Literature DB >> 33723322

Quantitative analysis of contrast enhanced spectral mammography grey value for early prediction of pathological response of breast cancer to neoadjuvant chemotherapy.

Dong Xing1, Ning Mao1, Jianjun Dong1, Heng Ma1, Qianqian Chen2, Yongbin Lv3.   

Abstract

A quantitative analysis of contrast-enhanced spectral mammography (CESM) enhancement was conducted for the early prediction of the pathological response after neoadjuvant chemotherapy (NAC). Retrospective analysis of the data of 111 patients was conducted, and all of them underwent NAC in our hospital and surgical resection after the end of all cycles from January 2018 to May 2019. They were divided into pathological complete response (PCR) and non-PCR groups. We determined whether a statistical difference in the percentage of CESM grey value reduction (ΔCGV) was present in the PCR and non-PCR groups and whether a statistical difference was observed in the diagnostic efficiency of craniocaudal (CC) and mediolateral oblique (MLO) view subtraction images. Independent sample t-test was used to compare different groups, the receiver operating characteristic (ROC) curve was used to compare the diagnostic efficacy of CC and MLO for pathological response after NAC, and the Delong test was used to compare the area under the ROC curve (AUC). Statistical significance was considered at P < 0.05. A statistical difference was observed in the ΔCGV in the PCR and non-PCR groups. No statistical difference was observed in the AUCs of CC and MLO view subtraction images. The ΔCGV can be used as a quantitative index to predict PCR early, and no statistical difference was observed in the diagnostic efficacy of CC and MLO view subtraction images.

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Year:  2021        PMID: 33723322      PMCID: PMC7960703          DOI: 10.1038/s41598-021-85353-9

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  30 in total

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Authors:  K D Miller; C J Sweeney; G W Sledge
Journal:  J Clin Oncol       Date:  2001-02-15       Impact factor: 44.544

2.  Neoadjuvant chemotherapy of breast cancer: tumor markers as predictors of pathologic response, recurrence, and survival.

Authors:  Lisa M Precht; Kimberly A Lowe; Mary Atwood; J David Beatty
Journal:  Breast J       Date:  2010-04-28       Impact factor: 2.431

3.  Gadobenate dimeglumine-enhanced MR imaging breast vascular maps: association between invasive cancer and ipsilateral increased vascularity.

Authors:  Francesco Sardanelli; Andrea Iozzelli; Alfonso Fausto; Alessandro Carriero; Miles A Kirchin
Journal:  Radiology       Date:  2005-04-21       Impact factor: 11.105

4.  Prediction of clinicopathologic response of breast cancer to primary chemotherapy at contrast-enhanced MR imaging: initial clinical results.

Authors:  Anwar R Padhani; Carmel Hayes; Laura Assersohn; Trevor Powles; Andreas Makris; John Suckling; Martin O Leach; Janet E Husband
Journal:  Radiology       Date:  2006-03-16       Impact factor: 11.105

5.  Contrast-enhanced spectral mammography (CESM) versus breast magnetic resonance imaging (MRI): A retrospective comparison in 66 breast lesions.

Authors:  L Li; R Roth; P Germaine; S Ren; M Lee; K Hunter; E Tinney; L Liao
Journal:  Diagn Interv Imaging       Date:  2016-09-26       Impact factor: 4.026

6.  Magnetic resonance imaging evaluation of residual tumors in breast cancer after neoadjuvant chemotherapy: surgical implications.

Authors:  Juan Zhou; Gongjie Li; Fugeng Sheng; Penggang Qiao; Hongtao Zhang; Xudong Xing
Journal:  Acta Radiol       Date:  2015-07-31       Impact factor: 1.990

7.  Breast cancer: early prediction of response to neoadjuvant chemotherapy using parametric response maps for MR imaging.

Authors:  Nariya Cho; Seock-Ah Im; In-Ae Park; Kyung-Hun Lee; Mulan Li; Wonshik Han; Dong-Young Noh; Woo Kyung Moon
Journal:  Radiology       Date:  2014-04-13       Impact factor: 11.105

Review 8.  Preoperative therapy in invasive breast cancer: pathologic assessment and systemic therapy issues in operable disease.

Authors:  Julie R Gralow; Harold J Burstein; William Wood; Gabriel N Hortobagyi; Luca Gianni; Gunter von Minckwitz; Aman U Buzdar; Ian E Smith; William F Symmans; Baljit Singh; Eric P Winer
Journal:  J Clin Oncol       Date:  2008-02-10       Impact factor: 44.544

Review 9.  Selective elimination of breast cancer surgery in exceptional responders: historical perspective and current trials.

Authors:  Raquel F D van la Parra; Henry M Kuerer
Journal:  Breast Cancer Res       Date:  2016-03-08       Impact factor: 6.466

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  2 in total

1.  A Spatial Attention Guided Deep Learning System for Prediction of Pathological Complete Response Using Breast Cancer Histopathology Images.

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Journal:  Bioinformatics       Date:  2022-08-13       Impact factor: 6.931

Review 2.  Advances in Imaging in Evaluating the Efficacy of Neoadjuvant Chemotherapy for Breast Cancer.

Authors:  Xianshu Kong; Qian Zhang; Xuemei Wu; Tianning Zou; Jiajun Duan; Shujie Song; Jianyun Nie; Chu Tao; Mi Tang; Maohua Wang; Jieya Zou; Yu Xie; Zhenhui Li; Zhen Li
Journal:  Front Oncol       Date:  2022-05-20       Impact factor: 5.738

  2 in total

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