scholarly journals Disorganization of white matter architecture in major depressive disorder: a meta-analysis of diffusion tensor imaging with tract-based spatial statistics

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Guangxiang Chen ◽  
Xinyu Hu ◽  
Lei Li ◽  
Xiaoqi Huang ◽  
Su Lui ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Depressive Disorder ◽  
Spatial Statistics ◽  
Diffusion Tensor ◽  
Meta Analysis ◽  
Major Depressive ◽  
Tract Based Spatial Statistics

scholarly journals White Matter Abnormalities in Patients With Parkinson's Disease: A Meta-Analysis of Diffusion Tensor Imaging Using Tract-Based Spatial Statistics

2021 ◽  
Vol 12 ◽  
Author(s):  
Xia Wei ◽  
Chunyan Luo ◽  
Qian Li ◽  
Na Hu ◽  
Yuan Xiao ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Spatial Statistics ◽  
Diffusion Tensor ◽  
Meta Analysis ◽  
The Body ◽  
Online Databases ◽  
Tract Based Spatial Statistics

Background: Tract-based spatial statistics (TBSS) studies based on diffusion tensor imaging (DTI) have revealed extensive abnormalities in white matter (WM) fibers of Parkinson's disease (PD); however, the results were inconsistent. Therefore, a meta-analytical approach was used in this study to find the most prominent and replicable WM abnormalities of PD.Methods: Online databases were systematically searched for all TBSS studies comparing fractional anisotropy (FA) between patients with PD and controls. Subsequently, we performed the meta-analysis using a coordinate-based meta-analytic software called seed-based d mapping. Meanwhile, meta-regression was performed to explore the potential correlation between the alteration of FA and the clinical characteristics of PD.Results: Out of a total of 1,701 studies that were identified, 23 studies were included. Thirty datasets, including 915 patients (543 men) with PD and 836 healthy controls (449 men), were included in the current study. FA reduction was identified in the body of the corpus callosum (CC; 245 voxels; z = −1.739; p < 0.001) and the left inferior fronto-occipital fasciculus (IFOF) 118 voxels; z = −1.182; p < 0.001). Both CC and IFOF maintained significance in the sensitivity analysis. No increase in FA was identified, but the percentage of male patients with PD was positively associated with the value of FA in the body of the CC.Conclusions: Although some limitations exist, DTI is regarded as a valid way to identify the pathophysiology of PD. It could be more beneficial to integrate DTI parameters with other MRI techniques to explore brain degeneration in PD.

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