Computerized prediction of risk for developing breast cancer based on bilateral mammographic breast tissue asymmetry

Medical Engineering and Physics

Volumn 33, Issue 8, 2011, Pages 934-942

  Wang, Xingwei ^a   Lederman, Dror ^a   Tan, Jun ^a   Wang, Xiao Hui ^a   Zheng, Bin ^a  

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

Author keywords

Breast cancer; Breast tissue asymmetry; Computer aided detection; Mammography; Risk assessment

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BREAST ABNORMALITIES; BREAST CANCER; BREAST TISSUES; CLASSIFICATION PERFORMANCE; CLASSIFICATION RESULTS; CLASSIFIER PERFORMANCE; COMPUTER-AIDED DETECTION; COMPUTERIZED PREDICTION; DIGITAL MAMMOGRAPHY; FUSION METHODS; MAMMOGRAPHIC; MEDIO-LATERAL OBLIQUE VIEWS; REGIONS OF INTEREST; ROC CURVES; TEST CASE; VALIDATION METHODS; WEIGHTED AVERAGES;

DISEASES; FEATURE EXTRACTION; FORECASTING; LAKES; MAMMOGRAPHY; NEURAL NETWORKS; RATING; TISSUE;

RISK ASSESSMENT;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BREAST CANCER; BREAST EXAMINATION; CANCER RISK; CLINICAL FEATURE; COMPUTER AIDED DESIGN; CONTROLLED STUDY; DATA BASE; FEASIBILITY STUDY; GENETIC ALGORITHM; HIGH RISK POPULATION; MAMMOGRAPHY; PREDICTION; PRIORITY JOURNAL; PROCESS OPTIMIZATION; RECEIVER OPERATING CHARACTERISTIC; VALIDATION PROCESS;

ALGORITHMS; AREA UNDER CURVE; BREAST; BREAST NEOPLASMS; FEMALE; HUMANS; MAMMOGRAPHY; NEURAL NETWORKS (COMPUTER); RISK; ROC CURVE;

EID: 80051808919     PISSN: 13504533     EISSN: 18734030     Source Type: Journal    
DOI: 10.1016/j.medengphy.2011.03.001     Document Type: Article

References (40)

1. Cady B., Michaelson J.S. The life-sparing potential of mammographic screening. Cancer 2001, 91:1699-1703.
2. Sickles E.A., Wolverton D.E., Dee K.E. Performance parameters for screening and diagnostic mammography: specialist and general radiologists. Radiology 2002, 224:861-869.
3. Berlin L., Hall F.M. More mammography muddle: emotions, politics, science, costs and polarization. Radiology 2010, 255:311-316.
4. Amir E., Freedman O.C., Seruga B., Evans D.G. Assessing women at high risk of breast cancer: a review of risk assessment models. J Natl Cancer Inst 2010, 102:680-691.
5. Tice J.A., Cummings S.R., Smith-Bindman R., Ichikawa L., Barlow W.E., Kerlikowske K Using clinical factors and mammographic breast density to estimate breast cancer risk: development and validation of a new predictive model. Ann Intern Med 2008, 148:337-347.
6. McComack V.A., dos Santos Silva I. Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. Cancer Epidemiol Biomarkers Prev 2006, 15:1159-1169.
7. Mitchell G., Antoniou A.C., Warren R., Peock S., Brown J., Davies R., et al. Mammographic density and breast cancer risk in BRCA1 and BRCA2 mutation carriers. Cancer Res 2006, 66:1866-1872.
8. Gail M.H., Mai P.L. Comparing breast cancer risk assessment models. J Natl Cancer Inst 2010, 102:665-668.
9. Bi-RADS Breast Imaging Reporting and Data System Breast Imaging Atlas. Reston, VA: American College of Radiology; 2003.
10. Berg W.A., Campassi C., Langenberg P., Sexton M.J. Breast Imaging Reporting and Data System: inter- and intra-observer variability in feature analysis and final assessment. Am J Roentgenol 2000, 174:1769-1777.
11. Taboces P.G., Correa J., Souto M., Gómez L., Vidal J.J. Computer-assisted diagnosis: the classification of mammographic breast parenchymal patterns. Phys. Med. Biol. 1995, 40:103-117.
12. Byng J.W., Yaffe M.J., Lockwood L.E., Little L.E., Tritchler D.L., Boyd N.F. Automated analysis of mammographic densities and breast carcinoma risk. Cancer 1997, 80:66-74.
13. Zhou C., Chan H.P., Petrick N., Helvie M.A., Goodsitt M.M., Sahiner B., et al. Computerized image analysis: estimation of breast density on mammograms. Med. Phys. 2001, 28:1056-1069.
14. Chang Y.H., Wang X.H., Hardesty L.A., Chang T.S., Poller W.R., Good W.F., et al. Computerized assessment of tissue composition on digitized mammograms. Acad Radiol 2002, 9:898-905.
15. Wang X.H., Good W.F., Chapman B.E., Chang Y.H., Poller W.R., Chang T.S., et al. Automated assessment of composition of breast tissue revealed on tissue-thickness-corrected mammography. Am J Roentgenol 2003, 180:257-262.
16. Li H., Giger M.L., Olopade O.I., Margolis A., Lan L., Chinander M.R. Computerized texture analysis of mammographic parenchymal patterns of digitized mammograms. Acad Radiol 2005, 12:863-873.
17. Highnam R., Pan X., Warren R., Jeffreys M., Davey Smith G., Brady M. Breast composition measurements using retrospective standard mammogram form (SMF). Phys Med Biol 2006, 51:2696-2713.
18. Glide-Hurst C.K., Duric N., Littrup P. A new method for quantitative analysis of mammographic density. Med Phys 2007, 34:4491-4498.
19. Oliver A., Freixenet J., Mart R., Pont J., Póerez E., Denton E.R.E., et al. A novel breast tissue density classification methodology. IEEE Trans Inf Technol Biomed 2008, 12:55-65.
20. Subashini T.S., Ramalingam V., Palanivel Automated assessment of breast tissue density in digital mammograms. Comput Vision Image Understand 2010, 114:33-43.
21. Krishnan M.M.R., Banerjee S., Chakraborty C., Chakraborty C., Ray A.K. Statistical analysis of mammographic features and its classification using support vector machine. Expert Syst Appl 2010, 37:470-478.
22. Huo Z., Giger M.L., Olopade O.I., Wolverton D.E., Weber B.L., Metz C.E., et al. Computerized analysis of digitized mammograms of BRCA1 and BRCA2 gene mutation carriers. Radiology 2002, 225:519-526.
23. Li H., Giger M.L., Olopade O.I., Chinander M.R. Power spectral analysis of mammographic parenchymal patterns for breast cancer risk assessment. J Digit Imaging 2008, 21:145-152.
24. Madigan M.P., Ziegler R.G., Benichou J., Byrne C., Hoover R.N. Proportion of breast cancer cases in the United States explained by well-established risk factors. J Natl Cancer Inst 1995, 87:1681-1685.
25. Scutt D., Lancaster G.A., Manning J.T. Breast asymmetry and predisposition to breast cancer. Breast Cancer Res 2006, 8:R14. 10.1186/bcr1388.
26. Scutt D., Manning J.T., Whitehouse G.H., Leinster S.J., Massey C.P. The relationship between breast asymmetry, breast size and the occurrence of breast cancer. Br J Radiol 1997, 70:1017-1021.
27. Alterson R., Plewes D.B. Bilateral symmetry analysis of breast MRI. Phys Med Biol 2003, 48:3431-3443.
28. Wang X., Lederman D., Tan J., Wang X.H., Zheng B. Computerized detection of breast tissue asymmetry depicted on bilateral mammograms: a preliminary study of breast risk stratification. Acad Radiol 2010, 17:1234-1241.
29. Zheng B., Wang X., Lederman D., Tan J., Gur D. Computer-aided detection: the effect of training databases on detection of subtle breast masses, 2010. Acad Radiol 2010, 17:1401-1408.
30. Cheng B., Leader J.K., Abrams G.S., Lu A.H., Wallace L.P., Maitz G.S., et al. Multiview-based computer-aided detection scheme for breast masses. Med Phys 2006, 33:3135-3143.
31. Mitchell T.M. Machine learning 1997, WCB/McGraw-Hill, Boston, MA.
32. Park S.C., Pu J., Zheng B. Improving performance of computer-aided detection scheme by combining results from two machine learning classifiers. Acad Radiol 2009, 16:266-274.
33. Kantrowitz M. Prime time freeware for AI. Issue 1-1 Artificial Intelligence Repository 1 selected materials from the Carnegie Mellon University 1994, Prime Time Freeware, Sunnyvale, CA.
34. Li Q., Doi K. Analysis and minimization of overtraining effect in rule-based classifiers for computer-aided diagnosis. Med Phys 2006, 33:320-328.
35. Metz CE. ROCKIT 0.9B Beta Version. University of Chicago, http://www-radiology.uchicago.edu/krl/1998.
36. Liu B., Metz C.E., Jiang Y. An ROC comparison of four methods of combining information from multiple images of the same patient. Med Phys 2004, 31:2552-2563.
37. Yin F.F., Giger M.L., Doi K., Metz C.E., Vyborny C.J., Schmidt R.A. Computerized detection of masses in digital mammograms: analysis of bilateral subtraction images. Med Phys 1991, 18:955-963.
38. Zheng B., Chang Y.H., Gur D. Computerized detection of masses from digitized mammograms: comparison of single-image segmentation and bilateral-image subtracton. Acad Radiol 1995, 2:1056-1061.
39. Mendez A.J., Tahoces P.G., Lado M.J. Computer-aided diagnosis: automatic detection of malignant masses in digitized mammograms. Med Phys 1998, 25:957-964.
40. Gur D., Stalder J.S., Hardesty L.A., Zheng B., Sumkin J.H., Chough D.M., et al. Computer-aided detection performance in mammographic examination of masses: assessment. Radiology 2004, 233:418-423.