Literature DB >> 30066421

Breast MRI phenotype and background parenchymal enhancement may predict tumor response to neoadjuvant endocrine therapy.

Talal Hilal1, Matthew Covington2, Heidi E Kosiorek3, Christine Zwart2, Idris T Ocal4, Barbara A Pockaj5, Donald W Northfelt1, Bhavika K Patel2.   

Abstract

Neoadjuvant endocrine therapy (NET) is increasingly used for the treatment of estrogen receptor positive, HER2 negative breast cancer. We evaluated whether MRI phenotype and background parenchymal enhancement (BPE) can predict response to NET. Patients with localized breast cancer treated with NET and had a pre-treatment breast MRI were identified. Baseline MRI phenotype and BPE was interpreted by a single radiologist blinded to the results of systemic therapy. Response was defined as stable disease or reduction in tumor size on clinical and/or ultrasound examination. Of the 21 patients identified, 17 were responders; all patients with minimal/mild BPE had a response compared to 5/9 (56%) patients with moderate/marked BPE (P = 0.02). All four nonresponders had moderate/marked BPE as compared to 5/17 (29%) responders (P = 0.02). This pilot study suggests that minimal/mild BPE may be predictive of a positive response to NET. A higher degree of background enhancement was significantly predictive of negative response to NET.
© 2018 Wiley Periodicals, Inc.

Entities:  

Keywords:  breast MRI; breast cancer; endocrine therapy; neoadjuvant therapy; radiomics

Mesh:

Substances:

Year:  2018        PMID: 30066421     DOI: 10.1111/tbj.13101

Source DB:  PubMed          Journal:  Breast J        ISSN: 1075-122X            Impact factor:   2.431


  7 in total

Review 1.  Background parenchymal enhancement on breast MRI: A comprehensive review.

Authors:  Geraldine J Liao; Leah C Henze Bancroft; Roberta M Strigel; Rhea D Chitalia; Despina Kontos; Linda Moy; Savannah C Partridge; Habib Rahbar
Journal:  J Magn Reson Imaging       Date:  2019-04-19       Impact factor: 4.813

2.  Radiomic signatures derived from multiparametric MRI for the pretreatment prediction of response to neoadjuvant chemotherapy in breast cancer.

Authors:  Tiantian Bian; Zengjie Wu; Qing Lin; Haibo Wang; Yaqiong Ge; Shaofeng Duan; Guangming Fu; Chunxiao Cui; Xiaohui Su
Journal:  Br J Radiol       Date:  2020-09-02       Impact factor: 3.039

3.  The rate of breast fibroglandular enhancement during dynamic contrast-enhanced MRI reflects response to neoadjuvant therapy.

Authors:  John Virostko; Garrett Kuketz; Erin Higgins; Chengyue Wu; Anna G Sorace; Julie C DiCarlo; Sarah Avery; Debra Patt; Boone Goodgame; Thomas E Yankeelov
Journal:  Eur J Radiol       Date:  2021-01-09       Impact factor: 3.528

4.  The Clinical Impact of Neoadjuvant Endocrine Treatment on Luminal-like Breast Cancers and Its Prognostic Significance: Results from a Single-Institution Prospective Cohort Study.

Authors:  Covadonga Martí; Laura Yébenes; José María Oliver; Elisa Moreno; Laura Frías; Alberto Berjón; Adolfo Loayza; Marcos Meléndez; María José Roca; Vicenta Córdoba; David Hardisson; María Ángeles Rodríguez; José Ignacio Sánchez-Méndez
Journal:  Curr Oncol       Date:  2022-03-23       Impact factor: 3.109

Review 5.  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

6.  Prognostic value of breast MRI characteristics before and during neoadjuvant endocrine therapy in patients with ER+/HER2- breast cancer.

Authors:  Max Aa Ragusi; Gonneke Ao Winter-Warnars; Jelle Wesseling; Sabine C Linn; Regina G Beets-Tan; Bas Hm van der Velden; Sjoerd G Elias; Kenneth Ga Gilhuijs; Claudette E Loo
Journal:  Br J Radiol       Date:  2021-07-01       Impact factor: 3.039

7.  Accuracy of breast MRI in patients receiving neoadjuvant endocrine therapy: comprehensive imaging analysis and correlation with clinical and pathological assessments.

Authors:  Joana Reis; Jonas Christoffer Lindstrøm; Joao Boavida; Kjell-Inge Gjesdal; Daehoon Park; Nazli Bahrami; Manouchehr Seyedzadeh; Woldegabriel A Melles; Torill Sauer; Jürgen Geisler; Jonn Terje Geitung
Journal:  Breast Cancer Res Treat       Date:  2020-08-12       Impact factor: 4.624

  7 in total

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