Advancing MR elastography to map mechanical signatures of key AD/ADRD processes

推进 MR 弹性成像以绘制关键 AD/ADRD 过程的机械特征

• 批准号: 10585119
• 负责人: Matthew Christopher Murphy
• 金额: $ 44.2万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-01 至 2027-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10585119
• 关键词: Affect; Aging; Alzheimer' s Disease; Alzheimer' s disease related dementia; Alzheimer’s disease biomarker; Amyloid; Amyloid deposition; Anatomy; Anisotropy; Atrophic; Biological; Biological Markers; Biomechanics; Brain; Buffers; Chemicals; Clinic; Clinical Trials; Cognition; Cognitive; Country; Coupled; Data; Data Discovery; Data Set; Dementia; Development; Diffusion Magnetic Resonance Imaging; Disease; Environment; Face; Functional disorder; Future; Goals; Health; Impaired cognition; Individual; Inflammatory Response; Knowledge; Learning; Link; Machine Learning; Magnetic Resonance Elastography; Maps; Measurement; Measures; Mechanics; Microglia; Modality; Modeling; Nerve Degeneration; Neurophysiology - biologic function; Neuropsychological Tests; Noise; Pathologic; Pathology; Patient Recruitments; Performance; Persons; Physiological Processes; Play; Positioning Attribute; Positron-Emission Tomography; Predisposition; Process; Prognosis; Relaxation; Reporter; Reporting; Research; Resolution; Role; Sampling; Signal Transduction; Structure; Techniques; Technology; Testing; Therapeutic; Translating; United States; White Matter Hyperintensity; Work; burden of illness; cardiometabolism; cell motility; cognitive function; cognitive performance; demographics; design; elastography; experimental study; follow-up; imaging modality; improved; in vivo; insight; magnetic field; mechanical properties; resilience; simulation; structural determinants; success; tau Proteins; tau aggregation; tool; vector; white matter

1 PROJECT SUMMARY 2 Alzheimer’s disease (AD) is the leading cause of dementia in the United States and its impact is only growing with 3 shifting demographics. The development of powerful biomarkers, measuring amyloid deposition, tau accumulation, 4 and neurodegeneration, has provided important insights into the pathophysiology of AD and AD-related dementias 5 (ADRD). Nonetheless, given the large variability across individuals, our understanding of the link between pathology 6 and cognitive dysfunction remains incomplete. Structural factors contribute significantly to this pathology-cognition 7 disconnect and are termed as “brain reserve.” There is a critical need for objective measures of reserve that will 8 improve the assessment of individual prognosis and guide therapy. 9 Brain biomechanics are an understudied structural feature of the brain, due in large part to the difficulty in measuring 10 relevant biomechanical states in vivo. Magnetic resonance elastography (MRE) is currently unmatched for 11 noninvasive measurement of brain mechanical properties. We have previously demonstrated that brain stiffness is 12 reduced due to AD, and our group and others have demonstrated in multiple studies that brain stiffness is a significant 13 reporter of cognitive function. However, previous studies face important limitations, namely technologies that were 14 optimized for reliability over resolution, and incomplete pathological assessment. Therefore, we will investigate two 15 aims with the overall goals to (1) advance MRE technology in order to (2) evaluate of the role of biomechanics in 16 brain reserve. 17 In Aim 1, we will optimize our machine learning-based MRE inversion framework by incorporating new a priori 18 information into the model that is specific to the brain. These advances to the model include the incorporation of 19 partial volume effects to reduce atrophy-related bias, and mechanical anisotropy to accurately model the coherent 20 structure of white matter tracts. Each advance will be tested in simulation and phantom experiments, and finally in 21 vivo for its ability to boost sensitivity to key AD/ADRD processes. 22 In Aim 2, we will use these tools to simultaneously map the mechanical signature of 4 pathophysiological processes 23 including amyloid, tau, white matter hyperintensities, and cardiometabolic conditions. Using first a discovery data set, 24 we will extract the mechanical feature that best reports cognitive performance, both globally and in specific domains. 25 These MRE-based features will then be evaluated in an independent test set for their ability to predict concurrent and 26 future cognitive performance. Finally, we will assess the unique value of mechanical biomarkers to predict cognitive 27 performance, using a parallel analysis but controlling for existing biomarkers derived from anatomical, functional, and 28 diffusion MRI. 29 In sum, the success of this proposal will shed new light on alterations to brain biomechanics with respect to 30 AD/ADRD processes, and their role as a buffer between pathology and cognition.

1个项目摘要 2阿尔茨海默氏病（AD）是美国痴呆症的主要原因，其影响只会随之增长 3个人口统计学。强大的生物标志物的发展，测量淀粉样蛋白沉积，tau积累， 4和神经变性为AD和AD相关痴呆症的病理生理提供了重要的见解 5（Adrd）。但是，鉴于个人之间的差异很大，我们对病理之间的联系的理解 6并且认知功能障碍仍然不完整。结构因素对这种病理认知产生了重大贡献 7断开连接，被称为“大脑储备”。对储备的客观衡量标准的迫切需要 8改善对个体预后和指导疗法的评估。 9大脑生物力学是大脑的结构特征，这在很大程度上是由于难以测量的 体内10个相关的生物力学状态。磁共振弹性图（MRE）目前是无与伦比的 11大脑机械性能的无创测量。我们以前已经证明了大脑刚度 12减少了AD，我们的小组和其他人在多次研究中证明了大脑僵硬是重要的 13认知功能的记者。但是，以前的研究面临着重要的局限性，即 14针对解决方案的可靠性优化，病理评估不完整。因此，我们将调查两个 15的目标是（1）推进MRE技术的总体目标，以评估生物力学在 16大脑储备。 17在AIM 1中，我们将通过合并新的先验来优化基于机器学习的MRE反转框架 18在特定于大脑的模型中的信息。这些模型的这些进步包括 19部分体积效应，以减少萎缩相关偏差和机械各向异性，以准确对相干建模 20白质结构。每个进步将在模拟和幻影实验中进行测试，最后在 21 Vivo具有提高对关键AD/ADRD过程敏感性的能力。 22在AIM 2中，我们将使用这些工具同时绘制4个病理生理过程的机械签名 23在内，包括淀粉样蛋白，tau，白质超强度和心脏代谢状况。首先使用发现数据集， 24我们将提取最能报告全球和特定领域认知性能的机械特征。 25这些基于MRE的功能将在独立的测试集中评估，以预测并发和 26未来的认知表现。最后，我们将评估机械生物标志物的独特价值以预测认知 27性能，使用并行分析，但控制着源自解剖，功能和功能的现有生物标志物 28扩散MRI。 29总的来说，该提案的成功将为有关脑生物力学的改变而新的启示 30 AD/ADRD的过程及其在病理和认知之间的缓冲液作用。