Abnormal Intrinsic Brain Activity and Neuroimaging-Based fMRI Classification in Patients With Herpes Zoster and Postherpetic Neuralgia - Huang, Jiabin; Li, Yongxin; Xie, Huijun; Yang, Shaomin; Jiang, Changyu; Sun, Wuping; Li, Disen; Liao, Yuliang; Ba, Xiyuan; Xiao, Lizu (Frontiers in Neurology, 2020)
Neuroimaging studies in neuropathic pain have shown abnormalities in brain structure and function. However, the brain pattern changes from herpes zoster (HZ) to postherpetic neuralgia (PHN) remain unclear. The present study aimed to explore the effects of HZ and PHN on the brain activity and detect the neural mechanisms underlying the cognitive impairment in neuropathic pain patients. Resting-state fMRI was acquired from 28 right-handed HZ patients, 24 right-handed PHN patients and 20 healthy controls, using a 3T MRI system. The amplitude of low-frequency fluctuation (ALFF) change was analyzed to detect the functional abnormality between groups. Correlations between ALFF and clinical pain scales were assessed in the two patient groups. Differences in brain activity between groups were examined and used in a support vector machine learning model for classification. results suggested that the spontaneous activity of these regions reflect the severity of PHN pain. In particular vector machine learning showed decreases in brain activity in these regions could provide the ability to classify between neuropathic pain patients (HZ and PHN) and healthy subjects. The ability to discriminate between HZ and PHN also reaches an acceptable level. Classification results indicated that mean ALFF values in these pain-related regions can be used for cross-group classification. These results are valuable in explaining the interaction between neuropathic pain and brain functional abnormalities, and it's the underlying neural mechanisms. The present study provides new insights into fMRI as a pain biomarker, assisting the diagnosis and classification of patients with neuropathic pain. Future work should combine functional information with structural imaging data to examine whether this leads to higher levels of diagnostic accuracy.