Mammographic classification of interval breast cancers and artificial intelligence performance.

ABSTRACT:

Background

European studies suggest that artificial intelligence (AI) can reduce interval breast cancers. Research on interval breast cancer classification and AI's effectiveness in the United States, however, particularly using digital breast tomosynthesis and annual screening, is limited. We aimed to mammographically classify interval breast cancers and assess AI performance using a 12-month screening interval.

Methods

From digital mammography and digital breast tomosynthesis screening mammograms acquired between 2010 and 2019 at a US tertiary-care academic center, we identified interval breast cancers diagnosed less than 12 months after a negative mammogram. At least 3 breast radiologists retrospectively classified interval breast cancers as missed-reading error, minimal

SUBMITTER: Yu TT 

PROVIDER: S-EPMC12342771 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature