Local Structural Indices Changes During Different Periods of Postherpetic Neuralgia: A Graphical Study in Structural Covariance Networks

Abstract

Purpose: In this study, we aim to explore the changes in network graph theory indices of structural covariance networks (SCNs) in PHN patients with different disease durations.

Patients and methods: High-resolution T1 magnetic resonance images were collected from 109 subjects. We constructed SCNs based on cortical thickness data and analyzed the changes in global and regional network measures of PHN patients and herpes zoster (HZ) patients, and get hubs of each group.

Results: (1) PHN patients with a disease duration >6 months had reduced global efficiency (P=0.035) and increased characteristic shortest path length (P=0.028). (2) Nodal efficiency of the right pars opercularis was greater in both HZ and PHN patients with a disease duration of 1 to 3 months (P<0.001); in PHN patients with a disease duration > 6 months, the nodal degree of the left pars triangularis and nodal efficiency of the right middle temporal gyrus were greater (P<0.001). (3) The right supramarginal gyrus was the common hub of healthy controls (HCs) and HZ patients, the right pars opercularis was the common hub of HZ patients and PHN patients with a disease duration of 1 to 3 months, and the bilateral superior frontal gyrus was the common hub of HZ patients and PHN patients with a disease duration >6 months.

Conclusion: There have changes in SCN indices in PHN patients with different disease durations. PHN patients with a disease duration >6 months had increased SCN integration and diminished information transfer capability between nodes, which complemented the topological properties of previous PHN networks. Eglobal and Lp can be considered as potential imaging markers for future clinical restaging of PHN.

Keywords: cortical thickness; graph theory; herpes zoster; postherpetic neuralgia; small world; structural covariance network.

Figure 1

Correlation matrix of the cortex thicknesses in each group. The upper row shows the cortical thickness correlation matrices of the HC, HZ, and PHN groups after excluding self-connections. The color bar indicates the strength of the correlation coefficients. The lower row is the binary matrix for each group.

Figure 2

Changes in the global network properties with increasing network density. The changes in (A) clustering coefficient, (B) characteristic shortest path length, (C) global efficiency, (D) local efficiency, (E) normalized characteristic shortest path length (γ), (F) normalized clustering coefficient (γ) and (G) small-worldness (σ) with increasing network density. (Network density: ranging from 0.05 to 0.40).

Figure 3

Differences between PHN patients (>6 m) and HCs in global network parameters as a function of network density (0.05–0.40). (A) Clustering coefficient, (B) characteristic shortest path length, (C) global efficiency, (D) local efficiency, (E) normalized characteristic shortest path length (γ), (F) normalized clustering coefficient (γ) and (G) small-worldness (σ). The 95% confidence interval is represented by upper and lower blue lines, and the black line in the middle is the mean difference after 1000 permutations. The red line represents the true differences between groups, which fall outside the confidence interval and indicate significant differences between groups (p < 0.050) under the current threshold.

Figure 4

Regions showing significant between-group differences in nodal centralities (P<0.050, corrected). (A) Nodes that differ between the HZ group and the HC group. (B) Nodes that differ between the 1–3 month PHN group and the HC group. (C) Nodes that differ between the PHN group with duration greater than 6 months and the HC group.

Figure 5

Network hubs of five groups. (A) HC group. (B) HZ group. (C) PHN group of 1 to 3 months. (D) PHN group of 3 to 6 months. (E) PHN group of greater than 6 months.