Generic placeholder image

Current Medical Imaging

Editor-in-Chief

ISSN (Print): 1573-4056
ISSN (Online): 1875-6603

Research Article

Standardization of Breast Dynamic Contrast-enhanced MRI Signal with Application to the Assessment of Background Parenchymal Enhancement Rate

Author(s): Milica Medved*, Keiko Tsuchiya, Xiaobing Fan, Gregory S. Karczmar and Hiroyuki Abe

Volume 20, 2024

Published on: 11 April, 2023

Article ID: e060323214364 Pages: 7

DOI: 10.2174/1573405619666230306105820

open_access

Abstract

Background: There is currently no clinically accepted method for quantifying background parenchymal enhancement (BPE), though a sensitive method might allow individualized risk management based on the response to cancer-preventative hormonal therapy.

Objective: The objective of this pilot study is to demonstrate the utility of linear modeling of standardized dynamic contrast-enhanced MRI (DCEMRI) signal for quantifying changes in BPE rates.

Methods: On a retrospective database search, 14 women with DCEMRI examinations pre- and post-treatment with tamoxifen were identified. DCEMRI signal was averaged over the parenchymal ROIs to obtain time-dependent signal curves S(t). The gradient echo signal equation was used to standardize scale S(t) to values of FA = 10° and TR= 5.5 ms, and obtain the standardized DCE-MRI signal SP(t) . Relative signal enhancement RSEP was calculated from SP, and the reference tissue method for T1 calculation was used to standardize RSEP to gadodiamide as the contrast agent, obtaining RSE. RSE in the first 6 minutes post-contrast administration was fit to a linear model with the slope αRSE denoting the standardized rate relative BPE.

Results: Changes in αRSE were not found to be significantly correlated with the average duration of tamoxifen treatment, age at the initiation of preventative treatment, or pre-treatment BIRADS breast density category. The average change in αRSE showed a large effect size of -1.12, significantly higher than -0.86 observed without signal standardization (p < 0.01).

Conclusion: Linear modeling of BPE in standardized DCEMRI can provide quantitative measurements of BPE rates, improving sensitivity to changes due to tamoxifen treatment.

Keywords: Quantitative MRI, Dynamic contrast-enhanced MRI (DCE-MRI), Background parenchymal enhancement (BPE), MRI signal standardization, Breast cancer preventative therapy, Risk assessment.

[1]
Arasu VA, Miglioretti DL, Sprague BL, et al. Population-based assessment of the association between magnetic resonance imaging background parenchymal enhancement and future primary breast cancer risk. J Clin Oncol 2019; 37(12): 954-63.
[http://dx.doi.org/10.1200/JCO.18.00378] [PMID: 30625040]
[2]
Lam DL, Hippe DS, Kitsch AE, Partridge SC, Rahbar H. Assessment of quantitative magnetic resonance imaging background parenchymal enhancement parameters to improve determination of individual breast cancer risk. J Comput Assist Tomogr 2019; 43(1): 85-92.
[http://dx.doi.org/10.1097/RCT.0000000000000774] [PMID: 30052617]
[3]
Grimm LJ, Saha A, Ghate SV, et al. Relationship between background parenchymal enhancement on high-risk screening MRI and future breast cancer risk. Acad Radiol 2019; 26(1): 69-75.
[http://dx.doi.org/10.1016/j.acra.2018.03.013] [PMID: 29602724]
[4]
Dontchos BN, Rahbar H, Partridge SC, et al. Are qualitative assessments of background parenchymal enhancement, amount of fibroglandular tissue on MR images, and mammographic density associated with breast cancer risk? Radiology 2015; 276(2): 371-80.
[http://dx.doi.org/10.1148/radiol.2015142304] [PMID: 25965809]
[5]
King V, Brooks JD, Bernstein JL, Reiner AS, Pike MC, Morris EA. Background parenchymal enhancement at breast MR imaging and breast cancer risk. Radiology 2011; 260(1): 50-60.
[http://dx.doi.org/10.1148/radiol.11102156] [PMID: 21493794]
[6]
Liao GJ, Henze Bancroft LC, Strigel RM, et al. Background parenchymal enhancement on breast MRI: A comprehensive review. J Magn Reson Imaging 2020; 51(1): 43-61.
[http://dx.doi.org/10.1002/jmri.26762] [PMID: 31004391]
[7]
Kim JY, Cho N, Jeyanth JX, et al. Smaller reduction in 3D breast density associated with subsequent cancer recurrence in patients with breast cancer receiving adjuvant tamoxifen therapy. AJR Am J Roentgenol 2014; 202(4): 912-21.
[http://dx.doi.org/10.2214/AJR.13.11109] [PMID: 24660724]
[8]
Robinson B, Dijkstra B, Davey V, Tomlinson S, Frampton C. Adherence to adjuvant endocrine therapy in christchurch women with early breast cancer. Clinical Oncology 2018; 30(1): 9-15.
[http://dx.doi.org/10.1016/j.clon.2017.10.015]
[9]
Hu X, Jiang L, Li Q, Gu Y. Quantitative assessment of background parenchymal enhancement in breast magnetic resonance images predicts the risk of breast cancer. Oncotarget 2017; 8(6): 10620-7.
[http://dx.doi.org/10.18632/oncotarget.13538] [PMID: 27895314]
[10]
Wu S, Weinstein SP, DeLeo MJ III, et al. Quantitative assessment of background parenchymal enhancement in breast MRI predicts response to risk-reducing salpingo-oophorectomy: Preliminary evaluation in a cohort of BRCA1/2 mutation carriers. Breast Cancer Res 2015; 17(1): 67.
[http://dx.doi.org/10.1186/s13058-015-0577-0] [PMID: 25986460]
[11]
Wu S, Berg WA, Zuley ML, et al. Breast MRI contrast enhancement kinetics of normal parenchyma correlate with presence of breast cancer. Breast Cancer Res 2016; 18(1): 76.
[http://dx.doi.org/10.1186/s13058-016-0734-0] [PMID: 27449059]
[12]
Virostko J, Kuketz G, Higgins E, et al. The rate of breast fibroglandular enhancement during dynamic contrast-enhanced MRI reflects response to neoadjuvant therapy. Eur J Radiol 2021; 136: 109534.
[http://dx.doi.org/10.1016/j.ejrad.2021.109534] [PMID: 33454460]
[13]
Canty M. Fuzzy c-means clustering IDL code. 2004. Available from: https://comp.lang.idl-pvwave.narkive.com/BpMyro7J/fuzzy-c-means-clustering-idl-code
[14]
Dunn JC. A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters. J Cybern 1973; 3(3): 32-57.
[http://dx.doi.org/10.1080/01969727308546046]
[15]
Rakow-Penner R, Daniel B, Yu H, Sawyer-Glover A, Glover GH. Relaxation times of breast tissue at 1.5T and 3T measured using IDEAL. J Magn Reson Imaging 2006; 23(1): 87-91.
[http://dx.doi.org/10.1002/jmri.20469] [PMID: 16315211]
[16]
Medved M, Karczmar G, Yang C, et al. Semiquantitative analysis of dynamic contrast enhanced MRI in cancer patients: Variability and changes in tumor tissue over time. J Magn Reson Imaging 2004; 20(1): 122-8.
[http://dx.doi.org/10.1002/jmri.20061] [PMID: 15221817]
[17]
Shen Y, Goerner FL, Snyder C, et al. T1 relaxivities of gadolinium-based magnetic resonance contrast agents in human whole blood at 1.5, 3, and 7 T. Invest Radiol 2015; 50(5): 330-8.
[http://dx.doi.org/10.1097/RLI.0000000000000132] [PMID: 25658049]
[18]
Saha A, Grimm LJ, Ghate SV, et al. Machine learning-based prediction of future breast cancer using algorithmically measured background parenchymal enhancement on high-risk screening MRI. J Magn Reson Imaging 2019; 50(2): 456-64.
[http://dx.doi.org/10.1002/jmri.26636] [PMID: 30648316]
[19]
Bennani-Baiti B, Dietzel M, Baltzer PA. MRI background parenchymal enhancement is not associated with breast cancer. PLoS One 2016; 11(7): e0158573.
[http://dx.doi.org/10.1371/journal.pone.0158573] [PMID: 27379395]
[20]
Telegrafo M, Rella L, Stabile Ianora AA, Angelelli G, Moschetta M. Breast MRI background parenchymal enhancement (BPE) correlates with the risk of breast cancer. Magn Reson Imaging 2016; 34(2): 173-6.
[http://dx.doi.org/10.1016/j.mri.2015.10.014] [PMID: 26597834]
[21]
Pike MC, Pearce CL. Mammographic density, MRI background parenchymal enhancement and breast cancer risk. Annals of Oncology 2013; 24(Suppl 8): 37-41.
[22]
King V, Kaplan J, Pike MC, et al. Impact of tamoxifen on amount of fibroglandular tissue, background parenchymal enhancement, and cysts on breast magnetic resonance imaging. Breast J 2012; 18(6): 527-34.
[http://dx.doi.org/10.1111/tbj.12002] [PMID: 23002953]
[23]
King V, Goldfarb SB, Brooks JD, et al. Effect of aromatase inhibitors on background parenchymal enhancement and amount of fibroglandular tissue at breast MR imaging. Radiology 2012; 264(3): 670-8.
[http://dx.doi.org/10.1148/radiol.12112669] [PMID: 22771878]

© 2024 Bentham Science Publishers | Privacy Policy