Striatal shape alteration as a staging biomarker for Parkinson's Disease

Neuroimage Clin. 2020;27:102272. doi: 10.1016/j.nicl.2020.102272. Epub 2020 May 19.

Abstract

Parkinson's Disease provokes alterations of subcortical deep gray matter, leading to subtle changes in the shape of several subcortical structures even before the manifestation of motor and non-motor clinical symptoms. We used an automated registration and segmentation pipeline to measure this structural alteration in one early and one advanced Parkinson's Disease (PD) cohorts, one prodromal stage cohort and one healthy control cohort. These structural alterations are then passed to a machine learning pipeline to classify these populations. Our workflow is able to distinguish different stages of PD based solely on shape analysis of the bilateral caudate nucleus and putamen, with balanced accuracies in the range of 59% to 85%. Furthermore, we compared the significance of each of these subcortical structure, compared the performances of different classifiers on this task, thus quantifying the informativeness of striatal shape alteration as a staging bio-marker for PD.

Keywords: Machine learning; Medical imaging; Morphometric biomarkers; Parkinson’s disease; Staging biomarker.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Biomarkers / analysis*
  • Caudate Nucleus / diagnostic imaging*
  • Corpus Striatum / diagnostic imaging
  • Female
  • Gray Matter / diagnostic imaging
  • Humans
  • Male
  • Middle Aged
  • Parkinson Disease / diagnosis
  • Parkinson Disease / diagnostic imaging*
  • Putamen / diagnostic imaging*

Substances

  • Biomarkers