Comparison of breast density measured on MR images acquired using fat-suppressed versus nonfat-suppressed sequences
- PMID: 22047360
- PMCID: PMC3215688
- DOI: 10.1118/1.3646756
Comparison of breast density measured on MR images acquired using fat-suppressed versus nonfat-suppressed sequences
Abstract
Purpose: To investigate the difference of MR percent breast density measured from fat-suppressed versus nonfat-suppressed imaging sequences.
Methods: Breast magnetic resonance imaging (MRI) with and without fat suppression was acquired from 38 subjects. Breasts were divided into subgroups of different morphological patterns ("central" and "intermingled" types). Breast volume, fibroglandular tissue volume, and percent density were measured. The results were compared using nonparametric statistical tests and regarded as significant at p < 0.05.
Results: Breast volume, fibroglandular volume, and percent density between fat-suppressed and nonfat-suppressed sequences were highly correlated. Breast volumes measured on these two sequences were almost identical. Fibroglandular tissue volume and percent density, however, had small (<5%) yet significant differences between the two sequences-they were both higher on the fat-suppressed sequence. Intraobserver variability was within 4% for both sequences and different morphological types. The fibroglandular tissue volume measured on downsampled images showed a small (<5%) yet significant difference.
Conclusions: The measurement of breast density made on MRI acquired using fat-suppressed and nonfat-suppressed T1W images was about 5% difference, only slightly higher than the intraobserver variability of 3%-4%. When the density data from multiple centers were to be combined, evaluating the degree of difference is needed to take this difference into account.
Figures




Similar articles
-
Quantitative Measurement of Breast Density Using Personalized 3D-Printed Breast Model for Magnetic Resonance Imaging.Diagnostics (Basel). 2020 Oct 6;10(10):793. doi: 10.3390/diagnostics10100793. Diagnostics (Basel). 2020. PMID: 33036272 Free PMC article.
-
An investigation of the effect of fat suppression and dimensionality on the accuracy of breast MRI segmentation using U-nets.Med Phys. 2019 Mar;46(3):1230-1244. doi: 10.1002/mp.13375. Epub 2019 Feb 4. Med Phys. 2019. PMID: 30609062
-
Fatty and fibroglandular tissue volumes in the breasts of women 20-83 years old: comparison of X-ray mammography and computer-assisted MR imaging.AJR Am J Roentgenol. 1997 Feb;168(2):501-6. doi: 10.2214/ajr.168.2.9016235. AJR Am J Roentgenol. 1997. PMID: 9016235
-
Consistency of breast density measured from the same women in four different MR scanners.Med Phys. 2012 Aug;39(8):4886-95. doi: 10.1118/1.4736824. Med Phys. 2012. PMID: 22894415 Free PMC article.
-
Correlation between mammographic density and volumetric fibroglandular tissue estimated on breast MR images.Med Phys. 2004 Apr;31(4):933-42. doi: 10.1118/1.1668512. Med Phys. 2004. PMID: 15125012 Clinical Trial.
Cited by
-
Quantitative Measurements of Breast Density Using Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis.J Clin Med. 2019 May 24;8(5):745. doi: 10.3390/jcm8050745. J Clin Med. 2019. PMID: 31137728 Free PMC article. Review.
-
Breast cancer MRI radiomics: An overview of algorithmic features and impact of inter-reader variability in annotating tumors.Med Phys. 2018 Jul;45(7):3076-3085. doi: 10.1002/mp.12925. Epub 2018 May 11. Med Phys. 2018. PMID: 29663411 Free PMC article.
-
Comparison of Dixon Sequences for Estimation of Percent Breast Fibroglandular Tissue.PLoS One. 2016 Mar 24;11(3):e0152152. doi: 10.1371/journal.pone.0152152. eCollection 2016. PLoS One. 2016. PMID: 27011312 Free PMC article.
-
Development of patient-specific 3D-printed breast phantom using silicone and peanut oils for magnetic resonance imaging.Quant Imaging Med Surg. 2020 Jun;10(6):1237-1248. doi: 10.21037/qims-20-251. Quant Imaging Med Surg. 2020. PMID: 32550133 Free PMC article.
-
Quantitative Measurement of Breast Density Using Personalized 3D-Printed Breast Model for Magnetic Resonance Imaging.Diagnostics (Basel). 2020 Oct 6;10(10):793. doi: 10.3390/diagnostics10100793. Diagnostics (Basel). 2020. PMID: 33036272 Free PMC article.
References
-
- Boyd N. F., Byng J. W., Jong R. A., Fishell E. K., Little L. E., Miller A. B., Lockwood G. A., Tritchler D. L., and Yaffe M. J., “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).10.1093/jnci/87.9.670 - DOI - PubMed
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical