Intra-individual structural covariance network in patients with chronic neck and shoulder pain: a longitudinal brain...

Neuroimaging studies have suggested that the neural mechanisms underlying chronic neck and shoulder pain (CNSP) are associated with morphological alterations in various cortical regions. However, there is a scarcity of research exploring the structural network characteristics of the brain in patients with CNSP. While most existing studies focus on group-level brain structural networks, there is a lack of insight into individual variability. Additionally, longitudinal studies investigating changes in the brain's structural networks following treatment in CNSP patients remain limited.

To address these gaps, this study enrolled 25 patients with CNSP, obtaining structural brain MRI data and clinical measures before treatment and 3 months after a minimally invasive intervention. Individual-level structural covariance networks were constructed for each participant to explore structural network differences between CNSP patients and healthy controls (HCs). Longitudinal changes in these networks were also assessed post-intervention.

Compared to HCs, CNSP patients exhibited significantly reduced Degree Centrality (P = 0.03, FDR corrected) and Nodal Efficiency (P = 0.0082, FDR corrected) in the right inferior frontal gyrus (pars triangularis), with significant structural recovery observed 3 months after the intervention. In terms of global network topology, the CNSP group showed decreased small-world properties, specifically in Gamma (P = 0.0093) and Sigma (P = 0.0301) indices; however, unlike local metrics, no significant recovery was observed in these global metrics 3 months post-intervention. Furthermore, correlation analysis demonstrated a significant negative association between the baseline Degree Centrality of the right inferior frontal gyrus and the percentage change in VAS scores (r = -0.47, P = 0.0168, FDR corrected), suggesting a potential prognostic value.

These findings provide valuable longitudinal data that help elucidate the central mechanisms of pain in CNSP patients. They also identify potential biomarkers that could predict the response to minimally invasive interventions, offering insights into individualized treatment strategies for chronic cervical and shoulder pain.