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.
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.
Authors: Joshua J Fenton; Linn Abraham; Stephen H Taplin; Berta M Geller; Patricia A Carney; Carl D'Orsi; Joann G Elmore; William E Barlow Journal: J Natl Cancer Inst Date: 2011-07-27 Impact factor: 13.506
Authors: Cary P Gross; Jessica B Long; Joseph S Ross; Maysa M Abu-Khalaf; Rong Wang; Brigid K Killelea; Heather T Gold; Anees B Chagpar; Xiaomei Ma Journal: JAMA Intern Med Date: 2013-02-11 Impact factor: 21.873
Authors: Kendra A Batchelder; Aaron B Tanenbaum; Seth Albert; Lyne Guimond; Pierre Kestener; Alain Arneodo; Andre Khalil Journal: PLoS One Date: 2014-09-15 Impact factor: 3.240