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.
[http://dx.doi.org/10.1200/JCO.18.00378] [PMID: 30625040]
[http://dx.doi.org/10.1097/RCT.0000000000000774] [PMID: 30052617]
[http://dx.doi.org/10.1016/j.acra.2018.03.013] [PMID: 29602724]
[http://dx.doi.org/10.1148/radiol.2015142304] [PMID: 25965809]
[http://dx.doi.org/10.1148/radiol.11102156] [PMID: 21493794]
[http://dx.doi.org/10.1002/jmri.26762] [PMID: 31004391]
[http://dx.doi.org/10.2214/AJR.13.11109] [PMID: 24660724]
[http://dx.doi.org/10.1016/j.clon.2017.10.015]
[http://dx.doi.org/10.18632/oncotarget.13538] [PMID: 27895314]
[http://dx.doi.org/10.1186/s13058-015-0577-0] [PMID: 25986460]
[http://dx.doi.org/10.1186/s13058-016-0734-0] [PMID: 27449059]
[http://dx.doi.org/10.1016/j.ejrad.2021.109534] [PMID: 33454460]
[http://dx.doi.org/10.1080/01969727308546046]
[http://dx.doi.org/10.1002/jmri.20469] [PMID: 16315211]
[http://dx.doi.org/10.1002/jmri.20061] [PMID: 15221817]
[http://dx.doi.org/10.1097/RLI.0000000000000132] [PMID: 25658049]
[http://dx.doi.org/10.1002/jmri.26636] [PMID: 30648316]
[http://dx.doi.org/10.1371/journal.pone.0158573] [PMID: 27379395]
[http://dx.doi.org/10.1016/j.mri.2015.10.014] [PMID: 26597834]
[http://dx.doi.org/10.1111/tbj.12002] [PMID: 23002953]
[http://dx.doi.org/10.1148/radiol.12112669] [PMID: 22771878]