ArticleEuropean radiology2021
Maximum slope using ultrafast breast DCE-MRI at 1.5 Tesla: a potential tool for predicting breast lesion aggressiveness.
Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 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
- Background parenchymal enhancement in ultrafast MRI: Inter-reader agreement before and after training, and correlations with prognostic factors of breast cancer.European journal of radiology open · 2026Article
- Multiparametric MRI-derived biomarkers for preoperative prediction of recurrence and/or metastasis after neoadjuvant chemoradiotherapy in locally advanced rectal cancer.Quantitative imaging in medicine and surgery · 2026Article
- 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
- A simplified method for generating maximum slope maps in ultrafast dynamic contrast-enhanced breast magnetic resonance imaging.Radiological physics and technology · 2025Article
- Development of a prediction model for HER2 low breast cancer using quantitative intra- and peri-tumoral heterogeneity and MRI features on high-spatial resolution ultrafast DCE-MRI.Quantitative imaging in medicine and surgery · 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
- Ultrafast Breast MRI: A Narrative Review.Journal of personalized medicine · 2025Review
- Optimizing ultrafast dynamic contrast-enhanced MRI scan duration in the differentiation of benign and malignant breast lesions.Insights into imaging · 2024Article
- Localization of contrast-enhanced breast lesions in ultrafast screening MRI using deep convolutional neural networks.European radiology · 2024Article
- Diagnostic Accuracy of Combined 3.0T Magnetic Resonance Imaging and Molybdenum Target X-Ray in Triple-Negative Breast Cancer: Correlation with Prognosis in Patients Undergoing Sentinel Lymph Node Biopsy.Women's health reports (New Rochelle, N.Y.) · 2024Article
- Ultrafast dynamic contrast-enhanced breast MRI with quantitative perfusion parameters in differentiating breast cancer: a study focusing on triple-negative and HER2 positive breast cancer.Frontiers in oncology · 2024Article
- Value of dynamic contrast-enhanced magnetic resonance imaging in combination with mammography for screening early-stage breast cancer.African health sciences · 2023Article
- Combination of ultrafast dynamic contrast-enhanced MRI-based radiomics and artificial neural network in assessing BI-RADS 4 breast lesions: Potential to avoid unnecessary biopsies.Frontiers in oncology · 2023Article
- Breast MRI during pregnancy and lactation: clinical challenges and technical advances.Insights into imaging · 2022Review
- Breast Cancer Subtypes and Quantitative Magnetic Resonance Imaging: A Systemic Review.Life (Basel, Switzerland) · 2022Review
- Advanced Magnetic Resonance Imaging (MRI) Techniques: Technical Principles and Applications in Nanomedicine.Cancers · 2022Review
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesWe evaluated the relationship between the maximum slope (MS) based on ultrafast breast DCE-MRI sequences, and the clinical parameters and routine prognostic factors of breast cancer.
methods210 lesions were retrospectively evaluated: 150 malignant (30 each of luminal A invasive carcinoma, luminal B invasive carcinoma, HER2 overexpression (HER2), triple negative (TN), invasive lobular carcinoma (ILC)), and 60 benign. For each lesion, the MS was obtained with an ultrafast sequence and semi-quantitative curves were classified into three types with a conventional DCE sequence. The correlation between MS and age, body mass index (BMI), menopause, and routine prognostic factors were analyzed.
resultsA MS cut-off at 6.5%/s could discriminate benign from malignant lesions, with sensitivity and specificity of 84% and 90%, respectively, whereas analysis of semi-quantitative curves showed sensitivity and specificity of 89.3% and 55%, respectively. In multivariate analysis, MS values decreased with BMI increasing (p = 0.035), postmenopausal status (p < 0.001), and positive ER status (p < 0.001) and increased with tumor size (p < 0.001). The MS was significantly lower for the pooled luminal A + ILC group than for the pooled luminal B + HER2 + TN group featuring tumors with poorer prognoses (p < 0.001). With a threshold of 11%/s, the sensitivity and specificity to identify invasive carcinoma subtypes with poorer prognoses were 71% and 68%, respectively.
conclusionThe MS allows better tumor characterization and identifies factors of poor prognosis for breast cancer. KEY POINTS: • Maximum slope calculated from ultrafast breast DCE-MRI differentiates benign from malignant breast lesions better than semi-quantitative curves of conventional DCE-MRI. • Maximum slope calculated from ultrafast breast DCE-MRI identifies breast cancers with poor prognoses. • In the case of multiple lesions, the most aggressive may be identified and targeted by measuring the maximum slope.
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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.