脑默认模式网络显示临床慢性疼痛程度变化的研究

Study of the Effect of Variation Intensities of Chronic Pain on the Default Mode Network at Resting-state

目的:本研究旨在探讨脑默认网络(DMN)作为神经影像标志物在慢性疼痛中的应用。疼痛是否和如何影响DMN,以及该DMN连接性变化与疼痛改变的相关性。方法:采用静息态功能性磁共振(f MRI)技术对17例慢性非特异性腰痛患者(cn LBP)在治疗前后,以及17例年龄和性别匹配的健康对照组进行扫描。疼痛程度采用视觉模拟评分进行评估,f MRI的数据采用独立成份分析法来提取DMN,并计算功能连接性变化与疼痛程度变化之间的相关性。结果:cn LBP患者比较健康受试者,可见DMN连接性的降低(顶下小叶,后扣带皮质和楔前叶等)。患者治疗后,疼痛程度减少呈现DMN功能连接性增加。结论:DMN作为一个影像标志物提供了一个客观的方法评价临床自发性慢性疼痛。

Purpose： This study sought to explore the application of default mode network（DMN） connectivity as neuroimaging biomarker for chronic pain, as well as the correlation between the DMN and the variation intensity of spontaneous pain. Methods： Seventeen patients with chronic non-specific low back pain （cnLBP） and 17 age- and gender-matched healthy controls were enrolled. They were all undergone resting-state fMRI exam. Independent components analysis method was used to extract the DMN from the fMRI data. Visual analogue scale was used to assess the clinical pain levels. Correlation analysis was used to study the relationship between the dynamics connectivity and chronic pain intensity. Results： Less connectivity within the DMN was found in patients than that in healthy controls, which was mainly in the inferior parietal lobe, posterior cingulate gyrus and precuneus. The increase of DMN connectivity was correlated with the decrease of clinical pain after treatment. Conclusion： DMN connectivity can be implicated as an objective neuroimaging biomarker for assessing variation in spontaneous chronic pain within individual cnLBP patients.