Application of Fully Convolutional Neural Networks in the Assessment of Cerebral White Matter Involvement in Primary Sjögren's Syndrome.

Although covariate adjustment slightly reduced effect sizes and reduced the number of marginally significant findings, the core set of highly affected tracts remained significant, confirming that the observed alterations are robust and not attributable to demographic confounding.

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In contrast, pathological RF positivity demonstrated only one nominally significant association at the Pearson level, which did not persist after BH adjustment, suggesting a modest or tract-restricted effect.

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The strongest effects were found in cerebellar peduncles, anterior thalamic radiations, fronto-pontine tracts, and corticospinal tracts, all showing large standardized mean differences (Cohen’s d raging from − 1.5 to − 2.5) and highly significant Mann–Whitney U test results.

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