AUTHOR=Onicas Adrian I. , Ware Ashley L. , Harris Ashley D. , Beauchamp Miriam H. , Beaulieu Christian , Craig William , Doan Quynh , Freedman Stephen B. , Goodyear Bradley G. , Zemek Roger , Yeates Keith Owen , Lebel Catherine TITLE=Multisite Harmonization of Structural DTI Networks in Children: An A-CAP Study JOURNAL=Frontiers in Neurology VOLUME=13 YEAR=2022 URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2022.850642 DOI=10.3389/fneur.2022.850642 ISSN=1664-2295 ABSTRACT=
The analysis of large, multisite neuroimaging datasets provides a promising means for robust characterization of brain networks that can reduce false positives and improve reproducibility. However, the use of different MRI scanners introduces variability to the data. Managing those sources of variability is increasingly important for the generation of accurate group-level inferences. ComBat is one of the most promising tools for multisite (multiscanner) harmonization of structural neuroimaging data, but no study has examined its application to graph theory metrics derived from the structural brain connectome. The present work evaluates the use of ComBat for multisite harmonization in the context of structural network analysis of diffusion-weighted scans from the Advancing Concussion Assessment in Pediatrics (A-CAP) study. Scans were acquired on six different scanners from 484 children aged 8.00–16.99 years [Mean = 12.37 ± 2.34 years; 289 (59.7%) Male] ~10 days following mild traumatic brain injury (