1
|
Chougar L, Faucher A, Faouzi J, Lejeune FX, Gama Lobo G, Jovanovic C, Cormier F, Dupont G, Vidailhet M, Corvol JC, Colliot O, Lehéricy S, Grabli D, Degos B. Contribution of MRI for the Early Diagnosis of Parkinsonism in Patients with Diagnostic Uncertainty. Mov Disord 2024; 39:825-835. [PMID: 38486423 DOI: 10.1002/mds.29760] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 01/16/2024] [Accepted: 02/16/2024] [Indexed: 05/18/2024] Open
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.
Collapse
Affiliation(s)
- Lydia Chougar
- Department of Neuroradiology, Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, DMU DIAMENT, Paris, France
- ICM, Centre de NeuroImagerie de Recherche-CENIR, Paris, France
- ICM, Team "Movement Investigations and Therapeutics" (MOV'IT), Paris, France
- Department of Neuroradiology, Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, CNRS, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, DMU DIAMENT, Paris, France
| | - Alice Faucher
- Assistance Publique Hôpitaux de Paris, Service de Neurologie, Hôpital Avicenne, Hôpitaux Universitaires de Paris Seine-Saint-Denis, Sorbonne Paris Nord, NS-PARK/FCRIN Network, Bobigny, France
| | - Johann Faouzi
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, Paris, France
- CREST, ENSAI, Campus de Ker-Lann, Bruz, France
| | - François-Xavier Lejeune
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, CNRS, Inserm, Paris, France
- ICM, Data Analysis Core (DAC), Paris, France
| | - Gonçalo Gama Lobo
- Neuroradiology Department, Centro Hospitalar Universitário de Lisboa Central, Lisboa, Portugal
| | - Carna Jovanovic
- Neurology Clinic, University Clinical Center of Serbia, Belgrade, Serbia
| | - Florence Cormier
- Département de Neurologie, Hôpital Pitié-Salpêtrière, Assistance Publique Hôpitaux de Paris, Clinique des Mouvements Anormaux, Clinical Investigation Center for Neurosciences, Paris, France
| | - Gwendoline Dupont
- Université de Bourgogne, Dijon, France
- Département de Neurologie, Centre Hospitalier Universitaire François Mitterrand, Dijon, France
| | - Marie Vidailhet
- ICM, Team "Movement Investigations and Therapeutics" (MOV'IT), Paris, France
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, CNRS, Inserm, Paris, France
| | - Jean-Christophe Corvol
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, CNRS, Inserm, Paris, France
- Département de Neurologie, Hôpital Pitié-Salpêtrière, Assistance Publique Hôpitaux de Paris, Clinique des Mouvements Anormaux, Clinical Investigation Center for Neurosciences, Paris, France
| | - Olivier Colliot
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, Paris, France
| | - Stéphane Lehéricy
- ICM, Centre de NeuroImagerie de Recherche-CENIR, Paris, France
- ICM, Team "Movement Investigations and Therapeutics" (MOV'IT), Paris, France
- Department of Neuroradiology, Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, CNRS, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, DMU DIAMENT, Paris, France
| | - David Grabli
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, CNRS, Inserm, Paris, France
- Département de Neurologie, Hôpital Pitié-Salpêtrière, Assistance Publique Hôpitaux de Paris, Clinique des Mouvements Anormaux, Clinical Investigation Center for Neurosciences, Paris, France
| | - Bertrand Degos
- Assistance Publique Hôpitaux de Paris, Service de Neurologie, Hôpital Avicenne, Hôpitaux Universitaires de Paris Seine-Saint-Denis, Sorbonne Paris Nord, NS-PARK/FCRIN Network, Bobigny, France
- Dynamics and Pathophysiology of Neuronal Networks Team, Center for Interdisciplinary Research in Biology, Collège de France, CNRS UMR7241/INSERM U1050, Université PSL, Paris, France
| |
Collapse
|
2
|
Chougar L, Lejeune FX, Faouzi J, Morino B, Faucher A, Hoyek N, Grabli D, Cormier F, Vidailhet M, Corvol JC, Colliot O, Degos B, Lehéricy S. Comparison of mean diffusivity, R2* relaxation rate and morphometric biomarkers for the clinical differentiation of parkinsonism. Parkinsonism Relat Disord 2023; 108:105287. [PMID: 36706616 DOI: 10.1016/j.parkreldis.2023.105287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 12/15/2022] [Accepted: 01/14/2023] [Indexed: 01/19/2023]
Abstract
INTRODUCTION Quantitative biomarkers for clinical differentiation of parkinsonian syndromes are still lacking. Our aim was to evaluate the value of combining clinically feasible manual measurements of R2* relaxation rates and mean diffusivity (MD) in subcortical regions and brainstem morphometric measurements to improve the discrimination of parkinsonian syndromes. METHODS Twenty-two healthy controls (HC), 25 patients with Parkinson's disease (PD), 19 with progressive supranuclear palsy (PSP) and 27 with multiple system atrophy (MSA, 21 with the parkinsonian variant -MSAp, 6 with the cerebellar variant -MSAc) were recruited. R2*, MD measurements and morphometric biomarkers including the midbrain to pons area ratio and the Magnetic Resonance Parkinsonism Index (MRPI) were compared between groups and their diagnostic performances were assessed. RESULTS Morphometric biomarkers discriminated better patients with PSP (ratio: AUC 0.89, MRPI: AUC 0.89) and MSAc (ratio: AUC 0.82, MRPI: AUC 0.75) from other groups. R2* and MD measurements in the posterior putamen performed better in separating patients with MSAp from PD (R2*: AUC 0.89; MD: AUC 0.89). For the three-class classification "MSA vs PD vs PSP", the combination of MD and R2* measurements in the posterior putamen with morphometric biomarkers (AUC: 0.841) outperformed each marker separately. At the individual-level, there were seven discordances between imaging-based prediction and clinical diagnosis involving MSA. Using the new Movement Disorder Society criteria for the diagnosis of MSA, three of these seven patients were clinically reclassified as predicted by quantitative imaging. CONCLUSION Combining R2* and MD measurements in the posterior putamen with morphometric biomarkers improves the discrimination of parkinsonism.
Collapse
Affiliation(s)
- Lydia Chougar
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, DMU DIAMENT, Department of Neuroradiology, F-75013, Paris, France; ICM, Centre de NeuroImagerie de Recherche-CENIR, Paris, France; ICM, Team "Movement Investigations and Therapeutics" (MOV'IT), Paris, France; Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, DMU DIAMENT, Department of Neuroradiology, F-75013, Paris, France.
| | - François-Xavier Lejeune
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, F-75013, Paris, France; ICM, Data and Analysis Core, Paris, France
| | - Johann Faouzi
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, F-75013, Paris, France; Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, F-75013, Paris, France
| | - Benjamin Morino
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, DMU DIAMENT, Department of Neuroradiology, F-75013, Paris, France
| | - Alice Faucher
- Dynamics and Pathophysiology of Neuronal Networks Team, Center for Interdisciplinary Research in Biology, Collège de France, CNRS UMR7241/INSERM U1050, Université PSL, Paris, France; Service de Neurologie, Hôpital Avicenne, Hôpitaux Universitaires de Paris Seine-Saint-Denis, APHP, Bobigny, France
| | - Nadine Hoyek
- Department of Radiology, Hotel Dieu de France University Hospital, Faculty of Medicine, Saint Joseph University, Beirut, Lebanon
| | - David Grabli
- Clinique des mouvements anormaux, Département de Neurologie, Assistance Publique Hôpitaux de Paris, Hôpital Pitié-Salpêtrière, Paris, France; ICM, Centre d'Investigation Clinique Neurosciences, Paris, France
| | - Florence Cormier
- Clinique des mouvements anormaux, Département de Neurologie, Assistance Publique Hôpitaux de Paris, Hôpital Pitié-Salpêtrière, Paris, France; ICM, Centre d'Investigation Clinique Neurosciences, Paris, France
| | - Marie Vidailhet
- ICM, Team "Movement Investigations and Therapeutics" (MOV'IT), Paris, France; Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, F-75013, Paris, France; Clinique des mouvements anormaux, Département de Neurologie, Assistance Publique Hôpitaux de Paris, Hôpital Pitié-Salpêtrière, Paris, France; ICM, Centre d'Investigation Clinique Neurosciences, Paris, France
| | - Jean-Christophe Corvol
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, F-75013, Paris, France; Clinique des mouvements anormaux, Département de Neurologie, Assistance Publique Hôpitaux de Paris, Hôpital Pitié-Salpêtrière, Paris, France; ICM, Centre d'Investigation Clinique Neurosciences, Paris, France
| | - Olivier Colliot
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, F-75013, Paris, France; Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, F-75013, Paris, France
| | - Bertrand Degos
- Dynamics and Pathophysiology of Neuronal Networks Team, Center for Interdisciplinary Research in Biology, Collège de France, CNRS UMR7241/INSERM U1050, Université PSL, Paris, France; Service de Neurologie, Hôpital Avicenne, Hôpitaux Universitaires de Paris Seine-Saint-Denis, APHP, Bobigny, France
| | - Stéphane Lehéricy
- ICM, Centre de NeuroImagerie de Recherche-CENIR, Paris, France; ICM, Team "Movement Investigations and Therapeutics" (MOV'IT), Paris, France; Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, DMU DIAMENT, Department of Neuroradiology, F-75013, Paris, France
| |
Collapse
|