Abstract #1775

MRI Based Artificial Neural Network Model Used in Prostate Cancer Detection

Chengyan Wang¹, Juan Hu², He Wang², Hui Zhang¹, Rui Wang², Wenchao Cai², Wei Wang², Xiaoying Wang,¹², Jue Zhang³,⁴, Jing Fang,¹³

¹Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; ²Department of Radiology, Peking University First Hospital, Beijing, China; ³College of Engineering, Peking University, Beijing, China; ⁴Academy for Advanced Interdisciplinary Studies, Peking University , Beijing, China

In the present study, we propose a multi-layer artificial neural network (ANN) model integrating MR images (T2 weighted imagesdiffusion weighted images, dynamic contrast enhanced images and MR spectroscopy) and clinical examination (Total PSA value, free/total PSA ratio and age) for prostate cancer detection. The new model is able to provide high accuracy in detection of prostate cancer through proper training. Significant improvement in the AUC can be produced when compared to clinical-only model, and this demonstrates the capacity of MRI for computer-aided prostate cancer identification.