The DOI matches its Crossref record; 127 of the 127 references it cites were found in a registry or an index.
In Vivo Quantitative Susceptibility Mapping (QSM) in Alzheimer's Disease
Open accessAbstract
BACKGROUND: This study explores the magnetostatic properties of the Alzheimer's disease brain using a recently proposed, magnetic resonance imaging, postprocessed contrast mechanism. Quantitative susceptibility mapping (QSM) has the potential to monitor in vivo iron levels by reconstructing magnetic susceptibility sources from field perturbations. However, with phase data acquired at a single head orientation, the technique relies on several theoretical approximations and requires fast-evolving regularisation strategies. METHODS: In this context, the present study describes a complete methodological framework for magnetic susceptibility measurements with a review of its theoretical foundations. FINDINGS AND SIGNIFICANCE: The regional and whole-brain cross-sectional comparisons between Alzheimer's disease subjects and matched controls indicate that there may be significant magnetic susceptibility differences for deep brain nuclei--particularly the putamen--as well as for posterior grey and white matter regions. The methodology and findings described suggest that the QSM method is ready for larger-scale clinical studies.
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Older Adults' Reasons for Using Technology while Aging in Place
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Fast robust automated brain extraction
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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
Liu, C., Li, W., Tong, K. A., Yeom, K. W., & Kuzminski, S. (2015) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.24768 · Cited by 503
Overview of quantitative susceptibility mapping
Deistung, A., Schweser, F., & Reichenbach, J. R. (2017) · NMR in Biomedicine · doi:10.1002/nbm.3569 · Cited by 338
Wáng, Y. X. J., & Idée, J.-M. (2017) · Quantitative Imaging in Medicine and Surgery · doi:10.21037/qims.2017.02.09 · Cited by 247
Gong, N.-J., Dibb, R., Bulk, M., van der Weerd, L., & Liu, C. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.02.019 · Cited by 162
Metadata
- Authors
- Acosta-Cabronero, J., Williams, G. B., Cardenas-Blanco, A., Arnold, R. J., Lupson, V., & Nestor, P. J.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-11-21
- Volume
- 8
- Issue
- 11
- Pages
- e81093
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W2126681103
- Cited by
- 287
- References
- 127
- FWCI
- 8.32
- Type
- journal article
- Language
- en
- Open access
- gold
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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.
