Artikel ; Online: Contribution of MRI for the Early Diagnosis of Parkinsonism in Patients with Diagnostic Uncertainty.
Movement disorders : official journal of the Movement Disorder Society
2024 Band 39, Heft 5, Seite(n) 825–835
Abstract: Background: International clinical criteria are the reference for the diagnosis of degenerative parkinsonism in clinical research, but they may lack sensitivity and specificity in the early stages.: Objectives: To determine whether magnetic resonance ...
| Abstract | Background: International clinical criteria are the reference for the diagnosis of degenerative parkinsonism in clinical research, but they may lack sensitivity and specificity in the early stages. Objectives: To determine whether magnetic resonance imaging (MRI) analysis, through visual reading or machine-learning approaches, improves diagnostic accuracy compared with clinical diagnosis at an early stage in patients referred for suspected degenerative parkinsonism. Materials: Patients with initial diagnostic uncertainty between Parkinson's disease (PD), progressive supranuclear palsy (PSP), and multisystem atrophy (MSA), with brain MRI performed at the initial visit (V1) and available 2-year follow-up (V2), were included. We evaluated the accuracy of the diagnosis established based on: (1) the international clinical diagnostic criteria for PD, PSP, and MSA at V1 ("Clin1"); (2) MRI visual reading blinded to the clinical diagnosis ("MRI"); (3) both MRI visual reading and clinical criteria at V1 ("MRI and Clin1"), and (4) a machine-learning algorithm ("Algorithm"). The gold standard diagnosis was established by expert consensus after a 2-year follow-up. Results: We recruited 113 patients (53 with PD, 31 with PSP, and 29 with MSA). Considering the whole population, compared with clinical criteria at the initial visit ("Clin1": balanced accuracy, 66.2%), MRI visual reading showed a diagnostic gain of 14.3% ("MRI": 80.5%; P = 0.01), increasing to 19.2% when combined with the clinical diagnosis at the initial visit ("MRI and Clin1": 85.4%; P < 0.0001). The algorithm achieved a diagnostic gain of 9.9% ("Algorithm": 76.1%; P = 0.08). Conclusion: Our study shows the use of MRI analysis, whether by visual reading or machine-learning methods, for early differentiation of parkinsonism. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. |
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| Mesh-Begriff(e) | Humans ; Female ; Magnetic Resonance Imaging/methods ; Magnetic Resonance Imaging/standards ; Male ; Aged ; Middle Aged ; Supranuclear Palsy, Progressive/diagnostic imaging ; Supranuclear Palsy, Progressive/diagnosis ; Parkinsonian Disorders/diagnostic imaging ; Parkinsonian Disorders/diagnosis ; Parkinson Disease/diagnostic imaging ; Parkinson Disease/diagnosis ; Multiple System Atrophy/diagnostic imaging ; Multiple System Atrophy/diagnosis ; Early Diagnosis ; Machine Learning ; Uncertainty ; Diagnosis, Differential ; Sensitivity and Specificity |
| Sprache | Englisch |
| Erscheinungsdatum | 2024-03-14 |
| Erscheinungsland | United States |
| Dokumenttyp | Journal Article |
| ZDB-ID | 607633-6 |
| ISSN | 1531-8257 ; 0885-3185 |
| ISSN (online) | 1531-8257 |
| ISSN | 0885-3185 |
| DOI | 10.1002/mds.29760 |
| Datenquelle | MEDical Literature Analysis and Retrieval System OnLINE |
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