A Multidimensional Alzheimer's Disease Brain Atlas

多维阿尔茨海默病大脑图谱

基本信息

批准号：
7493972
负责人：
PAUL M THOMPSON
金额：
$ 34.49万
依托单位：
UNIVERSITY OF CALIFORNIA LOS ANGELES
依托单位国家：
美国
项目类别：
财政年份：
2007
资助国家：
美国
起止时间：
2007-09-05 至 2011-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7493972
关键词：
Address Affect Age Aging Algorithms Alzheimer&apos s Disease Amyloid Amyloid beta-Protein Anatomy Anterior Apolipoprotein E Appendix Area Atlases Atrophic Automation Autopsy Back Biochemistry Biological Markers Brain Brain Diseases Brain Mapping Brain imaging Brain scan Build-it Cerebrum Cessation of life Class Clinical Clinical Engineering Clinical assessments Cognition Cognitive Collaborations Communities Complement Computational Biology Computational Technique Computer software Cost of Illness Cryoultramicrotomy Data Data Set Databases Dementia Deterioration Development Differential Diagnosis Direct Costs Disasters Disease Disease Progression Early treatment Elderly Employee Engineering Experimental Designs Foundations Frequencies Frontotemporal Dementia Functional Magnetic Resonance Imaging Funding Future Genetic Risk Genetic Status Grant Growth Head Health Histologic Histology Histopathology Housing Human Image Image Analysis Impaired cognition Individual Influentials Informatics Information Theory International Joints Journals Label Laboratories Language Lateral Life Link Liquid substance Magnetic Resonance Imaging Maps Mathematics Measurable Measures Mechanics Medial Medical Imaging Memory Meta-Analysis Methods Modality Molecular Monitor Multimodal Imaging Neurofibrillary Tangles Neurosciences Onset of illness Outcome Paper Parietal Lobe Pathologic Pathology Patients Pattern Peer Review Perfusion Pharmaceutical Preparations Physiological Population Positron-Emission Tomography Process Protocols documentation Psyche structure Public Health Publications Publishing Rate Research Research Infrastructure Research Personnel Resolution Resources Risk Risk Factors Scanning Scientist Score Senile Plaques Signal Transduction Site Source Specimen Staging Staging System Standards of Weights and Measures Structure Supercomputing Surface Symptoms System Techniques Technology Temporal Lobe Testing Therapy Clinical Trials Thick Time Tracer Ursidae Family Work age effect aged base brain research burden of illness cerebral atrophy computerized data processing computerized tools density digital driving force executive function frontal lobe glucose metabolism human very old age (85+)image processing improved in vivo innovation insight interest longitudinal positron emission tomography mathematical algorithm mild neurocognitive impairment morphometry neuroimaging neuropathology neuropsychological normal aging novel novel strategies programs size skills socioeconomics statistics success tool tool development

项目摘要

DESCRIPTION (provided by applicant): This is a competitive renewal of a 10-year project that has provided enormous insight into Alzheimer's Disease (AD), a disease that costs $113 billion/yr in the U.S. alone, with no known cure. The project develops a multidimensional, computational atlas of AD. Our 5-year plan of work provides the most powerful computational tools to track AD emerging and spreading in the living brain - years before symptoms begin. We will correlate 3 perspectives on AD in an atlas coordinate framework - serial MRI, novel PET tracers, and 3D pathology. This will provide scientists will the most sensitive approach ever created to gauge which factors affect disease progression (drug treatment, genetic risk, etc.), and how effectively treatments slow the transition to AD. First, we chart the anatomic trajectory of AD with novel analyses of serial MRI (Aims 1,2). Our tools to detect brain changes (cortical thickness mapping, tensor-based morphometry) provided the first time-lapse maps of the disease spreading in the living brain. Here we apply them to MCI subjects (who are at five-fold higher risk of converting to AD in any given year) to identify the best predictors of imminent disease onset, and to predict changes in specific cognitive domains. This will greatly advance drug trials by better identifying candidates for early treatment, who can benefit most before irreversible damage sets in. Next, we will use novel PET tracer molecules to reconstruct the dynamic sequence of AD pathology as it builds up and spreads in the living brain (Aim 3). Hailed as a breakthrough in the AD community, our newly-developed PET (positron emission tomography) tracer compound, [18F]-FDDNP, visualizes amyloid plaques and neurofibrillary tangles (NFTs) - hallmarks of AD previously only detectable at autopsy. Our sensitive surface-based 3D analytic techniques will map the spatio-temporal trajectory of plaque and tangle build-up in aging, mild cognitive impairment, and AD, comparing groups to identify brain changes that predict imminent cognitive deterioration or transition to AD; we will compare and correlate these signals with MRI measures of atrophic rates and cortical degeneration to create joint MR-PET measures of disease burden. We will pioneer 3D cryosection imaging (in 3 subjects/year) to establish how 3D reconstructed maps of tangle density and betaamyloid distribution throughout the brain correlate with imaging measures from living patients. This groundtruth data will be a resource to the AD community, revealing the cellular correlates of imaging signals whose physiological meaning is poorly understood. We will map individuals and populations, revealing group patterns of cortical thinning and plaque and tangle pathology that predict outcomes. Identifying predictors of imminent decline and disease onset, our atlas will identify candidates with emerging pathology for early drug treatment, and will store statistical data to quantify how well treatments resist AD in those at risk. We will share all images, protocols, and algorithms with our 100+ collaborating laboratories.

描述（由申请人提供）：这是一个为期 10 年的项目的竞争性更新，该项目为阿尔茨海默病 (AD) 提供了深入的见解，这种疾病仅在美国每年就花费 1,130 亿美元，而且尚无已知的治愈方法。该项目开发了一个多维的 AD 计算图集。我们的 5 年工作计划提供了最强大的计算工具来追踪 AD 在活体大脑中的出现和传播——在症状出现之前的几年。我们将在图谱坐标框架中关联 AD 的 3 个视角 - 连续 MRI、新型 PET 示踪剂和 3D 病理学。这将为科学家们提供有史以来最灵敏的方法来衡量哪些因素影响疾病进展（药物治疗、遗传风险等），以及治疗如何有效地减缓 AD 的转变。首先，我们通过连续 MRI 的新颖分析绘制了 AD 的解剖轨迹（目标 1,2）。我们检测大脑变化的工具（皮质厚度测绘、基于张量的形态测量）提供了疾病在活体大脑中传播的第一个延时图。在这里，我们将它们应用于 MCI 受试者（在任何一年内转化为 AD 的风险高出五倍），以确定即将发生疾病的最佳预测因素，并预测特定认知领域的变化。这将通过更好地识别早期治疗的候选者，从而极大地推进药物试验，这些候选者可以在不可逆转的损害发生之前受益最大。下一步，我们将使用新型 PET 示踪分子来重建 AD 病理在生物体中形成和传播的动态序列。大脑（目标 3）。我们新开发的 PET（正电子发射断层扫描）示踪剂化合物 [18F]-FDDNP 被誉为 AD 领域的一项突破，可显示淀粉样斑块和神经原纤维缠结 (NFT)，而这些是 AD 的标志，以前只能在尸检中检测到。我们敏感的基于表面的 3D 分析技术将绘制衰老、轻度认知障碍和 AD 中斑块和缠结形成的时空轨迹，比较各组以确定预测即将发生的认知恶化或转变为 AD 的大脑变化；我们将把这些信号与萎缩率和皮质变性的 MRI 测量值进行比较和关联，以创建疾病负担的联合 MR-PET 测量值。我们将开创 3D 冷冻切片成像（每年 3 名受试者），以确定整个大脑中缠结密度和 β 淀粉样蛋白分布的 3D 重建图如何与活体患者的成像测量相关联。这些真实数据将成为 AD 界的资源，揭示成像信号的细胞相关性，而这些信号的生理意义尚不清楚。我们将绘制个体和人群图，揭示预测结果的皮质变薄、斑块和缠结病理的群体模式。通过识别即将发生的衰退和疾病发作的预测因素，我们的图谱将识别具有新兴病理学的候选者进行早期药物治疗，并将存储统计数据以量化治疗对高危人群抵抗 AD 的效果。我们将与 100 多个合作实验室共享所有图像、协议和算法。