原发性痛经患者疼痛发展个体差异影像学研究

Primary dysmenorrhea is of high prevalence in young female, which induces a series of disorders involving psychology, physiology and central pain pathway. Long term menstrual pain in youth may increase the risk of developing secondary or combining other chronic pain diseases in their adult life. Central nervous system may play a critical role in this chronicity involving pain perception and its maintaining or progression. In this longitudinal follow-up study, we investigate brain structural and functional abnormalities associated with pain perception, modulation and emotion by using functional magnetic resonance imaging (MRI) in young patients with primary dysmenorrhea, from whom high risk groups in pain chronicity may be extracted based on imaging features. Furthermore, gene polymorphism related with generation and sensitivity of dysmenorrhea will be analysed by single nucleotide polymorphisms (SNP) genotyping. Using correlation and regression analysis method, we intend to find interactions between neuroimaging features and painful symptom development in different genotypes in primary dysmenorrhea. Finally, based on the data from previous studies and this current longitudinal study, we are trying to establish effective and feasible training and forecast model to describe predictive neuroimaging biomarkers that are associated with pain severity and progression. By combining the nature and nurture informations related with sensitive biomarkers of brain imaging feature and genotype, the current study is not only contributing to improve the pathological mechanism of primary dysmenorrhea, but also valuable for individual disease risk prediction and early management.

原发性痛经持续存在不仅易引发各种心理问题、生理功能紊乱及痛觉中枢微结构改变和功能异常，还会增加继发或合并其他慢性痛疾病的风险，中枢神经系统调控功能异常可能在其中发挥关键作用。本研究以青年原发性痛经患者为研究载体，基于多时间点纵向实验设计，借助多模态功能磁共振分析方法考察大脑疼痛感知、调节、情感通路的结构及功能随疾病进展变化特点，探寻疼痛不良进展高危人群影像学特征；采用单核苷酸多态性技术，分析与痛经产生和严重程度密切相关基因在疾病中的分型特点，通过相关回归分析，进一步考察不同基因亚组人群疼痛发展曲线特性及其与影像学表型的关联特性；结合前期研究基础及纵向试验数据构建训练预测模型，试图建立原发性痛经患者疼痛强度及症状发展相关的个体化中枢影像学预测标记。基于上述研究，本项目不仅为探索原发性痛经慢性化发展高风险人群的早期影像学预测提供客观依据，对临床开展疾病的早期评估、诊疗也具有重要意义。

慢性原发性痛经易诱发情绪障碍、降低生活质量，甚至进展为慢性疼痛对健康构成更大威胁，以往研究发现中枢神经系统在疼痛感知、疼痛慢性化中发挥重要作用。本研究旨在探寻与痛经的严重程度相关神经影像学特征，提取客观影像学评估指标；对比无痛时期（排卵期）以及疼痛时期（月经期）中枢影像差异与痛经的关系，寻找中枢疼痛处理网络特征与疼痛的个体化差异，为临床实时早期干预提供依据。.研究结果显示，大脑多个脑区（丘脑、杏仁核、初级感觉皮层等）灰质密度异常和功能连接存在异常，与痛经强度以及血清中疼痛调节因子异常存在关联，特别是在非疼痛时期丘脑与初级感觉皮层之间的白质纤维束微结构异常与疼痛强度存在显著负相关，提示长期痛经影响之下，大脑结构和功能存在异常变化，这些变化还能预测痛经感知强度。.此外本研究引入疼痛共情任务并关联任务态功能磁共振扫描，发现无论在非疼痛期和疼痛期，痛经人群都比健康对照表现出更高的疼痛共情能力，而这种异常的疼痛共情与大脑中前脑岛的激活密切相关，并且慢性疼痛可能会造成个体对他人疼痛感知异常，而且这种异常并不会随着个体状态的改变而变化。因此，痛经女性异常的疼痛共情可能是由于周期性疼痛造成的共情网络失调所致。.为了探究痛经子宫结构的变化，我们使用图像处理将子宫分割成子宫内膜，肌层，结合带，子宫体部四个感兴趣区域，并使用机器学习算法筛选子宫纹理特征，构建痛经子宫分类预测模型，发现排卵期子宫结构纹理特征可很好的区分痛经组与对照组，原发性痛经子宫在非痛时期就存在形态结构异常。将大脑白质弥散特性、灰质和功能连接特性与子宫纹理特征联合起来生成特征向量并进行预测建模，发现联合预测性能优于大脑或子宫单独预测性能。.本研究结果提示长期痛经存在大脑结构及功能调节异常，部分脑区与情绪调节异常、血液相关疼痛调节因子存在密切关联；联合大脑结构、功能以及子宫纹理特征可以更好预测痛经严重程度。