ArticlePloS one2018
Comparison of six fit algorithms for the intra-voxel incoherent motion model of diffusion-weighted magnetic resonance imaging data of pancreatic cancer patients.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.
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Who cites it
32 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI.Magma (New York, N.Y.) · 2020Pooled it
- Accurate estimation of intravoxel incoherent motion parameters based on implicit neural representation.Medical physics · 2026Article
- A Comparative Study of IVIM-MRI Fitting Techniques in Glioma Grading: Conventional, Bayesian, and Voxel-Wise and Spatially-Aware Deep Learning Approaches.Journal of magnetic resonance imaging : JMRI · 2026Article
- Simulation-Informed Evaluation of Microvascular Parameter Mapping for Diffusion MR Imaging of Solid Tumours.Magnetic resonance in medicine · 2026Article
- Hierarchical Bayesian Modelling Improves Microstructural Parameter Mapping in Diffusion and Exchange MRI Data.NMR in biomedicine · 2026Article
- Towards Clinical Translation of Intravoxel Incoherent Motion MRI: Acquisition and Analysis Consensus Recommendations.Journal of magnetic resonance imaging : JMRI · 2026Article
- The role of diffusion-weighted MRI in biological image-guided radiation therapy: a roadmap.Physics in medicine and biology · 2026Review
- Characterizing white matter hyperintensities in myotonic dystrophy type 1 through IVIM derived metrics.Scientific reports · 2025Article
- Optimized analytical segmented method for improved intravoxel incoherent motion parameter extraction in low-perfused tissues.Magnetic resonance in medicine · 2025Article
- SpinFlowSim: A blood flow simulation framework for histology-informed diffusion MRI microvasculature mapping in cancer.Medical image analysis · 2025Article
- Advanced breast diffusion-weighted imaging: what are the next steps? A proposal from the EUSOBI International Breast Diffusion-weighted Imaging working group.European radiology · 2025Review
- IVIM-Morph: Motion-compensated quantitative Intra-voxel Incoherent Motion (IVIM) analysis for functional fetal lung maturity assessment from diffusion-weighted MRI data.Medical image analysis · 2025Article
- Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.Frontiers in oncology · 2025Article
- Test-retest repeatability of intravoxel incoherent motion (IVIM) measurements in the cervical cord.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Reproducibility and Repeatability of Intravoxel Incoherent Motion MRI Acquisition Methods in Liver.Journal of magnetic resonance imaging : JMRI · 2024Article
- Assessment of fitting methods and variability of IVIM parameters in muscles of the lumbar spine at rest.Frontiers in musculoskeletal disorders · 2024Article
- A supervised deep neural network approach with standardized targets for enhanced accuracy of IVIM parameter estimation from multi-SNR images.NMR in biomedicine · 2022Article
- Intravoxel Incoherent Motion Magnetic Resonance Imaging in Skeletal Muscle: Review and Future Directions.Journal of magnetic resonance imaging : JMRI · 2022Review
- Impact of AlternateTomography (Ann Arbor, Mich.) · 2022Article
- Perfusion-Diffusion Ratio: A New IVIM Approach in Differentiating Solid Benign and Malignant Primary Lesions of the Liver.BioMed research international · 2022Article
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11 authors.
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Abstract
The intravoxel incoherent motion (IVIM) model for diffusion-weighted imaging (DWI) MRI data bears much promise as a tool for visualizing tumours and monitoring treatment response. To improve the currently poor precision of IVIM, several fit algorithms have been suggested. In this work, we compared the performance of two Bayesian IVIM fit algorithms and four other IVIM fit algorithms for pancreatic cancer imaging. DWI data were acquired in 14 pancreatic cancer patients during two MRI examinations. Three different measures of performance of the fitting algorithms were assessed: (i) uniqueness of fit parameters (Spearman's rho); (ii) precision (within-subject coefficient of variation, wCV); and (iii) contrast between tumour and normal-appearing pancreatic tissue. For the diffusivity D and perfusion fraction f, a Bayesian fit (IVIM-Bayesian-lin) offered the best trade-off between tumour contrast and precision. With the exception for IVIM-Bayesian-lin, all algorithms resulted in a very poor precision of the pseudo-diffusion coefficient D* with a wCV of more than 50%. The pseudo-diffusion coefficient D* of the Bayesian approaches were, however, significantly correlated with D and f. Therefore, the added value of fitting D* was considered limited in pancreatic cancer patients. The easier implemented least squares fit with fixed D* (IVIM-fixed) performed similar to IVIM-Bayesian-lin for f and D. In conclusion, the best performing IVIM fit algorithm was IVM-Bayesian-lin, but an easier to implement least squares fit with fixed D* performs similarly in pancreatic cancer patients.
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