本文關鍵詞： 帶狀皰疹后遺神經(jīng)痛 功能磁共振 圖論 腦結構網(wǎng)絡 小世界網(wǎng)絡　出處：《昆明醫(yī)科大學》2017年碩士論文　論文類型：學位論文

【摘要】：[目的]本研究采用近年學科交叉研究熱點的腦網(wǎng)絡分析方法,將磁共振擴散張量成像(diffusion tensor imaging,DTI)技術與圖論分析方法相結合,利用解剖學自動標記模板(Automated Anatomical Labeling,AAL)把大腦劃分為90腦區(qū)定義為90個節(jié)點,邊的權重(wij)定義為任意兩個腦區(qū)間白質纖維束的纖維束數(shù)量(Fiber number,FN)與平均各項異性分數(shù)值(Fractional Anisotropy,FA)的乘積(wij=FNij × FAij),由此構建具有纖維束復合屬性的加權腦結構網(wǎng)絡(90X90)圖論模型,檢測和定量分析帶狀瘡疹后遺神經(jīng)痛(postherpetic neuralgia,PHN)腦結構網(wǎng)絡拓撲屬性改變特點,從一個全新的視角認識和探討PHN中樞微觀改變。[方法]分別采集15例帶狀皰疹后并發(fā)PHN患者和與之性別、年齡、受教育程度匹配的健康志愿者磁共振圖像數(shù)據(jù),包括全腦DTI和3D T1WI數(shù)據(jù){采集數(shù)據(jù)當天同時采集所有被試者一般臨床資料和PHN患者視覺模擬評分(visual analogue scale,VAS)、病程、部位等相關信息}。使用北京師范大學腦認知與學習國家重點實驗室自行設計的DTI自動處理軟件PANDA和基于Matlab軟件開發(fā)的針對磁共振影像數(shù)據(jù)基于圖論的復雜腦網(wǎng)絡分析軟件Gretna、NBS(Network-Based Statistic)對數(shù)據(jù)進行處理,利用解剖學自動標記模板把大腦劃分為90腦區(qū)定于為90個節(jié)點,邊的權重(wij)定義為任意兩個腦區(qū)間白質纖維束的FN與FA值的乘積(wij = FNij × FAij),由此構建具有纖維束復合屬性的加權腦結構網(wǎng)絡(90X90)圖論模型,以年齡、性別、受教育程度作為協(xié)變量,采用兩獨立樣本t檢驗對兩組被試腦結構網(wǎng)絡模型各項拓撲屬性特征進行差異性統(tǒng)計分析,包括小世界屬性、網(wǎng)絡全局效率及局部效率、節(jié)點效率。對兩組網(wǎng)絡屬性改變與臨床變量(VAS評分、病程)作偏相關分析,觀察PHN患者網(wǎng)絡屬性異常改是否與臨床變量存在顯著相關性。[結果]1、PHN組和正常對照組(Normalcontrol,HC)的腦結構網(wǎng)絡均具有明顯的“小世界”屬性(采用雙樣本t檢驗進行統(tǒng)計分析,經(jīng)FDR校正,取P0.05時,認為兩組間差異有統(tǒng)計學意義)。2、PHN組和HC組的腦結構網(wǎng)絡全局效率和局部效率差異均無統(tǒng)計學意義(P0.05)。3、PHN組與HC組腦結構網(wǎng)絡各腦區(qū)節(jié)點效率相比,PHN組局部腦區(qū)節(jié)點效率顯著減低,包括左側腦島、左側海馬旁回、左側豆狀殼核、右側眶部額中回、右側眶部額下回、雙側直回、右側枕下回(P0.05)。4、與HC組相比,PHN組腦結構網(wǎng)絡部分腦區(qū)間連接邊的連接強度顯著減低,分別位于左側海馬旁回-左側舌回,左側舌回-左側直回,左側直回-右側前扣帶回和扣帶旁回,左側直回-左側眶內(nèi)額上回,左側眶內(nèi)額上回-右側尾狀核,左側眶內(nèi)額上回-左側豆狀殼核,右側尾狀核-左側丘腦,右側尾狀核-左側背外側額上回(P0.05)。5、回歸去除年齡、性別、受教育程度的影響后,相關性分析結果顯示PHN患者腦結構網(wǎng)絡局部腦區(qū)節(jié)點效率減低及部分腦區(qū)間的連接邊強度減低均與VAS評分、病程之間無明顯統(tǒng)計意義相關性(P0.05)。[結論]1、PHN患者和正常對照者的腦結構網(wǎng)絡均具有明顯的“小世界”屬性,再次證實了人腦具有經(jīng)濟-低能的“小世界”式信息處理模式,反映了人腦結構網(wǎng)絡功能分化和整合之間的優(yōu)化平衡。2、PHN患者和正常對照者的腦結構網(wǎng)絡全局效率和局部效率無顯著差異,說明PHN腦結構網(wǎng)絡整體連接模式并未發(fā)生本質的改變。3、PHN患者腦結構網(wǎng)絡左側島葉、左側海馬旁回、左側豆狀殼核、右側眶部額中回、右側眶部額下回、雙側直回及右側枕下回多個腦區(qū)節(jié)點效率較HC組顯著減低;且多個腦區(qū)間連接邊的連接強度顯著減低。這些腦區(qū)主要涉及感覺,記憶,情感和情緒過程,提示PHN疼痛的產(chǎn)生可能與不同腦區(qū)間結構連接失調(diào)有關,間接反映了PHN患者白質連接存在廣泛的損傷。4、基于圖論的腦結構網(wǎng)絡研究方法可以全面、立體的檢測和定量分析腦結構網(wǎng)絡拓撲屬性改變特點,為探索PHN的中樞機制、觀察其腦網(wǎng)絡結構的改變以及解釋相應臨床表現(xiàn)提供了一個全新的方向。
[Abstract]:[Objective] this study used in cross interdisciplinary research topics of brain network analysis method, the diffusion tensor magnetic resonance imaging (diffusion tensor, imaging, DTI) technology combining with the graph theory, the automatic labeling template (Automated Anatomical Labeling, according to the anatomy of the brain is divided into AAL) defined 90 brain areas with 90 nodes and edges the weight of fiber (Wij) is defined as any two brain white matter fiber bundles (Fiber number, FN) and the average anisotropy value (Fractional Anisotropy, FA) of the product (wij=FNij * FAij), thus constructing weighted brain structure network with fiber composite attribute (90X90) graph model the detection and quantitative analysis of herpes zoster neuralgia (postherpetic neuralgia, PHN) the changes of topological properties of brain structure network, from a new perspective and explore the microscopic changes of central PHN method were collected. In 15 cases of herpes zoster patients with PHN and gender, age, healthy volunteers with magnetic resonance image data, level of education, including whole brain DTI and 3D T1WI data acquisition data collected at the same time the day {all the subjects of general clinical data and PHN patients with visual analogue scale (visual analogue, scale, VAS) course site, and other related information. The use of brain cognition and learning of Beijing Normal University State Key Laboratory of self-designed DTI automatic processing software PANDA and Matlab software development based on magnetic resonance imaging data of complex brain network analysis software Gretna, NBS (Network-Based Statistic) for data processing, the use of automatic marking the template anatomy of the brain is divided into 90 brain is scheduled to 90 nodes, edge weights (Wij) is defined as the product of any two brain white matter fiber FN and FA values (Wij = FNij * FAij) Thus, to construct weighted brain structure network with fiber bundle composite attribute (90X90) graph theory model, by age, gender, education level as a covariate, using two independent sample t test on the two groups of subjects brain structure network model the topology characteristics and differences in statistical analysis, including small world properties, the overall efficiency of the network and the local efficiency, efficiency of the two groups of network node attribute changes and clinical variables (VAS score, duration) for partial correlation analysis, PHN on patients with abnormal change of whether the network properties and the clinical variables have significant correlation. The results of]1, PHN group and normal control group (Normalcontrol, HC) of the brain structural networks had obvious the "small world" attribute (with two sample t test was used for statistical analysis, the FDR correction was P0.05, there was significant difference between the two groups of.2), PHN group and HC group, the brain structure of the overall efficiency of the network and the local There were no significant differences in the efficiency of.3 (P0.05), PHN group and HC group brain areas of the brain structure of the network node efficiency compared to the PHN node group of local brain regions significantly reduce the efficiency, including the left insula, left parahippocampal gyrus, left putamen, right orbital frontal gyrus, right inferior frontal gyrus bilateral orbital. Straight back, right middle occipital gyrus (.4, P0.05) compared with HC group, PHN group network connection strength of brain structure interval with edge part of the brain was significantly decreased, respectively located in the left parahippocampal gyrus, left lingual gyrus, left lingual gyrus and left straight back, left back straight - right anterior cingulate and cingulate gyrus the left back, straight - left orbital frontal gyrus, left orbital frontal gyrus and right caudate nucleus, left orbital frontal gyrus and left putamen, right caudate nucleus, left thalamus, right caudate nucleus - left dorsolateral frontal gyrus (P0.05).5, regression removal age, gender, education level of the after correlation analysis Results showed that the brain structure in patients with PHN brain network nodes and reduce efficiency of the connecting edge part of the brain interval strength decreased with VAS score, no obvious statistical significance of the correlation between the course of disease (P0.05). Conclusion]1, PHN patients and normal controls, the brain structural networks have obvious small world property, once again confirmed the human brain has low energy economy "small world" type information processing model, reflects the optimal balance between.2 differentiation and integration of human brain structure network function, there was no significant difference between the global and local efficiency of brain structure of PHN patients and normal controls, PHN brain structure overall network connection mode does not change the nature of the occurrence of.3. Brain PHN networks in patients with left insula, left parahippocampal gyrus, left putamen, right orbital frontal gyrus, right orbital frontal gyrus, bilateral straight gyrus and right inferior occipital gyrus in multiple brain regions of nodes Efficiency is significantly lower than the HC group; and a plurality of connection strength side of the brain regions decreased significantly. These brain regions are involved in sensory, memory, emotion and emotional process, suggesting that PHN may produce pain with different brain regions connected structure disorder, indirectly reflects the PHN patients with white matter damage.4 connection exists widely, brain study on the structure of the network based on graph theory can change the characteristics of comprehensive, three-dimensional detection and quantitative analysis of brain network topology attributes for the central mechanism of PHN exploration, to observe the brain network structure change and explain the corresponding clinical manifestations and provides a new direction.

【學位授予單位】：昆明醫(yī)科大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R445.2;R752.12

【參考文獻】

相關期刊論文 前6條

1 伍小敏;于泳健;蔡放;王宏法;;帶狀皰疹后遺神經(jīng)痛的發(fā)病相關因素分析[J];中華全科醫(yī)學;2016年03期

2 梁豪文;肖禮祖;秋云海;劉小武;張強;藍惠琴;熊東林;張德仁;;帶狀皰疹不同階段局部一致性腦功能磁共振對比研究[J];中國疼痛醫(yī)學雜志;2014年10期

3 張曉楠;程敬亮;王斐斐;孫夢恬;林亞南;張風光;楊璐;;有或無海馬硬化的顳葉癲癇患者丘腦DTI變化的分析[J];實用放射學雜志;2014年01期

4 何昌杰;;78例卡馬西平片治療帶狀皰疹神經(jīng)后遺癥的療效與分析[J];中國醫(yī)藥指南;2012年24期

5 伊慧明;周媛;張權;張，

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