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Published 2024 | Version v1
Journal article

How do AI markings on screening mammograms correspond to cancer location? An informed review of 270 breast cancer cases in BreastScreen Norway

  • 1. Faculty of Health Sciences, University of Stavanger, Stavanger (Norway)
  • 2. Department of Radiology, Stavanger University Hospital, Stavanger (Norway)
  • 3. Section for Breast Cancer Screening, Cancer Registry of Norway, Norwegian Institute of Public Health, P.O. Box 5313, 0304, Oslo (Norway)
  • 4. Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Bergen (Norway)
  • 5. University of Oslo, Institute of Clinical Medicine, Oslo (Norway)
  • 6. Department of Radiology, Østfold Hospital Trust, Kalnes (Norway)
  • 7. Section for Radiology, Department of Clinical Medicine, University of Bergen, Bergen (Norway)
  • 8. Department of Health and Care Sciences, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø (Norway)

Description

To compare the location of AI markings on screening mammograms with cancer location on diagnostic mammograms, and to classify interval cancers with high AI score as false negative, minimal sign, or true negative. In a retrospective study from 2022, we compared the performance of an AI system with independent double reading according to cancer detection. We found 93% (880/949) of the screen-detected cancers, and 40% (122/305) of the interval cancers to have the highest AI risk score (AI score of 10). In this study, four breast radiologists reviewed mammograms from 126 randomly selected screen-detected cancers and all 120 interval cancers with an AI score of 10. The location of the AI marking was stated as correct/not correct in craniocaudal and mediolateral oblique view. Interval cancers with an AI score of 10 were classified as false negative, minimal sign significant/non-specific, or true negative. All screen-detected cancers and 78% (93/120) of the interval cancers with an AI score of 10 were correctly located by the AI system. The AI markings matched in both views for 79% (100/126) of the screen-detected cancers and 22% (26/120) of the interval cancers. For interval cancers with an AI score of 10, 11% (13/120) were correctly located and classified as false negative, 10% (12/120) as minimal sign significant, 26% (31/120) as minimal sign non-specific, and 31% (37/120) as true negative. AI markings corresponded to cancer location for all screen-detected cancers and 78% of the interval cancers with high AI score, indicating a potential for reducing the number of interval cancers. However, it is uncertain whether interval cancers with subtle findings in only one view are actionable for recall in a true screening setting. In this study, AI markings corresponded to the location of the cancer in a high percentage of cases, indicating that the AI system accurately identifies the cancer location in mammograms with a high AI score.

Additional details

Identifiers

Publishing Information

Journal Title
European Radiology (Internet)
Journal Volume
34
Journal Issue
9
Journal Page Range
p. 6158-6167
ISSN
1432-1084
CODEN
EURAE3