruskal-Wallis rank sum test was used to determine the effects of contrast medium and ROI for all of the maps, and the Wilcoxon signed-rank test was performed for either paired t test between pre- and post-contrast values of DTI indices for the ROIs or the post hoc test. Statistically significant differences between pre-contrast and post-contrast DT-MRI are shown in the trace value of the peritumoral edema area (p = 0.0195) and the FA value of the tumor area (p = 0.0273). Trace and FA values of the other areas show no statistically significant differences between pre- and post-contrast (p > 0.05). In addition, we find a significant ROI effect for both FA (chi (2) = 26.514, df = 2, p = 0.0001) and trace (chi (2) = 21.218, df = 2, p = 0.0001). DT-MRI obtained after contrast medium injection of 6 min results in significant changes in diffusion isotropic and anisotropic values. Therefore, clinical applications of DT-MRI after administrating a contrast medium require caution in interpretation.
Hu, Hui; Lu, Hong; He, Zhanping; Han, Xiangjun; Chen, Jing; Tu, Rong
2012-07-25
To investigate the effects of mRNA interference on aquaporin-4 expression in swollen tissue of rats with ischemic cerebral edema, and diagnose the significance of diffusion-weighted MRI, we injected 5 μL shRNA- aquaporin-4 (control group) or siRNA- aquaporin-4 solution (1:800) (RNA interference group) into the rat right basal ganglia immediately before occlusion of the middle cerebral artery. At 0.25 hours after occlusion of the middle cerebral artery, diffusion-weighted MRI displayed a high signal; within 2 hours, the relative apparent diffusion coefficient decreased markedly, aquaporin-4 expression increased rapidly, and intracellular edema was obviously aggravated; at 4 and 6 hours, the relative apparent diffusion coefficient slowly returned to control levels, aquaporin-4 expression slightly increased, and angioedema was observed. In the RNA interference group, during 0.25-6 hours after injection of siRNA- aquaporin-4 solution, the relative apparent diffusion coefficient slightly fluctuated and aquaporin-4 expression was upregulated; during 0.5-4 hours, the relative apparent diffusion coefficient was significantly higher, while aquaporin-4 expression was significantly lower when compared with the control group, and intracellular edema was markedly reduced; at 0.25 and 6 hours, the relative apparent diffusion coefficient and aquaporin-4 expression were similar when compared with the control group; obvious angioedema remained at 6 hours. Pearson's correlation test results showed that aquaporin-4 expression was negatively correlated with the apparent diffusion coefficient (r = -0.806, P < 0.01). These findings suggest that upregulated aquaporin-4 expression is likely to be the main molecular mechanism of intracellular edema and may be the molecular basis for decreased relative apparent diffusion coefficient. Aquaporin-4 gene interference can effectively inhibit the upregulation of aquaporin-4 expression during the stage of intracellular edema with time-effectiveness. Moreover, diffusion-weighted MRI can accurately detect intracellular edema.
Billiet, Thibo; Mädler, Burkhard; D'Arco, Felice; Peeters, Ronald; Deprez, Sabine; Plasschaert, Ellen; Leemans, Alexander; Zhang, Hui; den Bergh, Bea Van; Vandenbulcke, Mathieu; Legius, Eric; Sunaert, Stefan; Emsell, Louise
2014-01-01
The histopathological basis of "unidentified bright objects" (UBOs) (hyperintense regions seen on T2-weighted magnetic resonance (MR) brain scans in neurofibromatosis-1 (NF1)) remains unclear. New in vivo MRI-based techniques (multi-exponential T2 relaxation (MET2) and diffusion MR imaging (dMRI)) provide measures relating to microstructural change. We combined these methods and present previously unreported data on in vivo UBO microstructure in NF1. 3-Tesla dMRI data were acquired on 17 NF1 patients, covering 30 white matter UBOs. Diffusion tensor, kurtosis and neurite orientation and dispersion density imaging parameters were calculated within UBO sites and in contralateral normal appearing white matter (cNAWM). Analysis of MET2 parameters was performed on 24 UBO-cNAWM pairs. No significant alterations in the myelin water fraction and intra- and extracellular (IE) water fraction were found. Mean T2 time of IE water was significantly higher in UBOs. UBOs furthermore showed increased axial, radial and mean diffusivity, and decreased fractional anisotropy, mean kurtosis and neurite density index compared to cNAWM. Neurite orientation dispersion and isotropic fluid fraction were unaltered. Our results suggest that demyelination and axonal degeneration are unlikely to be present in UBOs, which appear to be mainly caused by a shift towards a higher T2-value of the intra- and extracellular water pool. This may arise from altered microstructural compartmentalization, and an increase in 'extracellular-like', intracellular water, possibly due to intramyelinic edema. These findings confirm the added value of combining dMRI and MET2 to characterize the microstructural basis of T2 hyperintensities in vivo.
Magnetic resonance imaging of clays: swelling, sedimentation, dissolution
NASA Astrophysics Data System (ADS)
Dvinskikh, Sergey; Furo, Istvan
2010-05-01
While most magnetic resonance imaging (MRI) applications concern medical research, there is a rapidly increasing number of MRI studies in the field of environmental science and technology. In this presentation, MRI will be introduced from the latter perspective. While many processes in these areas are similar to those addressed in medical applications of MRI, parameters and experimental implementations are often quite different and, in many respects, far more demanding. This hinders direct transfer of existing methods developed for biomedical research, especially when facing the challenging task of obtaining spatially resolved quantitative information. In MRI investigation of soils, clays, and rocks, mainly water signal is detected, similarly to MRI of biological and medical samples. However, a strong variation of water mobility and a wide spread of water spin relaxation properties in these materials make it difficult to use standard MRI approaches. Other significant limitations can be identified as following: T2 relaxation and probe dead time effects; molecular diffusion artifacts; varying dielectric losses and induced currents in conductive samples; limited dynamic range; blurring artifacts accompanying drive for increasing sensitivity and/or imaging speed. Despite these limitations, by combining MRI techniques developed for solid and liquid states and using independent information on relaxation properties of water, interacting with the material of interest, true images of distributions of both water, material and molecular properties in a wide range of concentrations can be obtained. Examples of MRI application will be given in the areas of soil and mineral research where understanding water transport and erosion processes is one of the key challenges. Efforts in developing and adapting MRI approaches to study these kinds of systems will be outlined as well. Extensive studies of clay/water interaction have been carried out in order to provide a quantitative measure of clay distribution in extended samples during different physical processes such as swelling, dissolution, and sedimentation on the time scale from minutes to years [1-3]. To characterize the state of colloids that form after/during clay swelling the water self-diffusion coefficient was measured on a spatially resolved manner. Both natural clays and purified and ion-exchanged montmorillonite clays were investigated. The primary variables were clay composition and water ionic strength. These results have a significant impact for engineering barriers for storage of spent nuclear fuel where clay erosion by low salinity water must be addressed. Presented methods were developed under the motivation of using bentonite clays as a buffer medium to build in-ground barriers for the encapsulation of radioactive waste. Nevertheless, the same approaches can be found suitable in other applications in soil and environmental science to study other types of materials as they swell, dissolve, erode, or sediment. Acknowledgements: This work has been supported by the Swedish Nuclear Fuel and Waste Management Co (SKB) and the Swedish Research Council VR. [1] N. Nestle, T. Baumann, R. Niessner, Magnetic resonance imaging in environmental science. Environ. Sci. Techn. 36 154A (2002). [2] S. V. Dvinskikh, K. Szutkowski, I. Furó. MRI profiles over a very wide concentration ranges: application to swelling of a bentonite clay. J. Magn. Reson. 198 146 (2009). [3] S. V. Dvinskikh, I. Furó. Magnetic resonance imaging and nuclear magnetic resonance investigations of bentonite systems. Technical Report, TR-09-27, SKB (2009), www.skb.se.
Min, Qinghua; Shao, Kangwei; Zhai, Lulan; Liu, Wei; Zhu, Caisong; Yuan, Lixin; Yang, Jun
2015-02-07
Diffusion-weighted magnetic resonance imaging (DW-MRI) is different from conventional diagnostic methods and has the potential to delineate the microscopic anatomy of a target tissue or organ. The purpose of our study was to evaluate the value of DW-MRI in the diagnosis of benign and malignant breast masses, which would help the clinical surgeon to decide the scope and pattern of operation. A total of 52 female patients with palpable solid breast masses received breast MRI scans using routine sequences, dynamic contrast-enhanced imaging, and diffusion-weighted echo-planar imaging at b values of 400, 600, and 800 s/mm(2), respectively. Two regions of interest (ROIs) were plotted, with a smaller ROI for the highest signal and a larger ROI for the overall lesion. Apparent diffusion coefficient (ADC) values were calculated at three different b values for all detectable lesions and from two different ROIs. The sensitivity, specificity, positive predictive value, and positive likelihood ratio of DW-MRI were determined for comparison with histological results. A total of 49 (49/52, 94.2%) lesions were detected using DW-MRI, including 20 benign lesions (two lesions detected in the same patient) and 29 malignant lesions. Benign lesion had a higher mean ADC value than their malignant counterparts, regardless of b value. According to the receiver operating characteristic (ROC) curve, the smaller-range ROI was more effective in differentiation between benign and malignant lesions. The area under the ROC curve was the largest at a b value of 800 s/mm(2). With a threshold ADC value at 1.23 × 10(-3) mm(2)/s, DW-MRI achieved a sensitivity of 82.8%, specificity of 90.0%, positive predictive value of 92.3%, and positive likelihood ratio of 8.3 for differentiating benign and malignant lesions. DW-MRI is an accurate diagnostic tool for differentiation between benign and malignant breast lesions, with an optimal b value of 800 s/mm(2). A smaller-range ROI focusing on the highest signal has a better differential value.
Batalle, Dafnis; Eixarch, Elisenda; Figueras, Francesc; Muñoz-Moreno, Emma; Bargallo, Nuria; Illa, Miriam; Acosta-Rojas, Ruthy; Amat-Roldan, Ivan; Gratacos, Eduard
2012-04-02
Intrauterine growth restriction (IUGR) due to placental insufficiency affects 5-10% of all pregnancies and it is associated with a wide range of short- and long-term neurodevelopmental disorders. Prediction of neurodevelopmental outcomes in IUGR is among the clinical challenges of modern fetal medicine and pediatrics. In recent years several studies have used magnetic resonance imaging (MRI) to demonstrate differences in brain structure in IUGR subjects, but the ability to use MRI for individual predictive purposes in IUGR is limited. Recent research suggests that MRI in vivo access to brain connectivity might have the potential to help understanding cognitive and neurodevelopment processes. Specifically, MRI based connectomics is an emerging approach to extract information from MRI data that exhaustively maps inter-regional connectivity within the brain to build a graph model of its neural circuitry known as brain network. In the present study we used diffusion MRI based connectomics to obtain structural brain networks of a prospective cohort of one year old infants (32 controls and 24 IUGR) and analyze the existence of quantifiable brain reorganization of white matter circuitry in IUGR group by means of global and regional graph theory features of brain networks. Based on global and regional analyses of the brain network topology we demonstrated brain reorganization in IUGR infants at one year of age. Specifically, IUGR infants presented decreased global and local weighted efficiency, and a pattern of altered regional graph theory features. By means of binomial logistic regression, we also demonstrated that connectivity measures were associated with abnormal performance in later neurodevelopmental outcome as measured by Bayley Scale for Infant and Toddler Development, Third edition (BSID-III) at two years of age. These findings show the potential of diffusion MRI based connectomics and graph theory based network characteristics for estimating differences in the architecture of neural circuitry and developing imaging biomarkers of poor neurodevelopment outcome in infants with prenatal diseases. Copyright © 2012 Elsevier Inc. All rights reserved.
Multi-parametric spinal cord MRI as potential progression marker in amyotrophic lateral sclerosis.
El Mendili, Mohamed-Mounir; Cohen-Adad, Julien; Pelegrini-Issac, Mélanie; Rossignol, Serge; Morizot-Koutlidis, Régine; Marchand-Pauvert, Véronique; Iglesias, Caroline; Sangari, Sina; Katz, Rose; Lehericy, Stéphane; Benali, Habib; Pradat, Pierre-François
2014-01-01
To evaluate multimodal MRI of the spinal cord in predicting disease progression and one-year clinical status in amyotrophic lateral sclerosis (ALS) patients. After a first MRI (MRI1), 29 ALS patients were clinically followed during 12 months; 14/29 patients underwent a second MRI (MRI2) at 11±3 months. Cross-sectional area (CSA) that has been shown to be a marker of lower motor neuron degeneration was measured in cervical and upper thoracic spinal cord from T2-weighted images. Fractional anisotropy (FA), axial/radial/mean diffusivities (λ⊥, λ//, MD) and magnetization transfer ratio (MTR) were measured within the lateral corticospinal tract in the cervical region. Imaging metrics were compared with clinical scales: Revised ALS Functional Rating Scale (ALSFRS-R) and manual muscle testing (MMT) score. At MRI1, CSA correlated significantly (P<0.05) with MMT and arm ALSFRS-R scores. FA correlated significantly with leg ALFSRS-R scores. One year after MRI1, CSA predicted (P<0.01) arm ALSFSR-R subscore and FA predicted (P<0.01) leg ALSFRS-R subscore. From MRI1 to MRI2, significant changes (P<0.01) were detected for CSA and MTR. CSA rate of change (i.e. atrophy) highly correlated (P<0.01) with arm ALSFRS-R and arm MMT subscores rate of change. Atrophy and DTI metrics predicted ALS disease progression. Cord atrophy was a better biomarker of disease progression than diffusion and MTR. Our study suggests that multimodal MRI could provide surrogate markers of ALS that may help monitoring the effect of disease-modifying drugs.
de Jong, Antoinette; Kwee, Thomas C; de Klerk, John MH; Adam, Judit A; de Keizer, Bart; Fijnheer, Rob; Kersten, Marie José; Ludwig, Inge; Jauw, Yvonne WS; Zijlstra, Josée M; den Bos, Indra C Pieters - Van; Stoker, Jaap; Hoekstra, Otto S; Nievelstein, Rutger AJ
2014-01-01
The purpose of this study was to determine the correlation between the 18F-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) standardized uptake value (SUV) and the diffusion-weighted magnetic resonance imaging (MRI) apparent diffusion coefficient (ADC) in newly diagnosed diffuse large B-cell lymphoma (DLBCL). Pretreatment FDG-PET and diffusion-weighted MRI of 21 patients with histologically proven DLBCL were prospectively analyzed. In each patient, maximum, mean and peak standardized uptake value (SUV) was measured in the lesion with visually highest FDG uptake and in the largest lesion. Mean ADC (ADCmean, calculated with b-values of 0 and 1000 s/mm2) was measured in the same lesions. Correlations between FDG-PET metrics (SUVmax, SUVmean, SUVpeak) and ADCmean were assessed using Pearson’s correlation coefficients. In the lesions with visually highest FDG uptake, no significant correlations were found between the SUVmax, SUVmean, SUVpeak and the ADCmean (P=0.498, P=0.609 and P=0.595, respectively). In the largest lesions, there were no significant correlations either between the SUVmax, SUVmean, SUVpeak and the ADCmean (P=0.992, P=0.843 and P=0.894, respectively). The results of this study indicate that the glycolytic rate as measured by FDG-PET and changes in water compartmentalization and water diffusion as measured by the ADC are independent biological phenomena in newly diagnosed DLBCL. Further studies are warranted to assess the complementary roles of these different imaging biomarkers in the evaluation and follow-up of DLBCL. PMID:24795837
Diffusion Weighted MRI and MRS to Differentiate Radiation Necrosis and Recurrent Disease in Gliomas
NASA Astrophysics Data System (ADS)
Ewell, Lars
2006-03-01
A difficulty encountered in the diagnosis of patients with gliomas is the differentiation between recurrent disease and Radiation Induced Necrosis (RIN). Both can appear as ‘enhancing lesions’ on a typical T2 weighted MRI scan. Magnetic Resonance Spectroscopy (MRS) and Diffusion Weighted MRI (DWMRI) have the potential to be helpful regarding this differentiation. MRS has the ability to measure the concentration of brain metabolites, such as Choline, Creatin and N- Acetyl Aspartate, the ratios of which have been shown to discriminate between RIN and recurrent disease. DWMRI has been linked via a rise in the Apparent Diffusion Coefficient (ADC) to successful treatment of disease. Using both of these complimentary non-invasive imaging modalities, we intend to initiate an imaging protocol whereby we will study how best to combine metabolite ratios and ADC values to obtain the most useful information in the least amount of scan time. We will look for correlations over time between ADC values, and MRS, among different sized voxels.
NASA Astrophysics Data System (ADS)
Chen, L. Leon; Ulmer, Stephan; Deisboeck, Thomas S.
2010-01-01
We present an application of a previously developed agent-based glioma model (Chen et al 2009 Biosystems 95 234-42) for predicting spatio-temporal tumor progression using a patient-specific MRI lattice derived from apparent diffusion coefficient (ADC) data. Agents representing collections of migrating glioma cells are initialized based upon voxels at the outer border of the tumor identified on T1-weighted (Gd+) MRI at an initial time point. These simulated migratory cells exhibit a specific biologically inspired spatial search paradigm, representing a weighting of the differential contribution from haptotactic permission and biomechanical resistance on the migration decision process. ADC data from 9 months after the initial tumor resection were used to select the best search paradigm for the simulation, which was initiated using data from 6 months after the initial operation. Using this search paradigm, 100 simulations were performed to derive a probabilistic map of tumor invasion locations. The simulation was able to successfully predict a recurrence in the dorsal/posterior aspect long before it was depicted on T1-weighted MRI, 18 months after the initial operation.
Chen, L Leon; Ulmer, Stephan; Deisboeck, Thomas S
2010-01-21
We present an application of a previously developed agent-based glioma model (Chen et al 2009 Biosystems 95 234-42) for predicting spatio-temporal tumor progression using a patient-specific MRI lattice derived from apparent diffusion coefficient (ADC) data. Agents representing collections of migrating glioma cells are initialized based upon voxels at the outer border of the tumor identified on T1-weighted (Gd+) MRI at an initial time point. These simulated migratory cells exhibit a specific biologically inspired spatial search paradigm, representing a weighting of the differential contribution from haptotactic permission and biomechanical resistance on the migration decision process. ADC data from 9 months after the initial tumor resection were used to select the best search paradigm for the simulation, which was initiated using data from 6 months after the initial operation. Using this search paradigm, 100 simulations were performed to derive a probabilistic map of tumor invasion locations. The simulation was able to successfully predict a recurrence in the dorsal/posterior aspect long before it was depicted on T1-weighted MRI, 18 months after the initial operation.
Multimodal Neuroimaging in Schizophrenia: Description and Dissemination.
Aine, C J; Bockholt, H J; Bustillo, J R; Cañive, J M; Caprihan, A; Gasparovic, C; Hanlon, F M; Houck, J M; Jung, R E; Lauriello, J; Liu, J; Mayer, A R; Perrone-Bizzozero, N I; Posse, S; Stephen, J M; Turner, J A; Clark, V P; Calhoun, Vince D
2017-10-01
In this paper we describe an open-access collection of multimodal neuroimaging data in schizophrenia for release to the community. Data were acquired from approximately 100 patients with schizophrenia and 100 age-matched controls during rest as well as several task activation paradigms targeting a hierarchy of cognitive constructs. Neuroimaging data include structural MRI, functional MRI, diffusion MRI, MR spectroscopic imaging, and magnetoencephalography. For three of the hypothesis-driven projects, task activation paradigms were acquired on subsets of ~200 volunteers which examined a range of sensory and cognitive processes (e.g., auditory sensory gating, auditory/visual multisensory integration, visual transverse patterning). Neuropsychological data were also acquired and genetic material via saliva samples were collected from most of the participants and have been typed for both genome-wide polymorphism data as well as genome-wide methylation data. Some results are also presented from the individual studies as well as from our data-driven multimodal analyses (e.g., multimodal examinations of network structure and network dynamics and multitask fMRI data analysis across projects). All data will be released through the Mind Research Network's collaborative informatics and neuroimaging suite (COINS).
Diffusion MRI noise mapping using random matrix theory
Veraart, Jelle; Fieremans, Els; Novikov, Dmitry S.
2016-01-01
Purpose To estimate the spatially varying noise map using a redundant magnitude MR series. Methods We exploit redundancy in non-Gaussian multi-directional diffusion MRI data by identifying its noise-only principal components, based on the theory of noisy covariance matrices. The bulk of PCA eigenvalues, arising due to noise, is described by the universal Marchenko-Pastur distribution, parameterized by the noise level. This allows us to estimate noise level in a local neighborhood based on the singular value decomposition of a matrix combining neighborhood voxels and diffusion directions. Results We present a model-independent local noise mapping method capable of estimating noise level down to about 1% error. In contrast to current state-of-the art techniques, the resultant noise maps do not show artifactual anatomical features that often reflect physiological noise, the presence of sharp edges, or a lack of adequate a priori knowledge of the expected form of MR signal. Conclusions Simulations and experiments show that typical diffusion MRI data exhibit sufficient redundancy that enables accurate, precise, and robust estimation of the local noise level by interpreting the PCA eigenspectrum in terms of the Marchenko-Pastur distribution. PMID:26599599
Constituents and functional implications of the rat default mode network.
Hsu, Li-Ming; Liang, Xia; Gu, Hong; Brynildsen, Julia K; Stark, Jennifer A; Ash, Jessica A; Lin, Ching-Po; Lu, Hanbing; Rapp, Peter R; Stein, Elliot A; Yang, Yihong
2016-08-02
The default mode network (DMN) has been suggested to support a variety of self-referential functions in humans and has been fractionated into subsystems based on distinct responses to cognitive tasks and functional connectivity architecture. Such subsystems are thought to reflect functional hierarchy and segregation within the network. Because preclinical models can inform translational studies of neuropsychiatric disorders, partitioning of the DMN in nonhuman species, which has previously not been reported, may inform both physiology and pathophysiology of the human DMN. In this study, we sought to identify constituents of the rat DMN using resting-state functional MRI (rs-fMRI) and diffusion tensor imaging. After identifying DMN using a group-level independent-component analysis on the rs-fMRI data, modularity analyses fractionated the DMN into an anterior and a posterior subsystem, which were further segregated into five modules. Diffusion tensor imaging tractography demonstrates a close relationship between fiber density and the functional connectivity between DMN regions, and provides anatomical evidence to support the detected DMN subsystems. Finally, distinct modulation was seen within and between these DMN subcomponents using a neurocognitive aging model. Taken together, these results suggest that, like the human DMN, the rat DMN can be partitioned into several subcomponents that may support distinct functions. These data encourage further investigation into the neurobiological mechanisms of DMN processing in preclinical models of both normal and disease states.
Maiwald, Bettina; Lobsien, Donald; Kahn, Thomas; Stumpp, Patrick
2014-01-01
Objectives To compare 64-slice contrast-enhanced computed tomography (CT) with 3-Tesla magnetic resonance imaging (MRI) using Gd-EOB-DTPA for the diagnosis of hepatocellular carcinoma (HCC) and evaluate the utility of diffusion-weighted imaging (DWI) in this setting. Methods 3-phase-liver-CT was performed in fifty patients (42 male, 8 female) with suspected or proven HCC. The patients were subjected to a 3-Tesla-MRI-examination with Gd-EOB-DTPA and diffusion weighted imaging (DWI) at b-values of 0, 50 and 400 s/mm2. The apparent diffusion coefficient (ADC)-value was determined for each lesion detected in DWI. The histopathological report after resection or biopsy of a lesion served as the gold standard, and a surrogate of follow-up or complementary imaging techniques in combination with clinical and paraclinical parameters was used in unresected lesions. Diagnostic accuracy, sensitivity, specificity, and positive and negative predictive values were evaluated for each technique. Results MRI detected slightly more lesions that were considered suspicious for HCC per patient compared to CT (2.7 versus 2.3, respectively). ADC-measurements in HCC showed notably heterogeneous values with a median of 1.2±0.5×10−3 mm2/s (range from 0.07±0.1 to 3.0±0.1×10−3 mm2/s). MRI showed similar diagnostic accuracy, sensitivity, and positive and negative predictive values compared to CT (AUC 0.837, sensitivity 92%, PPV 80% and NPV 90% for MRI vs. AUC 0.798, sensitivity 85%, PPV 79% and NPV 82% for CT; not significant). Specificity was 75% for both techniques. Conclusions Our study did not show a statistically significant difference in detection in detection of HCC between MRI and CT. Gd-EOB-DTPA-enhanced MRI tended to detect more lesions per patient compared to contrast-enhanced CT; therefore, we would recommend this modality as the first-choice imaging method for the detection of HCC and therapeutic decisions. However, contrast-enhanced CT was not inferior in our study, so that it can be a useful image modality for follow-up examinations. PMID:25375778
Postural headache in a patient with Marfan's syndrome.
Ferrante, E; Citterio, A; Savino, A; Santalucia, P
2003-09-01
A 26-year-old man with Marfan's syndrome had postural headache. Brain MRI with gadolinium showed diffuse pachymeningeal enhancement. MRI myelography revealed bilateral multiple large meningeal diverticula at sacral nerve roots level. He was suspected to have spontaneous intracranial hypotension syndrome. Eight days later headache improved with bed rest and hydration. One month after the onset he was asymptomatic and 3 months later brain MRI showed no evidence of diffuse pachymeningeal enhancement. The 1-year follow-up revealed no neurological abnormalities. The intracranial hypotension syndrome likely resulted from a CSF leak from one of the meningeal diverticula. In conclusion patients with spinal meningeal diverticula (frequently seen in Marfan's syndrome) might be at increased risk of developing CSF leaks, possibly secondary to Valsalva maneuver or minor unrecognized trauma.
Stephen, Renu M.; Jha, Abhinav K.; Roe, Denise J.; Trouard, Theodore P.; Galons, Jean-Philippe; Kupinski, Matthew A.; Frey, Georgette; Cui, Haiyan; Squire, Scott; Pagel, Mark D.; Rodriguez, Jeffrey J.; Gillies, Robert J.; Stopeck, Alison T.
2015-01-01
Purpose To assess the value of semi-automated segmentation applied to diffusion MRI for predicting the therapeutic response of liver metastasis. Methods Conventional diffusion weighted magnetic resonance imaging (MRI) was performed using b-values of 0, 150, 300 and 450 s/mm2 at baseline and days 4, 11 and 39 following initiation of a new chemotherapy regimen in a pilot study with 18 women with 37 liver metastases from primary breast cancer. A semi-automated segmentation approach was used to identify liver metastases. Linear regression analysis was used to assess the relationship between baseline values of the apparent diffusion coefficient (ADC) and change in tumor size by day 39. Results A semi-automated segmentation scheme was critical for obtaining the most reliable ADC measurements. A statistically significant relationship between baseline ADC values and change in tumor size at day 39 was observed for minimally treated patients with metastatic liver lesions measuring 2–5 cm in size (p = 0.002), but not for heavily treated patients with the same tumor size range (p = 0.29), or for tumors of smaller or larger sizes. ROC analysis identified a baseline threshold ADC value of 1.33 μm2/ms as 75% sensitive and 83% specific for identifying non-responding metastases in minimally treated patients with 2–5 cm liver lesions. Conclusion Quantitative imaging can substantially benefit from a semi-automated segmentation scheme. Quantitative diffusion MRI results can be predictive of therapeutic outcome in selected patients with liver metastases, but not for all liver metastases, and therefore should be considered to be a restricted biomarker. PMID:26284600
Stephen, Renu M; Jha, Abhinav K; Roe, Denise J; Trouard, Theodore P; Galons, Jean-Philippe; Kupinski, Matthew A; Frey, Georgette; Cui, Haiyan; Squire, Scott; Pagel, Mark D; Rodriguez, Jeffrey J; Gillies, Robert J; Stopeck, Alison T
2015-12-01
To assess the value of semi-automated segmentation applied to diffusion MRI for predicting the therapeutic response of liver metastasis. Conventional diffusion weighted magnetic resonance imaging (MRI) was performed using b-values of 0, 150, 300 and 450s/mm(2) at baseline and days 4, 11 and 39 following initiation of a new chemotherapy regimen in a pilot study with 18 women with 37 liver metastases from primary breast cancer. A semi-automated segmentation approach was used to identify liver metastases. Linear regression analysis was used to assess the relationship between baseline values of the apparent diffusion coefficient (ADC) and change in tumor size by day 39. A semi-automated segmentation scheme was critical for obtaining the most reliable ADC measurements. A statistically significant relationship between baseline ADC values and change in tumor size at day 39 was observed for minimally treated patients with metastatic liver lesions measuring 2-5cm in size (p=0.002), but not for heavily treated patients with the same tumor size range (p=0.29), or for tumors of smaller or larger sizes. ROC analysis identified a baseline threshold ADC value of 1.33μm(2)/ms as 75% sensitive and 83% specific for identifying non-responding metastases in minimally treated patients with 2-5cm liver lesions. Quantitative imaging can substantially benefit from a semi-automated segmentation scheme. Quantitative diffusion MRI results can be predictive of therapeutic outcome in selected patients with liver metastases, but not for all liver metastases, and therefore should be considered to be a restricted biomarker. Copyright © 2015 Elsevier Inc. All rights reserved.
Theys, Catherine; Wouters, Jan; Ghesquière, Pol
2014-01-01
Advanced Magnetic Resonance Imaging (MRI) techniques such as Diffusion Tensor Imaging (DTI) and resting-state functional MRI (rfMRI) are widely used to study structural and functional neural connectivity. However, as these techniques are highly sensitive to motion artifacts and require a considerable amount of time for image acquisition, successful acquisition of these images can be challenging to complete with certain populations. This is especially true for young children. This paper describes a new approach termed the ‘submarine protocol’, designed to prepare 5- and 6-year-old children for advanced MRI scanning. The submarine protocol aims to ensure that successful scans can be acquired in a time- and resource-efficient manner, without the need for sedation. This manuscript outlines the protocol and details its outcomes, as measured through the number of children who completed the scanning procedure and analysis of the degree of motion present in the acquired images. Seventy-six children aged between 5.8 and 6.9 years were trained using the submarine protocol and subsequently underwent DTI and rfMRI scanning. After completing the submarine protocol, 75 of the 76 children (99%) completed their DTI-scan and 72 children (95%) completed the full 35-minute scan session. Results of diffusion data, acquired in 75 children, showed that the motion in 60 of the scans (80%) did not exceed the threshold for excessive motion. In the rfMRI scans, this was the case for 62 of the 71 scans (87%). When placed in the context of previous studies, the motion data of the 5- and 6-year-old children reported here were as good as, or better than those previously reported for groups of older children (i.e., 8-year-olds). Overall, this study shows that the submarine protocol can be used successfully to acquire DTI and rfMRI scans in 5 and 6-year-old children, without the need for sedation or lengthy training procedures. PMID:24718364
Unal, Emre; Idilman, Ilkay Sedakat; Karçaaltıncaba, Muşturay
2017-02-01
New advances in liver magnetic resonance imaging (MRI) may enable diagnosis of unseen pathologies by conventional techniques. Normal T1 (550-620 ms for 1.5 T and 700-850 ms for 3 T), T2, T2* (>20 ms), T1rho (40-50 ms) mapping, proton density fat fraction (PDFF) (≤5%) and stiffness (2-3kPa) values can enable differentiation of a normal liver from chronic liver and diffuse diseases. Gd-EOB-DTPA can enable assessment of liver function by using postcontrast hepatobiliary phase or T1 reduction rate (normally above 60%). T1 mapping can be important for the assessment of fibrosis, amyloidosis and copper overload. T1rho mapping is promising for the assessment of liver collagen deposition. PDFF can allow objective treatment assessment in NAFLD and NASH patients. T2 and T2* are used for iron overload determination. MR fingerprinting may enable single slice acquisition and easy implementation of multiparametric MRI and follow-up of patients. Areas covered: T1, T2, T2*, PDFF and stiffness, diffusion weighted imaging, intravoxel incoherent motion imaging (ADC, D, D* and f values) and function analysis are reviewed. Expert commentary: Multiparametric MRI can enable biopsyless diagnosis and more objective staging of diffuse liver disease, cirrhosis and predisposing diseases. A comprehensive approach is needed to understand and overcome the effects of iron, fat, fibrosis, edema, inflammation and copper on MR relaxometry values in diffuse liver disease.
Update on the magnetic resonance imaging core of the Alzheimer's disease neuroimaging initiative.
Jack, Clifford R; Bernstein, Matt A; Borowski, Bret J; Gunter, Jeffrey L; Fox, Nick C; Thompson, Paul M; Schuff, Norbert; Krueger, Gunnar; Killiany, Ronald J; Decarli, Charles S; Dale, Anders M; Carmichael, Owen W; Tosun, Duygu; Weiner, Michael W
2010-05-01
Functions of the Alzheimer's Disease Neuroimaging Initiative (ADNI) magnetic resonance imaging (MRI) core fall into three categories: (1) those of the central MRI core laboratory at Mayo Clinic, Rochester, Minnesota, needed to generate high quality MRI data in all subjects at each time point; (2) those of the funded ADNI MRI core imaging analysis groups responsible for analyzing the MRI data; and (3) the joint function of the entire MRI core in designing and problem solving MR image acquisition, pre-processing, and analyses methods. The primary objective of ADNI was and continues to be improving methods for clinical trials in Alzheimer's disease. Our approach to the present ("ADNI-GO") and future ("ADNI-2," if funded) MRI protocol will be to maintain MRI methodological consistency in the previously enrolled "ADNI-1" subjects who are followed up longitudinally in ADNI-GO and ADNI-2. We will modernize and expand the MRI protocol for all newly enrolled ADNI-GO and ADNI-2 subjects. All newly enrolled subjects will be scanned at 3T with a core set of three sequence types: 3D T1-weighted volume, FLAIR, and a long TE gradient echo volumetric acquisition for micro hemorrhage detection. In addition to this core ADNI-GO and ADNI-2 protocol, we will perform vendor-specific pilot sub-studies of arterial spin-labeling perfusion, resting state functional connectivity, and diffusion tensor imaging. One of these sequences will be added to the core protocol on systems from each MRI vendor. These experimental sub-studies are designed to demonstrate the feasibility of acquiring useful data in a multicenter (but single vendor) setting for these three emerging MRI applications. Copyright 2010 The Alzheimer
NASA Astrophysics Data System (ADS)
Lin, Yuting; Ghijsen, Michael; Thayer, David; Nalcioglu, Orhan; Gulsen, Gultekin
2011-03-01
Dynamic contrast enhanced MRI (DCE-MRI) has been proven to be the most sensitive modality in detecting breast lesions. Currently available MR contrast agent, Gd-DTPA, is a low molecular weight extracellular agent and can diffuse freely from the vascular space into interstitial space. Due to this reason, DCE-MRI has low sensitivity in differentiating benign and malignant tumors. Meanwhile, diffuse optical tomography (DOT) can be used to provide enhancement kinetics of an FDA approved optical contrast agent, ICG, which behaves like a large molecular weight optical agent due to its binding to albumin. The enhancement kinetics of ICG may have a potential to distinguish between the malignant and benign tumors and hence improve the specificity. Our group has developed a high speed hybrid MRI-DOT system. The DOT is a fully automated, MR-compatible, multi-frequency and multi-spectral imaging system. Fischer-344 rats bearing subcutaneous R3230 tumor are injected simultaneously with Gd-DTPA (0.1nmol/kg) and IC-Green (2.5mg/kg). The enhancement kinetics of both contrast agents are recorded simultaneously with this hybrid MRI-DOT system and evaluated for different tumors.
Scurr, E D; Collins, D J; Temple, L; Karanjia, N; Leach, M O; Koh, D-M
2012-03-01
To describe the appearances of colorectal liver metastases on diffusion-weighted MRI (DW-MRI) and to compare these appearances with histopathology. 43 patients with colorectal liver metastases were evaluated using breath-hold DW-MRI (b-values 0, 150 and 500 s mm(-2)). The b=500 s mm(-2) DW-MRI were reviewed consensually for lesion size and appearance by two readers. 18/43 patients underwent surgery allowing radiological-pathological comparison. Tissue sections were reviewed by a pathologist, who classified metastases histologically as cellular, fibrotic, necrotic or mixed. The frequency of DW-MRI findings and histological features were compared using the χ(2) test. 84 metastases were found in 43 patients. On b=500 s mm(-2) DW-MRI, metastases showed three high signal intensity patterns: rim (55/84), uniform (23/84) and variegate (6/84). Of the 55 metastases showing rim pattern, 54 were >1 cm in diameter (p<0.01, χ(2) test). 25/84 metastases were surgically resected. Of these, 11/22 metastases >1 cm in diameter showed rim pattern and demonstrated central necrosis at histopathology (p=0.04, χ(2) test). No definite relationship was found between uniform and variegate patterns with histology. Rim high signal intensity was the most common appearance of colorectal liver metastases >1 cm diameter on DW-MRI at b-values of 500 s mm(-2), a finding attributable to central necrosis.
Winfield, Jessica M.; Payne, Geoffrey S.; Weller, Alex; deSouza, Nandita M.
2016-01-01
Abstract Multi-parametric magnetic resonance imaging (mpMRI) offers a unique insight into tumor biology by combining functional MRI techniques that inform on cellularity (diffusion-weighted MRI), vascular properties (dynamic contrast-enhanced MRI), and metabolites (magnetic resonance spectroscopy) and has scope to provide valuable information for prognostication and response assessment. Challenges in the application of mpMRI in the clinic include the technical considerations in acquiring good quality functional MRI data, development of robust techniques for analysis, and clinical interpretation of the results. This article summarizes the technical challenges in acquisition and analysis of multi-parametric MRI data before reviewing the key applications of multi-parametric MRI in clinical research and practice. PMID:27748710
2015-04-01
Current routine MRI examinations rely on the acquisition of qualitative images that have a contrast "weighted" for a mixture of (magnetic) tissue properties. Recently, a novel approach was introduced, namely MR Fingerprinting (MRF) with a completely different approach to data acquisition, post-processing and visualization. Instead of using a repeated, serial acquisition of data for the characterization of individual parameters of interest, MRF uses a pseudo randomized acquisition that causes the signals from different tissues to have a unique signal evolution or 'fingerprint' that is simultaneously a function of the multiple material properties under investigation. The processing after acquisition involves a pattern recognition algorithm to match the fingerprints to a predefined dictionary of predicted signal evolutions. These can then be translated into quantitative maps of the magnetic parameters of interest. MR Fingerprinting (MRF) is a technique that could theoretically be applied to most traditional qualitative MRI methods and replaces them with acquisition of truly quantitative tissue measures. MRF is, thereby, expected to be much more accurate and reproducible than traditional MRI and should improve multi-center studies and significantly reduce reader bias when diagnostic imaging is performed. Key Points • MR fingerprinting (MRF) is a new approach to data acquisition, post-processing and visualization.• MRF provides highly accurate quantitative maps of T1, T2, proton density, diffusion.• MRF may offer multiparametric imaging with high reproducibility, and high potential for multicenter/ multivendor studies.
Hu, Hui; Lu, Hong; He, Zhanping; Han, Xiangjun; Chen, Jing; Tu, Rong
2012-01-01
To investigate the effects of mRNA interference on aquaporin-4 expression in swollen tissue of rats with ischemic cerebral edema, and diagnose the significance of diffusion-weighted MRI, we injected 5 μL shRNA- aquaporin-4 (control group) or siRNA- aquaporin-4 solution (1:800) (RNA interference group) into the rat right basal ganglia immediately before occlusion of the middle cerebral artery. At 0.25 hours after occlusion of the middle cerebral artery, diffusion-weighted MRI displayed a high signal; within 2 hours, the relative apparent diffusion coefficient decreased markedly, aquaporin-4 expression increased rapidly, and intracellular edema was obviously aggravated; at 4 and 6 hours, the relative apparent diffusion coefficient slowly returned to control levels, aquaporin-4 expression slightly increased, and angioedema was observed. In the RNA interference group, during 0.25–6 hours after injection of siRNA- aquaporin-4 solution, the relative apparent diffusion coefficient slightly fluctuated and aquaporin-4 expression was upregulated; during 0.5–4 hours, the relative apparent diffusion coefficient was significantly higher, while aquaporin-4 expression was significantly lower when compared with the control group, and intracellular edema was markedly reduced; at 0.25 and 6 hours, the relative apparent diffusion coefficient and aquaporin-4 expression were similar when compared with the control group; obvious angioedema remained at 6 hours. Pearson's correlation test results showed that aquaporin-4 expression was negatively correlated with the apparent diffusion coefficient (r = −0.806, P < 0.01). These findings suggest that upregulated aquaporin-4 expression is likely to be the main molecular mechanism of intracellular edema and may be the molecular basis for decreased relative apparent diffusion coefficient. Aquaporin-4 gene interference can effectively inhibit the upregulation of aquaporin-4 expression during the stage of intracellular edema with time-effectiveness. Moreover, diffusion-weighted MRI can accurately detect intracellular edema. PMID:25657707
Zhang, Huiting; Xie, Junshuai; Xiao, Sa; Zhao, Xiuchao; Zhang, Ming; Shi, Lei; Wang, Ke; Wu, Guangyao; Sun, Xianping; Ye, Chaohui; Zhou, Xin
2018-05-04
To demonstrate the feasibility of compressed sensing (CS) to accelerate the acquisition of hyperpolarized (HP) 129 Xe multi-b diffusion MRI for quantitative assessments of lung microstructural morphometry. Six healthy subjects and six chronic obstructive pulmonary disease (COPD) subjects underwent HP 129 Xe multi-b diffusion MRI (b = 0, 10, 20, 30, and 40 s/cm 2 ). First, a fully sampled (FS) acquisition of HP 129 Xe multi-b diffusion MRI was conducted in one healthy subject. The acquired FS dataset was retrospectively undersampled in the phase encoding direction, and an optimal twofold undersampled pattern was then obtained by minimizing mean absolute error (MAE) between retrospective CS (rCS) and FS MR images. Next, the FS and CS acquisitions during separate breath holds were performed on five healthy subjects (including the above one). Additionally, the FS and CS synchronous acquisitions during a single breath hold were performed on the sixth healthy subject and one COPD subject. However, only CS acquisitions were conducted in the rest of the five COPD subjects. Finally, all the acquired FS, rCS and CS MR images were used to obtain morphometric parameters, including acinar duct radius (R), acinar lumen radius (r), alveolar sleeve depth (h), mean linear intercept (L m ), and surface-to-volume ratio (SVR). The Wilcoxon signed-rank test and the Bland-Altman plot were employed to assess the fidelity of the CS reconstruction. Moreover, the t-test was used to demonstrate the effectiveness of the multi-b diffusion MRI with CS in clinical applications. The retrospective results demonstrated that there was no statistically significant difference between rCS and FS measurements using the Wilcoxon signed-rank test (P > 0.05). Good agreement between measurements obtained with the CS and FS acquisitions during separate breath holds was demonstrated in Bland-Altman plots of slice differences. Specifically, the mean biases of the R, r, h, L m , and SVR between the CS and FS acquisitions were 1.0%, 2.6%, -0.03%, 1.5%, and -5.5%, respectively. Good agreement between measurements with the CS and FS acquisitions was also observed during the single breath-hold experiments. Furthermore, there were significant differences between the morphometric parameters for the healthy and COPD subjects (P < 0.05). Our study has shown that HP 129 Xe multi-b diffusion MRI with CS could be beneficial in lung microstructural assessments by acquiring less data while maintaining the consistent results with the FS acquisitions. © 2018 American Association of Physicists in Medicine.
Zhang, Li; Tang, Min; Min, Zhiqian; Lu, Jun; Lei, Xiaoyan; Zhang, Xiaoling
2016-06-01
Magnetic resonance imaging (MRI) is increasingly being used to examine patients with suspected breast cancer. To determine the diagnostic performance of combined dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) for breast cancer detection. A comprehensive search of the PUBMED, EMBASE, Web of Science, and Cochrane Library databases was performed up to September 2014. Statistical analysis included pooling of sensitivity and specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and diagnostic accuracy using the summary receiver operating characteristic (SROC). All analyses were conducted using STATA (version 12.0), RevMan (version 5.2), and Meta-Disc 1.4 software programs. Fourteen studies were analyzed, which included a total of 1140 patients with 1276 breast lesions. The pooled sensitivity and specificity of combined DCE-MRI and DWI were 91.6% and 85.5%, respectively. The pooled sensitivity and specificity of DWI-MRI were 86.0% and 75.6%, respectively. The pooled sensitivity and specificity of DCE-MRI were 93.2% and 71.1%. The area under the SROC curve (AUC-SROC) of combined DCE-MRI and DWI was 0.94, the DCE-MRI of 0.85. Deeks testing confirmed no significant publication bias in all studies. Combined DCE-MRI and DWI had superior diagnostic accuracy than either DCE-MRI or DWI alone for the diagnosis of breast cancer. © The Foundation Acta Radiologica 2015.
Van Hecke, Wim; Sijbers, Jan; De Backer, Steve; Poot, Dirk; Parizel, Paul M; Leemans, Alexander
2009-07-01
Although many studies are starting to use voxel-based analysis (VBA) methods to compare diffusion tensor images between healthy and diseased subjects, it has been demonstrated that VBA results depend heavily on parameter settings and implementation strategies, such as the applied coregistration technique, smoothing kernel width, statistical analysis, etc. In order to investigate the effect of different parameter settings and implementations on the accuracy and precision of the VBA results quantitatively, ground truth knowledge regarding the underlying microstructural alterations is required. To address the lack of such a gold standard, simulated diffusion tensor data sets are developed, which can model an array of anomalies in the diffusion properties of a predefined location. These data sets can be employed to evaluate the numerous parameters that characterize the pipeline of a VBA algorithm and to compare the accuracy, precision, and reproducibility of different post-processing approaches quantitatively. We are convinced that the use of these simulated data sets can improve the understanding of how different diffusion tensor image post-processing techniques affect the outcome of VBA. In turn, this may possibly lead to a more standardized and reliable evaluation of diffusion tensor data sets of large study groups with a wide range of white matter altering pathologies. The simulated DTI data sets will be made available online (http://www.dti.ua.ac.be).
Tissue microstructure estimation using a deep network inspired by a dictionary-based framework.
Ye, Chuyang
2017-12-01
Diffusion magnetic resonance imaging (dMRI) captures the anisotropic pattern of water displacement in the neuronal tissue and allows noninvasive investigation of the complex tissue microstructure. A number of biophysical models have been proposed to relate the tissue organization with the observed diffusion signals, so that the tissue microstructure can be inferred. The Neurite Orientation Dispersion and Density Imaging (NODDI) model has been a popular choice and has been widely used for many neuroscientific studies. It models the diffusion signal with three compartments that are characterized by distinct diffusion properties, and the parameters in the model describe tissue microstructure. In NODDI, these parameters are estimated in a maximum likelihood framework, where the nonlinear model fitting is computationally intensive. Therefore, efforts have been made to develop efficient and accurate algorithms for NODDI microstructure estimation, which is still an open problem. In this work, we propose a deep network based approach that performs end-to-end estimation of NODDI microstructure, which is named Microstructure Estimation using a Deep Network (MEDN). MEDN comprises two cascaded stages and is motivated by the AMICO algorithm, where the NODDI microstructure estimation is formulated in a dictionary-based framework. The first stage computes the coefficients of the dictionary. It resembles the solution to a sparse reconstruction problem, where the iterative process in conventional estimation approaches is unfolded and truncated, and the weights are learned instead of predetermined by the dictionary. In the second stage, microstructure properties are computed from the output of the first stage, which resembles the weighted sum of normalized dictionary coefficients in AMICO, and the weights are also learned. Because spatial consistency of diffusion signals can be used to reduce the effect of noise, we also propose MEDN+, which is an extended version of MEDN. MEDN+ allows incorporation of neighborhood information by inserting a stage with learned weights before the MEDN structure, where the diffusion signals in the neighborhood of a voxel are processed. The weights in MEDN or MEDN+ are jointly learned from training samples that are acquired with diffusion gradients densely sampling the q-space. We performed MEDN and MEDN+ on brain dMRI scans, where two shells each with 30 gradient directions were used, and measured their accuracy with respect to the gold standard. Results demonstrate that the proposed networks outperform the competing methods. Copyright © 2017 Elsevier B.V. All rights reserved.
Wang, Xin-Yan; Yan, Fei; Hao, Hui; Wu, Jian-Xing; Chen, Qing-Hua; Xian, Jun-Fang
2015-01-01
Background: Differentiating benign from malignant sinonsal lesions is essential for treatment planning as well as determining the patient's prognosis, but the differentiation is often difficult in clinical practice. The study aimed to determine whether the combination of diffusion-weighted (DW) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can improve the performance in differentiating benign from malignant sinonasal tumors. Methods: This retrospective study included 197 consecutive patients with sinonasal tumors (116 malignant tumors and 81 benign tumors). All patients underwent both DW and DCE-MRI in a 3-T magnetic resonance scanner. Two different settings of b values (0,700 and 0,1000 s/mm2) and two different strategies of region of interest (ROI) including whole slice (WS) and partial slice (PS) were used to calculate apparent diffusion coefficients (ADCs). A DW parameter with WS ADCsb0,1000 and two DCE-MRI parameters (time intensity curve [TIC] and time to peak enhancement [Tpeak]) were finally combined to use in differentiating the benign from the malignant tumors in this study. Results: The mean ADCs of malignant sinonasal tumors (WS ADCsb0,1000 = 1.084 × 10−3 mm2/s) were significantly lower than those of benign tumors (WS ADCsb0,1000 = 1.617 × 10−3 mm2/s, P < 0.001). The accuracy using WS ADCsb0,1000 alone was 83.7% in differentiating the benign from the malignant tumors (85.3% sensitivity, 81.2% specificity, 86.4% positive predictive value [PPV], and 79.5% negative predictive value [NPV]). The accuracy using DCE with Tpeak and TIC alone was 72.1% (69.1% sensitivity, 74.1% specificity, 77.5% PPV, and 65.1% NPV). Using DW-MRI parameter was superior than using DCE parameters in differentiation between benign and malignant sinonasal tumors (P < 0.001). The accuracy was 87.3% (90.5% sensitivity, 82.7% specificity, 88.2% PPV, and 85.9% NPV) using DW-MRI combined with DCE-MRI, which was superior than that using DCE-MRI alone or using DW-MRI alone (both P < 0.001) in differentiating the benign from the malignant tumors. Conclusions: Diffusion-weighted combined with DCE-MRI can improve imaging performance in differentiating benign from malignant sinonasal tumors, which has the potential to improve diagnostic accuracy and to provide added value in the management for these tumors. PMID:25698188
Kawashima, Hiroko; Miyati, Tosiaki; Ohno, Naoki; Ohno, Masako; Inokuchi, Masafumi; Ikeda, Hiroko; Gabata, Toshifumi
2018-04-01
To investigate whether the parameters derived from intravoxel incoherent motion (IVIM) MRI could differentiate phyllodes tumours (PTs) from fibroadenomas (FAs) by comparing the apparent diffusion coefficient (ADC) values. This retrospective study included 7 FAs, 10 benign PTs (BPTs), 4 borderline PTs, and one malignant PT. Biexponential analyses of IVIM were performed using a 3 T MRI scanner. Quantitative IVIM parameters [pure diffusion coefficient (D), perfusion-related diffusion coefficient (D*), and fraction (f)] were calculated. The ADC was also calculated using monoexponential fitting. The D and ADC values showed an increasing tendency in the order of FA, BPT, and borderline or malignant PT (BMPT). No significant difference was found in the D value among the three groups. The ADC value of the BMPT group was significantly higher than that of the FA group (p = 0.048). The D* value showed an increasing tendency in the order of BMPT, BPT, and FA, and the D* value of the BMPT group was significantly lower than that of the FA group (p = 0.048). The D* derived from IVIM and the ADC were helpful for differentiating between FA and BMPT. Advances in knowledge: IVIM MRI examination showed that the perfusion-related diffusion coefficient is lower in borderline and malignant PTs than in FAs and the opposite is true for the ADC.
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.
Magnetic resonance imaging based clinical research in Alzheimer's disease.
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.
Breschi, Gian Luca; Librizzi, Laura; Pastori, Chiara; Zucca, Ileana; Mastropietro, Alfonso; Cattalini, Alessandro; de Curtis, Marco
2010-08-01
Magnetic resonance imaging (MRI) during the acute phase of a stroke contributes to recognize ischemic regions and is potentially useful to predict clinical outcome. Yet, the functional significance of early MRI alterations during brain ischemia is not clearly understood. We achieved an experimental study to interpret MRI signals in a novel model of focal ischemia in the in vitro isolated guinea pig brain. By combining neurophysiological and morphological analysis with MR-imaging, we evaluated the suitability of MR to identify ischemic and peri-ischemic regions. Extracellular recordings demonstrated depolarizations in the ischemic core, but not in adjacent areas, where evoked activity was preserved and brief peri-infarct depolarizations occurred. Diffusion-weighted MRI and immunostaining performed after neurophysiological characterization showed changes restricted to the core region. Diffusion-weighted MR alterations did not include the penumbra region characterized by peri-infarct depolarizations. Therefore, by comparing neurophysiological, imaging and anatomical data, we can conclude that DW-MRI underestimates the extension of the tissue damage involved in brain ischemia.
MRI and clinical features of maple syrup urine disease: preliminary results in 10 cases.
Cheng, Ailan; Han, Lianshu; Feng, Yun; Li, Huimin; Yao, Rong; Wang, Dengbin; Jin, Biao
2017-01-01
We aimed to evaluate the magnetic resonance imaging (MRI) and clinical features of maple syrup urine disease (MSUD). This retrospective study consisted of 10 MSUD patients confirmed by genetic testing. All patients underwent brain MRI. Phenotype, genotype, and areas of brain injury on MRI were retrospectively reviewed. Six patients (60%) had the classic form of MSUD with BCKDHB mutation, three patients (30%) had the intermittent form (two with BCKDHA mutations and one with DBT mutation), and one patient (10%) had the thiamine-responsive form with DBT mutation. On diffusion-weighted imaging, nine cases presented restricted diffusion in myelinated areas, and one intermittent case with DBT mutation was normal. The classic form of MSUD involved the basal ganglia in six cases; the cerebellum, mesencephalon, pons, and supratentorial area in five cases; and the thalamus in four cases, respectively. The intermittent form involved the cerebellum, pons, and supratentorial area in two cases. The thiamine-responsive form involved the basal ganglia and supratentorial area. Our preliminary results indicate that patients with MSUD presented more commonly in classic form with BCKDHB mutation and displayed extensive brain injury on MRI.
[Optimization of diagnosis indicator selection and inspection plan by 3.0T MRI in breast cancer].
Jiang, Zhongbiao; Wang, Yunhua; He, Zhong; Zhang, Lejun; Zheng, Kai
2013-08-01
To optimize 3.0T MRI diagnosis indicator in breast cancer and to select the best MRI scan program. Totally 45 patients with breast cancers were collected, and another 35 patients with benign breast tumor served as the control group. All patients underwent 3.0T MRI, including T1- weighted imaging (T1WI), fat suppression of the T2-weighted imaging (T2WI), diffusion weighted imaging (DWI), 1H magnetic resonance spectroscopy (1H-MRS) and dynamic contrast enhanced (DCE) sequence. With operation pathology results as the gold standard in the diagnosis of breast diseases, the pathological results of benign and malignant served as dependent variables, and the diagnostic indicators of MRI were taken as independent variables. We put all the indicators of MRI examination under Logistic regression analysis, established the Logistic model, and optimized the diagnosis indicators of MRI examination to further improve MRI scan of breast cancer. By Logistic regression analysis, some indicators were selected in the equation, including the edge feature of the tumor, the time-signal intensity curve (TIC) type and the apparent diffusion coefficient (ADC) value when b=500 s/mm2. The regression equation was Logit (P)=-21.936+20.478X6+3.267X7+ 21.488X3. Valuable indicators in the diagnosis of breast cancer are the edge feature of the tumor, the TIC type and the ADC value when b=500 s/mm2. Combining conventional MRI scan, DWI and dynamic enhanced MRI is a better examination program, while MRS is the complementary program when diagnosis is difficult.
Lucas, Rita; Lopes Dias, João; Cunha, Teresa Margarida
2015-01-01
We aimed to evaluate the added value of diffusion-weighted imaging (DWI) to standard magnetic resonance imaging (MRI) for detecting post-treatment cervical cancer recurrence. The detection accuracy of T2-weighted (T2W) images was compared with that of T2W MRI combined with either dynamic contrast-enhanced (DCE) MRI or DWI. Thirty-eight women with clinically suspected uterine cervical cancer recurrence more than six months after treatment completion were examined with 1.5 Tesla MRI including T2W, DCE, and DWI sequences. Disease was confirmed histologically and correlated with MRI findings. The diagnostic performance of T2W imaging and its combination with either DCE or DWI were analyzed. Sensitivity, positive predictive value, and accuracy were calculated. Thirty-six women had histologically proven recurrence. The accuracy for recurrence detection was 80% with T2W/DCE MRI and 92.1% with T2W/DWI. The addition of DCE sequences did not significantly improve the diagnostic ability of T2W imaging, and this sequence combination misclassified two patients as falsely positive and seven as falsely negative. The T2W/DWI combination revealed a positive predictive value of 100% and only three false negatives. The addition of DWI to T2W sequences considerably improved the diagnostic ability of MRI. Our results support the inclusion of DWI in the initial MRI protocol for the detection of cervical cancer recurrence, leaving DCE sequences as an option for uncertain cases.
Stanzione, Arnaldo; Imbriaco, Massimo; Cocozza, Sirio; Fusco, Ferdinando; Rusconi, Giovanni; Nappi, Carmela; Mirone, Vincenzo; Mangiapia, Francesco; Brunetti, Arturo; Ragozzino, Alfonso; Longo, Nicola
2016-12-01
To prospectively determine the diagnostic accuracy of a biparametric 3T magnetic resonance imaging protocol (BP-MRI) for prostatic cancer detection, compared to a multiparametric MRI protocol (MP-MRI), in a biopsy naïve patient population. Eighty-two untreated patients (mean age 65±7.6years) with clinical suspicion of prostate cancer and/or altered prostate-specific antigen (PSA) levels underwent a MP-MRI, including T2-weighted imaging, diffusion-weighted imaging (with the correspondent apparent diffusion coefficient maps) and dynamic contrast enhanced sequence, followed by prostate biopsy. Two radiologists reviewed both the BP-MRI and the MP-MRI protocols to establish a radiological diagnosis. Receiver operating characteristics curves were obtained to determine the diagnostic performance of the two protocols. The mean PSA level was 8.8±8.1ng/ml. A total of 34 prostatic tumors were identified, with a Gleason score that ranged from 3+3 to 5+4. Of these 34 tumors, 29 were located within the peripheral zone and 5 in the transitional zone. BP-MRI and MP-MRI showed a similar performance in terms of overall diagnostic accuracy, with an area under the curve of 0.91 and 0.93, respectively (p=n.s.). BP-MRI prostate protocol is feasible for prostatic cancer detection compared to a standard MP-MRI protocol, requiring a shorter acquisition and interpretation time, with comparable diagnostic accuracy to the conventional protocol, without the administration of gadolinium-based contrast agent. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Polarized Helium to Image the Lung
NASA Astrophysics Data System (ADS)
Leduc, Michèle; Nacher, Pierre Jean
2005-05-01
The main findings of the european PHIL project (Polarised Helium to Image the Lung) are reported. State of the art optical pumping techniques for polarising 3He gas are described. MRI methodological improvements allow dynamical ventilation images with a good resolution, ultimately limited by gas diffusion. Diffusion imaging appears as a robust method of lung diagnosis. A discussion of the potential advantage of low field MRI is presented. Selected PHIL results for emphysema are given, with the perspectives that this joint work opens up for the future of respiratory medicine.
Whole-body diffusion-weighted MR image stitching and alignment to anatomical MRI
NASA Astrophysics Data System (ADS)
Ceranka, Jakub; Polfliet, Mathias; Lecouvet, Frederic; Michoux, Nicolas; Vandemeulebroucke, Jef
2017-02-01
Whole-body diffusion-weighted (WB-DW) MRI in combination with anatomical MRI has shown a great poten- tial in bone and soft tissue tumour detection, evaluation of lymph nodes and treatment response assessment. Because of the vast body coverage, whole-body MRI is acquired in separate stations, which are subsequently combined into a whole-body image. However, inter-station and inter-modality image misalignments can occur due to image distortions and patient motion during acquisition, which may lead to inaccurate representations of patient anatomy and hinder visual assessment. Automated and accurate whole-body image formation and alignment of the multi-modal MRI images is therefore crucial. We investigated several registration approaches for the formation or stitching of the whole-body image stations, followed by a deformable alignment of the multi- modal whole-body images. We compared a pairwise approach, where diffusion-weighted (DW) image stations were sequentially aligned to a reference station (pelvis), to a groupwise approach, where all stations were simultaneously mapped to a common reference space while minimizing the overall transformation. For each, a choice of input images and corresponding metrics was investigated. Performance was evaluated by assessing the quality of the obtained whole-body images, and by verifying the accuracy of the alignment with whole-body anatomical sequences. The groupwise registration approach provided the best compromise between the formation of WB- DW images and multi-modal alignment. The fully automated method was found to be robust, making its use in the clinic feasible.
Tensor Based Representation and Analysis of Diffusion-Weighted Magnetic Resonance Images
ERIC Educational Resources Information Center
Barmpoutis, Angelos
2009-01-01
Cartesian tensor bases have been widely used to model spherical functions. In medical imaging, tensors of various orders can approximate the diffusivity function at each voxel of a diffusion-weighted MRI data set. This approximation produces tensor-valued datasets that contain information about the underlying local structure of the scanned tissue.…
Retinal microvasculature and white matter microstructure: The Rotterdam Study.
Mutlu, Unal; Cremers, Lotte G M; de Groot, Marius; Hofman, Albert; Niessen, Wiro J; van der Lugt, Aad; Klaver, Caroline C W; Ikram, M Arfan; Vernooij, Meike W; Ikram, M Kamran
2016-09-06
To investigate whether retinal microvascular damage is related to normal-appearing white matter microstructure on diffusion tensor MRI. We included 2,436 participants (age ≥45 years) from the population-based Rotterdam Study (2005-2009) who had gradable retinal images and brain MRI scans. Retinal arteriolar and venular calibers were measured semiautomatically on fundus photographs. White matter microstructure was assessed using diffusion tensor MRI. We used linear regression models to investigate the associations of retinal vascular calibers with markers of normal-appearing white matter microstructure, adjusting for age, sex, the fellow vascular caliber, and additionally for structural MRI markers and cardiovascular risk factors. Narrower arterioles and wider venules were associated with poor white matter microstructure: adjusted difference in fractional anisotropy per SD decrease in arteriolar caliber -0.061 (95% confidence interval -0.106 to -0.016), increase in venular caliber -0.054 (-0.096 to -0.011), adjusted difference in mean diffusivity per SD decrease in arteriolar caliber 0.048 (0.007-0.088), and increase in venular caliber 0.047 (0.008-0.085). The associations for venules were more prominent in women. Retinal vascular calibers are related to normal-appearing white matter microstructure. This suggests that microvascular damage in the white matter is more widespread than visually detectable as white matter lesions. © 2016 American Academy of Neurology.
Vidić, Igor; Egnell, Liv; Jerome, Neil P; Teruel, Jose R; Sjøbakk, Torill E; Østlie, Agnes; Fjøsne, Hans E; Bathen, Tone F; Goa, Pål Erik
2018-05-01
Diffusion-weighted MRI (DWI) is currently one of the fastest developing MRI-based techniques in oncology. Histogram properties from model fitting of DWI are useful features for differentiation of lesions, and classification can potentially be improved by machine learning. To evaluate classification of malignant and benign tumors and breast cancer subtypes using support vector machine (SVM). Prospective. Fifty-one patients with benign (n = 23) and malignant (n = 28) breast tumors (26 ER+, whereof six were HER2+). Patients were imaged with DW-MRI (3T) using twice refocused spin-echo echo-planar imaging with echo time / repetition time (TR/TE) = 9000/86 msec, 90 × 90 matrix size, 2 × 2 mm in-plane resolution, 2.5 mm slice thickness, and 13 b-values. Apparent diffusion coefficient (ADC), relative enhanced diffusivity (RED), and the intravoxel incoherent motion (IVIM) parameters diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f) were calculated. The histogram properties (median, mean, standard deviation, skewness, kurtosis) were used as features in SVM (10-fold cross-validation) for differentiation of lesions and subtyping. Accuracies of the SVM classifications were calculated to find the combination of features with highest prediction accuracy. Mann-Whitney tests were performed for univariate comparisons. For benign versus malignant tumors, univariate analysis found 11 histogram properties to be significant differentiators. Using SVM, the highest accuracy (0.96) was achieved from a single feature (mean of RED), or from three feature combinations of IVIM or ADC. Combining features from all models gave perfect classification. No single feature predicted HER2 status of ER + tumors (univariate or SVM), although high accuracy (0.90) was achieved with SVM combining several features. Importantly, these features had to include higher-order statistics (kurtosis and skewness), indicating the importance to account for heterogeneity. Our findings suggest that SVM, using features from a combination of diffusion models, improves prediction accuracy for differentiation of benign versus malignant breast tumors, and may further assist in subtyping of breast cancer. 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1205-1216. © 2017 International Society for Magnetic Resonance in Medicine.
Makropoulos, Antonios; Robinson, Emma C; Schuh, Andreas; Wright, Robert; Fitzgibbon, Sean; Bozek, Jelena; Counsell, Serena J; Steinweg, Johannes; Vecchiato, Katy; Passerat-Palmbach, Jonathan; Lenz, Gregor; Mortari, Filippo; Tenev, Tencho; Duff, Eugene P; Bastiani, Matteo; Cordero-Grande, Lucilio; Hughes, Emer; Tusor, Nora; Tournier, Jacques-Donald; Hutter, Jana; Price, Anthony N; Teixeira, Rui Pedro A G; Murgasova, Maria; Victor, Suresh; Kelly, Christopher; Rutherford, Mary A; Smith, Stephen M; Edwards, A David; Hajnal, Joseph V; Jenkinson, Mark; Rueckert, Daniel
2018-06-01
The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity. Copyright © 2018 Elsevier Inc. All rights reserved.
Scala, Marcello; Morana, Giovanni; Milanaccio, Claudia; Pavanello, Marco; Nozza, Paolo; Garrè, Maria Luisa
2017-09-01
Atypical choroid plexus papillomas can metastasize in the form of leptomeningeal seeding. Postoperative chemotherapy is the recommended first-line treatment when gross-total removal is not achieved or in cases of disseminated disease. Here the authors report on 2 children with atypical choroid plexus papillomas and MRI findings of diffuse leptomeningeal enhancement at diagnosis, later presenting with spontaneous resolution of the leptomeningeal involvement after removal of the primary lesions. Observations in this report expand our knowledge about the natural history and biological behavior of these tumors and highlight the role of close neuroimaging surveillance in the management of atypical choroid plexus papillomas in cases with MRI evidence of diffuse leptomeningeal enhancement at presentation.
Functional magnetic resonance imaging in a low-field intraoperative scanner.
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
Multi-Parametric Spinal Cord MRI as Potential Progression Marker in Amyotrophic Lateral Sclerosis
El Mendili, Mohamed-Mounir; Cohen-Adad, Julien; Pelegrini-Issac, Mélanie; Rossignol, Serge; Morizot-Koutlidis, Régine; Marchand-Pauvert, Véronique; Iglesias, Caroline; Sangari, Sina; Katz, Rose; Lehericy, Stéphane; Benali, Habib; Pradat, Pierre-François
2014-01-01
Objective To evaluate multimodal MRI of the spinal cord in predicting disease progression and one-year clinical status in amyotrophic lateral sclerosis (ALS) patients. Materials and Methods After a first MRI (MRI1), 29 ALS patients were clinically followed during 12 months; 14/29 patients underwent a second MRI (MRI2) at 11±3 months. Cross-sectional area (CSA) that has been shown to be a marker of lower motor neuron degeneration was measured in cervical and upper thoracic spinal cord from T2-weighted images. Fractional anisotropy (FA), axial/radial/mean diffusivities (λ⊥, λ//, MD) and magnetization transfer ratio (MTR) were measured within the lateral corticospinal tract in the cervical region. Imaging metrics were compared with clinical scales: Revised ALS Functional Rating Scale (ALSFRS-R) and manual muscle testing (MMT) score. Results At MRI1, CSA correlated significantly (P<0.05) with MMT and arm ALSFRS-R scores. FA correlated significantly with leg ALFSRS-R scores. One year after MRI1, CSA predicted (P<0.01) arm ALSFSR-R subscore and FA predicted (P<0.01) leg ALSFRS-R subscore. From MRI1 to MRI2, significant changes (P<0.01) were detected for CSA and MTR. CSA rate of change (i.e. atrophy) highly correlated (P<0.01) with arm ALSFRS-R and arm MMT subscores rate of change. Conclusion Atrophy and DTI metrics predicted ALS disease progression. Cord atrophy was a better biomarker of disease progression than diffusion and MTR. Our study suggests that multimodal MRI could provide surrogate markers of ALS that may help monitoring the effect of disease-modifying drugs. PMID:24755826
Miura, Akiko; Kumabe, Yuri; Kimura, En; Yamashita, Satoshi; Ueda, Akihiko; Hirano, Teruyuki; Uchino, Makoto
2010-01-01
Adult-onset metachromatic leukodystrophy (MLD) often shows schizophrenia- or encephalopathy-like symptoms at an early stage, such as behavioural abnormalities, cognitive impairment, mood disorders and hallucinations. The authors report the case of an adult woman with MLD who had been given antipsychotic medication for schizophrenia. In the differential diagnosis, screening of auto-antibodies was important for ruling out other encephalopathies as she had a euthyroid Hashimoto thyroiditis. Diagnosis was based the results of MRI, nerve conduction velocity, sensory evoked potential, motor evoked potential, lysosomal enzyme activity and gene analysis studies. Brain MRI showed diffuse demyelination spreading from the deep white matter to subcortical area as high signals at the edges of these lesions in diffusion and apparent diffusion coefficient-map images with the U-fibres conserved. The authors diagnosed adult-onset MLD coexisting with euthyroid autoimmune Hashimoto thyroiditis. PMID:22798296
Evaluation of non-Gaussian diffusion in cardiac MRI.
McClymont, Darryl; Teh, Irvin; Carruth, Eric; Omens, Jeffrey; McCulloch, Andrew; Whittington, Hannah J; Kohl, Peter; Grau, Vicente; Schneider, Jürgen E
2017-09-01
The diffusion tensor model assumes Gaussian diffusion and is widely applied in cardiac diffusion MRI. However, diffusion in biological tissue deviates from a Gaussian profile as a result of hindrance and restriction from cell and tissue microstructure, and may be quantified better by non-Gaussian modeling. The aim of this study was to investigate non-Gaussian diffusion in healthy and hypertrophic hearts. Thirteen rat hearts (five healthy, four sham, four hypertrophic) were imaged ex vivo. Diffusion-weighted images were acquired at b-values up to 10,000 s/mm 2 . Models of diffusion were fit to the data and ranked based on the Akaike information criterion. The diffusion tensor was ranked best at b-values up to 2000 s/mm 2 but reflected the signal poorly in the high b-value regime, in which the best model was a non-Gaussian "beta distribution" model. Although there was considerable overlap in apparent diffusivities between the healthy, sham, and hypertrophic hearts, diffusion kurtosis and skewness in the hypertrophic hearts were more than 20% higher in the sheetlet and sheetlet-normal directions. Non-Gaussian diffusion models have a higher sensitivity for the detection of hypertrophy compared with the Gaussian model. In particular, diffusion kurtosis may serve as a useful biomarker for characterization of disease and remodeling in the heart. Magn Reson Med 78:1174-1186, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
Design and validation of diffusion MRI models of white matter
NASA Astrophysics Data System (ADS)
Jelescu, Ileana O.; Budde, Matthew D.
2017-11-01
Diffusion MRI is arguably the method of choice for characterizing white matter microstructure in vivo. Over the typical duration of diffusion encoding, the displacement of water molecules is conveniently on a length scale similar to that of the underlying cellular structures. Moreover, water molecules in white matter are largely compartmentalized which enables biologically-inspired compartmental diffusion models to characterize and quantify the true biological microstructure. A plethora of white matter models have been proposed. However, overparameterization and mathematical fitting complications encourage the introduction of simplifying assumptions that vary between different approaches. These choices impact the quantitative estimation of model parameters with potential detriments to their biological accuracy and promised specificity. First, we review biophysical white matter models in use and recapitulate their underlying assumptions and realms of applicability. Second, we present up-to-date efforts to validate parameters estimated from biophysical models. Simulations and dedicated phantoms are useful in assessing the performance of models when the ground truth is known. However, the biggest challenge remains the validation of the “biological accuracy” of estimated parameters. Complementary techniques such as microscopy of fixed tissue specimens have facilitated direct comparisons of estimates of white matter fiber orientation and densities. However, validation of compartmental diffusivities remains challenging, and complementary MRI-based techniques such as alternative diffusion encodings, compartment-specific contrast agents and metabolites have been used to validate diffusion models. Finally, white matter injury and disease pose additional challenges to modeling, which are also discussed. This review aims to provide an overview of the current state of models and their validation and to stimulate further research in the field to solve the remaining open questions and converge towards consensus.
In vivo lung morphometry with hyperpolarized 3He diffusion MRI: Theoretical background
NASA Astrophysics Data System (ADS)
Sukstanskii, A. L.; Yablonskiy, D. A.
2008-02-01
MRI-based study of 3He gas diffusion in lungs may provide important information on lung microstructure. Lung acinar airways can be described in terms of cylinders covered with alveolar sleeve [Haefeli-Bleuer, Weibel, Anat. Rec. 220 (1988) 401]. For relatively short diffusion times (on the order of a few ms) this geometry allows description of the 3He diffusion attenuated MR signal in lungs in terms of two diffusion coefficients—longitudinal (D) and transverse (D) with respect to the individual acinar airway axis [Yablonskiy et al., PNAS 99 (2002) 3111]. In this paper, empirical relationships between D and D and the geometrical parameters of airways and alveoli are found by means of computer Monte Carlo simulations. The effects of non-Gaussian signal behavior (dependence of D and D on b-value) are also taken into account. The results obtained are quantitatively valid in the physiologically important range of airway parameters characteristic of healthy lungs and lungs with mild emphysema. In lungs with advanced emphysema, the results provide only "apparent" characteristics but still could potentially be used to evaluate emphysema progression. This creates a basis for in vivo lung morphometry—evaluation of the geometrical parameters of acinar airways from hyperpolarized 3He diffusion MRI, despite the airways being too small to be resolved by direct imaging. These results also predict a rather substantial dependence of 3He ADC on the experimentally-controllable diffusion time, Δ. If Δ is decreased from 3 ms to 1 ms, the ADC in normal human lungs may increase by almost 50%. This effect should be taken into account when comparing experimental data obtained with different pulse sequences.
Thomsen, Felix Sebastian Leo; Delrieux, Claudio Augusto; de Luis-García, Rodrigo
2017-03-01
Descriptors extracted from magnetic resonance imaging (MRI) of the brain can be employed to locate and characterize a wide range of pathologies. Scalar measures are typically derived within a single-voxel unit, but neighborhood-based texture measures can also be applied. In this work, we propose a new set of descriptors to compute local texture characteristics from scalar measures of diffusion tensor imaging (DTI), such as mean and radial diffusivity, and fractional anisotropy. We employ weighted rotational invariant local operators, namely standard deviation, inter-quartile range, coefficient of variation, quartile coefficient of variation and skewness. Sensitivity and specificity of those texture descriptors were analyzed with tract-based spatial statistics of the white matter on a diffusion MRI group study of elderly healthy controls, patients with mild cognitive impairment (MCI), and mild or moderate Alzheimer's disease (AD). In addition, robustness against noise has been assessed with a realistic diffusion-weighted imaging phantom and the contamination of the local neighborhood with gray matter has been measured. The new texture operators showed an increased ability for finding formerly undetected differences between groups compared to conventional DTI methods. In particular, the coefficient of variation, quartile coefficient of variation, standard deviation and inter-quartile range of the mean and radial diffusivity detected significant differences even between previously not significantly discernible groups, such as MCI versus moderate AD and mild versus moderate AD. The analysis provided evidence of low contamination of the local neighborhood with gray matter and high robustness against noise. The local operators applied here enhance the identification and localization of areas of the brain where cognitive impairment takes place and thus indicate them as promising extensions in diffusion MRI group studies.
Design and validation of diffusion MRI models of white matter
Jelescu, Ileana O.; Budde, Matthew D.
2018-01-01
Diffusion MRI is arguably the method of choice for characterizing white matter microstructure in vivo. Over the typical duration of diffusion encoding, the displacement of water molecules is conveniently on a length scale similar to that of the underlying cellular structures. Moreover, water molecules in white matter are largely compartmentalized which enables biologically-inspired compartmental diffusion models to characterize and quantify the true biological microstructure. A plethora of white matter models have been proposed. However, overparameterization and mathematical fitting complications encourage the introduction of simplifying assumptions that vary between different approaches. These choices impact the quantitative estimation of model parameters with potential detriments to their biological accuracy and promised specificity. First, we review biophysical white matter models in use and recapitulate their underlying assumptions and realms of applicability. Second, we present up-to-date efforts to validate parameters estimated from biophysical models. Simulations and dedicated phantoms are useful in assessing the performance of models when the ground truth is known. However, the biggest challenge remains the validation of the “biological accuracy” of estimated parameters. Complementary techniques such as microscopy of fixed tissue specimens have facilitated direct comparisons of estimates of white matter fiber orientation and densities. However, validation of compartmental diffusivities remains challenging, and complementary MRI-based techniques such as alternative diffusion encodings, compartment-specific contrast agents and metabolites have been used to validate diffusion models. Finally, white matter injury and disease pose additional challenges to modeling, which are also discussed. This review aims to provide an overview of the current state of models and their validation and to stimulate further research in the field to solve the remaining open questions and converge towards consensus. PMID:29755979
Bouts, Mark J R J; Möller, Christiane; Hafkemeijer, Anne; van Swieten, John C; Dopper, Elise; van der Flier, Wiesje M; Vrenken, Hugo; Wink, Alle Meije; Pijnenburg, Yolande A L; Scheltens, Philip; Barkhof, Frederik; Schouten, Tijn M; de Vos, Frank; Feis, Rogier A; van der Grond, Jeroen; de Rooij, Mark; Rombouts, Serge A R B
2018-01-01
Overlapping clinical symptoms often complicate differential diagnosis between patients with Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD). Magnetic resonance imaging (MRI) reveals disease specific structural and functional differences that aid in differentiating AD from bvFTD patients. However, the benefit of combining structural and functional connectivity measures to-on a subject-basis-differentiate these dementia-types is not yet known. Anatomical, diffusion tensor (DTI), and resting-state functional MRI (rs-fMRI) of 30 patients with early stage AD, 23 with bvFTD, and 35 control subjects were collected and used to calculate measures of structural and functional tissue status. All measures were used separately or selectively combined as predictors for training an elastic net regression classifier. Each classifier's ability to accurately distinguish dementia-types was quantified by calculating the area under the receiver operating characteristic curves (AUC). Highest AUC values for AD and bvFTD discrimination were obtained when mean diffusivity, full correlations between rs-fMRI-derived independent components, and fractional anisotropy (FA) were combined (0.811). Similarly, combining gray matter density (GMD), FA, and rs-fMRI correlations resulted in highest AUC of 0.922 for control and bvFTD classifications. This, however, was not observed for control and AD differentiations. Classifications with GMD (0.940) and a GMD and DTI combination (0.941) resulted in similar AUC values (p = 0.41). Combining functional and structural connectivity measures improve dementia-type differentiations and may contribute to more accurate and substantiated differential diagnosis of AD and bvFTD patients. Imaging protocols for differential diagnosis may benefit from also including DTI and rs-fMRI.
[A case of MM1+2 Creutzfeldt-Jakob disease with a longitudinal study of EEG and MRI].
Katsube, Mizuho; Shiota, Yuri; Harada, Takayuki; Shibata, Hiroshi; Nagai, Atsushi
2013-11-01
We report a case of definite MM1 + 2 sporadic Creutzfeldt-Jakob disease (sCJD). A 66-year-old woman was admitted to our hospital with memory disturbance and disorientation for three months. On admission she presented a progressive cognitive insufficiency. Electroencephalography (EEG) revealed a frontal intermittent rhythmical delta activity (FIRDA) and the brain magnetic resonance imaging (MRI) showed high signal intensities in cerebral cortex on diffusion weighted images (DWI). After four months from the onset, she reached the akinetic mutism state followed by myoclonus. Follow up examination revealed that periodic synchronous discharge (PSD) was found in EEG, and DWI revealed enlargement of high signal intensity lesions in cerebral cortex. At seven months from the onset, PSD and high signal intensities of cortex became unclear with disappearance of myoclonus, and brain white matter lesions were evident on MRI. Serial studies of EEG and MRI revealed that PSD generalized from frontal lobe dominant pattern, while high signal intensity lesions of cortex diffusely increased on DWI. At ten months from the onset patient died. Pathological examination in brain showed moderate and diffuse neuronal cell loss and gliosis in cerebral cortex corresponding with DWI changes. The genotype at codon 129 of the prion protein (PrP) was homozygous methionine (MM) and the type of protease-resistant PrP (PrPres) was the mixed type of 1 and 2 in Western blot analysis. It has been rare to analyze the changes of EEG and MRI in the entire stage and to investigate pathological finding in the case of sCJD-MM1 + 2. A longitudinal examination of EEG and MRI is useful for early diagnosis of CJD. Also we could correlate these findings with clinical and histopathological phenotype.
Software Toolbox for Low-Frequency Conductivity and Current Density Imaging Using MRI.
Sajib, Saurav Z K; Katoch, Nitish; Kim, Hyung Joong; Kwon, Oh In; Woo, Eung Je
2017-11-01
Low-frequency conductivity and current density imaging using MRI includes magnetic resonance electrical impedance tomography (MREIT), diffusion tensor MREIT (DT-MREIT), conductivity tensor imaging (CTI), and magnetic resonance current density imaging (MRCDI). MRCDI and MREIT provide current density and isotropic conductivity images, respectively, using current-injection phase MRI techniques. DT-MREIT produces anisotropic conductivity tensor images by incorporating diffusion weighted MRI into MREIT. These current-injection techniques are finding clinical applications in diagnostic imaging and also in transcranial direct current stimulation (tDCS), deep brain stimulation (DBS), and electroporation where treatment currents can function as imaging currents. To avoid adverse effects of nerve and muscle stimulations due to injected currents, conductivity tensor imaging (CTI) utilizes B1 mapping and multi-b diffusion weighted MRI to produce low-frequency anisotropic conductivity tensor images without injecting current. This paper describes numerical implementations of several key mathematical functions for conductivity and current density image reconstructions in MRCDI, MREIT, DT-MREIT, and CTI. To facilitate experimental studies of clinical applications, we developed a software toolbox for these low-frequency conductivity and current density imaging methods. This MR-based conductivity imaging (MRCI) toolbox includes 11 toolbox functions which can be used in the MATLAB environment. The MRCI toolbox is available at http://iirc.khu.ac.kr/software.html . Its functions were tested by using several experimental datasets, which are provided together with the toolbox. Users of the toolbox can focus on experimental designs and interpretations of reconstructed images instead of developing their own image reconstruction softwares. We expect more toolbox functions to be added from future research outcomes. Low-frequency conductivity and current density imaging using MRI includes magnetic resonance electrical impedance tomography (MREIT), diffusion tensor MREIT (DT-MREIT), conductivity tensor imaging (CTI), and magnetic resonance current density imaging (MRCDI). MRCDI and MREIT provide current density and isotropic conductivity images, respectively, using current-injection phase MRI techniques. DT-MREIT produces anisotropic conductivity tensor images by incorporating diffusion weighted MRI into MREIT. These current-injection techniques are finding clinical applications in diagnostic imaging and also in transcranial direct current stimulation (tDCS), deep brain stimulation (DBS), and electroporation where treatment currents can function as imaging currents. To avoid adverse effects of nerve and muscle stimulations due to injected currents, conductivity tensor imaging (CTI) utilizes B1 mapping and multi-b diffusion weighted MRI to produce low-frequency anisotropic conductivity tensor images without injecting current. This paper describes numerical implementations of several key mathematical functions for conductivity and current density image reconstructions in MRCDI, MREIT, DT-MREIT, and CTI. To facilitate experimental studies of clinical applications, we developed a software toolbox for these low-frequency conductivity and current density imaging methods. This MR-based conductivity imaging (MRCI) toolbox includes 11 toolbox functions which can be used in the MATLAB environment. The MRCI toolbox is available at http://iirc.khu.ac.kr/software.html . Its functions were tested by using several experimental datasets, which are provided together with the toolbox. Users of the toolbox can focus on experimental designs and interpretations of reconstructed images instead of developing their own image reconstruction softwares. We expect more toolbox functions to be added from future research outcomes.
Bernardin, L; Douglas, N H M; Collins, D J; Giles, S L; O'Flynn, E A M; Orton, M; deSouza, N M
2014-02-01
To establish repeatability of apparent diffusion coefficients (ADCs) acquired from free-breathing diffusion-weighted magnetic resonance imaging (DW-MRI) in malignant lung lesions and investigate effects of lesion size, location and respiratory motion. Thirty-six malignant lung lesions (eight patients) were examined twice (1- to 5-h interval) using T1-weighted, T2-weighted and axial single-shot echo-planar DW-MRI (b = 100, 500, 800 s/mm(2)) during free-breathing. Regions of interest around target lesions on computed b = 800 s/mm(2) images by two independent observers yielded ADC values from maps (pixel-by-pixel fitting using all b values and a mono-exponential decay model). Intra- and inter-observer repeatability was assessed per lesion, per patient and by lesion size (> or <2 cm) or location. ADCs were similar between observers (mean ± SD, 1.15 ± 0.28 × 10(-3) mm(2)/s, observer 1; 1.15 ± 0.29 × 10(-3) mm(2)/s, observer 2). Intra-observer coefficients of variation of the mean [median] ADC per lesion and per patient were 11% [11.4%], 5.7% [5.7%] for observer 1 and 9.2% [9.5%], 3.9% [4.7%] for observer 2 respectively; inter-observer values were 8.9% [9.3%] (per lesion) and 3.0% [3.7%] (per patient). Inter-observer coefficient of variation (CoV) was greater for lesions <2 cm (n = 20) compared with >2 cm (n = 16) (10.8% vs 6.5% ADCmean, 11.3% vs 6.7% ADCmedian) and for mid (n = 14) vs apical (n = 9) or lower zone (n = 13) lesions (13.9%, 2.7%, 3.8% respectively ADCmean; 14.2%, 2.8%, 4.7% respectively ADCmedian). Free-breathing DW-MRI of whole lung achieves good intra- and inter-observer repeatability of ADC measurements in malignant lung tumours. • Diffusion-weighted MRI of the lung can be satisfactorily acquired during free-breathing • DW-MRI demonstrates high contrast between primary and metastatic lesions and normal lung • Apparent diffusion coefficient (ADC) measurements in lung tumours are repeatable and reliable • ADC offers potential in assessing response in lung metastases in clinical trials.
Yan, Ren; Haopeng, Pang; Xiaoyuan, Feng; Jinsong, Wu; Jiawen, Zhang; Chengjun, Yao; Tianming, Qiu; Ji, Xiong; Mao, Sheng; Yueyue, Ding; Yong, Zhang; Jianfeng, Luo; Zhenwei, Yao
2016-02-01
This study was conducted to compare the association of Gaussian and non-Gaussian magnetic resonance imaging (MRI)-derived parameters with histologic grade and MIB-1 (Ki-67 labeling) index (MI) in brain glioma. Sixty-five patients with pathologically confirmed glioma, who underwent diffusion-weighted MRI with 2 b values (0, 1000 s/mm(2)) and 22 b values (≤5000 s/mm(2)), respectively, were divided into three groups of grade II (n = 35), grade III (n = 8), and grade IV (n = 22). Comparisons by two groups were made for apparent diffusion coefficient (ADC), slow diffusion coefficient (Dslow), distributed diffusion coefficient (DDC), and heterogeneity index α. Analyses of receiver operating characteristic (ROC) curve were performed to maximize the area under the curve (AUC) for differentiating grade III + IV (high-grade glioma, HGG) from grade II (low-grade glioma, LGG) and grade IV (glioblastoma multiforme, GBM) from grade II + III (other grade glioma, OGG). Correlations with MI were analyzed for the MRI parameters. On tumor regions, the values of ADC, Dslow, DDC, and α were significantly higher in grade II [(1.37 ± 0.29, 0.70 ± 0.11, 1.39 ± 0.34) (×10(-3) mm(2)/s) and 0.88 ± 0.05, respectively] than in grade III [(0.99 ± 0.13, 0.55 ± 0.07, 1.04 ± 0.20) (×10(-3) mm(2)/s) and 0.80 ± 0.03, respectively] and grade IV [(1.03 ± 0.14, 0.50 ± 0.05, 1.02 ± 0.16) (×10(-3) mm(2)/s) and 0.76 ± 0.04, respectively] (all P < 0.001). The parameter α showed the highest AUCs of 0.950 and 0.922 in discriminating HGG from LGG and GBM from OGG, respectively. Significant correlations with histologic grade and MI were observed for the MRI parameters. The non-Gaussian MRI-derived parameters α and Dslow are superior to ADC in glioma grading, which are comparable with ADC as reliable biomarkers in noninvasively predicting the proliferation level of glioma malignancy.
Major Superficial White Matter Abnormalities in Huntington's Disease
Phillips, Owen R.; Joshi, Shantanu H.; Squitieri, Ferdinando; Sanchez-Castaneda, Cristina; Narr, Katherine; Shattuck, David W.; Caltagirone, Carlo; Sabatini, Umberto; Di Paola, Margherita
2016-01-01
Background: The late myelinating superficial white matter at the juncture of the cortical gray and white matter comprising the intracortical myelin and short-range association fibers has not received attention in Huntington's disease. It is an area of the brain that is late myelinating and is sensitive to both normal aging and neurodegenerative disease effects. Therefore, it may be sensitive to Huntington's disease processes. Methods: Structural MRI data from 25 Pre-symptomatic subjects, 24 Huntington's disease patients and 49 healthy controls was run through a cortical pattern-matching program. The surface corresponding to the white matter directly below the cortical gray matter was then extracted. Individual subject's Diffusion Tensor Imaging (DTI) data was aligned to their structural MRI data. Diffusivity values along the white matter surface were then sampled at each vertex point. DTI measures with high spatial resolution across the superficial white matter surface were then analyzed with the General Linear Model to test for the effects of disease. Results: There was an overall increase in the axial and radial diffusivity across much of the superficial white matter (p < 0.001) in Pre-symptomatic subjects compared to controls. In Huntington's disease patients increased diffusivity covered essentially the whole brain (p < 0.001). Changes are correlated with genotype (CAG repeat number) and disease burden (p < 0.001). Conclusions: This study showed broad abnormalities in superficial white matter even before symptoms are present in Huntington's disease. Since, the superficial white matter has a unique microstructure and function these abnormalities suggest it plays an important role in the disease. PMID:27242403
Multiparametric MRI changes persist beyond recovery in concussed adolescent hockey players
Manning, Kathryn Y.; Schranz, Amy; Bartha, Robert; Dekaban, Gregory A.; Barreira, Christy; Brown, Arthur; Fischer, Lisa; Asem, Kevin; Doherty, Timothy J.; Fraser, Douglas D.; Holmes, Jeff
2017-01-01
Objective: To determine whether multiparametric MRI data can provide insight into the acute and long-lasting neuronal sequelae after a concussion in adolescent athletes. Methods: Players were recruited from Bantam hockey leagues in which body checking is first introduced (male, age 11–14 years). Clinical measures, diffusion metrics, resting-state network and region-to-region functional connectivity patterns, and magnetic resonance spectroscopy absolute metabolite concentrations were analyzed from an independent, age-matched control group of hockey players (n = 26) and longitudinally in concussed athletes within 24 to 72 hours (n = 17) and 3 months (n = 14) after a diagnosed concussion. Results: There were diffusion abnormalities within multiple white matter tracts, functional hyperconnectivity, and decreases in choline 3 months after concussion. Tract-specific spatial statistics revealed a large region along the superior longitudinal fasciculus with the largest decreases in diffusivity measures, which significantly correlated with clinical deficits. This region also spatially intersected with probabilistic tracts connecting cortical regions where we found acute functional connectivity changes. Hyperconnectivity patterns at 3 months after concussion were present only in players with relatively less severe clinical outcomes, higher choline concentrations, and diffusivity indicative of relatively less axonal disruption. Conclusions: Changes persisted well after players' clinical scores had returned to normal and they had been cleared to return to play. Ongoing white matter maturation may make adolescent athletes particularly vulnerable to brain injury, and they may require extended recovery periods. The consequences of early brain injury for ongoing brain development and risk of more serious conditions such as second impact syndrome or neural degenerative processes need to be elucidated. PMID:29070666
Hagmann, Cornelia; Singer, Jitka; Latal, Beatrice; Knirsch, Walter; Makki, Malek
2016-03-01
The purpose of the study is to investigate the structural development of the corpus callosum in term neonates with congenital heart defect before and after surgery using diffusion tensor imaging and 3-dimensional T1-weighted magnetic resonance imaging (MRI). We compared parallel and radial diffusions, apparent diffusion coefficient (ADC), fractional anisotropy, and volume of 5 substructures of the corpus callosum: genu, rostral body, body, isthmus, and splenium. Compared to healthy controls, we found a significantly lower volume of the splenium and total corpus callosum and a higher radial diffusion and lower fractional anisotropy in the splenium of patients presurgery; a lower volume in all substructures in the postsurgery group; higher radial diffusion in the rostral body, body, and splenium; and a higher apparent diffusion coefficient in the splenium of postsurgery patients. Similar fractional anisotropy changes in congenital heart defect patients were reported in preterm infants. Our findings in apparent diffusion coefficient in the splenium of these patients (pre and postsurgery) are comparable to findings in preterm neonates with psychomotor delay. Delayed maturation of the isthmus was also reported in preterm infants. © The Author(s) 2015.
Hosseinbor, Ameer Pasha; Chung, Moo K; Wu, Yu-Chien; Alexander, Andrew L
2011-01-01
The estimation of the ensemble average propagator (EAP) directly from q-space DWI signals is an open problem in diffusion MRI. Diffusion spectrum imaging (DSI) is one common technique to compute the EAP directly from the diffusion signal, but it is burdened by the large sampling required. Recently, several analytical EAP reconstruction schemes for multiple q-shell acquisitions have been proposed. One, in particular, is Diffusion Propagator Imaging (DPI) which is based on the Laplace's equation estimation of diffusion signal for each shell acquisition. Viewed intuitively in terms of the heat equation, the DPI solution is obtained when the heat distribution between temperatuere measurements at each shell is at steady state. We propose a generalized extension of DPI, Bessel Fourier Orientation Reconstruction (BFOR), whose solution is based on heat equation estimation of the diffusion signal for each shell acquisition. That is, the heat distribution between shell measurements is no longer at steady state. In addition to being analytical, the BFOR solution also includes an intrinsic exponential smootheing term. We illustrate the effectiveness of the proposed method by showing results on both synthetic and real MR datasets.
Molina-Romero, Miguel; Gómez, Pedro A; Sperl, Jonathan I; Czisch, Michael; Sämann, Philipp G; Jones, Derek K; Menzel, Marion I; Menze, Bjoern H
2018-03-23
The compartmental nature of brain tissue microstructure is typically studied by diffusion MRI, MR relaxometry or their correlation. Diffusion MRI relies on signal representations or biophysical models, while MR relaxometry and correlation studies are based on regularized inverse Laplace transforms (ILTs). Here we introduce a general framework for characterizing microstructure that does not depend on diffusion modeling and replaces ill-posed ILTs with blind source separation (BSS). This framework yields proton density, relaxation times, volume fractions, and signal disentanglement, allowing for separation of the free-water component. Diffusion experiments repeated for several different echo times, contain entangled diffusion and relaxation compartmental information. These can be disentangled by BSS using a physically constrained nonnegative matrix factorization. Computer simulations, phantom studies, together with repeatability and reproducibility experiments demonstrated that BSS is capable of estimating proton density, compartmental volume fractions and transversal relaxations. In vivo results proved its potential to correct for free-water contamination and to estimate tissue parameters. Formulation of the diffusion-relaxation dependence as a BSS problem introduces a new framework for studying microstructure compartmentalization, and a novel tool for free-water elimination. © 2018 International Society for Magnetic Resonance in Medicine.
A midas plugin to enable construction of reproducible web-based image processing pipelines
Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A.; Oguz, Ipek
2013-01-01
Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline. PMID:24416016
A midas plugin to enable construction of reproducible web-based image processing pipelines.
Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A; Oguz, Ipek
2013-01-01
Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline.
Canales-Rodríguez, Erick J.; Caruyer, Emmanuel; Aja-Fernández, Santiago; Radua, Joaquim; Yurramendi Mendizabal, Jesús M.; Iturria-Medina, Yasser; Melie-García, Lester; Alemán-Gómez, Yasser; Thiran, Jean-Philippe; Sarró, Salvador; Pomarol-Clotet, Edith; Salvador, Raymond
2015-01-01
Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on many factors such as the number of coils and the methodology used to combine multichannel MRI signals. Indeed, the two prevailing methods for multichannel signal combination lead to noise patterns better described by Rician and noncentral Chi distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD) technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL) algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV) spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in human brain data. PMID:26470024
A phenome-wide examination of neural and cognitive function.
Poldrack, R A; Congdon, E; Triplett, W; Gorgolewski, K J; Karlsgodt, K H; Mumford, J A; Sabb, F W; Freimer, N B; London, E D; Cannon, T D; Bilder, R M
2016-12-06
This data descriptor outlines a shared neuroimaging dataset from the UCLA Consortium for Neuropsychiatric Phenomics, which focused on understanding the dimensional structure of memory and cognitive control (response inhibition) functions in both healthy individuals (130 subjects) and individuals with neuropsychiatric disorders including schizophrenia (50 subjects), bipolar disorder (49 subjects), and attention deficit/hyperactivity disorder (43 subjects). The dataset includes an extensive set of task-based fMRI assessments, resting fMRI, structural MRI, and high angular resolution diffusion MRI. The dataset is shared through the OpenfMRI project, and is formatted according to the Brain Imaging Data Structure (BIDS) standard.
Reduced acoustic noise in diffusion tensor imaging on a compact MRI system.
Tan, Ek T; Hardy, Christopher J; Shu, Yunhong; In, Myung-Ho; Guidon, Arnaud; Huston, John; Bernstein, Matt A; K F Foo, Thomas
2018-06-01
To investigate the feasibility of substantially reducing acoustic noise while performing diffusion tensor imaging (DTI) on a compact 3T (C3T) MRI scanner equipped with a 42-cm inner-diameter asymmetric gradient. A-weighted acoustic measurements were made using 10 mT/m-amplitude sinusoidal waveforms, corresponding to echo-planar imaging (EPI) echo spacing of 0.25 to 5.0 ms, on a conventional, whole-body 3T MRI and on the C3T. Acoustic measurements of DTI with trapezoidal EPI waveforms were then made at peak gradient performance on the C3T (80 mT/m amplitude, 700 T/m/s slew rate) and at derated performance (33 mT/m, 10 to 50 T/m/s) for acoustic noise reduction. DTI was acquired in two different phantoms and in seven human subjects, with and without gradient-derating corresponding to multi- and single-shot acquisitions, respectively. Sinusoidal waveforms on the C3T were quieter by 8.5 to 15.6 A-weighted decibels (dBA) on average as compared to the whole-body MRI. The derated multishot DTI acquisition noise level was only 8.7 dBA (at 13 T/m/s slew rate) above ambient, and was quieter than non-derated, single-shot DTI by 22.3 dBA; however, the scan time was almost quadrupled. Although derating resulted in negligible diffusivity differences in the phantoms, small biases in diffusivity measurements were observed in human subjects (apparent diffusion coefficient = +9.3 ± 8.8%, fractional anisotropy = +3.2 ± 11.2%, radial diffusivity = +9.4 ± 16.8%, parallel diffusivity = +10.3 ± 8.4%). The feasibility of achieving reduced acoustic noise levels with whole-brain DTI on the C3T MRI was demonstrated. Magn Reson Med 79:2902-2911, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
Stochastic DT-MRI connectivity mapping on the GPU.
McGraw, Tim; Nadar, Mariappan
2007-01-01
We present a method for stochastic fiber tract mapping from diffusion tensor MRI (DT-MRI) implemented on graphics hardware. From the simulated fibers we compute a connectivity map that gives an indication of the probability that two points in the dataset are connected by a neuronal fiber path. A Bayesian formulation of the fiber model is given and it is shown that the inversion method can be used to construct plausible connectivity. An implementation of this fiber model on the graphics processing unit (GPU) is presented. Since the fiber paths can be stochastically generated independently of one another, the algorithm is highly parallelizable. This allows us to exploit the data-parallel nature of the GPU fragment processors. We also present a framework for the connectivity computation on the GPU. Our implementation allows the user to interactively select regions of interest and observe the evolving connectivity results during computation. Results are presented from the stochastic generation of over 250,000 fiber steps per iteration at interactive frame rates on consumer-grade graphics hardware.
Voxelwise multivariate analysis of multimodality magnetic resonance imaging.
Naylor, Melissa G; Cardenas, Valerie A; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin
2014-03-01
Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remain a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. Copyright © 2013 Wiley Periodicals, Inc.
Scurr, E D; Collins, D J; Temple, L; Karanjia, N; Leach, M O; Koh, D-M
2012-01-01
Objective To describe the appearances of colorectal liver metastases on diffusion-weighted MRI (DW-MRI) and to compare these appearances with histopathology. Methods 43 patients with colorectal liver metastases were evaluated using breath-hold DW-MRI (b-values 0, 150 and 500 s mm–2). The b=500 s mm–2 DW-MRI were reviewed consensually for lesion size and appearance by two readers. 18/43 patients underwent surgery allowing radiological–pathological comparison. Tissue sections were reviewed by a pathologist, who classified metastases histologically as cellular, fibrotic, necrotic or mixed. The frequency of DW-MRI findings and histological features were compared using the χ2 test. Results 84 metastases were found in 43 patients. On b=500 s mm–2 DW-MRI, metastases showed three high signal intensity patterns: rim (55/84), uniform (23/84) and variegate (6/84). Of the 55 metastases showing rim pattern, 54 were >1 cm in diameter (p<0.01, χ2 test). 25/84 metastases were surgically resected. Of these, 11/22 metastases >1 cm in diameter showed rim pattern and demonstrated central necrosis at histopathology (p=0.04, χ2 test). No definite relationship was found between uniform and variegate patterns with histology. Conclusion Rim high signal intensity was the most common appearance of colorectal liver metastases >1 cm diameter on DW-MRI at b-values of 500 s mm–2, a finding attributable to central necrosis. PMID:21224302
Wallerian Degeneration Beyond the Corticospinal Tracts: Conventional and Advanced MRI Findings.
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.
Delouche, Aurélie; Attyé, Arnaud; Heck, Olivier; Grand, Sylvie; Kastler, Adrian; Lamalle, Laurent; Renard, Felix; Krainik, Alexandre
2016-01-01
Mild traumatic brain injury (mTBI) is a leading cause of disability in adults, many of whom report a distressing combination of physical, emotional and cognitive symptoms, collectively known as post-concussion syndrome, that persist after the injury. Significant developments in magnetic resonance diffusion imaging, involving voxel-based quantitative analysis through the measurement of fractional anisotropy or mean diffusivity, have enhanced our knowledge on the different stages of mTBI pathophysiology. Other diffusion imaging-derived techniques, including diffusion kurtosis imaging with multi-shell diffusion and high-order tractography models, have recently demonstrated their usefulness in mTBI. Our review starts by briefly outlining the physical basis of diffusion tensor imaging including the pitfalls for use in brain trauma, before discussing findings from diagnostic trials testing its usefulness in assessing brain structural changes in patients with mTBI. Use of different post-processing techniques for the diffusion imaging data, identified the corpus callosum as the most frequently injured structure in mTBI, particularly at sub-acute and chronic stages, and a crucial location for evaluating functional outcome. However, structural changes appear too subtle for identification using traditional diffusion biomarkers, thus disallowing expansion of these techniques into clinical practice. In this regard, more advanced diffusion techniques are promising in the assessment of this complex disease. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Temporal and spatial profile of brain diffusion-weighted MRI after cardiac arrest
Mlynash, M.; Campbell, D.M.; Leproust, E.M.; Fischbein, N.J.; Bammer, R.; Eyngorn, I.; Hsia, A.W.; Moseley, M.; Wijman, C.A.C.
2010-01-01
Background and Purpose Diffusion-weighted MRI (DWI) of the brain is a promising technique to help predict functional outcome in comatose survivors of cardiac arrest. We aimed to evaluate prospectively the temporal-spatial profile of brain apparent diffusion coefficient (ADC) changes in comatose survivors during the first 8 days after cardiac arrest. Methods ADC values were measured by two independent and blinded investigators in predefined brain regions in 18 good and 15 poor outcome patients with 38 brain MRIs, and compared with 14 normal controls. The same brain regions were also assessed qualitatively by two other independent and blinded investigators. Results In poor outcome patients, cortical structures, in particular the occipital and temporal lobes, and the putamen exhibited the most profound ADC reductions, which were noted as early as 1.5 days and reached nadir between 3 to 5 days after the arrest. Conversely, when compared to normal controls, good outcome patients exhibited increased diffusivity, in particular in the hippocampus, temporal and occipital lobes, and corona radiata. By the qualitative MRI readings, one or more cortical gray matter structures were read as moderately-to-severely abnormal in all poor outcome patients imaged beyond 54 hours after the arrest, but not in the three patients imaged earlier. Conclusions Brain DWI changes in comatose post-cardiac arrest survivors in the first week after the arrest are region- and time-dependent and differ between good and poor outcome patients. With the increasing use of MRI in this context, it is important to be aware of these relationships. PMID:20595666
A Hough Transform Global Probabilistic Approach to Multiple-Subject Diffusion MRI Tractography
Aganj, Iman; Lenglet, Christophe; Jahanshad, Neda; Yacoub, Essa; Harel, Noam; Thompson, Paul M.; Sapiro, Guillermo
2011-01-01
A global probabilistic fiber tracking approach based on the voting process provided by the Hough transform is introduced in this work. The proposed framework tests candidate 3D curves in the volume, assigning to each one a score computed from the diffusion images, and then selects the curves with the highest scores as the potential anatomical connections. The algorithm avoids local minima by performing an exhaustive search at the desired resolution. The technique is easily extended to multiple subjects, considering a single representative volume where the registered high-angular resolution diffusion images (HARDI) from all the subjects are non-linearly combined, thereby obtaining population-representative tracts. The tractography algorithm is run only once for the multiple subjects, and no tract alignment is necessary. We present experimental results on HARDI volumes, ranging from simulated and 1.5T physical phantoms to 7T and 4T human brain and 7T monkey brain datasets. PMID:21376655
Seizeur, Romuald; Magro, Elsa; Prima, Sylvain; Wiest-Daesslé, Nicolas; Maumet, Camille; Morandi, Xavier
2014-03-01
Cerebral hemispheres represent both structural and functional asymmetry, which differs among right- and left-handers. The left hemisphere is specialised for language and task execution of the right hand in right-handers. We studied the corticospinal tract in right- and left-handers by diffusion tensor imaging and tractography. The present study aimed at revealing a morphological difference resulting from a region of interest (ROI) obtained by functional MRI (fMRI). Twenty-five healthy participants (right-handed: 15, left-handed: 10) were enrolled in our assessment of morphological, functional and diffusion tensor MRI. Assessment of brain fibre reconstruction (tractography) was done using a deterministic algorithm. Fractional anisotropy (FA) and mean diffusivity (MD) were studied on the tractography traces of the reference slices. We observed a significant difference in number of leftward fibres based on laterality. The significant difference in regard to FA and MD was based on the slices obtained at different levels and the laterality index. We found left-hand asymmetry and right-hand asymmetry, respectively, for the MD and FA. Our study showed the presence of hemispheric asymmetry based on laterality index in right- and left-handers. These results are inconsistent with some studies and consistent with others. The reported difference in hemispheric asymmetry could be related to dexterity (manual skill).
Rasova, Kamila; Prochazkova, Marie; Tintera, Jaroslav; Ibrahim, Ibrahim; Zimova, Denisa; Stetkarova, Ivana
2015-03-01
There is still little scientific evidence for the efficacy of neurofacilitation approaches and their possible influence on brain plasticity and adaptability. In this study, the outcome of a new kind of neurofacilitation approach, motor programme activating therapy (MPAT), was evaluated on the basis of a set of clinical functions and with MRI. Eighteen patients were examined four times with standardized clinical tests and diffusion tensor imaging to monitor changes without therapy, immediately after therapy and 1 month after therapy. Moreover, the strength of effective connectivity was analysed before and after therapy. Patients underwent a 1-h session of MPAT twice a week for 2 months. The data were analysed by nonparametric tests of association and were subsequently statistically evaluated. The therapy led to significant improvement in clinical functions, significant increment of fractional anisotropy and significant decrement of mean diffusivity, and decrement of effective connectivity at supplementary motor areas was observed immediately after the therapy. Changes in clinical functions and diffusion tensor images persisted 1 month after completing the programme. No statistically significant changes in clinical functions and no differences in MRI-diffusion tensor images were observed without physiotherapy. Positive immediate and long-term effects of MPAT on clinical and brain functions, as well as brain microstructure, were confirmed.
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.
Optimizing Filter-Probe Diffusion Weighting in the Rat Spinal Cord for Human Translation
Budde, Matthew D.; Skinner, Nathan P.; Muftuler, L. Tugan; Schmit, Brian D.; Kurpad, Shekar N.
2017-01-01
Diffusion tensor imaging (DTI) is a promising biomarker of spinal cord injury (SCI). In the acute aftermath, DTI in SCI animal models consistently demonstrates high sensitivity and prognostic performance, yet translation of DTI to acute human SCI has been limited. In addition to technical challenges, interpretation of the resulting metrics is ambiguous, with contributions in the acute setting from both axonal injury and edema. Novel diffusion MRI acquisition strategies such as double diffusion encoding (DDE) have recently enabled detection of features not available with DTI or similar methods. In this work, we perform a systematic optimization of DDE using simulations and an in vivo rat model of SCI and subsequently implement the protocol to the healthy human spinal cord. First, two complementary DDE approaches were evaluated using an orientationally invariant or a filter-probe diffusion encoding approach. While the two methods were similar in their ability to detect acute SCI, the filter-probe DDE approach had greater predictive power for functional outcomes. Next, the filter-probe DDE was compared to an analogous single diffusion encoding (SDE) approach, with the results indicating that in the spinal cord, SDE provides similar contrast with improved signal to noise. In the SCI rat model, the filter-probe SDE scheme was coupled with a reduced field of view (rFOV) excitation, and the results demonstrate high quality maps of the spinal cord without contamination from edema and cerebrospinal fluid, thereby providing high sensitivity to injury severity. The optimized protocol was demonstrated in the healthy human spinal cord using the commercially-available diffusion MRI sequence with modifications only to the diffusion encoding directions. Maps of axial diffusivity devoid of CSF partial volume effects were obtained in a clinically feasible imaging time with a straightforward analysis and variability comparable to axial diffusivity derived from DTI. Overall, the results and optimizations describe a protocol that mitigates several difficulties with DTI of the spinal cord. Detection of acute axonal damage in the injured or diseased spinal cord will benefit the optimized filter-probe diffusion MRI protocol outlined here. PMID:29311786
Rayhan, Rakib U; Stevens, Benson W; Timbol, Christian R; Adewuyi, Oluwatoyin; Walitt, Brian; VanMeter, John W; Baraniuk, James N
2013-01-01
Gulf War exposures in 1990 and 1991 have caused 25% to 30% of deployed personnel to develop a syndrome of chronic fatigue, pain, hyperalgesia, cognitive and affective dysfunction. Gulf War veterans (n = 31) and sedentary veteran and civilian controls (n = 20) completed fMRI scans for diffusion tensor imaging. A combination of dolorimetry, subjective reports of pain and fatigue were correlated to white matter diffusivity properties to identify tracts associated with symptom constructs. Gulf War Illness subjects had significantly correlated fatigue, pain, hyperalgesia, and increased axial diffusivity in the right inferior fronto-occipital fasciculus. ROC generated thresholds and subsequent binary regression analysis predicted CMI classification based upon axial diffusivity in the right inferior fronto-occipital fasciculus. These correlates were absent for controls in dichotomous regression analysis. The right inferior fronto-occipital fasciculus may be a potential biomarker for Gulf War Illness. This tract links cortical regions involved in fatigue, pain, emotional and reward processing, and the right ventral attention network in cognition. The axonal neuropathological mechanism(s) explaining increased axial diffusivity may account for the most prominent symptoms of Gulf War Illness.
Ferradal, Silvina L; Eggebrecht, Adam T; Hassanpour, Mahlega; Snyder, Abraham Z; Culver, Joseph P
2014-01-15
Diffuse optical imaging (DOI) is increasingly becoming a valuable neuroimaging tool when fMRI is precluded. Recent developments in high-density diffuse optical tomography (HD-DOT) overcome previous limitations of sparse DOI systems, providing improved image quality and brain specificity. These improvements in instrumentation prompt the need for advancements in both i) realistic forward light modeling for accurate HD-DOT image reconstruction, and ii) spatial normalization for voxel-wise comparisons across subjects. Individualized forward light models derived from subject-specific anatomical images provide the optimal inverse solutions, but such modeling may not be feasible in all situations. In the absence of subject-specific anatomical images, atlas-based head models registered to the subject's head using cranial fiducials provide an alternative solution. In addition, a standard atlas is attractive because it defines a common coordinate space in which to compare results across subjects. The question therefore arises as to whether atlas-based forward light modeling ensures adequate HD-DOT image quality at the individual and group level. Herein, we demonstrate the feasibility of using atlas-based forward light modeling and spatial normalization methods. Both techniques are validated using subject-matched HD-DOT and fMRI data sets for visual evoked responses measured in five healthy adult subjects. HD-DOT reconstructions obtained with the registered atlas anatomy (i.e. atlas DOT) had an average localization error of 2.7mm relative to reconstructions obtained with the subject-specific anatomical images (i.e. subject-MRI DOT), and 6.6mm relative to fMRI data. At the group level, the localization error of atlas DOT reconstruction was 4.2mm relative to subject-MRI DOT reconstruction, and 6.1mm relative to fMRI. These results show that atlas-based image reconstruction provides a viable approach to individual head modeling for HD-DOT when anatomical imaging is not available. Copyright © 2013. Published by Elsevier Inc.
Thomalla, Götz; Boutitie, Florent; Fiebach, Jochen B; Simonsen, Claus Z; Nighoghossian, Norbert; Pedraza, Salvador; Lemmens, Robin; Roy, Pascal; Muir, Keith W; Ebinger, Martin; Ford, Ian; Cheng, Bastian; Galinovic, Ivana; Cho, Tae-Hee; Puig, Josep; Thijs, Vincent; Endres, Matthias; Fiehler, Jens; Gerloff, Christian
2017-03-01
We describe clinical and magnetic resonance imaging (MRI) characteristics of stroke patients with unknown time of symptom onset potentially eligible for thrombolysis from a large prospective cohort. We analyzed baseline data from WAKE-UP (Efficacy and Safety of MRI-Based Thrombolysis in Wake-Up Stroke: A Randomized, Doubleblind, Placebo-Controlled Trial), an investigator-initiated, randomized, placebo-controlled trial of MRI-based thrombolysis in stroke patients with unknown time of symptom onset. MRI judgment included assessment of the mismatch between visibility of the acute ischemic lesion on diffusion-weighted imaging and fluid-attenuated inversion recovery. Of 1005 patients included, diffusion-weighted imaging and fluid-attenuated inversion recovery mismatch was present in 479 patients (48.0%). Patients with daytime-unwitnessed stroke (n=138, 13.7%) had a shorter delay between symptom recognition and hospital arrival (1.5 versus 1.8 hours; P =0.002), a higher National Institutes of Stroke Scale score on admission (8 versus 6; P <0.001), and more often aphasia (72.5% versus 34.0%; P <0.001) when compared with stroke patients waking up from nighttime sleep. Frequency of diffusion-weighted imaging and fluid-attenuated inversion recovery mismatch was comparable between both groups (43.7% versus 48.7%; P =0.30). Almost half of the patients with unknown time of symptom onset stroke otherwise eligible for thrombolysis had MRI findings making them likely to be within a time window for safe and effective thrombolysis. Patients with daytime onset unwitnessed stroke differ from wake-up stroke patients with regards to clinical characteristics but are comparable in terms of MRI characteristics of lesion age. URL: http://www.clinicaltrials.gov. Unique identifier: NCT01525290. URL: https://www.clinicaltrialsregister.eu. Unique identifier: 2011-005906-32. © 2017 American Heart Association, Inc.
EEG-fMRI evaluation of patients with mesial temporal lobe sclerosis.
Avesani, Mirko; Giacopuzzi, Silvia; Bongiovanni, Luigi Giuseppe; Borelli, Paolo; Cerini, Roberto; Pozzi Mucelli, Roberto; Fiaschi, Antonio
2014-02-01
This preliminary study sought more information on blood oxygen level dependent (BOLD) activation, especially contralateral temporal/extratemporal spread, during continuous EEG-fMRI recordings in four patients with mesial temporal sclerosis (MTS). In two patients, EEG showed unilateral focal activity during the EEG-fMRI session concordant with the interictal focus previously identified with standard and video-poly EEG. In the other two patients EEG demonstrated a contralateral diffusion of the irritative focus. In the third patient (with the most drug-resistant form and also extratemporal clinical signs), there was an extratemporal diffusion over frontal regions, ipsilateral to the irritative focus. fMRI analysis confirmed a single activation in the mesial temporal region in two patients whose EEG showed unilateral focal activity, while it demonstrated a bilateral activation in the mesial temporal regions in the other two patients. In the third patient, fMRI demonstrated an activation in the supplementary motxor area. This study confirms the most significant activation with a high firing rate of the irritative focus, but also suggests the importance of using new techniques (such as EEG-fMRI to examine cerebral blood flow) to identify the controlateral limbic activation, and any other extratemporal activations, possible causes of drug resistance in MTS that may require a more precise pre-surgical evaluation with invasive techniques.
EEG-fMRI Evaluation of Patients with Mesial Temporal Lobe Sclerosis
Avesani, Mirko; Giacopuzzi, Silvia; Bongiovanni, Luigi Giuseppe; Borelli, Paolo; Cerini, Roberto; Pozzi Mucelli, Roberto; Fiaschi, Antonio
2014-01-01
Summary This preliminary study sought more information on blood oxygen level dependent (BOLD) activation, especially contralateral temporal/extratemporal spread, during continuous EEG-fMRI recordings in four patients with mesial temporal sclerosis (MTS). In two patients, EEG showed unilateral focal activity during the EEG-fMRI session concordant with the interictal focus previously identified with standard and video-poly EEG. In the other two patients EEG demonstrated a contralateral diffusion of the irritative focus. In the third patient (with the most drug-resistant form and also extratemporal clinical signs), there was an extratemporal diffusion over frontal regions, ipsilateral to the irritative focus. fMRI analysis confirmed a single activation in the mesial temporal region in two patients whose EEG showed unilateral focal activity, while it demonstrated a bilateral activation in the mesial temporal regions in the other two patients. In the third patient, fMRI demonstrated an activation in the supplementary motxor area. This study confirms the most significant activation with a high firing rate of the irritative focus, but also suggests the importance of using new techniques (such as EEG-fMRI to examine cerebral blood flow) to identify the controlateral limbic activation, and any other extratemporal activations, possible causes of drug resistance in MTS that may require a more precise pre-surgical evaluation with invasive techniques. PMID:24571833
Studying Autism Spectrum Disorder with Structural and Diffusion Magnetic Resonance Imaging: A Survey
Ismail, Marwa M. T.; Keynton, Robert S.; Mostapha, Mahmoud M. M. O.; ElTanboly, Ahmed H.; Casanova, Manuel F.; Gimel'farb, Georgy L.; El-Baz, Ayman
2016-01-01
Magnetic resonance imaging (MRI) modalities have emerged as powerful means that facilitate non-invasive clinical diagnostics of various diseases and abnormalities since their inception in the 1980s. Multiple MRI modalities, such as different types of the sMRI and DTI, have been employed to investigate facets of ASD in order to better understand this complex syndrome. This paper reviews recent applications of structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI), to study autism spectrum disorder (ASD). Main reported findings are sometimes contradictory due to different age ranges, hardware protocols, population types, numbers of participants, and image analysis parameters. The primary anatomical structures, such as amygdalae, cerebrum, and cerebellum, associated with clinical-pathological correlates of ASD are highlighted through successive life stages, from infancy to adulthood. This survey demonstrates the absence of consistent pathology in the brains of autistic children and lack of research investigations in patients under 2 years of age in the literature. The known publications also emphasize advances in data acquisition and analysis, as well as significance of multimodal approaches that combine resting-state, task-evoked, and sMRI measures. Initial results obtained with the sMRI and DTI show good promise toward the early and non-invasive ASD diagnostics. PMID:27242476
MRI Features of Hepatocellular Carcinoma Related to Biologic Behavior
Cho, Eun-Suk
2015-01-01
Imaging studies including magnetic resonance imaging (MRI) play a crucial role in the diagnosis and staging of hepatocellular carcinoma (HCC). Several recent studies reveal a large number of MRI features related to the prognosis of HCC. In this review, we discuss various MRI features of HCC and their implications for the diagnosis and prognosis as imaging biomarkers. As a whole, the favorable MRI findings of HCC are small size, encapsulation, intralesional fat, high apparent diffusion coefficient (ADC) value, and smooth margins or hyperintensity on the hepatobiliary phase of gadoxetic acid-enhanced MRI. Unfavorable findings include large size, multifocality, low ADC value, non-smooth margins or hypointensity on hepatobiliary phase images. MRI findings are potential imaging biomarkers in patients with HCC. PMID:25995679
Unusual MRI findings in an immunocompetent patient with EBV encephalitis: a case report
2011-01-01
Blackground It is well-known that Epstein-Barr virus (EBV) can affect the central nervous system (CNS). Case presentation Herein the authors report unusual timely Magnetic Resonance Imaging (MRI) brain scan findings in an immunocompetent patient with EBV encephalitis. Diffusion weighted MRI sequence performed during the acute phase of the disease was normal, whereas the Fast Relaxation Fast Spin Echo T2 image showed diffuse signal intensity changes in white matter. The enhancement pattern suggested an inflammatory response restricted to the brain microcirculation. Acyclovir and corticosteroid therapy was administered. After three weeks, all signal intensities returned to normal and the patient showed clinical recovery. Conclusion This report demonstrates that EBV in an immunocompetent adult can present with diffuse, reversible brain white matter involvement in the acute phase of mononucleosis. Moreover, our case suggests that a negative DWI sequence is associated with a favorable improvement in severe EBV CNS infection. More extensive studies are needed to assess what other instrumental data can help to distinguish viral lesions from other causes in the acute phase of disease. PMID:21435249
Is contrast enhancement needed for diagnostic prostate MRI?
Rondoni, Valeria; Aisa, Maria Cristina; Martorana, Eugenio; D’Andrea, Alfredo; Malaspina, Corrado Maria; Orlandi, Agostino; Galassi, Giorgio; Orlandi, Emanuele; Scialpi, Pietro; Dragone, Michele; Palladino, Diego; Simeone, Annalisa; Amenta, Michele; Bianchi, Giampaolo
2017-01-01
Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) provides clinical guidelines for multiparametric magnetic resonance imaging (mpMRI) [T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)] of prostate. However, DCE-MRI seems to show a limited contribution in prostate cancer (PCa) detection and management. In our experience, DCE-MRI, did not show significant change in diagnostic performance in addition to DWI and T2WI [biparametric MRI (bpMRI)] which represent the predominant sequences to detect suspected lesions in peripheral and transitional zone (TZ). In this article we reviewed the role of DCE-MRI also indicating the potential contribute of bpMRI approach (T2WI and DWI) and lesion volume evaluation in the diagnosis and management of suspected PCa. PMID:28725592
Is contrast enhancement needed for diagnostic prostate MRI?
Scialpi, Michele; Rondoni, Valeria; Aisa, Maria Cristina; Martorana, Eugenio; D'Andrea, Alfredo; Malaspina, Corrado Maria; Orlandi, Agostino; Galassi, Giorgio; Orlandi, Emanuele; Scialpi, Pietro; Dragone, Michele; Palladino, Diego; Simeone, Annalisa; Amenta, Michele; Bianchi, Giampaolo
2017-06-01
Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) provides clinical guidelines for multiparametric magnetic resonance imaging (mpMRI) [T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)] of prostate. However, DCE-MRI seems to show a limited contribution in prostate cancer (PCa) detection and management. In our experience, DCE-MRI, did not show significant change in diagnostic performance in addition to DWI and T2WI [biparametric MRI (bpMRI)] which represent the predominant sequences to detect suspected lesions in peripheral and transitional zone (TZ). In this article we reviewed the role of DCE-MRI also indicating the potential contribute of bpMRI approach (T2WI and DWI) and lesion volume evaluation in the diagnosis and management of suspected PCa.
Dianat, Seyed Saeid; Carter, H Ballentine; Schaeffer, Edward M; Hamper, Ulrik M; Epstein, Jonathan I; Macura, Katarzyna J
2015-10-01
Purpose of this pilot study was to correlate quantitative parameters derived from the multiparametric magnetic resonance imaging (MP-MRI) of the prostate with results from MRI guided transrectal ultrasound (MRI/TRUS) fusion prostate biopsy in men with suspected prostate cancer. Thirty-nine consecutive patients who had 3.0T MP-MRI and subsequent MRI/TRUS fusion prostate biopsy were included and 73 MRI-identified targets were sampled by 177 cores. The pre-biopsy MP-MRI consisted of T2-weighted, diffusion weighted (DWI), and dynamic contrast enhanced (DCE) images. The association of quantitative MRI measurements with biopsy histopathology findings was assessed by Mann-Whitney U- test and Kruskal-Wallis test. Of 73 targets, biopsy showed benign prostate tissue in 46 (63%), cancer in 23 (31.5%), and atypia/high grade prostatic intraepithelial neoplasia in four (5.5%) targets. The median volume of cancer-positive targets was 1.3 cm3. The cancer-positive targets were located in the peripheral zone (56.5%), transition zone (39.1%), and seminal vesicle (4.3%). Nine of 23 (39.1%) cancer-positive targets were higher grade cancer (Gleason grade > 6). Higher grade targets and cancer-positive targets compared to benign lesions exhibited lower mean apparent diffusion coefficient (ADC) value (952.7 < 1167.9 < 1278.9), and lower minimal extracellular volume fraction (ECF) (0.13 < 0.185 < 0.213), respectively. The difference in parameters was more pronounced between higher grade cancer and benign lesions. Our findings from a pilot study indicate that quantitative MRI parameters can predict malignant histology on MRI/TRUS fusion prostate biopsy, which is a valuable technique to ensure adequate sampling of MRI-visible suspicious lesions under TRUS guidance and may impact patient management. The DWI-based quantitative measurement exhibits a stronger association with biopsy findings than the other MRI parameters.
Hölsken, Annett; Schwarz, Marc; Gillmann, Clarissa; Pfister, Christina; Uder, Michael; Doerfler, Arnd; Buchfelder, Michael; Schlaffer, Sven; Fahlbusch, Rudolf; Buslei, Rolf; Bäuerle, Tobias
2018-01-01
Adamantinomatous craniopharyngiomas (ACP) as benign sellar brain tumors are challenging to treat. In order to develop robust in vivo drug testing methodology, the murine orthotopic craniopharyngioma model (PDX) was characterized by magnetic resonance imaging (MRI) and histology in xenografts from three patients (ACP1-3). In ACP PDX, multiparametric MRI was conducted to assess morphologic characteristics such as contrast-enhancing tumor volume (CETV) as well as functional parameters from dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI) including area-under-the-curve (AUC), peak enhancement (PE), time-to-peak (TTP) and apparent diffusion coefficient (ADC). These MRI parameters evaluated in 27 ACP PDX were correlated to histological features and percentage of vital tumor cell content. Qualitative analysis of MRI and histology from PDX revealed a similar phenotype as seen in patients, although the MRI appearance in mice resulted in a more solid tumor growth than in humans. CETV were significantly higher in ACP2 xenografts relative to ACP1 and ACP3 which correspond to respective average vitality of 41%, <10% and 26% determined histologically. Importantly, CETV prove tumor growth of ACP2 PDX as it significantly increases in longitudinal follow-up of 110 days. Furthermore, xenografts from ACP2 revealed a significantly higher AUC, PE and TTP in comparison to ACP3, and significantly increased ADC relative to ACP1 and ACP3 respectively. Overall, DCE-MRI and DWI can be used to distinguish vital from non-vital grafts, when using a cut off value of 15% for vital tumor cell content. MRI enables the assessment of craniopharyngioma PDX vitality in vivo as validated histologically.
Zhang, Yuxin; Holmes, James; Rabanillo, Iñaki; Guidon, Arnaud; Wells, Shane; Hernando, Diego
2018-09-01
To evaluate the reproducibility of quantitative diffusion measurements obtained with reduced Field of View (rFOV) and Multi-shot EPI (msEPI) acquisitions, using single-shot EPI (ssEPI) as a reference. Diffusion phantom experiments, and prostate diffusion-weighted imaging in healthy volunteers and patients with known or suspected prostate cancer were performed across the three different sequences. Quantitative diffusion measurements of apparent diffusion coefficient, and diffusion kurtosis parameters (healthy volunteers), were obtained and compared across diffusion sequences (rFOV, msEPI, and ssEPI). Other possible confounding factors like b-value combinations and acquisition parameters were also investigated. Both msEPI and rFOV have shown reproducible quantitative diffusion measurements relative to ssEPI; no significant difference in ADC was observed across pulse sequences in the standard diffusion phantom (p = 0.156), healthy volunteers (p ≥ 0.12) or patients (p ≥ 0.26). The ADC values within the non-cancerous central gland and peripheral zone of patients were 1.29 ± 0.17 × 10 -3 mm 2 /s and 1.74 ± 0.23 × 10 -3 mm 2 /s respectively. However, differences in quantitative diffusion parameters were observed across different number of averages for rFOV, and across b-value groups and diffusion models for all the three sequences. Both rFOV and msEPI have the potential to provide high image quality with reproducible quantitative diffusion measurements in prostate diffusion MRI. Copyright © 2018 Elsevier Inc. All rights reserved.
Neuroimaging Techniques: a Conceptual Overview of Physical Principles, Contribution and History
NASA Astrophysics Data System (ADS)
Minati, Ludovico
2006-06-01
This paper is meant to provide a brief overview of the techniques currently used to image the brain and to study non-invasively its anatomy and function. After a historical summary in the first section, general aspects are outlined in the second section. The subsequent six sections survey, in order, computed tomography (CT), morphological magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), diffusion-tensor magnetic resonance imaging (DWI/DTI), positron emission tomography (PET), and electro- and magneto-encephalography (EEG/MEG) based imaging. Underlying physical principles, modelling and data processing approaches, as well as clinical and research relevance are briefly outlined for each technique. Given the breadth of the scope, there has been no attempt to be comprehensive. The ninth and final section outlines some aspects of active research in neuroimaging.
Applications of Molecular Imaging
Galbán, Craig; Galbán, Stefanie; Van Dort, Marcian; Luker, Gary D.; Bhojani, Mahaveer S.; Rehemtualla, Alnawaz; Ross, Brian D.
2015-01-01
Today molecular imaging technologies play a central role in clinical oncology. The use of imaging techniques in early cancer detection, treatment response and new therapy development is steadily growing and has already significantly impacted clinical management of cancer. In this chapter we will overview three different molecular imaging technologies used for the understanding of disease biomarkers, drug development, or monitoring therapeutic outcome. They are (1) optical imaging (bioluminescence and fluorescence imaging) (2) magnetic resonance imaging (MRI), and (3) nuclear imaging (e.g, single photon emission computed tomography (SPECT) and positron emission tomography (PET)). We will review the use of molecular reporters of biological processes (e.g. apoptosis and protein kinase activity) for high throughput drug screening and new cancer therapies, diffusion MRI as a biomarker for early treatment response and PET and SPECT radioligands in oncology. PMID:21075334
DOE Office of Scientific and Technical Information (OSTI.GOV)
Minati, Ludovico
This paper is meant to provide a brief overview of the techniques currently used to image the brain and to study non-invasively its anatomy and function. After a historical summary in the first section, general aspects are outlined in the second section. The subsequent six sections survey, in order, computed tomography (CT), morphological magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), diffusion-tensor magnetic resonance imaging (DWI/DTI), positron emission tomography (PET), and electro- and magneto-encephalography (EEG/MEG) based imaging. Underlying physical principles, modelling and data processing approaches, as well as clinical and research relevance are briefly outlined for each technique. Givenmore » the breadth of the scope, there has been no attempt to be comprehensive. The ninth and final section outlines some aspects of active research in neuroimaging.« less
Structural covariance networks in the mouse brain.
Pagani, Marco; Bifone, Angelo; Gozzi, Alessandro
2016-04-01
The presence of networks of correlation between regional gray matter volume as measured across subjects in a group of individuals has been consistently described in several human studies, an approach termed structural covariance MRI (scMRI). Complementary to prevalent brain mapping modalities like functional and diffusion-weighted imaging, the approach can provide precious insights into the mutual influence of trophic and plastic processes in health and pathological states. To investigate whether analogous scMRI networks are present in lower mammal species amenable to genetic and experimental manipulation such as the laboratory mouse, we employed high resolution morphoanatomical MRI in a large cohort of genetically-homogeneous wild-type mice (C57Bl6/J) and mapped scMRI networks using a seed-based approach. We show that the mouse brain exhibits robust homotopic scMRI networks in both primary and associative cortices, a finding corroborated by independent component analyses of cortical volumes. Subcortical structures also showed highly symmetric inter-hemispheric correlations, with evidence of distributed antero-posterior networks in diencephalic regions of the thalamus and hypothalamus. Hierarchical cluster analysis revealed six identifiable clusters of cortical and sub-cortical regions corresponding to previously described neuroanatomical systems. Our work documents the presence of homotopic cortical and subcortical scMRI networks in the mouse brain, thus supporting the use of this species to investigate the elusive biological and neuroanatomical underpinnings of scMRI network development and its derangement in neuropathological states. The identification of scMRI networks in genetically homogeneous inbred mice is consistent with the emerging view of a key role of environmental factors in shaping these correlational networks. Copyright © 2016 Elsevier Inc. All rights reserved.
Corticobulbar tract changes as predictors of dysarthria in childhood brain injury.
Liégeois, Frédérique; Tournier, Jacques-Donald; Pigdon, Lauren; Connelly, Alan; Morgan, Angela T
2013-03-05
To identify corticobulbar tract changes that may predict chronic dysarthria in young people who have sustained a traumatic brain injury (TBI) in childhood using diffusion MRI tractography. We collected diffusion-weighted MRI data from 49 participants. We compared 17 young people (mean age 17 years, 10 months; on average 8 years postinjury) with chronic dysarthria who sustained a TBI in childhood (range 3-16 years) with 2 control groups matched for age and sex: 1 group of young people who sustained a traumatic injury but had no subsequent dysarthria (n = 15), and 1 group of typically developing individuals (n = 17). We performed tractography from spherical seed regions within the precentral gyrus white matter to track: 1) the hand-related corticospinal tract; 2) the dorsal corticobulbar tract, thought to correspond to the lips/larynx motor representation; and 3) the ventral corticobulbar tract, corresponding to the tongue representation. Despite widespread white matter damage, radial (perpendicular) diffusivity within the left dorsal corticobulbar tract was the best predictor of the presence of dysarthria after TBI. Diffusion metrics in this tract also predicted speech and oromotor performance across the whole group of TBI participants, with additional significant contributions from ventral speech tract volume in the right hemisphere. An intact left dorsal corticobulbar tract seems crucial to the normal execution of speech long term after acquired injury. Examining the speech-related motor pathways using diffusion-weighted MRI tractography offers a promising prognostic tool for people with acquired, developmental, or degenerative neurologic conditions likely to affect speech.
Rose, Jessica; Butler, Erin E; Lamont, Lauren E; Barnes, Patrick D; Atlas, Scott W; Stevenson, David K
2009-07-01
The neurological basis of an increased incidence of cerebral palsy (CP) in preterm males is unknown. This study examined neonatal brain structure on magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) at term-equivalent age, sex, and neurodevelopment at 1 year 6 months on the basis of the Amiel-Tison neurological examination, Gross Motor Function Classification System, and Bayley Scales of Infant Development in 78 very-low-birthweight preterm children (41 males, 37 females; mean gestational age 27.6 wks, SD 2.5; mean birthweight 1021 g, SD 339). Brain abnormalities on MRI and DTI were not different between males and females except in the splenium of the corpus callosum, where males had lower DTI fractional anisotropy (p=0.025) and a higher apparent diffusion coefficient (p=0.013), indicating delayed splenium development. In the 26 infants who were at higher risk on the basis of DTI, males had more abnormalities on MRI (p=0.034) and had lower fractional anisotropy and a higher apparent diffusion coefficient in the splenium (p=0.049; p=0.025) and right posterior limb of the internal capsule (PLIC; p=0.003; p=0.033). Abnormal neurodevelopment was more common in males (n=9) than in females (n=2; p=0.036). Children with abnormal neurodevelopment had more abnormalities on MRI (p=0.014) and reduced splenium and right PLIC fractional anisotropy (p=0.001; p=0.035). In children with abnormal neurodevelopment, right PLIC fractional anisotropy was lower than left (p=0.035), whereas in those with normal neurodevelopment right PLIC fractional anisotropy was higher than left (p=0.001). Right PLIC fractional anisotropy correlated to neurodevelopment (rho=0.371, p=0.002). Logistic regression predicted neurodevelopment with 94% accuracy; only right PLIC fractional anisotropy was a significant logistic coefficient. Results indicate that the higher incidence of abnormal neurodevelopment in preterm males relates to greater incidence and severity of brain abnormalities, including reduced PLIC and splenium development.
Cox, Simon R.; MacPherson, Sarah E.; Ferguson, Karen J.; Royle, Natalie A.; Maniega, Susana Muñoz; Hernández, Maria del C. Valdés; Bastin, Mark E.; MacLullich, Alasdair M.J.; Wardlaw, Joanna M.; Deary, Ian J.
2015-01-01
Elevated glucocorticoid (GC) levels putatively damage specific brain regions, which in turn may accelerate cognitive ageing. However, many studies are cross-sectional or have relatively short follow-up periods, making it difficult to relate GCs directly to changes in cognitive ability with increasing age. Moreover, studies combining endocrine, MRI and cognitive variables are scarce, measurement methods vary considerably, and formal tests of the underlying causal hypothesis (cortisol → brain → cognition) are absent. In this study, 90 men, aged 73 years, provided measures of fluid intelligence, processing speed and memory, diurnal and reactive salivary cortisol and two measures of white matter (WM) structure (WM hyperintensity volume from structural MRI and mean diffusivity averaged across 12 major tracts from diffusion tensor MRI), hippocampal volume, and also cognitive ability at age 11. We tested whether negative relationships between cognitive ageing differences (over more than 60 years) and salivary cortisol were significantly mediated by WM and hippocampal volume. Significant associations between reactive cortisol at 73 and cognitive ageing differences between 11 and 73 (r = −.28 to −.36, p < .05) were partially mediated by both WM structural measures, but not hippocampal volume. Cortisol-WM relationships were modest, as was the degree to which WM structure attenuated cortisol–cognition associations (<15%). These data support the hypothesis that GCs contribute to cognitive ageing differences from childhood to the early 70s, partly via brain WM structure. PMID:26298692
Advanced structural multimodal imaging of a patient with subcortical band heterotopia.
Kini, Lohith G; Nasrallah, Ilya M; Coto, Carlos; Ferraro, Lindsay C; Davis, Kathryn A
2016-12-01
Subcortical band heterotopia (SBH) is a disorder of neuronal migration most commonly due to mutations of the Doublecortin (DCX) gene. A range of phenotypes is seen, with most patients having some degree of epilepsy and intellectual disability. Advanced diffusion and structural magnetic resonance imaging (MRI) sequences may be useful in identifying heterotopias and dysplasias of different sizes in drug-resistant epilepsy. We describe a patient with SBH and drug-resistant epilepsy and investigate neurite density, neurite dispersion, and diffusion parameters as compared to a healthy control through the use of multiple advanced MRI modalities. Neurite density and dispersion in heterotopia was found to be more similar to white matter than gray matter. Neurite density and dispersion maps obtained using diffusion imaging may be able to better characterize different subtypes of heterotopia.
Noninvasive Localization of Prostate Cancer via Diffusion Sensitive MRI
2008-03-01
sequence, Haker et al and Roebuck et al using a line-scan diffusion sequence, and Vigneron et al using a fast spin-echo diffusion sequence (33,35-37...Mulkern RV, Haker S, Zhang J, Zou KH, Maier SE, Tempany CM. Detection of prostate cancer by integration of line-scan diffusion, T2-mapping and T2-weighted...36. Haker SJ, Szot Barnes A, Maier SE, Tempany CM, Mulkern RV. Diffusion Tensor Imaging for Prostate Cancer Detection: Preliminary Results from a
On the Viability of Diffusion MRI-Based Microstructural Biomarkers in Ischemic Stroke
Boscolo Galazzo, Ilaria; Brusini, Lorenza; Obertino, Silvia; Zucchelli, Mauro; Granziera, Cristina; Menegaz, Gloria
2018-01-01
Recent tract-based analyses provided evidence for the exploitability of 3D-SHORE microstructural descriptors derived from diffusion MRI (dMRI) in revealing white matter (WM) plasticity. In this work, we focused on the main open issues left: (1) the comparative analysis with respect to classical tensor-derived indices, i.e., Fractional Anisotropy (FA) and Mean Diffusivity (MD); and (2) the ability to detect plasticity processes in gray matter (GM). Although signal modeling in GM is still largely unexplored, we investigated their sensibility to stroke-induced microstructural modifications occurring in the contralateral hemisphere. A more complete picture could provide hints for investigating the interplay of GM and WM modulations. Ten stroke patients and ten age/gender-matched healthy controls were enrolled in the study and underwent diffusion spectrum imaging (DSI). Acquisitions at three and two time points (tp) were performed on patients and controls, respectively. For all subjects and acquisitions, FA and MD were computed along with 3D-SHORE-based indices [Generalized Fractional Anisotropy (GFA), Propagator Anisotropy (PA), Return To the Axis Probability (RTAP), Return To the Plane Probability (RTPP), and Mean Square Displacement (MSD)]. Tract-based analysis involving the cortical, subcortical and transcallosal motor networks and region-based analysis in GM were successively performed, focusing on the contralateral hemisphere to the stroke. Reproducibility of all the indices on both WM and GM was quantitatively proved on controls. For tract-based, longitudinal group analyses revealed the highest significant differences across the subcortical and transcallosal networks for all the indices. The optimal regression model for predicting the clinical motor outcome at tp3 included GFA, PA, RTPP, and MSD in the subcortical network in combination with the main clinical information at baseline. Region-based analysis in the contralateral GM highlighted the ability of anisotropy indices in discriminating between groups mainly at tp1, while diffusivity indices appeared to be altered at tp2. 3D-SHORE indices proved to be suitable in probing plasticity in both WM and GM, further confirming their viability as a novel family of biomarkers in ischemic stroke in WM and revealing their potential exploitability in GM. Their combination with tensor-derived indices can provide more detailed insights of the different tissue modulations related to stroke pathology. PMID:29515362
Acute hepatic encephalopathy presenting as cortical laminar necrosis: case report.
Choi, Jong Mun; Kim, Yoon Hee; Roh, Sook Young
2013-01-01
We report on a 55-year-old man with alcoholic liver cirrhosis who presented with status epilepticus. Laboratory analysis showed markedly elevated blood ammonia. Brain magnetic resonance imaging (MRI) showed widespread cortical signal changes with restricted diffusion, involving both temporo-fronto-parietal cortex, while the perirolandic regions and occipital cortex were uniquely spared. A follow-up brain MRI demonstrated diffuse cortical atrophy with increased signals on T1-weighted images in both the basal ganglia and temporal lobe cortex, representing cortical laminar necrosis. We suggest that the brain lesions, in our case, represent a consequence of toxic effect of ammonia.
NASA Astrophysics Data System (ADS)
Caffini, Matteo; Bergsland, Niels; LaganÃ, Marcella; Tavazzi, Eleonora; Tortorella, Paola; Rovaris, Marco; Baselli, Giuseppe
2014-03-01
Despite advances in the application of nonconventional MRI techniques in furthering the understanding of multiple sclerosis pathogenic mechanisms, there are still many unanswered questions, such as the relationship between gray and white matter damage. We applied a combination of advanced surface-based reconstruction and diffusion tensor imaging techniques to address this issue. We found significant relationships between white matter tract integrity indices and corresponding cortical structures. Our results suggest a direct link between damage in white and gray matter and contribute to the notion of gray matter loss relating to clinical disability.
Szczepankiewicz, Filip; van Westen, Danielle; Englund, Elisabet; Westin, Carl-Fredrik; Ståhlberg, Freddy; Lätt, Jimmy; Sundgren, Pia C; Nilsson, Markus
2016-11-15
The structural heterogeneity of tumor tissue can be probed by diffusion MRI (dMRI) in terms of the variance of apparent diffusivities within a voxel. However, the link between the diffusional variance and the tissue heterogeneity is not well-established. To investigate this link we test the hypothesis that diffusional variance, caused by microscopic anisotropy and isotropic heterogeneity, is associated with variable cell eccentricity and cell density in brain tumors. We performed dMRI using a novel encoding scheme for diffusional variance decomposition (DIVIDE) in 7 meningiomas and 8 gliomas prior to surgery. The diffusional variance was quantified from dMRI in terms of the total mean kurtosis (MK T ), and DIVIDE was used to decompose MK T into components caused by microscopic anisotropy (MK A ) and isotropic heterogeneity (MK I ). Diffusion anisotropy was evaluated in terms of the fractional anisotropy (FA) and microscopic fractional anisotropy (μFA). Quantitative microscopy was performed on the excised tumor tissue, where structural anisotropy and cell density were quantified by structure tensor analysis and cell nuclei segmentation, respectively. In order to validate the DIVIDE parameters they were correlated to the corresponding parameters derived from microscopy. We found an excellent agreement between the DIVIDE parameters and corresponding microscopy parameters; MK A correlated with cell eccentricity (r=0.95, p<10 -7 ) and MK I with the cell density variance (r=0.83, p<10 -3 ). The diffusion anisotropy correlated with structure tensor anisotropy on the voxel-scale (FA, r=0.80, p<10 -3 ) and microscopic scale (μFA, r=0.93, p<10 -6 ). A multiple regression analysis showed that the conventional MK T parameter reflects both variable cell eccentricity and cell density, and therefore lacks specificity in terms of microstructure characteristics. However, specificity was obtained by decomposing the two contributions; MK A was associated only to cell eccentricity, and MK I only to cell density variance. The variance in meningiomas was caused primarily by microscopic anisotropy (mean±s.d.) MK A =1.11±0.33 vs MK I =0.44±0.20 (p<10 -3 ), whereas in the gliomas, it was mostly caused by isotropic heterogeneity MK I =0.57±0.30 vs MK A =0.26±0.11 (p<0.05). In conclusion, DIVIDE allows non-invasive mapping of parameters that reflect variable cell eccentricity and density. These results constitute convincing evidence that a link exists between specific aspects of tissue heterogeneity and parameters from dMRI. Decomposing effects of microscopic anisotropy and isotropic heterogeneity facilitates an improved interpretation of tumor heterogeneity as well as diffusion anisotropy on both the microscopic and macroscopic scale. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Littooij, Annemieke S; Nikkels, Peter G; Hulsbergen-van de Kaa, Christina A; van de Ven, Cees P; van den Heuvel-Eibrink, Marry M; Olsen, Øystein E
2017-11-01
Nephroblastomas represent a group of heterogeneous tumours with variable proportions of distinct histopathological components. The purpose of this study was to investigate whether direct comparison of apparent diffusion coefficient (ADC) measurements with post-resection histopathology subtypes is feasible and whether ADC metrics are related to histopathological components. Twenty-three children were eligible for inclusion in this retrospective study. All children had MRI including diffusion-weighted imaging (DWI) after preoperative chemotherapy, just before tumour resection. A pathologist and radiologist identified corresponding slices at MRI and postoperative specimens using tumour morphology, the upper/lower calyx and hilar vessels as reference points. An experienced reader performed ADC measurements, excluding non-enhancing areas. A pathologist reviewed the corresponding postoperative slides according to the international standard guidelines. We tested potential associations with the Spearman rank test. Side-by-side comparison of MRI-DWI with corresponding histopathology slides was feasible in 15 transverse slices in 9 lesions in 8 patients. Most exclusions were related to extensive areas of necrosis/haemorrhage. In one lesion correlation was not possible because of the different orientation of sectioning of the specimen and MRI slices. The 25% ADC showed a strong relationship with percentage of blastema (Spearman rho=-0.71, P=0.003), whereas median ADC was strongly related to the percentage stroma (Spearman rho=0.74, P=0.002) at histopathology. Side-by-side comparison of MRI-DWI and histopathology is feasible in the majority of patients who do not have massive necrosis and hemorrhage. Blastemal and stromal components have a strong linear relationship with ADC markers.
Heidemann, Robin M; Anwander, Alfred; Feiweier, Thorsten; Knösche, Thomas R; Turner, Robert
2012-04-02
There is ongoing debate whether using a higher spatial resolution (sampling k-space) or a higher angular resolution (sampling q-space angles) is the better way to improve diffusion MRI (dMRI) based tractography results in living humans. In both cases, the limiting factor is the signal-to-noise ratio (SNR), due to the restricted acquisition time. One possible way to increase the spatial resolution without sacrificing either SNR or angular resolution is to move to a higher magnetic field strength. Nevertheless, dMRI has not been the preferred application for ultra-high field strength (7 T). This is because single-shot echo-planar imaging (EPI) has been the method of choice for human in vivo dMRI. EPI faces several challenges related to the use of a high resolution at high field strength, for example, distortions and image blurring. These problems can easily compromise the expected SNR gain with field strength. In the current study, we introduce an adapted EPI sequence in conjunction with a combination of ZOOmed imaging and Partially Parallel Acquisition (ZOOPPA). We demonstrate that the method can produce high quality diffusion-weighted images with high spatial and angular resolution at 7 T. We provide examples of in vivo human dMRI with isotropic resolutions of 1 mm and 800 μm. These data sets are particularly suitable for resolving complex and subtle fiber architectures, including fiber crossings in the white matter, anisotropy in the cortex and fibers entering the cortex. Copyright © 2011 Elsevier Inc. All rights reserved.
A quantitative comparison of two methods to correct eddy current-induced distortions in DT-MRI.
Muñoz Maniega, Susana; Bastin, Mark E; Armitage, Paul A
2007-04-01
Eddy current-induced geometric distortions of single-shot, diffusion-weighted, echo-planar (DW-EP) images are a major confounding factor to the accurate determination of water diffusion parameters in diffusion tensor MRI (DT-MRI). Previously, it has been suggested that these geometric distortions can be removed from brain DW-EP images using affine transformations determined from phantom calibration experiments using iterative cross-correlation (ICC). Since this approach was first described, a number of image-based registration methods have become available that can also correct eddy current-induced distortions in DW-EP images. However, as yet no study has investigated whether separate eddy current calibration or image-based registration provides the most accurate way of removing these artefacts from DT-MRI data. Here we compare how ICC phantom calibration and affine FLIRT (http://www.fmrib.ox.ac.uk), a popular image-based multi-modal registration method that can correct both eddy current-induced distortions and bulk subject motion, perform when registering DW-EP images acquired with different slice thicknesses (2.8 and 5 mm) and b-values (1000 and 3000 s/mm(2)). With the use of consistency testing, it was found that ICC was a more robust algorithm for correcting eddy current-induced distortions than affine FLIRT, especially at high b-value and small slice thickness. In addition, principal component analysis demonstrated that the combination of ICC phantom calibration (to remove eddy current-induced distortions) with rigid body FLIRT (to remove bulk subject motion) provided a more accurate registration of DT-MRI data than that achieved by affine FLIRT.
Malyarenko, Dariya I; Ross, Brian D; Chenevert, Thomas L
2014-03-01
Gradient nonlinearity of MRI systems leads to spatially dependent b-values and consequently high non-uniformity errors (10-20%) in apparent diffusion coefficient (ADC) measurements over clinically relevant field-of-views. This work seeks practical correction procedure that effectively reduces observed ADC bias for media of arbitrary anisotropy in the fewest measurements. All-inclusive bias analysis considers spatial and time-domain cross-terms for diffusion and imaging gradients. The proposed correction is based on rotation of the gradient nonlinearity tensor into the diffusion gradient frame where spatial bias of b-matrix can be approximated by its Euclidean norm. Correction efficiency of the proposed procedure is numerically evaluated for a range of model diffusion tensor anisotropies and orientations. Spatial dependence of nonlinearity correction terms accounts for the bulk (75-95%) of ADC bias for FA = 0.3-0.9. Residual ADC non-uniformity errors are amplified for anisotropic diffusion. This approximation obviates need for full diffusion tensor measurement and diagonalization to derive a corrected ADC. Practical scenarios are outlined for implementation of the correction on clinical MRI systems. The proposed simplified correction algorithm appears sufficient to control ADC non-uniformity errors in clinical studies using three orthogonal diffusion measurements. The most efficient reduction of ADC bias for anisotropic medium is achieved with non-lab-based diffusion gradients. Copyright © 2013 Wiley Periodicals, Inc.
Cheng, Hai-Ling Margaret; Loai, Yasir; Beaumont, Marine; Farhat, Walid A
2010-08-01
Bladder acellular matrices (ACMs) derived from natural tissue are gaining increasing attention for their role in tissue engineering and regeneration. Unlike conventional scaffolds based on biodegradable polymers or gels, ACMs possess native biomechanical and many acquired biologic properties. Efforts to optimize ACM-based scaffolds are ongoing and would be greatly assisted by a noninvasive means to characterize scaffold properties and monitor interaction with cells. MRI is well suited to this role, but research with MRI for scaffold characterization has been limited. This study presents initial results from quantitative MRI measurements for bladder ACM characterization and investigates the effects of incorporating hyaluronic acid, a natural biomaterial useful in tissue-engineering and regeneration. Measured MR relaxation times (T(1), T(2)) and diffusion coefficient were consistent with increased water uptake and glycosaminoglycan content observed on biochemistry in hyaluronic acid ACMs. Multicomponent MRI provided greater specificity, with diffusion data showing an acellular environment and T(2) components distinguishing the separate effects of increased glycosaminoglycans and hydration. These results suggest that quantitative MRI may provide useful information on matrix composition and structure, which is valuable in guiding further development using bladder ACMs for organ regeneration and in strategies involving the use of hyaluronic acid.
Balachandar, R; John, J P; Saini, J; Kumar, K J; Joshi, H; Sadanand, S; Aiyappan, S; Sivakumar, P T; Loganathan, S; Varghese, M; Bharath, S
2015-05-01
Alzheimer's disease (AD) is a progressive neurodegenerative condition where in early diagnosis and interventions are key policy priorities in dementia services and research. We studied the functional and structural connectivity in mild AD to determine the nature of connectivity changes that coexist with neurocognitive deficits in the early stages of AD. Fifteen mild AD subjects and 15 cognitively healthy controls (CHc) matched for age and gender, underwent detailed neurocognitive assessment and magnetic resonance imaging (MRI) of resting state functional MRI (rs-fMRI) and diffusion tensor imaging (DTI). Rest fMRI was analyzed using dual regression approach and DTI by voxel wise statistics. Patients with mild AD had significantly lower functional connectivity (FC) within the default mode network and increased FC within the executive network. The mild AD group scored significantly lower in all domains of cognition compared with CHc. But fractional anisotropy did not significantly (p < 0.05) differ between the groups. Resting state functional connectivity alterations are noted during initial stages of cognitive decline in AD, even when there are no significant white matter microstructural changes. Copyright © 2014 John Wiley & Sons, Ltd.
MRI and clinical features of maple syrup urine disease: preliminary results in 10 cases
Cheng, Ailan; Han, Lianshu; Feng, Yun; Li, Huimin; Yao, Rong; Wang, Dengbin; Jin, Biao
2017-01-01
PURPOSE We aimed to evaluate the magnetic resonance imaging (MRI) and clinical features of maple syrup urine disease (MSUD). METHODS This retrospective study consisted of 10 MSUD patients confirmed by genetic testing. All patients underwent brain MRI. Phenotype, genotype, and areas of brain injury on MRI were retrospectively reviewed. RESULTS Six patients (60%) had the classic form of MSUD with BCKDHB mutation, three patients (30%) had the intermittent form (two with BCKDHA mutations and one with DBT mutation), and one patient (10%) had the thiamine-responsive form with DBT mutation. On diffusion-weighted imaging, nine cases presented restricted diffusion in myelinated areas, and one intermittent case with DBT mutation was normal. The classic form of MSUD involved the basal ganglia in six cases; the cerebellum, mesencephalon, pons, and supratentorial area in five cases; and the thalamus in four cases, respectively. The intermittent form involved the cerebellum, pons, and supratentorial area in two cases. The thiamine-responsive form involved the basal ganglia and supratentorial area. CONCLUSION Our preliminary results indicate that patients with MSUD presented more commonly in classic form with BCKDHB mutation and displayed extensive brain injury on MRI. PMID:28830848
Progression of white matter damage in progressive supranuclear palsy with predominant parkinsonism.
Caso, Francesca; Agosta, Federica; Ječmenica-Lukić, Milica; Petrović, Igor; Meani, Alessandro; Kostic, Vladimir S; Filippi, Massimo
2018-04-01
Progressive supranuclear palsy with predominant parkinsonism (PSP-P) accounts for 14-35% of all PSP cases. A few cross-sectional MRI studies in PSP-P showed a remarkable white matter (WM) damage. Progression of brain structural damage in these patients remains unknown. Longitudinal clinical, cognitive and diffusion tensor (DT) MRI data were obtained over a mean 1.6 year follow up in 10 PSP-P patients. At study entry, patients were compared with 36 healthy controls. Voxelwise statistical analysis of white matter DT MRI data (mean, axial and radial diffusivity, and fractional anisotropy) was carried out using tract-based spatial statistics. During the 1.6 year follow up, PSP-P patients showed significant decline of motor, cognitive and mood disturbances. DT MRI analysis revealed at baseline a widespread pattern of WM alterations. Over time, PSP-P patients exhibited progression of WM damage in supratentorial tracts compared to baseline. No WM changes were detected in cerebellar WM. In PSP-P patients, WM damage significantly progressed over time. Longitudinal DT MRI measures are a potential in vivo marker of disease progression in PSP-P. Copyright © 2018 Elsevier Ltd. All rights reserved.
MRI to assess renal structure and function.
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.
Imaging the accumulation and suppression of tau pathology using multiparametric MRI
Holmes, Holly E.; Colgan, Niall; Ismail, Ozama; Ma, Da; Powell, Nick M.; O'Callaghan, James M.; Harrison, Ian F.; Johnson, Ross A.; Murray, Tracey K.; Ahmed, Zeshan; Heggenes, Morton; Fisher, Alice; Cardoso, M.J.; Modat, Marc; Walker-Samuel, Simon; Fisher, Elizabeth M.C.; Ourselin, Sebastien; O'Neill, Michael J.; Wells, Jack A.; Collins, Emily C.; Lythgoe, Mark F.
2016-01-01
Mouse models of Alzheimer's disease have served as valuable tools for investigating pathogenic mechanisms relating to neurodegeneration, including tau-mediated and neurofibrillary tangle pathology—a major hallmark of the disease. In this work, we have used multiparametric magnetic resonance imaging (MRI) in a longitudinal study of neurodegeneration in the rTg4510 mouse model of tauopathy, a subset of which were treated with doxycycline at different time points to suppress the tau transgene. Using this paradigm, we investigated the sensitivity of multiparametric MRI to both the accumulation and suppression of pathologic tau. Tau-related atrophy was discernible from 5.5 months within the cortex and hippocampus. We observed markedly less atrophy in the treated rTg4510 mice, which was enhanced after doxycycline intervention from 3.5 months. We also observed differences in amide proton transfer, cerebral blood flow, and diffusion tensor imaging parameters in the rTg4510 mice, which were significantly less altered after doxycycline treatment. We propose that these non-invasive MRI techniques offer insight into pathologic mechanisms underpinning Alzheimer's disease that may be important when evaluating emerging therapeutics targeting one of more of these processes. PMID:26923415
Neuroimaging of the Injured Pediatric Brain: Methods and New Lessons.
Dennis, Emily L; Babikian, Talin; Giza, Christopher C; Thompson, Paul M; Asarnow, Robert F
2018-02-01
Traumatic brain injury (TBI) is a significant public health problem in the United States, especially for children and adolescents. Current epidemiological data estimate over 600,000 patients younger than 20 years are treated for TBI in emergency rooms annually. While many patients experience a full recovery, for others there can be long-lasting cognitive, neurological, psychological, and behavioral disruptions. TBI in youth can disrupt ongoing brain development and create added family stress during a formative period. The neuroimaging methods used to assess brain injury improve each year, providing researchers a more detailed characterization of the injury and recovery process. In this review, we cover current imaging methods used to quantify brain disruption post-injury, including structural magnetic resonance imaging (MRI), diffusion MRI, functional MRI, resting state fMRI, and magnetic resonance spectroscopy (MRS), with brief coverage of other methods, including electroencephalography (EEG), single-photon emission computed tomography (SPECT), and positron emission tomography (PET). We include studies focusing on pediatric moderate-severe TBI from 2 months post-injury and beyond. While the morbidity of pediatric TBI is considerable, continuing advances in imaging methods have the potential to identify new treatment targets that can lead to significant improvements in outcome.
[Cavernous sinus thrombosis as a rare cause of exophthalmos in childhood : A case report].
Kamawal, A; Schmidt, M A; Rompel, O; Gusek-Schneider, G C; Mardin, C Y; Trollmann, R
2017-05-01
Complications of acute bacterial sinusitis mostly occur in children and adolescents. In particular, intracranial spread of the infection can lead to severe even fatal courses of the disease. This article is a case report about a 13-year-old boy suffering from left-sided headache, meningismus and exophthalmos as presenting symptoms. Cranial magnetic resonance imaging (MRI) showed merely right-sided sphenoid sinusitis; however, the diffusion-weighted MRI sequence indicated a left-sided cavernous sinus thrombosis, which could be confirmed by computed tomography (CT) angiography. Cerebrospinal fluid diagnostics showed significant leukocytosis confirming secondary meningitis. Finally, exophthalmos was explained by parainfectious cavernous sinus thrombosis and periorbital edema. This case report highlights the importance of extended and specific diagnostic imaging in cases of clinically suspected complications in children and adolescents with sinusitis and the diagnostic significance of diffusion-weighted MRI.
Hubbard, Nicholas A; Turner, Monroe P; Ouyang, Minhui; Himes, Lyndahl; Thomas, Binu P; Hutchison, Joanna L; Faghihahmadabadi, Shawheen; Davis, Scott L; Strain, Jeremy F; Spence, Jeffrey; Krawczyk, Daniel C; Huang, Hao; Lu, Hanzhang; Hart, John; Frohman, Teresa C; Frohman, Elliot M; Okuda, Darin T; Rypma, Bart
2017-11-01
Multiple sclerosis (MS) involves damage to white matter microstructures. This damage has been related to grey matter function as measured by standard, physiologically-nonspecific neuroimaging indices (i.e., blood-oxygen-level dependent signal [BOLD]). Here, we used calibrated functional magnetic resonance imaging and diffusion tensor imaging to examine the extent to which specific, evoked grey matter physiological processes were associated with white matter diffusion in MS. Evoked changes in BOLD, cerebral blood flow (CBF), and oxygen metabolism (CMRO 2 ) were measured in visual cortex. Individual differences in the diffusion tensor measure, radial diffusivity, within occipital tracts were strongly associated with MS patients' BOLD and CMRO 2 . However, these relationships were in opposite directions, complicating the interpretation of the relationship between BOLD and white matter microstructural damage in MS. CMRO 2 was strongly associated with individual differences in patients' fatigue and neurological disability, suggesting that alterations to evoked oxygen metabolic processes may be taken as a marker for primary symptoms of MS. This work demonstrates the first application of calibrated and diffusion imaging together and details the first application of calibrated functional MRI in a neurological population. Results lend support for neuroenergetic hypotheses of MS pathophysiology and provide an initial demonstration of the utility of evoked oxygen metabolism signals for neurology research. Hum Brain Mapp 38:5375-5390, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Ghosh, Adarsh; Singh, Tulika; Singla, Veenu; Bagga, Rashmi; Khandelwal, Niranjan
2017-12-01
Apparent diffusion coefficient (ADC) maps are usually generated by builtin software provided by the MRI scanner vendors; however, various open-source postprocessing software packages are available for image manipulation and parametric map generation. The purpose of this study is to establish the reproducibility of absolute ADC values obtained using different postprocessing software programs. DW images with three b values were obtained with a 1.5-T MRI scanner, and the trace images were obtained. ADC maps were automatically generated by the in-line software provided by the vendor during image generation and were also separately generated on postprocessing software. These ADC maps were compared on the basis of ROIs using paired t test, Bland-Altman plot, mountain plot, and Passing-Bablok regression plot. There was a statistically significant difference in the mean ADC values obtained from the different postprocessing software programs when the same baseline trace DW images were used for the ADC map generation. For using ADC values as a quantitative cutoff for histologic characterization of tissues, standardization of the postprocessing algorithm is essential across processing software packages, especially in view of the implementation of vendor-neutral archiving.
Assessing White Matter Microstructure in Brain Regions with Different Myelin Architecture Using MRI.
Groeschel, Samuel; Hagberg, Gisela E; Schultz, Thomas; Balla, Dávid Z; Klose, Uwe; Hauser, Till-Karsten; Nägele, Thomas; Bieri, Oliver; Prasloski, Thomas; MacKay, Alex L; Krägeloh-Mann, Ingeborg; Scheffler, Klaus
2016-01-01
We investigate how known differences in myelin architecture between regions along the cortico-spinal tract and frontal white matter (WM) in 19 healthy adolescents are reflected in several quantitative MRI parameters that have been proposed to non-invasively probe WM microstructure. In a clinically feasible scan time, both conventional imaging sequences as well as microstructural MRI parameters were assessed in order to quantitatively characterise WM regions that are known to differ in the thickness of their myelin sheaths, and in the presence of crossing or parallel fibre organisation. We found that diffusion imaging, MR spectroscopy (MRS), myelin water fraction (MWF), Magnetization Transfer Imaging, and Quantitative Susceptibility Mapping were myelin-sensitive in different ways, giving complementary information for characterising WM microstructure with different underlying fibre architecture. From the diffusion parameters, neurite density (NODDI) was found to be more sensitive than fractional anisotropy (FA), underlining the limitation of FA in WM crossing fibre regions. In terms of sensitivity to different myelin content, we found that MWF, the mean diffusivity and chemical-shift imaging based MRS yielded the best discrimination between areas. Multimodal assessment of WM microstructure was possible within clinically feasible scan times using a broad combination of quantitative microstructural MRI sequences. By assessing new microstructural WM parameters we were able to provide normative data and discuss their interpretation in regions with different myelin architecture, as well as their possible application as biomarker for WM disorders.
Cerebral involvement in axonal Charcot-Marie-Tooth neuropathy caused by mitofusin2 mutations.
Brockmann, Knut; Dreha-Kulaczewski, Steffi; Dechent, Peter; Bönnemann, Carsten; Helms, Gunther; Kyllerman, Marten; Brück, Wolfgang; Frahm, Jens; Huehne, Kathrin; Gärtner, Jutta; Rautenstrauss, Bernd
2008-07-01
Mutations in the mitofusin 2 (MFN2) gene are a major cause of primary axonal Charcot- Marie-Tooth (CMT) neuropathy. This study aims at further characterization of cerebral white matter alterations observed in patients with MFN2 mutations. Molecular genetic, magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), and diffusion tensor imaging (DTI) investigations were performed in four unrelated patients aged 7 to 38 years with early onset axonal CMT neuropathy. Three distinct and so far undescribed MFN2 mutations were detected. Two patients had secondary macrocephaly and mild diffuse predominantly periventricular white matter alterations on MRI. In addition, one boy had symmetrical T2-hyperintensities in both thalami. Two patients had optic atrophy, one of them with normal MRI. In three patients proton MRS revealed elevated concentrations of total N-acetyl compounds (neuronal marker), total creatine (found in all cells) and myo-inositol (astrocytic marker) in cerebral white and gray matter though with regional variation. These alterations were most pronounced in the two patients with abnormal MRI. DTI of these patients revealed mild reductions of fractional anisotropy and mild increase of mean diffusivity in white matter. The present findings indicate an enhanced cellular density in cerebral white matter of MFN2 neuropathy which is primarily due to a reactive gliosis without axonal damage and possibly accompanied by mild demyelination.
Higher-Order Motion-Compensation for In Vivo Cardiac Diffusion Tensor Imaging in Rats
Welsh, Christopher L.; DiBella, Edward V. R.; Hsu, Edward W.
2015-01-01
Motion of the heart has complicated in vivo applications of cardiac diffusion MRI and diffusion tensor imaging (DTI), especially in small animals such as rats where ultra-high-performance gradient sets are currently not available. Even with velocity compensation via, for example, bipolar encoding pulses, the variable shot-to-shot residual motion-induced spin phase can still give rise to pronounced artifacts. This study presents diffusion-encoding schemes that are designed to compensate for higher-order motion components, including acceleration and jerk, which also have the desirable practical features of minimal TEs and high achievable b-values. The effectiveness of these schemes was verified numerically on a realistic beating heart phantom, and demonstrated empirically with in vivo cardiac diffusion MRI in rats. Compensation for acceleration, and lower motion components, was found to be both necessary and sufficient for obtaining diffusion-weighted images of acceptable quality and SNR, which yielded the first in vivo cardiac DTI demonstrated in the rat. These findings suggest that compensation for higher order motion, particularly acceleration, can be an effective alternative solution to high-performance gradient hardware for improving in vivo cardiac DTI. PMID:25775486
Afacan, Onur; Gholipour, Ali; Mulkern, Robert V; Barnewolt, Carol E; Estroff, Judy A; Connolly, Susan A; Parad, Richard B; Bairdain, Sigrid; Warfield, Simon K
2016-12-01
To evaluate the feasibility of using diffusion-weighted magnetic resonance imaging (DW-MRI) to assess the fetal lung apparent diffusion coefficient (ADC) at 3 Tesla (T). Seventy-one pregnant women (32 second trimester, 39 third trimester) were scanned with a twice-refocused Echo-planar diffusion-weighted imaging sequence with 6 different b-values in 3 orthogonal diffusion orientations at 3T. After each scan, a region-of-interest (ROI) mask was drawn to select a region in the fetal lung and an automated robust maximum likelihood estimation algorithm was used to compute the ADC parameter. The amount of motion in each scan was visually rated. When scans with unacceptable levels of motion were eliminated, the lung ADC values showed a strong association with gestational age (P < 0.01), increasing dramatically between 16 and 27 weeks and then achieving a plateau around 27 weeks. We show that to get reliable estimates of ADC values of fetal lungs, a multiple b-value acquisition, where motion is either corrected or considered, can be performed. J. Magn. Reson. Imaging 2016;44:1650-1655. © 2016 International Society for Magnetic Resonance in Medicine.
Veraart, Jelle; Sijbers, Jan; Sunaert, Stefan; Leemans, Alexander; Jeurissen, Ben
2013-11-01
Linear least squares estimators are widely used in diffusion MRI for the estimation of diffusion parameters. Although adding proper weights is necessary to increase the precision of these linear estimators, there is no consensus on how to practically define them. In this study, the impact of the commonly used weighting strategies on the accuracy and precision of linear diffusion parameter estimators is evaluated and compared with the nonlinear least squares estimation approach. Simulation and real data experiments were done to study the performance of the weighted linear least squares estimators with weights defined by (a) the squares of the respective noisy diffusion-weighted signals; and (b) the squares of the predicted signals, which are reconstructed from a previous estimate of the diffusion model parameters. The negative effect of weighting strategy (a) on the accuracy of the estimator was surprisingly high. Multi-step weighting strategies yield better performance and, in some cases, even outperformed the nonlinear least squares estimator. If proper weighting strategies are applied, the weighted linear least squares approach shows high performance characteristics in terms of accuracy/precision and may even be preferred over nonlinear estimation methods. Copyright © 2013 Elsevier Inc. All rights reserved.
Dijkstra, Hildebrand; Dorrius, Monique D; Wielema, Mirjam; Pijnappel, Ruud M; Oudkerk, Matthijs; Sijens, Paul E
2016-12-01
To assess if specificity can be increased when semiautomated breast lesion analysis of quantitative diffusion-weighted imaging (DWI) is implemented after dynamic contrast-enhanced (DCE-) magnetic resonance imaging (MRI) in the workup of BI-RADS 3 and 4 breast lesions larger than 1 cm. In all, 120 consecutive patients (mean-age, 48 years; age range, 23-75 years) with 139 breast lesions (≥1 cm) were examined (2010-2014) with 1.5T DCE-MRI and DWI (b = 0, 50, 200, 500, 800, 1000 s/mm 2 ) and the BI-RADS classification and histopathology were obtained. For each lesion malignancy was excluded using voxelwise semiautomated breast lesion analysis based on previously defined thresholds for the apparent diffusion coefficient (ADC) and the three intravoxel incoherent motion (IVIM) parameters: molecular diffusion (D slow ), microperfusion (D fast ), and the fraction of D fast (f fast ). The sensitivity (Se), specificity (Sp), and negative predictive value (NPV) based on only IVIM parameters combined in parallel (D slow , D fast , and f fast ), or the ADC or the BI-RADS classification by DCE-MRI were compared. Subsequently, the Se, Sp, and NPV of the combination of the BI-RADS classification by DCE-MRI followed by the IVIM parameters in parallel (or the ADC) were compared. In all, 23 of 139 breast lesions were benign. Se and Sp of DCE-MRI was 100% and 30.4% (NPV = 100%). Se and Sp of IVIM parameters in parallel were 92.2% and 52.2% (NPV = 57.1%) and for the ADC 95.7% and 17.4%, respectively (NPV = 44.4%). In all, 26 of 139 lesions were classified as BI-RADS 3 (n = 7) or BI-RADS 4 (n = 19). DCE-MRI combined with ADC (Se = 99.1%, Sp = 34.8%) or IVIM (Se = 99.1%, Sp = 56.5%) did significantly improve (P = 0.016) Sp of DCE-MRI alone for workup of BI-RADS 3 and 4 lesions (NPV = 92.9%). Quantitative DWI has a lower NPV compared to DCE-MRI for evaluation of breast lesions and may therefore not be able to replace DCE-MRI; when implemented after DCE-MRI as problem solver for BI-RADS 3 and 4 lesions, the combined specificity improves significantly. J. Magn. Reson. Imaging 2016;44:1642-1649. © 2016 International Society for Magnetic Resonance in Medicine.
Pasini, Gabriella; Greco, Fulvia; Cremonini, Mauro A; Brandolini, Andrea; Consonni, Roberto; Gussoni, Maristella
2015-05-27
The aim of the present study was to characterize the structure of two different types of pasta, namely Triticum turgidum ssp. durum (cv. Saragolla) and Triticum monococcum ssp. monococcum (cv. Monlis), under different processing conditions. MRI analysis and NMR spectroscopy (i.e., T1 and T2 NMR relaxation times and diffusion parameters) were conducted on pasta, and (1)H NMR spectroscopic analysis of the chemical compounds released by pasta samples during the cooking process was performed. In addition, starch digestibility (enzimatically determined) was also investigated. The NMR results indicated that Saragolla pasta has a more compact structure, ascribed to pasta network and in particular to different technological gluten properties, that mainly determine the lower ability of Monlis pasta in binding water. These results correlate well with the lower rate of starch hydrolysis measured for Monlis pasta compared to Saragolla when both are dried at high temperature.
Zacharzewska-Gondek, Anna; Maksymowicz, Hanna; Szymczyk, Małgorzata; Sąsiadek, Marek; Bladowska, Joanna
2017-01-01
Restricted diffusion that is found on magnetic resonance diffusion-weighted imaging (DWI) typically indicates acute ischaemic stroke. However, restricted diffusion can also occur in other diseases, like metastatic brain tumours, which we describe in this case report. A 57-year-old male, with a diagnosis of small-cell cancer of the right lung (microcellular anaplastic carcinoma), was admitted with focal neurological symptoms. Initial brain MRI revealed multiple, disseminated lesions that were hyperintense on T2-weighted images and did not enhance after contrast administration; notably, some lesions manifested restricted diffusion on DWI images. Based on these findings, disseminated ischaemic lesions were diagnosed. On follow-up MRI that was performed after 2 weeks, we observed enlargement of the lesions; there were multiple, disseminated, sharply outlined, contrast-enhancing, oval foci with persistent restriction of diffusion. We diagnosed the lesions as disseminated brain metastases due to lung cancer. To our knowledge, this is the first description of a patient with brain metastases that were characterised by restricted diffusion and no contrast enhancement. Multiple, disseminated brain lesions, that are characterised by restricted diffusion on DWI, typically indicate acute or hyperacute ischemic infarcts; however, they can also be due to hypercellular metastases, even if no contrast enhancement is observed. This latter possibility should be considered particularly in patients with cancer.
Lee, So-Yeon; Jee, Won-Hee; Jung, Joon-Yong; Park, Michael Y; Kim, Sun-Ki; Jung, Chan-Kwon; Chung, Yang-Guk
2016-03-01
To determine the added value of diffusion-weighted imaging (DWI) to standard magnetic resonance imaging (MRI) to differentiate malignant from benign soft tissue tumours at 3.0 T. 3.0 T MR images including DWI in 63 patients who underwent surgery for soft tissue tumours were retrospectively analyzed. Two readers independently interpreted MRI for the presence of malignancy in two steps: standard MRI alone, standard MRI and DWI with qualitative and quantitative analysis combined. There were 34 malignant and 29 non-malignant soft tissue tumours. In qualitative analysis, hyperintensity relative to skeletal muscle was more frequent in malignant than benign tumours on DWI (P=0.003). In quantitative analysis, ADCs of malignant tumours were significantly lower than those of non-malignant tumours (P≤0.002): 759±385 vs. 1188±423 μm(2)/sec minimum ADC value, 941±440 vs. 1310±440 μm(2)/sec average ADC value. The mean sensitivity, specificity and accuracy of both readers were 96%, 72%, and 85% on standard MRI alone and 97%, 90%, and 94% on standard MRI with DWI. The addition of DWI to standard MRI improves the diagnostic accuracy for differentiation of malignant from benign soft tissue tumours at 3.0 T. DWI has added value for differentiating malignant from benign soft tissue tumours. Addition of DWI to standard MRI at 3.0 T improves the diagnostic accuracy. Measurements of both ADC min within solid portion and ADC av are helpful.
Winter, René M; Leibfarth, Sara; Schmidt, Holger; Zwirner, Kerstin; Mönnich, David; Welz, Stefan; Schwenzer, Nina F; la Fougère, Christian; Nikolaou, Konstantin; Gatidis, Sergios; Zips, Daniel; Thorwarth, Daniela
2018-05-07
Functional PET/MRI has great potential to improve radiotherapy planning (RTP). However, data integration requires imaging with radiotherapy-specific patient positioning. Here, we investigated the feasibility and image quality of radiotherapy-customized PET/MRI in head-and-neck cancer (HNC) patients using a dedicated hardware setup. Ten HNC patients were examined with simultaneous PET/MRI before treatment, with radiotherapy and diagnostic scan setup, respectively. We tested feasibility of radiotherapy-specific patient positioning and compared the image quality between both setups by pairwise image analysis of 18 F-FDG-PET, T1/T2-weighted and diffusion-weighted MRI. For image quality assessment, similarity measures including average symmetric surface distance (ASSD) of PET and MR-based tumor contours, MR signal-to-noise ratio (SNR) and mean apparent diffusion coefficient (ADC) value were used. PET/MRI in radiotherapy position was feasible - all patients were successfully examined. ASSD (median/range) of PET and MR contours was 0.6 (0.4-1.2) and 0.9 (0.5-1.3) mm, respectively. For T2-weighted MRI, a reduced SNR of -26.2% (-39.0--11.7) was observed with radiotherapy setup. No significant difference in mean ADC was found. Simultaneous PET/MRI in HNC patients using radiotherapy positioning aids is clinically feasible. Though SNR was reduced, the image quality obtained with a radiotherapy setup meets RTP requirements and the data can thus be used for personalized RTP. Copyright © 2018 The Author(s). Published by Elsevier B.V. All rights reserved.