北京生物醫(yī)學(xué)工程

基于彌散張量成像的腦結(jié)構(gòu)網(wǎng)絡(luò)參數(shù)研究

Research of brain structure network parameters based on diffusion tensor imaging

作者：余敏陶玲錢志余朱威州

單位：                      南京航空航天大學(xué)自動(dòng)化學(xué)院（南京210016）        

關(guān)鍵詞：彌散張量成像；小世界網(wǎng)絡(luò)；核心節(jié)點(diǎn)

分類號(hào)：

出版年·卷·期（頁(yè)碼）：2014·33·5（446-451）

摘要：

目的利用復(fù)雜網(wǎng)絡(luò)參數(shù)評(píng)估大腦特征，是探明大腦工作機(jī)制的新思路。方法本研究基于彌散張量纖維束追蹤和小世界網(wǎng)絡(luò)理論構(gòu)建腦結(jié)構(gòu)網(wǎng)絡(luò)。首先利用自動(dòng)解剖標(biāo)定(automated anatomical labeling, AAL)模板對(duì)大腦分區(qū)，并計(jì)算腦區(qū)間的纖維連接情況，對(duì)正常人的大腦結(jié)構(gòu)進(jìn)行網(wǎng)絡(luò)建模。然后分析腦結(jié)構(gòu)網(wǎng)絡(luò)中節(jié)點(diǎn)度、簇系數(shù)和節(jié)點(diǎn)介數(shù)等網(wǎng)絡(luò)參數(shù)，并通過引入小世界網(wǎng)絡(luò)的介數(shù)和損傷性定義人腦結(jié)構(gòu)網(wǎng)絡(luò)的核心節(jié)點(diǎn)位置和特征。結(jié)果腦結(jié)構(gòu)網(wǎng)絡(luò)具有小世界屬性，且網(wǎng)絡(luò)中存在少量的核心節(jié)點(diǎn)，具有較高的節(jié)點(diǎn)度和簇系數(shù)值。結(jié)論利用彌散張量成像能夠客觀構(gòu)建大腦結(jié)構(gòu)網(wǎng)絡(luò)，而核心節(jié)點(diǎn)的存在為揭示腦疾病的病理生理機(jī)制提供新的思路。

Objective To assess the brain characteristics by using complex network parameters is a new idea to ascertain the brain working mechanism. Methods In this study, we built structural network based on diffusion tensor fiber bundle tracking and small-world network theory. The fiber connections between each AAL brain region were extracted to model the normal brain structure. The location and characteristics of hub nodes were defined by using the node betweenness and vulnerability. The network node degree, clustering coefficient and node betweenness were then calculated. Results The brain structure networks exhibited efficient small-world properties and there were a few hub nodes in the brain which had high node degree and clustering coefficient. Conclusions Brain structure networks could be objectively constructed by diffusion tensor imaging and the existence of hub nodes provided new ideas for the pathophysiology of brain disease.

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