Three-dimensional convolutional neural network model to identify clinically significant prostate cancer in transrectal ultrasound videos: a prospective, multi-institutional, diagnostic study

作者：Yi-Kang Sun, Boyang Zhou, Yao Miao, Yi-Lei Shi, Shihao Xu, Dao-Ming Wu, Lei Zhang, Guang Xu, Tingfan Wu, Lifan Wang, Haohao Yin, Xin Ye, Dan Lu, Hong Han, Li‐Hua Xiang, Xiao Xiang Zhu, Chong-Ke Zhao, Hui‐Xiong Xu · 发表于：EClinicalMedicine · 年份：2023 · DOI：10.1016/j.eclinm.2023.102027 · 被引用次数：31 · 研究领域：Prostate Cancer Diagnosis and Treatment、Advanced Radiotherapy Techniques、AI in cancer detection

Background: Identifying patients with clinically significant prostate cancer (csPCa) before biopsy helps reduce unnecessary biopsies and improve patient prognosis. The diagnostic performance of traditional transrectal ultrasound (TRUS) for csPCa is relatively limited. This study was aimed to develop a high-performance convolutional neural network (CNN) model (P-Net) based on a TRUS video of the entire prostate and investigate its efficacy in identifying csPCa. Methods: Between January 2021 and December 2022, this study prospectively evaluated 832 patients from four centres who underwent prostate biopsy and/or radical prostatectomy. All patients had a standardised TRUS video of the whole prostate. A two-dimensional CNN (2D P-Net) and three-dimensional CNN (3D P-Net) were constructed using the training cohort (559 patients) and tested on the internal validation cohort (140 patients) as well as on the external validation cohort (133 patients). The performance of 2D P-Net and 3D P-Net in predicting csPCa was assessed in terms of the area under the receiver operating characteristic curve (AUC), biopsy rate, and unnecessary biopsy rate, and compared with the TRUS 5-point Likert score system as well as multiparametric magnetic resonance imaging (mp-MRI) prostate imaging reporting and data system (PI-RADS) v2.1. Decision curve analyses (DCAs) were used to determine the net benefits associated with their use. The study is registered at https://www.chictr.org.cn with the unique identif...