Julia E McGuinness, Garnet L Anderson, Simukayi Mutasa, Dawn L Hershman, Mary Beth Terry, Parisa Tehranifar, Danika L Lew, Monica Yee, Eric A Brown, Sebastien S Kairouz, Nafisa Kuwajerwala, Therese B Bevers, John E Doster, Corrine Zarwan, Laura Kruper, Lori M Minasian, Leslie Ford, Banu Arun, Marian L Neuhouser, Gary E Goodman, Powel H Brown, Richard Ha, Katherine D Crew
Deep learning-based mammographic evaluations could noninvasively assess response to breast cancer (BC) chemoprevention. We evaluated change in a convolutional neural network (CNN)-based BC risk model applied to mammograms among women enrolled in SWOG S0812, which randomized 208 premenopausal high-risk women to receive oral vitamin D3 20,000IU weekly or placebo for 12 months. We applied the CNN model to mammograms collected at baseline (n = 109), 12 months (n = 97) and 24 months (n = 67), and compared changes in CNN risk score between treatment groups...
May 30, 2024: JNCI Cancer Spectrum