Literature DB >> 30179110

Diffusion-weighted MRI Findings Predict Pathologic Response in Neoadjuvant Treatment of Breast Cancer: The ACRIN 6698 Multicenter Trial.

Savannah C Partridge1, Zheng Zhang1, David C Newitt1, Jessica E Gibbs1, Thomas L Chenevert1, Mark A Rosen1, Patrick J Bolan1, Helga S Marques1, Justin Romanoff1, Lisa Cimino1, Bonnie N Joe1, Heidi R Umphrey1, Haydee Ojeda-Fournier1, Basak Dogan1, Karen Oh1, Hiroyuki Abe1, Jennifer S Drukteinis1, Laura J Esserman1, Nola M Hylton1.   

Abstract

Purpose To determine if the change in tumor apparent diffusion coefficient (ADC) at diffusion-weighted (DW) MRI is predictive of pathologic complete response (pCR) to neoadjuvant chemotherapy for breast cancer. Materials and Methods In this prospective multicenter study, 272 consecutive women with breast cancer were enrolled at 10 institutions (from August 2012 to January 2015) and were randomized to treatment with 12 weekly doses of paclitaxel (with or without an experimental agent), followed by 12 weeks of treatment with four cycles of anthracycline. Each woman underwent breast DW MRI before treatment, at early treatment (3 weeks), at midtreatment (12 weeks), and after treatment. Percentage change in tumor ADC from that before treatment (ΔADC) was measured at each time point. Performance for predicting pCR was assessed by using the area under the receiver operating characteristic curve (AUC) for the overall cohort and according to tumor hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) disease subtype. Results The final analysis included 242 patients with evaluable serial imaging data, with a mean age of 48 years ± 10 (standard deviation); 99 patients had HR-positive (hereafter, HR+)/HER2-negative (hereafter, HER2-) disease, 77 patients had HR-/HER2- disease, 42 patients had HR+/HER2+ disease, and 24 patients had HR-/HER2+ disease. Eighty (33%) of 242 patients experienced pCR. Overall, ΔADC was moderately predictive of pCR at midtreatment/12 weeks (AUC = 0.60; 95% confidence interval [CI]: 0.52, 0.68; P = .017) and after treatment (AUC = 0.61; 95% CI: 0.52, 0.69; P = .013). Across the four disease subtypes, midtreatment ΔADC was predictive only for HR+/HER2- tumors (AUC = 0.76; 95% CI: 0.62, 0.89; P < .001). In a test subset, a model combining tumor subtype and midtreatment ΔADC improved predictive performance (AUC = 0.72; 95% CI: 0.61, 0.83) over ΔADC alone (AUC = 0.57; 95% CI: 0.44, 0.70; P = .032.). Conclusion After 12 weeks of therapy, change in breast tumor apparent diffusion coefficient at MRI predicts complete pathologic response to neoadjuvant chemotherapy. © RSNA, 2018 Online supplemental material is available for this article.

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Year:  2018        PMID: 30179110      PMCID: PMC6283325          DOI: 10.1148/radiol.2018180273

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   29.146


  29 in total

Review 1.  Breast magnetic resonance imaging for monitoring response to therapy.

Authors:  Haydee Ojeda-Fournier; Jade de Guzman; Nola Hylton
Journal:  Magn Reson Imaging Clin N Am       Date:  2013-08       Impact factor: 2.266

2.  Diffusion-weighted MRI in pretreatment prediction of response to neoadjuvant chemotherapy in patients with breast cancer.

Authors:  Raphael Richard; Isabelle Thomassin; Marion Chapellier; Aurélie Scemama; Patricia de Cremoux; Mariana Varna; Sylvie Giacchetti; Marc Espié; Eric de Kerviler; Cedric de Bazelaire
Journal:  Eur Radiol       Date:  2013-05-08       Impact factor: 5.315

3.  Magnetic resonance imaging response monitoring of breast cancer during neoadjuvant chemotherapy: relevance of breast cancer subtype.

Authors:  Claudette E Loo; Marieke E Straver; Sjoerd Rodenhuis; Sara H Muller; Jelle Wesseling; Marie-Jeanne T F D Vrancken Peeters; Kenneth G A Gilhuijs
Journal:  J Clin Oncol       Date:  2011-01-10       Impact factor: 44.544

4.  Adaptive Randomization of Neratinib in Early Breast Cancer.

Authors:  John W Park; Minetta C Liu; Douglas Yee; Christina Yau; Laura J van 't Veer; W Fraser Symmans; Melissa Paoloni; Jane Perlmutter; Nola M Hylton; Michael Hogarth; Angela DeMichele; Meredith B Buxton; A Jo Chien; Anne M Wallace; Judy C Boughey; Tufia C Haddad; Stephen Y Chui; Kathleen A Kemmer; Henry G Kaplan; Claudine Isaacs; Rita Nanda; Debasish Tripathy; Kathy S Albain; Kirsten K Edmiston; Anthony D Elias; Donald W Northfelt; Lajos Pusztai; Stacy L Moulder; Julie E Lang; Rebecca K Viscusi; David M Euhus; Barbara B Haley; Qamar J Khan; William C Wood; Michelle Melisko; Richard Schwab; Teresa Helsten; Julia Lyandres; Sarah E Davis; Gillian L Hirst; Ashish Sanil; Laura J Esserman; Donald A Berry
Journal:  N Engl J Med       Date:  2016-07-07       Impact factor: 91.245

5.  Locally advanced breast cancer: MR imaging for prediction of response to neoadjuvant chemotherapy--results from ACRIN 6657/I-SPY TRIAL.

Authors:  Nola M Hylton; Jeffrey D Blume; Wanda K Bernreuter; Etta D Pisano; Mark A Rosen; Elizabeth A Morris; Paul T Weatherall; Constance D Lehman; Gillian M Newstead; Sandra Polin; Helga S Marques; Laura J Esserman; Mitchell D Schnall
Journal:  Radiology       Date:  2012-06       Impact factor: 11.105

6.  Role of the Apparent Diffusion Coefficient in the Prediction of Response to Neoadjuvant Chemotherapy in Patients With Locally Advanced Breast Cancer.

Authors:  Enida Bufi; Paolo Belli; Melania Costantini; Antonio Cipriani; Marialuisa Di Matteo; Angelo Bonatesta; Gianluca Franceschini; Daniela Terribile; Antonino Mulé; Luigia Nardone; Lorenzo Bonomo
Journal:  Clin Breast Cancer       Date:  2015-02-21       Impact factor: 3.225

7.  Neoadjuvant Chemotherapy for Breast Cancer: Functional Tumor Volume by MR Imaging Predicts Recurrence-free Survival-Results from the ACRIN 6657/CALGB 150007 I-SPY 1 TRIAL.

Authors:  Nola M Hylton; Constantine A Gatsonis; Mark A Rosen; Constance D Lehman; David C Newitt; Savannah C Partridge; Wanda K Bernreuter; Etta D Pisano; Elizabeth A Morris; Paul T Weatherall; Sandra M Polin; Gillian M Newstead; Helga S Marques; Laura J Esserman; Mitchell D Schnall
Journal:  Radiology       Date:  2015-12-01       Impact factor: 11.105

8.  Diffusion-Weighted Breast Magnetic Resonance Imaging: A Semiautomated Voxel Selection Technique Improves Interreader Reproducibility of Apparent Diffusion Coefficient Measurements.

Authors:  Habib Rahbar; Brenda F Kurland; Matthew L Olson; Averi E Kitsch; John R Scheel; Xiaoyu Chai; Joshua Usoro; Constance D Lehman; Savannah C Partridge
Journal:  J Comput Assist Tomogr       Date:  2016 May-Jun       Impact factor: 1.826

9.  The role of mean diffusivity (MD) as a predictive index of the response to chemotherapy in locally advanced breast cancer: a preliminary study.

Authors:  Chiara Iacconi; Marco Giannelli; Carolina Marini; Anna Cilotti; Monica Moretti; Paolo Viacava; Eugenia Picano; Andrea Michelotti; Davide Caramella
Journal:  Eur Radiol       Date:  2009-09-17       Impact factor: 5.315

10.  Measurement of residual breast cancer burden to predict survival after neoadjuvant chemotherapy.

Authors:  W Fraser Symmans; Florentia Peintinger; Christos Hatzis; Radhika Rajan; Henry Kuerer; Vicente Valero; Lina Assad; Anna Poniecka; Bryan Hennessy; Marjorie Green; Aman U Buzdar; S Eva Singletary; Gabriel N Hortobagyi; Lajos Pusztai
Journal:  J Clin Oncol       Date:  2007-09-04       Impact factor: 44.544

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  61 in total

Review 1.  [Diffusion-weighted imaging-diagnostic supplement or alternative to contrast agents in early detection of malignancies?]

Authors:  S Bickelhaupt; C Dreher; F König; K Deike-Hofmann; D Paech; H P Schlemmer; T A Kuder
Journal:  Radiologe       Date:  2019-06       Impact factor: 0.635

Review 2.  MRI Performance in Detecting pCR After Neoadjuvant Chemotherapy by Molecular Subtype of Breast Cancer.

Authors:  Nancy Yu; Vivian W Y Leung; Sarkis Meterissian
Journal:  World J Surg       Date:  2019-09       Impact factor: 3.352

3.  Additive value of diffusion-weighted MRI in the I-SPY 2 TRIAL.

Authors:  Wen Li; David C Newitt; Lisa J Wilmes; Ella F Jones; Vignesh Arasu; Jessica Gibbs; Bo La Yun; Elizabeth Li; Savannah C Partridge; John Kornak; Laura J Esserman; Nola M Hylton
Journal:  J Magn Reson Imaging       Date:  2019-04-26       Impact factor: 4.813

4.  MRI does not predict pathologic complete response after neoadjuvant chemotherapy for breast cancer.

Authors:  Stephen F Sener; Rachel E Sargent; Connie Lee; Tejas Manchandia; Vivian Le-Tran; Yuliya Olimpiadi; Nicole Zaremba; Andrew Alabd; Maria Nelson; Julie E Lang
Journal:  J Surg Oncol       Date:  2019-08-09       Impact factor: 3.454

5.  Radiomics methodology for breast cancer diagnosis using multiparametric magnetic resonance imaging.

Authors:  Qiyuan Hu; Heather M Whitney; Maryellen L Giger
Journal:  J Med Imaging (Bellingham)       Date:  2020-08-24

6.  Test-retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial.

Authors:  David C Newitt; Zheng Zhang; Jessica E Gibbs; Savannah C Partridge; Thomas L Chenevert; Mark A Rosen; Patrick J Bolan; Helga S Marques; Sheye Aliu; Wen Li; Lisa Cimino; Bonnie N Joe; Heidi Umphrey; Haydee Ojeda-Fournier; Basak Dogan; Karen Oh; Hiroyuki Abe; Jennifer Drukteinis; Laura J Esserman; Nola M Hylton
Journal:  J Magn Reson Imaging       Date:  2018-10-22       Impact factor: 4.813

Review 7.  Imaging for Response Assessment in Cancer Clinical Trials.

Authors:  Anna G Sorace; Asser A Elkassem; Samuel J Galgano; Suzanne E Lapi; Benjamin M Larimer; Savannah C Partridge; C Chad Quarles; Kirsten Reeves; Tiara S Napier; Patrick N Song; Thomas E Yankeelov; Stefanie Woodard; Andrew D Smith
Journal:  Semin Nucl Med       Date:  2020-06-10       Impact factor: 4.446

8.  Retrospective Correction of ADC for Gradient Nonlinearity Errors in Multicenter Breast DWI Trials: ACRIN6698 Multiplatform Feasibility Study.

Authors:  Dariya I Malyarenko; David C Newitt; Ghoncheh Amouzandeh; Lisa J Wilmes; Ek T Tan; Luca Marinelli; Ajit Devaraj; Johannes M Peeters; Shivraman Giri; Axel Vom Endt; Nola M Hylton; Savannah C Partridge; Thomas L Chenevert
Journal:  Tomography       Date:  2020-06

9.  Nyquist ghost correction of breast diffusion weighted imaging using referenceless methods.

Authors:  Jessica A McKay; Steen Moeller; Lei Zhang; Edward J Auerbach; Michael T Nelson; Patrick J Bolan
Journal:  Magn Reson Med       Date:  2018-11-02       Impact factor: 4.668

10.  A Comparison of Methods for High-Spatial-Resolution Diffusion-weighted Imaging in Breast MRI.

Authors:  Jessica A McKay; An L Church; Nathan Rubin; Tim H Emory; Noelle F Hoven; Jessica E Kuehn-Hajder; Michael T Nelson; Sudhir Ramanna; Edward J Auerbach; Steen Moeller; Patrick J Bolan
Journal:  Radiology       Date:  2020-08-25       Impact factor: 11.105

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