Autistic vs. Control Differences in MRI Scan Quality Across ABIDE-II Sites

Background: Head motion and variability in scan quality remain major methodological challenges in autism neuroimaging. Large multi-site datasets such as ABIDE-II provide a unique opportunity to systematically quantify diagnostic differences in MRI data quality and assess the influence of site-level heterogeneity. Methods: Functional MRI Quality Assessment Protocol (QAP) metrics were combined with phenotypic data from ABIDE-II. Participants were classified as autistic (ASD) or typically developing (TD). Key quality metrics-including mean framewise displacement (mFD), proportion of volumes exceeding 0.20 mm (FD > 0.20), signal-to-noise ratio (SNR), and entropy focus criterion (EFC)-were analyzed alongside age, sex, IQ, and site. Group differences were evaluated using non-parametric tests and linear mixed-effects models with site as a random factor. Additional analyses examined site-level heterogeneity and the impact of quality-control (QC) thresholds on sample composition. Results: The final sample included 1277 participants (579 ASD; 698 TD) across 14 sites. ASD participants exhibited significantly greater head motion (median mFD = 0.101 vs. 0.081 mm; p < 1 × 10^-10) and modest reductions in signal quality (lower SNR, higher EFC). Elevated motion in ASD was observed in 12 of 14 sites, although effect sizes varied substantially. Mixed-effects models confirmed that diagnosis remained a significant predictor of motion after adjusting for covariates. In contrast, signal-quality differences were small and largely explained by site effects. Simulated QC procedures disproportionately excluded ASD participants, with exclusion rates up to 31% compared to 18% in TD. Conclusions: ASD participants show consistently higher head motion, while signal-quality differences are minimal and largely site-driven. Standard QC procedures disproportionately exclude ASD individuals, highlighting the need for improved motion handling and more balanced quality-control strategies in multi-site studies.