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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書誌詳細

出版年:	NeuroImage: Clinical
主要な著者:	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
フォーマット:	論文
言語:	英語
出版事項:	Elsevier 2024-01-01
主題:	Clinical neurology Frontotemporal dementia Frontotemporal lobar degeneration FDG-PET Machine learning
オンライン･アクセス:	http://www.sciencedirect.com/science/article/pii/S2213158223002504