Complex regional pain syndrome: The matter of white matter?. Issue 5 (5th April 2017)

• Record Type: Journal Article
• Authors: Hotta, Jaakko; Zhou, Guangyu; Harno, Hanna; Forss, Nina; Hari, Riitta
• Is Part Of: Brain and behavior. Volume 7:Issue 5(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-04-05
• Subjects: central nervous system -- chronic pain -- connectivity -- diffusion tensor imaging -- motor skills; Neurology -- Periodicals; Neurosciences -- Periodicals; Psychology -- Periodicals; Psychiatry -- Periodicals; 616.8005
• DOI: 10.1002/brb3.647
• Languages: English
• ISSNs: 2162-3279

Abstract

Abstract: Introduction: Many central pathophysiological aspects of complex regional pain syndrome (CRPS) are still unknown. Although brain‐imaging studies are increasingly supporting the contribution of the central nervous system to the generation and maintenance of the CRPS pain, the brain's white‐matter alterations are seldom investigated. Methods: In this study, we used diffusion tensor imaging to explore white‐matter changes in twelve CRPS‐type‐1 female patients suffering from chronic right upper‐limb pain compared with twelve healthy control subjects. Results: Tract‐based spatial‐statistics analysis revealed significantly higher mean diffusivity, axial diffusivity, and radial diffusivity in the CRPS patients, suggesting that the structural connectivity is altered in CRPS. All these measures were altered in the genu, body, and splenium of corpus callosum, as well as in the left anterior and posterior and the right superior parts of the corona radiata. Axial diffusivity was significantly correlated with clinical motor symptoms at whole‐brain level, supporting the physiological significance of the observed white‐matter abnormalities. Conclusions: Altogether, our findings further corroborate the involvement of the central nervous system in CRPS. Abstract : Complex regional pain syndrome is associated with brain changes. In this study, the effects of this syndrome on brain's white matter are explored using diffusion tensor imaging.