Development and Validation of Automated Magnetic Resonance Parkinsonism Index 2.0 to Distinguish Progressive Supranuclear Palsy-Parkinsonism From Parkinson's Disease.
Andrea QuattroneMaria G BiancoAngelo AntoniniDavid E VaillancourtKlaus SeppiRoberto CeravoloAntonio P StrafellaGioacchino TedeschiAlessandro TessitoreRoberto CiliaMaurizio MorelliSalvatore NigroBasilio VescioPier Paolo ArcuriRosa De MiccoMario CirilloLuca WeisEleonora FiorenzatoRoberta BiundoRoxana G BurciuFlorian KrismerNikolaus R McFarlandChristoph MuellerElke R GizewskiMirco CosottiniEleonora Del PreteSonia MazzucchiAldo QuattronePublished in: Movement disorders : official journal of the Movement Disorder Society (2022)
Our study provides an automated, validated, and generalizable magnetic resonance biomarker to distinguish PSP-P from PD. The use of the automated MRPI 2.0 algorithm rather than manual measurements could be important to standardize measures in patients with PSP-P across centers, with a positive impact on multicenter studies and clinical trials involving patients from different geographic regions. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Keyphrases
- magnetic resonance
- machine learning
- deep learning
- clinical trial
- end stage renal disease
- ejection fraction
- high throughput
- parkinson disease
- chronic kidney disease
- newly diagnosed
- multiple sclerosis
- drug induced
- prognostic factors
- peritoneal dialysis
- randomized controlled trial
- systematic review
- magnetic resonance imaging
- computed tomography
- patient reported outcomes
- case control
- double blind
- open label
- study protocol