ArticleMagnetic resonance in medicine2021
QSM reconstruction challenge 2.0: A realistic in silico head phantom for MRI data simulation and evaluation of susceptibility mapping procedures.
Article in Magnetic resonance in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- A Realistic In Silico Brain Phantom for Quantifying Susceptibility Anisotropy-Induced Error in Susceptibility Separation.Magnetic resonance in medicine · 2026Article
- Simulation of realistic brain phantoms for susceptibility tensor imaging.Magma (New York, N.Y.) · 2026Article
- An external reference to enable quantitative susceptibility mapping (QSM) in absolute terms: theoretical considerations, simulations, and experimental evaluation.Magma (New York, N.Y.) · 2026Article
- Singular Value Decomposition-Based Coil Combination Improves the Accuracy and Noise-Robustness of Quantitative Susceptibility Maps.medRxiv : the preprint server for health sciences · 2026Article
- Quantitative Susceptibility Mapping in Skull Base Chordoma: In Silico Analysis and In Vivo Application Towards Indirect Hypoxia Assessment.Magnetic resonance in medicine · 2026Article
- Nonlinear inversion model-driven deep learning method for magnetic resonance imaging (MRI) quantitative susceptibility mapping imaging.Quantitative imaging in medicine and surgery · 2026Article
- Mapping a reproducible water fraction and TMagnetic resonance in medicine · 2026Article
- Mapping heterogeneous region- and tissue-specific brain ageing patterns using quantitative MRI.Brain communications · 2026Article
- Quantitative MRI in Neuroimaging: A Review of Techniques, Biomarkers, and Emerging Clinical Applications.Brain sciences · 2025Review
- Quantitative susceptibility mapping in magnetically inhomogeneous tissues.Magnetic resonance in medicine · 2025Article
- Unraveling Microstructural and Macrostructural Brain Age Dynamics in Multiple Sclerosis.Neurology(R) neuroimmunology & neuroinflammation · 2025Article
- An Optimized Framework of QSM Mask Generation Using Deep Learning: QSMmask-Net.NMR in biomedicine · 2025Article
- Sensitivity of Quantitative Susceptibility Mapping for Clinical Research in Deep Gray Matter.Human brain mapping · 2025Article
- Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro-magnetic tissue properties study group.Magnetic resonance in medicine · 2024Article
- The Advanced BRain Imaging on ageing and Memory (ABRIM) data collection: Study design, data processing, and rationale.PloS one · 2024Article
- Region Expansion of Background Field Removal with Local Spherical Harmonics Approximation for Whole-brain Quantitative Susceptibility Mapping.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2023Article
- Evaluation of multi-channel phase reconstruction methods for quantitative susceptibility mapping on postmortem human brain.Journal of magnetic resonance open · 2023Article
- Toward a realistic in silico abdominal phantom for QSM.Magnetic resonance in medicine · 2023Article
- Investigating the effect of oblique image acquisition on the accuracy of QSM and a robust tilt correction method.Magnetic resonance in medicine · 2023Article
- Incomplete spectrum QSM using support information.Frontiers in neuroscience · 2023Article
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9 authors.
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Abstract
purposeTo create a realistic in silico head phantom for the second QSM reconstruction challenge and for future evaluations of processing algorithms for QSM.
methodsWe created a digital whole-head tissue property phantom by segmenting and postprocessing high-resolution (0.64 mm isotropic), multiparametric MRI data acquired at 7 T from a healthy volunteer. We simulated the steady-state magnetization at 7 T using a Bloch simulator and mimicked a Cartesian sampling scheme through Fourier-based processing. Computer code for generating the phantom and performing the MR simulation was designed to facilitate flexible modifications of the phantom in the future, such as the inclusion of pathologies as well as the simulation of a wide range of acquisition protocols. Specifically, the following parameters and effects were implemented: TR and TE, voxel size, background fields, and RF phase biases. Diffusion-weighted imaging phantom data are provided, allowing future investigations of tissue-microstructure effects in phase and QSM algorithms.
resultsThe brain part of the phantom featured realistic morphology with spatial variations in relaxation and susceptibility values similar to the in vivo setting. We demonstrated some of the phantom's properties, including the possibility of generating phase data with nonlinear evolution over TE due to partial-volume effects or complex distributions of frequency shifts within the voxel.
conclusionThe presented phantom and computer programs are publicly available and may serve as a ground truth in future assessments of the faithfulness of quantitative susceptibility reconstruction algorithms.
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