Study of fiber anatomy in mouse brain development via MRI/DTI

描述(申请人提供)：这项研究计划的主要目标是描述小鼠大脑的发育，重点是脑白质解剖学，结合计算神经解剖学领域的定量图像和形状分析的数学方法，使用磁共振显微成像。通过研究正常动物和转基因动物大脑发育过程中的差异，改变包括小鼠在内的模型动物的基因型的方法的发展，为更好地了解不同基因在大脑发育和疾病中的作用打开了巨大的可能性。成像，特别是MRI，必将在小鼠模型的结构表型中发挥重要作用，因为它可以作为一种有效的筛选工具，指向更详细但繁琐的组织学分析，并且不受切片和染色失真伪影的影响，但提供空间上一致的3D体积。然而，传统的成像技术不能揭示内部白质结构，它由各种纤维束组成，对了解大脑发育非常感兴趣。尤其是胎鼠和幼鼠的大脑，髓鞘不发达，T1或T2加权图像甚至无法以足够的对比度区分灰质和白质。扩散张量成像(DTI)提供了极好的对比度，通过成像沿轴突纤维相对较高的微观水扩散，即使是年轻的大脑，也能够区分白质中的各种结构。因此，DTI在研究大脑发育和脑连通性以及了解基因突变如何影响轴突纤维的形成、髓鞘形成或退化方面肯定是至关重要的。与显微磁共振成像的进步同步的是计算解剖学的数学方法的进步，计算解剖学是一个迅速成熟的定量技术领域，用于从体积图像分析脑形态。这些新方法现在被一些神经成像和神经信息学小组采用，它们构成了以高度自动化和详细的方式进行结构表型鉴定的强大工具；它们对形态变化的微妙和空间复杂模式特别敏感。在这个项目中，我们将继续开发小鼠大脑的定量分析方法，并使用它们来生成C57BL/6J小鼠品系脑发育的标准化数据，并研究野生型和转基因小鼠模型之间的表型差异。重点将继续是DTI(目标1和2)中获得的张量图像的复杂性带来的数学和计算挑战，特别是图像配准和形态分析方面的挑战，这些挑战是由于在出生后早期发育期间观察到的快速变化以及转基因小鼠和野生型小鼠之间的形态差异造成的。此外，我们将在三个具体项目的研究中测试我们的方法的有效性，这些项目涉及精神分裂症、自闭症和Rett综合征的小鼠模型(目标3)，共同努力。 与公众健康相关：该项目寻求通过高分辨率扩散张量成像来调查小鼠正常的大脑发育，这是一种提供脑组织和纤维结构良好清晰度的MRI对比。将进一步开发和验证用于扩散张量图像的先进计算图像分析工具，强调该项目面临的两个挑战：1)出生后早期发育过程中的快速解剖变化；2)野生型和转基因小鼠之间的形态差异。这些神经信息学工具将被应用于3个合作项目，寻求识别野生型小鼠和精神分裂症、自闭症和雷特氏综合症小鼠模型之间的大脑差异。

DESCRIPTION (provided by applicant): The main goal of this research program is to characterize the development of the mouse brain, with emphasis on white matter anatomy, using magnetic resonance micro-imaging in conjunction with mathematical methodologies for quantitative image and shape analysis following the field of computational neuroanatomy. The development of methods for altering the genotype of model animals, including mice, has opened enormous possibilities for better understanding the role of different genes in brain development and diseases, by studying differences in the course of brain development between normal and transgenic animals. Imaging, and in particular MRI, is bound to play an important role in structural phenotyping of mouse models, since it can serve as an effective screening tool pointing to more detailed yet laborious histological analyses, and does not suffer from sectioning and staining distortion artifacts, but provides spatially consistent 3D volumes. However, conventional imaging techniques cannot reveal the internal white matter architecture, which consists of various fiber tracts and is of great interest in understanding brain development. This is especially the case for fetal and young mouse brains, in which myelination is not well developed and the T1- or T2-weighted images cannot even distinguish the gray and white matter with adequate contrast. Diffusion tensor imaging (DTI) provides excellent contrast, and is able to distinguish various structures in the white matter of even young brains, by imaging microscopic water diffusion which is known to be relatively higher along axonal fibers. Therefore, DTI is bound to be critical in studying brain development and brain connectivity, as well in understanding how genetic mutations affect the formation, myelination, or degeneration of axonal fibers. Concurrent with advances in micro-MR imaging have been advances in mathematical methodologies for computational anatomy, a rapidly maturing field of quantitative techniques for analysis of brain morphology from volumetric images. These new approaches are now adopted by a number of neuroimaging and neuroinformatics groups, and they constitute powerful tools for structural phenotyping in highly automated and detailed ways; they are particularly sensitive to subtle and spatially complex patterns of morphological change. In this project, we will continue to develop methods for quantitative analysis of the mouse brain, and use them to generate normative data for brain development of the C57BL/6J mouse strain, and to investigate phenotypic differences between wildtype and transgenic mouse models. Emphasis will continue to be the mathematical and computational challenges posed by the complexity of tensor images, which are obtained in DTI (Aims 1 and 2), especially challenges in image registration and morphological analysis that are posed by the rapid changes observed during early postnatal development as well as by morphological differences between transgenic and wildtype mice. Moreover, we will test the utility of our methodologies in studies of 3 specific projects involving mouse models of schizophrenia, autism, and Rett's syndrome (Aim 3), in collaborative efforts. PUBLIC HEALTH RELEVANCE: This project seeks to investigate normal mouse brain development via high-resolution diffusion tensor imaging, an MRI contrast that provides good definition of brain tissues and of fiber architecture. Advanced computational image analysis tools for diffusion tensor images will be further developed and validated, emphasizing two of the challenges faced by this project: 1) rapid anatomical changes during early postnatal development; 2) morphological differences between wildtype and transgenic mice. These neuroinformatics tools will be applied to 3 collaborative projects, seeking to identify brain differences between wildtype mice and mouse models of schizophrenia, autism, and Rett's syndrome.