FSL在DTI大脑图像分析中的应用现状

Applications of FSL in the brain based on DTI

随着弥散张量成像(diffusion tensor imaging,DTI)技术在大脑结构方面应用研究的增多,与之相关的数据分析软件也在增多,其中FMRIB Software Library(FSL)在示踪时使用的是基于概率性示踪的算法,在进行交叉纤维示踪和灰质连接上有很大优势。本文主要根据数据分析方式的不同对FSL包含的两个子工具(tract-based spatial statistics,TBSS和FMRIB’s diffusion toolbox,FDT)在DTI大脑图像分析方面的应用现状进行分类介绍,主要涉及老年抑郁症、精神分裂症以及认知功能等领域。本文首先简要介绍DTI原理,然后根据数据分析方式的不同,在TBSS部分分为全脑分析和感兴趣区域(region of interest,ROI)分析两方面,在FDT部分分为全脑示踪、ROI互连分析、基于连通度的分类三方面进行介绍,最后对FSL的局限性以及发展状况进行总结。

With the advent of diffusion tensor imaging,the number of brain studies with DTI is growing steadily. Accordingly,the relevant software are also emerging. Notably,the fiber tracking algorithm in FSL is probabilistic diffusion tractography. It is suitable for the study on regions of fiber crossing and gray matter. Here,we mainly introduce the two sub-tools（ tract-based spatial statistics,TBSS and FMRIB ＇s diffusion toolbox,FDT） and their application in DTI brain image analysis classified by the different data analysis methods,mainly involving depression,schizophrenia and cognitive function and so on. In this paper,we briefly explain the basic principle of DTI at first. Next,according the different data analysis methods,we introduce the application of TBSS and FDT. In TBSS,there are two parts： the whole brain and region of interest（ ROI）. In FDT,there are three parts： the whole brain,ROI and the classification of connectivity. Finally,we summarize the limitation and the development of FSL currently.