The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Magnetic susceptibility mapping of brain tissue in vivo using MRI phase data
Open accessAbstract
Phase images in susceptibility‐weighted MRI of brain provide excellent contrast. However, the phase is affected by tissue geometry and orientation relative to the main magnetic field (B0), and phase changes extend beyond areas of altered susceptibility. Magnetic susceptibility, on the other hand, is an intrinsic tissue property, closely reflecting tissue composition. Therefore, recently developed inverse Fourier‐based methods were applied to calculate susceptibility maps from high‐resolution phase images acquired at a single orientation at 7 T in the human brain (in vivo and fixed) and at 11.7 T in fixed marmoset brain. In susceptibility images, the contrast of cortical layers was more consistent than in phase images and was independent of the structures' orientation relative to B0. The contrast of iron‐rich deep‐brain structures (red nucleus and substantia nigra) in susceptibility images agreed more closely with iron‐dominated R images than the phase image contrast, which extended outside the structures. The mean susceptibility in these regions was significantly correlated with their estimated iron content. Susceptibility maps calculated using this method overcome the orientation‐dependence and non‐locality of phase image contrast and seem to reflect underlying tissue composition. Susceptibility images should be easier to interpret than phase images and could improve our understanding of the sources of susceptibility contrast. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The rician distribution of noisy mri data
Gudbjartsson, H., & Patz, S. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340618 · Cited by 2,494
Susceptibility weighted imaging (SWI)
Haacke, E. M., Xu, Y., Cheng, Y. N., & Reichenbach, J. R. (2004) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20198 · Cited by 1,582
Schenck, J. F. (1996) · Medical Physics · doi:10.1118/1.597854 · Cited by 1,522
The effect of age on the non-haemin iron in the human brain
Hallgren, B., & Sourander, P. (1958) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.1958.tb12607.x · Cited by 1,427
Theory of NMR signal behavior in magnetically inhomogeneous tissues: The static dephasing regime
Yablonskiy, D. A., & Haacke, E. M. (1994) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910320610 · Cited by 1,198
Imaging iron stores in the brain using magnetic resonance imaging
Haacke, E. M., Cheng, N. Y. C., House, M. J., Liu, Q., Neelavalli, J., Ogg, R. J., Khan, A., Ayaz, M., Kirsch, W., & Obenaus, A. (2005) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2004.10.001 · Cited by 995
Fast, automated, N‐dimensional phase‐unwrapping algorithm
Jenkinson, M. (2003) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10354 · Cited by 695
High-field MRI of brain cortical substructure based on signal phase
Duyn, J. H., van Gelderen, P., Li, T.-Q., de Zwart, J. A., Koretsky, A. P., & Fukunaga, M. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0610821104 · Cited by 641
Self-citationHomodyne detection in magnetic resonance imaging
Noll, D. C., Nishimura, D. G., & Macovski, A. (1991) · IEEE Transactions on Medical Imaging · doi:10.1109/42.79473 · Cited by 514
Liu, T., Spincemaille, P., de Rochefort, L., Kressler, B., & Wang, Y. (2009) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21828 · Cited by 454
Cited by
Quantitative susceptibility mapping (QSM): Decoding MRI data for a tissue magnetic biomarker
Wang, Y., & Liu, T. (2015) · Magnetic Resonance in Medicine · doi:10.1002/mrm.25358 · Cited by 878
Langkammer, C., Schweser, F., Krebs, N., Deistung, A., Goessler, W., Scheurer, E., Sommer, K., Reishofer, G., Yen, K., Fazekas, F., et al. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.05.049 · Cited by 801
Schweser, F., Deistung, A., Lehr, B. W., & Reichenbach, J. R. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.10.070 · Cited by 710
Quantitative susceptibility mapping of human brain reflects spatial variation in tissue composition
Li, W., Wu, B., & Liu, C. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.11.088 · Cited by 624
Pros and cons of ultra-high-field MRI/MRS for human application
Ladd, M. E., Bachert, P., Meyerspeer, M., Moser, E., Nagel, A. M., Norris, D. G., Schmitter, S., Speck, O., Straub, S., & Zaiss, M. (2018) · Progress in Nuclear Magnetic Resonance Spectroscopy · doi:10.1016/j.pnmrs.2018.06.001 · Cited by 544
Metadata
- Authors
- Shmueli, K., de Zwart, J. A., van Gelderen, P., Li, T., Dodd, S. J., & Duyn, J. H.
- Venue
- Magnetic Resonance in Medicine
- Publisher
- Wiley
- Published
- 2009-10-26
- Volume
- 62
- Issue
- 6
- Pages
- 1510-1522
- ISSN
- 0740-3194 (ISSN-L)
- 1522-2594
- OpenAlex
- W1974155908
- Cited by
- 527
- References
- 24
- FWCI
- 16.68
- Type
- journal article
- Language
- en
- Open access
- bronze
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.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Magnetic susceptibility mapping of brain tissue in vivo using MRI phase data. https://app.cochat.ai/papers/10.1002/mrm.22135
- The paper
- Shmueli, K., de Zwart, J. A., van Gelderen, P., Li, T., Dodd, S. J., & Duyn, J. H. (2009). Magnetic susceptibility mapping of brain tissue in vivo using MRI phase data. Magnetic Resonance in Medicine. https://doi.org/10.1002/mrm.22135
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.