ArticleMagnetic resonance in medicine2022
Characterization of the diffusion signal of breast tissues using multi-exponential models.
Article in Magnetic resonance in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Development and evaluation of a cervical cancer-specific restriction spectrum imaging (RSI) model.Magnetic resonance imaging · 2026Article
- The role of diffusion-weighted MRI in biological image-guided radiation therapy: a roadmap.Physics in medicine and biology · 2026Review
- Discrimination Between Benign and Malignant Lesions With Restriction Spectrum Imaging MRI in an Enriched Breast Cancer Screening Cohort.Journal of magnetic resonance imaging : JMRI · 2025Article
- Multimodal apparent diffusion MRI model in noninvasive evaluation of breast cancer and Ki-67 expression.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Diffusion-Weighted Imaging for Skin Pathologies of the Breast-A Feasibility Study.Diagnostics (Basel, Switzerland) · 2024Article
- Quantitative characterization of breast lesions and normal fibroglandular tissue using compartmentalized diffusion-weighted model: comparison of intravoxel incoherent motion and restriction spectrum imaging.Breast cancer research : BCR · 2024Article
- Restriction spectrum imaging with elastic image registration for automated evaluation of response to neoadjuvant therapy in breast cancer.Frontiers in oncology · 2023Article
- Precision of region of interest-based tri-exponential intravoxel incoherent motion quantification and the role of the Intervoxel spatial distribution of flow velocities.Magnetic resonance in medicine · 2022Article
- Article
- Diffusion Breast MRI: Current Standard and Emerging Techniques.Frontiers in oncology · 2022Review
- Discrimination of Breast Cancer from Healthy Breast Tissue Using a Three-component Diffusion-weighted MRI Model.Clinical cancer research : an official journal of the American Association for Cancer Research · 2021Observational
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19 authors.
Funding
Abstract
purposeRestriction spectrum imaging (RSI) decomposes the diffusion-weighted MRI signal into separate components of known apparent diffusion coefficients (ADCs). The number of diffusion components and optimal ADCs for RSI are organ-specific and determined empirically. The purpose of this work was to determine the RSI model for breast tissues.
methodsThe diffusion-weighted MRI signal was described using a linear combination of multiple exponential components. A set of ADC values was estimated to fit voxels in cancer and control ROIs. Later, the signal contributions of each diffusion component were estimated using these fixed ADC values. Relative-fitting residuals and Bayesian information criterion were assessed. Contrast-to-noise ratio between cancer and fibroglandular tissue in RSI-derived signal contribution maps was compared to DCE imaging.
resultsA total of 74 women with breast cancer were scanned at 3.0 Tesla MRI. The fitting residuals of conventional ADC and Bayesian information criterion suggest that a 3-component model improves the characterization of the diffusion signal over a biexponential model. Estimated ADCs of triexponential model were D
conclusionBreast diffusion-weighted MRI signal was best described using a triexponential model. Tumor conspicuity in breast RSI model is comparable to that of DCE without the use of exogenous contrast. These data may be used as differential features between healthy and malignant breast tissues.
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