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A deep learning model to predict near pathological complete response for rectal cancer by the diffusion MRI data before chemoradiotherapy

Hai-Tao Zhu¹, Xiao-Yan Zhang¹, Yan-Jie Shi¹, Xiao-Ting Li¹, and Ying-Shi Sun¹
¹Peking University Cancer Hospital, BEIJING, China

A deep learning model is proposed to predict near pathological complete response by diffusion MRI data before chemoradiotherapy. 624 participants are included in this study with 424 for training and 200 for testing. The area under the curve of receiver operating characteristic is 0.80.

Fig.1: Structure of convolutional neural networks.DWI images at b=0 and b=1000 s/mm² are inputted into convolutional neural networks from two separated channels. Each channel passes through 5 repetitions of convolution and max-pooling layers (CMC unit). The last layer is densely connected.

Fig. 2: Receiver operating characteristic (ROC) curve of the deep learning model. The area under the curve (AUC) is 0.800 (95%CI: 0.735-0.851).