A Simulation Screening Mammography Module Created for Instruction and Assessment: Radiology Residents vs National Benchmarks

Jeffrey D. Poot, Alison L. Chetlen

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

Rationale and Objectives To improve mammographic screening training and breast cancer detection, radiology residents participated in a simulation screening mammography module in which they interpreted an enriched set of screening mammograms with known outcomes. This pilot research study evaluates the effectiveness of the simulation module while tracking the progress, efficiency, and accuracy of radiology resident interpretations and also compares their performance against national benchmarks. Materials and Methods A simulation module was created with 266 digital screening mammograms enriched with high-risk breast lesions (seven cases) and breast malignancies (65 cases). Over a period of 27 months, 39 radiology residents participated in the simulation screening mammography module. Resident sensitivity and specificity were compared to Breast Cancer Surveillance Consortium (BCSC data through 2009) national benchmark and American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) acceptable screening mammography audit ranges. Results The sensitivity, the percentage of cancers with an abnormal initial interpretation (BI-RADS 0), among residents was 84.5%, similar to the BCSC benchmark sensitivity of 84.9% (sensitivity for tissue diagnosis of cancer within 1 year following the initial examination) and within the acceptable ACR BI-RADS medical audit range of ≥75%. The specificity, the percentage of noncancers that had a negative image interpretation (BI-RADS 1 or 2), among residents was 83.2% compared to 90.3% reported in the BCSC benchmark data, but lower than the suggested ACR BI-RADS range of 88%–95%. Conclusions Using simulation modules for interpretation of screening mammograms is a promising method for training radiology residents to detect breast cancer and to help them achieve competence toward national benchmarks.

Original languageEnglish (US)
Pages (from-to)1454-1462
Number of pages9
JournalAcademic Radiology
Volume23
Issue number11
DOIs
Publication statusPublished - Nov 1 2016

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All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

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