Magnetic resonance imaging contrast-enhanced relaxometry of breast tumors: an MRI multicenter investigation concerning 100 patients
- PMID: 15120166
- DOI: 10.1016/j.mri.2004.01.024
Magnetic resonance imaging contrast-enhanced relaxometry of breast tumors: an MRI multicenter investigation concerning 100 patients
Abstract
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using extracellular contrast agents has proved to be useful for the characterization of breast tumors. DCE-MRI has demonstrated a high sensitivity (around 95%) but a rather poor and controversial specificity, varying, according to the different studies, from 45% to 90%. In order to increase (a) the specificity and (b) the robustness of this quantitative approach in multicenter evaluation (five MRI units), a quantitative approach called dynamic relaxometry has been developed. According to the proposed method, the time-dependent longitudinal relaxation rate measured on region of interest of the lesion was calculated during the contrast uptake, after intravenous bolus injection of contrast agent. A specifically developed method was used for fast R(1) measurements. Relaxometry time curves are fitted to the Tofts model allowing the measurement of the parameters describing the enhancement curve (maximum relation rate enhancement, initial, 30-s and 60-s slopes) and the tissue parameters [transfer constant (K(trans) min(-1)) and extracellular extravascular space fraction (v(e))]. Correspondence factorial analysis followed by hierarchical ascendant classification are then performed on the different parameters. Higher K(trans) values were observed in infiltrative ductal carcinomas than in infiltrative lobular carcinomas, in agreement with data published by other groups. Specificity of DCE-MRI has been increased up to 85%, with a sensitivity of 95% with K(trans)/v(e) and enhancement index I (ratio of initial slope by maximum relaxation rate enhancement). A multiparametric data analysis of the calculated parameters opens the way to include quantitative image-based information in new nosologic approaches to breast tumors.
Similar articles
-
Can breast MRI computer-aided detection (CAD) improve radiologist accuracy for lesions detected at MRI screening and recommended for biopsy in a high-risk population?Clin Radiol. 2009 Dec;64(12):1166-74. doi: 10.1016/j.crad.2009.08.003. Epub 2009 Oct 21. Clin Radiol. 2009. PMID: 19913125
-
Feature extraction and classification of dynamic contrast-enhanced T2*-weighted breast image data.IEEE Trans Med Imaging. 2001 Dec;20(12):1293-301. doi: 10.1109/42.974924. IEEE Trans Med Imaging. 2001. PMID: 11811829
-
Magnetic resonance imaging measurements of vascular permeability and extracellular volume fraction of breast tumors by dynamic Gd-DTPA-enhanced relaxometry.Magn Reson Imaging. 2007 Apr;25(3):293-302. doi: 10.1016/j.mri.2006.10.016. Epub 2006 Dec 6. Magn Reson Imaging. 2007. PMID: 17371717
-
Functional tumor imaging with dynamic contrast-enhanced magnetic resonance imaging.J Magn Reson Imaging. 2003 May;17(5):509-20. doi: 10.1002/jmri.10304. J Magn Reson Imaging. 2003. PMID: 12720260 Review.
-
Unusual malignant tumors of the breast: MRI features and pathologic correlation.Eur J Radiol. 2010 Aug;75(2):178-84. doi: 10.1016/j.ejrad.2009.04.038. Epub 2009 May 14. Eur J Radiol. 2010. PMID: 19446418 Review.
Cited by
-
Molecular MR Imaging Probes.Proc IEEE Inst Electr Electron Eng. 2005 Apr;93(4):800-808. doi: 10.1109/JPROC.2005.844264. Proc IEEE Inst Electr Electron Eng. 2005. PMID: 19194516 Free PMC article.
-
A clinically feasible method to estimate pharmacokinetic parameters in breast cancer.Med Phys. 2009 Aug;36(8):3786-94. doi: 10.1118/1.3152113. Med Phys. 2009. PMID: 19746812 Free PMC article.
-
Automatic segmentation of invasive breast carcinomas from dynamic contrast-enhanced MRI using time series analysis.J Magn Reson Imaging. 2014 Aug;40(2):467-75. doi: 10.1002/jmri.24394. Epub 2013 Sep 23. J Magn Reson Imaging. 2014. PMID: 24115175 Free PMC article.
-
Can dynamic contrast-enhanced magnetic resonance imaging combined with texture analysis differentiate malignant glioneuronal tumors from other glioblastoma?Neurol Res Int. 2012;2012:195176. doi: 10.1155/2012/195176. Epub 2011 Dec 1. Neurol Res Int. 2012. PMID: 22203901 Free PMC article.
-
Comparison of three physiologically-based pharmacokinetic models for the prediction of contrast agent distribution measured by dynamic MR imaging.J Magn Reson Imaging. 2008 Jun;27(6):1388-98. doi: 10.1002/jmri.21344. J Magn Reson Imaging. 2008. PMID: 18504759 Free PMC article.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Medical
Miscellaneous