Objective: To identify characteristic metabolic brain patterns specific for multiple system atrophy (MSA) and progressive supranuclear palsy (PSP) in a new cohort of patients and to study its clinical significance.

Background: Focal brain dysfunction affects the activity of various remote areas via neuronal networks, which can be studied with multivariate analysis of FDG-PET images. Several neurodegenerative disease specific metabolic brain patterns have been identified using multivariate analysis, among them Parkinson’s disease related pattern (PDRP), MSA-related pattern (MSARP) and PSP-related pattern (PSPRP). While PDRP was reproduced and validated several times (1–4) in different populations and its correlation with clinical measures was proven, only a few groups studied PSPRP and MSARP reproducibility and their clinical correlations (5,6).

Method: 29 patients with MSA (age 63.2±9.5, disease duration (DD) 4.5±2.7 years), 18 with PSP (age 69.6±8.4, DD 4.5±1.5) and 20 normal controls (NC; age 67.2±5.7) underwent FGD-PET brain imaging. After preprocessing a SSM/PCA analysis was performed on MSA and NC to identify MSARP and on PSP and NC to identify PSPRP. The reliability of both patterns was tested with bootstrapping algorithm. MSARP and PSPRP expressions were calculated in each subject as their subject scores and correlated with disease duration and expressions of original patterns (5).

Results: Newly identified MSARP and PSPRP were proven stable at bootstrapping algorithm. MSARP was characterized by functionally connected hypometabolism in bilateral cerebellum, striatum (putamen more than caudate) and small areas of mediofrontal cortex while hypermetabolic areas were nonspecific [Figure 1]. PSPRP was characterized by hypometabolism in frontal cortex (especially mediofrontal), caudate and relative hypermetabolism in cerebellum and occipital cortices [Figure 2]. MSARP expressions correlated with disease duration (r=0.53, p=0.003) and there was a trend of correlation also for PSPRP (r=0.35, p=0.17). Both new patterns’ expressions correlated significantly with original patterns (MSARP, r=0.80, p<0.0001; PSPRP r=0.97, p<0.0001).

Conclusion: The newly identified metabolic brain patterns specific for MSA and PSP are a potential metabolic imaging biomarker of atypical parkinsonisms. They are consistent with the original patterns and also clinically significant.

References: 1. Ma Y, Tang C, Spetsieris PG, Dhawan V, Eidelberg D. Abnormal metabolic network activity in Parkinson’s disease: test-retest reproducibility. J Cereb Blood Flow Metab. 2007;27(3):597–605. 2. Teune LK, Renken RJ, Mudali D, De Jong BM, Dierckx RA, Roerdink JBTM, et al. Validation of parkinsonian disease-related metabolic brain patterns. Mov Disord. 2013 Apr;28(4):547–51. 3. Tomše P, Jensterle L, Rep S, Grmek M, Zaletel K, Eidelberg D, et al. The effect of 18F-FDG-PET image reconstruction algorithms on the expression of characteristic metabolic brain network in Parkinson’s disease. Phys Med. 2017 Sep;41:129–35. 4. Wu P, Wang J, Peng S, Ma Y, Zhang H, Guan Y, et al. Metabolic brain network in the Chinese patients with Parkinson’s disease based on 18F-FDG PET imaging. Parkinsonism Relat Disord. 2013;19(6):622–7. 5. Eckert T, Tang C, Ma Y, Brown N, Lin T, Frucht S, et al. Abnormal metabolic networks in atypical parkinsonism. Mov Disord. 2008;23(5):727–33. 6. Ge J, Wu J, Peng S, Wu P, Wang J, Zhang H, et al. Reproducible network and regional topographies of abnormal glucose metabolism associated with progressive supranuclear palsy: Multivariate and univariate analyses in American and Chinese patient cohorts. Hum Brain Mapp. 2018 Jul;39(7):2842–58.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/abnormal-metabolic-brain-network-in-multiple-system-atrophy-and-progressive-supranuclear-palsy-a-replication-on-a-new-european-cohort/