Browsing by Subject "Diffusion MRI"
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Item Age‐dependent white matter disruptions after military traumatic brain injury: Multivariate analysis results from ENIGMA brain injury(Wiley, 2022) Bouchard, Heather C.; Sun, Delin; Dennis, Emily L.; Newsome, Mary R.; Disner, Seth G.; Elman, Jeremy; Silva, Annelise; Velez, Carmen; Irimia, Andrei; Davenport, Nicholas D.; Sponheim, Scott R.; Franz, Carol E.; Kremen, William S.; Coleman, Michael J.; Williams, M. Wright; Geuze, Elbert; Koerte, Inga K.; Shenton, Martha E.; Adamson, Maheen M.; Coimbra, Raul; Grant, Gerald; Shutter, Lori; George, Mark S.; Zafonte, Ross D.; McAllister, Thomas W.; Stein, Murray B.; Thompson, Paul M.; Wilde, Elisabeth A.; Tate, David F.; Sotiras, Aristeidis; Morey, Rajendra A.; Psychiatry, School of MedicineMild Traumatic brain injury (mTBI) is a signature wound in military personnel, and repetitive mTBI has been linked to age‐related neurogenerative disorders that affect white matter (WM) in the brain. However, findings of injury to specific WM tracts have been variable and inconsistent. This may be due to the heterogeneity of mechanisms, etiology, and comorbid disorders related to mTBI. Non‐negative matrix factorization (NMF) is a data‐driven approach that detects covarying patterns (components) within high‐dimensional data. We applied NMF to diffusion imaging data from military Veterans with and without a self‐reported TBI history. NMF identified 12 independent components derived from fractional anisotropy (FA) in a large dataset (n = 1,475) gathered through the ENIGMA (Enhancing Neuroimaging Genetics through Meta‐Analysis) Military Brain Injury working group. Regressions were used to examine TBI‐ and mTBI‐related associations in NMF‐derived components while adjusting for age, sex, post‐traumatic stress disorder, depression, and data acquisition site/scanner. We found significantly stronger age‐dependent effects of lower FA in Veterans with TBI than Veterans without in four components (q < 0.05), which are spatially unconstrained by traditionally defined WM tracts. One component, occupying the most peripheral location, exhibited significantly stronger age‐dependent differences in Veterans with mTBI. We found NMF to be powerful and effective in detecting covarying patterns of FA associated with mTBI by applying standard parametric regression modeling. Our results highlight patterns of WM alteration that are differentially affected by TBI and mTBI in younger compared to older military Veterans.Item Assessing pulsatile waveforms of paravascular cerebrospinal fluid dynamics using dynamic diffusion-weighted imaging (dDWI)(Elsevier, 2022-10-15) Wen, Qiuting; Tong, Yunjie; Zhou, Xiaopeng; Dzemidzic, Mario; Ho, Chang Yueh; Wu, Yu-Chien; Neurology, School of MedicineCerebrospinal fluid (CSF) in the paravascular spaces of the surface arteries (sPVS) is a vital pathway in brain waste clearance. Arterial pulsations may be the driving force of the paravascular flow, but its pulsatile pattern remains poorly characterized, and no clinically practical method for measuring its dynamics in the human brain is available. In this work, we introduce an imaging and quantification framework for in-vivo non-invasive assessment of pulsatile fluid dynamics in the sPVS. It used dynamic Diffusion-Weighted Imaging (dDWI) at a lower b-values of 150s/mm2 and retrospective gating to detect the slow flow of CSF while suppressing the fast flow of adjacent arterial blood. The waveform of CSF flow over a cardiac cycle was revealed by synchronizing the measurements with the heartbeat. A data-driven approach was developed to identify sPVS and allow automatic quantification of the whole-brain fluid waveforms. We applied dDWI to twenty-five participants aged 18-82 y/o. Results demonstrated that the fluid waveforms across the brain showed an explicit cardiac-cycle dependency, in good agreement with the vascular pumping hypothesis. Furthermore, the shape of the CSF waveforms closely resembled the pressure waveforms of the artery wall, suggesting that CSF dynamics is tightly related to artery wall mechanics. Finally, the CSF waveforms in aging participants revealed a strong age effect, with a significantly wider systolic peak observed in the older relative to younger participants. The peak widening may be associated with compromised vascular compliance and vessel wall stiffening in the older brain. Overall, the results demonstrate the feasibility, reproducibility, and sensitivity of dDWI for detecting sPVS fluid dynamics of the human brain. Our preliminary data suggest age-related alterations of the paravascular pumping. With an acquisition time of under six minutes, dDWI can be readily applied to study fluid dynamics in normal physiological conditions and cerebrovascular/neurodegenerative diseases.Item Assessing pulsatile waveforms of paravascular cerebrospinal fluid dynamics within the glymphatic pathways using dynamic diffusion-weighted imaging (dDWI)(Elsevier, 2022) Wen, Qiuting; Tong, Yunjie; Zhou, Xiaopeng; Dzemidzic, Mario; Ho, Chang Yueh; Wu, Yu-Chien; Radiology and Imaging Sciences, School of MedicineCerebrospinal fluid (CSF) in the paravascular spaces of the surface arteries (sPVS) is a vital pathway in brain waste clearance. Arterial pulsations may be the driving force of the paravascular flow, but its pulsatile pattern remains poorly characterized, and no clinically practical method for measuring its dynamics in the human brain is available. In this work, we introduce an imaging and quantification framework for in-vivo non-invasive assessment of pulsatile fluid dynamics in the sPVS. It used dynamic Diffusion-Weighted Imaging (dDWI) at a lower b-values of 150s/mm2 and retrospective gating to detect the slow flow of CSF while suppressing the fast flow of adjacent arterial blood. The waveform of CSF flow over a cardiac cycle was revealed by synchronizing the measurements with the heartbeat. A data-driven approach was developed to identify sPVS and allow automatic quantification of the whole-brain fluid waveforms. We applied dDWI to twenty-five participants aged 18-82 y/o. Results demonstrated that the fluid waveforms across the brain showed an explicit cardiac-cycle dependency, in good agreement with the vascular pumping hypothesis. Furthermore, the shape of the CSF waveforms closely resembled the pressure waveforms of the artery wall, suggesting that CSF dynamics is tightly related to artery wall mechanics. Finally, the CSF waveforms in aging participants revealed a strong age effect, with a significantly wider systolic peak observed in the older relative to younger participants. The peak widening may be associated with compromised vascular compliance and vessel wall stiffening in the older brain. Overall, the results demonstrate the feasibility, reproducibility, and sensitivity of dDWI for detecting sPVS fluid dynamics of the human brain. Our preliminary data suggest age-related alterations of the paravascular pumping. With an acquisition time of under six minutes, dDWI can be readily applied to study fluid dynamics in normal physiological conditions and cerebrovascular/neurodegenerative diseases.Item Bifurcated Topological Optimization for IVIM(Frontiers Media, 2021-12-15) Fadnavis, Shreyas; Endres, Stefan; Wen, Qiuting; Wu, Yu-Chien; Cheng, Hu; Koudoro, Serge; Rane, Swati; Rokem, Ariel; Garyfallidis, Eleftherios; Radiology and Imaging Sciences, School of MedicineIn this work, we shed light on the issue of estimating Intravoxel Incoherent Motion (IVIM) for diffusion and perfusion estimation by characterizing the objective function using simplicial homology tools. We provide a robust solution via topological optimization of this model so that the estimates are more reliable and accurate. Estimating the tissue microstructure from diffusion MRI is in itself an ill-posed and a non-linear inverse problem. Using variable projection functional (VarPro) to fit the standard bi-exponential IVIM model we perform the optimization using simplicial homology based global optimization to better understand the topology of objective function surface. We theoretically show how the proposed methodology can recover the model parameters more accurately and consistently by casting it in a reduced subspace given by VarPro. Additionally we demonstrate that the IVIM model parameters cannot be accurately reconstructed using conventional numerical optimization methods due to the presence of infinite solutions in subspaces. The proposed method helps uncover multiple global minima by analyzing the local geometry of the model enabling the generation of reliable estimates of model parameters.Item Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal aging(bioRxiv, 2023-05-18) Archer, Derek B.; Schilling, Kurt; Shashikumar, Niranjana; Jasodanand, Varuna; Moore, Elizabeth E.; Pechman, Kimberly R.; Bilgel, Murat; Beason-Held, Lori L.; An, Yang; Shafer, Andrea; Ferrucci, Luigi; Risacher, Shannon L.; Gifford, Katherine A.; Landman, Bennett A.; Jefferson, Angela L.; Saykin, Andrew J.; Resnick, Susan M.; Hohman, Timothy J.; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineIntroduction: It is unclear how rates of white matter microstructural decline differ between normal aging and abnormal aging. Methods: Diffusion MRI data from several well-established longitudinal cohorts of aging [Alzheimer's Neuroimaging Initiative (ADNI), Baltimore Longitudinal Study of Aging (BLSA), Vanderbilt Memory & Aging Project (VMAP)] was free-water corrected and harmonized. This dataset included 1,723 participants (age at baseline: 72.8±8.87 years, 49.5% male) and 4,605 imaging sessions (follow-up time: 2.97±2.09 years, follow-up range: 1-13 years, mean number of visits: 4.42±1.98). Differences in white matter microstructural decline in normal and abnormal agers was assessed. Results: While we found global decline in white matter in normal/abnormal aging, we found that several white matter tracts (e.g., cingulum bundle) were vulnerable to abnormal aging. Conclusions: There is a prevalent role of white matter microstructural decline in aging, and future large-scale studies in this area may further refine our understanding of the underlying neurodegenerative processes. Highlights: Longitudinal data was free-water corrected and harmonizedGlobal effects of white matter decline were seen in normal and abnormal agingThe free-water metric was most vulnerable to abnormal agingCingulum free-water was the most vulnerable to abnormal aging.Item Resolution and b value dependent structural connectome in ex vivo mouse brain(Elsevier, 2022) Crater, Stephanie; Maharjan, Surendra; Qi, Yi; Zhao, Qi; Cofer, Gary; Cook, James C.; Johnson, G. Allan; Wang, Nian; Radiology and Imaging Sciences, School of MedicineDiffusion magnetic resonance imaging has been widely used in both clinical and preclinical studies to characterize tissue microstructure and structural connectivity. The diffusion MRI protocol for the Human Connectome Project (HCP) has been developed and optimized to obtain high-quality, high-resolution diffusion MRI (dMRI) datasets. However, such efforts have not been fully explored in preclinical studies, especially for rodents. In this study, high quality dMRI datasets of mouse brains were acquired at 9.4T system from two vendors. In particular, we acquired a high-spatial resolution dMRI dataset (25 μm isotropic with 126 diffusion encoding directions), which we believe to be the highest spatial resolution yet obtained; and a high-angular resolution dMRI dataset (50 μm isotropic with 384 diffusion encoding directions), which we believe to be the highest angular resolution compared to the dMRI datasets at the microscopic resolution. We systematically investigated the effects of three important parameters that affect the final outcome of the connectome: b value (1000s/mm2 to 8000 s/mm2), angular resolution (10 to 126), and spatial resolution (25 µm to 200 µm). The stability of tractography and connectome increase with the angular resolution, where more than 50 angles is necessary to achieve consistent results. The connectome and quantitative parameters derived from graph theory exhibit a linear relationship to the b value (R2 > 0.99); a single-shell acquisition with b value of 3000 s/mm2 shows comparable results to the multi-shell high angular resolution dataset. The dice coefficient decreases and both false positive rate and false negative rate gradually increase with coarser spatial resolution. Our study provides guidelines and foundations for exploration of tradeoffs among acquisition parameters for the structural connectome in ex vivo mouse brain.Item Tau deposition and structural connectivity demonstrate differential association patterns with neurocognitive tests(Springer, 2022) Hall, Zack; Chien, Billy; Zhao, Yi; Risacher, Shannon L.; Saykin, Andrew J.; Wu, Yu‑Chien; Wen, Qiuting; Biostatistics and Health Data Science, School of MedicineTau neurofibrillary tangles have a central role in the pathogenesis of Alzheimer's Disease (AD). Mounting evidence indicates that the propagation of tau is assisted by brain connectivity with weakened white-matter integrity along the propagation pathways. Recent advances in tau positron emission tomography tracers and diffusion magnetic resonance imaging allow the visualization of tau pathology and white-matter connectivity of the brain in vivo. The current study aims to investigate how tau deposition and structural connectivity are associated with memory function in prodromal AD. In this study, tau accumulation and structural connectivity data from 83 individuals (57 cognitively normal participants and 26 participants with mild cognitive impairment) were associated with neurocognitive test scores. Statistical analyses were performed in 70 cortical/subcortical brain regions to determine: 1. the level of association between tau and network metrics extracted from structural connectivity and 2. the association patterns of brain memory function with tau accumulation and network metrics. The results showed that tau accumulation and network metrics were correlated in early tau deposition regions. Furthermore, tau accumulation was associated with worse performance in almost all neurocognitive tests performance evaluated in the study. In comparison, decreased network connectivity was associated with declines in the delayed memory recall in Craft Stories and Benson Figure Copy. Interaction analysis indicates that tau deposition and dysconnectivity have a synergistic effect on the delayed Benson Figure Recall. Overall, our findings indicate that both tau deposition and structural dysconnectivity are associated with neurocognitive dysfunction. They also suggest that tau-PET may have better sensitivity to neurocognitive performance than diffusion MRI-derived measures of white-matter connectivity.Item The impact of edema and fiber crossing on diffusion MRI metrics assessed in an ex vivo nerve phantom: Multi-tensor model vs. diffusion orientation distribution function(Wiley, 2021) Ye, Zezhong; Gary, Sam E.; Sun, Peng; Mustafi, Sourajit Mitra; Glenn, George Russell; Yeh, Fang-Cheng; Merisaari, Harri; Song, Chunyu; Yang, Ruimeng; Huang, Guo-Shu; Kao, Hung-Wen; Lin, Chien-Yuan; Wu, Yu-Chien; Jensen, Jens H.; Song, Sheng-Kwei; Radiology and Imaging Sciences, School of MedicineDiffusion tensor imaging (DTI) has been employed for over two decades to noninvasively quantify central nervous system (CNS) diseases/injuries. However, DTI is an inadequate simplification of diffusion modeling in the presence of co-existing inflammation, edema, and crossing nerve fibers. We employed a tissue phantom using fixed mouse trigeminal nerves coated with various amounts of agarose gel to mimic crossing fibers in the presence of vasogenic edema. Diffusivity measures derived by DTI and diffusion basis spectrum imaging (DBSI) were compared at increasing levels of simulated edema and degrees of fiber crossing. Further, we assessed the ability of DBSI, diffusion kurtosis imaging (DKI), generalized q-sampling imaging (GQI), q-ball imaging (QBI), and neurite orientation dispersion and density imaging (NODDI) to resolve fiber crossing, in reference to the gold standard angles measured from structural images. DTI-computed diffusivities and fractional anisotropy (FA) were significantly confounded by gel-mimicked edema and crossing fibers. Conversely, DBSI calculated accurate diffusivities of individual fibers regardless of the extent of simulated edema and degrees of fiber crossing angles. Additionally, DBSI accurately and consistently estimated crossing angles in various conditions of gel-mimicked edema when comparing with gold standard (r2=0.92, p=1.9×10−9, bias=3.9°). Small crossing angles and edema significantly impact dODF, making DKI, GQI and QBI less accurate in detecting and estimating fibers crossing angles. Lastly, we used diffusion tensor ellipsoids to demonstrate that DBSI resolves the confounds of edema and crossing fiber in peritumoral edema region from a patient with lung cancer metastasis while DTI failed. In summary, DBSI is able to separate two crossing fibers and accurately recover their diffusivities in a complex environment characterized by increasing crossing angles and amounts of gel-mimicked edema. DBSI also indicated better angular resolution compared with DKI, QBI and GQI.Item White matter microstructural metrics are sensitively associated with clinical staging in Alzheimer's disease(Wiley, 2023-05-17) Yang, Yisu; Schilling, Kurt; Shashikumar, Niranjana; Jasodanand, Varuna; Moore, Elizabeth E.; Pechman, Kimberly R.; Bilgel, Murat; Beason-Held, Lori L.; An, Yang; Shafer, Andrea; Risacher, Shannon L.; Landman, Bennett A.; Jefferson, Angela L.; Saykin, Andrew J.; Resnick, Susan M.; Hohman, Timothy J.; Archer, Derek B.; Alzheimer's Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineIntroduction: White matter microstructure may be abnormal along the Alzheimer's disease (AD) continuum. Methods: Diffusion magnetic resonance imaging (dMRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 627), Baltimore Longitudinal Study of Aging (BLSA, n = 684), and Vanderbilt Memory & Aging Project (VMAP, n = 296) cohorts were free-water (FW) corrected and conventional, and FW-corrected microstructural metrics were quantified within 48 white matter tracts. Microstructural values were subsequently harmonized using the Longitudinal ComBat technique and inputted as independent variables to predict diagnosis (cognitively unimpaired [CU], mild cognitive impairment [MCI], AD). Models were adjusted for age, sex, race/ethnicity, education, apolipoprotein E (APOE) ε4 carrier status, and APOE ε2 carrier status. Results: Conventional dMRI metrics were associated globally with diagnostic status; following FW correction, the FW metric itself exhibited global associations with diagnostic status, but intracellular metric associations were diminished. Discussion: White matter microstructure is altered along the AD continuum. FW correction may provide further understanding of the white matter neurodegenerative process in AD. Highlights: Longitudinal ComBat successfully harmonized large-scale diffusion magnetic resonance imaging (dMRI) metrics.Conventional dMRI metrics were globally sensitive to diagnostic status. Free-water (FW) correction mitigated intracellular associations with diagnostic status.The FW metric itself was globally sensitive to diagnostic status. Multivariate conventional and FW-corrected models may provide complementary information.