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

阿尔茨海默病(AD)和相关痴呆(ADRD)的特点是进行性结构性 脑组织的改变，导致认知和功能能力的衰弱丧失，并具有深远的 对社会和经济的影响。而标志性AD病理(如β淀粉样蛋白沉积和 神经fi视网膜缠结)在细胞水平上非常显著，目前没有成功的非 侵入性脑成像技术来报告这些微结构的变化。 弥散磁共振成像(Dmri)是一种广泛应用的非侵入性临床成像方法。 由于它对复杂的大脑灰质(GM)内水的微妙运动很敏感，因此具有这种潜力 白质(WM)组织结构。原则上，dmri既可以报告局部组织结构，也可以报告局部组织结构。 神经束的距离连通性，以确定病理和确定AD对功能的影响 大脑网络。不幸的是，标准dmri方法的临床应用受到以下因素的严重影响 其缺乏特殊的fi城，使微结构组织的变化低于图像分辨率。 然而，最近我们开发了一种新的采集和分析方法，称为联合估计 对GM和GM/WM边界区域的微观结构特征高度敏感的扩散成像(JEDI)， 还提供了来自WM的改进的连接性地图。绝地武士很容易在临床扫描仪上实现 我们最近将它纳入了一项fiFirst研究，研究对象从认知正常(CN)到轻度 认知损害(MCI)到早期AD，以评估其检测这些群体的变化的能力。 扩展绝地在AD中的临床应用的两个关键步骤是：1)描述两者之间的关系 绝地武士数据和特殊fic组织微结构特征之间的关系，以开发定量的临床 指标和2)为显微结构敏感性和受限患者开发有效的fi采集方案 扫描时间。这就是这项提案的重点，它将涉及三个方面的工作：1)数字计算机 在真实的组织模型中模拟绝地实验，将使我们能够利用fi科学地优化 最大规格fi城市和最小时间的采集协议；2)通过体内验证这些优化 评价雪貂的正常衰老过程和身体的体外放射病理学分析 来自AD不同阶段患者的人体组织；3)将这些优化融入绝地武士 使用SPECIfic语言在临床扫描仪上获取和分析人类协议以检查 在衰老-MCI-AD连续体中，前驱体微结构组织发生变化。 通过实现一种可靠的、经过验证的和临床上可行的方法来定量描述微妙的 脑组织的变化在衰老-脑梗塞-AD的连续体中，绝地武士将显著增强我们的fi能力 了解阿尔茨海默病最早的神经退行性改变特征，并对其原因提供新的见解， 后果，以及可能的治疗目标。

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.