Background: Post-stroke pain (PSP) presents with diverse pain qualities. However, the structural brain correlates underlying these distinct pain qualities remains poorly understood.
Methods: We analysed PSP patients using clinical assessments, clustering based on pain qualities assessed using the Neuropathic Pain Symptom Inventory, longitudinal pain intensity evaluation and brain lesion/disconnection mapping (computed tomography/magnetic resonance imaging and Bayesian lesion-deficit inference). Pain quality-based clusters and their corresponding lesion sites and white matter tracts were identified.
Results: We analysed 114 PSP patients. Cluster analysis using pain qualities classified patients into four distinct subgroups: CL1 (cold-evoked/tingling), CL2 (deep squeezing/pressure), CL3 (tingling) and CL4 (pressure-evoked). CL1 and CL3 patients predominantly exhibited features of central post-stroke pain, characterised by sensory disturbances such as allodynia and numbness. Lesion mapping revealed involvement of the thalamus, putamen and posterior insula. Disconnection analysis identified the superior thalamic radiation (Bayes factor > 70) as a common white matter tract. In contrast, CL2 and CL4 were characterised by musculoskeletal-type pain associated with joint pain, restricted range of motion and higher motor impairment. Lesions in these groups were mainly localised to the frontal lobe, with disconnection of the corticospinal and fronto-aslant tracts (Bayes factor > 50). Longitudinal analysis demonstrated pain intensity decreased over time across all clusters, with a trend towards slower improvement in Cluster 3.
Conclusions: Pain quality reflects distinct pathological mechanisms of PSP and may be associated with specific patterns of brain lesions and white matter disconnections and rehabilitation prognosis. Identifying pain-quality subtypes may help inform outcomes and guide personalised rehabilitation.
Significance statement: By linking distinct pain qualities with lesion and disconnection profiles, this study clarifies the neural mechanisms underlying post-stroke pain. Identifying these pain-quality subtypes provides insights into prognosis and supports the development of personalized rehabilitation strategies tailored to specific pain mechanisms.
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