A Multi-modal Imaging Model to Predict Mobility in Older Adults

预测老年人行动能力的多模态成像模型

• 批准号: 9805204
• 负责人: Victoria N Poole
• 金额: $ 12.54万
• 依托单位: HEBREW REHABILITATION CENTER FOR AGED
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2019-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9805204
• 关键词: Accounting; Address; Adult; Affect; Age; Aging; Alzheimer' s Disease; Attention; Biological Markers; Boston; Brain; Clinical; Cognition; Cognitive; Communities; Complex; Data; Data Science; Diffuse; Disease; Elderly; Functional Magnetic Resonance Imaging; Functional disorder; Future; Gait; Goals; Image; Impaired cognition; Impairment; Individual; Intervention; Investigation; K-Series Research Career Programs; Knowledge; Lasso; Magnetic Resonance Imaging; Measures; Memory; Methodology; Methods; Modality; Modeling; Motor; Multimodal Imaging; Nerve Degeneration; Neuraxis; Neurocognitive; Neurosciences; Outcome; Population; Predictive Value; Principal Component Analysis; Procedures; Process; Rehabilitation therapy; Research; Resources; Rest; Statistical Models; Structure; Testing; Training; Universities; Validation; Walking; Work; age related; aging population; base; clinical predictors; cohort; diffusion weighted; disability; early detection biomarkers; falls; functional disability; imaging modality; improved; improved mobility; improved outcome; mortality; multidisciplinary; multimodality; neural network; neuroimaging; neuromechanism; neuroregulation; phenotypic data; programs; recruit; relating to nervous system; secondary analysis; skills; study population; vector; walking speed; white matter damage; Accounting; Address; Adult; Affect; Age; Aging; Alzheimer' s Disease; Attention; Biological Markers; Boston; Brain; Clinical; Cognition; Cognitive; Communities; Complex; Data; Data Science; Diffuse; Disease; Elderly; Functional Magnetic Resonance Imaging; Functional disorder; Future; Gait; Goals; Image; Impaired cognition; Impairment; Individual; Intervention; Investigation; K-Series Research Career Programs; Knowledge; Lasso; Magnetic Resonance Imaging; Measures; Memory; Methodology; Methods; Modality; Modeling; Motor; Multimodal Imaging; Nerve Degeneration; Neuraxis; Neurocognitive; Neurosciences; Outcome; Population; Predictive Value; Principal Component Analysis; Procedures; Process; Rehabilitation therapy; Research; Resources; Rest; Statistical Models; Structure; Testing; Training; Universities; Validation; Walking; Work; age related; aging population; base; clinical predictors; cohort; diffusion weighted; disability; early detection biomarkers; falls; functional disability; imaging modality; improved; improved mobility; improved outcome; mortality; multidisciplinary; multimodality; neural network; neuroimaging; neuromechanism; neuroregulation; phenotypic data; programs; recruit; relating to nervous system; secondary analysis; skills; study population; vector; walking speed; white matter damage

Project Summary Although functional and structural MRI have been used to characterize aging, disease, and cognition, the central nervous system mechanisms underlying mobility impairments in older age remain under-explored. The current proposal investigates brain contributions to the clinically valuable measure of walking speed, a known predictor of falls, disability, and mortality in older age. Several studies to date have found evidence that neurocognitive dysfunction and neurodegeneration result in slower walking. The observed relationships, however, are not consistent across studies. Structural investigations may or may not report relationships with impaired mobility; age-related declines of structure are variable, spatially diffuse, and cannot be fully captured in a single imaging modality. The applicant’s previous work has shown that brain function may be a better predictor of gait, although these measures are typically underutilized and not easily integrated with structural measures. This proposal aims to address the need to accurately identify the most important neural mechanisms of walking for older adults by combining imaging data across multiple MR modalities in the presence of other clinical factors and predictors. The overall objectives of this proposal are to identify the relative contributions of brain structure, function, and their interactions to walking speed, and to test their generalizability to other older adult populations. Specifically, the applicant will 1) develop an integrative model utilizing functional and structural MR biomarkers from the MOBILIZE Boston Study (MBS) of older community- dwelling adults to predict walking speed, and 2) validate the model in a separate cohort from the Rush University Alzheimer’s Disease Center Memory and Aging Project (MAP). For this project, the applicant’s central hypothesis is that the intact functional dynamics of executive and attention neural networks are essential for maintained/improved mobility in older adults. For this three-year Career Development Award, the applicant proposes to pursue these research aims and train in advanced statistical modeling and data science, project management, and rehabilitative interventions for mobility under the guidance of a multi-disciplinary multi-institutional team. The specific research and statistical modeling methods gained from this project supports the applicant’s long-term goal to inform successful aging for older adults by (1) investigating the neural mechanisms that contribute to functional impairments commonly encountered in older age, (2) identifying early biomarkers of these declines, and (3) developing neuroscience-informed interventions for improved outcomes.

项目摘要 尽管功能和结构性MRI已被用来表征衰老，疾病和认知，但 中枢神经系统机制在老年年龄造成的迁移障碍障碍的基础机制仍然不足。这 当前的建议调查了大脑对临床上有价值的步行速度测量的贡献，这是一个已知的 跌倒，残疾和死亡率的预测因子。迄今为止的几项研究发现了证据 神经认知功能障碍和神经变性导致步行较慢。观察到的关系， 但是，在整个研究中都不一致。结构调查可能会或可能不会报告与 流动性受损；与年龄相关的结构下降是可变的，空间扩散的，不能完全捕获 在单个成像方式中。申请人以前的工作表明大脑功能可能更好 尽管这些措施通常不足，并且不容易与结构集成 措施。该建议旨在满足准确确定最重要的中性的需求 通过在多种MR模式中结合成像数据来为老年人步行的机制 存在其他临床因素和预测因子。该提案的总体目标是确定 大脑结构，功能及其相互作用对步行速度的相对贡献，并测试其 对其他老年人群体的普遍性。具体而言，申请人将1）开发一个综合模型 利用来自老年社区的波士顿研究（MBS）的功能和结构性MR生物标志物 居住成年人预测步行速度，2）在与匆忙的单独队列中验证该模型 阿尔茨海默氏病大学病中心记忆和衰老项目（MAP）。对于这个项目，申请人的 中心假设是执行和注意力神经网络的完整功能动态是 维持/改善老年人的流动性至关重要。对于这个三年的职业发展奖， 申请人提出这些研究的目的并培训高级统计建模和数据科学的培训， 在多学科的指导下，项目管理和对流动性的康复干预措施 多机构的团队。从该项目中获得的具体研究和统计建模方法 支持申请人的长期目标，以通过（1）调查来告知老年人的成功衰老 有助于在老年时遇到的功能障碍的神经机制，（2） 确定这些下降的早期生物标志物，以及（3）开发神经科学知识的干预措施 改善的结果。