Neural Alterations in Chronic Pain: MRI Analysis

Background: Chronic pain affects hundreds of millions worldwide and remains a major clinical challenge, despite numerous available treatments. Advances in brain imaging offer a promising path toward identifying neural signatures of chronic pain, potentially enhancing diagnosis and guiding treatment. However, while a core set of brain regions, including the insula, cingulate, and somatosensory cortices, has been repeatedly implicated, findings regarding other regions and connectivity patterns involved remain inconsistent, with limited robust replication. Objective: To address these gaps, the present work characterizes resting-state functional connectivity and gray matter volume differences between chronic pain patients and pain-free controls. Methods: In this secondary analysis of publicly available data, anatomical and resting-state functional MRI were analyzed from 56 patients with chronic knee pain due to osteoarthritis and 20 pain-free controls. Group comparisons used Network-Based Statistic (NBS) and Bayesian multivariate regression models, controlling for demographic covariates. Results: In the pain group, about 75% of parcellated brain regions exhibited increased functional connectivity compared to controls. The 30 highest degree centrality regions in the NBS network were concentrated in regions consistent with prior pain neuroimaging findings. Additionally, chronic pain patients exhibited reduced gray matter volume (-3.98%; SD 1.2%) across 33% of parcellated brain regions, including key regions implicated in pain processing. Conclusions: These findings demonstrate widespread functional and anatomical neural alterations in chronic pain, revealing a global pattern of reorganization extending beyond previously reported network-pair effects. Characterizing such alterations may contribute to ongoing efforts to identify neuroimaging markers of chronic pain, with potential translational relevance.