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Prospective Assessment of Computer-Aided Detection in Interpretation of Screening Mammography

¹ Department of Radiology, Caritas St. Elizabeth's Medical Center and Tufts University School of Medicine, Boston, MA.
² Present address: Department of Radiology, Hospital of Saint Raphael, New Haven, CT.
³ Present address: Department of Radiology, Boston University School of Medicine, Boston Medical Center, 88 East Newton St., Boston, MA 02118.

OBJECTIVE. The purpose of this study was to prospectively assess the usefulness of computer-aided detection (CAD) in the interpretation of screening mammography and to provide the true sensitivity and specificity of this technique in a clinical setting.

SUBJECTS AND METHODS. Over a 26-month period, 5,016 screening mammograms were interpreted without, and subsequently with, the assistance of the iCAD MammoReader detection system. Data collected for actionable findings included dominant feature (calcification, mass, asymmetry, architectural distortion), detection method (radiologist only, CAD only, or both radiologist and CAD), BI-RADS assessment code, associated histopathology for those undergoing biopsy, and tumor stage for malignant lesions. The study population was cross-checked against an independent reference standard to identify false-negative cases.

RESULTS. Of the 5,016 cases, the recall rate increased from 12% to 14% with the addition of CAD. Of the 107 (2%) patients who underwent biopsy, 101 (94%) were prompted by the radiologist and six (6%) were prompted by CAD. Of the 124 biopsies performed on actionable findings in the 107 patients, findings in 79 (64%) were benign and in 45 (36%) were in situ or invasive carcinoma. Three study participants who were not recalled by the radiologist with the assistance of CAD developed cancer within 1 year of the screening mammogram and were considered to be false-negative cases. The radiologist detected 43 (90%) of the 48 total malignancies and 45 (94%) of the 48 malignancies with the assistance of CAD. CAD missed eight cancers that were detected by the radiologist, which presented as architectural distortions (n = 3), irregular masses (n = 4), and a circumscribed mass (n = 1). CAD detected two in situ cancers as a faint cluster of calcifications that had not been perceived by the radiologist and one mass that was dismissed by the radiologist, accounting for at least a 4.7% increase in cancer detection rate. Sensitivity of screening mammography with the use of CAD (94%) represented an absolute and relative 4% increase over the sensitivity of the radiologist alone (90%). Specificity of screening mammography with and without the use of CAD was 99%.

CONCLUSION. Routine use of CAD while interpreting screening mammograms significantly increases recall rates, has no significant effect on positive predictive value for biopsy, and can increase cancer detection rate by at least 4.7% and sensitivity by at least 4%. This study provides "true" values for sensitivity and specificity for use of CAD in interpretation of screening mammography as measured prospectively in the context of a working clinical setting.

Keywords: breast cancer • computer-aided detection • mammography • screening

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