MR susceptibility imaging
Open accessAbstract
This work reviews recent developments in the use of magnetic susceptibility contrast for human MRI, with a focus on the study of brain anatomy. The increase in susceptibility contrast with modern high field scanners has led to novel applications and insights into the sources and mechanism contributing to this contrast in brain tissues. Dedicated experiments have demonstrated that in most of healthy brain, iron and myelin dominate tissue susceptibility variations, although their relative contribution varies substantially. Local variations in these compounds can affect both amplitude and frequency of the MRI signal. In white matter, the myelin sheath introduces an anisotropic susceptibility that has distinct effects on the water compartments inside the axons, between the myelin sheath, and the axonal space, and renders their signals dependent on the angle between the axon and the magnetic field. This offers opportunities to derive tissue properties specific to these cellular compartments.
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Myelin and iron decrease T2*, but have an opposing effect on frequency owing to the diamagnetic properties of myelin (as opposed to iron's paramagnetic properties).
“Myelin and iron decrease T2*, but have an opposing effect on frequency owing to the diamagnetic properties of myelin (as opposed to iron’s paramagnetic properties).204”
From The role of iron in brain ageing and neurodegenerative disorders (2014) · cites this paper as [204]
Studies at high-field strength show that the confounding effect of myelin on T2* can be accounted for by including frequency information, which is normally discarded.
“Additionally, studies at high-field strength show that the confounding effect of myelin on T2* can be accounted for by including frequency information, which is normally discarded.51,203,204”
From The role of iron in brain ageing and neurodegenerative disorders (2014) · cites this paper as [204]
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Tumor blood vessel visualization
Missbach‐Guentner, J., Hunia, J., & Alves, F. (2011) · The International Journal of Developmental Biology · doi:10.1387/ijdb.103229jm · Cited by 19 · see citing works
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Limitations of rapid myelin water quantification using 3D bSSFP
Lenz, C., Klarhöfer, M., & Scheffler, K. (2010) · Magnetic Resonance Materials in Physics Biology and Medicine · doi:10.1007/s10334-010-0211-1 · Cited by 18 · see citing works
Novel frontiers in ultra-structural and molecular MRI of the brain
Duyn, J. H., & Koretsky, A. P. (2011) · Current Opinion in Neurology · doi:10.1097/wco.0b013e328348972a · Cited by 18 · see citing works
Self-citationMR imaging detection of calcified intracranial lesions and differentiation from iron‐laden lesions
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Microfabricated high‐moment micrometer‐sized MRI contrast agents
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Multimodal population brain imaging in the UK Biobank prospective epidemiological study
Miller, K. L., Alfaro-Almagro, F., Bangerter, N. K., Thomas, D. L., Yacoub, E., Xu, J., Bartsch, A. J., Jbabdi, S., Sotiropoulos, S. N., Andersson, J. L. R., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4393 · Cited by 2,020 · see citing works
The role of iron in brain ageing and neurodegenerative disorders
Ward, R. J., Zucca, F. A., Duyn, J. H., Crichton, R. R., & Zecca, L. (2014) · The Lancet Neurology · doi:10.1016/s1474-4422(14)70117-6 · Cited by 1,819 · see citing works
Self-citationOverview of quantitative susceptibility mapping
Deistung, A., Schweser, F., & Reichenbach, J. R. (2017) · NMR in Biomedicine · doi:10.1002/nbm.3569 · Cited by 338 · see citing works
Quantitative susceptibility mapping using deep neural network: QSMnet
Yoon, J., Gong, E., Chatnuntawech, I., Bilgic, B., Lee, J., Jung, W., Ko, J., Jung, H., Setsompop, K., Zaharchuk, G., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.06.030 · Cited by 185 · see citing works
- Authors
- Duyn, J.
- Affiliations
- National Institutes of Health (US)
- Corresponding author
- Duyn, Jeff
- ORCID
- Duyn, Jeff
- Venue
- Journal of Magnetic Resonance
- Publisher
- Elsevier BV
- Published
- 2013-04
- Volume
- 229
- Pages
- 198-207
- ISSN
- 1090-7807 (ISSN-L)
- PMC
- PMC3602381
- OpenAlex
- W2172159160
- Cited by
- 95
- References
- 108
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 4 · 2023: 6 · 2022: 3 · 2021: 10 · 2020: 13 · 2019: 6 · 2018: 10 · 2017: 9 · 2016: 10 · 2015: 5 · 2014: 8 · 2013: 4
- FWCI
- 4.11
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Journal of Magnetic Resonance (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Institute of Neurological Disorders and Stroke (ZIANS002990)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Physical Sciences › Physics and Astronomy › Nuclear and High Energy Physics › NMR spectroscopy and applications
- Keywords
- magnetic susceptibility contrast, brain MRI, iron, myelin, white matter, anisotropic susceptibility, high-field MRI
- MeSH terms
- Algorithms, Animals, Axons, Brain, Brain Chemistry, Electromagnetic Fields, Humans, Image Processing, Computer-Assisted, Iron, Magnetic Resonance Imaging, Myelin Sheath, Anisotropy, Echo-Planar Imaging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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