Abstract
Increased brain water content (BWC) of up to 12% has been reported in brain inflammatory disease. However, no study has assessed variation of BWC in peripheral inflammatory disease, such as psoriasis. BWC, as one of the reference standards in quantitative magnetic resonance spectroscopy (MRS), has not been considered by previous studies mostly due to the challenge of acquiring the water signal within tolerable times in patients, for accurate estimation of BWC. In this study, we developed a technique of BWC quantification by optimizing the standard MRS acquisition from which unsuppressed water spectra were extracted by post-processing. The extracted in vivo unsuppressed water signal was adjusted for all necessary correction factors and calibrated against a reference signal deduced from voxel position-dependent polynomial equations derived from head coil sensitivity maps obtained from phantom experiments. Experiments were conducted on psoriasis patients and controls, comprising 16 (8 males, 8 females) participants in each group. CHESS water-suppressed spectra were recorded from the anterior cingulate cortex and bilateral hippocampi of participants using the standard PRESS sequence. BWC did not vary significantly (pā>ā0.05) between patients and controls, across all the brain regions of both patients and controls, and in patients at baseline and post anti-inflammatory medication. BWC in this study compared with published estimates, indicating that the technique is accurate. The results further indicate that BWC is unaltered in peripheral inflammation, and thus support the use of BWC as an internal reference standard for absolute quantitative MRS studies of peripheral inflammation.
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Acknowledgements
This study was funded by the Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE), University of Glasgow, and Sackler Institute of Psychological Research.
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Mumuni, A.N., McLean, J., Krishnadas, R., Lopez-Gonzalez, M.R., Cavanagh, J., Condon, B. (2019). Assessment of Brain Water Content in Peripheral Inflammation by an Optimized Single-Voxel MR Spectroscopy Quantitation Technique. In: Lhotska, L., Sukupova, L., LackoviÄ, I., Ibbott, G.S. (eds) World Congress on Medical Physics and Biomedical Engineering 2018. IFMBE Proceedings, vol 68/1. Springer, Singapore. https://doi.org/10.1007/978-981-10-9035-6_17
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DOI: https://doi.org/10.1007/978-981-10-9035-6_17
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