ArticleFrontiers in oncology2022
Correlation of dynamic contrast-enhanced MRI and diffusion-weighted MR imaging with prognostic factors and subtypes of breast cancers.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Emerging biomarkers in breast fibroadenoma: implications for differential diagnosis, malignant transformation, and precision medicine.Molecular biology reports · 2026Review
- Evaluating the predictive value of dynamic contrast-enhanced MRI and six diffusion models for prognostic factors in mass-type invasive ductal carcinoma of the breast.BMC medical imaging · 2026Article
- A multiparametric magnetic resonance imaging model incorporating the relative apparent diffusion coefficient for preoperative discrimination of triple-negative breast cancer.American journal of translational research · 2026Article
- Breast Cancer: Habitat imaging based on intravoxel incoherent motion for predicting pathologic complete response to neoadjuvant chemotherapy.Medical physics · 2025Article
- Radiomics model building from multiparametric MRI to predict Ki-67 expression in patients with primary central nervous system lymphomas: a multicenter study.BMC medical imaging · 2025Article
- Intravoxel incoherent motion-based habitat imaging for the prediction of immunohistochemistry in patients with breast cancer.Frontiers in oncology · 2025Article
- Correlation analysis of multiparametric magnetic resonance imaging features and molecular subtypes of breast cancer.Journal of clinical imaging science · 2025Article
- A Machine-Learning Model for the Prediction of Triple-Negative Breast Cancer Based on Multiparameter MRI.Breast cancer (Dove Medical Press) · 2025Article
- Preoperatively predicting human epidermal growth factor receptor 2-low expression in breast cancer using neural network model based on multiparameter magnetic resonance imaging.Quantitative imaging in medicine and surgery · 2024Article
- Radiomics characterization of tissues in an animal brain tumor model imaged using dynamic contrast enhanced (DCE) MRI.Scientific reports · 2023Article
- Article
- Evaluation of molecular receptors status in breast cancer using an mpMRI-based feature fusion radiomics model: mimicking radiologists' diagnosis.Frontiers in oncology · 2023Article
- Neoadjuvant chemotherapy for breast cancer: an evaluation of its efficacy and research progress.Frontiers in oncology · 2023Review
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4 authors.
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Abstract
Objective: To determine the preoperative magnetic resonance imaging (MRI) findings of breast cancer on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted magnetic resonance imaging (DWI) in different molecular subtypes. Materials and methods: A retrospective study was conducted on 116 breast cancer subjects who underwent preoperative MRI and surgery or biopsy. Three radiologists retrospectively assessed the morphological and kinetic characteristics on DCE-MRI and tumor detectability on DWI, by using apparent diffusion coefficient (ADC) values of lesions. The clinicopathologic and MRI features of four subtypes were compared. The correlation between clinical and MRI findings with molecular subtypes was evaluated using the chi-square and ANOVA tests, while the Mann-Whitney test was used to analyze the relationship between ADC and prognostic factors. Results: One hundred and sixteen women diagnosed with breast cancer confirmed by surgery or biopsy had the following subtypes of breast cancer: luminal A (27, 23.3%), luminal B (56, 48.2%), HER2 positive (14, 12.1%), and triple-negative breast cancer (TNBC) (19, 16.4%), respectively. Among the subtypes, significant differences were found in axillary node metastasis, histological grade, tumor shape, rim enhancement, margin, lesion type, intratumoral T2 signal intensity, Ki-67 index, and paratumoral enhancement ( Conclusion: The morphologic features of MRI can be used as imaging biomarkers to identify the molecular subtypes of breast cancer. In addition, quantitative assessments of ADC values on DWI may also provide biological clues about molecular subtypes.
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