Development and validation of the automated imaging differentiation in parkinsonism (AID-P): a multicentre machine learning study

作者：Derek B. Archer, Justin T Bricker, Winston T. Chu, Roxana G. Burciu, Johanna McCracken, Song Lai, Stephen A. Coombes, Ruogu Fang, Angelos Barmpoutis, Daniel M. Corcos, Ajay S. Kurani, Trina Mitchell, Mieniecia L. Black, Ellen Herschel, Tanya Simuni, Todd B. Parrish, Cynthia L. Comella, Tao Xie, Klaus Seppi, Nicolaas I. Bohnen, Martijn L.T.M. Müller, Roger L. Albin, Florian Krismer, Guangwei Du, Mechelle M. Lewis, Xuemei Huang, Hong Li, Ofer Pasternak, Nikolaus R. McFarland, Michael S. Okun, David E. Vaillancourt · 发表于：The Lancet Digital Health · 年份：2019 · DOI：10.1016/s2589-7500(19)30105-0 · 被引用次数：119 · 研究领域：Parkinson's Disease Mechanisms and Treatments、Neurological disorders and treatments、Voice and Speech Disorders

BACKGROUND: Development of valid, non-invasive biomarkers for parkinsonian syndromes is crucially needed. We aimed to assess whether non-invasive diffusion-weighted MRI can distinguish between parkinsonian syndromes using an automated imaging approach. METHODS: We did an international study at 17 MRI centres in Austria, Germany, and the USA. We used diffusion-weighted MRI from 1002 patients and the Movement Disorders Society Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) to develop and validate disease-specific machine learning comparisons using 60 template regions and tracts of interest in Montreal Neurological Institute space between Parkinson's disease and atypical parkinsonism (multiple system atrophy and progressive supranuclear palsy) and between multiple system atrophy and progressive supranuclear palsy. For each comparison, models were developed on a training and validation cohort and evaluated in an independent test cohort by quantifying the area under the curve (AUC) of receiving operating characteristic curves. The primary outcomes were free water and free-water-corrected fractional anisotropy across 60 different template regions. FINDINGS: In the test cohort for disease-specific comparisons, the diffusion-weighted MRI plus MDS-UPDRS III model (Parkinson's disease vs atypical parkinsonism had an AUC 0·962; multiple system atrophy vs progressive supranuclear palsy AUC 0·897) and diffusion-weighted MRI only model had high AUCs (Parkinson's disease ...