New York City-based Weill Cornell Medicine received a five-year grant from the National Institute of Diabetes and Digestive and Kidney Diseases to support TRACE, an AI-powered tool to measure organ volumes from imaging data.
TRACE, an acronym for Tool for Reproducible, Accurate Contour Estimation, uses deep-learning algorithms to reduce variability in imaging assessments and improve accuracy in tracking disease progression, according to an Oct. 20 news release. The project aims to support researchers studying autosomal dominant polycystic kidney disease, a genetic condition that affects about 600,000 people in the U.S. and accounts for 90% of all PKD cases.
The team is building a national PKD imaging database — the PKD Image Phenotyping Repository Core — using deidentified MRI and CT images of the kidneys and surrounding organs. The repository will also include data on skeletal muscle index and cyst metrics to support research on disease severity and treatment response.
Weill Cornell researchers plan to make the database publicly accessible to advance PKD research and clinical trial design.
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