Literature DB >> 28350486

Predictive Clinicopathologic and Dynamic Contrast-Enhanced MRI Findings for Tumor Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer.

Hye-Joung Eom1, Joo Hee Cha1, Woo Jung Choi1, Eun Young Chae1, Hee Jung Shin1, Hak Hee Kim1.   

Abstract

OBJECTIVE: The purpose of this study is to investigate whether clinicopathologic factors and dynamic contrast-enhanced MRI (DCE-MRI) features are associated with pathologic tumor response to neoadjuvant chemotherapy (NAC) in patients with triple-negative breast cancer (TNBC).
MATERIALS AND METHODS: Seventy-three patients with TNBC who underwent pre-NAC MRI, completed NAC, and underwent surgery between January 2009 and December 2010 were included in the study. MRI features and clinicopathologic factors for predicting pathologic responses were analyzed, and residual tumor sizes, as measured using MRI and surgical specimens, were evaluated.
RESULTS: Of 73 study patients, 20 (27%) had a pathologic complete response (pCR). Homogeneous enhancement on pre-NAC MRI (odds ratio from multivariate analysis, 14.66) and a concentric shrinkage pattern of tumor volume reduction on post-NAC MRI (odds ratio, 8.63) were independently associated with pCR. Residual tumor sizes, as measured using MRI and surgical specimens, showed a strong correlation (r = 0.652, p < 0.001). The correlation for residual tumor sizes was stronger for patients with pCR (r = 0.600, p < 0.001) and those with a concentric shrinkage pattern (r = 0.818, p < 0.001) than for patients with a response other than near pCR or pCR (i.e., the non-pCR group) (r = -0.128, p = 0.590) and patients with a dendritic shrinkage pattern of tumor volume reduction (r = 0.270, p = 0.182).
CONCLUSION: Homogeneous enhancement of tumors on pre-NAC MRI and the presence of a concentric shrinkage pattern after NAC are associated with pCR in patients with TNBC. Residual tumor sizes on MRI and surgical specimens tended to show a stronger correlation in the pCR group or the concentric shrinkage group than in the non-pCR group or the dendritic shrinkage group.

Entities:  

Keywords:  MRI; breast; neoadjuvant chemotherapy; triple-negative breast cancer

Mesh:

Substances:

Year:  2017        PMID: 28350486     DOI: 10.2214/AJR.16.17125

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  15 in total

1.  Breast Conservation After Neoadjuvant Chemotherapy for Triple-Negative Breast Cancer: Surgical Results From the BrighTNess Randomized Clinical Trial.

Authors:  Mehra Golshan; Sibylle Loibl; Stephanie M Wong; Jens Bodo Houber; Joyce O'Shaughnessy; Hope S Rugo; Norman Wolmark; Mark D McKee; David Maag; Danielle M Sullivan; Otto Metzger-Filho; Gunter Von Minckwitz; Charles E Geyer; William M Sikov; Michael Untch
Journal:  JAMA Surg       Date:  2020-03-18       Impact factor: 14.766

2.  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

3.  Preoperative Breast Magnetic Resonance Imaging as a Predictor of Response to Neoadjuvant Chemotherapy.

Authors:  Robert Browne; Peter McAnena; Niamh O'Halloran; Brian M Moloney; Emily Crilly; Michael J Kerin; Aoife J Lowery
Journal:  Breast Cancer (Auckl)       Date:  2022-06-24

4.  Construction of Nomograms for Predicting Pathological Complete Response and Tumor Shrinkage Size in Breast Cancer.

Authors:  Shuai Yan; Wenjie Wang; Bifa Zhu; Xixi Pan; Xiaoyan Wu; Weiyang Tao
Journal:  Cancer Manag Res       Date:  2020-09-10       Impact factor: 3.989

5.  Early prediction of response to neoadjuvant chemotherapy using contrast-enhanced ultrasound in breast cancer.

Authors:  Juan Peng; Huan Pu; Yan Jia; Chuang Chen; Xiao-Kang Ke; Qing Zhou
Journal:  Medicine (Baltimore)       Date:  2021-05-14       Impact factor: 1.889

6.  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

Review 7.  Evaluation of the Efficacy of Neoadjuvant Chemotherapy for Breast Cancer.

Authors:  Huan Wang; Xiaoyun Mao
Journal:  Drug Des Devel Ther       Date:  2020-06-18       Impact factor: 4.162

8.  Evaluation of MRI accuracy after primary systemic therapy in breast cancer patients considering tumor biology: optimizing the surgical planning.

Authors:  Alberto Bouzón; Ángela Iglesias; Benigno Acea; Cristina Mosquera; Paz Santiago; Joaquín Mosquera
Journal:  Radiol Oncol       Date:  2019-05-08       Impact factor: 2.991

9.  Prediction of Tumor Shrinkage Pattern to Neoadjuvant Chemotherapy Using a Multiparametric MRI-Based Machine Learning Model in Patients With Breast Cancer.

Authors:  Yuhong Huang; Wenben Chen; Xiaoling Zhang; Shaofu He; Nan Shao; Huijuan Shi; Zhenzhe Lin; Xueting Wu; Tongkeng Li; Haotian Lin; Ying Lin
Journal:  Front Bioeng Biotechnol       Date:  2021-07-06

10.  Pretreatment prediction of pathologic complete response to neoadjuvant chemotherapy in breast cancer: Perfusion metrics of dynamic contrast enhanced MRI.

Authors:  Jeongmin Lee; Sung Hun Kim; Bong Joo Kang
Journal:  Sci Rep       Date:  2018-06-22       Impact factor: 4.379

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