ComBat harmonization for multi-site fixel-based analysis using traveling subject dataset

Motivation: Although multi-site DWI with large sample size has high statistical power and is sensitive to the subtle microstructural tissue changes, different models or protocols-induced measurement biases affect the reliability and reproducibility of the study. Therefore, harmonization is necessary to improve this issue. Goal(s): The goal of our study is to evaluate the effectiveness of ComBat harmonization in mitigating measurement biases in FBA measures. Approach: Our study utilized a traveling-subject DWI dataset, while various FBA measures were calculated and subsequently harmonized using the ComBat method. Results: Our findings demonstrated that ComBat harmonization could effectively mitigate site, model, and protocol-induced measurement biases in FBA measures. Impact: A significant contribution of this study is the seamless integration of ComBat into the fixel-based framework, which may enhance the reliability and reproducibility of multi-site research, offering a valuable tool for investigating microstructural tissue changes in the large-scale, multi-site studies.