Literature DB >> 25805427

Prediction of pathological complete response to neoadjuvant chemotherapy by magnetic resonance imaging in breast cancer patients.

Shintaro Michishita1, Seung Jin Kim2, Kenzo Shimazu1, Yoshiaki Sota1, Yasuto Naoi1, Naomi Maruyama1, Naofumi Kagara1, Masafumi Shimoda1, Atsushi Shimomura1, Shinzaburo Noguchi1.   

Abstract

The purpose of this study was to evaluate whether the baseline breast MRI findings would be useful for the prediction for pathological complete response (pCR) by breast cancer patients to neoadjuvant chemotherapy. Primary breast cancer patients (stage II-III) preoperatively treated with sequential paclitaxel (12 cycles) and fluorouracil, epirubicin, and cyclophosphamide (4 cycles), followed by surgery were retrospectively enrolled, and 229 patients were eligible. Before chemotherapy, breast MRI studies were performed. Breast tumors were dichotomized into round + oval and irregular types based on MRI morphology. The round + oval tumors showed a significantly higher pCR rate than the irregular tumors (42.0% vs 17.3%; P < 0.001). In addition, PAM50 analysis revealed that basal and HER2-enriched tumors were significantly more prevalent among round + oval than irregular type tumors (P = 0.015). Baseline MRI morphology appears to be a significant predictor for pCR. The higher rate of the basal and HER2-enriched tumors among the round + oval tumors may explain their better chemo-sensitivity.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Intrinsic subtype; MRI morphology; Neoadjuvant chemotherapy; Predictor; pCR

Mesh:

Substances:

Year:  2015        PMID: 25805427     DOI: 10.1016/j.breast.2015.01.001

Source DB:  PubMed          Journal:  Breast        ISSN: 0960-9776            Impact factor:   4.380


  8 in total

Review 1.  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

2.  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

3.  Prediction of pathologic complete response on MRI in patients with breast cancer receiving neoadjuvant chemotherapy according to molecular subtypes.

Authors:  Jieun Kim; Boo-Kyung Han; Eun Young Ko; Eun Sook Ko; Ji Soo Choi; Ko Woon Park
Journal:  Eur Radiol       Date:  2022-01-06       Impact factor: 5.315

4.  Role of Magnetic Resonance Imaging in the Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy.

Authors:  Giorgia Pasquero; Alessandra Surace; Antonio Ponti; Massimiliano Bortolini; Donatella Tota; Maria Piera Mano; Riccardo Arisio; Chiara Benedetto; Maria Grazia Baù
Journal:  In Vivo       Date:  2020 Mar-Apr       Impact factor: 2.155

5.  Early ultrasound evaluation identifies excellent responders to neoadjuvant systemic therapy among patients with triple-negative breast cancer.

Authors:  Beatriz E Adrada; Rosalind Candelaria; Stacy Moulder; Alastair Thompson; Peng Wei; Gary J Whitman; Vicente Valero; Jennifer K Litton; Lumarie Santiago; Marion E Scoggins; Tanya W Moseley; Jason B White; Elizabeth E Ravenberg; Wei T Yang; Gaiane M Rauch
Journal:  Cancer       Date:  2021-04-20       Impact factor: 6.921

6.  Application of imaging mass spectrometry for the molecular diagnosis of human breast tumors.

Authors:  Xinxin Mao; Jiuming He; Tiegang Li; Zhaohui Lu; Jian Sun; Yunxiao Meng; Zeper Abliz; Jie Chen
Journal:  Sci Rep       Date:  2016-02-12       Impact factor: 4.379

7.  Early response by MR imaging and ultrasound as predictor of pathologic complete response to 12-week neoadjuvant therapy for different early breast cancer subtypes: Combined analysis from the WSG ADAPT subtrials.

Authors:  Monika Graeser; Simone Schrading; Oleg Gluz; Kevin Strobel; Rachel Würstlein; Sherko Kümmel; Claudia Schumacher; Eva-Maria Grischke; Helmut Forstbauer; Michael Braun; Matthias Christgen; Jascha Adams; Henrik Nitzsche; Marianne Just; Hans Holger Fischer; Bahriye Aktas; Jochem Potenberg; Raquel von Schumann; Cornelia Kolberg-Liedtke; Nadia Harbeck; Christiane K Kuhl; Ulrike Nitz
Journal:  Int J Cancer       Date:  2021-02-03       Impact factor: 7.396

8.  Highly accurate response prediction in high-risk early breast cancer patients using a biophysical simulation platform.

Authors:  John A Cole; Rita Nanda; Frederick M Howard; Gong He; Joseph R Peterson; J R Pfeiffer; Tyler Earnest; Alexander T Pearson; Hiroyuki Abe
Journal:  Breast Cancer Res Treat       Date:  2022-09-05       Impact factor: 4.624

  8 in total

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