rTMS通过前额叶-基底神经节环路调控射精行为的信息处理机制研究

原发性早泄（LPE）核心是射精控制力差，其中前额叶-基底神经节环路功能紊乱起重要作用。我们前期也发现：患者前额叶区域抑制控制减弱，应用重复经颅磁刺激（rTMS）干预患者前额叶疗效肯定，但机制不明。另外它的有效率仅55%，如果能在治疗前预测哪些患者适合该治疗将提高LPE治愈率。因此，我们提出的假说是rTMS通过改善前额叶功能来调控射精，且rTMS有效与无效组的基线脑中枢表征可预测疗效。我们拟运用磁共振波谱分析rTMS干预后神经递质水平变化；通过MRI技术采集rTMS干预前后患者影像数据，应用区域一致性、功能连接度等图像处理手段，评估rTMS对射精影响的中枢表征差异；基于影像组学理论，选定相关中枢表征通过机器学习方法建立最佳rTMS治疗适应人群预测模型，并交叉验证。从脑代谢、脑结构等方面探索rTMS刺激前额叶调控射精的神经机制，挖掘最佳rTMS治疗人群预测模型，为LPE的科学治疗提供理论依据。

Premature Ejaculation is one of the most common types of male sexual dysfunction. Among the different types, lifelong premature ejaculation (LPE) is more severe and has a poor response to therapy. The core symptom of lifelong premature ejaculation is poor ejaculation control. Neuroimaging studies have found that the prefrontal-basal ganglia loop plays an important role in the regulation of ejaculation. Our previous work also found that the inhibition and control of dorsolateral prefrontal lobe and basal ganglia were weakened. Repeated Transcranial Magnetic Stimulation (rTMS) could prolong intra-vaginal ejaculation latency time of patients with right dorsolateral prefrontal lobe, but the neural mechanism is unclear. Moreover, it is an urgent scientific problem to predict which patients are suitable for rTMS before treatment. Therefore, the hypothesis of the current study is that rTMS can improve the local brain metabolism of dorsolateral prefrontal lobe, and the effective and ineffective groups of rTMS have different central characterization. We intend to use Magnetic Resonance Spectroscopy to detect changes of neurotransmitter level before and after rTMS intervention, and observe the effects of changed prefrontal brain metabolism on ejaculation regulation. Based on the resting and task-fMRI,We then would like to evaluate the impact of rTMS on ejaculation function combining medical image processing methods with behavioral analysis methods. We hope that these studies may improve our understanding of the neural mechanism of rTMS-stimulated prefrontal-basal ganglia to regulate ejaculation through aspects of local brain metabolism and function networks. Based on the difference of central representation of radiomics, the prediction model of rTMS treatment adaptation population is established by Machine Learning Methods such as Support Vector Machine and Cross Validation. The neural mechanism of rTMS stimulating prefrontal lobe to regulate ejaculation will be explored from the aspects of brain metabolism, brain structure and function. At the same time, the prediction model of rTMS treatment may be excavated to help clinical decision-making, and finally to provide theoretical basis for the scientific treatment of lifelong premature ejaculation.