Diagnosis and Gleason grading of prostate cancer in biopsies are critical for the clinical management of men with prostate cancer. Despite this, the high grading variability among pathologists leads to the potential for under- and overtreatment. Artificial intelligence (AI) systems have shown promise in assisting pathologists to perform Gleason grading, which could help address this problem. In this mini-review, we highlight studies reporting on the development of AI systems for cancer detection and Gleason grading, and discuss the progress needed for widespread clinical implementation, as well as anticipated future developments. PATIENT SUMMARY: This mini-review summarizes the evidence relating to the validation of artificial intelligence (AI)-assisted cancer detection and Gleason grading of prostate cancer in biopsies, and highlights the remaining steps required prior to its widespread clinical implementation. We found that, although there is strong evidence to show that AI is able to perform Gleason grading on par with experienced uropathologists, more work is needed to ensure the accuracy of results from AI systems in diverse settings across different patient populations, digitization platforms, and pathology laboratories.
European urology focus. 2021 Aug 12 [Epub ahead of print]
Kimmo Kartasalo, Wouter Bulten, Brett Delahunt, Po-Hsuan Cameron Chen, Hans Pinckaers, Henrik Olsson, Xiaoyi Ji, Nita Mulliqi, Hemamali Samaratunga, Toyonori Tsuzuki, Johan Lindberg, Mattias Rantalainen, Carolina Wählby, Geert Litjens, Pekka Ruusuvuori, Lars Egevad, Martin Eklund
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland., Department of Pathology, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands., Department of Pathology and Molecular Medicine, Wellington School of Medicine and Health Sciences, University of Otago, Wellington, New Zealand., Google Health, Palo Alto, CA, USA., Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden., Aquesta Uropathology and University of Queensland, Brisbane, QLD, Australia., Department of Surgical Pathology, School of Medicine, Aichi Medical University, Nagakute, Japan., Centre for Image Analysis, Department of Information Technology, Uppsala University, Uppsala, Sweden; BioImage Informatics Facility of SciLifeLab, Uppsala, Sweden., Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Institute of Biomedicine, Cancer Research Unit and FICAN West Cancer Centre, University of Turku and Turku University Hospital, Turku, Finland., Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden., Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. Electronic address: .