A large study found that AI-based computer-aided detection (AI-CAD) can improve breast cancer detection and support radiologists in screening mammography.
Key Details
- 1The study analyzed data from 24,543 women undergoing screening mammography between 2021 and 2022.
- 2AI-CAD (Lunit Insight Mammography v1.1.7.1) achieved a sensitivity of 89.9% and specificity of 94.3%.
- 3The positive predictive value of recall (PPV1) was 8.7%, slightly above BI-RADS benchmarks.
- 4AI-CAD found 3.4% of cancers missed by radiologists, but missed 8.1% detected by radiologists.
- 5AI-CAD false negatives were more common in women with dense breast tissue, with an overall false negative rate of 10.1%.
- 6AI-CAD does not incorporate prior mammograms unlike human readers.
Why It Matters
These results affirm that AI-CAD can enhance radiologists' performance in breast cancer screening, potentially improving early detection rates. Understanding strengths and limitations of AI-CAD helps guide its integration into clinical workflows, especially considering variable performance in dense breast tissue.
Source
AuntMinnie
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