Computerized analysis of mammographic parenchymal patterns on a large clinical dataset of full-field digital mammograms: Robustness study with two high-risk datasets

Journal of Digital Imaging

Volumn 25, Issue 5, 2012, Pages 591-598

  Li, Hui ^a   Giger, Maryellen L ^a   Lan, Li ^a   Bancroft Brown, Jeremy ^a   MacMahon, Aoife ^a   Mussman, Mary ^a   Olopade, Olufunmilayo I ^a   Sennett, Charlene ^a  

^a UNIVERSITY OF CHICAGO   (United States)

Author keywords

Breast cancer risk assessment; Computerized texture analysis; Full field digital mammograms; Mammographic parenchymal patterns; Quantitative imaging analysis

Indexed keywords

BREAST CANCER RISK ASSESSMENTS; COMPUTERIZED TEXTURE ANALYSIS; FULL-FIELD DIGITAL MAMMOGRAMS; MAMMOGRAPHIC PARENCHYMAL PATTERNS; QUANTITATIVE IMAGING ANALYSIS;

DISEASES; FEATURE EXTRACTION; GENES; MEDICAL IMAGING; NEURAL NETWORKS; RISK ASSESSMENT; TEXTURES; X RAY SCREENS;

MAMMOGRAPHY;

ADULT; AGE DISTRIBUTION; AGED; ARTICLE; BAYES THEOREM; BREAST TUMOR; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; CONFIDENCE INTERVAL; EVALUATION; FACTUAL DATABASE; FEMALE; GENETIC PREDISPOSITION; GENETICS; HUMAN; IMAGE QUALITY; INCIDENCE; MAMMOGRAPHY; METHODOLOGY; MIDDLE AGED; PATHOLOGY; RADIOGRAPHY; RECEIVER OPERATING CHARACTERISTIC; RETROSPECTIVE STUDY; RISK ASSESSMENT; RISK MANAGEMENT; TUMOR SUPPRESSOR GENE;

ADULT; AGE DISTRIBUTION; AGED; BAYES THEOREM; BREAST NEOPLASMS; CONFIDENCE INTERVALS; DATABASES, FACTUAL; EVALUATION STUDIES AS TOPIC; FEMALE; GENES, BRCA2; GENETIC PREDISPOSITION TO DISEASE; HUMANS; INCIDENCE; MAMMOGRAPHY; MIDDLE AGED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; RETROSPECTIVE STUDIES; RISK ASSESSMENT; RISK MANAGEMENT; ROC CURVE; YOUNG ADULT;

EID: 84870063227     PISSN: 08971889     EISSN: 1618727X     Source Type: Journal    
DOI: 10.1007/s10278-012-9452-z     Document Type: Article

References (31)

1. Siegel R,Ward E, Brawley O, Jemal A: Cancer Statistics, 2011: the impact of eliminating socioeconomic and racial disparities on premature cancer deaths. CA Cancer J Clin 61:212-236, 2011
2. American College of Radiology: Breast Imaging Reporting and Data System (BI-RADS), 4th edition. American College of Radiology, Reston, Va, 2003
3. Wolfe JN: Breast patterns as an index of risk for developing breast cancer. Am J Roentgenol 126:1130-1139, 1976
4. Boyd NF, Martin LJ, Stone J, Greenberg, et al: Mammographic densities as a marker of human breast cancer risk and their use in chemoprevention. Curr Oncol Rep 3:314-321, 2001
5. Brisson J, Diorio C, Mâsse B: Wolfe's parenchymal pattern and percentage of the breast with mammographic densities: redundant or complementary classifications? Cancer Epidemiol Biomarkers Prev 12:728-732, 2003
6. Boyd NF, Lockwood GA, Martin LJ, et al: Mammographic densities and breast cancer risk. Breast Dis 10:113-126, 1998
7. Boyd NF, Martin LJ, Stone J, et al: Mammographic densities as a marker of human breast cancer risk and their use in chemoprevention. Cancer Prev 3:314-321, 2001
8. Atkinson C, Warren R, Bingham SA, et al: Mammographic patterns as a predictive biomarker of breast cancer risk: effect of tamoxifen. Cancer Epidemiol Biomarkers Prev 8:863-866, 1999
9. Saftlas AF, Hoover RN, Brinton LA, et al: Mammographic densities and risk of breast cancer. Cancer 67:2833-2838, 1991
10. Byrne C, Schairer C, Wolfe JN, et al: Mammographic features and breast cancer risk: Effects with time, age, and menopause status. J Natl Cancer Inst 87:1622-1629, 1995
11. Boyd NF, Byng J, Jong R: Quantitative classification of mammographic densities and breast cancer risk: Results from the Canadian National Breast Screening Study. J Natl Cancer Inst 87:670-675, 1995
12. Boyd NF, Guo H, Martin LJ, et al: Mammographic density and the risk and detection of breast cancer. N Engl J Med 356:227-236, 2007
13. Byng JW, Yaffe MJ, Lockwood GA, et al: Automated analysis of mammographic densities and breast carcinoma risk. Cancer 80:66- 74, 1997
14. Manduca A, Carston MJ, Heine JJ, et al: Texture features from mammographic images and risk of breast cancer. Cancer Epidemiol Biomarkers Prev 18:837-845, 2009
15. Wei J, Chan HP, Wu YT, et al: Association of computerized mammographic parenchymal pattern measure with breast cancer risk: a pilot case-control study. Radiology 260:42-49, 2011
16. Huo Z, Giger ML, Wolverton DE, et al: Computerized analysis of mammographic parenchymal patterns for breast cancer risk assessment: feature selection. Med Phys 27:4-12, 2000
17. Huo Z, Giger ML, Olopade OI, et al: Computerized analysis of digitized mammograms of BRCA1 and BRCA2 gene mutation carriers. Radiology 225:519-526, 2002
18. Li H, Giger ML, Olopade OI, et al: Computerized texture analysis of mammographic parenchymal patterns of digitized mammograms. Acad Radiol 12:863-873, 2005
19. Li H, Giger ML, Olopade OI, et al: Fractal analysis of mammographic parenchymal patterns in breast cancer risk assessment. Acad Radiol 14:513-521, 2007
20. Li H, Giger ML, Olopade OI, et al: Power spectral analysis of mammographic parenchymal patterns for breast cancer risk assessment. J Digit Imaging 21:145-152, 2008
21. Metz CE: ROC methodology in radiographic imaging. Invest Radiol 21:720-733, 1986
22. Metz CE: Some practical issues of experimental design and data analysis in radiological ROC studies. Invest Radiol 24:234-245, 1989
23. Gail MH, Brinton LA, Byar DP, et al: Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst 81:1879-1886, 1989
24. Li H, Giger ML, Huo Z, et al: Computerized analysis of mammographic parenchymal patterns for assessing breast cancer risk: effect of ROI size and location. Med Phys 31:549-555, 2004
25. Chen W, Giger ML, Li H, Bick U, Newstead GM: Volumetric texture analysis of breast lesions on contrast-enhanced magnetic resonance images. Magn Reson Med 58:562-571, 2007
26. Huberty CJ: Applied Discriminant Analysis, John Wiley and Sons, Inc, 1994
27. Lachenbruch PL: Discriminant Analysis. Hafer, London, England, 1975
28. Kupinski MA, Edwards DC, Giger ML, et al: Ideal observer approximation using Bayesian classification neural networks. IEEE Trans Med Imaging 20:886-899, 2001
29. ROC software, http://www-radiology.uchicago.edu/krl/roc-soft6.htm
30. Holm S: A simple sequentially rejective multiple test procedure. Scand J Stat 6:65-70, 1979
31. Johnson RA, Wichern DW: Applied multivariate statistical analysis, 3rd edition. Prentice-Hall, Englewood Cliffs, NJ, 1992