DOI: 10.1101/19007575Sep 25, 2019Paper

Towards accurate and unbiased imaging based differentiation of Parkinson's Disease, Progressive Supranuclear Palsy and Corticobasal Syndrome

MedRxiv : the Preprint Server for Health Sciences
Marta M CorreiaJ. B. Rowe

Abstract

The early and accurate differential diagnosis of parkinsonian disorders is still a significant challenge for clinicians. In recent years, a number of studies have used MRI data combined with machine learning and statistical classifiers to successfully differentiate between different forms of Parkinsonism. However, several questions and methodological issues remain, to minimise bias and artefact-driven classification. In this study we compared different approaches for feature selection, as well as different MRI modalities, with well matched patient groups and tightly controlling for data quality issues related to patient motion. Our sample was drawn from a cohort of 69 healthy controls, and patients with idiopathic Parkinson's disease (n=35, PD), Progressive Supranuclear Palsy Richardson's syndrome (n=52, PSP) and corticobasal syndrome (n=36, CBS). Participants underwent standardised T1-weighted MPRAGE and diffusion-weighted MRI. We compared two different methods for feature selection and dimensionality reduction: whole-brain principal components analysis, and an anatomical region-of-interest based approach. In both cases, support vector machines were used to construct a statistical model for pairwise classification of healthy c...Continue Reading

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