ReviewNeuroImage2018
Physical and numerical phantoms for the validation of brain microstructural MRI: A cookbook.
Review in NeuroImage, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
61 citing papers in PubMed, 2 syntheses or guidelines pooled it, 118 citations in OpenAlex.
- Considerations and recommendations from the ISMRM diffusion study group for preclinical diffusion MRI: Part 2-Ex vivo imaging: Added value and acquisition.Magnetic resonance in medicine · 2025Guideline
- Anthropomorphic brain phantoms for use in MRI systems: a systematic review.Magma (New York, N.Y.) · 2022Pooled it
- Clinical Soma and Neurite Density Imaging (SANDI): Translational Microstructure Mapping on Clinical 3T MRI Scanners.Magnetic resonance in medicine · 2026Article
- Dependence of the Extra-Cellular Diffusion Coefficient on the Fractions of Neurites and Cell Bodies in Gray Matter.Magnetic resonance in medicine · 2026Article
- Detecting and characterizing restricted diffusion with accessible magnetic field gradients.PNAS nexus · 2026Article
- Simulation-Informed Evaluation of Microvascular Parameter Mapping for Diffusion MR Imaging of Solid Tumours.Magnetic resonance in medicine · 2026Article
- Axon Diameter Mapping From Myelin Water Diffusion MRI.IEEE transactions on medical imaging · 2026Article
- Monte Carlo Assessment of Accuracy for Mean Kärger Model Water Exchange Rate Estimates From Diffusional Kurtosis Time Dependence.NMR in biomedicine · 2026Article
- Quantifying Transmembrane Water Exchange by Diffusion NMR Methods: From Yeast Cells to Optic Nerve Ex Vivo.NMR in biomedicine · 2026Article
- Diffusion-MRI-Based Estimation of Cortical Architecture via Machine Learning (DECAM) in Primate Brains.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Construction of Phantoms for MR Electrical Properties Tomography (From Structure to Composition): A Guideline From the ISMRM Electro-Magnetic Tissue Properties Study Group.Journal of magnetic resonance imaging : JMRI · 2026Article
- Validating the neurite exchange imaging (NEXI) model of gray matter using Monte Carlo simulations in numerical substrates.Imaging neuroscience (Cambridge, Mass.) · 2026Article
- Motion and Flow Robust Free-Breathing Diffusion Kurtosis Imaging of the Kidney.NMR in biomedicine · 2025Article
- Non-monotonic time- and frequency-dependent diffusion kurtosis in the human brain revealed by pulsed and oscillating gradient experiments.Magnetic resonance in medicine · 2025Article
- Histology-informed microstructural diffusion simulations for MRI cancer characterisation-the Histo-μSim framework.Communications biology · 2025Article
- In vivo cortical microstructure mapping using high-gradient diffusion MRI accounting for intercompartmental water exchange effects.NeuroImage · 2025Article
- Considerations and recommendations from the ISMRM diffusion study group for preclinical diffusion MRI: Part 1: In vivo small-animal imaging.Magnetic resonance in medicine · 2025Review
- Comparison of different neurite density metrics with brain asymmetry evaluation.Zeitschrift fur medizinische Physik · 2025Article
- SpinFlowSim: A blood flow simulation framework for histology-informed diffusion MRI microvasculature mapping in cancer.Medical image analysis · 2025Article
- Revealing membrane integrity and cell size from diffusion kurtosis time dependence.Magnetic resonance in medicine · 2025Article
1 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Phantoms, both numerical (software) and physical (hardware), can serve as a gold standard for the validation of MRI methods probing the brain microstructure. This review aims to provide guidelines on how to build, implement, or choose the right phantom for a particular application, along with an overview of the current state-of-the-art of phantoms dedicated to study brain microstructure with MRI. For physical phantoms, we discuss the essential requirements and relevant characteristics of both the (NMR visible) liquid and (NMR invisible) phantom materials that induce relevant microstructural features detectable via MRI, based on diffusion, intra-voxel incoherent motion, magnetization transfer or magnetic susceptibility weighted contrast. In particular, for diffusion MRI, many useful phantoms have been proposed, ranging from simple liquids to advanced biomimetic phantoms consisting of hollow or plain microfibers and capillaries. For numerical phantoms, the focus is on Monte Carlo simulations of random walk, for which the basic principles, along with useful criteria to check and potential pitfalls are reviewed, in addition to a literature overview highlighting recent advances. While many phantoms exist already, the current review aims to stimulate further research in the field and to address remaining needs.
Indexed as
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What OpenQuestion holds
Registered trials
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.