ArticleFrontiers in oncology2020
Background Parenchymal Enhancement on Breast MRI as a Prognostic Surrogate: Correlation With Breast Cancer Oncotype Dx Score.
Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 22 citations in OpenAlex.
- Automated calculation of background parenchymal enhancement as a biomarker of treatment responses and recurrence-free survival in breast cancer.Breast cancer research and treatment · 2026Article
- Multimodal deep learning model for prediction of breast cancer recurrence risk and correlation with oncotype DX.Breast cancer research : BCR · 2025Article
- Radiomics Analysis of Breast MRI to Predict Oncotype Dx Recurrence Score: Systematic Review.Diagnostics (Basel, Switzerland) · 2025Review
- Use and Comparison of Machine Learning Techniques to Discern the Protein Patterns of Autoantibodies Present in Women with and without Breast Pathology.Journal of proteome research · 2025Article
- Background parenchymal enhancement of the contralateral breast on preoperative contrast-enhanced breast MRI as a potential predictive factor for disease-free survival in triple-negative breast cancer patients.Frontiers in oncology · 2025Article
- AI Applications to Breast MRI: Today and Tomorrow.Journal of magnetic resonance imaging : JMRI · 2024Review
- Review
- New Frontiers in Breast Cancer Imaging: The Rise of AI.Bioengineering (Basel, Switzerland) · 2024Review
- Assessment of Background Parenchymal Enhancement at Dynamic Contrast-enhanced MRI in Predicting Breast Cancer Recurrence Risk.Radiology · 2024Article
- Location pattern of recurrence of fully resected grade 1 meningiomas.Acta neurochirurgica · 2023Article
- Precision Medicine in Breast Cancer: Do MRI Biomarkers Identify Patients Who Truly Benefit from the Oncotype DX Recurrence ScoreDiagnostics (Basel, Switzerland) · 2022Article
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Authors and funding
8 authors at 2 institutions in 4 countries.
Funding
Abstract
purposeBreast MRI background parenchymal enhancement (BPE) can potentially serve as a prognostic marker, by possible correlation with molecular subtype. Oncotype Dx, a gene assay, is a prognostic and predictive surrogate for tumor aggressiveness and treatment response. The purpose of this study was to investigate the association between contralateral non-tumor breast magnetic resonance imaging (MRI) background parenchymal enhancement and tumor oncotype score.
methodsIn this retrospective study, patients with ER+ and HER2- early stage invasive ductal carcinoma who underwent preoperative breast MRI, oncotype risk scoring, and breast conservation surgery from 2008-2010 were identified. After registration, BPE from the pre and three post-contrast phases was automatically extracted using a k-means clustering algorithm. Four metrics were calculated: initial enhancement (IE) relative to the pre-contrast signal, late enhancement, overall enhancement (OE), and area under the enhancement curve (AUC). Histogram analysis was performed to determine first order metrics which were compared to oncotype risk score groups using Mann-Whitney tests and Spearman rank correlation analysis.
resultsThis study included 80 women (mean age = 51.1 ± 10.3 years); 46 women were categorized as low risk (≤17) and 34 women were categorized as intermediate/high risk (≥18) according to Oncotype Dx. For the mean of the top 10% pixels, significant differences were noted for IE (p = 0.032), OE (p = 0.049), and AUC (p = 0.044). Using the risk score as a continuous variable, correlation analysis revealed a weak but significant correlation with the mean of the top 10% pixels for IE (r = 0.26, p = 0.02), OE (r = 0.25, p = 0.02), and AUC (r = 0.27, p = 0.02).
conclusionBPE metrics of enhancement in the non-tumor breast are associated with tumor Oncotype Dx recurrence score, suggesting that the breast microenvironment may relate to likelihood of recurrence and magnitude of chemotherapy benefit.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.