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Integration of advanced diffusion acquisition and analysis techniques to improve treatment management of brain tumor.

机译：集成了先进的扩散采集和分析技术，以改善脑肿瘤的治疗管理。

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摘要

Diffusion MRI is a technique that is capable of providing unique contrast that is sensitive to molecular displacement motion at cellular and sub-cellular length scales. By sensitizing MR signal to the random motion of water molecule protons at a microscopic level (of the order of 5-20mum), it is able to probe tissue microstructures in the brain such as axons, dendrites, glial cells, and extra-cellular spaces, in a manner that may provide valuable insights into tumor physiology.;Diffusion imaging is routinely acquired as part of the MR protocol for patients with brain tumors. However, the implications of the parameters being used are often not appreciated by the oncology community. This is especially true when applied to patients with high-grade glioma, where the lesion is highly heterogeneous and changes in diffusion parameters are due to a combination of treatment effects, edema and tumor infiltration. Although advanced diffusion models that aim to distinguish between different types of tissue have the potential for providing information that is complementary to conventional MR imaging, their application has been very limited due to their relatively long acquisition time.;These challenges have become the motivation for this thesis. We first explored the value of standard diffusion imaging methods in characterizing tumor response to therapy. By applying different ways of evaluating changes in the apparent diffusion coefficient (ADC) and examining their association with patient outcomes in clinical trials, we hoped to gain a better understanding of the physiological process behind the patterns of changes that occur, and improve the interpretation of the data obtained. The next step was to bridge the gap between advanced diffusion models and their clinical applications by using fast diffusion imaging techniques. This was achieved by optimizing the protocol for acquiring multiband diffusion data at 7T and the post-processing pipeline for such data. The quality of the 7T multiband data was evaluated qualitatively and quantitatively in comparison with data obtained at 3T. The acquisition of multiband two shell diffusion data allowed us to apply neurite orientation dispersion and density imaging (NODDI) to patients with glioma and to evaluate its performance in distinguishing between different types of tissue.;The results of this dissertation suggest that diffusion imaging plays an important role in assessing gliomas. These are very important steps towards improving the assessment of residual disease and distinguishing between tumor and treatment effects for patients with brain tumors.
机译：扩散MRI是一种能够提供对细胞和亚细胞长度尺度上的分子位移运动敏感的独特对比度的技术。通过使MR信号在微观水平（约5-20μm）对水分子质子的随机运动敏感，它能够探测大脑中的组织微结构，例如轴突，树突，神经胶质细胞和细胞外空间，以可能为肿瘤生理学提供有价值的见识的方式；对于脑肿瘤患者，通常将扩散成像作为MR方案的一部分。但是，肿瘤学界通常不理解所使用参数的含义。当将其用于病变高度异质且扩散参数的变化是由于治疗效果，水肿和肿瘤浸润的综合作用时，尤其适用于患有高度神经胶质瘤的患者。尽管旨在区分不同类型组织的先进扩散模型具有提供与常规MR成像相辅相成的信息的潜力，但由于其获取时间相对较长，其应用受到了很大限制。这些挑战已成为实现这一目标的动力。论文。我们首先探讨了标准扩散成像方法在表征肿瘤对治疗反应中的价值。通过在临床试验中采用不同的方法评估表观扩散系数（ADC）的变化并检查其与患者预后的关系，我们希望能更好地了解发生变化的模式背后的生理过程，并改善对获得的数据。下一步是通过使用快速扩散成像技术弥合先进扩散模型与其临床应用之间的鸿沟。这是通过优化用于在7T处获取多频带扩散数据的协议以及此类数据的后处理管道来实现的。与在3T获得的数据相比，对7T多频带数据的质量进行了定性和定量评估。多频带两层壳扩散数据的采集使我们能够对神经胶质瘤患者应用神经突取向弥散和密度成像（NODDI），并评估其在区分不同类型的组织中的性能。在评估神经胶质瘤中起重要作用。这些是改善残留疾病评估以及区分脑肿瘤患者的肿瘤和治疗效果的非常重要的步骤。

著录项

  • 作者

    Wen, Qiuting.;

  • 作者单位

    University of California, San Francisco.;

  • 授予单位 University of California, San Francisco.;
  • 学科 Medical imaging.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 177 p.
  • 总页数 177
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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