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Accuracy of Radiologists Interpretation of Mammographic Breast Density
S Vedantham1, L Shi1, A Karellas1*, A O'Connell2, (1) University of Massachusetts Medical School, Worcester, MA, (2) University of Rochester Medical Center, Rochester, NY
Presentations
MO-FG-CAMPUS-I-1 (Monday, July 13, 2015) 4:30 PM - 5:00 PM Room: Exhibit Hall
Purpose: Several commercial and non-commercial software and techniques are available for determining breast density from mammograms. However, where mandated by law the breast density information communicated to the subject/patient is based on radiologist’s interpretation of breast density from mammograms. Several studies have reported on the concordance among radiologists in interpreting mammographic breast density. In this work, we investigated the accuracy of radiologist’s interpretation of breast density.
Methods: Volumetric breast density (VBD) determined from 134 unilateral dedicated breast CT scans from 134 subjects was considered the truth. An MQSA-qualified study radiologist with more than 20 years of breast imaging experience reviewed the DICOM “for presentation” standard 2-view mammograms of the corresponding breasts and assigned BIRADS breast density categories. For statistical analysis, the breast density categories were dichotomized in two ways; fatty vs. dense breasts where “fatty” corresponds to BIRADS breast density categories A/B, and “dense” corresponds to BIRADS breast density categories C/D, and extremely dense vs. fatty to heterogeneously dense breasts, where extremely dense corresponds to BIRADS breast density category D and BIRADS breast density categories A through C were grouped as fatty to heterogeneously dense breasts. Logistic regression models (SAS 9.3) were used to determine the association between radiologist’s interpretation of breast density and VBD from breast CT, from which the area under the ROC (AUC) was determined.
Results: Both logistic regression models were statistically significant (Likelihood Ratio test, p<0.0001). The accuracy (AUC) of the study radiologist for classification of fatty vs. dense breasts was 88.4% (95% CI: 83-94%) and for classification of extremely dense breast was 94.3% (95% CI: 90-98%).
Conclusion: The accuracy of the radiologist in classifying dense and extremely dense breasts is high. Considering the variability in VBD estimates from commercial software, the breast density information communicated to the patient should be based on radiologist’s interpretation.
Funding Support, Disclosures, and Conflict of Interest: This work was supported in part by NIH R21 CA176470 and R21 CA134128. The contents are solely the responsibility of the authors and do not reflect the official views of the NIH or NCI.
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