Integration of Quantitative DCE-MRI and ADC Mapping to Monitor Treatment Response in Human Breast Cancer: Initial Results

Overview

Journal Magn Reson Imaging

Publisher Elsevier

Specialty Radiology

Date 2007 Jan 16

PMID 17222711

Citations 160

Authors

Thomas E Yankeelov

Martin Lepage

Anuradha Chakravarthy

Elizabeth E Broome

Kenneth J Niermann

Mark C Kelley

Ingrid Meszoely

Ingrid A Mayer

Cheryl R Herman

Kevin McManus

Ronald R Price

John C Gore

Affiliations

Soon will be listed here.

Abstract

Purpose: The objective of this study was to assess changes in the water apparent diffusion coefficient (ADC) and in pharmacokinetic parameters obtained from the fast-exchange regime (FXR) modeling of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) during neoadjuvant chemotherapy in breast cancer.

Materials And Methods: Eleven patients with locally advanced breast cancer underwent MRI examination prior to and after chemotherapy but prior to surgery. A 1.5-T scanner was used to obtain T1, ADC and DCE-MRI data. DCE-MRI data were analyzed by the FXR model returning estimates of K(trans) (volume transfer constant), v(e) (extravascular extracellular volume fraction) and tau(i) (average intracellular water lifetime). Histogram and correlation analyses assessed parameter changes post-treatment.

Results: Significant (P < .05) changes or trends towards significance (P < .10) were seen in all parameters except tau(i), although there was qualitative reduction in tau(i) values post-treatment. In particular, there was reduction (P < .035) in voxels with K(trans) values in the range 0.2-0.5 min(-1) and a decrease (P < .05) in voxels with ADC values in the range 0.99 x 10(-3) to 1.35 x 10(-3) mm2/s. ADC and v(e) were negatively correlated (r = -.60, P < .02). Parameters sensitive to water distribution and geometry (T(1), v(e), tau(i) and ADC) correlated with a multivariable linear regression model.

Conclusion: The analysis presented here is sensitive to longitudinal changes in breast tumor status; K(trans) and ADC are most sensitive to these changes. Relationships between parameters provide information on water distribution and geometry in the tumor environment.

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