Altered functional connectivity density and structural covariance networks in women with premenstrual syndrome

Chengxiang Liu; Gaoxiong Duan; Shuming Zhang; Yichen Wei; Lingyan Liang; Bowen Geng; Ruiqing Piao; Ke Xu; Pengyu Li; Xiao Zeng; Demao Deng; Peng Liu

doi:10.21037/qims-22-506

Altered functional connectivity density and structural covariance networks in women with premenstrual syndrome

Quant Imaging Med Surg. 2023 Feb 1;13(2):835-851. doi: 10.21037/qims-22-506. Epub 2023 Jan 2.

Authors

Chengxiang Liu^#^{1

2

3}, Gaoxiong Duan^#⁴, Shuming Zhang^{1

2

3}, Yichen Wei⁴, Lingyan Liang⁴, Bowen Geng^{1

2

3}, Ruiqing Piao^{1

2

3}, Ke Xu^{1

2

3}, Pengyu Li^{1

2

3}, Xiao Zeng^{1

2

3}, Demao Deng⁴, Peng Liu^{1

2

3}

Affiliations

¹ Life Science Research Center, School of Life Science and Technology, Xidian University, Xi'an, China.
² Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China.
³ Xi'an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, China.
⁴ Department of Radiology, the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.

^# Contributed equally.

Abstract

Background: Premenstrual syndrome (PMS) is a menstrual-related disorder, characterized by physical, emotional, behavioral and cognitive symptoms. However, the neuropathological mechanisms of PMS remain unclear. This study aimed to investigate the frequency-specific functional connectivity density (FCD) and structural covariance in PMS.

Methods: Functional and T1-weighted structural data were obtained from 35 PMS patients and 36 healthy controls (HCs). This study was a cross-sectional and prospective design. The local/long-range FCD (LFCD/LRFCD) across slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) bands were computed, and two-way analysis of variance (ANOVA) was performed to ascertain the main effects of group and interaction effects between group and frequency band. Receiver operating characteristic (ROC) curve was performed to investigate reliable biomarkers for identifying PMS from HCs. Based on the ROC results, characterized the changes of whole-brain structural covariance patterns of striatum subregions in two groups. Correlation analysis was applied to examine relationships between the clinical symptoms and abnormal brain regions.

Results: Compared with HCs, PMS patients exhibited: (I) aberrant functional communication in the middle cingulate cortex and precentral gyrus; (II) significant frequency band-by-group interaction effects of the striatum, thalamus and orbitofrontal cortex; (III) the better classification ability of the LFCD in the striatum in ROC analysis (slow-5); (IV) decreased gray matter volumes in the caudate subregions and decreased structural associations of between the caudate subregions and frontal cortex; (V) the LFCD value in thalamus were significantly negatively correlated with the sleep problems (slow-5).

Conclusions: Based on multi-modal magnetic resonance imaging (MRI) analysis, this study might imply the aberrant emotional regulation and cognitive function related to menstrual cycle in PMS and improve our understanding of the pathophysiologic mechanism in PMS from novel perspective.

Keywords: Magnetic resonance imaging (MRI); frequency-specific; functional connectivity density (FCD); premenstrual syndrome (PMS); structural covariance.