Related Experiment Video
Updated: Dec 6, 2025
09:55
Monitoring Acupuncture Effects on Human Brain by fMRI
Published on: April 8, 2010
15.8K
Resting-State Functional Connectivity Patterns Predict Acupuncture Treatment Response in Primary Dysmenorrhea
Siyi Yu1, Mingguo Xie2, Shuqin Liu2
1Brain Research Center, Department of Acupuncture & Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Frontiers in Neuroscience
|October 5, 2020
Summary
Real acupuncture effectively reduces primary dysmenorrhea (PDM) pain by altering brain connectivity. Specific functional connectivity (FC) patterns identified before treatment can predict individual patient responses to acupuncture.
Area of Science:
- Neuroscience
- Integrative Medicine
- Pain Management
Background:
- Primary dysmenorrhea (PDM) is a prevalent gynecological condition causing significant pain and discomfort.
- While acupuncture shows efficacy for PDM, substantial variations in patient response necessitate personalized treatment approaches.
- Understanding the neural underpinnings of acupuncture's effects is crucial for optimizing therapeutic strategies.
Purpose of the Study:
- To investigate the distinct neural mechanisms influenced by real versus sham acupuncture in PDM patients.
- To determine if baseline functional connectivity (FC) patterns can predict individual treatment responses to acupuncture.
- To explore the potential of neuroimaging biomarkers for personalized acupuncture therapy in PDM.
Main Methods:
- Fifty-four PDM patients were randomized into real or sham acupuncture groups over three menstrual cycles.
- Pain-related functional connectivity (FC) matrices were analyzed at baseline and post-treatment.
- Multivariate analysis of variance (MANOVA) and machine learning-based multivariate pattern analysis (MVPA) were employed.
Main Results:
- Real acupuncture significantly alleviated pain severity, whereas sham acupuncture did not.
- Distinct alterations in FC were observed between real and sham acupuncture groups, particularly involving the descending pain modulatory system (DPMS), sensorimotor network (SMN), salience network (SN), and default mode network (DMN).
- Baseline FC patterns successfully predicted individual patient responses to acupuncture treatment via MVPA.
Conclusions:
- Real and sham acupuncture exert differential effects on brain functional connectivity in PDM patients.
- Neuroimaging biomarkers, specifically baseline FC patterns, can predict treatment outcomes, supporting personalized acupuncture.
- This study validates the use of neuroimaging for developing individualized, precise acupuncture treatments for primary dysmenorrhea.
