基于大型脑网络多模态MRI的海洛因成瘾者复吸机制探讨

复吸是海洛因成瘾治疗的难点和关键点。尽管一些治疗方法在降低海洛因渴求和缓减戒断症状方面发挥积极作用，但仍无法解决高复吸率问题。前期研究表明海洛因成瘾主要涉及默认功能网络、突显性网络和执行控制网络相关的脑区，但这三个大型脑网络的内在特征，尤其是相互关系在复吸机制中的作用仍不清楚。我们的初步研究发现，海洛因成瘾者的突显性网络与默认功能网络之间的功能连接强度和复吸次数成正相关，而左侧执行控制网络与默认功能网络之间的功能连接强度和复吸次数成负相关，提示阐明海洛因成瘾者大型脑网络的内在特征，尤其是网络间相互作用关系可能是阐明复吸机制的关键点。本项目拟采用结合功能和结构多模态MRI的方法，从前瞻性角度探讨海洛因成瘾者默认功能网络、突显性网络和执行控制网络的内在功能、结构特征，尤其是网络间相互关系在复吸机制中的作用，并明确复吸相关的影像学诊断指标，为预测复吸风险、发展新的治疗方案、预防复吸行为提供依据。

Relapse is the difficult and critical point for treatment of heroin addiction..Although some measures play an active role in reducing heroin craving and alleviating withdrawal symptoms, the problem of high relapse rates still remains to be solved. Previous studies demonstrated that the brain regions included in Default Mode Network (DMN), Salience Network (SN) and Executive Control Network (ECN) are mainly involved in heroin addiction. However, the inherent characteristics of the DMN, SN and ECN large-scale networks, especially the interactions among them underlying the mechanism of relapse remains unclear. Recently, we found that the heroin-dependent individuals demonstrated positive relationship between the relapse behavior and coupling of SN and DMN, but negative relationship between the relapse behavior and coupling of left ECN and DMN. The results suggested that to clarify the inherent characteristics of large-scale brain networks, especially the interactions among them is the key to clarifying the mechanism of relapse. The aim of this prospective project is to explore the inherent functional and structural characteristics of the DMN, SN and ECN large-scale networks, especially the interactions among them underlying the mechanism of relapse in use of multimodal functional magnetic resonance imaging. Meanwhile, this project is aimed to identify the biomarkers related to relapse and it will contribute to providing experimental support for predicting the risk of relapse, developing new treatment for heroin addiction, and preventing relapse behavior of heroin addicts.