Literature DB >> 30396666

Comparison of mammography, digital breast tomosynthesis, automated breast ultrasound, magnetic resonance imaging in evaluation of residual tumor after neoadjuvant chemotherapy.

Jiyoon Park1, Eun Young Chae2, Joo Hee Cha2, Hee Jung Shin2, Woo Jung Choi2, Young-Wook Choi3, Hak Hee Kim4.   

Abstract

BACKGROUND: To compare the accuracy of mammography (MG), digital breast tomosynthesis (DBT), automated breast ultrasound (ABUS) and magnetic resonance imaging (MRI) for the assessment of residual tumor extent in breast cancer after neoadjuvant chemotherapy (NAC).
METHODS: Fifty-one stage II-III breast cancer undergoing NAC were enrolled from March 2015 to December 2016. The longest diameter of residual tumor measured with MG, DBT, ABUS and MRI was compared with the pathologic tumor size. Statistical analysis was performed using intraclass correlation coefficients (ICC) and marginal homogeneity test. Receiver operating characteristics (ROC) analysis was used to evaluate the diagnostic performance for predicting pathologic complete response (pCR).
RESULTS: MRI size correlated well with pathology (ICC = 0.83), significantly better than MG, DBT and ABUS size (ICC = 0.56, ICC = 0.63 and ICC = 0.55, respectively). The discrepancy between MRI and pathology was statistical different from that of MG and ABUS (p = 0.0231 and 0.0039, respectively), but not different from that of DBT (p = 0.5727). For predicting pCR, MRI and DBT had a better performance compared to MG and US (area under the ROC curve: 0.92, 0.84, 0.72, 0.75, respectively; p = 0.3749 for DBT, p = 0.0972 for MG and p = 0.0596 for ABUS, when MRI being reference).
CONCLUSIONS: MRI and DBT allow more accurate assessment of tumor size compared to pathology compared with MG and ABUS. MRI and DBT outperform MG and ABUS in the prediction of pathologic complete response.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Diagnostic ultrasound; Digital breast tomosynthesis; Magnetic resonance imaging; Mammography; Neoadjuvant

Mesh:

Year:  2018        PMID: 30396666     DOI: 10.1016/j.ejrad.2018.09.032

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  14 in total

1.  Tumor size estimation of the breast cancer molecular subtypes using imaging techniques.

Authors:  Gulten Sezgın; Melda Apaydın; Demet Etıt; Murat Kemal Atahan
Journal:  Med Pharm Rep       Date:  2020-07-22

2.  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

3.  Prediction of Pathologic Complete Response in Breast Cancer Patients Comparing Magnetic Resonance Imaging with Ultrasound in Neoadjuvant Setting.

Authors:  Frederik Knude Palshof; Charlotte Lanng; Niels Kroman; Cemil Benian; Ilse Vejborg; Anne Bak; Maj-Lis Talman; Eva Balslev; Tove Filtenborg Tvedskov
Journal:  Ann Surg Oncol       Date:  2021-05-27       Impact factor: 5.344

4.  The value of coronal view as a stand-alone assessment in women undergoing automated breast ultrasound.

Authors:  Simone Schiaffino; Licia Gristina; Simona Tosto; Elena Massone; Sara De Giorgis; Alessandro Garlaschi; Alberto Tagliafico; Massimo Calabrese
Journal:  Radiol Med       Date:  2020-07-16       Impact factor: 3.469

5.  Is Clinical Exam of the Axilla Sufficient to Select Node-Positive Patients Who Downstage After NAC for SLNB? A Comparison of the Accuracy of Clinical Exam Versus MRI.

Authors:  Tracy-Ann Moo; Maxine S Jochelson; Emily C Zabor; Michelle Stempel; Monica Raiss; Anita Mamtani; Audree B Tadros; Mahmoud El-Tamer; Monica Morrow
Journal:  Ann Surg Oncol       Date:  2019-10-03       Impact factor: 5.344

Review 6.  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

7.  Diagnostic accuracy of contrast-enhanced spectral mammography for breast lesions: A systematic review and meta-analysis.

Authors:  Matteo Basilio Suter; Filippo Pesapane; Giorgio Maria Agazzi; Tania Gagliardi; Olga Nigro; Anna Bozzini; Francesca Priolo; Silvia Penco; Enrico Cassano; Claudio Chini; Alessandro Squizzato
Journal:  Breast       Date:  2020-06-10       Impact factor: 4.380

Review 8.  Current Landscape of Breast Cancer Imaging and Potential Quantitative Imaging Markers of Response in ER-Positive Breast Cancers Treated with Neoadjuvant Therapy.

Authors:  Ella F Jones; Deep K Hathi; Rita Freimanis; Rita A Mukhtar; A Jo Chien; Laura J Esserman; Laura J Van't Veer; Bonnie N Joe; Nola M Hylton
Journal:  Cancers (Basel)       Date:  2020-06-09       Impact factor: 6.575

Review 9.  Machine learning with multiparametric magnetic resonance imaging of the breast for early prediction of response to neoadjuvant chemotherapy.

Authors:  Roberto Lo Gullo; Sarah Eskreis-Winkler; Elizabeth A Morris; Katja Pinker
Journal:  Breast       Date:  2019-11-23       Impact factor: 4.380

10.  Texture Analysis of Dynamic Contrast-Enhanced MRI in Evaluating Pathologic Complete Response (pCR) of Mass-Like Breast Cancer after Neoadjuvant Therapy.

Authors:  Kun Cao; Bo Zhao; Xiao-Ting Li; Yan-Ling Li; Ying-Shi Sun
Journal:  J Oncol       Date:  2019-12-26       Impact factor: 4.375

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