Prostate cancer (PCa) is a common malignancy in males. The pathology review of PCa is crucial for clinical decision-making, but traditional pathology review is labor intensive and subjective to some extent. Digital pathology and whole-slide imaging enable the application of artificial intelligence (AI) in pathology. This review highlights the success of AI in detecting and grading PCa, predicting patient outcomes, and identifying molecular subtypes. We propose that AI-based methods could collaborate with pathologists to reduce workload and assist clinicians in formulating treatment recommendations. We also introduce the general process and challenges in developing AI pathology models for PCa. Importantly, we summarize publicly available datasets and open-source codes to facilitate the utilization of existing data and the comparison of the performance of different models to improve future studies.
Cell reports. Medicine. 2024 Apr 08 [Epub]
Lingxuan Zhu, Jiahua Pan, Weiming Mou, Longxin Deng, Yinjie Zhu, Yanqing Wang, Gyan Pareek, Elias Hyams, Benedito A Carneiro, Matthew J Hadfield, Wafik S El-Deiry, Tao Yang, Tao Tan, Tong Tong, Na Ta, Yan Zhu, Yisha Gao, Yancheng Lai, Liang Cheng, Rui Chen, Wei Xue
Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China; Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Changping Laboratory, Beijing, China., Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China., Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China., Department of Urology, Shanghai Changhai Hospital, Second Military Medical University, Shanghai 200433, China., Department of Surgery (Urology), Brown University Warren Alpert Medical School, Providence, RI, USA; Minimally Invasive Urology Institute, Providence, RI, USA., The Legorreta Cancer Center at Brown University, Lifespan Cancer Institute, Providence, RI, USA., The Legorreta Cancer Center at Brown University, Laboratory of Translational Oncology and Experimental Cancer Therapeutics, Department of Pathology & Laboratory Medicine, The Warren Alpert Medical School of Brown University, The Joint Program in Cancer Biology, Brown University and Lifespan Health System, Division of Hematology/Oncology, The Warren Alpert Medical School of Brown University, Providence, RI, USA., Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China., Faculty of Applied Sciences, Macao Polytechnic University, Address: R. de Luís Gonzaga Gomes, Macao, China., College of Physics and Information Engineering, Fuzhou University, Fujian 350108, China., Department of Pathology, Shanghai Changhai Hospital, Second Military Medical University, Shanghai 200433, China., Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China; The First School of Clinical Medicine, Southern Medical University, Guangzhou, China., Department of Surgery (Urology), Brown University Warren Alpert Medical School, Providence, RI, USA; Department of Pathology and Laboratory Medicine, Department of Surgery (Urology), Brown University Warren Alpert Medical School, Lifespan Health, and the Legorreta Cancer Center at Brown University, Providence, RI, USA. Electronic address: ., Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China. Electronic address: ., Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China. Electronic address: .