AUTHOR=La Parker L. , Bell Tiffany K. , Craig William , Doan Quynh , Beauchamp Miriam H. , Zemek Roger , Yeates Keith Owen , Harris Ashley D. 

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

JOURNAL=Frontiers in Psychology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2023.1130188

DOI=10.3389/fpsyg.2023.1130188

ISSN=1664-1078

ABSTRACT=Introduction: 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: Data for the current study includes 545 MRS datasets to measure tNAA, tCr, tCho, Glx, and mI, to study pediatric concussion acquired across 5 sites, 6 scanners, and 2 different MRI vendors. For each metabolite, site and vendor were accounted for in 7 different models of general linear model (GLM) or mixed effects models, while testing for group differences between 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 models controlled for age and sex as covariates.
Results: Models 1 and 2 controlled for site and vendor showed no significant effect of group in any metabolites, but vendor and site were significant factors in the GLM. Model 3, which included scanner, showed a significant effect of group for tNAA and tCho, and scanner was a significant factor. Model 4, controlling for scanner, did not show a group effect. Data harmonized by vendor using ComBat (Models 5 and 6) had no significant group effect in both the GLM and mixed models. Lastly, data harmonized by scanner using ComBat (Model 7) showed no significant group effect. Individual site data suggests 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 site and vendor effects.