Potential Effect of Different Radiologist Reporting Methods on Studies Showing Benefit of CAD

Academic Radiology

Volumn 15, Issue 2, 2008, Pages 139-152

  Horsch, Karla ^a   Giger, Maryellen L ^a   Metz, Charles E ^a  

^a UNIVERSITY OF CHICAGO   (United States)

Author keywords

breast; Computer aided diagnosis; mammography; ROC curves; ultrasound

Indexed keywords

ARTICLE; BENIGN TUMOR; BREAST CANCER; COMPUTER ASSISTED DIAGNOSIS; ECHOMAMMOGRAPHY; MALIGNANT NEOPLASTIC DISEASE; MAMMOGRAPHY; METHODOLOGY; PRIORITY JOURNAL; PROBABILITY; RADIOLOGIST; RATING SCALE; RECEIVER OPERATING CHARACTERISTIC; REPORTING METHOD; SENSITIVITY AND SPECIFICITY; STATISTICAL SIGNIFICANCE; STUDENT T TEST; TUMOR BIOPSY;

AREA UNDER CURVE; BIOPSY; BREAST NEOPLASMS; DIAGNOSIS, COMPUTER-ASSISTED; DOCUMENTATION; HUMANS; MAMMOGRAPHY; OBSERVER VARIATION; ROC CURVE; SENSITIVITY AND SPECIFICITY; ULTRASONOGRAPHY, MAMMARY;

EID: 38149065123     PISSN: 10766332     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.acra.2007.09.015     Document Type: Article

References (33)

1. American College of Radiology. Breast Imaging Reporting and Data System Atlas (BI-RADS Atlas) (2003), American College of Radiology, Reston, Va
2. Giger M.L., Huo Z., Kupinski M.A., et al. Computer-aided diagnosis in mammography. In: Fitzpatrick M.J., and Sonka M. (Eds). Handbook of medical imaging vol 2 (2000), SPIE Press, Bellingham, Wash 915-1004
3. Vyborny C.J., and Giger M.L. Computer vision and artificial intelligence in mammography. AJR Am J Roentgenol 162 (1994) 699-708
4. Giger M.L. CAD in diagnostic mammography and multimodality breast imaging. In: Karellas A., and Giger M.L. (Eds). RSNA categorical course in diagnostic radiology physics: physical aspects of breast imaging (2004), Radiological Society of North America, Oak Brook, Ill 205-217
5. Jiang Y. Classification of breast lesions in mammograms. In: Bankman (Ed). Handbook of medical imaging, processing and analysis (2000), Academic Press, San Diego, Calif 341-358
6. Jiang Y., Nishikawa R.M., Schmidt R.A., et al. Improving breast cancer diagnosis with computer-aided diagnosis. Acad Radiol 6 (1999) 22-33
7. Hou Z., Giger M.L., Vyborny C.J., et al. Breast cancer: effectiveness of computer-aided diagnosis-observer study with independent database of mammograms. Radiology 224 (2002) 560-588
8. Giger M.L., Huo Z., and Vyborny C.J. Results of an observer study with an intelligent mammographic workstation for CAD. In: Peitgen H.-O. (Ed). Digital mammography: IWDM 2002 (2002), Springer, Berlin 297-303
9. Hadjiiski L., Chan H.P., Sahiner B., et al. Improvement in radiologists' characterization of malignant and benign masses on serial mammograms with computer-aided diagnosis: an ROC study. Radiology 233 (2004) 255-265
10. Horsch K., Giger M.L., Vyborny C.J., et al. Performance of computer-aided diagnosis in the interpretation of lesions on breast sonography. Acad Radiol 3 (2004) 272-280
11. Horsch K., Giger M.L., Vyborny C.J., et al. Multi-modality computer-aided diagnosis for the classification of breast lesions: observer study results on an independent clinical dataset. Radiology 240 (2006) 357-368
12. Metz C. ROC methodology in radiologic imaging. Invest Radiol 21 (1986) 720-733
13. Wagner R.F. Toward a strategy for consensus development on a quantitative approach to medical imaging. Acad Radiol 13 (2007) 137-139
14. R2 Technology, Inc, ImageChecker® CT CAD Software, Professional Labeling. Website of US Food and Drug Administration. http://www.fda.gov/cdrh/PDF3/p030012.html Accessed 2007
15. Rockette H.E., Gur D., and Metz C.E. The use of continuous and discrete confidence judgments in receiver operating characteristic studies of diagnostic imaging techniques. Invest Radiol 27 (1992) 169-172
16. King J.L., Bitton C.A., Gur D., et al. On the validity of the continuous and discrete confidence rating scales in receiver operating characteristic studies. Invest Radiol 28 (1993) 962-963
17. Wagner R.F., Beiden S.V., and Metz C.E. Continuous versus categorical data for ROC analysis: some quantitative considerations. Acad Radiol 8 (2001) 328-334
18. Hadjiiski L., Chan H.P., Sahiner B., et al. Quasi-continuous and discrete confidence rating scales for observer performance studies: effects on ROC analysis. Acad Radiol 17 (2007) 38-48
19. Giger M.L., Huo Z., and Lan L. Intelligent search workstation for computer aided diagnosis. In: Lemke H.U., Inamura K., Kunio D., et al. (Eds). Proceedings of Computer Assisted Radiology and Surgery (CARS) 2000 (2000), Elsevier, Philadelphia, Pa 822-827
20. Huo Z., Giger M.L., Vyborny C.J., et al. Analysis of spiculation in the computerized classification of mammographic masses. Med Phys 22 (1995) 1569-1579
21. Huo Z., Giger M.L., Vyborny C.J., et al. Automated computerized classification of malignant and benign masses on digitized mammograms. Acad Radiol 5 (1998) 155-168
22. Giger M.L., Al-Hallaq H., Huo Z., et al. Computerized analysis of lesions in US images of the breast. Acad Radiol 6 (1999) 665-674
23. Horsch K., Giger M.L., Venta L.A., et al. Automatic segmentation of breast lesions on ultrasound. Med Phys 28 (2001) 1652-1659
24. Horsch K., Giger M.L., Venta L.A., et al. Computerized diagnosis of breast lesions on ultrasound. Med Phys 29 (2002) 157-164
25. LABROC4. Website of Kurt Rossman Laboratories, Department of Radiology, University of Chicago. http://www-radiology.uchicago.edu/krl/roc_soft.htm Accessed June 10, 2004
26. Metz C.E., Herman B.A., and Shen J.-H. Maximum-likelihood estimation of ROC curves from continuously-distributed data. Statist Med 17 (1998) 1033-1053
27. PROPROC. Website of Kurt Rossman Laboratories, Department of Radiology, University of Chicago. http://www-radiology.uchicago.edu/krl/roc_soft.htm Accessed 2004
28. Metz C.E., and Pan X. "Proper" binormal ROC curves: theory and maximum-likelihood estimation. J Math Psych 43 (1999) 1-33
29. Pan X., and Metz C.E. The "proper" binormal model: parametric receiver operating characteristic curve estimation with degenerate data. Acad Radiol 4 (1997) 380-389
30. Pesce L.L., and Metz C.E. Reliable and computationally efficient maximum-likelihood estimation of "proper" binormal ROC curves. Acad Radiol 14 (2007) 814-829
31. Sahiner B., Chan H.P., Hadjiski L., et al. The effect of a multi-modality computer classifier on radiologists' accuracy in characterizing breast masses using mammograms and volumetric ultrasound images: an ROC study. Scientific Paper. RSNA (2004)
32. Metz C.E. Some practical issues of experimental-design and data-analysis in radiological ROC studies. Invest Radiol 24 (1989) 234-245
33. Wagner R.F., Metz C.E., and Campbell G. Assessment of medical imaging systems and computer aids: a tutorial review. Acad Radiol 14 (2007) 723-748