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https://www.readbyqxmd.com/read/29149383/diffusion-mri-in-pediatric-brain-injury
#1
Emily L Dennis, Talin Babikian, Christopher C Giza, Paul M Thompson, Robert F Asarnow
Traumatic brain injury (TBI) is a major public health issue around the world and can be especially devastating in children as TBI can derail cognitive and social development. White matter (WM) is particularly vulnerable to disruption post-TBI, as myelination is ongoing during this period. Diffusion magnetic resonance imaging (dMRI) is a versatile modality for identifying and quantifying WM disruption and can detect diffuse axonal injury (DAI or TAI (traumatic axonal injury)). This review covers dMRI studies of pediatric TBI, including mild to severe injuries, and covering all periods post-injury...
October 2017: Child's Nervous System: ChNS: Official Journal of the International Society for Pediatric Neurosurgery
https://www.readbyqxmd.com/read/29126955/white-matter-changes-correlates-of-peripheral-neuroinflammation-in-patients-with-parkinson-s-disease
#2
Maryam Haghashomar, Farzaneh Rahmani, Mohammad Hadi Aarabi, Shima Shahjouei, Soheila Sobhnai, Maryam Rahmani
Neuroinflammatory pathology has long been identified to contribute to the pathology of Parkinson disease. Early microstructural changes in white matter tracts might give a clue for earlier detection of PD. We investigated through diffusion MRI connectometry the structural correlates of white matter tracts of 81 patients with PD with whole blood neutrophil to lymphocyte ratio (NLR), controlling for age and sex. Diffusion data were reconstructed in the MNI space using q-space diffeomorphic reconstruction to obtain the spin distribution function...
November 7, 2017: Neuroscience
https://www.readbyqxmd.com/read/29120867/quantifying-the-ultrastructure-of-carotid-arteries-using-high-resolution-micro-diffusion-tensor-imaging-comparison-of-intact-versus-open-cut-tissue
#3
Syed Salman Shahid, Robert T Gaul, Christian Kerskens, Vittoria Flamini, Caitríona Lally
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 µm(3) 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...
November 9, 2017: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/29093806/low-rank-and-sparse-decomposition-model-for-accelerating-dynamic-mri-reconstruction
#4
Junbo Chen, Shouyin Liu, Min Huang
The reconstruction of dynamic magnetic resonance imaging (dMRI) from partially sampled k-space data has to deal with a trade-off between the spatial resolution and temporal resolution. In this paper, a low-rank and sparse decomposition model is introduced to resolve this issue, which is formulated as an inverse problem regularized by robust principal component analysis (RPCA). The inverse problem can be solved by convex optimization method. We propose a scalable and fast algorithm based on the inexact augmented Lagrange multipliers (IALM) to carry out the convex optimization...
2017: Journal of Healthcare Engineering
https://www.readbyqxmd.com/read/29092950/slicerdmri-open-source-diffusion-mri-software-for-brain-cancer-research
#5
Isaiah Norton, Walid Ibn Essayed, Fan Zhang, Sonia Pujol, Alex Yarmarkovich, Alexandra J Golby, Gordon Kindlmann, Demian Wasserman, Raul San Jose Estepar, Yogesh Rathi, Steve Pieper, Ron Kikinis, Hans J Johnson, Carl-Fredrik Westin, Lauren J O'Donnell
Diffusion MRI (dMRI) is the only noninvasive method for mapping white matter connections in the brain. We describe SlicerDMRI, a software suite that enables visualization and analysis of dMRI for neuroscientific studies and patient-specific anatomic assessment. SlicerDMRI has been successfully applied in multiple studies of the human brain in health and disease, and here, we especially focus on its cancer research applications. As an extension module of the 3D Slicer medical image computing platform, the SlicerDMRI suite enables dMRI analysis in a clinically relevant multimodal imaging workflow...
November 1, 2017: Cancer Research
https://www.readbyqxmd.com/read/29075681/subject-specific-structural-parcellations-based-on-randomized-ab-divergences
#6
Nicolas Honnorat, Drew Parker, Birkan Tunç, Christos Davatzikos, Ragini Verma
Brain parcellation provides a means to approach the brain in smaller regions. It also affords an appropriate dimensionality reduction in the creation of connectomes. Most approaches to creating connectomes start with registering individual scans to a template, which is then parcellated. Data processing usually ends with the projection of individual scans onto the parcellation for extracting individual biomarkers, such as connectivity signatures. During this process, registration errors can significantly alter the quality of biomarkers...
September 2017: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
https://www.readbyqxmd.com/read/29074279/histological-validation-of-diffusion-mri-fiber-orientation-distributions-and-dispersion
#7
Kurt G Schilling, Vaibhav Janve, Yurui Gao, Iwona Stepniewska, Bennett A Landman, Adam W Anderson
Diffusion magnetic resonance imaging (dMRI) is widely used to probe tissue microstructure, and is currently the only non-invasive way to measure the brain's fiber architecture. While a large number of approaches to recover the intra-voxel fiber structure have been utilized in the scientific community, a direct, 3D, quantitative validation of these methods against relevant histological fiber geometries is lacking. In this study, we investigate how well different high angular resolution diffusion imaging (HARDI) models and reconstruction methods predict the ground-truth histologically defined fiber orientation distribution (FOD), as well as investigate their behavior over a range of physical and experimental conditions...
October 23, 2017: NeuroImage
https://www.readbyqxmd.com/read/29060679/spatial-regularization-based-on-dmri-to-solve-eeg-meg-inverse-problem
#8
Brahim Belaoucha, Theodore Papadopoulo
In this paper, we present a new approach to reconstruct dipole magnitudes of a distributed source model for magnetoencephalographic (MEG) and electroencephalographic (EEG). This approach is based on the structural homogeneity of the cortical regions which are obtained using diffusion MRI (dMRI). First, we parcellate the cortical surface into functional regions using structural information. Then, we use a weighting matrix that relates the dipoles' magnitudes of sources inside these functional regions. The weights are based on the region's structural homogeneity...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/29046903/fod-restoration-for-enhanced-mapping-of-white-matter-lesion-connectivity
#9
Wei Sun, Lilyana Amezcua, Yonggang Shi
To achieve improved understanding of white matter (WM) lesions and their effect on brain functions, it is important to obtain a comprehensive map of their connectivity. However, changes of the cellular environment in WM lesions attenuate diffusion MRI (dMRI) signals and make the robust estimation of fiber orientation distributions (FODs) difficult. In this work, we integrate techniques from image inpainting and compartment modeling to develop a novel method for enhancing FOD estimation in WM lesions from multi-shell dMRI, which is becoming increasingly popular with the success of the Human Connectome Project (HCP)...
September 2017: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
https://www.readbyqxmd.com/read/29024679/short-range-connections-in-the-developmental-connectome-during-typical-and-atypical-brain-maturation
#10
REVIEW
Minhui Ouyang, Huiying Kang, John A Detre, Timothy P L Roberts, Hao Huang
The human brain is remarkably complex with connectivity constituting its basic organizing principle. Although long-range connectivity has been focused on in most research, short-range connectivity is characterized by unique and spatiotemporally heterogeneous dynamics from infancy to adulthood. Alterations in the maturational dynamics of short-range connectivity has been associated with neuropsychiatric disorders, such as autism and schizophrenia. Recent advances in neuroimaging techniques, especially diffusion magnetic resonance imaging (dMRI), resting-state functional MRI (rs-fMRI), electroencephalography (EEG) and magnetoencephalography (MEG), have made quantification of short-range connectivity possible in pediatric populations...
October 9, 2017: Neuroscience and Biobehavioral Reviews
https://www.readbyqxmd.com/read/28982075/non-parametric-graphnet-regularized-representation-of-dmri-in-space-and-time
#11
Rutger H J Fick, Alexandra Petiet, Mathieu Santin, Anne-Charlotte Philippe, Stephane Lehericy, Rachid Deriche, Demian Wassermann
Effective representation of the four-dimensional diffusion MRI signal - varying over three-dimensional q-space and diffusion time τ - is a sought-after and still unsolved challenge in diffusion MRI (dMRI). We propose a functional basis approach that is specifically designed to represent the dMRI signal in this qτ-space. Following recent terminology, we refer to our qτ-functional basis as "qτ-dMRI". qτ-dMRI can be seen as a time-dependent realization of q-space imaging by Paul Callaghan and colleagues. We use GraphNet regularization - imposing both signal smoothness and sparsity - to drastically reduce the number of diffusion-weighted images (DWIs) that is needed to represent the dMRI signal in the qτ-space...
September 14, 2017: Medical Image Analysis
https://www.readbyqxmd.com/read/28980973/quantifying-the-ultrastructure-of-carotid-artery-using-high-resolution-micro-diffusion-tensor-imaging-comparison-of-intact-vs-open-cut-tissue
#12
Syed Salman Shahid, Robert Gaul, Christian M Kerskens, Vittoria Flamini, Caitriona Lally
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 µm<sup>3</sup> in less than 2 hours 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...
October 5, 2017: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/28952937/single-and-multiple-shell-uniform-sampling-schemes-for-diffusion-mri-using-spherical-codes
#13
Jian Cheng, Dinggang Shen, Pew-Thian Yap, Peter J Basser
In diffusion MRI (dMRI), a good sampling scheme is important for efficient acquisition and robust reconstruction. Diffusion weighted signal is normally acquired on single or multiple shells in q-space. Signal samples are typically distributed uniformly on different shells to make them invariant to the orientation of structures within tissue, or the laboratory coordinate frame. The Electrostatic Energy Minimization (EEM) method, originally proposed for single shell sampling scheme in dMRI, was recently generalized to multi-shell schemes, called Generalized EEM (GEEM)...
September 25, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28944347/fiber-orientation-estimation-guided-by-a-deep-network
#14
Chuyang Ye, Jerry L Prince
Diffusion magnetic resonance imaging (dMRI) is currently the only tool for noninvasively imaging the brain's white matter tracts. The fiber orientation (FO) is a key feature computed from dMRI for tract reconstruction. Because the number of FOs in a voxel is usually small, dictionary-based sparse reconstruction has been used to estimate FOs. However, accurate estimation of complex FO configurations in the presence of noise can still be challenging. In this work we explore the use of a deep network for FO estimation in a dictionary-based framework and propose an algorithm named Fiber Orientation Reconstruction guided by a Deep Network (FORDN)...
September 2017: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
https://www.readbyqxmd.com/read/28936280/enhancing-diffusion-mri-measures-by-integrating-grey-and-white-matter-morphometry-with-hyperbolic-wasserstein-distance
#15
Wen Zhang, Jie Shi, Jun Yu, Liang Zhan, Paul M Thompson, Yalin Wang
In order to improve the preclinical diagnose of Alzheimer's disease (AD), there is a great deal of interest in analyzing the AD related brain structural changes with magnetic resonance image (MRI) analyses. As the major features, variation of the structural connectivity and the cortical surface morphometry provide different views of structural changes to determine whether AD is present on presymptomatic patients. However, the large scale tensor-valued information and relatively low imaging resolution in diffusion MRI (dMRI) have created huge challenges for analysis...
2017: Proceedings of the IEEE International Symposium on Biomedical Imaging: from Nano to Macro
https://www.readbyqxmd.com/read/28936158/bayesian-tractography-using-geometric-shape-priors
#16
Xiaoming Dong, Zhengwu Zhang, Anuj Srivastava
The problem of estimating neuronal fiber tracts connecting different brain regions is important for various types of brain studies, including understanding brain functionality and diagnosing cognitive impairments. The popular techniques for tractography are mostly sequential-tracts are grown sequentially following principal directions of local water diffusion profiles. Despite several advancements on this basic idea, the solutions easily get stuck in local solutions, and can't incorporate global shape information...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28935239/te-dependent-diffusion-imaging-teddi-distinguishes-between-compartmental-t2-relaxation-times
#17
Jelle Veraart, Dmitry S Novikov, Els Fieremans
Biophysical modeling of macroscopic diffusion-weighted MRI signal in terms of microscopic cellular parameters holds the promise of quantifying the integrity of white matter. Unfortunately, even fairly simple multi-compartment models of proton diffusion in the white matter do not provide a unique, biophysically plausible solution. Here we report a nontrivial diffusion MRI signal dependence on echo time (TE) in human white matter in vivo. We demonstrate that such TE dependence originates from compartment-specific T2 values and that it is a promising "orthogonal measure" able to break the degeneracy in parameter estimation, and to yield important relaxation metrics robustly...
September 19, 2017: NeuroImage
https://www.readbyqxmd.com/read/28928638/affective-circuitry-alterations-in-patients-with-trigeminal-neuralgia
#18
Dave J Hayes, David Q Chen, Jidan Zhong, Ariel Lin, Brendan Behan, Matthew Walker, Mojgan Hodaie
Trigeminal neuralgia (TN) is a severe chronic neuropathic facial pain disorder. Affect-related behavioral and structural brain changes have been noted across chronic pain disorders, but have not been well-studied in TN. We examined the potential impact of TN (37 patients: 23 with right-sided TN, 14 with left-sided TN), compared to age- and sex-matched healthy controls, on three major white matter tracts responsible for carrying affect-related signals-i.e., cingulum, fornix, and medial forebrain bundle. Diffusion magnetic resonance imaging (dMRI), deterministic multi-tensor tractography for tract modeling, and a model-driven region-of-interest approach was used...
2017: Frontiers in Neuroanatomy
https://www.readbyqxmd.com/read/28915311/can-increased-spatial-resolution-solve-the-crossing-fiber-problem-for-diffusion-mri
#19
Kurt Schilling, Yurui Gao, Vaibhav Janve, Iwona Stepniewska, Bennett A Landman, Adam W Anderson
It is now widely recognized that voxels with crossing fibers or complex geometrical configurations present a challenge for diffusion MRI (dMRI) reconstruction and fiber tracking, as well as microstructural modeling of brain tissues. This "crossing fiber" problem has been estimated to affect anywhere from 30% to as many as 90% of white matter voxels, and it is often assumed that increasing spatial resolution will decrease the prevalence of voxels containing multiple fiber populations. The aim of this study is to estimate the extent of the crossing fiber problem as we progressively increase the spatial resolution, with the goal of determining whether it is possible to mitigate this problem with higher resolution spatial sampling...
December 2017: NMR in Biomedicine
https://www.readbyqxmd.com/read/28910696/tissue-microstructure-estimation-using-a-deep-network-inspired-by-a-dictionary-based-framework
#20
Chuyang Ye
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...
September 6, 2017: Medical Image Analysis
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