Altered Structural Brain Connectivity in Postherpetic Neuralgia and its Association with Neuropathic Pain Severity: A Diffusion Tensor Imaging Study
摘要
Postherpetic neuralgia (PHN), the most severe complication of herpes zoster, causes persistent neuropathic pain that impairs quality of life. This study investigated alterations in structural brain connectivity in patients with PHN using diffusion tensor imaging (DTI) and examined associations with symptom severity. We enrolled 42 patients with PHN and 41 age- and sex-matched healthy controls. All participants underwent DTI, and data were analyzed using DSI Studio. Graph-theoretical network metrics were computed to assess global and local structural connectivity. PHN symptom severity was evaluated using the Douleur Neuropathique en 4 (DN4) questionnaire. A significant group difference was found in global structural connectivity, with patients showing lower global efficiency (0.564 vs. 0.569, p = 0.001) and higher characteristic path length (1.904 vs. 1.889, p = 0.002) than controls. Significant local connectivity differences were also observed, with lower betweenness centrality in the right (29.965 vs. 55.609, p < 0.001) and left (25.298 vs. 46.267, p < 0.001) caudate nuclei in patients. In DN4-stratified analyses, the high DN4 group showed higher betweenness centrality in the right anterior circular sulcus of the insula (28.939 vs. 3.774, p < 0.001), and DN4 scores negatively correlated with clustering coefficient (r = − 0.316, p = 0.041) and transitivity (r = − 0.350, p = 0.023). PHN was associated with altered structural brain network topology, including lower global efficiency and reduced caudate betweenness centrality. Greater neuropathic pain severity was linked to lower segregation-related metrics. These findings highlight distinct alterations in global and local structural connectivity in PHN and may inform future biomarker-oriented studies. This study identified reduced global efficiency and reduced caudate betweenness centrality using DTI-based connectomic analysis.