Zou Rushi, Li Linling, Zhang Li, Huang Gan, Liang Zhen, Zhang Zhiguo
School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China.
Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen University, Shenzhen, China.
Front Neurosci. 2021 Feb 10;15:615944. doi: 10.3389/fnins.2021.615944. eCollection 2021.
Pain sensitivity is highly variable among individuals, and it is clinically important to predict an individual's pain sensitivity for individualized diagnosis and management of pain. Literature has shown that pain sensitivity is associated with regional structural features of the brain, but it remains unclear whether pain sensitivity is also related to structural brain connectivity. In the present study, we investigated the relationship between pain thresholds and morphological connectivity (MC) inferred from structural MRI based on data of 221 healthy participants. We found that MC was highly predictive of an individual's pain thresholds and, importantly, it had a better prediction performance than regional structural features. We also identified a number of most predictive MC features and confirmed the crucial role of the prefrontal cortex in the determination of pain sensitivity. These results suggest the potential of using structural MRI-based MC to predict an individual's pain sensitivity in clinical settings, and hence this study has important implications for diagnosis and treatment of pain.
个体间的疼痛敏感性差异很大,预测个体的疼痛敏感性对于疼痛的个体化诊断和管理具有重要的临床意义。文献表明,疼痛敏感性与大脑的区域结构特征有关,但疼痛敏感性是否也与大脑结构连接性相关尚不清楚。在本研究中,我们基于221名健康参与者的数据,研究了疼痛阈值与从结构磁共振成像(MRI)推断出的形态连接性(MC)之间的关系。我们发现,MC能够高度预测个体的疼痛阈值,重要的是,它比区域结构特征具有更好的预测性能。我们还确定了一些最具预测性的MC特征,并证实了前额叶皮质在确定疼痛敏感性中的关键作用。这些结果表明,基于结构MRI的MC在临床环境中预测个体疼痛敏感性的潜力,因此本研究对疼痛的诊断和治疗具有重要意义。