A study of neurite orientation dispersion and density imaging in wilson's disease.

Abstract

Previous studies have indicated that neurite orientation dispersion and density imaging (NODDI) could be used as a biomarker for detecting microstructural changes of brain. To quantitatively evaluate the changes in basal ganglia (BG) and thalamus in Wilson's disease (WD) by NODDI and assess the correlation between parameters and disease severity. Prospective case-control study. In total, 24 WD patients and 25 age- and sex-matched normal controls were involved in this study. EPI diffusion-weighted MR images (b-values = 0, 1000, and 2000 with 30 diffusion gradient directions) were acquired on a 3T scanner. Diffusion data were analyzed using voxel-based analysis. NODDI indices including intracellular volume fraction (Vic), orientation dispersion index (ODI), and isotropic volume fraction (Viso) were estimated from the BG and thalamus. The disease severity was assessed by two experienced neurologists based on the Global Assessment Scale (GAS). The relative importance of NODDI indices in diagnosing WD and predictive accuracy were also analyzed. The Shapiro-Wilk test, Student's t-test, χ2 test, Mann-Whitney-Wilcoxon test, Spearman rank correlation coefficient analysis and random-forest analysis were used for statistical analyses. The Vic and ODI in the BG and thalamus were significantly lower in WD patients than normal controls, while the Viso in the BG and thalamus were significantly higher (P < 0.01). The Vic in the putamen and ODI in the globus pallidus were negatively correlated with clinical severity (rvic = -0.727, P < 0.001; rodi = -0.705, P < 0.001). The Vic in the putamen was the most valuable predictor for diagnosing WD and the prediction accuracy of NODDI was 95.92%. NODDI can effectively evaluate the changes of microstructure and metabolism during copper deposition in WD, and thus, it is likely to be useful in detecting the changes in the brain of this disease and assessing its progression. 2 Technical Efficacy Stage 2 J. MAGN. RESON. IMAGING 2018;48:423-430.