Screening Mammography with Computer-aided Detection: Prospective Study of 12,860 Patients in a Community Breast Center

Freer, Timothy W.; Ulissey, Michael J.

doi:10.1148/radiol.2203001282

Cited by 722 publications

(446 citation statements)

References 13 publications

Supporting

Mentioning

387

Contrasting

Unclassified

Order By: Relevance

“…Eligible studies were identified for ultrasound (Kolb et al, 1998;Buchberger et al, 1999;O'Driscol et al, 2001;Warner et al, 2001;Hou et al, 2002) magnetic resonance imaging (MRI) (Kuhl et al, 2000;Tilanus-Linthorst et al, 2000a, b;Stoutjesdijk et al, 2001;Warner et al, 2001), CAD (te Brake et al, 1998; Burhenne et al, 2000;Birdwell et al, 2001;Freer and Ulissey, 2001), and full-field digital mammography (FFDM) (Lewin et al, 2001(Lewin et al, , 2002. For ultrasound, MRI, and CAD, findings are summarised in Tables 1 -3.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

New technologies in screening for breast cancer: a systematic review of their accuracy

2004

View full text Add to dashboard Cite

We systematically reviewed the literature on the accuracy of new technologies proposed for breast cancer screening. Four potential tests were identified (ultrasound, magnetic resonance imaging (MRI), full-field digital mammography (FFDM), and computer-aided detection (CAD)) for which primary studies met quality and applicability criteria and provided adequate data on test accuracy. These technologies have been assessed in cross-sectional studies of test accuracy where the new test is compared to mammography. Ultrasound, used as an adjunct to mammography in women with radiologically dense breasts, detects additional cancers and causes additional false positives. Magnetic resonance imaging may have a better sensitivity (but lower specificity) than mammography in selected high-risk women, but studies of this technology included small number of cancers. Computer-aided detection may enhance the sensitivity of mammography and warrants further evaluation in large prospective trials. One study of FFDM suggests that it may identify some cancers not identified on conventional mammography and may result in a lower recall rate. The evidence is currently insufficient to support the use of any of these new technologies in population screening, but would support further evaluation. British Journal of Cancer (2004) Despite recent controversy surrounding the efficacy of mammographic screening, it remains the only screening test for breast cancer that has been extensively evaluated in randomised controlled trials (RCTs) and shown to reduce breast cancer mortality (IARC, 2002;Nystrom et al, 2002). Since evidence exists that early detection reduces mortality from breast cancer, it is reasonable to evaluate a new screening test by assessing its effect on early detection of breast cancer. While RCTs examining mortality as an outcome are the gold standard, studies assessing new tests are commonly evaluated using surrogate measures as indicators of early breast cancer detection. These surrogate measures may be measurable at the time of screening or require follow-up. Immediate indicators include the cancer detection rate and the size, stage, and nodal status of cancers detected. The measure requiring follow-up is the interval cancer rate. Ascertainment of interval breast cancers poses a number of challenges that include identification (requiring linkage to cancer registries), standardisation, and validation of review and categorisation methods, as well as access to the films taken at diagnosis. Assessing whether tests differ in their interval cancer rate is best assessed by randomising people to the different tests. In designs in which women are assessed by both tests, women in whom cancers are detected by either test would obviously be identified and treated; interval cancers that arise thereafter would be those missed by both tests. To assess whether interval cancer rates differ between the tests is therefore best assessed by randomising women to the different tests. However, all of the immediately measurable surrogates can be asses...

show abstract

Section: Resultsmentioning

confidence: 99%

“…CAD (Table 3) has been assessed in several studies with over 650 cancers. However, only one of these studies was prospectively conducted (Freer and Ulissey, 2001). All of the studies examined the incremental value of CAD and showed improved sensitivity; the evidence on specificity is conflicting.…”

Section: Resultsmentioning

confidence: 99%

New technologies in screening for breast cancer: a systematic review of their accuracy

2004

View full text Add to dashboard Cite

show abstract

“…Many studies have validated CAD techniques in screening populations and found a sensitivity ranging from 73 [2] to 96% [3]. Moreover, the impact of a CAD system on the performance of mammogram observers was evaluated in several studies [2,[4][5][6][7][8][9][10][11][12][13][14], showing that there is insufficient evidence to claim that CAD improves cancer detection rates but that it does increase recall rates in screening programs for breast cancer [15].…”

Section: Introductionmentioning

confidence: 99%

Computer-aided detection in full-field digital mammography in a clinical population: performance of radiologist and technologists

Biggelaar

Kessels

Engelshoven

et al. 2009

Breast Cancer Res Treat

View full text Add to dashboard Cite

The purpose of the study was to evaluate the impact of a computer-aided detection (CAD) system on the performance of mammogram readers in interpreting digital mammograms in a clinical population. Furthermore, the ability of a CAD system to detect breast cancer in digital mammography was studied in comparison to the performance of radiologists and technologists as mammogram readers. Digital mammograms of 1,048 consecutive patients were evaluated by a radiologist and three technologists. Abnormalities were recorded and an imaging conclusion was given as a BI-RADS score before and after CAD analysis. Pathology results during 12 months follow up were used as a reference standard for breast cancer. Fifty-one malignancies were found in 50 patients. Sensitivity and specificity were computed before and after CAD analysis and provided with 95% CIs. In order to assess the detection rate of malignancies by CAD and the observers, the pathological locations of these 51 breast cancers were matched with the locations of the CAD marks and the mammographic locations that were considered to be suspicious by the observers. For all observers, the sensitivity rates did not change after application of CAD. A mean sensitivity of 92% was found for all technologists and 84% for the radiologist. For two technologists, the specificity decreased (from 84 to 83% and from 77 to 75%). For the radiologist and one technologist, the application of CAD did not have any impact on the specificity rates (95 and 83%, respectively). CAD detected 78% of all malignancies. Five malignancies were indicated by CAD without being noticed as suspicious by the observers. In conclusion, the results show that systematic application of CAD in a clinical patient population failed to improve the overall sensitivity of mammogram interpretation by the readers and was associated with an increase in false-positive results. However, CAD marked five malignancies that were missed by the different readers.

show abstract

“…While studies have showed that using CAD helped radiologists detect more cancers associated with microcalcification clusters [13,14], current CAD has no or little impact in helping radiologists detecting more subtle cancers associated with mass-like abnormalities [15,16]. Studies have shown that due to the inability to explain the reasoning of the CAD decision making (the "black-box" type approach) and the higher falsepositive cueing rates, radiologists in general had very low confidence in accepting or considering CAD-cued mass-like abnormalities [17].…”

Section: Introductionmentioning

confidence: 99%

An Interactive System for Computer-Aided Diagnosis of Breast Masses

Wang

Liu

et al. 2012

J Digit Imaging

View full text Add to dashboard Cite

Although mammography is the only clinically accepted imaging modality for screening the general population to detect breast cancer, interpreting mammograms is difficult with lower sensitivity and specificity. To provide radiologists "a visual aid" in interpreting mammograms, we developed and tested an interactive system for computeraided detection and diagnosis (CAD) of mass-like cancers. Using this system, an observer can view CAD-cued mass regions depicted on one image and then query any suspicious regions (either cued or not cued by CAD). CAD scheme automatically segments the suspicious region or accepts manually defined region and computes a set of image features. Using content-based image retrieval (CBIR) algorithm, CAD searches for a set of reference images depicting "abnormalities" similar to the queried region. Based on image retrieval results and a decision algorithm, a classification score is assigned to the queried region. In this study, a reference database with 1,800 malignant mass regions and 1,800 benign and CAD-generated false-positive regions was used. A modified CBIR algorithm with a new function of stretching the attributes in the multi-dimensional space and decision scheme was optimized using a genetic algorithm. Using a leave-one-out testing method to classify suspicious mass regions, we compared the classification performance using two CBIR algorithms with either equally weighted or optimally stretched attributes. Using the modified CBIR algorithm, the area under receiver operating characteristic curve was significantly increased from 0.865 ±0.006 to 0.897±0.005 (p<0.001). This study demonstrated the feasibility of developing an interactive CAD system with a large reference database and achieving improved performance.

show abstract

Screening Mammography with Computer-aided Detection: Prospective Study of 12,860 Patients in a Community Breast Center

Abstract: The use of CAD in the interpretation of screening mammograms can increase the detection of early-stage malignancies without undue effect on the recall rate or positive predictive value for biopsy.

Cited by 722 publications

References 13 publications

New technologies in screening for breast cancer: a systematic review of their accuracy

New technologies in screening for breast cancer: a systematic review of their accuracy

Computer-aided detection in full-field digital mammography in a clinical population: performance of radiologist and technologists

An Interactive System for Computer-Aided Diagnosis of Breast Masses

Contact Info

Product

Resources

About