Automated Analysis of Diffusion‐Weighted Magnetic Resonance Imaging for the Differential Diagnosis of Multiple System Atrophy from Parkinson's Disease. Issue 1 (16th September 2020)

• Record Type: Journal Article
• Authors: Krismer, Florian; Beliveau, Vincent; Seppi, Klaus; Mueller, Christoph; Goebel, Georg; Gizewski, Elke R.; Wenning, Gregor K.; Poewe, Werner; Scherfler, Christoph
• Is Part Of: Movement disorders. Volume 36:Issue 1(2021)
• Page Start: 241
• Page End: 245
• Publication Date: 2020-09-16
• Subjects: multiple system atrophy -- MRI -- diffusion‐weighted imaging -- Freesurfer; Movement disorders -- Periodicals; 610
• DOI: 10.1002/mds.28281
• Languages: English
• ISSNs: 0885-3185

Abstract

ABSTRACT: Background: Manual region‐of‐interest analysis of putaminal and middle cerebellar peduncle diffusivity distinguishes patients with multiple system atrophy (MSA) and Parkinson's disease (PD) with high diagnostic accuracy. However, a recent meta‐analysis found substantial between‐study heterogeneity of diagnostic accuracy due to the lack of harmonized imaging protocols and standardized analyses pipelines. Objective: Evaluation of diagnostic accuracy of observer‐independent analysis of microstructural integrity as measured by diffusion‐tensor imaging in patients with MSA and PD. Methods: A total of 29 patients with MSA and 19 patients with PD (matched for age, gender, and disease duration) with 3 years of follow‐up were investigated with diffusion‐tensor imaging and T1‐weighted magnetic resonance imaging. Automated localization of relevant brain regions was obtained, and mean diffusivity and fractional anisotropy values were averaged within the regions of interest. The classification was performed using a C5.0 hierachical decision tree algorithm. Results: Mean diffusivity of the middle cerebellar peduncle and cerebellar gray and white matter compartment as well as the putamen were significantly increased in patients with MSA and showed superior effect sizes compared to the volumetric analysis of these regions. A classifier model identified mean diffusivity of the middle cerebellar peduncle and putamen as the most predictive parameters. Cross‐validation of the classification model yields a Cohen's κ and overall diagnostic accuracy of 0.823 and 0.914, respectively. Conclusion: Analysis of microstructural integrity within the middle cerebellar peduncle and putamen yielded a superior effect size compared to the volumetric measures, resulting in excellent diagnostic accuracy to discriminate patients with MSA from PD in the early to moderate disease stages. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society