Abstract
Background: Multi-site functional MRI (fMRI) databases are becoming increasingly prevalent in the study of neurodevelopmental and psychiatric disorders. However, multi-site databases are known to introduce site effects that may confound neurobiological and measures such as functional connectivity (FC). Although studies have been conducted to mitigate site effects, these methods often result in reduced effect size in FC comparisons between controls and patients.Methods: We present a site-wise de-meaning (SWD) strategy in multi-site FC analysis and compare its performance with two common site-effect mitigation methods, i.e., generalized linear model (GLM) and Combining Batches (ComBat) Harmonization. For SWD, after FC was calculated and Fisher z-transformed, the site-wise FC mean was removed from each subject before group-level statistical analysis. The above methods were tested on two multi-site psychiatric consortiums [Autism Brain Imaging Data Exchange (ABIDE) and Bipolar and Schizophrenia Network on Intermediate Phenotypes (B-SNIP)]. Preservation of consistent FC alterations in patients were evaluated for each method through the effect sizes (Hedge’s g) of patients vs. controls.Results: For the B-SNIP dataset, SWD improved the effect size between schizophrenic and control subjects by 4.5–7.9%, while GLM and ComBat decreased the effect size by 22.5–42.6%. For the ABIDE dataset, SWD improved the effect size between autistic and control subjects by 2.9–5.3%, while GLM and ComBat decreased the effect size by up to 11.4%.Conclusion: Compared to the original data and commonly used methods, the SWD method demonstrated superior performance in preserving the effect size in FC features associated with disorders.
Highlights
Neuroimaging has become a powerful tool in studying psychiatric disorders (Peter et al, 2018)
For the Autism Brain Imaging Data Exchange (ABIDE) dataset, site-wise de-meaning (SWD) improved the effect size between autistic and control subjects by 2.9–5.3%, while generalized linear model (GLM) and Combining Batches (ComBat) decreased the effect size by up to 11.4%
Compared to the original data and commonly used methods, the SWD method demonstrated superior performance in preserving the effect size in functional connectivity (FC) features associated with disorders
Summary
Neuroimaging has become a powerful tool in studying psychiatric disorders (Peter et al, 2018). Multi-site neuroimaging consortiums are becoming increasingly common in attempts to capture heterogeneity associated with various disorders, as well as to increase geographic variability, sample size, and statistical power (Van Horn and Toga, 2009). FMRI data from different sites may contain scanner and site variability, leading to conflicting results and inferior reliability (Van Horn and Toga, 2009; Newton et al, 2012; Birn et al, 2013; Rane et al, 2014; An et al, 2017; Badhwar et al, 2019). In many multi-site consortiums, individual imaging sites utilized different scanning parameters, including repetition time, echo time, acquisition time, voxel size, flip angle, field of view, and slice thickness, in collecting fMRI data. The use of different scanning parameters has been known to influence resting-state fMRI results (Newton et al, 2012; Birn et al, 2013; Rane et al, 2014). Studies have been conducted to mitigate site effects, these methods often result in reduced effect size in FC comparisons between controls and patients
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