Multiple System Atrophy: Phenotypic spectrum approach coupled with brain 18-FDG PET. (October 2019)

• Record Type: Journal Article
• Authors: Grimaldi, Stephan; Boucekine, Mohamed; Witjas, Tatiana; Fluchère, Frédérique; Renaud, Mathilde; Azulay, Jean-Philippe; Guedj, Eric; Eusebio, Alexandre
• Is Part Of: Parkinsonism & related disorders. Volume 67(2019)
• Page Start: 3
• Page End: 9
• Publication Date: 2019-10
• Subjects: Multiple system atrophy -- Clinical phenotypes -- Latent class analysis -- 18-FDG PET -- Cognitive impairment; Parkinson's disease -- Periodicals; Movement disorders -- Periodicals; Movement Disorders -- Periodicals; Nerve Degeneration -- Periodicals; Nervous System Diseases -- Periodicals; Parkinson Disease -- Periodicals; Tremor -- Periodicals; Parkinson, Maladie de -- Périodiques; Parkinson's disease; 616.833
• DOI: 10.1016/j.parkreldis.2019.09.005
• Languages: English
• ISSNs: 1353-8020

Abstract

Abstract: Objective: The 2008 diagnostic criteria classify Multiple System Atrophy (MSA) patients in a predominantly parkinsonian (MSA-P) or cerebellar (MSA-C) type. Phenotypic descriptions have since highlighted a clinical heterogeneity among patients (e.g., mixed-type, cognitive impairment, atypical longer survival). This study attempts to identify different phenotypes of patients with MSA and to describe corresponding brain 18-FDG Positron Emission Tomography (PET) patterns. Methods: Patients with a "probable" MSA diagnosis for whom a brain 18-FDG PET was performed were included. A retrospective analysis (from 2006 to 2017) was conducted using standardized data collection. We used Latent Class Analysis (LCA), an innovative statistical approach, to identify profiles of patients based on common clinical characteristics. Brain metabolism of different groups was studied at rest. Results: Eighty-five patients were included. Three different profiles were revealed (entropy = 0.835): 1. extrapyramidal, axial, laryngeal-pharyngeal involvement (LPI) and cerebellar symptoms (n = 46, 54.1%); 2. cerebellar and LPI symptoms (n = 30, 35.3%); 3. cerebellar and cognitive symptoms (n = 9, 10.6%). Brain metabolism analyses (k > 89; p < 0.001) showed hypometabolism of the basal ganglia, frontal/prefrontal, temporal cortices and left posterior cerebellum in profile 1. In profile 2 there was hypometabolism of the medulla, prefrontal, temporal, cingular cortices, putamen and bilateral cerebellar hemispheres. In profile 3 there was hypometabolism of bilateral posterior cerebellar hemispheres and vermis. Conclusion: Beyond the two most common phenotypes of MSA, a third and particularly atypical profile with cerebellar and cognitive symptoms but without LPI involvement is described. These profiles are supported by different brain metabolic abnormalities which could be useful for diagnostic purposes. Highlights: We revealed three profiles of MSA patients using Latent Class Analysis (LCA). Two majority profiles recalled the ones proposed by the consensus classification. The third profile had cognitive symptoms associated with cerebellar involvement. These profiles were supported by different brain metabolic abnormalities.