The use of digital pathology and artificial intelligence in histopathological diagnostic assessment of prostate cancer: a survey of Prostate Cancer UK supporters

Rakovic, K. et al. (2022) The use of digital pathology and artificial intelligence in histopathological diagnostic assessment of prostate cancer: a survey of Prostate Cancer UK supporters. Diagnostics, 12(5), 1225. (doi: 10.3390/diagnostics12051225) (PMID:35626380) (PMCID:PMC9141178)

Abstract

There has been particular interest in the deployment of digital pathology (DP) and artificial intelligence (AI) in the diagnosis of prostate cancer, but little is known about the views of the public on their use. Prostate Cancer UK supporters were invited to an online survey which included quantitative and qualitative questions exploring views on the use of DP and AI in histopathological assessment. A total of 1276 responses to the survey were analysed (response rate 12.5%). Most respondents were supportive of DP (87%, 1113/1276) and of testing AI in clinical practice as a diagnostic adjunct (83%, 1058/1276). Respondents saw DP as potentially increasing workflow efficiency, facilitating research, education/training and fostering clinical discussions between clinician and patient. Some respondents raised concerns regarding data security, reliability and the need for human oversight. Among those who were unsure about AI, information was requested regarding its performance and others wanted to defer the decision to use it to an expert. Although most are in favour of its use, some are unsure, and their concerns could be addressed with more information or better communication. A small minority (1%) are not in favour of the testing of the use of AI in histopathology for reasons which are not easily addressed.

• Item Type: Articles
• Keywords: Prostate cancer, digital pathology, artificial intelligence.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Rakovic, Dr Kai

Creator Roles

Rakovic, K.: Data curation, Formal analysis, Writing – original draft, Writing – review and editing

• Authors: Rakovic, K., Colling, R., Browning, L., Dolton, M., Horton, M. R., Protheroe, A., Lamb, A. D., Bryant, R. J., Scheffer, R., Crofts, J., Stanislaus, E., and Verrill, C.
• College/School: College of Medical Veterinary and Life Sciences > School of Cancer Sciences
• Journal Name: Diagnostics
• Publisher: MDPI
• ISSN: 2075-4418
• ISSN (Online): 2075-4418
• Published Online: 13 May 2022
• Copyright Holders: Copyright © 2022 The Authors
• First Published: First published in Diagnostics 12(5): 1225
• Publisher Policy: Reproduced under a Creative Commons License