Highlights
- •Metabolic brain imaging can help differentiate between parkinsonian syndromes.
- •Metabolic brain patterns are robust and reproducible biomarkers of MSA and PSP.
- •Heat-maps present individual brain region's contribution to the metabolic pattern.
Abstract
Purpose
Differentiation between neurodegenerative parkinsonisms, whose early clinical presentation
is similar, may be improved with metabolic brain imaging. In this study we applied
a specific network analysis to 2-[18F]FDG PET brain scans to identify the characteristic metabolic patterns for multiple
system atrophy (MSA) and progressive supranuclear palsy (PSP) in a new European cohort.
We also developed a new tool to recognize and estimate patients’ metabolic brain heterogeneity.
Methods
20 MSA-P patients, 20 PSP patients and 20 healthy controls (HC) underwent 2-[18F]FDG PET brain imaging. The scaled subprofile model/principal component analysis
was applied to identify MSA/PSP-related patterns; MSARP and PSPRP. Additional, 56
MSA, 45 PSP, 116 PD and 61 HC subjects were analyzed for validation. We innovatively
applied heat-map analysis to extract and graphically display the pattern’s regional
sub-scores in individual subjects.
Results
MSARP was characterized by hypometabolism in cerebellum and putamen, and PSPRP by
hypometabolism in medial prefrontal cortices, nucleus caudatus, frontal cortices and
mesencephalon. Patterns’ expression discriminated between MSA/PSP patients and HCs
as well as between different parkinsonian cohorts (p < 0.001). Both patterns were sensitive and specific (AUC for MSARP/PSPRP: 0.96/0.99).
Heat-map analysis showed differences within MSA/PSP subjects and HCs consistent with
clinical presentation.
Conclusions
Replication and validation of MSARP and PSPRP confirms robustness of these metabolic
biomarkers and supports its application in clinical and research practice. Heat-map
analysis gives us an insight into the contribution of various pattern’s regions to
patterns’ expression in individual subjects, which improves our insight into the heterogeneity
of studied syndromes.
Keywords
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Article info
Publication history
Published online: May 07, 2022
Accepted:
April 27,
2022
Received in revised form:
March 15,
2022
Received:
December 15,
2021
Identification
Copyright
© 2022 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights reserved.
