AI-based density prediction for breast cancer prevention: Can we measure mammographic density in just one breast?

Megan Perry; Stepan Romanov; Sacha J. Howell; D. Gareth Evans; Elaine F. Harkness; Susan M. Astley

doi:10.1117/12.3006745

3 April 2024 AI-based density prediction for breast cancer prevention: Can we measure mammographic density in just one breast?

Megan Perry, Stepan Romanov, Sacha J. Howell, D. Gareth Evans, Elaine F. Harkness, Susan M. Astley

Author Affiliations +

Proceedings Volume 12927, Medical Imaging 2024: Computer-Aided Diagnosis; 129270D (2024) https://doi.org/10.1117/12.3006745
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Abstract

Breast density is an important factor in assessing individual breast cancer risk. We aim to identify women at increased risk of developing breast cancer before they enter routine screening, using mammography in combination with known risk factors. This will enable targeting of preventive therapies and personalised screening. To reduce radiation risk, this paper examines whether density measurements in one breast or mammographic view could be used to accurately reflect individual risk. We analysed breast cancer risk using breast density in a 1:3 case-control dataset of mammograms from the Predicting Risk of Cancer at Screening Study (PROCAS). Breast density was measured using pVAS, an AI-based approach. Cancer risk in low and high breast density groups was compared using conditional logistic regression. High breast density was independently associated with increased breast cancer risk. Women in the highest breast density quintile averaged across all views had an Odds Ratio (OR) of 4.16 (95% CI 2.90-5.97) compared to those in the lowest. A similar OR was found in both the left 3.77 (95% CI 2.68-5.31) and right 4.52 (95% CI 3.12-6.55) breasts individually. ORs were also significant for each individual view: right mediolateral oblique (MLO) 4.19 (2.92–6.00), right craniocaudal (CC) 4.40 (3.09–6.27), left MLO 3.27 (2.34–4.56) and left CC 3.65 (2.60–5.11). The ability to predict breast cancer risk due to increased breast density was achieved using one breast and even one mammographic view. This provides the possibility of a pre-screening risk assessment using fewer images and therefore less radiation.

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(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Megan Perry, Stepan Romanov, Sacha J. Howell, D. Gareth Evans, Elaine F. Harkness, and Susan M. Astley "AI-based density prediction for breast cancer prevention: Can we measure mammographic density in just one breast?", Proc. SPIE 12927, Medical Imaging 2024: Computer-Aided Diagnosis, 129270D (3 April 2024); https://doi.org/10.1117/12.3006745

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