Reducing Inter-Site Variability for Fluctuation Amplitude Metrics in Multisite Resting State BOLD-fMRI Data.

Area of Science:

• Neuroimaging
• Quantitative MRI
• Brain Signal Analysis

Background:

• Resting state fluctuation amplitude (RSFA) exhibits significant inter-site variability, hindering multisite neuroimaging studies.
• Global normalization methods reduce site effects but risk introducing artificial findings.

Purpose of the Study:

• To identify alternative strategies for minimizing RSFA inter-site variability without compromising data integrity.
• To evaluate the effectiveness of controlling confounding factors as a harmonization approach.

Main Methods:

• Modified the amplitude of low-frequency fluctuation (ALFF) algorithm for conceptual validation and data length insensitivity.
• Investigated the relationship between global mean ALFF/fALFF and BOLD signal intensity/TRs across sites.
• Assessed the impact of signal intensity rescaling and TR controlling on RSFA inter-site variability.

Main Results:

• Global mean ALFF correlated with BOLD signal intensity; global mean fALFF correlated with TRs.
• Raw RSFA showed significant inter-site variations in both gray and white matter.
• Signal intensity rescaling reduced ALFF variability but did not eliminate it; TR controlling completely removed fALFF site effects.
• fALFF inter-site variability was reduced to an acceptable level, with detection power comparable to monosite data.

Conclusions:

• Controlling for signal intensity, TR, and full-band power can effectively harmonize RSFA across sites.
• These confounding factor controls offer a viable alternative to global normalization, avoiding spurious results.
• This approach enhances the reliability of RSFA in multisite neuroimaging research.