2023/11/28 by Siying Zhu, Lijuan Wang, Xiang Lv +4 · 3 citations
Mathematics · Medicine · Neuroscience · #Advanced Neuroimaging Techniques and Applications #Artificial intelligence #Biology #Cluster analysis #Clustering coefficient #Combinatorics #Computer science #Default mode network #Diffusion MRI #Disconnection #Disease #Functional Brain Connectivity Studies #Functional magnetic resonance imaging #Kurtosis #Magnetic resonance imaging #Mathematics #Medicine #Neuroscience #Parkinson's Disease Mechanisms and Treatments #Pathology #Radiology #Statistics #Topology (electrical circuits)
paper · doi:10.1177/02841851231216039
published in Acta Radiologica 65(2), 233-240 (SAGE Publishing)
crossref issued 2023/11/28 · crossref published 2023/11/28 · crossref published-online 2023/11/28 · openalex publication_date 2023/11/28 · crossref created 2023/11/29 · crossref published-print 2024/02/01 · openalex created_date 2025/10/10 · crossref deposited 2026/04/28 · crossref indexed 2026/08/03 · openalex updated_date 2026/08/03
Background Parkinson's disease (PD) has been regarded as a disconnection syndrome with functional and structural disturbances. However, as the anatomic determinants, the structural disconnections in PD have yet to be fully elucidated. Purpose To non-invasively construct structural networks based on microstructural complexity and to further investigate their potential topological abnormalities in PD given the technical superiority of diffusion kurtosis imaging (DKI) to the quantification of microstructure. Material and Methods The microstructural data of gray matter in both the PD group and the healthy control (HC) group were acquired using DKI. The structural networks were constructed at the group level by a covariation approach, followed by the calculation of topological properties based on graph theory and statistical comparisons between groups. Results A total of 51 patients with PD and 50 HCs were enrolled. Individuals were matched between groups with respect to demographic characteristics ( P >0.05). The constructed structural networks in both the PD and HC groups featured small-world properties. In comparison with the HC group, the PD group exhibited significantly altered global properties, with higher normalized characteristic path lengths, clustering coefficients, local efficiency values, and characteristic path lengths and lower global efficiency values ( P <0.05). In terms of nodal centralities, extensive nodal disruptions were observed in patients with PD ( P <0.05); these disruptions were mainly distributed in the sensorimotor network, default mode network, frontal-parietal network, visual network, and subcortical network. Conclusion These findings contribute to the technical application of DKI and the elucidation of disconnection syndrome in PD.