A novel multi-modal, multi-scale imaging pipeline for the validation of diffusion MRI of the brain

一种用于验证大脑扩散 MRI 的新型多模式、多尺度成像流程

• 批准号: 10204138
• 负责人: Timothy Scott Trinkle
• 金额: $ 4.17万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2022-09-17
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10204138
• 关键词: 3-Dimensional; Address; Algorithms; Anatomy; Architecture; Automobile Driving; Axon; Biological; Brain; Characteristics; Clinical Research; Computer Vision Systems; Data; Data Set; Diagnosis; Diagnostic radiologic examination; Diffusion; Diffusion Magnetic Resonance Imaging; Electron Microscopy; Failure; Fiber; Future; Goals; Heavy Metals; Histologic; Histology; Image; Imaging Device; Magnetic Resonance Imaging; Maps; Metals; Methods; Modality; Modeling; Modernization; Morphology; Mosaicism; Mus; Nerve Tissue; Neurologic; Optics; Performance; Phase; Plant Resins; Play; Population; Process; Property; Reporting; Research; Resolution; Roentgen Rays; Role; Sampling; Scanning; Scheme; Signal Transduction; Slice; Specificity; Specimen; Stains; Structure; Synchrotrons; Techniques; Theoretical model; Thick; Thinness; Three-Dimensional Imaging; Time; Tissue imaging; Tissues; Validation; Work; absorption; base; contrast enhanced; data acquisition; electron tomography; follow-up; image reconstruction; insight; interest; microCT; multimodality; nanometer; nanoscale; nervous system disorder; novel; physical process; reconstruction; relating to nervous system; success; tomography; tool; tractography; validation studies

Project Summary In this project, we propose to validate and characterize fiber orientation estimation from diffusion tensor imag- ing (DTI) through the optimization of a multi-modality, multi-scale imaging pipeline for whole mouse brains. DTI is a powerful tool used to noninvasively report 3D microstructural properties of nervous tissue on a macroscopic scale, and has played an important role in the understanding and diagnosis of a number of neurological disease processes. Modern acquisitions of DTI data can be processed to generate a 3D diffusion profile known as an orientation diffusion function (ODF) at each voxel. The ODF is used to infer the orientation of local axon fiber pop- ulations. Previous efforts to validate these orientation estimates have primarily relied on serial optical histology as a ground truth dataset. Histology-based pipelines involve the labor intensive task of physically sectioning the tissue into thin slices, leading to physical destruction of the sample and anisotropic resolution. These limitations potentially confound the accuracy of 3D orientation estimation, complicate the process of spatially registering the ground-truth and DTI datasets, and limit quantitative comparisons to select regions of interest (ROI) across the brain sample. In recent years, synchrotron x-ray microcomputed tomography (microCT) has emerged as a powerful tool for high-resolution tissue imaging. With a mosaic projection-stitching method, a whole mouse brain can be imaged at an isotropic, 3D resolution of 1.2 microns after prior imaging with DTI. To enhance microCT contrast, the tis- sue specimens are fixed and stained with the same kind of metal-based stains used in electron microscopy (EM) prior to embedding in resin. We will optimize this microCT-EM validation pipeline to address the limitations of pre- vious histology-based studies, and characterize DTI algorithm performance across a whole mouse brain using micron- to nano-scale neurological information. The specific aims of the proposal are: (1) model phase contrast to optimize microCT data acquisition, (2) vali- date DTI ODF reconstruction methods using ground-truth microCT (3) characterize DTI performance using under- lying tissue microstructure information from EM. Upon completion, aim 1 will generate a novel theoretical model and acquisition strategy to exploit microCT phase contrast in strongly absorbing biological samples. Aim 2 will generate a ground-truth dataset of ODFs across a whole mouse brain, which will be used to calculate algorithm- specific spatial maps of DTI performance. In Aim 3, around 20 ROI will be selected for nano-scale imaging with EM, and DTI performance will be characterized by quantitative features of the underlying neural architecture. These results will provide an unprecedented microstructure-driven understanding of the DTI signal, allowing fu- ture studies to develop more advanced DTI models and acquisition strategies to better leverage fiber orientation and connectivity information in the treatment of neurological disease.

项目摘要 在这个项目中，我们建议验证和表征从扩散张量的想象的纤维取向估计。 ING（DTI）通过优化全鼠大脑的多模式，多尺度成像管道。 DTI 是一种强大的工具，用于非侵入性地报告神经组织在宏观组织上的3D微结构特性 尺度，并且在理解和诊断多种神经疾病中发挥了重要作用 过程。可以处理现代DTI数据的现代收购，以生成3D扩散率，称为 每个体素的方向扩散函数（ODF）。 ODF用于推断局部轴突弹出的方向 以前验证这些取向估计值的努力主要依赖于串行光学组织学 作为地面真相数据集。基于组织学的管道涉及劳动密集型任务，以便将 组织成薄片，导致样品的物理破坏和各向异性分辨率。这些限制 可能混淆3D取向估计的准确性，使空间记录的过程复杂化 地面真相和DTI数据集，并将定量比较限制在整个范围内的关注区域（ROI） 大脑样本。 近年来，Synchrotron X射线微型层析成像（Microct）已成为强大的工具 高分辨率组织成像。使用马赛克投影方法，可以成像整个小鼠大脑 在与DTI成像之前，在各向同性的3D分辨率为1.2微米。为了增强MicroCT对比，TIS- SUE样品用电子显微镜（EM）的相同类型的金属污渍固定并染色 在嵌入树脂之前。我们将优化此MicroCT-EM验证管道，以解决PRE-的局限性 更重要的是，基于组织学的研究并使用整个小鼠大脑的DTI算法性能表征 微米至纳米级神经信息信息。 该提案的特定目的是：（1）优化MicroCT数据采集的模型相对比，（2）Vali- 使用地面真实微观（3）使用DTI ODF重建方法（3）表征DTI性能的情况 来自EM的组织微观结构信息。完成后，AIM 1将产生一种新颖的理论模型 和采集策略，以利用强烈吸收生物样品的MicroCT相对比。 AIM 2意志 在整个小鼠大脑上生成ODF的地面真相数据集，该数据集将用于计算算法 - DTI性能的特定空间图。在AIM 3中，将选择大约20个ROI进行纳米级成像 EM和DTI性能将以基本神经结构的定量特征为特征。 这些结果将为DTI信号提供前所未有的微观结构驱动的理解，从而使FU- 进行研究以开发更先进的DTI模型和获取策略，以更好地利用纤维取向 以及神经疾病治疗中的连通性信息。