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.

项目概要 在这个项目中，我们建议验证和表征来自扩散张量图像的纤维取向估计。 通过优化整个小鼠大脑的多模态、多尺度成像管道来进行 DTI 成像（DTI）。 是一种强大的工具，用于在宏观上无创地报告神经组织的 3D 微观结构特性 量表，并在许多神经系统疾病的理解和诊断中发挥了重要作用 现代 DTI 数据采集可被处理以生成 3D 扩散剖面，称为 3D 扩散剖面。 每个体素的方向扩散函数（ODF）用于推断局部轴突纤维的方向。 先前验证这些方向估计的努力主要依赖于串行光学组织学。 作为地面实况数据集，基于组织学的管道涉及物理切片的劳动密集型任务。 组织切成薄片，导致样品的物理破坏和各向异性分辨率。 可能会混淆 3D 方向估计的准确性，使空间配准过程复杂化 地面实况和 DTI 数据集，并限制对整个区域中选定的感兴趣区域 (ROI) 的定量比较 大脑样本。 近年来，同步加速器X射线显微计算机断层扫描（microCT）已成为一种强大的工具。 通过马赛克投影拼接方法，可以对整个小鼠大脑进行成像。 预先使用 DTI 成像后，各向同性 3D 分辨率为 1.2 微米，以增强 microCT 对比度。 将样本固定并用电子显微镜 (EM) 中使用的相同金属基染色剂进行染色 在嵌入树脂之前，我们将优化此 microCT-EM 验证流程，以解决预嵌入的局限性。 之前基于组织学的研究，并使用 DTI 算法表征整个小鼠大脑的性能 微米到纳米级的神经信息。 该提案的具体目标是：（1）模型相衬以优化 microCT 数据采集，（2）验证 使用地面实况 microCT 的日期 DTI ODF 重建方法 (3) 使用 under- 表征 DTI 性能 来自 EM 的躺卧组织微观结构信息完成后，目标 1 将生成一个新颖的理论模型。 目标 2 中利用 microCT 相差的采集策略。 生成整个小鼠大脑中 ODF 的真实数据集，该数据集将用于计算算法 - 在目标 3 中，将选择大约 20 个 ROI 进行纳米级成像。 EM 和 DTI 性能将通过底层神经架构的定量特征来表征。 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 正在进行研究以开发更先进的 DTI 模型和采集策略，以更好地利用纤维取向 以及神经系统疾病治疗中的连接信息。