Comparison of breast density assessment between human eye and automated software on digital and synthetic mammography: Impact on breast cancer risk

Abstract

PurposeTo evaluate the agreement between automatic assessment software of breast density based on artificial intelligence (AI) and visual assessment by a senior and a junior radiologist, as well as the impact on the assessment of breast cancer risk (BCR) at 5 years. Materials and methodsWe retrospectively included 311 consecutive women (mean age, 55.6±8.5 [SD]; range: 40–74 years) without a personal history of breast cancer who underwent routine mammography between January 1, 2019 and February 28, 2019. Mammographic breast density (MBD) was independently evaluated by a junior and a senior reader on digital mammography (DM) and synthetic mammography (SM) using BI-RADS (5th edition) and by an AI software. For each MBD, BCR at 5 years was estimated per woman by the AI software. Interobserver agreement for MBD between the two readers and the AI software were evaluated by quadratic κ coefficients. Reproducibility of BCR was assessed by intraclass correlation coefficient (ICC). ResultsAgreement for MBD assessment on DM and SM was almost perfect between senior and junior radiologists (κ=0.88 [95% CI: 0.84–0.92] and κ=0.86 [95% CI: 0.82–0.90], respectively) and substantial between the senior radiologist and AI (κ=0.79; 95% CI: 0.73–0.84). There was substantial agreement between DM and SM for the senior radiologist (κ=0.79; 95% CI: 0.74–0.84). BCR evaluation at 5 years was highly reproducible between the two radiologists on DM and SM (ICC=0.98 [95% CI: 0.97–0.98] for both), between BCR evaluation based on DM and SM evaluated by the senior (ICC=0.96; 95% CI: 0.95–0.97) or junior radiologist (ICC=0.97; 95% CI: 0.96–0.98) and between the senior radiologist and AI (ICC=0.96; 95% CI: 0.95–0.97). ConclusionThis preliminary study demonstrates a very good agreement for BCR evaluation based on the evaluation of MBD by a senior radiologist, junior radiologist and AI software.