Structural Connectivity Alterations Within Frontal Subregions in Parkinson's Disease: Implications for Motor Dysfunction.
Structural Connectivity Alterations Within Frontal Subregions in Parkinson's Disease: Implications for Motor Dysfunction.
Where did the research take place?
The study site has not been established. Author addresses may differ from where the research occurred.
Qingdao, CN · Author affiliation
College of Control Science and Engineering, China University of Petroleum (East China), Qingdao 266580, PR China (Y.Y., W.L., Y.W.).Location evidence
Nottingham, GB · Author affiliation
School of Medicine, Queen's Medical Centre, University of Nottingham, Nottingham, UK (M.K.); NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK (M.K.).Location evidence
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Original abstract
RATIONALE AND OBJECTIVES: Parkinson's disease (PD) is characterized by disrupted basal ganglia-thalamo-cortical connectivity, yet how frontal network topology relates to motor phenotype heterogeneity remains unclear. Conventional atlas-based approaches average out microscale organization within heterogeneous cortical areas. This study aimed to characterize fine-grained frontal subregional connectivity alterations in PD using high-resolution structural network analysis. MATERIALS AND METHODS: Twenty-three patients with PD and 22 age- and sex-matched controls underwent diffusion tensor imaging and T1-weighted magnetic resonance imaging. Individual high-resolution frontal networks were constructed, and graph-theoretical metrics were computed for each frontal subregion to quantify connectivity patterns. Consensus Louvain clustering assessed modularity, and machine learning with SHapley Additive exPlanations interpretation performed individual classification. RESULTS: Patients with PD exhibited heterogeneous topological alterations across multiple frontal subregions (corrected p < 0.05). The left rostral middle frontal gyrus (RMF.L) showed increased density and degree, whereas the lateral and medial orbitofrontal cortices showed decreases. RMF.L further exhibited a greater number of modules together with an altered modular organization. These topological alterations were significantly correlated with UPDRS-III motor scores. Topological features achieved a diagnostic accuracy of 91.69% for PD diagnosis and 91.90% for subtype differentiation, exceeding the performance of connectivity-based features. CONCLUSION: Intraregional topological reorganization within the frontal lobe, most prominently in RMF.L, was associated with motor impairment in PD and may reflect maladaptive network remodeling. High-resolution network analysis may provide a sensitive framework for characterizing intraregional structural reorganization in PD and warrants further validation as an adjunctive imaging marker for disease stratification.