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National Performance Benchmarks for Screening Digital Breast Tomosynthesis: Update from the Breast Cancer
Christoph I Lee1, Linn Abraham1, Diana L Miglioretti1
1From the Department of Radiology, University of Washington School of Medicine, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson Cancer Center, 825 Eastlake Ave E, LG-200, Seattle, WA 98109 (C.I.L., J.M.L.); Department of Health Systems & Population Health, University of Washington School of Public Health, Seattle, Wash (C.I.L.); Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Wash (C.I.L., L.A., D.L.M., J.M.L., E.J.A.B.); Division of Biostatistics, Department of Public Health Sciences, University of California Davis School of Medicine, Davis, Calif (D.L.M.); Department of Population Health Sciences, and the Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (T.O.); Department of Medicine, Department of Epidemiology and Biostatistics, and General Internal Medicine Section, Department of Veterans Affairs, University of California, San Francisco, San Francisco, Calif (K.K.); Department of Surgery, Office of Health Promotion Research, Larner College of Medicine at the University of Vermont and University of Vermont Cancer Center, Burlington, Vt (B.L.S.); The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon, NH (A.N.A.T.); Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, Chicago, Ill (G.H.R.); Department of Radiology, Geisel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.A.); and Department of Radiology, University of North Carolina, Chapel Hill, NC (L.M.H.).
Abstract:
Background It is important to establish screening mammography performance benchmarks for quality improvement efforts. Purpose To establish performance benchmarks for digital breast tomosynthesis (DBT) screening and evaluate performance trends over time in U.S. community practice. Materials and Methods In this retrospective study, DBT screening examinations were collected from five Breast Cancer Surveillance Consortium (BCSC) registries between 2011 and 2018. Performance measures included abnormal interpretation rate (AIR), cancer detection rate (CDR), sensitivity, specificity, and false-negative rate (FNR) and were calculated based on the American College of Radiology Breast Imaging Reporting and Data System, fifth edition, and compared with concurrent BCSC DM screening examinations, previously published BCSC and National Mammography Database benchmarks, and expert opinion acceptable performance ranges. Benchmarks were derived from the distribution of performance measures across radiologists (n = 84 or n = 73 depending on metric) and were presented as percentiles. Results A total of 896 101 women undergoing 2 301 766 screening examinations (458 175 DBT examinations [median age, 58 years; age range, 18-111 years] and 1 843 591 DM examinations [median age, 58 years; age range, 18-109 years]) were included in this study. DBT screening performance measures were as follows: AIR, 8.3% (95% CI: 7.5, 9.3); CDR per 1000 screens, 5.8 (95% CI: 5.4, 6.1); sensitivity, 87.4% (95% CI: 85.2, 89.4); specificity, 92.2% (95% CI: 91.3, 93.0); and FNR per 1000 screens, 0.8 (95% CI: 0.7, 1.0). When compared with BCSC DM screening examinations from the same time period and previously published BCSC and National Mammography Database performance benchmarks, all performance measures were higher for DBT except sensitivity and FNR, which were similar to concurrent and prior DM performance measures. The following proportions of radiologists achieved acceptable performance ranges with DBT: 97.6% for CDR, 91.8% for sensitivity, 75.0% for AIR, and 74.0% for specificity. Conclusion In U.S. community practice, large proportions of radiologists met acceptable performance ranges for screening performance metrics with DBT. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Lee and Moy in this issue.
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