Default mode network-basal ganglia network connectivity predicts the transition to postherpetic neuralgia
Ying Wu, Chao Wang, Wei Qian, Lieju Wang, Lina Yu, Minming Zhang, Min Yan
preprint DOI: 10.21203/rs.3.rs-4842138/v1 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Cross-sectional study |
|---|---|
| Sample size | 92 |
| Population | Patients with herpes zoster (acute, recuperating, or with postherpetic neuralgia) |
| Topics | Default mode network |
| Key findings | Default mode network-basal ganglia network connectivity in the acute period can predict the outcome of herpes zoster patients with 77.8% sensitivity and 63.2% specificity. |
Abstract
Abstract Background Neuroimaging study has revealed aberrant network functional connectivities in postherpetic neuralgia (PHN) patients. However, there is a lack of knowledge regarding the relationship between brain network connectivity in acute period and disease prognosis. The purpose was to detect a characteristic network connectivity in the process of herpes zoster (HZ) pain chronification and identify whether the abnormal network connectivity in acute period can predict outcome of HZ patient.
Methods: In this cross-sectional study, 31 PHN patients, 33 recuperation from herpes zoster (RHZ) patients, and 28 acute herpes zoster (AHZ) patients were recruited and underwent resting-state functional magnetic resonance imaging (fMRI). We investigated the differences in four resting-state network (RSN) connectivities among the aboved three groups. Receiver operating characteristic curve (ROC) analysis was performed to identify whether the abnormal network connectivity in acute period can predict the outcome of HZ patient.
Results: Firstly, we found within-basal ganglia network (BGN) and default mode network (DMN)-BGN connectivity differences, with PHN patients showing increased DMN-BGN connectivity compared with AHZ and RHZ patients, and RHZ patients showing increased within-BGN connectivity compared with AHZ and PHN patients. Moreover, DMN-BGN connectivity was associated with the ID pain score in AHZ patients. Finally, the DMN-BGN connectivity of AHZ patients can predict the outcome of HZ patients with sensitivity and specificity of 77.8% and 63.2%, respectively.
Conclusions: Our results provide evidence that DMN-BGN connectivity in acute period confers risk for the development of chronic pain and can act as a neuroimaging biomarker to predict the outcome of HZ patients.