Image based modeling of biomechanical factors for risk assessment of developing periventricular white matter hyperintensities

基于图像的生物力学因素建模，用于评估发生脑室周围白质高信号的风险

• 批准号: 10218918
• 负责人: YUNJIE TONG
• 金额: $ 42.33万
• 依托单位: PURDUE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-15 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10218918
• 关键词: 3-Dimensional; Age; Alzheimer' s disease patient; Alzheimer' s disease risk; Anatomy; Anterior; Area; Automobile Driving; Biomechanics; Biophysics; Blood Vessels; Brain; Cardiac; Cerebrospinal Fluid; Cognitive; Computer Models; Computing Methodologies; Coupled; Data; Dementia; Demyelinations; Development; Diffuse; Diffusion; Diffusion Magnetic Resonance Imaging; Elasticity; Elderly; Fiber; Geometry; Goals; Horns; Hypertension; Image; Impaired cognition; Knowledge; Lateral; Lead; Lesion; Location; Magnetic Resonance Imaging; Measurement; Measures; Methods; Microvascular Dysfunction; Modeling; Motion; Outcome; Pathologic; Periodicity; Physiologic pulse; Population; Prevalence; Property; Pulse Pressure; Risk Assessment; Risk Factors; Role; Speed; Stress; Structure; Tissues; Variant; Ventricular; White Matter Hyperintensity; base; biomechanical model; brain tissue; cerebrospinal fluid flow; foramen magnum; improved; intracranial artery; lateral ventricle; mechanical properties; mild cognitive impairment; neuroinflammation; novel; pressure; tool; ventricular system; white matter; white matter change

Image based modeling of biomechanical factors for risk assessment of developing periventricular white matter hyperintensities White matter lesions, visible as white matter hyperintensities (WMH) on T2-weighted MR images, have been shown to have a close association with cognitive impairment and dementia. Commonly found in periventricular brain areas and subcortical white matter, WMH are prevalent in the elderly population (age > 60). They are particularly prevalent in mild cognitive impairment and Alzheimer's disease patients. Multiple pathological changes have been found in WMH, including demyelination and loss of WM fibers. Moreover, WMH has been closely associated with vascular deficits, commonly called “small vessel disease”. Despite the prevalence and potential significance of WMH in cognitive declines, there is little to no in-depth knowledge regarding the underlying causes and biophysical vulnerability of the periventricular brain tissue. Our ultimate goal is to understand the role of various biomechanical factors in formation of WMH in order to predict or intervene in the WMH progression. The objective of this proposal is to determine the effect of biomechanical forces (acting on the lateral ventricular wall due to cardiac pulse) on the adjacent white matter microstructure and formation of periventricular WMH, by using novel MRI methods and image-based computational modeling. In this project, we will develop a computational modeling framework based on 3D brain anatomy obtained with structural MR images, ventricular boundary changes obtained with high-speed MR measurements and mechanical properties of the tissues. The image-based modeling will compute the stress variations in the brain, especially at periventricular white matter. The locations with high stresses will be correlated with the regions of WMHs, microstructural damages and cognitive measures. Understanding the contribution of biomechanical factors to WMH will allow us to improve characterization of WMH, reveal additional contributing factors (e.g., hypertension), and predict cognitive outcomes. In order to determine the role of biomechanical factors in WMH, we propose the following specific aims: Aims proposed:  Specific Aim 1: Develop an MRI-based modeling methodology for computing subject-specific stress distribution in the periventricular brain tissue due to cardiac pressure pulse.  Specific Aim 2: Determine the impact of pulsatile pressure on the formation of periventricular WMH.

基于图像的生物力学因素建模用于发展脑室周围白色的风险评估 白质高信号 在T2加权MR图像上可见为白色高信号（WMH）的白色病变已被 与认知障碍和痴呆症密切相关。常见于脑室周围 脑区和皮质下白色物质，WMH在老年人群中普遍存在（年龄> 60）。他们是 在轻度认知障碍和阿尔茨海默病患者中尤其普遍。多种病理学 在WMH中发现了包括脱髓鞘和WM纤维丢失的变化。此外，WMH一直 与血管缺陷密切相关，通常称为“小血管疾病”。尽管流行， WMH在认知能力下降中的潜在意义，关于WMH在认知能力下降中的作用， 潜在的原因和生物物理脆弱性的脑室周围脑组织。我们的最终目标是 了解各种生物力学因素在WMH形成中的作用，以预测或干预WMH的形成。 WMH进展。本提案的目的是确定生物力学力（作用于 侧脑室壁由于心脏搏动）对邻近白色物质的显微结构和形成 室周WMH，通过使用新的MRI方法和基于图像的计算建模。 在这个项目中，我们将开发一个基于3D大脑解剖结构的计算建模框架， 结构MR图像，通过高速MR测量获得的心室边界变化， 组织的机械性能。基于图像的建模将计算大脑中的压力变化， 特别是在脑室周围的白色物质。具有高应力的位置将与 微结构损伤和认知测量。理解生物力学的贡献 WMH的因素将允许我们改进WMH的表征，揭示另外的贡献因素（例如， 高血压），并预测认知结果。为了确定生物力学因素在WMH中的作用， 我们提出以下具体目标： 拟议目标： 具体目标1：开发一种基于MRI的建模方法，用于计算受试者特定的压力 分布在脑室周围脑组织由于心脏压力脉冲。 具体目标2：确定脉动压对室周WMH形成的影响。

项目成果

Neurofluid coupling during sleep and wake states.

睡眠和清醒状态下的神经流体耦合。

• DOI: 10.1016/j.sleep.2023.07.021
• 发表时间: 2023
• 期刊: Sleep medicine
• 影响因子: 4.8
• 作者: VijayakrishnanNair,Vidhya;Kish,BriannaR;Chong,PearlynneLh;Yang,Ho-ChingShawn;Wu,Yu-Chien;Tong,Yunjie;Schwichtenberg,AJ
• 通讯作者: Schwichtenberg,AJ