Literature DB >> 18927299

Early changes in functional dynamic magnetic resonance imaging predict for pathologic response to neoadjuvant chemotherapy in primary breast cancer.

Mei-Lin W Ah-See1, Andreas Makris, N Jane Taylor, Mark Harrison, Paul I Richman, Russell J Burcombe, J James Stirling, James A d'Arcy, David J Collins, Michael R Pittam, Duraisamy Ravichandran, Anwar R Padhani.   

Abstract

PURPOSE: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) allows noninvasive, in vivo measurements of tissue microvessel perfusion and permeability. We examined whether DCE-MRI done after two cycles of neoadjuvant chemotherapy could predict final clinical and pathologic response in primary breast cancers. EXPERIMENTAL
DESIGN: Thirty-seven patients with primary breast cancer, due to receive six cycles of neoadjuvant 5-fluorouracil, epirubicin and cyclophosphamide chemotherapy, were examined using DCE-MRI before neoadjuvant chemotherapy and after two cycles of treatment. Changes in DCE-MRI kinetic parameters (K(trans), k(ep), v(e), MaxGd, rBV, rBF, MTT) were correlated with the final clinical and pathologic response to neoadjuvant chemotherapy. Test-retest variability was used to determine individual patient response.
RESULTS: Twenty-eight patients were evaluable for response (19 clinical responders and 9 nonresponders; 11 pathologic responders and 17 nonresponders). Changes in the DCE-MRI kinetic parameters K(trans), k(ep), MaxGd, rBV, and rBF were significantly correlated with both final clinical and pathologic response (P < 0.01). Change in K(trans) was the best predictor of pathologic nonresponse (area under the receiver operating characteristic curve, 0.93; sensitivity, 94%; specificity, 82%), correctly identifying 94% of nonresponders and 73% of responders. Change in MRI-derived tumor size did not predict for pathologic response.
CONCLUSION: Changes in breast tumor microvessel functionality as depicted by DCE-MRI early on after starting anthracycline-based neoadjuvant chemotherapy can predict final clinical and pathologic response. The ability to identify nonresponders early may allow the selection of patients who may benefit from a therapy change.

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Year:  2008        PMID: 18927299     DOI: 10.1158/1078-0432.CCR-07-4310

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  104 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

Review 2.  Diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for monitoring anticancer therapy.

Authors:  Anwar R Padhani; Aftab Alam Khan
Journal:  Target Oncol       Date:  2010-04-11       Impact factor: 4.493

Review 3.  Applications of molecular imaging.

Authors:  Craig J Galbán; Stefanie Galbán; Marcian E Van Dort; Gary D Luker; Mahaveer S Bhojani; Alnawaz Rehemtulla; Brian D Ross
Journal:  Prog Mol Biol Transl Sci       Date:  2010       Impact factor: 3.622

4.  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

Review 5.  Imaging-based tumor treatment response evaluation: review of conventional, new, and emerging concepts.

Authors:  Hee Kang; Ho Yun Lee; Kyung Soo Lee; Jae-Hun Kim
Journal:  Korean J Radiol       Date:  2012-06-18       Impact factor: 3.500

6.  Quantitative DCE-MRI for prediction of pathological complete response following neoadjuvant treatment for locally advanced breast cancer: the impact of breast cancer subtypes on the diagnostic accuracy.

Authors:  Stylianos Drisis; Thierry Metens; Michael Ignatiadis; Konstantinos Stathopoulos; Shih-Li Chao; Marc Lemort
Journal:  Eur Radiol       Date:  2015-08-27       Impact factor: 5.315

Review 7.  Preoperative imaging for staging bladder cancer.

Authors:  Maxim J McKibben; Michael E Woods
Journal:  Curr Urol Rep       Date:  2015-04       Impact factor: 3.092

8.  [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

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.  Host genetic modifiers of nonproductive angiogenesis inhibit breast cancer.

Authors:  Michael J Flister; Shirng-Wern Tsaih; Alexander Stoddard; Cody Plasterer; Jaidip Jagtap; Abdul K Parchur; Gayatri Sharma; Anthony R Prisco; Angela Lemke; Dana Murphy; Mona Al-Gizawiy; Michael Straza; Sophia Ran; Aron M Geurts; Melinda R Dwinell; Andrew S Greene; Carmen Bergom; Peter S LaViolette; Amit Joshi
Journal:  Breast Cancer Res Treat       Date:  2017-05-31       Impact factor: 4.872

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