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Diffusion kurtosis magnetic resonance imaging and its application to traumatic brain injury.

机译：扩散峰度磁共振成像及其在颅脑外伤中的应用。

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摘要

Diffusion tensor imaging (DTI) is a popular magnetic resonance imaging technique that provides in vivo information about tissue microstructure, based on the local water diffusion environment. DTI models the diffusion displacement of water molecules in tissue as a Gaussian distribution. In this dissertation, to mimic the complex nature of water diffusion in brain tissues, a diffusion kurtosis model is used, to incorporate important non-Gaussian diffusion properties. This diffusion kurtosis imaging (DKI) is applied in an experimental traumatic brain injury in a rat model, to study whether it provides more information on microstructural changes than standard DTI. Our results indicate changes in ordinary DTI parameters, in various brain regions following injury, normalize to the baseline by the sub-acute stage. However, DKI parameters continue to show abnormalities at this sub-acute stage, as confirmed by immunohistochemical examination. Specifically, increased mean kurtosis (MK) was found to associate with increased reactive astrogliosis, a hallmark for inflammation, even in regions far removed from the injury foci. Findings suggest that monitoring changes in MK enhances the investigation of molecular and morphological changes in vivo.;Extending DKI to clinical usage, however, poses several challenges: (a) long image acquisition time (∼20 min) due to the augmented measurements required to fit the more complex model, (b) slow image reconstruction (∼90 min) due to required nonlinear fitting and, (c) errors associated with fitting the inherently low signal-to-noise ratio (SNR) images from higher diffusion weighting. The second portion of this dissertation is devoted to developing imaging schemes and image reconstruction methods that facilitate clinical DKI applications. A fast and efficient DKI reconstruction method is developed with a reconstruction time of 2-3 seconds, with improved accuracy and reduced variability in DKI estimation over conventional methods. Further analysis of diffusion weighted imaging schemes and their affect on DKI estimation leads to the identification of two clinically practical optimal imaging schemes (needing 7-10 min) that perform comparably to traditional schemes. The effect of SNR and reconstruction methods on DKI estimation is also studied, to provide a foundation for interpreting DKI results and optimizing DKI protocols.
机译：扩散张量成像（DTI）是一种流行的磁共振成像技术，可基于局部水扩散环境提供有关组织微结构的体内信息。 DTI将水分子在组织中的扩散位移建模为高斯分布。在本文中，为了模拟水在脑组织中扩散的复杂性质，使用了扩散峰度模型，以纳入重要的非高斯扩散特性。此扩散峰度成像（DKI）用于大鼠模型的实验性颅脑外伤，以研究它是否比标准DTI提供更多有关微结构变化的信息。我们的结果表明，损伤后各个脑区域中普通DTI参数的变化会在亚急性阶段恢复到基线水平。然而，如免疫组织化学检查所证实，DKI参数在此亚急性阶段继续显示异常。具体而言，发现平均峰度增加（MK）与反应性星形胶质增生增加有关，反应性星形胶质增生是炎症的标志，即使在远离受伤灶的区域也是如此。研究结果表明，监测MK的变化可增强体内分子和形态学变化的研究;然而，将DKI扩展到临床应用则面临一些挑战：（a）由于需要增加测量值，因此图像获取时间长（约20分钟）。拟合更复杂的模型，（b）由于所需的非线性拟合而导致的图像重建速度慢（约90分钟），以及（c）与来自较高扩散加权的固有低信噪比（SNR）图像拟合相关的误差。本论文的第二部分致力于开发有助于临床DKI应用的成像方案和图像重建方法。开发了一种快速有效的DKI重建方法，其重建时间为2-3秒，与传统方法相比，具有更高的准确性和DKI估计的可变性降低。对扩散加权成像方案及其对DKI估计的影响的进一步分析导致鉴定出与传统方案性能相当的两种临床实用的最佳成像方案（需要7-10分钟）。研究了信噪比和重建方法对DKI估计的影响，为解释DKI结果和优化DKI协议提供了基础。

著录项

  • 作者

    Zhuo, Jiachen.;

  • 作者单位

    University of Maryland, College Park.;

  • 授予单位 University of Maryland, College Park.;
  • 学科 Engineering Biomedical.;Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 161 p.
  • 总页数 161
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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