ArticleMagnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine2020
Impact of b-Value Sampling Scheme on Brain IVIM Parameter Estimation in Healthy Subjects.
Article in Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- Accurate estimation of intravoxel incoherent motion parameters based on implicit neural representation.Medical physics · 2026Article
- Multimodal magnetic resonance imaging of the vastus medialis for quantitative diagnosis and grading in early-stage knee osteoarthritis and its correlation with severity.Scientific reports · 2026Article
- Histogram analysis of IVIM MRI for differentiating glioma IDH-1 status, grade, and Ki-67 expression: a comparison of bi-exponential models at multiple B-value.BMC medical imaging · 2025Article
- The utility of multi-b-value diffusion and arterial spin labelling magnetic resonance imaging in gliomas grading and prediction of isocitrate dehydrogenase status.Quantitative imaging in medicine and surgery · 2025Article
- Diagnostic Efficacy and Correlation of Intravoxel Incoherent Motion (IVIM) and Contrast-Enhanced (CE) MRI Perfusion Parameters in Oncology Imaging: A Systematic Review and Meta-Analysis.International journal of biomedical imaging · 2025Review
- Effect of inflammation on neurovascular coupling, microperfusion, and clinical outcomes in ischemic stroke patients: a case series report.Frontiers in medicine · 2025Article
- Bi-exponential diffusion-weighted imaging for differentiating high-grade gliomas from solitary brain metastases: a VOI-based histogram analysis.Scientific reports · 2024Article
- Differentiation of glioma and solitary brain metastasis: a multi-parameter magnetic resonance imaging study using histogram analysis.BMC cancer · 2024Article
- Evaluation of Whole Brain Intravoxel Incoherent Motion (IVIM) Imaging.Diagnostics (Basel, Switzerland) · 2024Article
- Optimizing b-values schemes for diffusion MRI of the brain with segmented Intravoxel Incoherent Motion (IVIM) model.Journal of applied clinical medical physics · 2023Article
- Correlation Between IVIM-DWI Parameters and Pathological Classification of Idiopathic Orbital Inflammatory Pseudotumors: A Preliminary Study.Frontiers in oncology · 2022Article
- Signal to noise and b-value analysis for optimal intra-voxel incoherent motion imaging in the brain.PloS one · 2021Article
- Differentiating Brain Metastasis and High-Grade Glioma Using Multi-b Value Diffusion MRI and Tumor Volumetry.Journal of neuroimaging : official journal of the American Society of NeuroimagingArticle
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Abstract
purposeIntravoxel incoherent motion (IVIM) analysis has attracted the interest of the clinical community due to its close relationship with microperfusion. Nevertheless, there is no clear reference protocol for its implementation; one of the questions being which b-value distribution to use. This study aimed to stress the importance of the sampling scheme and to show that an optimized b-value distribution decreases the variance associated with IVIM parameters in the brain with respect to a regular distribution in healthy volunteers.
methodsTen volunteers were included in this study; images were acquired on a 1.5T MR scanner. Two distributions of 16 b-values were used: one considered 'regular' due to its close association with that used in other studies, and the other considered 'optimized' according to previous studies. IVIM parameters were adjusted according to the bi-exponential model, using two-step method. Analysis was undertaken in ROI defined using in the Automated Anatomical Labeling atlas, and parameters distributions were compared in a total of 832 ROI.
resultsMaps with fewer speckles were obtained with the 'optimized' distribution. Coefficients of variation did not change significantly for the estimation of the diffusion coefficient D but decreased by approximately 39% for the pseudo-diffusion coefficient estimation and by 21% for the perfusion fraction. Distributions of adjusted parameters were found significantly different in 50% of the cases for the perfusion fraction, in 80% of the cases for the pseudo-diffusion coefficient and 17% of the cases for the diffusion coefficient. Observations across brain areas show that the range of average values for IVIM parameters is smaller in the 'optimized' case.
conclusionUsing an optimized distribution, data are sampled in a way that the IVIM signal decay is better described and less variance is obtained in the fitted parameters. The increased precision gained could help to detect small variations in IVIM parameters.
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