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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Hlavní autoři:	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
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Elsevier 2024-01-01
Edice:	NeuroImage: Clinical
Témata:	Clinical neurology Frontotemporal dementia Frontotemporal lobar degeneration FDG-PET Machine learning
On-line přístup:	http://www.sciencedirect.com/science/article/pii/S2213158223002504
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