Abstract #0815

A Prior-Knowledge Embedded Convolutional Neural Network for Extracapsular Extension of the Prostate Cancer at Multi-Parametric MRI

Yihong Zhang¹, Ying Hou², Jie Bao³, Yang Song¹, Yu-dong Zhang², Xu Yan⁴, and Guang Yang¹

¹East China Normal University, Shanghai, China, ²the First Affiliated Hospital with Nanjing Medical University, Nanjing, China, ³the First Affiliated Hospital with Soochow University, Soochow, China, ⁴Siemens Healthcare, Shanghai, China

We proposed an algorithm to incorporate radiologist’s prior-knowledge about location of extension into a CNN model to diagnose the extracapsular extension of the prostate cancer from multiparametric MRI (mpMRI). The model was trained on 596 cases with ensemble learning before validated with an independent validation cohort of 150 cases and an external cohort of 103 cases. Our proposed model achieved an area under receiver operating characteristic curve (AUC) of 0.807/0.728 on the internal/external test cohort, which is better than the traditional model (AUC=0.746/0.723) and the clinical reports by two radiologists (AUC=0.725, 0.632/0.694, 0.712).

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