The combination of the 18F-FDG PET and susceptibility-weighted imaging for diagnosis of cerebral glucose metabolism and iron deposition in Parkinson’s disease - Zhibing He; Chao Yang; Ling Zhou; Shuang Li (Scientific Reports)
Abstract This study aimed to evaluate the diagnostic potential of combining 18F-FDG PET and susceptibility-weighted imaging (SWI) to assess cerebral glucose metabolism and iron deposition patterns in Parkinson’s disease (PD), and to determine their correlations with clinical progression and diagnostic accuracy. Forty-nine PD patients and 70 age-/sex-matched healthy controls underwent standardized 18F-FDG PET and SWI. Metabolic activity (SUVR) and SWI phase values were quantified in cortical/subcortical regions. Statistical analyses included Mann–Whitney U tests, Pearson/Spearman correlations, and ROC curve analysis to evaluate biomarker-clinical relationships and diagnostic performance. PD patients exhibited hypometabolism in frontal, parietal, and temporal cortices (P < 0.05) and hypermetabolism in the putamen, globus pallidus, and cerebellum (P < 0.05). Cortical hypometabolism correlated with Hoehn-Yahr (H-Y) stages (e.g., temporal lobe: r = − 0.405, P = 0.004) and UPDRS III scores (e.g., frontal cortex: r = − 0.364, P = 0.011). SWI revealed reduced phase values in the substantia nigra, red nucleus, and basal ganglia (P < 0.001), with substantia nigra phase values strongly correlating with H-Y stages (r = − 0.525) and UPDRS III scores (r = − 0.446). Multimodal integration of 18F-FDG PET and SWI achieved superior diagnostic accuracy (AUC = 0.844) compared to single-modality models (PET: AUC = 0.777; SWI: AUC = 0.780, P < 0.0001). The integration of 18F-FDG PET and SWI enhances PD diagnosis by capturing complementary metabolic and iron deposition biomarkers. Cortical hypometabolism may precede subcortical iron accumulation, aligning with Braak staging theory. Limitations include cross-sectional design and technical constraints in SWI quantification. Future studies should validate these findings with longitudinal cohorts and advanced techniques like QSM.