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BrainCAT - a tool for automated and combined functional magnetic resonance imaging and diffusion tensor imaging brain connectivity analysis

机译:BrainCAT-一种用于自动和组合功能磁共振成像和扩散张量成像大脑连通性分析的工具

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摘要

Multimodal neuroimaging studies have recently become a trend in the neuroimaging field and are certainly a standard for the future. Brain connectivity studies combining functional activation patterns using resting-state or task-related functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) tractography have growing popularity. However, there is a scarcity of solutions to perform optimized, intuitive, and consistent multimodal fMRI/DTI studies. Here we propose a new tool, brain connectivity analysis tool (BrainCAT), for an automated and standard multimodal analysis of combined fMRI/DTI data, using freely available tools. With a friendly graphical user interface, BrainCAT aims to make data processing easier and faster, implementing a fully automated data processing pipeline and minimizing the need for user intervention, which hopefully will expand the use of combined fMRI/DTI studies. Its validity was tested in an aging study of the default mode network (DMN) white matter connectivity. The results evidenced the cingulum bundle as the structural connector of the precuneus/posterior cingulate cortex and the medial frontal cortex, regions of the DMN. Moreover, mean fractional anisotropy (FA) values along the cingulum extracted with BrainCAT showed a strong correlation with FA values from the manual selection of the same bundle. Taken together, these results provide evidence that BrainCAT is suitable for these analyses.
机译:多模态神经影像学研究最近已成为神经影像学领域的趋势,并且无疑是未来的标准。结合使用静止状态或与任务相关的功能性磁共振成像(fMRI)和扩散张量成像(DTI)图像描记术的功能激活模式的大脑连通性研究越来越受欢迎。但是,缺乏执行优化,直观且一致的多峰fMRI / DTI研究的解决方案。在这里,我们提出了一种新工具,即大脑连通性分析工具(BrainCAT),该工具可以使用免费提供的工具对fMRI / DTI组合数据进行自动化和标准的多模式分析。通过一个友好的图形用户界面,BrainCAT的目标是使数据处理更容易,更快捷,实现全自动数据处理管道并最大程度地减少用户干预的需求,这有望扩大fMRI / DTI组合研究的使用范围。在对默认模式网络(DMN)白质连接的老化研究中测试了其有效性。结果证明了扣带束是DMN的前扣带/后扣带皮层和内侧额叶皮层的结构连接器。此外,使用BrainCAT提取的扣带沿平均平均分数各向异性(FA)值与手动选择相同束的FA值具有很强的相关性。综上所述,这些结果提供了证明BrainCAT适用于这些分析的证据。

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