Project Grant K99AG068310

Award Date 5/1/21
Completion Date 7/30/21
Dollars Obligated $137K
Federal Grant Program
93.866
Assistance Type
Project Grant
Place of Performance
Stanford, CA 94305, USA

This Project Grant from the National Institutes of Health's National Institute on Aging, under the Aging Research program (CFDA 93.866), provided $137,342.16 to Stanford University to develop generalizable deep learning networks for dual-tracer amyloid and tau positron emission tomography (PET) and magnetic resonance imaging (MRI) of Alzheimer's disease. Specifically, the university will validate the diagnostic value of convolutional neural networks (CNNs) in actual ultra-low-dose amyloid and tau imaging sessions with the injected dose as low as 1% of standard levels. It will also apply the ultra-low-dose CNNs to data from other PET systems and tracers to demonstrate generalizability. Finally, the university will evaluate the value of deep learning-aided ultra-low-dose amyloid and tau PET for tracking cognitive decline in a preclinical Alzheimer's disease population. The innovation lies in combining multimodal imaging and advanced machine learning to enable diagnostic-level PET images at extremely low radiation doses, allowing for more frequent and large-scale clinical longitudinal imaging studies.

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