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BackgroundThe underlying mechanisms linking structural and metabolic alterations of idiopathic Parkinson's disease (IPD) remain poorly understood. Utilizing integrated PET/MR for its precise spatial correlation, this study investigated the temporal relationship between gray matter (GM) atrophy and reduced FDG SUVR (RFS) across IPD stages to provide insights for early diagnosis.MethodsThis prospective study recruited 90 IPD patients stratified by Hoehn-Yahr (H-Y) stage into mild, moderate, and severe groups, alongside 30 age-matched healthy controls (HC). All participants underwent integrated 18F-FDG PET/MR imaging. SPM was used to extract the GM volume (VGM) and standardized uptake value ratio for each brain region. Group differences were analyzed with one-way ANOVA and Bonferroni tests. Spearman correlation analysis was utilized to evaluate the associations of both VGM and metabolic changes with H-Y staging. Individual Z-scores for VGM and metabolic alterations were calculated, and their relationship was examined using Spearman/Pearson correlation, followed by paired t-tests to compare their differences.ResultWith disease progression, GM atrophy and RFS in IPD patients gradually extend from focal to widespread patterns. A characteristic pattern of cerebral hypermetabolism was observed in IPD. H-Y stage demonstrated a significant inverse correlation with the extent of both brain GM atrophy (affecting 82 out of 90 regions) and RFS (affecting 20 regions). Conversely, it was positively correlated with hypermetabolism in regions including the sensorimotor cortex, amygdala, and globus pallidus. Moderate correlations between atrophy and RFS were confined to the left inferior parietal lobule (r = 0.619, p r = 0.612, p ConclusionWidespread RFS predominates during early stages, whereas structural atrophy gradually becomes the dominant imaging feature as the disease advances. These alterations are significantly correlated with disease severity, underscoring the potential of multimodal imaging biomarkers for the early diagnosis of IPD and monitor its progression.
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