Breast density and parenchymal texture measures as potential risk factors for estrogen-receptor positive breast cancer

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 9035, Issue , 2014, Pages

  Keller, Brad M ^a   Chen, Jinbo ^a   Conant, Emily F ^a   Kontos, Despina ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Breast Cancer Risk; Breast Percent Density (PD ); Digital Mammography; Parenchymal Texture; Receptor

Indexed keywords

COMPUTER AIDED DIAGNOSIS; DISEASES; MATHEMATICAL MODELS; MEDICAL IMAGING; REGRESSION ANALYSIS; TEXTURES; TISSUE;

BREAST CANCER RISK; BREAST PERCENT DENSITIES; DIGITAL MAMMOGRAPHY; LOGISTIC REGRESSION MODELING; MEDIO-LATERAL OBLIQUE VIEWS; QUANTITATIVE MEASURES; RECEIVER OPERATING CHARACTERISTICS; RECEPTOR;

RISK ASSESSMENT;

EID: 84902094417     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.2043710     Document Type: Conference Paper

References (21)

1. Kerlikowske, K., "Evidence-based breast cancer prevention: The importance of individual risk," Ann Intern Med, 151(10), 750-2 (2009).
2. Gail, M. H., "Personalized estimates of breast cancer risk in clinical practice and public health," Stat Med, 30(10), 1090-104 (2011).
3. Gail, M. H., Brinton, L. A., Byar, D. P., Corle, D. K., Green, S. B., Schairer, C., and Mulvihill, J. J., "Projecting individualized probabilities of developing breast cancer for white females who are being examined annually," J Natl Cancer Inst, 81(24), 1879-86 (1989).
4. Lehman, C. D., Blume, J. D., Weatherall, P., Thickman, D., Hylton, N., Warner, E., Pisano, E. et al., "Screening women at high risk for breast cancer with mammography and magnetic resonance imaging," Cancer, 103(9), 1898-905 (2005).
5. Saslow, D., Boetes, C., Burke, W., Harms, S., Leach, M. O., Lehman, C. D., Morris, E. et al., "American Cancer Society guidelines for breast screening with MRI as an adjunct to mammography," CA Cancer J Clin, 57(2), 75-89 (2007).
6. Thomsen, A., and Kolesar, J. M., "Chemoprevention of breast cancer," Am J Health Syst Pharm, 65(23), 2221-8 (2008).
7. Vogel, V. G., "Preventing breast cancer in high-risk women, 2008," Oncology (Williston Park), 22(6), 666-73; discussion 679, 682, 684 (2008).
8. Rockhill, B., Spiegelman, D., Byrne, C., Hunter, D. J., and Colditz, G. A., "Validation of the Gail et al. model of breast cancer risk prediction and implications for chemoprevention," J Natl Cancer Inst, 93(5), 358-66 (2001).
9. Fisher, B., Costantino, J. P., Wickerham, D. L., Cecchini, R. S., Cronin, W. M., Robidoux, A., Bevers, T. B. et al., "Tamoxifen for the prevention of breast cancer: current status of the National Surgical Adjuvant Breast and Bowel Project P-1 study," J Natl Cancer Inst, 97(22), 1652-62 (2005).
10. Boyd, N. F., Guo, H., Martin, L. J., Sun, L., Stone, J., Fishell, E., Jong, R. A. et al., "Mammographic density and the risk and detection of breast cancer," N Engl J Med, 356(3), 227-36 (2007).
11. Li, H., Giger, M. L., Lan, L., Bancroft Brown, J., MacMahon, A., Mussman, M., Olopade, O. I., and Sennett, C., "Computerized analysis of mammographic parenchymal patterns on a large clinical dataset of full-field digital mammograms: robustness study with two high-risk datasets," J Digit Imaging, 25(5), 591-8 (2012).
12. Chen, Y., Thompson, W., Semenciw, R., and Mao, Y., "Epidemiology of contralateral breast cancer," Cancer Epidemiol Biomarkers Prev, 8(10), 855-61 (1999).
13. Keller, B. M., Nathan, D. L., Wang, Y., Zheng, Y., Gee, J. C., Conant, E. F., and Kontos, D., "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, 39(8), 4903-17 (2012).
14. Zheng, Y., Wang, Y., Keller, B. M., Conant, E., Gee, J. C., and Kontos, D., "A fully-automated software pipeline for integrating breast density and parenchymal texture analysis for digital mammograms: parameter optimization in a case-control breast cancer risk assessment study. " 86701B-86701B-7.
15. Huo, Z., Giger, M. L., Wolverton, D. E., Zhong, W., Cumming, S., and Olopade, O. I., "Computerized analysis of mammographic parenchymal patterns for breast cancer risk assessment: feature selection," Med Phys, 27(1), 4-12 (2000).
16. Manduca, A., Carston, M. J., Heine, J. J., Scott, C. G., Pankratz, V. S., Brandt, K. R., Sellers, T. A. et al., "Texture features from mammographic images and risk of breast cancer," Cancer Epidemiol Biomarkers Prev, 18(3), 837-45 (2009).
17. Gibbs, P., and Turnbull, L. W., "Textural analysis of contrast-enhanced MR images of the breast," Magn Reson Med, 50(1), 92-8 (2003).
18. Li, H., Giger, M. L., Olopade, O. I., and Lan, L., "Fractal analysis of mammographic parenchymal patterns in breast cancer risk assessment," Acad Radiol, 14(5), 513-21 (2007).
19. Ojala, T., Pietikainen, M., and Maenpaa, T., "Multiresolution gray-scale and rotation invariant texture classification with local binary patterns," Pattern Analysis and Machine Intelligence, IEEE Transactions on, 24(7), 971-987 (2002).
20. Wang, Y., Keller, B. M., Zheng, Y., Acciavatti, R. J., Gee, J. C., Maidment, A. D., and Kontos, D., "Texture feature standardization in digital mammography for improving generalizability across devices. " 867026-867026-8.
21. Daye, D., Keller, B., Conant, E. F., Chen, J., Schnall, M. D., Maidment, A. D., and Kontos, D., "Mammographic parenchymal patterns as an imaging marker of endogenous hormonal exposure: a preliminary study in a high-risk population," Acad Radiol, 20(5), 635-46 (2013).