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Abstract #3004

Breast MRI radiomic shape features for the prediction of neoadjuvant therapy response

Wen Li1, Rohan Nadkarni1, David C Newitt1, Bo La Yun1,2, Deep Hathi1, Alex Nguyen1, Natsuko Onishi1, Lisa J Wilmes1, Ella F Jones1, Jessica Gibbs1, Teffany Joy Bareng1, Bonnie N Joe1, Elissa Price1, Rita Mukhtar1, John Kornak1, Efstathios Gennatos1, I-SPY 2 Consortium3, Laura J Esserman1, and Nola M Hylton1
1University of California, San Francisco, San Francisco, CA, United States, 2Seoul National University Bundang Hospital, Seoul, Korea, Republic of, 3Quantum Leap Healthcare Collaborative, San Francisco, CA, United States

A previous study demonstrated that tumor sphericity, measured from breast DCE-MRI during neoadjuvant therapy, is predictive of pathologic complete response and adds value to a predictive model based on functional tumor volume (FTV) alone. This study further explores the additive value of alternative radiomic shape features by breast cancer subtype. A subset of shape features were selected using visually assessed MRI morphological patterns as guidance. The analysis of treatment response prediction was conducted retrospectively using data from the multi-center neoadjuvant I-SPY 2 TRIAL. Improved predictive performance when adding shape features was observed at both pre-treatment and early treatment time points.

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