Controlling Quality and Capturing Uncertainty in Advanced Diffusion Weighted MRI

控制质量并捕捉高级扩散加权 MRI 的不确定性

• 批准号: 9146951
• 负责人: Bennett A. Landman
• 金额: $ 64.82万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-21 至 2019-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9146951
• 关键词: 3-Dimensional; Age; Area; Biological; Biological Markers; Brain; Clinical Research; Collaborations; Communities; Complex; Consensus; Contrast Sensitivity; Data; Data Analyses; Data Quality; Databases; Diagnosis; Diffusion; Diffusion Magnetic Resonance Imaging; Early Diagnosis; Educational workshop; Ensure; Environment; Failure; Fiber; Foundations; Future; Gender; Goals; Health; Image; Image Analysis; Imaging Techniques; Individual; Lead; Literature; Maps; Measures; Medicine; Methods; Modeling; Monitor; Morphologic artifacts; Motion; Neurosciences; Noise; Patient Care; Patients; Performance; Plague; Population Heterogeneity; Procedures; Process; Prognostic Marker; Protocols documentation; Quality Control; Reproducibility; Research; Research Personnel; Resolution; Role; Sampling; Scanning; Sensitivity and Specificity; Series; Site; Solid; Structure; System; Taxonomy; Techniques; Testing; Time; Tissues; Uncertainty; Validation; Vendor; Visualization software; Work; base; biophysical model; clinically relevant; cohort; comparative; data acquisition; design; imaging modality; improved; in vivo; innovation; millimeter; prognostic; research study; simulation; statistics; tool; volunteer

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.

描述（由申请人提供）：扩散加权磁共振成像（DW-MRI）为同时研究局部微体系结构和全局结构连通性提供了前所未有的机会。然而，在弥散张量成像 (DTI) 首次出现近二十年后，DW-MRI 在复杂组织区域（例如交叉纤维）的解释方面仍然受到基本理论挑战的困扰。使用先进的 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。尽管已经提出了许多潜在的采集和分析技术，但迄今为止，还没有对先进技术的采集设计和质量的影响进行系统的描述。 这项工作的动机假设是，考虑到实际图像采集的考虑（例如，可行的扫描时间、硬件、患者运动的倾向），不同的先进 DW-MRI 方法适用于不同的成像环境。考虑涉及先进 DW-MRI 的研究的研究人员面临着两个关键问题：（1）“可能的预期性能（特异性/敏感性）是什么？ ”和（2）“在特定的 DW-MRI 分析场景下，如何优化成像场景以达到目标性能水平？”该项目的总体目标是解决这些长期存在的重要问题。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模型研究，以绘制成像场景的经验敏感性和特异性。 先进的 DW-MRI 指标。这项研究将生成已知物理纤维结构的扫描-再扫描数据。 “其次，我们将进行迄今为止最广泛的扫描-重新扫描研究，以绘制先进的 DW-MRI 指标的体内可重复性。这项研究将在所有三个主要扫描供应商中生成扫描-重新扫描数据，其中包括按年龄和性别分层的神经系统正常对照志愿者。”第三，我们将与正在进行的临床研究合作，生成一个包含扫描-重新扫描验证数据的大型数据库。这项研究将能够绘制正常的受试者间方差图，构建先进的 DW-MRI 测量的规范数据库，并实现单受试者推理。 总之，这些努力将 (1) 在噪声和采样策略的背景下，为源自先进 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 基于先进的 DW-MRI 探索生物标志物，并最终改善患者护理。