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Computer-aided detection mammography for breast cancer screening: systematic review and meta-analysis

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Archives of Gynecology and Obstetrics Aims and scope Submit manuscript

Abstract

Context

Mammography is generally accepted as the best available breast cancer screening method; however, some cancers detectable on mammography images are missed. Computer-aided detection (CAD) systems for mammography are intended to reduce false negatives by marking suspicious areas of the mammograms for reviewers to consider. Although the prospect of improving the sensitivity of screening mammograms has led to the diffusion of CAD for mammography, little is known about its diagnostic accuracy.

Objective

To assess the diagnostic performance of CAD for screening mammography in terms of sensitivity and specificity and incremental recall, biopsy, and cancer diagnosis rates.

Data sources

Published literature identified by systematic literature searches of 17 databases, including MEDLINE, EMBASE, and the Cochrane Library, searched through 25 September 2008.

Study selection

A reviewer and an information specialist selected full-length English-language articles that enrolled asymptomatic women for routine breast cancer screening and provided data needed for our analyses using criteria established a priori. We identified 75 potentially relevant publications, of which 7 (9%) were included.

Data extraction

Data were extracted and internal validity was assessed by a single review author, and forms were approved by the co-authors.

Results

Three studies (n = 347,324) reported sensitivity and specificity, or data to calculate them, and five studies (n = 51,162) reported data to calculate incremental rates of cancer diagnoses and recall and biopsy of women who did not have breast cancer. The pooled sensitivity was 86.0% (95% CI 84.2–87.6%) and specificity was 88.2% (95% CI 88.1–88.3%). Of the 100,000 women screened, CAD yielded an additional 50 (95% CI 30–80) correct breast cancer diagnoses, 1,190 (95% CI 1,090–1,290) recalls of healthy women, and 80 (95% CI 60–100) biopsies of healthy women. A total of 96% (95% CI 93.9–97.3%) of women recalled based upon CAD and 65.1% (95% CI 52.3–76.0%) of women biopsied based upon CAD were healthy. No studies reported patient-oriented clinical outcomes.

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Acknowledgments

We thank the following individuals for helpful comments at various stages of the review process: Mark Robson, MD, Christopher H. Schmid, Ph.D., and Jonathan R. Treadwell, Ph.D. We also thank Eileen Erinoff for devising and performing literature searches and Helen Dunn and Tracey Monastero-Stem for organizing the retrieval and citation of articles. This work was entirely funded by ECRI Institute, an independent not-for-profit health research organization.

Conflict of interest statement

We declare that we have no conflicts of interest.

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Authors and Affiliations

  1. ECRI Institute, Evidence-based Practice Center and Health Technology Assessment Group, 5200 Butler Pike, Plymouth Meeting, 19462, USA

    Meredith Noble, Wendy Bruening, Stacey Uhl & Karen Schoelles

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  1. Meredith Noble
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  2. Wendy Bruening
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  3. Stacey Uhl
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  4. Karen Schoelles
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Correspondence to Meredith Noble.

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Noble, M., Bruening, W., Uhl, S. et al. Computer-aided detection mammography for breast cancer screening: systematic review and meta-analysis. Arch Gynecol Obstet 279, 881–890 (2009). https://doi.org/10.1007/s00404-008-0841-y

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  • DOI: https://doi.org/10.1007/s00404-008-0841-y

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