Novel decision algorithm to discriminate parkinsonism with combined blood and imaging biomarkers.
| Autor: | Mangesius S; Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria; Neuroimaging Core Facility, Medical University of Innsbruck, Innsbruck, Austria; Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria. Electronic address: stephanie.mangesius@i-med.ac.at., Mariotto S; Neurology Unit, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy. Electronic address: sara.mariotto@gmail.com., Ferrari S; Neurology Unit, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy. Electronic address: sergio.ferrari@aovr.veneto.it., Pereverzyev S Jr; Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria; Neuroimaging Core Facility, Medical University of Innsbruck, Innsbruck, Austria. Electronic address: sergiy.pereverzyev@i-med.ac.at., Lerchner H; Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria. Electronic address: hannes.lerchner@i-med.ac.at., Haider L; NMR Research Unit, Queens Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College London, London, UK; Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Vienna, Austria. Electronic address: lukas.haider@meduniwien.ac.at., Gizewski ER; Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria; Neuroimaging Core Facility, Medical University of Innsbruck, Innsbruck, Austria. Electronic address: elke.gizewski@i-med.ac.at., Wenning G; Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria. Electronic address: gregor.wenning@i-med.ac.at., Seppi K; Neuroimaging Core Facility, Medical University of Innsbruck, Innsbruck, Austria; Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria. Electronic address: klaus.seppi@i-med.ac.at., Reindl M; Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria. Electronic address: markus.reindl@i-med.ac.at., Poewe W; Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria. Electronic address: werner.poewe@i-med.ac.at. |
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| Jazyk: | angličtina |
| Zdroj: | Parkinsonism & related disorders [Parkinsonism Relat Disord] 2020 Aug; Vol. 77, pp. 57-63. Date of Electronic Publication: 2020 Jun 22. |
| DOI: | 10.1016/j.parkreldis.2020.05.033 |
| Abstrakt: | Introduction: To determine an exploratory multimodal approach including serum NFL and MR planimetric measures to discriminate Parkinson's disease (PD), multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). Methods: MR planimetric measurements and NFL serum levels, with a mean time interval of 60 months relative to symptom onset, were assessed in a retrospective cohort of 11 progressive supranuclear palsy (PSP), 22 Parkinson's disease (PD), 16 multiple system atrophy (MSA) patients and 42 healthy controls (HC). A decision tree model to discriminate PD, PSP, and MSA was constructed using receiver operating characteristic curve analysis and Classification and Regression Trees algorithm. Results: Our multimodal decision tree provided accurate differentiation of PD versus MSA and PSP patients using a serum NFL cut-off of 14.66 ng/L. The pontine-to-midbrain-diameter-ratio (P Conclusion: We provide a clinically feasible decision algorithm which combines serum NFL levels and a planimetric MRI marker to differentiate PD, MSA and PSP with high diagnostic accuracy. Classification of Evidence: This study provides Class III evidence that the combination of serum NFL levels und MR planimetric measurements discriminates between PD, PSP and MSA. (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.) |
| Databáze: | MEDLINE |
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