ArticleEuropean radiology2019
Diagnostic performance of initial enhancement analysis using ultra-fast dynamic contrast-enhanced MRI for breast lesions.
Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.
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Who cites it
35 citing papers in PubMed, 2 syntheses or guidelines pooled it, 62 citations in OpenAlex.
- The diagnostic performance of ultrafast MRI to differentiate benign from malignant breast lesions: a systematic review and meta-analysis.European radiology · 2024Pooled it
- Preoperative breast magnetic resonance imaging in patients with ductal carcinoma in situ: a systematic review for the European Commission Initiative on Breast Cancer (ECIBC).European radiology · 2021Pooled it
- Diagnostic performance of kinetic parameters of ultrafast breast MRI and their associations with immunohistopathological findings of breast carcinoma.Scientific reports · 2026Article
- The role of magnetic resonance imaging (MRI) in breast cancer molecular subtypes.Polish journal of radiology · 2026Review
- Diagnostic performance of kinetic parameters derived from ultrafast breast MRI in characterizing benign and malignant breast lesions: the added value of the semiautomatically based parameters.Insights into imaging · 2025Article
- Dynamic Contrast-Enhanced MRI in the Evaluation of Soft Tissue Tumors and Tumor-Like Lesions: Technical Principles and Clinical Applications.Korean journal of radiology · 2025Review
- The value of breast ultrafast dynamic contrast-enhanced magnetic resonance imaging in diagnosing axillary lymph node metastasis in mass-type invasive ductal carcinoma of the breast.Quantitative imaging in medicine and surgery · 2025Article
- Time to Enhancement Measured From Ultrafast Dynamic Contrast-Enhanced MRI for Improved Breast Lesion Diagnosis.Journal of breast imaging · 2025Article
- A simplified method for generating maximum slope maps in ultrafast dynamic contrast-enhanced breast magnetic resonance imaging.Radiological physics and technology · 2025Article
- Role of Ultrafast Dynamic Contrast-Enhanced MRI in Breast Cancer Prognostication: Correlation Between Early Kinetic Parameters and Tumor Aggressiveness and Histopathologic Characteristics.Journal of the Korean Society of Radiology · 2025Article
- Abbreviated and Ultrafast Dynamic Contrast-enhanced (DCE) MR Imaging.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Review
- Superior performance in classification of breast cancer molecular subtype and histological factors by radiomics based on ultrafast MRI over standard MRI: evidence from a prospective study.La Radiologia medica · 2025Observational
- Ultrafast sequence-based prediction model and nomogram to differentiate additional suspicious lesions on preoperative breast MRI.European radiology · 2025Article
- Relationship between kinetic parameters of ultrafast dynamic contrast-enhanced (DCE) MRI and tumor-infiltrating lymphocytes (TILs) in breast cancer.Japanese journal of radiology · 2025Article
- Quantitative MR Imaging of the Breast.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Review
- Optimizing ultrafast dynamic contrast-enhanced MRI scan duration in the differentiation of benign and malignant breast lesions.Insights into imaging · 2024Article
- Ultrafast MRI and T1 and T2 Radiomics for Predicting Invasive Components in Ductal Carcinoma in Situ Diagnosed With Percutaneous Needle Biopsy.Korean journal of radiology · 2023Article
- Ultrafast DCE-MRI for discriminating pregnancy-associated breast cancer lesions from lactation related background parenchymal enhancement.European radiology · 2023Article
- Magnetic resonance imaging diagnosis of non-mass enhancement of the breast.Journal of medical ultrasonics (2001) · 2023Review
- Assessment of Enhancement Kinetics Improves the Specificity of Abbreviated Breast MRI: Performance in an Enriched Cohort.Diagnostics (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
9 authors at 5 institutions in 2 countries.
Funding
Abstract
objectivesTo assess the diagnostic value and contribution to BI-RADS categorisation of initial enhancement on ultra-fast DCE-MRI for differentiating malignant and benign breast lesions.
methodsThe institutional review board approved this study, and written informed consent was obtained from each participant. Both ultra-fast DCE-MRI for initial enhancement analysis and conventional MRI were performed on 200 subjects with a total of 215 lesions (147 malignant and 68 benign). BI-RADS categorisation of enhancing lesions was performed using the conventional MRI. Two initial enhancement measures, time to enhancement (TTE) and maximum slope (MS), were derived from the ultra-fast DCE-MRI. Diagnostic performance and the additional diagnostic value of adding TTE and MS to BI-RADS were evaluated.
resultsBoth TTE and MS showed significant differences between malignant and benign breast lesions in masses (TTE, p <.001; MS, p = .006) and non-mass enhancement (NME) (TTE, p <.001; MS, p <.001). For masses, the AUC of TTE+MS combined with BI-RADS (0.864) was better than BI-RADS alone (0.823, p = .065). For NME, the AUC of TTE+MS combined with BI-RADS (0.923) was significantly larger than BI-RADS alone (0.865, p = .036), and diagnostic specificity improved by 40.9% (p = .005), without a significant decrease in the sensitivity (p = .083).
conclusionInitial enhancement analysis using ultra-fast DCE-MRI is especially useful for increasing the diagnostic performance of NME in breast MRI. KEY POINTS: • Ultra-fast dynamic MRI effectively differentiates benign from malignant breast lesions. • Ultra-fast dynamic MRI contributes to BI-RADS categorisation in non-mass enhancement. • Management of non-mass breast lesions becomes more appropriate.
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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.