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）及相关痴呆（ADRD）以进行性结构痴呆为特征