Accuracy and interpretation time of computer-aided detection among novice and experienced breast MRI readers

American Journal of Roentgenology

Volumn 200, Issue 6, 2013, Pages

  Lehman, Constance D ^a,b   Blume, Jeffrey D ^c   DeMartini, Wendy B ^a,b   Hylton, Nola M ^d   Herman, Benjamin ^e   Schnall, Mitchell D ^f  

^a UNIVERSITY OF WASHINGTON SCHOOL OF MEDICINE   (United States)

^b Seattle Cancer Care Alliance   (United States)

^c VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

^e BROWN UNIVERSITY   (United States)

^f HOSPITAL OF THE UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Accuracy; Breast MRI; Computer aided diagnosis; Reader study

Indexed keywords

ADULT; ARTICLE; BREAST CANCER; BREAST CARCINOMA; BREAST DISEASE; COMPUTER ASSISTED DIAGNOSIS; COMPUTER PROGRAM; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; FEMALE; HUMAN; INTERMETHOD COMPARISON; INTRADUCTAL CARCINOMA; MAJOR CLINICAL STUDY; NUCLEAR MAGNETIC RESONANCE IMAGING; PREDICTIVE VALUE; PRIORITY JOURNAL; RADIOLOGIST; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; WORK EXPERIENCE; ANALYSIS OF VARIANCE; AREA UNDER THE CURVE; BREAST TUMOR; CLINICAL COMPETENCE; COMPARATIVE STUDY; DIAGNOSTIC ERROR; DIFFERENTIAL DIAGNOSIS; METHODOLOGY; MIDDLE AGED; STATISTICS; THREE DIMENSIONAL IMAGING;

CONTRAST MEDIUM; DIAGNOSTIC AGENT;

ANALYSIS OF VARIANCE; AREA UNDER CURVE; BREAST NEOPLASMS; CLINICAL COMPETENCE; CONTRAST MEDIA; DIAGNOSIS, COMPUTER-ASSISTED; DIAGNOSIS, DIFFERENTIAL; DIAGNOSTIC ERRORS; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; MIDDLE AGED; PREDICTIVE VALUE OF TESTS; ROC CURVE; SENSITIVITY AND SPECIFICITY; SOFTWARE;

MLCS; MLOWN;

EID: 84880928029     PISSN: 0361803X     EISSN: 15463141     Source Type: Journal    
DOI: 10.2214/AJR.11.8394     Document Type: Article

References (29)

1. Saslow D, Boetes C, Burke W, et al. American Cancer Society guidelines for breast screening with MRI as an adjunct to mammography. CA Cancer J Clin 2007; 57:75-89
2. Lehman CD, Smith RA. The role of MRI in breast cancer screening. J Natl Compr Canc Netw 2009; 7:1109-1115
3. Lehman CD, DeMartini W, Anderson BO, Edge SB. Indications for breast MRI in the patient with newly diagnosed breast cancer. J Natl Compr Canc Netw 2009; 7:193-201
4. Lehman CD, Gatsonis C, Kuhl CK, et al. MRI evaluation of the contralateral breast in women with recently diagnosed breast cancer. N Engl J Med 2007; 356:1295-1303
5. Lehman CD, Blume JD, Weatherall P, et al. Screening women at high risk for breast cancer with mammography and magnetic resonance imaging. Cancer 2005; 103:1898-1905
6. Fischer U, Kopka L, Brinck U, Korabiowska M, Schauer A, Grabbe E. Prognostic value of contrast-enhanced MR mammography in patients with breast cancer. Eur Radiol 1997; 7:1002-1005
7. Lee SG, Orel SG, Woo IJ, et al. MR imaging screening of the contralateral breast in patients with newly diagnosed breast cancer: preliminary results. Radiology 2003; 226:773-778
8. Liberman L, Morris EA, Dershaw DD, Abramson AF, Tan LK. MR imaging of the ipsilateral breast in women with percutaneously proven breast cancer. AJR 2003; 180:901-910
9. Liberman L, Morris EA, Kim CM, et al. MR imaging findings in the contralateral breast of women with recently diagnosed breast cancer. AJR 2003; 180:333-341
10. Schnall MD, Blume J, Bluemke DA, et al. MRI detection of distinct incidental cancer in women with primary breast cancer studied in IBMC 68 J Surg Oncol 2005; 92:32-38
11. Obuchowski NA. Multireader, multimodality receiver operating characteristic curve studies: hypothesis testing and sample size estimation using an analysis of variance approach with dependent observations. Acad Radiol 1995; 2(suppl 1):S22-S29
12. Obuchowski NA. Computing sample size for receiver operating characteristic studies. Invest Radiol 1994; 29:238-243
13. Obuchowski NA. Sample size calculations in studies of test accuracy. Stat Methods Med Res 1998; 7:371-392
14. Obuchowski NA, McClish DK. Sample size determination for diagnostic accuracy studies involving binormal ROC curve indices. Stat Med 1997; 16:1529-1542
15. Blume JD. Bounding sample size projections for the area under a ROC curve. J Stat Plan Inference 2009; 139:711-721
16. Schnall MD, Blume J, Bluemke DA, et al. Diagnostic architectural and dynamic features at breast MR imaging: multicenter study. Radiology 2006; 238:42-53
17. Leisenring W, Alonzo T, Pepe MS. Comparisons of predictive values of binary medical diagnostic tests for paired designs. Biometrics 2000; 56:345-351
18. Pepe MS. The statistical evaluation of medical tests for classification and prediction. New York, NY: Oxford University Press, 2003
19. Zhou XH, Obuchowski NA, McClish DK. Statistical methods in diagnostic medicine. New York, NY: Wiley, 2002
20. Metz CE, Herman BA, Roe CA. Statistical comparison of two ROC-curve estimates obtained from partially-paired datasets. Med Decis Making 1998; 18:110-121
21. Metz CE, Herman BA, Shen JH. Maximum likelihood estimation of receiver operating characteristic (ROC) curves from continuously-distributed data. Stat Med 1998; 17:1033-1053
22. Obuchowski NA, Rockette HE. Hypothesis testing of diagnostic accuracy for multiple readers and multiple tests: an ANOVA approach with dependent observations. Commun Stat Simul Comput 1995; 24:285-308
23. Diggle PJ Liang KY, Zeger SL. Analysis of longitudinal data. New York, NY: Oxford University Press, 1994
24. Lehman CD, Peacock S, DeMartini WB, Chen X. A new automated software system to evaluate breast MR examinations: improved specificity without decreased sensitivity. AJR 2006; 187:51-56
25. Williams TC, DeMartini WB, Partridge SC, Peacock S, Lehman CD. Breast MR imaging: computer-aided evaluation program for discriminating benign from malignant lesions. Radiology 2007; 244:94-103
26. Wang LC, DeMartini WB, Partridge SC, Peacock S, Lehman CD. MRI-detected suspicious breast lesions: predictive values of kinetic features measured by computer-aided evaluation. AJR 2009; 193:826-831
27. Meeuwis C, van de Ven SM, Stapper G, et al. Computer-aided detection (CAD) for breast MRI: evaluation of efficacy at 3.0 T. Eur Radiol 2010; 20:522-528
28. Arazi-Kleinman T, Causer PA, Jong RA, Hill K, Warner E. Can breast MRI computer-aided detection (CAD) improve radiologist accuracy for lesions detected at MRI screening and recommended for biopsy in a high-risk population? Clin Radiol 2009; 64:1166-1174
29. Shimauchi A, Giger ML, Bhooshan N, et al. Evaluation of clinical breast MR imaging performed with prototype computer-aided diagnosis breast MR imaging workstation: reader study. Radiology 2011; 258:696-704