ArticleOncotarget2017
Prediction of low-risk breast cancer using quantitative DCE-MRI and its pathological basis.
Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Clinical application of gadoterate meglumine in abbreviated dynamic contrast-enhanced magnetic resonance imaging of the breast with ultrafast imaging: a single-center retrospective study.Quantitative imaging in medicine and surgery · 2025Article
- A correlative study between IVIM-DWI parameters and VEGF and MMPs expression in hepatocellular carcinoma.Quantitative imaging in medicine and surgery · 2023Article
- Effect of Neoadjuvant Chemotherapy on Angiogenesis and Cell Proliferation of Breast Cancer Evaluated by Dynamic Enhanced Magnetic Resonance Imaging.BioMed research international · 2022Article
- Combination of an ultrafast TWIST-VIBE Dixon sequence protocol and diffusion-weighted imaging into an accurate easily applicable classification tool for masses in breast MRI.European radiology · 2020Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study aimed to evaluate the difference of mass in dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) characteristics between low-risk and non-low-risk breast cancers and to explore the possible pathological basis. MATERIALS AND
methodsApproval from the institutional review board and informed consent were acquired for this study. The MR images of 104 patients with pathologically proven breast cancer (104 lesions) were prospectively analyzed. All of included patients were Chinese woman. The DCE-MRI morphologic findings, apparent diffusion coefficient (ADC) values, quantitative DCE-MRI parameters, and pathological biomarkers between the two subtypes of breast cancer were compared. The quantitative DCE-MRI parameters and ADC values were added to the morphologic features in multivariate models to evaluate diagnostic performance in predicting low-risk breast cancer. The values were further subjected to the receiver operating characteristic (ROC) curve analysis.
resultsLow-risk tumors showed significantly lower
conclusionsThe prediction parameter using
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Registered trials
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