强直少动型帕金森病的肾虚血瘀证候评分与脑结构网络相关性研究

发布时间：2018-01-02 06:42

  本文关键词：强直少动型帕金森病的肾虚血瘀证候评分与脑结构网络相关性研究　出处：《北京中医药大学》2017年硕士论文　论文类型：学位论文

  更多相关文章： 帕金森病 脑结构网络 中医证候 症状量表评分

【摘要】：研究背景:随着近年来对帕金森病理认识的进步,发现帕金森病理改变不始于亦不局限于中脑黑质,因其累及多处部位,症状多样,不易早期诊断。研究者试通过多种方式总结帕金森病症状规律特征,提高帕金森病的早期诊断率,以及早治疗,改善患者预后。强直少动型帕金森病是以动作迟缓、肌强直为特征的帕金森病亚型,因其震颤症状不显,早期诊断更为困难。已有研究证明中药益肾逐瘀法治疗强直少动型帕金森病可有效改善患者多种症状评分,包括运动症状及非运动症状(自主神经功能、精神症状、感觉障碍、睡眠障碍),且脑功能连接也在疗后有所改变,但中医证候与脑结构网络是否存在相关性仍有待进一步研究。"证候"是中医实现个体化治疗的根本依据。关于"证"的来源与发展问题一直为中医学所关注。现代医学用多种科技手段研究中医证候与现代理化指标之间的关系,以此论证中医"证候"概念并非仅仅只是历史经验总结及疾病根关症状堆砌,更存在共性的内在生物学基础。研究证候评分成为该探索过程中重要的量化指标。支持向量机(SVM)是一种较为先进的监督学习方法,可用于解决一些样本小,维度高的统计学问题。本研究试用支持向量机(Support Vector Machine,SVM)分类(SVC)及回归(SVR)方法比较治疗前PD组与正常人之间脑结构性网络差异,分析各症状量表评分(包括中医证候量表评分)与脑结构网络相关性。研究目的:(1)比较强直少动型PD患者不同于正常人的脑结构网络特征,为帕金森病精确诊断提供辅助手段;(2)比较三种PD量表评分(NMSS、UPDRS、TCM)与脑结构网络的相关性;(3)分析强直少动型帕金森病肾虚血瘀证是否存在脑结构网络特征性改变为该证候的内在生物学基础。研究方法:本研究依照试验标准由北京中医药大学东直门医院纳入9例强直少动型帕金森病患者,并予口服中药——培元解痉汤加减治疗,分别于治疗前后行NMSS(帕金森病非运动症状量表)、UPDRS(统一帕金病森评分量表Ⅲ)、TCM(PD中医证候量化分级表)三种量表评分,并采集核磁影像,将之与9名与治疗组年龄、文化程度基本匹配的正常人核磁影像对照研究。采用FreeSUrfer5.3进行皮层分割,FATCAT工具包行白质纤维追踪,分别按确定性算法(Deterministic tractography,DET),简略概率算法(Mini-Probabilistic Tracking,MINIP)和全概率算法(Probabilistic Tracking,PROB)计算纤维连接。用支持向量机(Support Vector Machine,SVM)分类(SVC)比较治疗前PD组与正常人之间脑结构性网络的差异,并行交叉验证。采用支持向量机回归(SVR)分析三种量表评分(NMSS、UPDRS、TCM)与脑结构网络相关性。研究结果:1.强直少动型帕金森病患者与正常人相比存在脑结构网络的特异性改变;其NMSS、UPDRS、TCM症状量表评分与脑连接改变具有相关性。2.SVC中对识别PD组贡献度大的连接以中央前回、间脑腹侧、额下回盖部为主要节点,以中央前回-额下回盖部、中央前回-间脑腹侧的连接改变为显著;对识别正常对照组贡献度大的连接以额上回、豆状核壳、杏仁核、扣带回为节点;以缘上回-岛叶、扣带回-额上回的连接改变为显著。3.与NMSS量表评分正相关的连接主要以间脑腹侧、中央前回、顶上小叶、豆状核壳为节点,以间脑腹侧-中央前回、顶上小叶-豆状核壳的连接相关性为显著;负相关连接主要以内嗅皮质、顶下小叶、额上回、缘上回为节点,以顶下小叶-缘上回,内嗅皮质-杏仁核相关性显著。4.与UPDRS量表评分正相关的连接主要以豆状核壳、内嗅皮质、额上回、颞极为节点,以内嗅皮质-颞极、顶上小叶-豆状核壳、额上回-间脑腹侧、中央前回-岛叶连接相关性为显著;负相关连接主要以海马、内嗅皮质、丘脑本体为节点,以海马-内嗅皮质、丘脑本体-海马连接相关显著。5.与TCM量表评分正相关连接主要以舌回、眶外侧回为节点,结构连接以眶外侧回-颞上回,舌回-扣带回、舌回-颞下回相关性显著;负相关的连接以内嗅皮质、海马、中央旁小叶为主要节点,连接中以海马-内嗅皮质、内嗅皮质-豆状核壳、海马-间脑腹侧、内嗅皮质-杏仁核、中央旁小叶-中央前回相关性显著。结论:1.强直少动型帕金森病患者与正常人相比存在脑结构网络的改变;NMSS、UPDRS、TCM症状量表评分与脑连接改变具有相关性;可有助于PD临床诊断与证候量化;2.以内嗅皮质和基底节(主要为豆状核壳、杏仁核)为节点的结构连接改变符合帕金森病原发病理改变特征;3.TCM量表相关的连接较NMSS及UPDRS具有个性及规律性,提示PD肾虚血瘀证不仅为PD症状集合,亦存在相应脑结构连接特征为生物学基础。
[Abstract]:Background: with the pathology of Parkinson in recent years progress, found that Parkinson does not start with the pathological changes was not confined to the substantia nigra, because it involved multiple sites, diverse symptoms, early diagnosis is not easy. The researchers tried through a variety of ways to summarize the characteristic symptoms of Parkinson's disease law, improve the rate of early diagnosis of Parkinson's disease, and early treatment, improve the prognosis of patients with Parkinson disease. Less action is slow, myotonia characterized the Parkinson disease subtypes, because the tremor is not significant, early diagnosis is more difficult. It has been shown that the traditional Chinese medicine of Tonifying the kidney and removing blood stasis in treatment of ankylosing hypokinesia type of Parkinson's disease can effectively improve symptoms in patients with a variety of score. Including motor symptoms and non motor symptoms (autonomic function, psychiatric symptoms, sensory disturbances, sleep disorders), and brain functional connectivity also changes in the after treatment, but the TCM syndrome and brain structure network The correlation remains to be further studied. The "syndrome" is the fundamental basis of TCM individual treatment. The origin and development of "syndrome" in traditional Chinese medicine has been concerned. The relationship between modern medical research in a variety of technical means of traditional Chinese medicine and modern physical and chemical indicators, in order to prove TCM "syndrome" concept not only the summary of the historical experience and disease symptoms of root pile, more inherent biological basis. Research on common syndrome score become important quantitative indicators of the exploration process. Support vector machine (SVM) is an advanced supervised learning method, can be used to solve some small samples, statistical problems of high dimensions. The trial research on support vector machine (Support Vector Machine, SVM) (SVC) classification and regression (SVR) method for brain structural network differences between PD group and normal people, analysis of each symptom scale ( Including the TCM Syndrome Scale scores) associated with structural brain networks. Objective: (1) compare the features of brain structure rigidity dynamic network of PD were different from normal people, provide supplementary means for accurate diagnosis of Parkinson's disease; (2) the score of three form PD (NMSS, UPDRS, TCM) correlation with the brain structure of the network; (3) analysis with less dynamic Parkinson disease of kidney deficiency and blood stasis in the existence of brain structure network characteristic changes for the syndrome of internal biological basis. Methods: in this study, in accordance with the standard test by the Beijing University of Chinese Medicine Dongzhimen hospital in 9 cases of patients with Parkinson's disease with less, and with oral administration of traditional Chinese Medicine - Peiyuan spasmolysis decoction, NMSS respectively before and after the treatment (non motor symptoms of Parkinson's Disease Rating Scale (UPDRS), unified Parkin's Disease Rating Scale III Sen (PD TCM), TCM Syndrome Scale) three kinds of scale, and acquisition of magnetic The 9 images, and the treatment group and the control of age, normal MRI, basic education. Using FreeSUrfer5.3 cortex segmentation, FATCAT tool kit for white matter fiber tracking, respectively according to the deterministic algorithm (Deterministic tractography DET), a probabilistic algorithm (Mini-Probabilistic Tracking MINIP) and total probability algorithm (Probabilistic Tracking, PROB) calculation of fiber connection. Support vector machine (Support Vector Machine, SVM) classification (SVC) comparison between the treatment group and PD normal human brain structural network difference, parallel cross validation. The support vector machine regression (SVR) analysis of three scores (NMSS, UPDRS, TCM) associated with structural brain networks. Results: 1. patients with Parkinson's disease with less specificity compared with the normal brain structure changes in the network; NMSS, UPDRS, TCM symptom scale score and brain connection With time-varying correlation in.2.SVC to identify the PD group contribution degree in order to precentral gyrus, inferior frontal ventral diencephalon, cover as the main node in the precentral gyrus - inferior frontal gyrus cover, precentral gyrus - ventral diencephalon connections significantly; recognition of the normal control group contribution connection in the superior frontal gyrus, putamen, amygdala, cingulate as nodes; in the supramarginal gyrus insula, cingulate gyrus - connected frontal gyrus change score in the ventral diencephalon is connected to the main related table was.3. and NMSS, precentral gyrus, superior parietal lobule, putamen for nodes. In the diencephalon ventral - precentral gyrus, superior parietal lobule - connected between putamen was significantly negatively correlated; main connection within the entorhinal cortex, inferior parietal lobule, superior frontal gyrus, supramarginal gyrus as nodes, with inferior parietal lobule - supramarginal gyrus, amygdala entorhinal cortex significantly correlated.4. and UPDRS scale. The main points are related connection 浠ヨ眴鐘舵牳澹，

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