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Frontiers in Neuroscience 2020Anorexia nervosa (AN) is a debilitating illness whose neural basis remains unclear. Studies using tract-based spatial statistics (TBSS) with diffusion tensor imaging...
Anorexia nervosa (AN) is a debilitating illness whose neural basis remains unclear. Studies using tract-based spatial statistics (TBSS) with diffusion tensor imaging (DTI) have demonstrated differences in white matter (WM) microarchitecture in AN, but the findings are inconclusive and controversial. To identify the most consistent WM abnormalities among previous TBSS studies of differences in WM microarchitecture in AN. By systematically searching online databases, a total of 11 datasets were identified, including 245 patients with AN and 246 healthy controls (HC). We used Seed-based d Mapping to analyze fractional anisotropy (FA) differences between AN patients and HC, and performed meta-regression analysis to explore the effects of clinical characteristics on WM abnormalities in AN. The pooled results of all AN patients showed robustly lower FA in the corpus callosum (CC) and the cingulum compared to HC. These two regions preserved significance in the sensitivity analysis as well as in all subgroup analyses. Fiber tracking showed that the WM tracts primarily involved were the body of the CC and the cingulum bundle. Meta-regression analysis revealed that the body mass index and mean age were not linearly correlated with the lower FA. The most consistent WM microstructural differences in AN were in the interhemispheric connections and limbic association fibers. These common "targets" advance our understanding of the complex neural mechanisms underlying the puzzling symptoms of AN, and may help in developing early treatment approaches.
PubMed: 32194371
DOI: 10.3389/fnins.2020.00159 -
Frontiers in Oncology 2019Controversy still exists on the diagnosability of diffusion tensor imaging (DTI) for breast lesions characterization across published studies. The clinical guideline of...
Controversy still exists on the diagnosability of diffusion tensor imaging (DTI) for breast lesions characterization across published studies. The clinical guideline of DTI used in the breast has not been established. This meta-analysis aims to pool relevant evidences and evaluate the diagnostic performance of DTI in the differential diagnosis of malignant and benign breast lesions. The studies that assessed the diagnostic performance of DTI parameters in the breast were searched in Embase, PubMed, and Cochrane Library between January 2010 and September 2019. Standardized mean differences and 95% confidence intervals of fractional anisotropy (FA), mean diffusivity (MD), and three diffusion eigenvalues (λ1, λ2, and λ3) were calculated using Review Manager 5.2. The pooled sensitivity, specificity, and area under the curve (AUC) were calculated with a bivariate model. Publication bias and heterogeneity between studies were also assessed using Stata 12.0. Sixteen eligible studies incorporating 1,636 patients were included. The standardized mean differences indicated that breast cancers had a significantly higher FA but lower MD, λ1, λ2, and λ3 than those of benign lesions (all < 0.05). Subgroup analysis indicated that invasive breast carcinoma (IBC) had a significantly lower MD value than that of ductal carcinoma (DCIS) ( = 0.02). λ1 showed the best diagnostic accuracy with pooled sensitivity, specificity, and AUC of 93%, 92%, and 0.97, followed by MD (AUC = 0.92, sensitivity = 87%, specificity = 83%) and FA (AUC = 0.76, sensitivity = 70%, specificity = 70%) in the differential diagnosis of breast lesions. DTI with multiple quantitative parameters was adequate to differentiate breast cancers from benign lesions based on their biological characteristics. MD can further distinguish IBC from DCIS. The parameters, especially λ1 and MD, should attract our attention in clinical practice.
PubMed: 31803615
DOI: 10.3389/fonc.2019.01229 -
Drug and Alcohol Dependence Aug 2019Converging lines of evidence from diffusion tensor imaging (DTI) studies reveal significant alterations in white matter (WM) microstructure in the prefrontal cortex of... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Converging lines of evidence from diffusion tensor imaging (DTI) studies reveal significant alterations in white matter (WM) microstructure in the prefrontal cortex of chronic stimulant users compared to controls, suggesting compromised axonal microstructure and/or myelin.
METHODS
A meta-analysis of DTI-based WM integrity was conducted for white matter regions across the corpus callosum and association fibers. Articles were sourced and selected using PRISMA guidelines for systematic review and meta-analysis. Inclusion and exclusion criteria were determined by the authors in order to best capture WM integrity among individuals with primary stimulant use in comparison to healthy control subjects.
RESULTS
Eleven studies that focused on region-of-interest (ROI)-based analysis of WM integrity were extracted from an initial pool of 113 independent studies. Analysis across ROIs indicated significantly lower fractional anisotropy (FA) values in stimulant use groups compared to controls with a small to moderate overall effect (Hedges' g = -0.37, 95% CI [-0.54, -0.20]). Eigenvalues were also analyzed, revealing a significant effect for radial diffusivity (RD; Hedges' g = 0.24, 95% CI [0.01, 0.47]) but not axial diffusivity (AD; Hedges' g = 0.05, 95% CI [-0.20, 0.29]) or mean diffusivity (MD; Hedges' g = 0.20, 95% CI [-0.01, 0.41]). Subgroup analyses based on specific ROIs, primary substance use, poly-substance use, and imaging technology were also explored.
CONCLUSION
Results of the present study suggest a consistent effect of compromised WM integrity for individuals with stimulant use disorders. Furthermore, no significant differences were found between cocaine and methamphetamine-based groups.
Topics: Adult; Amphetamine-Related Disorders; Anisotropy; Central Nervous System Stimulants; Corpus Callosum; Diffusion Tensor Imaging; Female; Humans; Male; Prefrontal Cortex; White Matter
PubMed: 31176066
DOI: 10.1016/j.drugalcdep.2019.03.023