Sophia Zackrisson
Research group manager, Principal investigator, Professor, MD
Personalized breast cancer screening with selective addition of digital breast tomosynthesis through artificial intelligence
Author
Summary, in English
PURPOSE: Breast cancer screening is predominantly performed using digital mammography (DM), but digital breast tomosynthesis (DBT) has higher sensitivity. DBT demands more resources than DM, and it might be more feasible to reserve DBT for women with a clear benefit from the technique. We explore if artificial intelligence (AI) can select women who would benefit from DBT imaging.
APPROACH: We used data from Malmö Breast Tomosynthesis Screening Trial, where all women prospectively were examined with separately double read DM and DBT. We retrospectively analyzed DM examinations (n=14768) with a breast cancer detection system and used the provided risk score (1 to 10) for risk stratification. We tested how different score thresholds for adding DBT to an initial DM affects the number of detected cancers, additional DBT examinations needed, detection rate, and false positives.
RESULTS: If using a threshold of 9.0, 25 (26%) more cancers would be detected compared to using DM alone. Of the 41 cancers only detected on DBT, 61% would be detected, with only 1797 (12%) of the women examined with both DM and DBT. The detection rate for the added DBT would be 14/1000 women, whereas the false-positive recalls would be increased with 58 (21%).
CONCLUSION: Using DBT only for selected high gain cases could be an alternative to complete DBT screening. AI can analyze initial DM images to identify high gain cases where DBT can be added during the same visit. There might be logistical challenges, and further studies in a prospective setting are necessary.
Department/s
- LUCC: Lund University Cancer Centre
- Radiology Diagnostics, Malmö
- Medical Radiation Physics, Malmö
- LU Profile Area: Light and Materials
- LTH Profile Area: Photon Science and Technology
- EpiHealth: Epidemiology for Health
Publishing year
2023-02
Language
English
Publication/Series
Journal of Medical Imaging
Volume
10
Issue
Suppl 2
Document type
Journal article
Publisher
SPIE
Topic
- Radiology, Nuclear Medicine and Medical Imaging
- Cancer and Oncology
Status
Published
Research group
- Radiology Diagnostics, Malmö
- Medical Radiation Physics, Malmö
ISBN/ISSN/Other
- ISSN: 2329-4302