Literature DB >> 15868426

Role of dynamic contrast enhanced MRI in monitoring early response of locally advanced breast cancer to neoadjuvant chemotherapy.

Martin D Pickles1, Martin Lowry, David J Manton, Peter Gibbs, Lindsay W Turnbull.   

Abstract

Neoadjuvant chemotherapy has become the standard treatment for patients with locally advanced breast cancer; however a technique that can accurately differentiate responders from non-responders at an early time point during treatment has still to be identified. The purpose of this work was to evaluate the ability of pharmacokinetically modelled dynamic contrast-enhanced MRI data to predict and monitor response of patients diagnosed with locally advanced breast cancer to neoadjuvant chemotherapy, at an early time point during treatment. Sixty-eight patients with histology proven breast cancer underwent MRI examination prior to treatment, early during treatment and following the final cycle of chemotherapy. A two compartment pharmacokinetic model provided the kinetic parameters transfer constant (Ktrans), rate constant (Kep) and extracellular extravascular space (Ve) for a region of interest encompassing the whole lesion (ROIwhole) and a 3x3 pixel 'hot-spot' showing the greatest mean maximum percentage enhancement from within that region (ROIhs). Following treatment 48 patients were classified as responders and 20 as non-responders based on total tumour volume reduction. Tumour volume changes between the pre-treatment and early treatment time points demonstrated differences between responders and non-responders with percentage change revealing the most significant result (p<0.001). Analysis based on ROIhs provided more statistically significant differences between responders and non-responders then ROIwhole analysis. ROIhs analysis demonstrated differences between responders and non-responders both prior to and early during treatment. A highly significant reduction in both Ktrans and Kep (p<0.001) was noted for responders between the pre-treatment and early treatment time points, while Ve significantly increased during the same time period for non-responders (p<0.001). Quantification of dynamic contrast enhancement parameters provides a potential means for differentiating responders from non-responders early during their treatment, thereby allowing a prompt change in treatment if necessary.

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Year:  2005        PMID: 15868426     DOI: 10.1007/s10549-004-5819-2

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  64 in total

1.  A feasible high spatiotemporal resolution breast DCE-MRI protocol for clinical settings.

Authors:  Luminita A Tudorica; Karen Y Oh; Nicole Roy; Mark D Kettler; Yiyi Chen; Stephanie L Hemmingson; Aneela Afzal; John W Grinstead; Gerhard Laub; Xin Li; Wei Huang
Journal:  Magn Reson Imaging       Date:  2012-07-06       Impact factor: 2.546

2.  Integration of quantitative DCE-MRI and ADC mapping to monitor treatment response in human breast cancer: initial results.

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
Journal:  Magn Reson Imaging       Date:  2006-11-21       Impact factor: 2.546

3.  Indications for breast magnetic resonance imaging. Consensus document "Attualità in senologia", Florence 2007.

Authors:  F Sardanelli; G M Giuseppetti; G Canavese; L Cataliotti; S Corcione; E Cossu; M Federico; L Marotti; L Martincich; P Panizza; F Podo; M Rosselli Del Turco; C Zuiani; C Alfano; M Bazzocchi; P Belli; S Bianchi; A Cilotti; M Calabrese; L Carbonaro; L Cortesi; C Di Maggio; A Del Maschio; A Esseridou; A Fausto; M Gennaro; R Girometti; R Ienzi; A Luini; S Manoukian; S Morassutt; D Morrone; J Nori; A Orlacchio; F Pane; P Panzarola; R Ponzone; G Simonetti; P Torricelli; G Valeri
Journal:  Radiol Med       Date:  2008-10-16       Impact factor: 3.469

4.  Three-dimensional Image-based Mechanical Modeling for Predicting the Response of Breast Cancer to Neoadjuvant Therapy.

Authors:  Jared A Weis; Michael I Miga; Thomas E Yankeelov
Journal:  Comput Methods Appl Mech Eng       Date:  2016-09-01       Impact factor: 6.756

5.  Usefulness of dynamic contrast-enhanced magnetic resonance imaging for predicting treatment response to vinorelbine-cisplatin with or without recombinant human endostatin in bone metastasis of non-small cell lung cancer.

Authors:  Rui Zhang; Zhi-Yu Wang; Yue-Hua Li; Yao-Hong Lu; Shuai Wang; Wen-Xi Yu; Hui Zhao
Journal:  Am J Cancer Res       Date:  2016-12-01       Impact factor: 6.166

6.  Uncertainty and bias in contrast concentration measurements using spoiled gradient echo pulse sequences.

Authors:  Matthias C Schabel; Dennis L Parker
Journal:  Phys Med Biol       Date:  2008-04-17       Impact factor: 3.609

7.  [Therapy monitoring of neoadjuvant therapy with MRI. RECIST and functional imaging].

Authors:  S Grandl; M Ingrisch; K Hellerhoff
Journal:  Radiologe       Date:  2014-03       Impact factor: 0.635

8.  Comparison of the diagnostic performance of response evaluation criteria in solid tumor 1.0 with response evaluation criteria in solid tumor 1.1 on MRI in advanced breast cancer response evaluation to neoadjuvant chemotherapy.

Authors:  Su Kyung Jeh; Sung Hun Kim; Bong Joo Kang
Journal:  Korean J Radiol       Date:  2012-12-28       Impact factor: 3.500

9.  A diffusion-compensated model for the analysis of DCE-MRI data: theory, simulations and experimental results.

Authors:  Jacob U Fluckiger; Mary E Loveless; Stephanie L Barnes; Martin Lepage; Thomas E Yankeelov
Journal:  Phys Med Biol       Date:  2013-03-04       Impact factor: 3.609

Review 10.  Multiparametric MR Imaging of Breast Cancer.

Authors:  Habib Rahbar; Savannah C Partridge
Journal:  Magn Reson Imaging Clin N Am       Date:  2016-02       Impact factor: 2.266

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