Artificial intelligence for breast cancer screening in mammography (AI-STREAM): Preliminary analysis of a prospective multicenter cohort study

Abstract

Several studies have shown that artificial intelligence (AI) improves mammography screening accuracy. Meanwhile, prospective evidence, particularly in a single-read setting, is lacking. This study aimed to compare the diagnostic accuracy of breast radiologists, with and without an AI-based computer-aided detection (AI-CAD) for interpreting screening mammograms in a real-world, single-read setting. A prospective multicenter cohort study in six academic hospitals participant in South Korea’s national breast cancer screening program was done, where women aged ³40 years were eligible for enrollment between February 2021 and December 2022. The primary outcome was screen-detected breast cancer diagnosed at a one-year follow-up. The primary analysis compared cancer detection rate (CDRs) and recall rates (RRs) of breast imaging specialized radiologists, with and without AI assistance. The exploratory, secondary analysis compared CDRs and RRs of general radiologists, with and without AI, as well as radiologists versus standalone AI. Of 25,008 women who were eligible for enrollment, 24,543 women were included in the final cohort (median age 61 years [IQR 51-68]), with 140 (0.57%) screen-detected breast cancers. The CDR was significantly higher by 13.8% for breast radiologists with AI-CAD (n=140 [5.70 ‰]) versus those without AI (n=123 [5.01 ‰]; p <0.001), with no significant difference in RRs (p =0.564). Similar trends were observed for general radiologists, with a significant 26.4% higher CDR in those with AI-CAD (n=120 [4.89 ‰]) versus those without AI (n=95 [3.87 ‰]; p <0.001). The CDR of standalone AI (n=128 [5.21 ‰]) was also significantly higher than that of general radiologists without AI (p=0.027), with no significant differences in RRs (p =0.809). This preliminary result from a prospective, multicenter cohort study provided evidence of significant improvement in CDRs without affected RRs of breast radiologists when using AI-CAD, as compared to not using AI-CAD, when interpreting screening mammograms in a radiologist’s standard single reading setting. Furthermore, AI-CAD assistance could potentially improve radiologist’s reading performance, regardless of experience (ClinicalTrials.gov: NCT0524591).