Assessing network degeneration and phenotypic heterogeneity in genetic frontotemporal lobar degeneration by decoding FDG-PET

Assessing network degeneration and phenotypic heterogeneity in genetic frontotemporal lobar degeneration by decoding FDG-PET

Genetic mutations causative of frontotemporal lobar degeneration (FTLD) are highly predictive of a specific proteinopathy, but there exists substantial inter-individual variability in their patterns of network degeneration and clinical manifestations. We collected clinical and 18Fluorodeoxyglucose-p...

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Bibliographic Details
Main Authors: Nick Corriveau-Lecavalier, Leland R. Barnard, Scott A. Przybelski, Venkatsampath Gogineni, Hugo Botha, Jonathan Graff-Radford, Vijay K. Ramanan, Leah K. Forsberg, Julie A. Fields, Mary M. Machulda, Rosa Rademakers, Ralitza H. Gavrilova, Maria I. Lapid, Bradley F. Boeve, David S. Knopman, Val J. Lowe, Ronald C. Petersen, Clifford R. Jack, Kejal Kantarci, David T. Jones
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:NeuroImage: Clinical
Subjects:
Clinical neurology
Frontotemporal dementia
Frontotemporal lobar degeneration
FDG-PET
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2213158223002504

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http://www.sciencedirect.com/science/article/pii/S2213158223002504

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