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Browsing by Subject "Q-space imaging"
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Item Detecting white matter alterations in multiple sclerosis using advanced diffusion magnetic resonance imaging(Wolters Kluwer, 2019-01) Mustafi, Sourajit M.; Harezlak, Jaroslaw; Kodiweera, Chandana; Randolph, Jennifer S.; Ford, James C.; Wishart, Heather A.; Wu, Yu-Chien; Radiology and Imaging Sciences, School of MedicineMultiple sclerosis is a neurodegenerative and inflammatory disease, a hallmark of which is demyelinating lesions in the white matter. We hypothesized that alterations in white matter microstructures can be non-invasively characterized by advanced diffusion magnetic resonance imaging. Seven diffusion metrics were extracted from hybrid diffusion imaging acquisitions via classic diffusion tensor imaging, neurite orientation dispersion and density imaging, and q-space imaging. We investigated the sensitivity of the diffusion metrics in 36 sets of regions of interest in the brain white matter of six female patients (age 52.8 ± 4.3 years) with multiple sclerosis. Each region of interest set included a conventional T2-defined lesion, a matched perilesion area, and normal-appearing white matter. Six patients with multiple sclerosis (n = 5) or clinically isolated syndrome (n = 1) at a mild to moderate disability level were recruited. The patients exhibited microstructural alterations from normal-appearing white matter transitioning to perilesion areas and lesions, consistent with decreased tissue restriction, decreased axonal density, and increased classic diffusion tensor imaging diffusivity. The findings suggest that diffusion compartment modeling and q-space analysis appeared to be sensitive for detecting subtle microstructural alterations between perilesion areas and normal-appearing white matter.Item Hybrid Diffusion Imaging in Mild Traumatic Brain Injury(Mary Ann Liebert, 2018-10-15) Wu, Yu-Chien; Mustafi, Sourajit M.; Harezlak, Jaroslaw; Kodiweera, Chandana; Flashman, Laura A.; McAllister, Thomas W.; Radiology and Imaging Sciences, School of MedicineMild traumatic brain injury (mTBI) is an important public health problem. Although conventional medical imaging techniques can detect moderate-to-severe injuries, they are relatively insensitive to mTBI. In this study, we used hybrid diffusion imaging (HYDI) to detect white matter alterations in 19 patients with mTBI and 23 other trauma control patients. Within 15 days (standard deviation = 10) of brain injury, all subjects underwent magnetic resonance HYDI and were assessed with a battery of neuropsychological tests of sustained attention, memory, and executive function. Tract-based spatial statistics (TBSS) was used for voxel-wise statistical analyses within the white matter skeleton to study between-group differences in diffusion metrics, within-group correlations between diffusion metrics and clinical outcomes, and between-group interaction effects. The advanced diffusion imaging techniques, including neurite orientation dispersion and density imaging (NODDI) and q-space analyses, appeared to be more sensitive then classic diffusion tensor imaging. Only NODDI-derived intra-axonal volume fraction (Vic) demonstrated significant group differences (i.e., 5-9% lower in the injured brain). Within the mTBI group, Vic and a q-space measure, P0, correlated with 6 of 10 neuropsychological tests, including measures of attention, memory, and executive function. In addition, the direction of correlations differed significantly between groups (R2 > 0.71 and pinteration < 0.03). Specifically, in the control group, higher Vic and P0 were associated with better performances on clinical assessments, whereas in the mTBI group, higher Vic and P0 were associated with worse performances with correlation coefficients >0.83. In summary, the NODDI-derived axonal density index and q-space measure for tissue restriction demonstrated superior sensitivity to white matter changes shortly after mTBI. These techniques hold promise as a neuroimaging biomarker for mTBI.