An artificial intelligence model for detecting pathological lymph node metastasis in prostate cancer using whole slide images: a retrospective, multicentre, diagnostic study

作者：Shaoxu Wu, Yun Wang, Guibin Hong, Yun Luo, Zhen Lin, Runnan Shen, Hong Zeng, Xun Xu, Peng Wu, Mingzhao Xiao, Xiaoyang Li, Peng Rao, Qishen Yang, Zhengyuan Feng, Quanhao He, Fan Jiang, Ye Xie, Chengxiao Liao, Xiaowei Huang, Rui Chen, Tianxin Lin · 发表于：EClinicalMedicine · 年份：2024 · DOI：10.1016/j.eclinm.2024.102580 · 被引用次数：9 · 研究领域：Prostate Cancer Diagnosis and Treatment、AI in cancer detection、Advanced Radiotherapy Techniques

Background The pathological examination of lymph node metastasis (LNM) is crucial for treating prostate cancer (PCa). However, the limitations with naked-eye detection and pathologist workload contribute to a high missed-diagnosis rate for nodal micrometastasis. We aimed to develop an artificial intelligence (AI)-based, time-efficient, and high-precision PCa LNM detector (ProCaLNMD) and evaluate its clinical application value. Methods In this multicentre, retrospective, diagnostic study, consecutive patients with PCa who underwent radical prostatectomy and pelvic lymph node dissection at five centres between Sep 2, 2013 and Apr 28, 2023 were included, and histopathological slides of resected lymph nodes were collected and digitised as whole-slide images for model development and validation. ProCaLNMD was trained at a dataset from a single centre (the Sun Yat-sen Memorial Hospital of Sun Yat-sen University [SYSMH]), and externally validated in the other four centres. A bladder cancer dataset from SYSMH was used to further validate ProCaLNMD, and an additional validation (human-AI comparison and collaboration study) containing consecutive patients with PCa from SYSMH was implemented to evaluate the application value of integrating ProCaLNMD into the clinical workflow. The primary endpoint was the area under the receiver operating characteristic curve (AUROC) of ProCaLNMD. In addition, the performance measures for pathologists with ProCaLNMD assistance was also assessed. Finding...