研究报告: 小动物高分辨扩散磁共振成像数据分析方法

扩散磁共振成像(dMRI)是一种非侵入性的、能提供生物体内水分子扩散运动相关信息的成像技术，可用于检测神经纤维微观结构的变化．dMRI的出现为大脑结构与功能研究提供了全新的检测手段．过去的20年中，dMRI在实验方法和临床应用上均取得了重大进展．然而dMRI应用在基于动物模型的临床前脑成像研究中却并不常见．本文针对dMRI在临床前脑成像研究中的应用，建立了系列针对小动物高分辨dMRI数据的分析方法：a．构建了大鼠高分辨dMRI图像模板；b．实现了适用于小动物研究的基于体素的统计分析(VBA)方法与基于纤维束的空间统计分析(TBSS)方法；c．实现了小动物脑白质纤维束的确定性与概率性跟踪．这些方法的实现不仅能为小动物脑dMRI研究提供统一的图像模板与完善的计算方法，还将大大促进dMRI技术在小动物脑成像研究中的应用．

Research Paper: Templates and Analysis Methods for Small Animal High-resolution Diffusion Magnetic Resonance Imaging

Diffusion magnetic resonance imaging (dMRI) is a non-invasive imaging technique capable of characterizing the diffusion properties of water molecules in vivo and detecting microstructural changes in brain tissue. It provides new tools to investigate the integrity of brain white matter. Although dMRI is widely used in clinical studies, and has become a common method in clinical radiology, it is infrequently used in preclinical brain imaging studies on small animal models. In this paper, we implemented computational methods for small animal dMRI. First, a high-resolution dMRI template for rat was constructed. Secondly, voxel-based analysis and tract-based spatial statistics methods for small animal dMRI were implemented. Last but not least, the deterministic and probabilistic tractography methods for small animal imaging were implemented. The implementation of these methods will facilitate the applications of dMRI in preclincal small animal imaging.