The Effect of Long-Term Menstrual Pain on Large-Scale Brain Network in Primary Dysmenorrhea Patients

Abstract

Purpose: Primary dysmenorrhea (PD) is a common gynecological disease, characterized by crampy and suprapubic pain occurring with menses. Growing evidences demonstrated that PD patients were associated with abnormalities in brain function and structure. However, little is known regarding whether the large-scale brain network changes in PD patients. The purpose of this study was to investigate the effect of long-term menstrual pain on large-scale brain network in PD patients using independent component analysis (ICA) method.

Methods: Twenty-eight PD patients (female, mean age, 24.25±1.00 years) and twenty-eight healthy controls (HCs) (mean age, 24.46±1.31 years), closely matched for age, sex, and education, underwent resting-state magnetic resonance imaging scans. ICA was applied to extract the resting-state networks (RSNs) in two groups. Then, two-sample t-tests were conducted to investigate different intranetwork FCs within RSNs and interactions among RSNs between two groups.

Results: Compared to the HC group, PD patients showed significant increased intra-network FCs within the auditory network (AN), sensorimotor network (SMN), right executive control network (RECN). However, PD patients showed significant decreased intra-network FCs within ventral default mode network (vDMN) and salience network (SN). Moreover, FNC analysis showed increased VN-AN and decreased VN-SMN functional connectivity between two groups.

Conclusion: Our study highlighted that PD patients had abnormal brain networks related to auditory, sensorimotor and higher cognitive network. Our results offer important insights into the altered large-scale brain network neural mechanisms of pain in PD patients.

Keywords: independent component analysis; primary dysmenorrhea; resting-state networks.

Figure 1

The typical spatial patterns in each RSN of both PD and HC groups, including, VN1, CER, AN, VN2, VN3, VN4, LECN, SMN, RECN, dDMN, DAN, vDMN, SN. scale represents T values with a range of 1~6.9 in each RSN (p < 0.001, FDR corrected).

Figure 2

Brain regions with significant differences for eight RSNs in the PD group vs the HC group (two-tailed, voxel-level P < 0.01, GRF correction, cluster-level P < 0.05). Compared with HC group, Cool colors indicated the decreased functional connectivity and hot colors indicated the increased functional connectivity in the PD group. (A–E) correspond to different resting-state networks. AN, SMN, RECN, vDMN and SN.

Figure 3

FNC correlations matrix (averaged over subjects) (A); the VN-AN and VN-SMN connections were found to be significantly altered between two groups (P < 0.01) (B).