Mammographic density assessment by an artificial intelligence model for breast cancer detection in BreastScreen Norway.

Marthe Larsen¹, Nataliia Moshina¹, Karl Øyvind Mikalsen^2,3, Solveig Roth Hoff^4,5, Håkon Lund-Hanssen⁶, Marit A Martiniussen^7,8, Marko Silberhorn⁹, Marte M Schulze¹⁰, Solveig Hofvind^11,12

¹Department of Breast Cancer Screening, The Cancer Registry of Norway, Norwegian Institute of Public Health, Oslo, Norway.

²SPKI-The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, Norway.

³Department of Clinical Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway.

⁴Department of Radiology, Møre og Romsdal Hospital Trust, Ålesund, Norway.

⁵Department of Health Sciences in Ålesund, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.

⁶Department of Radiology and Nuclear Medicine, St. Olavs University Hospital, Trondheim, Norway.

⁷Department of Radiology, Østfold Hospital Trust, Kalnes, Norway.

⁸Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

⁹Department of Radiology, Innlandet Hospital Trust, Hamar, Norway.

¹⁰Department of Radiology, Vestfold Hospital Trust, Tønsberg, Norway.

¹¹Department of Breast Cancer Screening, The Cancer Registry of Norway, Norwegian Institute of Public Health, Oslo, Norway. sshh@fhi.no.

¹²Department of Health and Care Sciences, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway. sshh@fhi.no.

PubMed DOI

Abstract

OBJECTIVES: The sensitivity of mammographic screening is lower for women with mammographically dense vs fatty breasts. We aimed to explore automated mammographic breast density and malignancy risk scores generated by an artificial intelligence (AI) model for breast cancer detection, stratified by mammography vendor. MATERIALS AND METHODS: This retrospective study included information from 200,000…

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