Comparison of different approaches to manage multi-site magnetic resonance spectroscopy clinical data analysis

La, P. L., Bell, T. K., Craig, W., Doan, Q., Beauchamp, M. H., Zemek, R., Yeates, K. O. and Harris, A. D. (2023) Comparison of different approaches to manage multi-site magnetic resonance spectroscopy clinical data analysis. Frontiers in Psychology, 14. 1130188. ISSN 1664-1078 doi: 10.3389/fpsyg.2023.1130188

Abstract/Summary

Introduction The effects caused by differences in data acquisition can be substantial and may impact data interpretation in multi-site/scanner studies using magnetic resonance spectroscopy (MRS). Given the increasing use of multi-site studies, a better understanding of how to account for different scanners is needed. Using data from a concussion population, we compare ComBat harmonization with different statistical methods in controlling for site, vendor, and scanner as covariates to determine how to best control for multi-site data. Methods The data for the current study included 545 MRS datasets to measure tNAA, tCr, tCho, Glx, and mI to study the pediatric concussion acquired across five sites, six scanners, and two different MRI vendors. For each metabolite, the site and vendor were accounted for in seven different models of general linear models (GLM) or mixed-effects models while testing for group differences between the concussion and orthopedic injury. Models 1 and 2 controlled for vendor and site. Models 3 and 4 controlled for scanner. Models 5 and 6 controlled for site applied to data harmonized by vendor using ComBat. Model 7 controlled for scanner applied to data harmonized by scanner using ComBat. All the models controlled for age and sex as covariates. Results Models 1 and 2, controlling for site and vendor, showed no significant group effect in any metabolites, but the vendor and site were significant factors in the GLM. Model 3, which included a scanner, showed a significant group effect for tNAA and tCho, and the scanner was a significant factor. Model 4, controlling for the scanner, did not show a group effect in the mixed model. The data harmonized by the vendor using ComBat (Models 5 and 6) had no significant group effect in both the GLM and mixed models. Lastly, the data harmonized by the scanner using ComBat (Model 7) showed no significant group effect. The individual site data suggest there were no group differences. Conclusion Using data from a large clinical concussion population, different analysis techniques to control for site, vendor, and scanner in MRS data yielded different results. The findings support the use of ComBat harmonization for clinical MRS data, as it removes the site and vendor effects.

Item Type	Article
URI	https://centaur.reading.ac.uk/id/eprint/125516
Identification Number/DOI	10.3389/fpsyg.2023.1130188
Refereed	Yes
Divisions	No Reading authors. Back catalogue items Life Sciences > School of Psychology and Clinical Language Sciences > Department of Psychology
Publisher	Frontiers Media
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