ArticleJournal of magnetic resonance imaging : JMRI2019
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.
Article in Journal of magnetic resonance imaging : JMRI, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 1 of them a synthesis that pooled it.
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Who cites it
59 citing papers in PubMed, 1 synthesis or guideline pooled it, 99 citations in OpenAlex.
- Diffusion-Weighted MRI for the Assessment of Molecular Prognostic Biomarkers in Breast Cancer.Korean journal of radiology · 2024Pooled it
- Diffusion-Weighted Imaging as a Quantitative Imaging Biomarker for Predicting Proliferation Rate in Hepatocellular Carcinoma: Developing a Radiomics Nomogram.Journal of computer assisted tomographyTrial
- Feasibility of predicting breast cancer Ki-67 expression using histogram features derived from time-dependent diffusion magnetic resonance imaging.Quantitative imaging in medicine and surgery · 2026Article
- The value of non-enhanced magnetic resonance imaging based on T2-weighted imaging and apparent diffusion coefficient in the study of three-tiered HER2 status in patients with breast cancer.Quantitative imaging in medicine and surgery · 2026Article
- Development and validation of an MRI-based deep learning system for triple-class ER expression classification in breast cancer: a large-scale multicenter study.BMC medicine · 2026Article
- Article
- ADC Histogram Features of Breast Cancer Brain Metastases as Candidate Imaging Biomarkers of Primary Tumor ER, PR, Ki-67, and Luminal Status.Diagnostics (Basel, Switzerland) · 2026Article
- Evaluation of Breast Lesions Using Multiparametric 3-Tesla Magnetic Resonance Imaging: A Cross-Sectional Study.Cureus · 2026Article
- Quantitative MRI mapping parameters to differentiate HER2-positive and HER2-low breast cancer.Quantitative imaging in medicine and surgery · 2026Article
- Integrating time-dependent diffusion MRI and intravoxel incoherent motion for predicting NPI and molecular subtypes in breast cancer.BMC medical imaging · 2026Article
- Deep learning-based prediction of HER2 status from breast diffusion-weighted MRI.Frontiers in oncology · 2026Article
- Fractal analysis of tumor subregions differentiates benign from malignant breast lesions.Polish journal of radiology · 2026Article
- The role of magnetic resonance imaging (MRI) in breast cancer molecular subtypes.Polish journal of radiology · 2026Review
- Monitoring Pharmacological Treatment of Breast Cancer with MRI.Current issues in molecular biology · 2025Review
- Automated deep learning method for whole-breast segmentation in contrast-free quantitative MRI.BMC medical imaging · 2025Article
- Comparison of MR cytometry methods in predicting immunohistochemical factor status and molecular subtypes of breast cancer.Radiology and oncology · 2025Article
- Breast Diffusion-weighted MR Imaging: Current Applications, Insights from Screening, and Future Directions.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Review
- Imaging Microstructural Parameters of Breast Tumor in Patient Using Time-Dependent Diffusion: A Feasibility Study.Diagnostics (Basel, Switzerland) · 2025Article
- Enhanced preoperative prediction of breast lesion pathology, prognostic biomarkers, and molecular subtypes using multiple models diffusion-weighted MR imaging.Scientific reports · 2025Article
- Article
Corrections and comments
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Authors and funding
14 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundDiffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping is one of the most useful additional MRI parameters to improve diagnostic accuracy and is now often used in a multiparameric imaging setting for breast tumor detection and characterization. PURPOSE: To evaluate whether different ADC metrics can also be used for prediction of receptor status, proliferation rate, and molecular subtype in invasive breast cancer. STUDY TYPE: Retrospective. SUBJECTS: In all, 107 patients with invasive breast cancer met the inclusion criteria (mean age 57 years, range 32-87) and underwent multiparametric breast MRI. FIELD STRENGTH/SEQUENCE: 3 T, readout-segmented echo planar imaging (rsEPI) with IR fat suppression, dynamic contrast-enhanced (DCE) T ASSESSMENT: Two readers independently drew a region of interest on ADC maps on the whole tumor (WTu), and on its darkest part (DpTu). Minimum, mean, and maximum ADC values of both WTu and DpTu were compared for receptor status, proliferation rate, and molecular subtypes. STATISTICAL TESTS: Wilcoxon rank sum, Mann-Whitney U-tests for associations between radiologic features and histopathology; histogram and q-q plots, Shapiro-Wilk's test to assess normality, concordance correlation coefficient for precision and accuracy; receiver operating characteristics curve analysis.
resultsEstrogen receptor (ER) and progesterone receptor (PR) status had significantly different ADC values for both readers. Maximum WTu (P = 0.0004 and 0.0005) and mean WTu (P = 0.0101 and 0.0136) were significantly lower for ER-positive tumors, while PR-positive tumors had significantly lower maximum WTu values (P = 0.0089 and 0.0047). Maximum WTu ADC was the only metric that was significantly different for molecular subtypes for both readers (P = 0.0100 and 0.0132) and enabled differentiation of luminal tumors from nonluminal (P = 0.0068 and 0.0069) with an area under the curve of 0.685 for both readers. DATA
conclusionMaximum WTu ADC values may be used to differentiate luminal from other molecular subtypes of breast cancer. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:836-846.
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