Harmonization of multi-site MRS data with ComBat

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Bell, T. K. ORCID: https://orcid.org/0000-0002-9591-706X, Godfrey, K. J., Ware, A. L., Yeates, K. O. and Harris, A. D. (2022) Harmonization of multi-site MRS data with ComBat. NeuroImage, 257. 119330. ISSN 1053-8119 doi: 10.1016/j.neuroimage.2022.119330

Abstract/Summary

Magnetic resonance spectroscopy (MRS) is a non-invasive neuroimaging technique used to measure brain chem- istry in vivo and has been used to study the healthy brain as well as neuropathology in numerous neurological disorders. The number of multi-site studies using MRS are increasing; however, non-biological variability in- troduced during data collection across multiple sites, such as differences in scanner vendors and site-specific acquisition implementations for MRS, can obscure detection of biological effects of interest. ComBat is a data harmonization technique that can remove non-biological sources of variance in multisite studies. It has been validated for use with structural and functional MRI metrics but not for MRS measured metabolites. This study investigated the validity of using ComBat to harmonize MRS metabolites for vendor and site differences. Anal- yses were performed using data acquired across 20 sites and included edited MRS for GABA + ( N = 218) and macromolecule-suppressed GABA data ( N = 209), as well as standard PRESS data to quantify NAA, creatine, choline, and glutamate ( N = 190). ComBat harmonization successfully mitigated vendor and site differences for all metabolites of interest. Moreover, significant associations were detected between sex and choline levels and between age and glutamate and GABA + levels that were not detectable prior to harmonization, confirming the importance of removing site and vendor effects in multi-site data. In conclusion, ComBat harmonization can be successfully applied to MRS data in multi-site MRS studies.

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Item Type Article
URI https://reading-pure-test.eprints-hosting.org/id/eprint/125519
Identification Number/DOI 10.1016/j.neuroimage.2022.119330
Refereed Yes
Divisions Life Sciences > School of Psychology and Clinical Language Sciences > Department of Psychology
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