ArticleMagnetic resonance in medicine2018
Quantitative susceptibility mapping: Report from the 2016 reconstruction challenge.
Article in Magnetic resonance in medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 4 of them syntheses that pooled it.
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Who cites it
79 citing papers in PubMed, 4 syntheses or guidelines pooled it, 194 citations in OpenAlex.
- Quantitative susceptibility mapping in pediatric neuroimaging: a systematic review of applications and advancements.Pediatric radiology · 2026Pooled it
- Quantitative susceptibility mapping in multiple sclerosis: A systematic review and meta-analysis.NeuroImage. Clinical · 2024Pooled it
- Iron Imaging as a Diagnostic Tool for Parkinson's Disease: A Systematic Review and Meta-Analysis.Frontiers in neurology · 2020Pooled it
- MatchingFrontiers in neuroanatomy · 2019Pooled it
- Simulation of realistic brain phantoms for susceptibility tensor imaging.Magma (New York, N.Y.) · 2026Article
- Comment on "Diagnostic Potential of Macromolecular Proton Fraction Mapping Combined with Quantitative Susceptibility Mapping as a Subcortical Biomarker for Parkinson's Disease" by Fujiwara et al.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of 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
- Quantitative susceptibility mapping in magnetically inhomogeneous tissues.Magnetic resonance in medicine · 2025Article
- Imaging of Cerebral Iron as an Emerging Marker for Brain Aging, Neurodegeneration, and Cerebrovascular Diseases.Brain sciences · 2025Review
- Article
- Quantitative susceptibility mapping of the human carotid artery: Assessing sensitivity to elastin and collagen ex vivo.Magnetic resonance in medicine · 2025Article
- Comparing repeatability metrics for quantitative susceptibility mapping in the head and neck.Magma (New York, N.Y.) · 2025Article
- Midbrain and pallidal iron changes identify patients with REM sleep behaviour disorder and Parkinson's disease.NPJ Parkinson's disease · 2025Article
- Sensitivity of Quantitative Susceptibility Mapping for Clinical Research in Deep Gray Matter.Human brain mapping · 2025Article
- A pilot study assessing the clinical utility of deep learning-reconstructed 3D-echo-planar-imaging-based quantitative susceptibility mapping in multiple sclerosis.Frontiers in neuroscience · 2025Article
- Impact of processing and analysis methodology on thalamic susceptibility assessment in multiple sclerosis.PloS one · 2025Article
- Thalamic iron in multiple sclerosis: Waning support for the early-rise late-decline hypothesis.NeuroImage. Clinical · 2025Article
- Article
- Brain Magnetic Resonance Imaging in Wilson's Disease-Significance and Practical Aspects-A Narrative Review.Brain sciences · 2024Review
- Spinet-QSM: model-based deep learning with schatten p-norm regularization for improved quantitative susceptibility mapping.Magma (New York, N.Y.) · 2024Article
19 more citing papers are in PubMed but not listed here.
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Authors and funding
17 authors at 14 institutions in 8 countries.
Funding
Abstract
purposeThe aim of the 2016 quantitative susceptibility mapping (QSM) reconstruction challenge was to test the ability of various QSM algorithms to recover the underlying susceptibility from phase data faithfully.
methodsGradient-echo images of a healthy volunteer acquired at 3T in a single orientation with 1.06 mm isotropic resolution. A reference susceptibility map was provided, which was computed using the susceptibility tensor imaging algorithm on data acquired at 12 head orientations. Susceptibility maps calculated from the single orientation data were compared against the reference susceptibility map. Deviations were quantified using the following metrics: root mean squared error (RMSE), structure similarity index (SSIM), high-frequency error norm (HFEN), and the error in selected white and gray matter regions.
resultsTwenty-seven submissions were evaluated. Most of the best scoring approaches estimated the spatial frequency content in the ill-conditioned domain of the dipole kernel using compressed sensing strategies. The top 10 maps in each category had similar error metrics but substantially different visual appearance.
conclusionBecause QSM algorithms were optimized to minimize error metrics, the resulting susceptibility maps suffered from over-smoothing and conspicuity loss in fine features such as vessels. As such, the challenge highlighted the need for better numerical image quality criteria. Magn Reson Med 79:1661-1673, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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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.