Jia Ke, Cheng Jin, Jinghua Tang, Haimei Cao, Songbing He, Peirong Ding, Xiaofeng Jiang, Hengyu Zhao, Wuteng Cao, Xiaochun Meng, Feng Gao, Ping Lan, Ruijiang Li, Xiaojian Wu
BACKGROUND: Accurate prediction of response to neoadjuvant chemoradiotherapy is critical for subsequent treatment decisions for patients with locally advanced rectal cancer. OBJECTIVE: To develop and validate a deep learning model that based on the comparison of paired magnetic resonance imaging before and after neoadjuvant chemoradiotherapy to predict pathological complete response. DESIGN: By capturing the changes from magnetic resonance images before and after neoadjuvant chemoradiotherapy in 638 patients, we trained a multitask deep learning model for response prediction (DeepRP-RC) that also allowed simultaneous segmentation...
September 8, 2023: Diseases of the Colon and Rectum