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Congress: ECR25
Poster Number: C-19515
Type: Poster: EPOS Radiologist (scientific)
DOI: 10.26044/ecr2025/C-19515
Authorblock: L. Guardiano, A. Stone, S. Cournane, L. Leon-Vintro; Dublin/IE
Disclosures:
Lawrence Guardiano: Nothing to disclose
Alan Stone: Nothing to disclose
Seán Cournane: Nothing to disclose
Luis Leon-Vintro: Nothing to disclose
Keywords: MR physics, Neuroradiology brain, Experimental, Image manipulation / Reconstruction, MR, Imaging sequences, Physics, Technology assessment, Quality assurance, Tissue characterisation
References

[1] K. E. Keenan et al., “Recommendations towards standards for quantitative MRI (qMRI) and outstanding needs,” J. Magn. Reson. Imaging, vol. 49, no. 7, Jun. 2019, doi: 10.1002/jmri.26598.

[2] A. Hervouin, J. Bézy-Wendling, and F. Noury, “How to accurately quantify brain magnetic susceptibility in the context of Parkinson’s disease: Validation on phantoms and healthy volunteers at 1.5 and 3 T,” NMR Biomed., vol. n/a, no. n/a, p. e5182, doi: 10.1002/nbm.5182.

[3] E. Olsson, R. Wirestam, and E. Lind, “MRI-Based Quantification of Magnetic Susceptibility in Gel Phantoms: Assessment of Measurement and Calculation Accuracy,” Radiol. Res. Pract., vol. 2018, pp. 1–13, Jul. 2018, doi: 10.1155/2018/6709525.

[4] T. Liu, W. Xu, P. Spincemaille, A. S. Avestimehr, and Y. Wang, “Accuracy of the Morphology Enabled Dipole Inversion (MEDI) Algorithm for Quantitative Susceptibility Mapping in MRI,” IEEE Trans. Med. Imaging, vol. 31, no. 3, pp. 816–824, Mar. 2012, doi: 10.1109/TMI.2011.2182523.

[5] N. Hobson et al., “Phantom validation of quantitative susceptibility and dynamic contrast‐enhanced permeability MR sequences across instruments and sites,” J. Magn. Reson. Imaging, vol. 51, no. 4, pp. 1192–1199, Apr. 2020, doi: 10.1002/jmri.26927.

[6] QSM Consensus Organization Committee et al., “Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro-magnetic tissue properties study group,” Magn. Reson. Med., vol. 91, no. 5, pp. 1834–1862, May 2024, doi: 10.1002/mrm.30006.

[7] K.-S. Chan and J. P. Marques, “SEPIA—Susceptibility mapping pipeline tool for phase images,” NeuroImage, vol. 227, p. 117611, Feb. 2021, doi: 10.1016/j.neuroimage.2020.117611.

[8] M. Jenkinson, C. F. Beckmann, T. E. J. Behrens, M. W. Woolrich, and S. M. Smith, “FSL,” NeuroImage, vol. 62, no. 2, pp. 782–790, Aug. 2012, doi: 10.1016/j.neuroimage.2011.09.015.

[9] A. Karsa, S. Punwani, and K. Shmueli, “High Repeatability of Quantitative Susceptibility Mapping (QSM) in the Head and Neck With a View to Detecting Hypoxic Cancer Sites,” presented at the 27th Annual Meeting of the ISMRM, Montreal, 2019.

[10] T. Liu et al., “Morphology enabled dipole inversion (MEDI) from a single-angle acquisition: Comparison with COSMOS in human brain imaging,” Magn. Reson. Med., vol. 66, no. 3, pp. 777–783, 2011, doi: 10.1002/mrm.22816.

[11] W. Li, B. Wu, and C. Liu, “Quantitative susceptibility mapping of human brain reflects spatial variation in tissue composition,” NeuroImage, vol. 55, no. 4, pp. 1645–1656, Apr. 2011, doi: 10.1016/j.neuroimage.2010.11.088.

[12] S. Wharton, A. Schäfer, and R. Bowtell, “Susceptibility mapping in the human brain using threshold-based k-space division,” Magn. Reson. Med., vol. 63, no. 5, pp. 1292–1304, 2010, doi: 10.1002/mrm.22334.
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