We developed a machine learning framework grounded in a computational model of brain function and FDG-PET imaging to predict Alzheimer’s disease (AD)-type tau across AD and related disorders (ADRD). The model was trained on 1088 research participants spanning normal aging and ADRD with FDG-PET and flortaucipir-PET...
Nick Corriveau-Lecavalier, Ge-Meng Zhang, H. Botha et al.· Nature Communications· 0 citations
Neuroimaging is now a cornerstone of Alzheimer's disease care and a crucial discriminator tool for characterising brain injury across the lifespan and with emerging fluid biomarkers, neuroimaging supports accurate diagnosis, prognosis, and treatment monitoring.
Tammie L. S. Benzinger, P. Cogswell, A. Arani et al.· Lancet Neurology· 2 citations
Amyloid-targeted monoclonal antibody therapies have introduced a new era in the treatment of early Alzheimer disease. However, their use has increased the importance of detecting and monitoring amyloid-related imaging abnormalities (ARIA) on MRI, as such findings may influence treatment continuation, dose modification,...
J. Petrella, F. Barkhof, T. Benzinger et al.· AJR. American journal of roe...· 0 citations
Diffusion MRI biomarkers were abnormal at least a decade before WMH abnormality in the population, revealing a prolonged phase of early SVD and highlighting their potential for SVD prevention.
P. Vemuri, Ming-Zhao Hu, Emily S. Lundt et al.· Stroke· 0 citations
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