Performance Benchmarks for Screening Breast MR Imaging in Community Practice.

Purpose To compare screening magnetic resonance (MR) imaging performance in the Breast Cancer Surveillance Consortium (BCSC) with Breast Imaging Reporting and Data System (BI-RADS) benchmarks. Materials and Methods This study was approved by the institutional review board and compliant with HIPAA and included BCSC screening MR examinations collected between 2005 and 2013 from 5343 women (8387 MR examinations) linked to regional Surveillance, Epidemiology, and End Results program registries, state tumor registries, and pathologic information databases that identified breast cancer cases and tumor characteristics. Clinical, demographic, and imaging characteristics were assessed. Performance measures were calculated according to BI-RADS fifth edition and included cancer detection rate (CDR), positive predictive value of biopsy recommendation (PPV2), sensitivity, and specificity. Results The median patient age was 52 years; 52% of MR examinations were performed in women with a first-degree family history of breast cancer, 46% in women with a personal history of breast cancer, and 15% in women with both risk factors. Screening MR imaging depicted 146 cancers, and 35 interval cancers were identified (181 total-54 in situ, 125 invasive, and two status unknown). The CDR was 17 per 1000 screening examinations (95% confidence interval [CI]: 15, 20 per 1000 screening examinations; BI-RADS benchmark, 20-30 per 1000 screening examinations). PPV2 was 19% (95% CI: 16%, 22%; benchmark, 15%). Sensitivity was 81% (95% CI: 75%, 86%; benchmark, >80%), and specificity was 83% (95% CI: 82%, 84%; benchmark, 85%-90%). The median tumor size of invasive cancers was 10 mm; 88% were node negative. Conclusion The interpretative performance of screening MR imaging in the BCSC meets most BI-RADS benchmarks and approaches benchmark levels for remaining measures. Clinical practice performance data can inform ongoing benchmark development and help identify areas for quality improvement. © RSNA, 2017.