Application of diffusion tensor imaging for detecting structural changes in the brain of schizophrenic patients

Situ, Weijun; Liao, Haiyan; Zhou, Bin; Xia, Xibin; Tan, Chongqing

doi:10.3109/13651501.2014.988270

Cited by 3 publications

(1 citation statement)

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“…Indeed, the analysis of diffusivity GM changes using MD has shown to be promising for detecting abnormalities in Alzheimer disease (Weston et al, 2015 ) and multiple sclerosis (Ceccarelli et al, 2007 ). GM FA alterations were also demonstrated in schizophrenic patients in Situ et al ( 2015 ), reporting increased MD and decreased FA values in patients compared to controls. In stroke patients, studies in GM are less consistent and generally consider the tissues in the contralateral hemisphere as normal appearing, although regions remote (upstream or downstream) from the infarct have been demonstrated to undergo marked changes over a time course of 2 days to 1 year (Sotak, 2002 ).…”

Section: Discussionmentioning

confidence: 76%

On the Viability of Diffusion MRI-Based Microstructural Biomarkers in Ischemic Stroke

et al. 2018

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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.

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Section: Discussionmentioning

confidence: 76%

On the Viability of Diffusion MRI-Based Microstructural Biomarkers in Ischemic Stroke

et al. 2018

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Transdiagnostic role of glutamate and white matter damage in neuropsychiatric disorders: A Systematic Review

Luttenbacher

Philips

Kazemi

et al. 2022

Journal of Psychiatric Research

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White matter and schizophrenia: A meta-analysis of voxel-based morphometry and diffusion tensor imaging studies

Vitolo

Tatu

Pignolo

et al. 2017

Psychiatry Research: Neuroimaging

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Voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) are the most implemented methodologies to detect alterations of both gray and white matter (WM). However, the role of WM in mental disorders is still not well defined. We aimed at clarifying the role of WM disruption in schizophrenia and at identifying the most frequently involved brain networks. A systematic literature search was conducted to identify VBM and DTI studies focusing on WM alterations in patients with schizophrenia compared to control subjects. We selected studies reporting the coordinates of WM reductions and we performed the anatomical likelihood estimation (ALE). Moreover, we labeled the WM bundles with an anatomical atlas and compared VBM and DTI ALE-scores of each significant WM tract. A total of 59 studies were eligible for the meta-analysis. WM alterations were reported in 31 and 34 foci with VBM and DTI methods, respectively. The most occurred WM bundles in both VBM and DTI studies and largely involved in schizophrenia were long projection fibers, callosal and commissural fibers, part of motor descending fibers, and fronto-temporal-limbic pathways. The meta-analysis showed a widespread WM disruption in schizophrenia involving specific cerebral circuits instead of well-defined regions.

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Application of diffusion tensor imaging for detecting structural changes in the brain of schizophrenic patients

Abstract: This study suggested that structural abnormalities in the frontal region of gray matter and white matter are present at the same time in patients with schizophrenia.

Cited by 3 publications

References 20 publications

On the Viability of Diffusion MRI-Based Microstructural Biomarkers in Ischemic Stroke

On the Viability of Diffusion MRI-Based Microstructural Biomarkers in Ischemic Stroke

Transdiagnostic role of glutamate and white matter damage in neuropsychiatric disorders: A Systematic Review

White matter and schizophrenia: A meta-analysis of voxel-based morphometry and diffusion tensor imaging studies

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