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

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.