Literature DB >> 20455064

Neoadjuvant chemotherapy for breast cancer: correlation between the baseline MR imaging findings and responses to therapy.

Takayoshi Uematsu1, Masako Kasami, Sachiko Yuen.   

Abstract

OBJECTIVE: To retrospectively evaluate the magnetic resonance (MR) imaging findings of breast cancer before neoadjuvant chemotherapy (NAC) and to compare findings of chemosensitive breast cancer with those of chemoresistant breast cancer.
METHODS: The MR imaging findings before NAC in 120 women undergoing NAC were reviewed. The MR imaging findings were compared with the pathological findings and responses.
RESULTS: A complete response (pCR) and marked response were achieved in 12 and 35% of 120 breast cancers in 120 women respectively. Breast cancers with a pCR or marked response were classified as chemosensitive breast cancer. The remaining 64 breast cancers (53%) were classified as chemoresistant breast cancer. Large tumour size, a lesion without mass effect, and very high intratumoural signal intensity on T2-weighted MR images were significantly associated with chemoresistant breast cancer. Lesions with mass effect and washout enhancement pattern were significantly associated with chemosensitive breast cancer. Areas with very high intratumoural signal intensity on T2-weighted images corresponded pathologically to areas of intratumoural necrosis.
CONCLUSION: Several MR imaging features of breast cancer before NAC can help predict the efficacy of NAC.

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Year:  2010        PMID: 20455064     DOI: 10.1007/s00330-010-1813-8

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  25 in total

1.  MRI of breast cancer: influence of chemotherapy on sensitivity.

Authors:  A Rieber; H Zeitler; H Rosenthal; J Görich; R Kreienberg; H J Brambs; R Tomczak
Journal:  Br J Radiol       Date:  1997-05       Impact factor: 3.039

2.  Preoperative evaluation of residual tumor extent by three-dimensional magnetic resonance imaging in breast cancer patients treated with neoadjuvant chemotherapy.

Authors:  Kenji Akazawa; Yasuhiro Tamaki; Tetsuya Taguchi; Yoshio Tanji; Yasuo Miyoshi; Seung Jin Kim; Satsuki Ueda; Tetsu Yanagisawa; Yoshinobu Sato; Shinichi Tamura; Shinzaburo Noguchi
Journal:  Breast J       Date:  2006 Mar-Apr       Impact factor: 2.431

3.  Histopathological criteria for assessment of therapeutic response in breast cancer (2007 version).

Authors:  Masafumi Kurosumi; Sadako Akashi-Tanaka; Futoshi Akiyama; Yoshifumi Komoike; Hirofumi Mukai; Seigo Nakamura; Hitoshi Tsuda
Journal:  Breast Cancer       Date:  2008       Impact factor: 4.239

4.  Accuracy of MR imaging for revealing residual breast cancer in patients who have undergone neoadjuvant chemotherapy.

Authors:  Savannah C Partridge; Jessica E Gibbs; Ying Lu; Laura J Esserman; Dan Sudilovsky; Nola M Hylton
Journal:  AJR Am J Roentgenol       Date:  2002-11       Impact factor: 3.959

5.  Contrast-Enhanced Magnetic Resonance Imaging to Assess Tumor Histopathology and Angiogenesis in Breast Carcinoma.

Authors:  Laura Esserman; Nola Hylton; Tracy George; Noel Weidner
Journal:  Breast J       Date:  1999-01       Impact factor: 2.431

6.  Tumor histology in lymph vessels and lymph nodes for the accurate prediction of outcome among breast cancer patients treated with neoadjuvant chemotherapy.

Authors:  Nobuko Tamura; Takahiro Hasebe; Nao Okada; Takashi Houjoh; Sadako Akashi-Tanaka; Chikako Shimizu; Tatsuhiro Shibata; Yuko Sasajima; Motoki Iwasaki; Takayuki Kinoshita
Journal:  Cancer Sci       Date:  2009-06-26       Impact factor: 6.716

7.  MRI evaluation of pathologically complete response and residual tumors in breast cancer after neoadjuvant chemotherapy.

Authors:  Jeon Hor Chen; Byron Feig; Byon Feig; Garima Agrawal; Hon Yu; Philip M Carpenter; Rita S Mehta; Orhan Nalcioglu; Min Ying Su
Journal:  Cancer       Date:  2008-01-01       Impact factor: 6.860

8.  Detection and quantification of breast tumor necrosis with MR imaging: value of the necrosis-avid contrast agent Gadophrin-3.

Authors:  Stephan Metz; Heike E Daldrup-Unk; Thomas Richter; Christoph Räth; Wolfgang Ebert; Marcus Settles; Ernst J Rummeny; Thomas M Link; Morand Piert
Journal:  Acad Radiol       Date:  2003-05       Impact factor: 3.173

9.  Triple-negative breast cancer: correlation between MR imaging and pathologic findings.

Authors:  Takayoshi Uematsu; Masako Kasami; Sachiko Yuen
Journal:  Radiology       Date:  2009-03       Impact factor: 11.105

10.  Utility of initial MRI for predicting extent of residual disease after neoadjuvant chemotherapy: analysis of 70 breast cancer patients.

Authors:  Yoriko Murata; Yasuhiro Ogawa; Shoji Yoshida; Kei Kubota; Satoshi Itoh; Mitsutaka Fukumoto; Akihito Nishioka; Toshiaki Moriki; Hironori Maeda; Yosuke Tanaka
Journal:  Oncol Rep       Date:  2004-12       Impact factor: 3.906

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  11 in total

1.  Baseline tumor oxygen saturation correlates with a pathologic complete response in breast cancer patients undergoing neoadjuvant chemotherapy.

Authors:  Shigeto Ueda; Darren Roblyer; Albert Cerussi; Amanda Durkin; Anais Leproux; Ylenia Santoro; Shanshan Xu; Thomas D O'Sullivan; David Hsiang; Rita Mehta; John Butler; Bruce J Tromberg
Journal:  Cancer Res       Date:  2012-07-09       Impact factor: 12.701

2.  The role of pre-treatment diffusion-weighted MRI in predicting long-term outcome of colorectal liver metastasis.

Authors:  H H Tam; D J Collins; G Brown; I Chau; D Cunningham; M O Leach; D-M Koh
Journal:  Br J Radiol       Date:  2013-08-30       Impact factor: 3.039

Review 3.  Pre-treatment differences and early response monitoring of neoadjuvant chemotherapy in breast cancer patients using magnetic resonance imaging: a systematic review.

Authors:  R Prevos; M L Smidt; V C G Tjan-Heijnen; M van Goethem; R G Beets-Tan; J E Wildberger; M B I Lobbes
Journal:  Eur Radiol       Date:  2012-09-16       Impact factor: 5.315

4.  Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set.

Authors:  Elizabeth Hope Cain; Ashirbani Saha; Michael R Harowicz; Jeffrey R Marks; P Kelly Marcom; Maciej A Mazurowski
Journal:  Breast Cancer Res Treat       Date:  2018-10-16       Impact factor: 4.872

5.  Development and validation of a nomogram based on pretreatment dynamic contrast-enhanced MRI for the prediction of pathologic response after neoadjuvant chemotherapy for triple-negative breast cancer.

Authors:  Yanbo Li; Yongzi Chen; Rui Zhao; Yu Ji; Junnan Li; Ying Zhang; Hong Lu
Journal:  Eur Radiol       Date:  2021-11-12       Impact factor: 7.034

6.  Radiomics of Tumor Heterogeneity in Longitudinal Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer.

Authors:  Ming Fan; Hang Chen; Chao You; Li Liu; Yajia Gu; Weijun Peng; Xin Gao; Lihua Li
Journal:  Front Mol Biosci       Date:  2021-03-22

7.  Predicting pathologic response to neoadjuvant chemotherapy in patients with locally advanced breast cancer using multiparametric MRI.

Authors:  Nannan Lu; Jie Dong; Xin Fang; Lufang Wang; Wei Jia; Qiong Zhou; Lingyu Wang; Jie Wei; Yueyin Pan; Xinghua Han
Journal:  BMC Med Imaging       Date:  2021-10-23       Impact factor: 1.930

8.  Dynamic contrast-enhanced MR imaging in a phase Ⅱ study on neoadjuvant chemotherapy combining Rh-endostatin with docetaxel and epirubicin for locally advanced breast cancer.

Authors:  Qianxin Jia; Junqing Xu; Weifeng Jiang; Minwen Zheng; Mengqi Wei; Jianghao Chen; Ling Wang; Yi Huan
Journal:  Int J Med Sci       Date:  2012-12-28       Impact factor: 3.738

Review 9.  Clinical application of magnetic resonance imaging in management of breast cancer patients receiving neoadjuvant chemotherapy.

Authors:  Jeon-Hor Chen; Min-Ying Su
Journal:  Biomed Res Int       Date:  2013-06-05       Impact factor: 3.411

10.  Texture analysis on MR images helps predicting non-response to NAC in breast cancer.

Authors:  N Michoux; S Van den Broeck; L Lacoste; L Fellah; C Galant; M Berlière; I Leconte
Journal:  BMC Cancer       Date:  2015-08-05       Impact factor: 4.430

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