Differentiation of multiple system atrophy from Parkinson's disease by structural connectivity derived from probabilistic tractography.

ABSTRACT: Recent studies combining diffusion tensor-derived metrics and machine learning have shown promising results in the discrimination of multiple system atrophy (MSA) and Parkinson's disease (PD) patients. This approach has not been tested using more complex methodologies such as probabilistic tractography. The aim of this work is assessing whether the strength of structural connectivity between subcortical structures, measured as the number of streamlines (NOS) derived from tractography, can be used to classify MSA and PD patients at the single-patient level. The classification performance of subcortical FA and MD was also evaluated to compare the discriminant ability between diffusion tensor-derived metrics and NOS. Using diffusion-weighted images acquired in a 3 T MRI scanner and probabilis

SUBMITTER: Abos A 

PROVIDER: S-EPMC6848175 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature