AI in breast screening mammography: breast screening readers' perspectives

• Published in: Insights into imaging 2022-12, Vol.13 (1), p.186-186, Article 186
• Main Authors: de Vries, Clarisse Florence, Colosimo, Samantha J., Boyle, Moragh, Lip, Gerald, Anderson, Lesley A., Staff, Roger T.
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Breast cancer; Breast screening reader; Datasets; Diagnostic Radiology; Guidelines; Imaging; Internal Medicine; Interventional Radiology; Mammography; Medicine; Medicine & Public Health; Neuroradiology; Original; Original Article; Polls & surveys; Radiologist; Radiology; Representations; Screening; Survey; Tumors; Ultrasound
• ISSN: 1869-4101; 1869-4101
• DOI: 10.1186/s13244-022-01322-4

Objectives This study surveyed the views of breast screening readers in the UK on how to incorporate Artificial Intelligence (AI) technology into breast screening mammography. Methods An online questionnaire was circulated to the UK breast screening readers. Questions included their degree of approval of four AI implementation scenarios: AI as triage, AI as a companion reader/reader aid, AI replacing one of the initial two readers, and AI replacing all readers. They were also asked to rank five AI representation options (discrete opinion; mammographic scoring; percentage score with 100% indicating malignancy; region of suspicion; heat map) and indicate which evidence they considered necessary to support the implementation of AI into their practice among six options offered. Results The survey had 87 nationally accredited respondents across the UK; 73 completed the survey in full. Respondents approved of AI replacing one of the initial two human readers and objected to AI replacing all human readers. Participants were divided on AI as triage and AI as a reader companion. A region of suspicion superimposed on the image was the preferred AI representation option. Most screen readers considered national guidelines (77%), studies using a nationally representative dataset (65%) and independent prospective studies (60%) as essential evidence. Participants’ free-text comments highlighted concerns and the need for additional validation. Conclusions Overall, screen readers supported the introduction of AI as a partial replacement of human readers and preferred a graphical indication of the suspected tumour area, with further evidence and national guidelines considered crucial prior to implementation. Key points Surveyed UK breast screening readers supported the introduction of AI. Respondents approved of the replacement of one of the two initial readers. Participants objected to the replacement of all human readers. Respondents preferred the AI to graphically indicate the suspected tumour area. Screen readers preferred forms of evidence based on national guidelines, national representative datasets, and independent prospective studies.