Salvatore Nigro1, Angelo Antonini2, David E Vaillancourt3,4, Klaus Seppi5,6, Roberto Ceravolo7, Antonio P Strafella8, Antonio Augimeri9, Andrea Quattrone10, Maurizio Morelli10, Luca Weis11, Eleonora Fiorenzato11, Roberta Biundo11, Roxana G Burciu12, Florian Krismer5, Nikolaus R McFarland4, Christoph Mueller5, Elke R Gizewski6,13, Mirco Cosottini14, Eleonora Del Prete7, Sonia Mazzucchi7, Aldo Quattrone1,15. 1. Neuroscience Centre, Magna Graecia University, Catanzaro, Italy. 2. Department of Neuroscience, University of Padua, Padua, Italy. 3. Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, Florida, USA. 4. Department of Neurology and Biomedical Engineering, University of Florida, Gainesville, Florida, USA. 5. Department of Neurology, Medical University Innsbruck, Innsbruck, Austria. 6. Neuroimaging Core Facility, Medical University Innsbruck, Innsbruck, Austria. 7. Department of Clinical and Experimental Medicine, Unit of Neurology, University of Pisa, Pisa, Italy. 8. Krembil Research Institute, UHN & Research Imaging Centre, Campbell Family Mental Health Research Institute, CAMH, University of Toronto, Toronto, Ontario, Canada. 9. Biotecnomed S.C. aR.L., Catanzaro, Italy. 10. Department of Medical and Surgical Sciences, Institute of Neurology, Magna Graecia University, Catanzaro, Italy. 11. IRCCS San Camillo Hospital, Venice, Italy. 12. Department of Kinesiology and Applied Physiology, University of Delaware, Newark, Delaware, USA. 13. Department of Neuroradiology, Medical University Innsbruck, Innsbruck, Austria. 14. Department of Translational Research and New Technologies, University of Pisa, Pisa, Italy. 15. Neuroimaging Research Unit, Institute of Molecular Bioimaging and Physiology, National Research Council, Catanzaro, Italy.
Abstract
BACKGROUND: The Magnetic Resonance Parkinsonism Index is listed as one of the most reliable imaging morphometric markers for diagnosis of progressive supranuclear palsy (PSP). However, the use of this index in diagnostic workup has been limited until now by the low generalizability of published results because of small monocentric patient cohorts, the lack of data validation in independent patient series, and manual measurements used for index calculation. The objectives of this study were to investigate the generalizability of Magnetic Resonance Parkinsonism Index performance validating previously established cutoff values in a large international cohort of PSP patients subclassified into PSP-Richardson's syndrome and PSP-parkinsonism and to standardize the use of the automated Magnetic Resonance Parkinsonism Index by providing a web-based platform to obtain homogenous measures around the world. METHODS: In a retrospective international multicenter study, a total of 173 PSP patients and 483 non-PSP participants were enrolled. A web-based platform (https://mrpi.unicz.it) was used to calculate automated Magnetic Resonance Parkinsonism Index values. RESULTS: Magnetic Resonance Parkinsonism Index values showed optimal performance in differentiating PSP-Richardson's syndrome and PSP-parkinsonism patients from non-PSP participants (93.6% and 86.5% of accuracy, respectively). The Magnetic Resonance Parkinsonism Index was also able to differentiate PSP-Richardson's syndrome and PSP-parkinsonism patients in an early stage of the disease from non-PSP participants (90.1% and 85.9%, respectively). The web-based platform provided the automated Magnetic Resonance Parkinsonism Index calculation in 94% of cases. CONCLUSIONS: Our study provides the first evidence on the generalizability of automated Magnetic Resonance Parkinsonism Index measures in a large international cohort of PSP-Richardson's syndrome and PSP-parkinsonism patients. The web-based platform enables widespread applicability of the automated Magnetic Resonance Parkinsonism Index to different clinical and research settings.
BACKGROUND: The Magnetic Resonance Parkinsonism Index is listed as one of the most reliable imaging morphometric markers for diagnosis of progressive supranuclear palsy (PSP). However, the use of this index in diagnostic workup has been limited until now by the low generalizability of published results because of small monocentric patient cohorts, the lack of data validation in independent patient series, and manual measurements used for index calculation. The objectives of this study were to investigate the generalizability of Magnetic Resonance Parkinsonism Index performance validating previously established cutoff values in a large international cohort of PSPpatients subclassified into PSP-Richardson's syndrome and PSP-parkinsonism and to standardize the use of the automated Magnetic Resonance Parkinsonism Index by providing a web-based platform to obtain homogenous measures around the world. METHODS: In a retrospective international multicenter study, a total of 173 PSPpatients and 483 non-PSPparticipants were enrolled. A web-based platform (https://mrpi.unicz.it) was used to calculate automated Magnetic Resonance Parkinsonism Index values. RESULTS: Magnetic Resonance Parkinsonism Index values showed optimal performance in differentiating PSP-Richardson's syndrome and PSP-parkinsonismpatients from non-PSPparticipants (93.6% and 86.5% of accuracy, respectively). The Magnetic Resonance Parkinsonism Index was also able to differentiate PSP-Richardson's syndrome and PSP-parkinsonismpatients in an early stage of the disease from non-PSPparticipants (90.1% and 85.9%, respectively). The web-based platform provided the automated Magnetic Resonance Parkinsonism Index calculation in 94% of cases. CONCLUSIONS: Our study provides the first evidence on the generalizability of automated Magnetic Resonance Parkinsonism Index measures in a large international cohort of PSP-Richardson's syndrome and PSP-parkinsonismpatients. The web-based platform enables widespread applicability of the automated Magnetic Resonance Parkinsonism Index to different clinical and research settings.
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