Beyond the chronic pain stage: default mode network perturbation depends on years lived with back pain.

ABSTRACT: Research has indicated that the default mode network (DMN) is perturbated in patients with chronic pain when compared with healthy controls, and this perturbation is correlated with the duration of pain during the chronic pain stage. It remains unclear whether DMN adaptations manifest during the subacute pain stage and progress over time because of the duration of pain experience, rather than being a specific correlate of the chronic pain stage. Furthermore, information regarding whether these adaptations are related to cognitive processes of adaptation is lacking. To this end, we examined the DMN in 31 patients with chronic back pain (CBP), 77 patients with subacute back pain (SBP), as well as 39 healthy pain-free controls (HC) applying a graph-theoretic network approach on functional resting-state magnetic resonance imaging. Beyond the comparison between groups, we used a linear analysis considering the years lived with pain (YLP) across all patients with back pain and additionally performed a mediation analysis of the role of cognitive pain coping. In line with previous studies, we found significant DMN perturbation in CBP compared with HC. However, this did not apply to the comparison of CBP with SBP. Instead, we observed a positive correlation between DMN perturbation and YLP. This was significantly mediated by coping attitudes towards pain. Default mode network perturbation may thus reflect neural adaptation processes to pain experience rather than a single correlate of the chronic pain stage and be modulated by cognitive adaption. This points to potentially underinvestigated significant adaptation processes that could enable more fine-grained patient stratification.

Brain white matter pathways of resilience to chronic back pain: a multisite validation.

Chronic back pain (CBP) is a global health concern with significant societal and economic burden. While various predictors of back pain chronicity have been proposed, including demographic and psychosocial factors, neuroimaging studies have shown that brain characteristics can serve as robust predictors of CBP. However, large-scale, multisite validation of these predictors is currently lacking. In two independent longitudinal studies, we examined white matter diffusion imaging data and pain characteristics in patients with subacute back pain (SBP) over six- and 12-month periods. Diffusion data from individuals with CBP and healthy controls (HC) were analyzed for comparison. Whole-brain tract-based spatial statistics analyses revealed that a cluster in the right superior longitudinal fasciculus (SLF) tract had larger fractional anisotropy (FA) values in patients who recovered (SBPr) compared to those with persistent pain (SBPp), and predicted changes in pain severity. The SLF FA values accurately classified patients at baseline and follow-up in a third publicly available dataset (Area under the Receiver Operating Curve ~ 0.70). Notably, patients who recovered had FA values larger than those of HC suggesting a potential role of SLF integrity in resilience to CBP. Structural connectivity-based models also classified SBPp and SBPr patients from the three data sets (validation accuracy 67%). Our results validate the right SLF as a robust predictor of CBP development, with potential for clinical translation. Cognitive and behavioral processes dependent on the right SLF, such as proprioception and visuospatial attention, should be analyzed in subacute stages as they could prove important for back pain chronicity.