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AI Risk Score on Screening Mammograms Preceding Breast Cancer Diagnosis
Marthe Larsen1, Camilla F Olstad1, Henrik W Koch1
1From the Section for Breast Cancer Screening (M.L., C.F.O., S.H.) and Department of Register Informatics (S.A., J.N.), Cancer Registry of Norway, P.O. Box 5313, 0304 Oslo, Norway; Department of Radiology, Stavanger University Hospital, Stavanger, Norway (H.W.K.); Faculty of Health Sciences, University of Stavanger, Stavanger, Norway (H.W.K.); Department of Radiology, Østfold Hospital Trust, Kalnes, Norway (M.A.M.); Institute of Clinical Medicine, University of Oslo, Oslo, Norway (M.A.M.); Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway (S.R.H.); Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, National University for Science and Technology, Trondheim, Norway (S.R.H.); Department of Radiology and Nuclear Medicine, St Olavs University Hospital, Trondheim, Norway (H.L.H.); Department of Radiology, Hospital of Southern Norway, Kristiansand, Norway (H.S.S.); SPKI-The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, Norway (K.Ø.M.); Department of Clinical Medicine (K.Ø.M.) and Health and Care Sciences (S.H.), Faculty of Health Sciences, UiT-The Arctic University of Norway, Tromsø, Norway; Department of Translational Medicine, Diagnostic Radiology, Lund University, Lund, Sweden (K.L.); Unilabs Mammography Unit, Skåne University Hospital, Malmø, Sweden (K.L.); School of Medicine, University of Nottingham, Clinical Science Building, Nottingham City Hospital, Nottingham, United Kingdom (Y.C.).
Artificial intelligence (AI) risk scores on prior mammograms identified over one-third of subsequent breast cancers. This suggests AI may improve early breast cancer detection in screening programs.
Area of Science:
- Radiology
- Artificial Intelligence
- Oncology
Background:
- Limited research exists on artificial intelligence (AI) in prior screening mammography.
- Evaluating AI's role in identifying breast cancer risk from historical screening data is crucial.
Purpose of the Study:
- To investigate the association between AI-generated risk scores from prior screening mammograms and subsequent breast cancer diagnosis.
- To assess if AI risk scores can predict malignancy in women later diagnosed with breast cancer.
Main Methods:
- Retrospective analysis of screening mammograms from BreastScreen Norway (2004-2019).
- Commercially available AI system assigned risk scores (1-10) to prior examinations of women diagnosed with breast cancer.
- Bivariate analysis tested the association between AI scores and mammographic features.
Main Results:
- Over one-third of screen-detected (38.3%) and interval (39.4%) breast cancers had the highest AI risk score (10) in the prior screening round.
- Among screen-detected cancers, 23.0% had the highest AI score up to four years before diagnosis.
- Mammographic features, like density with calcifications, were significantly associated with higher AI scores for invasive cancers (P < .001).
Conclusions:
- A significant proportion of breast cancers were flagged with the highest AI risk score in prior screening mammograms.
- AI risk scoring in mammography screening holds potential for earlier breast cancer detection.
- Further research into AI integration in screening workflows is warranted.
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