Resting-State Functional Connectivity Patterns Predict Acupuncture Treatment Response in Primary Dysmenorrhea.
Resting-State Functional Connectivity Patterns Predict Acupuncture Treatment Response in Primary Dysmenorrhea.
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静息状态功能连接模式预测针刺治疗对原发性痛经的疗效。
DOI：
10.3389/fnins.2020.559191
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发表时间：
2020
影响因子：
4.3
通讯作者：
Yang J
中科院分区：
文献类型：
--
作者：
Yu S;Xie M;Liu S;Guo X;Tian J;Wei W;Zhang Q;Zeng F;Liang F;Yang J
Primary dysmenorrhea (PDM) is a common complaint in women throughout the menstrual years. Acupuncture has been shown to be effective in dysmenorrhea; however, there are large interindividual differences in patients’ responses to acupuncture treatment. Fifty-four patients with PDM were recruited and randomized into real or sham acupuncture treatment groups (over the course of three menstrual cycles). Pain-related functional connectivity (FC) matrices were constructed at baseline and post-treatment period. The different neural mechanisms altered by real and sham acupuncture were detected with multivariate analysis of variance. Multivariate pattern analysis (MVPA) based on a machine learning approach was used to explore whether the different FC patterns predicted the acupuncture treatment response in the PDM patients. The results showed that real but not sham acupuncture significantly relieved pain severity in PDM patients. Real and sham acupuncture displayed differences in FC alterations between the descending pain modulatory system (DPMS) and sensorimotor network (SMN), the salience network (SN) and SMN, and the SN and default mode network (DMN). Furthermore, MVPA found that these FC patterns at baseline could predict the acupuncture treatment response in PDM patients. The present study verified differentially altered brain mechanisms underlying real and sham acupuncture in PDM patients and supported the use of neuroimaging biomarkers for individual-based precise acupuncture treatment in patients with PDM.
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影响因子：
2.3
作者：
Keshavan MS;Collin G;Guimond S;Kelly S;Prasad KM;Lizano P
通讯作者：
Lizano P
基于全脑结构 MRI 的无痛期原发性痛经分类：一项机器学习研究。
影响因子：
7.4
作者：
Chen, Tao;Mu, Junya;Liu, Jixin
通讯作者：
Liu, Jixin
颈椎病颈痛的区域同质性、多变量模式分析及治疗调节效果
影响因子：
4.3
作者：
Chen, Jun;Wang, Zengjian;Kong, Jian
通讯作者：
Kong, Jian
影响因子：
3.3
作者：
Chen X;Spaeth RB;Freeman SG;Scarborough DM;Hashmi JA;Wey HY;Egorova N;Vangel M;Mao J;Wasan AD;Edwards RR;Gollub RL;Kong J
通讯作者：
Kong J
DOI：
10.1073/pnas.1312902110
发表时间：
2013-11-12
影响因子：
11.1
作者：
Kucyi, Aaron;Salomons, Tim V.;Davis, Karen D.
通讯作者：
Davis, Karen D.