AI Risk Score on Screening Mammograms Preceding Breast Cancer Diagnosis

Abstract

More than 38% of both screen-detected and interval cancers were assigned the highest artificial intelligence risk score on screening mammograms that preceded breast cancer diagnosis.<p>

<p>Background - Few studies have evaluated the role of artificial intelligence (AI) in prior screening mammography.<p>

<p>Purpose - To examine AI risk scores assigned to screening mammography in women who were later diagnosed with breast cancer.<p>

<p>Materials and Methods - Image data and screening information of examinations performed from January 2004 to December 2019 as part of BreastScreen Norway were used in this retrospective study. Prior screening examinations from women who were later diagnosed with cancer were assigned an AI risk score by a commercially available AI system (scores of 1–7, low risk of malignancy; 8–9, intermediate risk; and 10, high risk of malignancy). Mammographic features of the cancers based on the AI score were also assessed. The association between AI score and mammographic features was tested with a bivariate test.<p>

<p>Results - A total of 2787 prior screening examinations from 1602 women (mean age, 59 years ± 5.1 [SD]) with screen-detected (n = 1016) or interval (n = 586) cancers showed an AI risk score of 10 for 389 (38.3%) and 231 (39.4%) cancers, respectively, on the mammograms in the screening round prior to diagnosis. Among the screen-detected cancers with AI scores available two screening rounds (4 years) before diagnosis, 23.0% (122 of 531) had a score of 10. Mammographic features were associated with AI score for invasive screen-detected cancers (P < .001). Density with calcifications was registered for 13.6% (43 of 317) of screen-detected cases with a score of 10 and 4.6% (15 of 322) for those with a score of 1–7.<p>

<p>Conclusion - More than one in three cases of screen-detected and interval cancers had the highest AI risk score at prior screening, suggesting that the use of AI in mammography screening may lead to earlier detection of breast cancers.