ArticleJournal of magnetic resonance imaging : JMRI2017
Apparent diffusion coefficient values may help predict which MRI-detected high-risk breast lesions will upgrade at surgical excision.
Article in Journal of magnetic resonance imaging : JMRI, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Risk prediction models for malignancy upgrade in high-risk breast lesions: a qualitative systematic review.Breast cancer research and treatment · 2025Pooled it
- A multiparametric [European journal of nuclear medicine and molecular imaging · 2019Trial
- High-Risk Benign Breast Lesions: An Ontario Health (Cancer Care Ontario) Recommendations Report.Current oncology (Toronto, Ont.) · 2026Review
- Upgrade to malignancy after excision of MRI-only B3 breast lesions: should the size and histological type of the lesion be considered for therapeutic management?Insights into imaging · 2026Article
- Influence of Complete Lesion Removal During Vacuum-Assisted Breast Biopsy on the Upgrade Rate of B3 Lesions Presenting as Microcalcifications.Journal of clinical medicine · 2025Article
- Non-contrast Breast MR Imaging.Radiologic clinics of North America · 2024Review
- The value of imaging combined with clinicopathological features in the diagnosis of high-risk breast lesions.Gland surgery · 2022Article
- Radiomics Nomogram Based on Radiomics Score from Multiregional Diffusion-Weighted MRI and Clinical Factors for Evaluating HER-2 2+ Status of Breast Cancer.Diagnostics (Basel, Switzerland) · 2021Article
- Diagnostic value of radiomics and machine learning with dynamic contrast-enhanced magnetic resonance imaging for patients with atypical ductal hyperplasia in predicting malignant upgrade.Breast cancer research and treatment · 2021Article
- Apparent diffusion coefficient values in borderline breast lesions upgraded and not upgraded at definitive histopathological examination after surgical excision.Polish journal of radiology · 2021Article
- Automated deep learning method for whole-breast segmentation in diffusion-weighted breast MRI.Journal of magnetic resonance imaging : JMRI · 2020Article
- Diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping as a quantitative imaging biomarker for prediction of immunohistochemical receptor status, proliferation rate, and molecular subtypes of breast cancer.Journal of magnetic resonance imaging : JMRI · 2019Article
- Multiparametric MRI model with dynamic contrast-enhanced and diffusion-weighted imaging enables breast cancer diagnosis with high accuracy.Journal of magnetic resonance imaging : JMRI · 2019Article
- Diffusion-weighted imaging of the breast: current status as an imaging biomarker and future role.BJR open · 2019Review
- Histogram Analysis and Visual Heterogeneity of Diffusion-Weighted Imaging with Apparent Diffusion Coefficient Mapping in the Prediction of Molecular Subtypes of Invasive Breast Cancers.Contrast media & molecular imaging · 2019Article
- DWI in the Assessment of Breast Lesions.Topics in magnetic resonance imaging : TMRI · 2017Article
- Visibility of mammographically occult breast cancer on diffusion-weighted MRI versus ultrasound.Clinical imagingArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
purposeTo investigate whether diffusion-weighted imaging (DWI) features could assist in determining which high-risk lesions identified on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and diagnosed on core needle biopsy (CNB) will upgrade to malignancy on surgical excision. MATERIALS AND
methodsThis Institutional Review Board (IRB)-approved prospective study included participants with MRI-detected Breast Imaging Reporting and Data System (BI-RADS) 4 or 5 lesions with high-risk pathology on CNB who underwent surgical excision. Twenty-three high-risk lesions detected on 3T breast MRI in 20 women (average age = 54 ± 9 years) were evaluated, of which six lesions (26%) upgraded to malignancy at surgery. DCE, DWI characteristics, and clinical factors were compared between high-risk lesions that upgraded to malignancy on surgical excision and those that did not. Logistic regression modeling was performed to identify features that optimally predicted upgrade to malignancy, with performance described using area under the receiver operating characteristic curve (AUC).
resultsHigh-risk lesions that upgraded on excision demonstrated lower apparent diffusion coefficient (ADC) than those that did not (median, 1.08 × 10
conclusionADC and maximum lesion size on MRI show promise for predicting which MRI-detected high-risk lesions will upgrade to malignancy at surgical excision. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1028-1036.
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