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：
7372602
负责人：
PAUL M THOMPSON
金额：
$ 34.65万
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/7372602
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）：这是对一个为期10年项目的竞争性续签，该项目提供了对阿尔茨海默氏病（AD）的巨大见解，这种疾病仅在美国就花费了1,130亿美元/年，没有已知的治疗方法。该项目开发了AD的多维计算地图集。我们的5年工作计划为在症状开始前几年提供了最强大的计算工具，以跟踪活体大脑中的广告出现和传播。我们将在ATLAS坐标框架中对AD的3个观点 - 串行MRI，新型宠物示踪剂和3D病理学相关联。这将为科学家提供有史以来最敏感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），以及如何有效治疗减慢过渡到AD的过渡。首先，我们使用新的串行MRI分析来绘制AD的解剖轨迹（AIMS 1,2）。我们检测大脑变化的工具（皮质厚度映射，基于张量的形态计量学）提供了在活大脑中疾病扩散的首次延时地图。在这里，我们将其应用于MCI受试者（在任何给定年份中转化为AD的风险更高），以确定即将发作的最佳预测指标，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来大大提高药物试验，他们可以在不可逆转的损害设定之前受益。接下来，我们将使用新型的PET示踪剂分子来重建AD病理学的动态序列，因为它在活体大脑中累积并扩散（AIM 3）。我们新发达的宠物（正电子发射断层扫描）示踪剂化合物，[18F] -fddnp被誉为突破，可视化淀粉样蛋白斑块和神经纤维纤维缠结（NFTS） - AD的标志以前仅在自动化时检测到AD。我们基于敏感的基于表面的3D分析技术将绘制衰老，轻度认知障碍和AD的牙菌斑和缠结堆积的时空轨迹，并比较组，以识别大脑变化，以预测即将到来的认知恶化或过渡到AD；我们将将这些信号与萎缩率和皮质变性的MRI指标进行比较并将其相关联，以产生联合MR-PET疾病负担的措施。我们将开拓3D冷冻成像（以3个受试者为单位），以确定3D在整个大脑中如何重建缠结密度和βAmybood分布的地图与活着患者的成像指标相关。该基础数据将是广告群体的资源，揭示了成像信号的细胞相关性，其生理含义知之甚少。我们将绘制个人和人群，揭示皮质稀疏，牙菌斑和纠缠病理的群体模式，以预测结果。确定即将衰落和疾病发作的预测因素，我们的地图集将确定具有早期药物治疗的新兴病理病理学的候选者，并将存储统计数据，以量化治疗方法在有风险的人中的抵抗程度。我们将与我们的100多个协作实验室共享所有图像，协议和算法。