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Scientific reports · 2025

The combination of the 18F-FDG PET and susceptibility-weighted imaging for diagnosis of cerebral glucose metabolism and iron deposition in Parkinson's disease.

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He Zhibing, Yang Chao, Zhou Ling, Li Shuang

Аннотация

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.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты