Literature DB >> 28790119

Complementary Value of Contralateral Parenchymal Enhancement on DCE-MRI to Prognostic Models and Molecular Assays in High-risk ER+/HER2- Breast Cancer.

Bas H M van der Velden1, Sjoerd G Elias2, Tycho Bismeijer3, Claudette E Loo4, Max A Viergever5, Lodewyk F A Wessels3, Kenneth G A Gilhuijs1.   

Abstract

Purpose: To determine whether markers of healthy breast stroma are able to select a subgroup of patients at low risk of death or metastasis from patients considered at high risk according to routine markers of the tumor.Experimental Design: Patients with ER+/HER2- breast cancer were consecutively included for retrospective analysis. The contralateral parenchyma was segmented automatically on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), where upon the average of the top-10% late enhancement was calculated. This contralateral parenchymal enhancement (CPE) was analyzed with respect to routine prognostic models and molecular assays (Nottingham Prognostic Index, Dutch clinical chemotherapy-selection guidelines, 70-gene signature, and 21-gene recurrence score). CPE was split in tertiles and tested for overall and distant disease-free survival. CPE was adjusted for patient and tumor characteristics, as well as systemic therapy, using inverse probability weighting (IPW). Subanalyses were performed in patients at high risk according to prognostic models and molecular assays.
Results: Four-hundred-and-fifteen patients were included, constituting the same group in which the association between CPE and survival was discovered. Median follow-up was 85 months, 34/415(8%) patients succumbed. After IPW-adjustment for patient and tumor characteristics, patients with high CPE had significantly better overall survival than those with low CPE in groups at high risk according to the Nottingham Prognostic Index [HR (95% CI): 0.08 (0.00-0.40), P < 0.001]; Dutch clinical guidelines [HR (95% CI): 0.22 (0.00-0.81), P = 0.021]; and 21-gene recurrence score [HR (95% CI): 0.14 (0.00-0.84), P = 0.030]. One group showed a trend [70-gene signature: HR (95% CI): 0.25 (0.00-1.02), P = 0.054].Conclusions: In patients at high risk based on the tumor, subgroups at relatively low risk were identified using pretreatment enhancement of the stroma on breast DCE-MRI. Clin Cancer Res; 23(21); 6505-15. ©2017 AACR. ©2017 American Association for Cancer Research.

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Year:  2017        PMID: 28790119     DOI: 10.1158/1078-0432.CCR-17-0176

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  7 in total

1.  Background parenchymal enhancement and breast cancer: a review of the emerging evidences about its potential use as imaging biomarker.

Authors:  Rossella Rella; Andrea Contegiacomo; Enida Bufi; Sara Mercogliano; Paolo Belli; Riccardo Manfredi
Journal:  Br J Radiol       Date:  2020-10-15       Impact factor: 3.039

2.  Contralateral parenchymal enhancement on dynamic contrast-enhanced MRI reproduces as a biomarker of survival in ER-positive/HER2-negative breast cancer patients.

Authors:  Bas H M van der Velden; Elizabeth J Sutton; Luca A Carbonaro; Ruud M Pijnappel; Elizabeth A Morris; Kenneth G A Gilhuijs
Journal:  Eur Radiol       Date:  2018-05-07       Impact factor: 5.315

3.  Amount of fibroglandular tissue FGT and background parenchymal enhancement BPE in relation to breast cancer risk and false positives in a breast MRI screening program : A retrospective cohort study.

Authors:  Suzan Vreemann; Mehmet U Dalmis; Peter Bult; Nico Karssemeijer; Mireille J M Broeders; Albert Gubern-Mérida; Ritse M Mann
Journal:  Eur Radiol       Date:  2019-02-22       Impact factor: 5.315

4.  Harmonization of Quantitative Parenchymal Enhancement in T1 -Weighted Breast MRI.

Authors:  Bas H M van der Velden; Michael J van Rijssel; Beatrice Lena; Marielle E P Philippens; Claudette E Loo; Max A A Ragusi; Sjoerd G Elias; Elizabeth J Sutton; Elizabeth A Morris; Lambertus W Bartels; Kenneth G A Gilhuijs
Journal:  J Magn Reson Imaging       Date:  2020-06-03       Impact factor: 4.813

5.  Prediction of Prognostic Factors and Genotypes in Patients With Breast Cancer Using Multiple Mathematical Models of MR Diffusion Imaging.

Authors:  Weiwei Wang; Xindong Zhang; Laimin Zhu; Yueqin Chen; Weiqiang Dou; Fan Zhao; Zhe Zhou; Zhanguo Sun
Journal:  Front Oncol       Date:  2022-01-31       Impact factor: 6.244

6.  Background Parenchymal Enhancement on Breast MRI as a Prognostic Surrogate: Correlation With Breast Cancer Oncotype Dx Score.

Authors:  Michelle Zhang; Meredith Sadinski; Dana Haddad; Min Sun Bae; Danny Martinez; Elizabeth A Morris; Peter Gibbs; Elizabeth J Sutton
Journal:  Front Oncol       Date:  2021-02-04       Impact factor: 6.244

Review 7.  Blockchain and artificial intelligence technology in e-Health.

Authors:  Priti Tagde; Sandeep Tagde; Tanima Bhattacharya; Pooja Tagde; Hitesh Chopra; Rokeya Akter; Deepak Kaushik; Md Habibur Rahman
Journal:  Environ Sci Pollut Res Int       Date:  2021-09-02       Impact factor: 4.223

  7 in total

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