慢性背痛的脑功能连接梯度分析研究  

Brain Functional Connectome Gradients Analysis Study of Chronic Back Pain

作　　者：杨俊超 尹小龙 黄力 江锋[3] 李钻芳[1,4] 梁胜祥 无 YANG Junchao;YIN Xiaolong;HUANG Li;JIANG Feng;LI Zuanfang;LIANG Shengxiang;无(National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology,Fujian University of Traditional Chinese Medicine,Fuzhou,Fujian 350122,China;College of Rehabilitation Medicine,Fujian University of Traditional Chinese Medicine,Fuzhou,Fujian 350122,China;The Second Affiliated Hospital of Fujian University of Traditional Chinese Medicine,Fuzhou,Fujian 350003,China;Innovation and Transformation Center,Fujian University of Traditional Chinese Medicine,Fuzhou,Fujian 350122,China;Key Laboratory of Cognitive Rehabilitation of Fujian Province,Fuzhou,Fujian 350122;Rehabilitation Industry Institute,Fujian University of Traditional Chinese Medicine,Fuzhou,Fujian 350122,China)

机构地区：[1]福建中医药大学康复医疗技术国家地方联合工程研究中心,福建福州350122 [2]福建中医药大学康复医学院,福建福州350122 [3]福建中医药大学附属第二人民医院,福建福州350003 [4]福建中医药大学科技创新与转化中心,福建福州350122 [5]福建省认知功能康复重点实验室,福建福州350122 [6]福建中医药大学康复产业研究院,福建福州350122

出　　处：《康复学报》2024年第5期457-464,共8页Rehabilitation Medicine

基　　金：国家自然科学基金项目(82004440);福建中医药大学高层次人才科研启动资金项目(2019002-人才)。

摘　　要：目的通过分析慢性背痛(CBP)组和健康对照(HC)组功能网络连接梯度的差异,探讨CBP组功能网络层级结构变化与疼痛的关系。方法从OpenPain数据库中获取CBP组和HC组的数据,包括VAS量表、疼痛年限等临床基本信息,以及静息态功能磁共振图像(rs-fMRI)。将其按年龄、性别进行1∶1匹配,每组32例。rs-fMRI数据经过预处理以获得Fisher-Z转换后的功能连接矩阵,采用BrainSpace分析2组被试7个功能网络(感觉运动网络、视觉网络、背侧注意网络、腹侧注意网络、边缘网络、额顶控制网络和默认网络)的梯度分数,统计分析比较2组被试功能网络梯度分数的差异,并将差异功能网络的梯度分数与VAS临床量表做相关性分析。结果CBP组功能网络层级的两端(即感觉运动网络和默认网络)相对于HC组范围明显收缩,皮质范围的梯度受到抑制。与HC组相比,CBP组的感觉运动网络、视觉网络、背侧注意网络、腹侧注意网络梯度分数升高;额顶控制网络、边缘网络和默认网络梯度分数降低;其中感觉运动网络(P<0.01)、腹侧注意网络(P<0.001)梯度分数升高以及边缘网络(P<0.05)、默认网络(P<0.001)梯度分数降低;相关性分析结果显示:CBP组感觉运动网络梯度分数与VAS评分呈正相关(r=0.432,P<0.05),即更高的感觉运动网络梯度分数表现为更加严重的疼痛反应;默认网络梯度分数与VAS评分呈负相关(r=-0.404,P<0.05),即更低的默认网络梯度分数表现出更为严重的疼痛症状。结论CBP组宏观网络层级结构发生了明显改变,并且该改变与CBP组疼痛症状密切相关,该结果不仅丰富了梯度分析的研究领域,也为进一步研究CBP组疼痛的神经机制提供了新视角。Objective The aim of this study was to investigate the relationship between changes in functional network hierarchy and pain in patients with chronic back pain(CBP)by analyzing the differences in functional network connectivity gradients between the CBP group and the healthy control group.Methods Data(including basic clinical information such as VAS scores,years of pain,and resting functional MRI images)from the patients with CBP and healthy controls(HC)were obtained from the OpenPain database.Participants were grouped into 32 pairs matched by age and sex.The rs-fMRI images were pre-processed to obtain Fisher-Z transformed functional connectivity matrices,and BrainSpace was used to analyse the gradient scores of seven functional networks(sensorimotor network,visual network,dorsal attention network,ventral attention network,limbic network,frontoparietal control network and default mode network)in the two groups.The differences in the gradient scores of the functional networks between the two groups were analyzed statistically.Besides,the correlation analysis was applied to explore the relationship between the different functional network gradient scores and the VAS scores.Results Both ends of the functional network hierarchy(i.e.,sensorimotor and default mode networks)were significantly constricted in the CBP group compared to the HC group,and gradients in the cortical range were suppressed.Compared to the HC group,the CBP group had higher gradient scores of sensorimotor,visual,dorsal attention,and ventral attention network,and lower gradient scores of frontoparietal control,limbic,and default mode network.There were significant differences in the increased gradient scores of sensorimotor network(P<0.01)and ventral attention network(P<0.001),and in the decreased gradient scores of limbic network(P<0.05)and default mode network(P<0.001).In addition,correlation analysis showed that the gradient scores of sensorimotor network in the CBP group was positively correlated with VAS scores(r=0.432,P<0.05),which suggested t

关 键 词：慢性背痛 梯度 默认网络 感觉运动网络 层级结构 

分 类 号：R681.55[医药卫生—骨科学] R49[医药卫生—外科学]