The Effect of Breast Parenchymal Density on Breast Cancer Subtypes and Prognostic Factors
Efficacy of Parenchymal Density on Breast Cancer
DOI:
https://doi.org/10.22317/jcms.v6i4.787Keywords:
Breast Cancer, Parenchymal Density, Prognosis, MammographyAbstract
Objective: Mammographic breast parenchymal density is the radiological composition of radiodense fibroglandular tissue and radiolucent adipose tissue. Dense breasts restrict the imaging of lesions detected by mammography and reduce the sensitivity of mammography. In this study, we investigated correlation between breast parenchymal density and prognosis, tumor biology, reoperation rates and prognostic factors.
Methods: Patients who were operated for breast cancer between January 2017-December 2019 were included. The craniocaudal and mediolateral images obtained during conventional mammograms were collected in a database. The appearance of radiologically dense and lucent areas on mammography was taken as the mammographic percentage consistent with the current literature.
Results: According to breast parenchymal density, there were 21 patients (14.7%) with type 1 breast density, 29 (20.3%) with type 2, 47 (32.9%) with type 3 and 46 (32.1%) with type 4. Mean survival time due to breast cancer was 27.45±17.85 months (1-63), and 139 patients (97.2%) lived, while 4 (2.8%) were exitus.
Conclusion: Increased breast parenchymal density is a crucial risk factor for breast cancer. The effects of density on tumor biology and prognosis are still controversial. Although increased breast density seems to have an effect on indicators of poor prognosis. Additional examinations should be taken into consideration in order not to cause delay or skipping in diagnosis due to the decreased sensitivity of mammography in dense breasts.
References
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27. Chen J-H, Hsu F-T, Shih H-N, Hsu C-C, Chang D, Nie K, et al. Does breast density show difference in patients with estrogen receptor-positive and estrogen receptor-negative breast cancer measured on MRI? Annals of oncology. 2009;20(8):1447-9.
28. Yang W-T, Dryden M, Broglio K, Gilcrease M, Dawood S, Dempsey PJ, et al. Mammographic features of triple receptor-negative primary breast cancers in young premenopausal women. Breast cancer research and treatment. 2008;111(3):405-10.
29. Conroy SM, Pagano I, Kolonel LN, Maskarinec G. Mammographic density and hormone receptor expression in breast cancer: the Multiethnic Cohort Study. Cancer epidemiology. 2011;35(5):448-52.
30. J.Ding J WR, Girling A, Thompson D, Easton D. . Mammographic density, estrogen receptor status and other breast cancer tumor characteristics. Breast J. 2010;16(3):279-89.
31. K.Ghosh K BK, Sellers T, et al. . Association of mammographic density with the pathology of subsequent breast cancer among postmenopausal women. Cancer Epidemiol Biomarkers Prev. 2008;17(4):872-9.
32. T. FS. Molecular portraits of breast cancer: tumour subtypes as distinct disease entities. Eur J Cancer. 2004;40(18):2667-75.
33. Ma H WY, Sullivan-Halley J, et al. Use of four biomarkers to evaluate the risk of breast cancer subtypes in the women’s contraceptive and reproductive experiences study. Cancer Res. 2010;70(2):575-87.
34. Yang X C-CJ, Goode E, et al. 2011;103(3): 250–263. . Associations of breast cancer risk factors with tumor subtypes: a pooled analysis from the Breast Cancer Association Consortium Studies. J Natl Cancer Inst. 2011;103(3):250-63.
35. Mema E SF, Chun J, Kaplowitz E, Price A, Goodgal J, Moy L. The relationship of breast density in mammography and magnetic resonance imaging in women with triple negative breast cancer. European Journal of Radiology. 2020;124.
36. Porter G EA, Cornford E, et al.. 2007;188(3):676–683. . Influence of mammographic paren- chymal pattern in screening-detected and interval invasive breast cancers on pathologic features, mammographic features, and patient survival. AJR Am J Roentgenol.188(3):676-83.
37. M.Sala E SL, Warren R, et al. . Size, node status and grade of breast tumours: association with mammographic parenchymal patterns. Eur Radiol. 2000;10(1):157-61.
38. Kerlikowske K, Cook AJ, Buist DS, Cummings SR, Vachon C, Vacek P, et al. Breast cancer risk by breast density, menopause, and postmenopausal hormone therapy use. Journal of Clinical Oncology. 2010;28(24):3830.
39. Ma Q, Dieterich LC, Detmar M. Multiple roles of lymphatic vessels in tumor progression. Current opinion in immunology. 2018;53:7-12.
40. Zhang S ZD, Gong M, Wen L, Liao C, Zou L High lymphatic vessel density and presence of lymphovascular inva- sion both predict poor prognosis in breast cancer. BMC Cancer 2017;17(1):335.
41. Rakha EA MS, Lee AH, Morgan D, Pharoah PD, Hodi Z, Macmillan D, Ellis IO. The prognostic significance of lymphovascular invasion in invasive breast carcinoma. Cancer. 2012:3670-80.
42. Zhang ZQ HY, Nian Q, Chen G, Cui SQ, Wang XY Tumor invasiveness, not lymphangiogenesis, is correlated with lymph node metastasis and unfavorable prognosis in young breast cancer patients. PLoS ONE. 2015.
2. Huo C, Chew G, Britt K, Ingman W, Henderson M, Hopper J, et al. Mammographic density—a review on the current understanding of its association with breast cancer. Breast cancer research and treatment. 2014;144(3):479-502.
3. Sickles EA, D’Orsi CJ, Bassett LW, Appleton CM, Berg WA, Burnside ES. ACR BI-RADS® Atlas, Breast imaging reporting and data system. Reston, VA: American College of Radiology. 2013:39-48.
4. Carney PA, Miglioretti DL, Yankaskas BC, Kerlikowske K, Rosenberg R, Rutter CM, et al. Individual and combined effects of age, breast density, and hormone replacement therapy use on the accuracy of screening mammography. Annals of internal medicine. 2003;138(3):168-75.
5. Masarwah A, Auvinen P, Sudah M, Dabravolskaite V, Arponen O, Sutela A, et al. Prognostic contribution of mammographic breast density and HER2 overexpression to the Nottingham Prognostic Index in patients with invasive breast cancer. BMC cancer. 2016;16(1):833.
6. Elsamany S, Alzahrani A, Elkhalik SA, Elemam O, Rawah E, Farooq MU, et al. Prognostic value of mammographic breast density in patients with metastatic breast cancer. Medical Oncology. 2014;31(8):96.
7. Masarwah A, Auvinen P, Sudah M, Rautiainen S, Sutela A, Pelkonen O, et al. Very low mammographic breast density predicts poorer outcome in patients with invasive breast cancer. European radiology. 2015;25(7):1875-82.
8. Boyd NF, Martin LJ, Yaffe MJ, Minkin S. Mammographic density and breast cancer risk: current understanding and future prospects. Breast cancer research. 2011;13(6):223.
9. Boyd N, O'sullivan B, Campbell J, Fishell E, Simor I, Cooke G, et al. Mammographic signs as risk factors for breast cancer. British journal of cancer. 1982;45(2):185-93.
10. Song T, Wang Y, Du W, Cao S, Tian Y, Liang Y. The method for breast cancer grade prediction and pathway analysis based on improved multiple kernel learning. Journal of bioinformatics and computational biology. 2017;15(01):1650037.
11. Ginsburg O, Martin L, Boyd N. Mammographic density, lobular involution, and risk of breast cancer. British journal of cancer. 2008;99(9):1369-74.
12. Sprague BL, Gangnon RE, Burt V, Trentham-Dietz A, Hampton JM, Wellman RD, et al. Prevalence of mammographically dense breasts in the United States. JNCI: Journal of the National Cancer Institute. 2014;106(10).
13. Kolb TM, Lichy J, Newhouse JH. Comparison of the performance of screening mammography, physical examination, and breast US and evaluation of factors that influence them: an analysis of 27,825 patient evaluations. Radiology. 2002;225(1):165-75.
14. Berg WA, Gutierrez L, NessAiver MS, Carter WB, Bhargavan M, Lewis RS, et al. Diagnostic accuracy of mammography, clinical examination, US, and MR imaging in preoperative assessment of breast cancer. radiology. 2004;233(3):830-49.
15. Wolfe JN. Breast patterns as an index of risk for developing breast cancer. American Journal of Roentgenology. 1976;126(6):1130-7.
16. Wolfe JN. Risk for breast cancer development determined by mammographic parenchymal pattern. Cancer. 1976;37(5):2486-92.
17. McCormack VA, dos Santos Silva I. Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. Cancer Epidemiology and Prevention Biomarkers. 2006;15(6):1159-69.
18. Guo Y-P, Martin LJ, Hanna W, Banerjee D, Miller N, Fishell E, et al. Growth factors and stromal matrix proteins associated with mammographic densities. Cancer Epidemiology and Prevention Biomarkers. 2001;10(3):243-8.
19. Li T, Sun L, Miller N, Nicklee T, Woo J, Hulse-Smith L, et al. The association of measured breast tissue characteristics with mammographic density and other risk factors for breast cancer. Cancer Epidemiology and Prevention Biomarkers. 2005;14(2):343-9.
20. Pettersson A, Graff RE, Ursin G, dos Santos Silva I, McCormack V, Baglietto L, et al. Mammographic density phenotypes and risk of breast cancer: a meta-analysis. Journal of the National Cancer Institute. 2014;106(5):dju078.
21. Boyd NF, Guo H, Martin LJ, Sun L, Stone J, Fishell E, et al. Mammographic density and the risk and detection of breast cancer. New England Journal of Medicine. 2007;356(3):227-36.
22. Nyante SJ, Sherman ME, Pfeiffer RM, Berrington de Gonzalez A, Brinton LA, Aiello Bowles EJ, et al. Prognostic significance of mammographic density change after initiation of tamoxifen for ER-positive breast cancer. JNCI: Journal of the National Cancer Institute. 2015;107(3).
23. Li J, Humphreys K, Eriksson L, Edgren G, Czene K, Hall P. Mammographic density reduction is a prognostic marker of response to adjuvant tamoxifen therapy in postmenopausal patients with breast cancer. Journal of Clinical Oncology. 2013;31(18):2249.
24. Chiu SY-H, Duffy S, Yen AM-F, Tabár L, Smith RA, Chen H-H. Effect of baseline breast density on breast cancer incidence, stage, mortality, and screening parameters: 25-year follow-up of a Swedish mammographic screening. Cancer Epidemiology and Prevention Biomarkers. 2010;19(5):1219-28.
25. Gierach GL, Ichikawa L, Kerlikowske K, Brinton LA, Farhat GN, Vacek PM, et al. Relationship between mammographic density and breast cancer death in the Breast Cancer Surveillance Consortium. Journal of the National Cancer Institute. 2012;104(16):1218-27.
26. Maskarinec G, Pagano IS, Little MA, Conroy SM, Park S-Y, Kolonel LN. Mammographic density as a predictor of breast cancer survival: the Multiethnic Cohort. Breast Cancer Research. 2013;15(1):R7.
27. Chen J-H, Hsu F-T, Shih H-N, Hsu C-C, Chang D, Nie K, et al. Does breast density show difference in patients with estrogen receptor-positive and estrogen receptor-negative breast cancer measured on MRI? Annals of oncology. 2009;20(8):1447-9.
28. Yang W-T, Dryden M, Broglio K, Gilcrease M, Dawood S, Dempsey PJ, et al. Mammographic features of triple receptor-negative primary breast cancers in young premenopausal women. Breast cancer research and treatment. 2008;111(3):405-10.
29. Conroy SM, Pagano I, Kolonel LN, Maskarinec G. Mammographic density and hormone receptor expression in breast cancer: the Multiethnic Cohort Study. Cancer epidemiology. 2011;35(5):448-52.
30. J.Ding J WR, Girling A, Thompson D, Easton D. . Mammographic density, estrogen receptor status and other breast cancer tumor characteristics. Breast J. 2010;16(3):279-89.
31. K.Ghosh K BK, Sellers T, et al. . Association of mammographic density with the pathology of subsequent breast cancer among postmenopausal women. Cancer Epidemiol Biomarkers Prev. 2008;17(4):872-9.
32. T. FS. Molecular portraits of breast cancer: tumour subtypes as distinct disease entities. Eur J Cancer. 2004;40(18):2667-75.
33. Ma H WY, Sullivan-Halley J, et al. Use of four biomarkers to evaluate the risk of breast cancer subtypes in the women’s contraceptive and reproductive experiences study. Cancer Res. 2010;70(2):575-87.
34. Yang X C-CJ, Goode E, et al. 2011;103(3): 250–263. . Associations of breast cancer risk factors with tumor subtypes: a pooled analysis from the Breast Cancer Association Consortium Studies. J Natl Cancer Inst. 2011;103(3):250-63.
35. Mema E SF, Chun J, Kaplowitz E, Price A, Goodgal J, Moy L. The relationship of breast density in mammography and magnetic resonance imaging in women with triple negative breast cancer. European Journal of Radiology. 2020;124.
36. Porter G EA, Cornford E, et al.. 2007;188(3):676–683. . Influence of mammographic paren- chymal pattern in screening-detected and interval invasive breast cancers on pathologic features, mammographic features, and patient survival. AJR Am J Roentgenol.188(3):676-83.
37. M.Sala E SL, Warren R, et al. . Size, node status and grade of breast tumours: association with mammographic parenchymal patterns. Eur Radiol. 2000;10(1):157-61.
38. Kerlikowske K, Cook AJ, Buist DS, Cummings SR, Vachon C, Vacek P, et al. Breast cancer risk by breast density, menopause, and postmenopausal hormone therapy use. Journal of Clinical Oncology. 2010;28(24):3830.
39. Ma Q, Dieterich LC, Detmar M. Multiple roles of lymphatic vessels in tumor progression. Current opinion in immunology. 2018;53:7-12.
40. Zhang S ZD, Gong M, Wen L, Liao C, Zou L High lymphatic vessel density and presence of lymphovascular inva- sion both predict poor prognosis in breast cancer. BMC Cancer 2017;17(1):335.
41. Rakha EA MS, Lee AH, Morgan D, Pharoah PD, Hodi Z, Macmillan D, Ellis IO. The prognostic significance of lymphovascular invasion in invasive breast carcinoma. Cancer. 2012:3670-80.
42. Zhang ZQ HY, Nian Q, Chen G, Cui SQ, Wang XY Tumor invasiveness, not lymphangiogenesis, is correlated with lymph node metastasis and unfavorable prognosis in young breast cancer patients. PLoS ONE. 2015.
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2020-08-26
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Yüksel, C., Çulcu, S., Bakırarar, B., & Doğan, L. . (2020). The Effect of Breast Parenchymal Density on Breast Cancer Subtypes and Prognostic Factors: Efficacy of Parenchymal Density on Breast Cancer. Journal of Contemporary Medical Sciences, 6(4), 181–186. https://doi.org/10.22317/jcms.v6i4.787
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