Controlling Quality and Capturing Uncertainty in Advanced Diffusion Weighted MRI

描述（由申请人提供）：弥散加权磁共振成像（DW-MRI）为同时研究局部微结构和全局结构连接性提供了前所未有的机会。然而，在弥散张量成像（DTI）最初出现近二十年后，DW-MRI仍然受到其在复杂组织区域（例如，交叉纤维）。用先进的DW-MRI方法了解这些复杂区域对于定量评估大脑结构组织、诊断连接异常和开发有用的生物标志物至关重要。虽然已经提出了许多潜在的采集和分析技术，但迄今为止，还没有系统地描述采集设计和质量对各种先进技术的影响。 这项工作的动机假设是，不同的先进DW-MRI方法适用于不同的成像背景，给出了实际的图像采集考虑（例如，可行的扫描时间、硬件、患者运动的倾向）。研究人员考虑研究涉及先进的DW-MRI面临着两个关键问题：（1）“什么是预期的性能（特异性/灵敏度）的可能 高级DW-MRI分析给出了一个特定的成像场景？和（2）“如何优化成像方案，以达到特定DW-MRI分析方案的目标性能水平？”“这个项目的总体目标是解决这些重要的长期存在的问题。我们将通过一系列三个实验来评估激励假设：“首先，我们将进行迄今为止最广泛的体模研究，以绘制先进DW-MRI指标的经验灵敏度和特异性。这项研究将产生已知的物理纤维结构的扫描重扫描数据。“其次，我们将进行迄今为止最广泛的扫描再扫描研究，以绘制先进DW-MRI指标的体内再现性。本研究将生成所有三家主要扫描供应商的扫描-再扫描数据，神经学正常对照志愿者按年龄和性别分层。“第三，我们将与正在进行的临床研究合作，以生成一个大型的扫描-再扫描验证数据数据库。本研究将能够绘制正常受试者间方差，构建高级DW-MRI测量的规范性数据库，并能够进行单受试者推断。 总之，这些努力将（1）在噪声和采样策略的背景下，为来自高级DW-MRI的生物标志物的生物物理解释提供定量基础，（2）为扫描时间和硬件限制内的协议优化提供坚实的理论和经验基础。数据、分析软件和可视化工具将免费提供，以促进持续改进和创新。这些努力将推动量化 探索基于先进DW-MRI的生物标志物，并最终改善患者护理。

DESCRIPTION (provided by applicant): Diffusion weighted magnetic resonance imaging (DW-MRI) has opened unprecedented opportunities to simultaneously study local microarchitecture and global structural connectivity. Yet, nearly two decades after the initial presentation of diffusion tensor imaging (DTI), DW-MRI remains plagued by basic theoretical challenges to its interpretation in regions of complex tissues (e.g., crossing fibers). Understanding these complex regions with advanced DW-MRI methods is critical to quantitative assessment of the brain architectural organization, diagnosing connectivity abnormalities, and developing useful biomarkers. Although numerous potential acquisition and analysis techniques have been proposed, to date, there has not been a systematic characterization of the impacts of acquisition design and quality across advanced techniques. The motivating hypothesis of this work is that different advanced DW-MRI methods are appropriate for different imaging contexts given practical image acquisition considerations (e.g., feasible scan time, hardware, propensity for patient motion). Investigators considering studies involving advanced DW-MRI are faced with two critical questions: (1) "What is the expected performance (specificity/sensitivity) of possible advanced DW-MRI analyses given a particular imaging scenario?" and (2) "How can an imaging scenario be optimized to achieve target level of performance given a particular DW-MRI analysis scenario?" The overall goal of this project is resolve these important long-standing questions. We will evaluate the motivating hypothesis through a series of three experiments: " First, we will perform the most extensive phantom study to date to map the empirical sensitivity and specificity of advanced DW-MRI metrics. This study will generate scan-rescan data of known physical fiber structures. " Second, we will perform the most extensive scan-rescan study to date to map the in vivo reproducibility of advanced DW-MRI metrics. This study will generate scan-rescan data across all three major scan vendors with neurologically normal control volunteers who are age and gender stratified. " Third, we will collaborate with on-going clinical research studies to generate a large database of scan-rescan validation data. This study will enable mapping of normal inter-subject variance, lead to the construction of a normative database of advanced DW-MRI measures, and enable single-subject inference. Together, these efforts will (1) provide a quantitative basis for biophysical interpretation of biomarkers derived from advanced DW-MRI in the context of noise and sampling strategies and (2) provide a solid theoretical and empirical basis for optimization of protocols within scan-time and hardware constraints. The data, analysis software, and visualization tools will be made freely available to facilitate continued improvement and innovation. These efforts will drive quantitative exploration for biomarkers based on advanced DW-MRI and, eventually, improve patient care.