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

  • Chang, Yun-Woo
  • Ryu, Jung Kyu
  • An, Jin Kyung
  • Choi, Nami
  • Park, Young Mi
  • 외 2명
Citations

WEB OF SCIENCE

66
Citations

SCOPUS

77

초록

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 parts per thousand]) compared to those without AI (n = 123 [5.01 parts per thousand]; 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).

키워드

PERFORMANCEBENEFITSHARMS
제목
Artificial intelligence for breast cancer screening in mammography (AI-STREAM): preliminary analysis of a prospective multicenter cohort study
저자
Chang, Yun-WooRyu, Jung KyuAn, Jin KyungChoi, NamiPark, Young MiKo, Kyung HeeHan, Kyunghwa
DOI
10.1038/s41467-025-57469-3
발행일
2025-03
유형
Article
저널명
Nature Communications
16
1