Mammographic parenchymal patterns as an imaging marker of endogenous hormonal exposure. A preliminary study in a high-risk population

Academic Radiology

Volumn 20, Issue 5, 2013, Pages 635-646

  Daye, Dania ^a   Keller, Brad ^b   Conant, Emily F ^b   Chen, Jinbo ^b   Schnall, Mitchell D ^b   Maidment, Andrew D A ^b   Kontos, Despina ^b  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Breast cancer risk; Digital mammography; Hormonal exposure; Parenchymal texture

Indexed keywords

SEX HORMONE;

ADULT; AGED; ARTICLE; BREAST; BREAST CANCER; CANCER PATIENT; CONTROLLED STUDY; DIGITAL MAMMOGRAPHY; ECHOMAMMOGRAPHY DEVICE; ETHNICITY; FEMALE; HORMONE ACTION; HORMONE SUBSTITUTION; HUMAN; MAJOR CLINICAL STUDY; MENARCHE; MENOPAUSE; PARITY; POSTMENOPAUSE; PRIORITY JOURNAL; RETROSPECTIVE STUDY;

ABSORPTIOMETRY, PHOTON; ADULT; AGED; AGED, 80 AND OVER; BREAST NEOPLASMS; FEMALE; HORMONES; HUMANS; MAMMOGRAPHY; MENOPAUSE; MIDDLE AGED; PENNSYLVANIA; PILOT PROJECTS; PREVALENCE; RISK ASSESSMENT;

EID: 84875890883     PISSN: 10766332     EISSN: 18784046     Source Type: Journal    
DOI: 10.1016/j.acra.2012.12.016     Document Type: Article

References (45)

1. Armstrong K., Quistberg D.A., Micco E., et al. Prescription of tamoxifen for breast cancer prevention by primary care physicians. Arch Intern Med 2006, 166:2260-2265.
2. Singh V., Saunders C., Wylie L., et al. New diagnostic techniques for breast cancer detection. Future Oncol 2008, 4:501-513.
3. Gulati A.P., Domchek S.M. The clinical management of BRCA1 and BRCA2 mutation carriers. Curr Oncol Rep 2008, 10:47-53.
4. Rockhill B., Spiegelman D., Byrne C., et al. Validation of the Gail et al. model of breast cancer risk prediction and implications for chemoprevention. J Natl Cancer Inst 2001, 93:358-366.
5. Tice J.A., Cummings S.R., Smith-Bindman R., et al. 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. Boyd N.F., Martin L.J., Yaffe M.J., et al. Mammographic density and breast cancer risk: current understanding and future prospects. Breast Cancer Res 2011, 13:223.
7. Li H., Giger M.L., Olopade O.I., et al. Fractal analysis of mammographic parenchymal patterns in breast cancer risk assessment. Acad Radiol 2007, 14:513-521.
8. Huo Z., Giger M.L., Olopade O.I., et al. Computerized analysis of digitized mammograms of BRCA1 and BRCA2 gene mutation carriers. Radiology 2002, 225:519-526.
9. Caldwell C.B., Stapleton S.J., Holdsworth D.W., et al. Characterisation of mammographic parenchymal pattern by fractal dimension. Phys Med Biol 1990, 35:235-247.
10. Li H., Giger M.L., Olopade O.I., et al. Computerized texture analysis of mammographic parenchymal patterns of digitized mammograms. Acad Radiol 2005, 12:863-873.
11. Boyd N.F., Guo H., Martin L.J., et al. Mammographic density and the risk and detection of breast cancer. N Engl J Med 2007, 356:227-236.
12. Manduca A., Carston M.J., Heine J.J., et al. Texture features from mammographic images and risk of breast cancer. Cancer Epidemiol Biomarkers Prev 2009, 18:837-845.
13. Haberle L., Wagner F., Fasching P.A., et al. Characterizing mammographic images by using generic texture features. Breast Cancer Res 2012, 14:R59.
14. Chlebowski R.T., McTiernan A. Biological significance of interventions that change breast density. J Natl Cancer Inst 2003, 95:4-5.
15. Greendale G.A., Reboussin B.A., Slone S., et al. Postmenopausal hormone therapy and change in mammographic density. J Natl Cancer Inst 2003, 95:30-37.
16. Prowell T.M., Blackford A.L., Byrne C., et al. Changes in breast density and circulating estrogens in postmenopausal women receiving adjuvant anastrozole. Cancer Prev Res (Phila) 2011, 4:1993-2001.
17. Clemons M., Goss P. Estrogen and the risk of breast cancer. N Engl J Med 2001, 344:276-285.
18. Kerlikowske K., Cook A.J., Buist D.S., et al. Breast cancer risk by breast density, menopause, and postmenopausal hormone therapy use. J Clin Oncol 2010, 28:3830-3837.
19. Daye D., Bobo E., Baumann B., et al. Mammographic parenchymal texture as an imaging marker of hormonal activity: a comparative study between pre- and post-menopausal women. Medical Imaging 2011: Computer-Aided Diagnosis, Proc SPIE 2011, 7963. 79631N-79631N.
20. Key T., Appleby P., Barnes I., et al. Endogenous sex hormones and breast cancer in postmenopausal women: reanalysis of nine prospective studies. J Natl Cancer Inst 2002, 94:606-616.
21. Missmer S.A., Eliassen A.H., Barbieri R.L., et al. Endogenous estrogen, androgen, and progesterone concentrations and breast cancer risk among postmenopausal women. J Natl Cancer Inst 2004, 96:1856-1865.
22. Pike M.C., Krailo M.D., Henderson B.E., et al. 'Hormonal' risk factors, 'breast tissue age' and the age-incidence of breast cancer. Nature 1983, 303:767-770.
23. Grady D. Clinical practice. Management of menopausal symptoms. N Engl J Med 2006, 355:2338-2347.
24. Kontos D., Bakic P.R., Carton A.K., et al. Parenchymal texture analysis in digital breast tomosynthesis for breast cancer risk estimation: a preliminary study. Acad Radiol 2009, 16:283-298.
25. Kontos D., Ikejimba L., Bakic P.R., et al. Digital breast tomosynthesis parenchymal texture analysis: comparison with digital mammography and implications for cancer risk assessment. Radiology 2011, 261:80-91.
26. Oliver A., Freixenet J., Marti R., et al. A novel breast tissue density classification methodology. IEEE Trans Inf Technol Biomed 2008, 12:55-65.
27. Kontos D., Ikejimba L.C., Bakic P.R., et al. Analysis of parenchymal texture with digital breast tomosynthesis: comparison with digital mammography and implications for cancer risk assessment. Radiology 2011, 261:80-91.
28. Haralick R.M., Shanmugam K., Dinstein I. Textural features for image classification. IEEE Trans Syst Man Cybernetics 1973, 3:610-621.
29. Amadasum M., King R. Textural features corresponding to textural properties. IEEE Trans Syst Man Cybernetics 1989, 19:1264-1274.
30. Wei J., Chan H.P., Wu Y.T., et al. Association of computerized mammographic parenchymal pattern measure with breast cancer risk: a pilot case-control study. Radiology 2011, 260:42-49.
31. Huo Z., Giger M.L., Wolverton D.E., et al. Computerized analysis of mammographic parenchymal patterns for breast cancer risk assessment: feature selection. Med Phys 2000, 27:4-12.
32. Li H., Giger M.L., Huo Z., et al. Computerized analysis of mammographic parenchymal patterns for assessing breast cancer risk: effect of ROI size and location. Med Phys 2004, 31:549-555.
33. McCormack 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.
34. Keller B., Nathan D., Wang Y., et al. Adaptive multi-cluster fuzzy C-means segmentation of breast parenchymal tissue in digital mammography. Med Image Comput Comput Assist Interv 2011, 14:562-569.
35. Keller B.M., Nathan D.L., Wang Y., et al. Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy C-means clustering and support vector machine segmentation. Med Phys 2012, 39:4903-4917.
36. Brodersen K.H., Ong C.S., Stephan K.E., et al. The binormal assumption on precision-recall curves. Proceedings of the 20th International Conference on Pattern Recognition (ICPR) 2010, 4263-4266.
37. Pepe M., Longton G., Janes H. Estimation and comparison of receiver operating characteristic curves. Stata J 2009, 9:1.
38. Boyd N., Melnichouk O., Martin L.J., et al. Mammographic density, response to hormones, and breast cancer risk. J Clin Oncol 2011, 29:2985-2992.
39. Boyd N., Martin L., Stone J., et al. A longitudinal study of the effects of menopause on mammographic features. Cancer Epidemiol Biomarkers Prev 2002, 11:1048-1053.
40. Greendale G.A., Reboussin B.A., Sie A., et al. Effects of estrogen and estrogen-progestin on mammographic parenchymal density. Postmenopausal Estrogen/Progestin Interventions (PEPI) Investigators. Ann Intern Med 1999, 130:262-269.
41. Cuzick J., Warwick J., Pinney E., et al. Tamoxifen and breast density in women at increased risk of breast cancer. J Natl Cancer Inst 2004, 96:621-628.
42. Kontos D, Berger R, Bakic PR, et al. Breast tissue classification in digital breast tomosynthesis images using texture features: a feasibility study. In SPIE Medical Imaging: Computer-Aided Diagnosis M.L. Giger, and N. Karssemeijer, editors. Orlando, FL; 2009.
43. Raundahl J., Loog M., Pettersen P., et al. Automated effect-specific mammographic pattern measures. IEEE Trans Med Imaging 2008, 27:1054-1060.
44. Haralick R.M. Statistical and structural approaches to texture. Proc IEEE 1979, 67:786-804.
45. Li H., Giger M.L., Olopade O.I., et al. Power spectral analysis of mammographic parenchymal patterns for breast cancer risk assessment. J Digit Imaging 2008, 21:145-152.