Browsing by Author "Mustafi, Sourajit Mitra"

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    Acute White-Matter Abnormalities in Sports-Related Concussion: A Diffusion Tensor Imaging Study from the NCAA-DoD CARE Consortium
    (Mary Ann Liebert, 2018-11-15) Mustafi, Sourajit Mitra; Harezlak, Jaroslaw; Koch, Kevin M.; Nencka, Andrew S.; Meier, Timothy B.; West, John D.; Giza, Christopher C.; DiFiori, John P.; Guskiewicz, Kevin M.; Mihalik, Jason P.; LaConte, Stephen M.; Duma, Stefan M.; Broglio, Steven P.; Saykin, Andrew J.; McCrea, Michael; McAllister, Thomas W.; Wu, Yu-Chien; Radiology and Imaging Sciences, School of Medicine
    Sports-related concussion (SRC) is an important public health issue. Although standardized assessment tools are useful in the clinical management of acute concussion, the underlying pathophysiology of SRC and the time course of physiological recovery after injury remain unclear. In this study, we used diffusion tensor imaging (DTI) to detect white matter alterations in football players within 48 h after SRC. As part of the NCAA-DoD CARE Consortium study of SRC, 30 American football players diagnosed with acute concussion and 28 matched controls received clinical assessments and underwent advanced magnetic resonance imaging scans. To avoid selection bias and partial volume effects, whole-brain skeletonized white matter was examined by tract-based spatial statistics to investigate between-group differences in DTI metrics and their associations with clinical outcome measures. Mean diffusivity was significantly higher in brain white matter of concussed athletes, particularly in frontal and subfrontal long white matter tracts. In the concussed group, axial diffusivity was significantly correlated with the Brief Symptom Inventory and there was a similar trend with the symptom severity score of the Sport Concussion Assessment Tool. In addition, concussed athletes with higher fractional anisotropy performed better on the cognitive component of the Standardized Assessment of Concussion. Overall, the results of this study are consistent with the hypothesis that SRC is associated with changes in white matter tracts shortly after injury, and these differences are correlated clinically with acute symptoms and functional impairments.
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    The Impact of Edema and Fiber Crossing on Diffusion MRI Metrics: DBSI vs. Diffusion ODF
    (Wiley, 2021) Ye, Zezhong; Gary, Sam E.; Sun, Peng; Mustafi, Sourajit Mitra; Glenn, George Russell; Yeh, Fang-Cheng; Merisaari, Harri; Huang, Guo-Shu; Kao, Hung-Wen; Lin, Chien-Yuan; Wu, Yu-Chien; Jensen, Jens H.; Song, Sheng-Kwei; Radiology and Imaging Sciences, School of Medicine
    Purpose Diffusion 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. Methods 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. Results DTI-computed diffusivities and fractional anisotropy (FA) were significantly confounded by gelmimicked 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. Additionaly, 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 sinficantly impact dODF, making DKI, GQI and QBI less accurate in detecting and estimating fibers corrsing angles. Lastly, we demonstrate DBSI’s superiority over DTI for recovering and delineating white matter tracts in peritumoral edema for preoperative planning of surgical resection. Conclusions 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 capability compared with DKI, QBI and GQI.
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    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 Medicine
    Diffusion 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.