Joint Estimate Diffusion Imaging (JEDI) for improved Tissue Characterization and Neural Connectivity in Aging and Alzheimer's Disease

联合估计扩散成像 (JEDI) 可改善衰老和阿尔茨海默病的组织表征和神经连接

• 批准号: 10662911
• 负责人: Mark W Bondi
• 金额: $ 141.58万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2028-02-29
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10662911
• 关键词: Activities of Daily Living; Aging; Alzheimer disease detection; Alzheimer' s Disease; Alzheimer' s disease pathology; Alzheimer' s disease related dementia; Alzheimer' s disease risk; Anisotropy; Architecture; Arizona; Autopsy; Brain; Brain imaging; Clinical; Cognitive; Complex; Computational Technique; Computer Simulation; Data; Dementia; Detection; Diffusion; Diffusion Magnetic Resonance Imaging; Dimensions; Entropy; Ferrets; Fiber; Geometry; Goals; Heterogeneity; Histologic; Human; Hybrids; Image; Imaging Techniques; Impaired cognition; Joints; Magnetic Resonance Imaging; Maps; Measures; Methodology; Methods; Microscopic; Morphologic artifacts; Motion; Multimodal Imaging; Nerve Degeneration; Neurofibrillary Tangles; Participant; Pathologic; Pathology; Patients; Performance; Physiologic pulse; Process; Protocols documentation; Proxy; Radiology Specialty; Reporting; Research; Resolution; Scanning; Sensitivity and Specificity; Signal Transduction; Source; Specificity; Structural defect; Structure; Techniques; Testing; Time; Tissue Model; Tissues; Translating; Translations; Universities; Validation; Water; Work; abeta deposition; brain tissue; clinical imaging; cognitive ability; cohort; diffusion anisotropy; economic implication; experimental study; gray matter; human subject; human tissue; imaging modality; improved; in vivo; in vivo evaluation; insight; mild cognitive impairment; neural; neural tract; new technology; normal aging; novel; simulation; simulation environment; social implication; tool; white matter; white matter change

Alzheimer's Disease (AD) and related dementias (ADRD) are characterized by progressive structural changes of brain tissue that results in a debilitating loss of cognitive and functional abilities and has profound social and economic implications. While hallmark AD pathology (e.g. beta amyloid depositions and neurofibrillary tangles) are remarkably pronounced at the cellular level, there are currently no successful non- invasive brain imaging techniques to report these microstructural changes. Diffusion magnetic resonance imaging (dMRI) is a widely available non-invasive clinical imaging method with this potential, as it is sensitive to the subtle motion of water within the complex brain gray matter (GM) and white matter (WM) tissue architecture. In principle, dMRI can report both the local tissue structure and the long range connectivity of neural tracts in order to identify pathology and determine the effects of AD on functional brain networks. Unfortunately, the clinical utility of the standard dMRI methodology is severely compromised by its lack of specificity to microstructural tissue changes below the image resolution. Recently, however, we have developed a novel acquisition and analysis method called Joint Estimation Diffusion Imaging (JEDI) that is highly sensitive to microstructural features of GM and GM/WM border regions, and also provides improved connectivity maps from WM. JEDI is easily implemented on a clinical scanner and we have recently incorporated it into a first study on subjects ranging from cognitively normal (CN) to Mild Cognitive Impairment (MCI) to early AD in order to assess its ability to detect changes in these groups. Two critical steps in extending the clinical utility of JEDI in AD are: 1) To characterize the relationship between the JEDI data and specific tissue microstructural features in order to develop quantitative clinical metrics and 2) To develop efficient acquisition protocols for both microstructural sensitivity and limited patient scan time. That is the focus of this proposal, which will involve three lines of work: 1) Numerical computer simulations of the JEDI experiment in realistic tissue models that will allow us to efficiently optimize the acquisition protocol for maximum specificity and minimal time; 2) Validate these optimizations through in-vivo evaluation of normal aging processes in the ferret and in ex-vivo radiologic-pathologic analysis in post-mortem human tissue from patients with different stages of AD; 3) Incorporate these optimizations into the JEDI acquisition and analysis of human protocols on our clinical scanners with specific application to examining the prodromal microstructure tissue changes across the aging-MCI-AD continuum. By enabling a reliable, validated and clinically viable method for the quantitative characterization of subtle brain tissue changes across the aging-MCI-AD continuum, JEDI will significantly enhance our ability to understand the earliest neurodegenerative features of AD and provide new insights into its causes, consequences, and possible treatment targets.

阿尔茨海默病 (AD) 和相关痴呆 (ADRD) 的特点是进行性结构性痴呆 脑组织的变化导致认知和功能能力的衰弱性丧失，并具有深远的影响 社会和经济影响。 神经原纤维缠结）在细胞水平上非常明显，目前还没有成功的非 侵入性脑成像技术可以报告这些微观结构的变化。 扩散磁共振成像（dMRI）是一种广泛使用的非侵入性临床成像方法 具有这种潜力，因为它对复杂的大脑灰质（GM）内水的微妙运动敏感，并且 白质 (WM) 组织结构 原则上，dMRI 可以报告局部组织结构和长组织结构。 神经束的范围连接，以识别病理并确定 AD 对功能的影响 不幸的是，标准 dMRI 方法的临床实用性受到严重影响。 它缺乏对微观结构组织变化的特异性，低于图像分辨率。 然而，最近我们开发了一种新颖的采集和分析方法，称为联合估计 扩散成像 (JEDI) 对 GM 和 GM/WM 边界区域的微观结构特征高度敏感， 还提供了 WM 的改进连接图，可轻松在临床扫描仪上实施 我们最近将其纳入第一项研究中，研究对象范围从认知正常 (CN) 到轻度 认知障碍（MCI）到早期AD，以评估其检测这些群体变化的能力。 扩展 JEDI 在 AD 中的临床效用的两个关键步骤是：1) 描述两者之间的关系 JEDI 数据和特定组织微观结构特征之间的关系，以便开发定量临床 指标和 2) 开发针对微观结构敏感性和有限患者的有效采集协议 这是本提案的重点，涉及三方面的工作：1）数值计算机。 在真实的组织模型中模拟 JEDI 实验，这将使我们能够有效地优化 最大特异性和最短时间的采集协议；2) 通过体内验证这些优化 雪貂正常衰老过程的评估和死后离体放射病理学分析 来自不同阶段 AD 患者的人体组织；3) 将这些优化纳入 JEDI 在我们的临床扫描仪上采集和分析人体协议，特别适用于检查 前驱微结构组织在衰老-MCI-AD 连续体中发生变化。 通过提供可靠、经​​过验证且临床可行的方法来定量表征微妙的 脑组织在衰老-MCI-AD 连续体中发生变化，JEDI 将显着增强我们的能力 AD 最早的神经退行性特征并为其病因提供新的见解， 后果和可能的治疗目标。