Evaluation of breast cancer with a computer-aided detection system by mammographic appearance and histopathology.

Background: The objective of this study was to evaluate the performance of a computer-aided detection (CAD) system for the detection of breast cancer, based on mammographic appearance and histopathology.

Methods: From 1000 consecutive screening mammograms from women with biopsy-proven breast carcinoma, 273 mammograms were selected randomly for retrospective evaluation by CAD. The sensitivity of the CAD system for breast cancer was assessed from the proportion of masses and microcalcifications detected.

A computer-aided detection system for the evaluation of breast cancer by mammographic appearance and lesion size.

Objective: The purpose of our study was to evaluate the performance of a computer-aided detection (CAD) system in the detection of breast cancer based on mammographic appearance and lesion size.

Conclusion: The CAD system correctly marked most biopsy-proven breast cancers, with a greater sensitivity for microcalcification than for mass lesions but with no significant difference in performance based on cancer size. CAD was highly effective in detecting even the smallest lesions, with a sensitivity of 92% for lesions of 5 mm or less.

Determining efficacy of mammographic CAD systems.

Computer-aided detection (CAD) system sensitivity estimates without a radiologist in the loop are straightforward to measure but are extremely data dependent. The only relevant performance metric is improvement in CAD-assisted radiologist sensitivity. Unfortunately, this is difficult to accurately assess.