Association between breast cancer, breast density, and body adiposity evaluated by MRI
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Despite the lack of reliable methods with which to measure breast density from 2D mammograms, numerous studies have demonstrated a positive association between breast cancer and breast density. The goal of this study was to study the association between breast cancer and body adiposity, as well as breast density quantitatively assessed from 3D MRI breast images.
Breast density was calculated from 3D T1-weighted MRI images. The thickness of the upper abdominal adipose layer was used as a surrogate marker for body adiposity. We evaluated the correlation between breast density, age, body adiposity, and breast cancer.
Breast density was calculated for 410 patients with unilateral invasive breast cancer, 73 patients with ductal carcinoma in situ (DCIS), and 361 controls without breast cancer. Breast density was inversely related to age and the thickness of the upper abdominal adipose layer. Breast cancer was only positively associated with body adiposity and age.
Age and body adiposity are predictive of breast density. Breast cancer was not associated with breast density; however, it was associated with the thickness of the upper abdominal adipose layer, a surrogate marker for body adiposity. Our results based on a limited number of patients warrant further investigations.
• MRI breast density is negatively associated with body adiposity.
• MRI breast density is negatively associated with age.
• Breast cancer is positively associated with body adiposity.
• Breast Cancer is not associated with MRI breast density.
KeywordsMagnetic resonance imaging Breast cancer Breast density Adiposity Age
Breast Imaging Reporting and Data System
invasive breast cancer
ductal carcinoma in situ
no breast cancer diagnosed
upper abdominal adipose layer
the thickness of the upper abdominal adipose layer
body mass index
We thank Dr. Vered Stearns for helpful discussions. We are grateful to Ms. Mary McAllister for editorial help with this manuscript. The scientific guarantor of this publication is Wenlian Zhu. The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article. This study has received funding by the National Cancer Institutes CA154738. Peng Huang kindly provided statistical advice for this manuscript. One of the authors has significant statistical expertise. Institutional Review Board approval was obtained. Written informed consent was waived by the Institutional Review Board. No study subjects or cohorts have been previously reported. Methodology: retrospective, cross sectional, performed at one institution.
- 5.D’Orsi CJ SE, Mendelson EB, Morris EA et al (2013) ACR BI-RADS® Atlas, Breast Imaging Reporting and Data System. American College of Radiology, RestonGoogle Scholar
- 6.(2013) American College of Radiology BI-RADS® ATLAS — MAMMOGRAPHY 5th Edition. Available via http://www.acr.org/~/media/ACR/Documents/PDF/QualitySafety/Resources/BIRADS/01%20Mammography/02%20%20BIRADS%20Mammography%20Reporting.pdf
- 17.Wengert GJ, Helbich TH, Vogl WD et al (2015) Introduction of an automated user-independent quantitative volumetric magnetic resonance imaging breast density measurement system using the Dixon sequence: comparison with mammographic breast density assessment. Invest Radiol 50:73–80CrossRefPubMedGoogle Scholar
- 32.Juntu J, Sijbers J, Van Dyck D, Gielen J (2005) Bias field correction for MRI images. Computer Recognition Systems, Proceedings:543-551Google Scholar
- 39.(2001) Familial breast cancer: collaborative reanalysis of individual data from 52 epidemiological studies including 58,209 women with breast cancer and 101,986 women without the disease. Lancet 358:1389-1399Google Scholar
- 41.Thomas EL, Saeed N, Hajnal JV et al (1985) (1998) Magnetic resonance imaging of total body fat. J Appl Physiol 85:1778–1785Google Scholar