ArticleJournal of magnetic resonance imaging : JMRI2014
Intravoxel incoherent motion diffusion-weighted MRI at 3.0 T differentiates malignant breast lesions from benign lesions and breast parenchyma.
Article in Journal of magnetic resonance imaging : JMRI, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 3 of them syntheses that pooled it.
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Who cites it
51 citing papers in PubMed, 3 syntheses or guidelines pooled 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
- Intravoxel Incoherent Motion Diffusion-Weighted Imaging for Quantitative Differentiation of Breast Tumors: A Meta-Analysis.Frontiers in oncology · 2020Pooled it
- Can apparent diffusion coefficient (ADC) distinguish breast cancer from benign breast findings? A meta-analysis based on 13 847 lesions.BMC cancer · 2019Pooled it
- 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
- Reduction of biopsy rate in BI-RADS4 breast lesions: potential of an abbreviated advanced DWI protocol.European radiology · 2025Article
- Evaluating Breast Cancer Intravoxel Incoherent Motion MRI Biomarkers across Software Platforms.Radiology. Imaging cancer · 2025Article
- Combined diffusion and perfusion index maps from simplified intravoxel incoherent motion imaging enable visual assessment of breast lesions.Scientific reports · 2025Article
- Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.Frontiers in oncology · 2025Article
- Multisite MRI Intravoxel Incoherent Motion Repeatability and Reproducibility across 3 T Scanners in a Breast Diffusion Phantom: A BReast Intravoxel Incoherent Motion Multisite (BRIMM) Study.Journal of magnetic resonance imaging : JMRI · 2024Article
- Intravoxel incoherent motion for differentiating residual/recurrent tumor from post-treatment change in patients with high-grade glioma.The neuroradiology journal · 2023Article
- Diagnostic value of multiple b-value diffusion-weighted imaging in discriminating the malignant from benign breast lesions.BMC medical imaging · 2023Article
- Simplified intravoxel incoherent motion DWI for differentiating malignant from benign breast lesions.European radiology experimental · 2022Article
- Characterization of the diffusion signal of breast tissues using multi-exponential models.Magnetic resonance in medicine · 2022Article
- Magnetic Resonance Imaging (MRI) and MR Spectroscopic Methods in Understanding Breast Cancer Biology and Metabolism.Metabolites · 2022Review
- Diffusion Breast MRI: Current Standard and Emerging Techniques.Frontiers in oncology · 2022Review
- Quantitative Measurement of Breast Tumors Using Intravoxel Incoherent Motion (IVIM) MR Images.Journal of personalized medicine · 2021Article
- Article
- Diagnostic Performance of Diffusion MRI for differentiating Benign and Malignant Nonfatty Musculoskeletal Soft Tissue Tumors: A Systematic Review and Meta-analysis.Journal of Cancer · 2021Article
- Application of Diffusion Weighted Imaging Techniques for Differentiating Benign and Malignant Breast Lesions.Frontiers in oncology · 2021Article
- The role of histogram analysis in diffusion-weighted imaging in the differential diagnosis of benign and malignant breast lesions.BMC medical informatics and decision making · 2020Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
purposeTo study the differentiation of malignant breast lesions from benign lesions and fibroglandular tissue (FGT) using apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) parameters. MATERIALS AND
methodsThis retrospective study included 26 malignant and 14 benign breast lesions in 35 patients who underwent diffusion-weighted MRI at 3.0T and nine b-values (0-1000 s/mm(2) ). ADC and IVIM parameters (perfusion fraction fp , pseudodiffusion coefficient Dp , and true diffusion coefficient Dd ) were determined in lesions and FGT. For comparison, IVIM was also measured in 16 high-risk normal patients. A predictive model was constructed using linear discriminant analysis. Lesion discrimination based on ADC and IVIM parameters was assessed using receiver operating characteristic (ROC) and area under the ROC curve (AUC).
resultsIn FGT of normal subjects, fp was 1.1 ± 1.1%. In malignant lesions, fp (6.4 ± 3.1%) was significantly higher than in benign lesions (3.1 ± 3.3%, P = 0.0025) or FGT (1.5 ± 1.2%, P < 0.001), and Dd ((1.29 ± 0.28) × 10(-3) mm(2) /s) was lower than in benign lesions ((1.56 ± 0.28) × 10(-3) mm(2) /s, P = 0.011) or FGT ((1.86 ± 0.34) × 10(-3) mm(2) /s, P < 0.001). A combination of Dd and fp provided higher AUC for discrimination between malignant and benign lesions (0.84) or FGT (0.97) than ADC (0.72 and 0.86, respectively).
conclusionThe IVIM parameters provide accurate identification of malignant lesions.
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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.