Brain white matter pathways of resilience to chronic back pain: a multisite validation.
Mina MišićNoah LeeFrancesca ZiddaKyungjin SohnKatrin UsaiMartin LöfflerMd Nasir UddinArsalan FarooqiGiovanni SchifittoZhengwu ZhangFrauke NeesPaul GehaHerta FlorPublished in: bioRxiv : the preprint server for biology (2024)
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.
Keyphrases
- white matter
- chronic pain
- multiple sclerosis
- global health
- pain management
- resting state
- electronic health record
- neuropathic pain
- big data
- end stage renal disease
- working memory
- functional connectivity
- ejection fraction
- newly diagnosed
- climate change
- public health
- mental health
- case control
- peritoneal dialysis
- artificial intelligence
- data analysis
- prognostic factors
- human health
- spinal cord
- spinal cord injury
- machine learning
- brain injury
- depressive symptoms
- risk assessment
- cerebral ischemia