ArticleEuropean radiology2013
Combined contrast-enhanced magnetic resonance and diffusion-weighted imaging reading adapted to the "Breast Imaging Reporting and Data System" for multiparametric 3-T imaging of breast lesions.
Article in European radiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 4 of them syntheses that pooled it.
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Who cites it
72 citing papers in PubMed, 4 syntheses or guidelines pooled it, 118 citations in OpenAlex.
- Meta-analysis of dynamic contrast enhancement and diffusion-weighted MRI for differentiation of benign from malignant non-mass enhancement breast lesions.Frontiers in oncology · 2024Pooled it
- Diffusion-weighted imaging of the breast-a consensus and mission statement from the EUSOBI International Breast Diffusion-Weighted Imaging working group.European radiology · 2020Guideline
- Diagnostic performance of breast tumor tissue selection in diffusion weighted imaging: A systematic review and meta-analysis.PloS one · 2020Pooled it
- Breast lesions classified as probably benign (BI-RADS 3) on magnetic resonance imaging: a systematic review and meta-analysis.European radiology · 2018Pooled it
- A multiparametric [European journal of nuclear medicine and molecular imaging · 2019Trial
- Utility of Diffusion-weighted Imaging to Decrease Unnecessary Biopsies Prompted by Breast MRI: A Trial of the ECOG-ACRIN Cancer Research Group (A6702).Clinical cancer research : an official journal of the American Association for Cancer Research · 2019Trial
- Diagnostic accuracy of (18)F-FDG PET/CT compared with that of contrast-enhanced MRI of the breast at 3 T.European journal of nuclear medicine and molecular imaging · 2015Trial
- Automated Apparent Diffusion Coefficient Measurement of Breast Tumors in Diffusion-weighted MRI for Early Neoadjuvant Chemotherapy Response Assessment.Radiology. Imaging cancer · 2026Article
- Evaluation of Breast Lesions Using Multiparametric 3-Tesla Magnetic Resonance Imaging: A Cross-Sectional Study.Cureus · 2026Article
- Artificial Intelligence in Triple-Negative Breast Cancer: Applications in Diagnosis, Treatment Response, and Prognosis.Diagnostics (Basel, Switzerland) · 2026Review
- Parameter Estimation for the Intravoxel Incoherent Motion-diffusional Kurtosis Imaging Model Using Synthetic Q-space Learning Toward Breast Tumor Diagnosis.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026Article
- Exploring MRI and Mammography Lesion Features for Breast Cancer Detection in PTEN Hamartoma Tumor Syndrome.Cancers · 2025Article
- External validation of multiparametric magnetic resonance imaging-based decision rules for characterizing breast lesions and comparison to Kaiser score and breast imaging reporting and data system (BI-RADS) category.Quantitative imaging in medicine and surgery · 2025Article
- Enhancing preoperative HER2 status classification of invasive breast cancers using machine learning models based on clinicopathological and MRI features: a multicenter study.Frontiers in cell and developmental biology · 2025Article
- DWI in the Differentiation of Malignant and Benign Breast Lesions Presenting with Non-Mass Enhancement on CE-MRI.Cancers · 2024Article
- 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
- Multiparametric MRI for characterization of the tumour microenvironment.Nature reviews. Clinical oncology · 2024Review
- Article
- Dynamic contrast-enhanced magnetic resonance imaging features and apparent diffusion coefficient value of HER2-positive/HR-negative breast carcinoma.Quantitative imaging in medicine and surgery · 2023Article
- Diffusion-Weighted Magnetic Resonance Imaging for Preoperative Evaluation of Patients With Breast Cancer: Protocol of a Prospective, Multicenter, Observational Cohort Study.Journal of breast cancer · 2023Review
12 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
11 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo develop and assess a combined reading for contrast-enhanced magnetic resonance (CE-MRI) and diffusion weighted imaging (DWI) adapted to the BI-RADS for multiparametric MRI of the breast at 3 T.
methodsA total of 247 patients with histopathologically verified breast lesions were included in this IRB-approved prospective study. All patients underwent CE-MR and DWI at 3 T. MRIs were classified according to BI-RADS and assessed for apparent diffusion coefficient (ADC) values. A reading method that adapted ADC thresholds to the assigned BI-RADS classification was developed. Sensitivity, specificity, diagnostic accuracy and the area under the curve were calculated. BI-RADS-adapted reading was compared with previously published reading methods in the same population. Inter- and intra-reader variability was assessed.
resultsSensitivity of BI-RADS-adapted reading was not different from the high sensitivity of CE-MRI (P = 0.4). BI-RADS-adapted reading maximised specificity (89.4 %), which was significantly higher compared with CE-MRI (P < 0.001). Previous reading methods did not perform as well as the BI-RADS method except for a logistic regression model. BI-RADS-adapted reading was more sensitive in non-mass-like enhancements (NMLE) and was more robust to inter- and intra-reader variability.
conclusionMultiparametric 3-T MRI of the breast using a BI-RADS-adapted reading is fast, simple to use and significantly improves the diagnostic accuracy of breast MRI. KEYPOINTS : • Multiparametric breast 3-T MRI with BI-RADS-adapted reading improves diagnostic accuracy. • BI-RADS-adapted reading of CE-MRI and DWI is based on established reporting guidelines. • BI-RADS-adapted reading is fast and easy to use in routine clinical practice. • BI-RADS-adapted reading is robust to intra- and inter-reader variability.
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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.