Journal Article
. 2007 Dec;81(962).
doi: 10.1259/bjr/98435332.

Measurement of pharmacokinetic parameters in histologically graded invasive breast tumours using dynamic contrast-enhanced MRI

A Radjenovic 1 B J Dall  J P Ridgway  M A Smith  
Affiliations
  • PMID: 18070824
  •     15 citations

Abstract

Dynamic contrast-enhanced MRI (DCE-MRI) has demonstrated high sensitivity for detection of breast cancer. Analysis of correlation between quantitative DCE-MRI findings and prognostic factors (such as histological tumour grade) is important for defining the role of this technique in the diagnosis of breast cancer as well as the monitoring of neoadjuvant therapies. This paper presents a practical clinical application of a quantitative pharmacokinetic model to study histologically confirmed and graded invasive human breast tumours. The hypothesis is that, given a documented difference in capillary permeability between benign and malignant breast tumours, a relationship between permeability-related DCE-MRI parameters and tumour aggressiveness persists within invasive breast carcinomas. In addition, it was hypothesized that pharmacokinetic parameters may demonstrate stronger correlation with prognostic factors than the more conventional black-box techniques, so a comparison was undertaken. Significant correlations were found between pharmacokinetic and black-box parameters in 59 invasive breast carcinomas. However, statistically significant variation with tumour grade was demonstrated in only two permeability-related pharmacokinetic parameters: k(ep) (p<0.05) and K(trans) (p<0.05), using one-way analysis of variance. Parameters k(ep) and K(trans) were significantly higher in Grade 3 tumours than in low-grade tumours. None of the measured DCE-MRI parameters varied significantly between Grade 1 and Grade 2 tumours. Measurement of k(ep) and K(trans) might therefore be used to monitor the effectiveness of neoadjuvant treatment of high-grade invasive breast carcinomas, but is unlikely to demonstrate remission in low-grade tumours.

Temporal sampling requirements for reference region modeling of DCE-MRI data in human breast cancer.
Catherine R Planey, E Brian Welch, +9 authors, Thomas E Yankeelov.
J Magn Reson Imaging, 2009 Jun 27; 30(1). PMID: 19557727    Free PMC article.
Pharmacokinetic mapping for lesion classification in dynamic breast MRI.
Matthias C Schabel, Glen R Morrell, +3 authors, Leigh A Neumayer.
J Magn Reson Imaging, 2010 Jun 01; 31(6). PMID: 20512889    Free PMC article.
Use of a reference tissue and blood vessel to measure the arterial input function in DCEMRI.
Xiaobing Fan, Chad R Haney, +4 authors, Gregory S Karczmar.
Magn Reson Med, 2010 Jul 29; 64(6). PMID: 20665893    Free PMC article.
Magnetic resonance in the era of molecular imaging of cancer.
John C Gore, H Charles Manning, +2 authors, Thomas E Yankeelov.
Magn Reson Imaging, 2011 Apr 29; 29(5). PMID: 21524870    Free PMC article.
Review.
3-T dynamic contrast-enhanced MRI of the breast: pharmacokinetic parameters versus conventional kinetic curve analysis.
Riham H El Khouli, Katarzyna J Macura, +2 authors, David A Bluemke.
AJR Am J Roentgenol, 2011 Nov 24; 197(6). PMID: 22109308    Free PMC article.
Inhibition of SUR1 decreases the vascular permeability of cerebral metastases.
Eric M Thompson, Gregory L Pishko, Leslie L Muldoon, Edward A Neuwelt.
Neoplasia, 2013 May 02; 15(5). PMID: 23633925    Free PMC article.
Statistical Learning Algorithm for in situ and invasive breast carcinoma segmentation.
Jagadeesan Jayender, Eva Gombos, +3 authors, Kirby G Vosburgh.
Comput Med Imaging Graph, 2013 May 23; 37(4). PMID: 23693000    Free PMC article.
Using dynamic contrast-enhanced magnetic resonance imaging data to constrain a positron emission tomography kinetic model: theory and simulations.
Jacob U Fluckiger, Xia Li, +3 authors, Thomas E Yankeelov.
Int J Biomed Imaging, 2013 Nov 14; 2013. PMID: 24222761    Free PMC article.
Is there any correlation between model-based perfusion parameters and model-free parameters of time-signal intensity curve on dynamic contrast enhanced MRI in breast cancer patients?
Boram Yi, Doo Kyoung Kang, +4 authors, Tae Hee Kim.
Eur Radiol, 2014 Feb 21; 24(5). PMID: 24553785
Modeling the effect of intra-voxel diffusion of contrast agent on the quantitative analysis of dynamic contrast enhanced magnetic resonance imaging.
Stephanie L Barnes, C Chad Quarles, Thomas E Yankeelov.
PLoS One, 2014 Oct 03; 9(9). PMID: 25275536    Free PMC article.
Automatic Segmentation of Breast Carcinomas from DCE-MRI using a Statistical Learning Algorithm.
J Jayender, K G Vosburgh, +5 authors, K Pohl.
Proc IEEE Int Symp Biomed Imaging, 2012 May 01; 2012. PMID: 28603582    Free PMC article.
Quantitative evaluation of contrast agent uptake in standard fat-suppressed dynamic contrast-enhanced MRI examinations of the breast.
Evanthia Kousi, Joely Smith, +7 authors, Maria A Schmidt.
Med Phys, 2017 Nov 03; 45(1). PMID: 29095484    Free PMC article.
Magnetic Resonance Angiography Shows Increased Arterial Blood Supply Associated with Murine Mammary Cancer.
Devkumar Mustafi, Abby Leinroth, +5 authors, Gregory S Karczmar.
Int J Biomed Imaging, 2019 Feb 23; 2019. PMID: 30792738    Free PMC article.
Integrated Multiparametric Radiomics and Informatics System for Characterizing Breast Tumor Characteristics with the OncotypeDX Gene Assay.
Michael A Jacobs, Christopher B Umbricht, +5 authors, Antonio C Wolff.
Cancers (Basel), 2020 Oct 01; 12(10). PMID: 32992569    Free PMC article.
Pharmacokinetic Analysis of Dynamic Contrast-Enhanced Magnetic Resonance Imaging at 7T for Breast Cancer Diagnosis and Characterization.
R Elena Ochoa-Albiztegui, Varadan Sevilimedu, +6 authors, Katja Pinker.
Cancers (Basel), 2020 Dec 18; 12(12). PMID: 33327532    Free PMC article.