ArticleWorld journal of surgical oncology2021
Dynamic contrast enhanced-MRI and diffusion-weighted image as predictors of lymphovascular invasion in node-negative invasive breast cancer.
Article in World journal of surgical oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.
- Association of peritumoral region features assessed on breast MRI and prognosis of breast cancer: a systematic review and meta-analysis.European radiology · 2024Pooled it
- Prior Clinico-Radiological Features Informed Multi-Modal MR Images Convolution Neural Network: A novel deep learning framework for prediction of lymphovascular invasion in breast cancer.Cancer medicine · 2024Trial
- Intratumoral and peritumoral-based radiomics for assessment of lymphovascular invasion in invasive breast cancer: model development and validation.Translational cancer research · 2026Article
- Magnetic resonance imaging-based radiomics analysis: predicting vascular invasion in breast invasive ductal carcinoma using different machine learning models.Translational cancer research · 2026Article
- Integrated PET-IVIM-DKI MRI for predicting lymphovascular invasion in NSCLC.Insights into imaging · 2025Article
- Breast Imaging: Correlation Between Axillary Lymph Nodes Apparent Diffusion Coefficient and Pathological Lymphovascular Invasion in Patients With Invasive Breast Cancer.European journal of breast health · 2025Article
- Establishment of a predictive nomogram for breast cancer lympho-vascular invasion based on radiomics obtained from digital breast tomography and clinical imaging features.BMC medical imaging · 2025Article
- Analysis of the diagnostic efficacy of ultrasound, MRI, and combined examination in benign and malignant breast tumors.Frontiers in oncology · 2025Article
- Preoperative Imaging Assessment of Lymphovascular Invasion in Breast Cancer: Current Evidence, Technical Advances, and Future Directions.Breast cancer (Dove Medical Press) · 2025Review
- Prediction of lymphovascular invasion in non-mass enhancement breast cancer using DCE-MRI and clinical-pathological features.Frontiers in oncology · 2025Article
- MRI-based radiomic and machine learning for prediction of lymphovascular invasion status in breast cancer.BMC medical imaging · 2024Article
- Diffusion tensor imaging: survival analysis prediction in breast cancer patients.Radiologie (Heidelberg, Germany) · 2024Article
- Predictive value of MRI-based deep learning model for lymphovascular invasion status in node-negative invasive breast cancer.Scientific reports · 2024Article
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- Predicting lymphovascular invasion in rectal cancer: evaluating the performance of golden-angle radial sparse parallel MRI for rectal perfusion assessment.Scientific reports · 2023Article
- Quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging to predict lymphovascular invasion and survival outcome in breast cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2022Article
- Radiomics of dynamic contrast-enhanced magnetic resonance imaging parametric maps and apparent diffusion coefficient maps to predict Ki-67 status in breast cancer.Frontiers in oncology · 2022Article
- Predicting Axillary Response in Hormone Receptor-Positive Breast Cancer after Neoadjuvant Chemotherapy Using Real-World Data.Journal of oncology · 2022Article
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLymphovascular invasion (LVI) is an important risk factor for prognosis of breast cancer and an unfavorable prognostic factor in node-negative invasive breast cancer patients. The purpose of this study was to evaluate the association between LVI and pre-operative features of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) in node-negative invasive breast cancer.
methodsData were collected retrospectively from 132 cases who had undergone pre-operative MRI and had invasive breast carcinoma confirmed on the last surgical pathology report. MRI and DWI data were analyzed for the size of tumor, mass shape, margin, internal enhancement pattern, kinetic enhancement curve, high intratumoral T2-weighted signal intensity, peritumoral edema, DWI rim sign, and apparent diffusion coefficient (ADC) values. We calculated the relationship between presence of LVI and various prognostic factors and MRI features.
resultsPathologic tumor size, mass margin, internal enhancement pattern, kinetic enhancement curve, DWI rim sign, and the difference between maximum and minimum ADC were significantly correlated with LVI (p < 0.05).
conclusionsWe suggest that DCE-MRI with DWI would assist in predicting LVI status in node-negative invasive breast cancer patients.
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