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

Authors

Yun-Woo Chang, Jung Kyu Ryu, Jin Kyung An, Nami Choi, Young Mi Park, Kyung Hee Ko, Kyunghwa Han

Published in

Nature communications. Volume 16. Issue 1. Pages 2248. Mar 06, 2025. Epub Mar 06, 2025.

Abstract

Artificial intelligence (AI) improves the accuracy of mammography screening, but prospective evidence, particularly in a single-read setting, remains limited. This study compares the diagnostic accuracy of breast radiologists with and without AI-based computer-aided detection (AI-CAD) for screening mammograms in a real-world, single-read setting. A prospective multicenter cohort study is conducted within South Korea's national breast cancer screening program for women. The primary outcomes are screen-detected breast cancer within one year, with a focus on cancer detection rates (CDRs) and recall rates (RRs) of radiologists. A total of 24,543 women are included in the final cohort, with 140 (0.57%) screen-detected breast cancers. The CDR is significantly higher by 13.8% for breast radiologists using AI-CAD (n = 140 [5.70‰]) compared to those without AI (n = 123 [5.01‰]; p < 0.001), with no significant difference in RRs (p = 0.564). These preliminary results show a significant improvement in CDRs without affecting RRs in a radiologist's standard single-reading setting (ClinicalTrials.gov: NCT05024591).

PMID:
40050619
Bibliographic data and abstract were imported from PubMed on 07 Mar 2025.

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