Literature DB >> 17114541

Prospective assessment of computer-aided detection in interpretation of screening mammography.

Justin M Ko1, Michael J Nicholas, Jeffrey B Mendel, Priscilla J Slanetz.   

Abstract

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.

Entities:  

Mesh:

Year:  2006        PMID: 17114541     DOI: 10.2214/AJR.05.1582

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  27 in total

1.  An interactive system for computer-aided diagnosis of breast masses.

Authors:  Xingwei Wang; Lihua Li; Wei Liu; Weidong Xu; Dror Lederman; Bin Zheng
Journal:  J Digit Imaging       Date:  2012-10       Impact factor: 4.056

2.  Interactive computer-aided diagnosis of breast masses: computerized selection of visually similar image sets from a reference library.

Authors:  Bin Zheng; Claudia Mello-Thoms; Xiao-Hui Wang; Gordon S Abrams; Jules H Sumkin; Denise M Chough; Marie A Ganott; Amy Lu; David Gur
Journal:  Acad Radiol       Date:  2007-08       Impact factor: 3.173

Review 3.  [Current situation and future perspectives of digital mammography].

Authors:  R Schulz-Wendtland; K-P Hermann; T Wacker; W Bautz
Journal:  Radiologe       Date:  2008-04       Impact factor: 0.635

4.  Optimization of reference library used in content-based medical image retrieval scheme.

Authors:  Sang Cheol Park; Rahul Sukthankar; Lily Mummert; Mahadev Satyanarayanan; Bin Zheng
Journal:  Med Phys       Date:  2007-11       Impact factor: 4.071

Review 5.  Noncalcified lung nodules: volumetric assessment with thoracic CT.

Authors:  Marios A Gavrielides; Lisa M Kinnard; Kyle J Myers; Nicholas Petrick
Journal:  Radiology       Date:  2009-04       Impact factor: 11.105

Review 6.  Anniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM.

Authors:  Maryellen L Giger; Heang-Ping Chan; John Boone
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

7.  False positive marks on unsuspicious screening mammography with computer-aided detection.

Authors:  Mary C Mahoney; Karthikeyan Meganathan
Journal:  J Digit Imaging       Date:  2011-10       Impact factor: 4.056

8.  Longitudinal disease detection rates for the evaluation of disease detection technologies with application in high-risk breast cancer screening.

Authors:  Jacob Levman
Journal:  J Clin Diagn Res       Date:  2013-10-22

9.  "CADEAT": considerations on the use of CAD (computer-aided diagnosis) in mammography.

Authors:  R Chersevani; S Ciatto; C Del Favero; A Frigerio; L Giordano; G Giuseppetti; C Naldoni; P Panizza; M Petrella; G Saguatti
Journal:  Radiol Med       Date:  2010-01-15       Impact factor: 3.469

10.  Computer-assisted diagnosis (CAD) in mammography: comparison of diagnostic accuracy of a new algorithm (Cyclopus, Medicad) with two commercial systems.

Authors:  S Ciatto; D Cascio; F Fauci; R Magro; G Raso; R Ienzi; F Martinelli; M Vasile Simone
Journal:  Radiol Med       Date:  2009-05-14       Impact factor: 3.469

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.