Literature DB >> 17434070

Monitoring breast cancer response to neoadjuvant systemic chemotherapy using parametric contrast-enhanced MRI: a pilot study.

Chen-Pin Chou1, Ming-Ting Wu, Hong-Tai Chang, Yu-Shin Lo, Huay-Ben Pan, Hadassa Degani, Edna Furman-Haran.   

Abstract

RATIONALE AND
OBJECTIVES: Neoadjuvant systemic therapy (NST) is the standard treatment for locally advanced breast cancer and a common option for primary operable disease. It is important to develop standardized imaging techniques that can monitor and quantify response to NST enabling treatment tailored to each individual patient, and facilitating surgical planning. Here we present a high spatial resolution, parametric method based on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), which evaluates breast cancer response to NST.
MATERIALS AND METHODS: DCE-MRI examinations were performed twice on 17 breast cancer patients, before and after treatment. Seven sets of axial breast images were sequentially recorded at 1.5 Tesla applying a three-dimensional, gradient echo at a spatial resolution approximately 2 x 1.2 x 0.6 mm(3) and temporal resolution approximately 2 minutes, using gadopentate dimeglumine (0.1 mmol/kg wt). Image analysis was based on a color-coded scheme related to physiologic perfusion parameters.
RESULTS: A high Pearson correlation coefficient of 0.96 (P < .0001) was found between the histopathologic estimation of viable neoplastic tissue volume and the segmented volume of all the pixels demonstrating fast and steady state washout after NST (colored in light red and green). Segmentation of these pixels before and after NST indicated response in terms of reduced tumor volume and a parallel decrease in enhancement rate which reflects diminished transcapillary transfer of the contrast agent.
CONCLUSIONS: The use of a parametric MRI technique provided a means to standardize segmentation and quantify changes in the perfusion of breast neoplastic tissue in response to NST. Whether this technique can serve to predict breast cancer recurrence and survival rates requires further clinical testing.

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Year:  2007        PMID: 17434070     DOI: 10.1016/j.acra.2007.02.005

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  18 in total

1.  Multiparametric magnetic resonance imaging for predicting pathological response after the first cycle of neoadjuvant chemotherapy in breast cancer.

Authors:  Xia Li; Richard G Abramson; Lori R Arlinghaus; Hakmook Kang; Anuradha Bapsi Chakravarthy; Vandana G Abramson; Jaime Farley; Ingrid A Mayer; Mark C Kelley; Ingrid M Meszoely; Julie Means-Powell; Ana M Grau; Melinda Sanders; Thomas E Yankeelov
Journal:  Invest Radiol       Date:  2015-04       Impact factor: 6.016

2.  Simulation-based comparison of two approaches frequently used for dynamic contrast-enhanced MRI.

Authors:  Stefan Zwick; Gunnar Brix; Paul S Tofts; Ralph Strecker; Annette Kopp-Schneider; Hendrik Laue; Wolfhard Semmler; Fabian Kiessling
Journal:  Eur Radiol       Date:  2009-09-01       Impact factor: 5.315

3.  Implementation of a semi-automated post-processing system for parametric MRI mapping of human breast cancer.

Authors:  Robert E Lee; E Brian Welch; Jared G Cobb; Tuhin Sinha; John C Gore; Thomas E Yankeelov
Journal:  J Digit Imaging       Date:  2008-04-30       Impact factor: 4.056

4.  Combining multiparametric MRI with receptor information to optimize prediction of pathologic response to neoadjuvant therapy in breast cancer: preliminary results.

Authors:  Hakmook Kang; Allison Hainline; Lori R Arlinghaus; Stephanie Elderidge; Xia Li; Vandana G Abramson; Anuradha Bapsi Chakravarthy; Richard G Abramson; Brian Bingham; Kareem Fakhoury; Thomas E Yankeelov
Journal:  J Med Imaging (Bellingham)       Date:  2017-12-29

5.  Intratumor partitioning and texture analysis of dynamic contrast-enhanced (DCE)-MRI identifies relevant tumor subregions to predict pathological response of breast cancer to neoadjuvant chemotherapy.

Authors:  Jia Wu; Guanghua Gong; Yi Cui; Ruijiang Li
Journal:  J Magn Reson Imaging       Date:  2016-04-15       Impact factor: 4.813

6.  Statistical comparison of dynamic contrast-enhanced MRI pharmacokinetic models in human breast cancer.

Authors:  Xia Li; E Brian Welch; A Bapsi Chakravarthy; Lei Xu; Lori R Arlinghaus; Jaime Farley; Ingrid A Mayer; Mark C Kelley; Ingrid M Meszoely; Julie Means-Powell; Vandana G Abramson; Ana M Grau; John C Gore; Thomas E Yankeelov
Journal:  Magn Reson Med       Date:  2011-11-29       Impact factor: 4.668

7.  On the relationship between the apparent diffusion coefficient and extravascular extracellular volume fraction in human breast cancer.

Authors:  Lori R Arlinghaus; Xia Li; A Ridwan Rahman; E Brian Welch; Lei Xu; John C Gore; Thomas E Yankeelov
Journal:  Magn Reson Imaging       Date:  2011-04-29       Impact factor: 2.546

8.  Novel ultrasound and DCE-MRI analyses after antiangiogenic treatment with a selective VEGF receptor inhibitor.

Authors:  Katherine D Watson; Xiaowen Hu; Chun-Yen Lai; Heather A Lindfors; Dana D Hu-Lowe; Theresa A Tuthill; David R Shalinsky; Katherine W Ferrara
Journal:  Ultrasound Med Biol       Date:  2011-04-30       Impact factor: 2.998

9.  Analyzing Spatial Heterogeneity in DCE- and DW-MRI Parametric Maps to Optimize Prediction of Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer.

Authors:  Xia Li; Hakmook Kang; Lori R Arlinghaus; Richard G Abramson; A Bapsi Chakravarthy; Vandana G Abramson; Jaime Farley; Melinda Sanders; Thomas E Yankeelov
Journal:  Transl Oncol       Date:  2014-02-01       Impact factor: 4.243

10.  Current and emerging quantitative magnetic resonance imaging methods for assessing and predicting the response of breast cancer to neoadjuvant therapy.

Authors:  Richard G Abramson; Lori R Arlinghaus; Jared A Weis; Xia Li; Adrienne N Dula; Eduard Y Chekmenev; Seth A Smith; Michael I Miga; Vandana G Abramson; Thomas E Yankeelov
Journal:  Breast Cancer (Dove Med Press)       Date:  2012-10
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