The Use of Digital Pathology and Artificial Intelligence in Histopathological Diagnostic Assessment of Prostate Cancer: A Survey of Prostate Cancer UK Supporters

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 quantitat...

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Published in:Diagnostics (Basel) Vol. 12; no. 5; p. 1225
Main Authors: Rakovic, Kai, Colling, Richard, Browning, Lisa, Dolton, Monica, Horton, Margaret R., Protheroe, Andrew, Lamb, Alastair D., Bryant, Richard J., Scheffer, Richard, Crofts, James, Stanislaus, Ewart, Verrill, Clare
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 13.05.2022
MDPI
Subjects:
Artificial intelligence
Biopsy
COVID-19
digital pathology
Histopathology
Mammography
Microscopy
Morphology
Pathology
Prostate cancer
United Kingdom > UK
Scotland
Wales
digital pathology
prostate cancer
artificial intelligence
ISSN:2075-4418, 2075-4418
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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.
AbstractList 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.
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.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.
Author Bryant, Richard J.
Crofts, James
Rakovic, Kai
Colling, Richard
Protheroe, Andrew
Stanislaus, Ewart
Browning, Lisa
Dolton, Monica
Scheffer, Richard
Horton, Margaret R.
Lamb, Alastair D.
Verrill, Clare
AuthorAffiliation 1 Institute of Cancer Sciences, University of Glasgow, Switchback Road, Glasgow G61 1QH, UK
2 Department of Pathology, Queen Elizabeth University Hospital, Govan Road, Glasgow G51 4TF, UK
9 Department of Urology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Old Road, Oxford OX3 7LE, UK
3 Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK; richard.colling@pmb.ox.ac.uk (R.C.); lisa.browning@ouh.nhs.uk (L.B.); clare.verrill@ouh.nhs.uk (C.V.)
5 NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK
4 Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK; monica.dolton@nds.ox.ac.uk (M.D.); alastair.lamb@nds.ox.ac.uk (A.D.L.); richard.bryant@nds.ox.ac.uk (R.J.B.); richard.scheffer@btinternet.com (R.S.); croftsj@hotmail.com (J.C
AuthorAffiliation_xml – name: 1 Institute of Cancer Sciences, University of Glasgow, Switchback Road, Glasgow G61 1QH, UK
– name: 3 Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK; richard.colling@pmb.ox.ac.uk (R.C.); lisa.browning@ouh.nhs.uk (L.B.); clare.verrill@ouh.nhs.uk (C.V.)
– name: 2 Department of Pathology, Queen Elizabeth University Hospital, Govan Road, Glasgow G51 4TF, UK
– name: 7 Department of Oncology, University of Oxford, Roosevelt Drive, Oxford OX3 7DQ, UK; andrew.protheroe@oncology.ox.ac.uk
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– name: 4 Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK; monica.dolton@nds.ox.ac.uk (M.D.); alastair.lamb@nds.ox.ac.uk (A.D.L.); richard.bryant@nds.ox.ac.uk (R.J.B.); richard.scheffer@btinternet.com (R.S.); croftsj@hotmail.com (J.C.); ewartbs@hotmail.com (E.S.)
– name: 6 Paige AI, 11 Times Sq, Fl 37, New York, NY 10036, USA; margaret.horton@paige.ai
– name: 8 Oxford Cancer & Haematology Centre, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Old Road, Oxford OX3 7LE, UK
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/35626380$$D View this record in MEDLINE/PubMed
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Issue 5
Keywords digital pathology
prostate cancer
artificial intelligence
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Snippet There has been particular interest in the deployment of digital pathology (DP) and artificial intelligence (AI) in the diagnosis of prostate cancer, but little...
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StartPage 1225
SubjectTerms Artificial intelligence
Biopsy
COVID-19
digital pathology
Histopathology
Mammography
Microscopy
Morphology
Pathology
Prostate cancer
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Title The Use of Digital Pathology and Artificial Intelligence in Histopathological Diagnostic Assessment of Prostate Cancer: A Survey of Prostate Cancer UK Supporters
URI https://www.ncbi.nlm.nih.gov/pubmed/35626380
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