Development of perivascular space mapping toolset as a diagnostic aid for Alzheimer's disease

开发血管周围空间测绘工具集作为阿尔茨海默病的诊断辅助工具

• 批准号: 10255954
• 负责人: Jeiran Choupan
• 金额: $ 46.1万
• 依托单位: NEUROSCOPE INC.
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10255954
• 关键词: Abeta clearance; Adopted; Affect; Age; Alzheimer' s Disease; Alzheimer' s disease diagnosis; Alzheimer' s disease pathology; Alzheimer' s disease patient; Alzheimer' s disease related dementia; American; Amyloid; Amyloid beta-Protein; Animal Experimentation; Axon; Blood - brain barrier anatomy; Brain; California; Cerebrospinal Fluid; Clinic; Clinical; Clinical Data; Clinical Research; Clinical assessments; Cognitive; Collaborations; Computational Technique; Computer software; Consumption; Data; Data Set; Demyelinations; Development; Diagnosis; Diagnostic; Disease; Economic Burden; Ensure; Feedback; Goals; Hippocampus (Brain); Human; Image; Impaired cognition; Individual; Industry; Infrastructure; Intercellular Fluid; Intervention; Liquid substance; Lymphatic; Lymphatic System; Machine Learning; Magnetic Resonance Imaging; Manuals; Maps; Measures; Medical Imaging; Metabolic; Monitor; Morphology; Neurofibrillary Tangles; Neuroglia; Neurologist; Operating System; Outcome; Participant; Pathologic; Pathology; Pathway interactions; Patient Monitoring; Phase; Play; Positron-Emission Tomography; Protocols documentation; Public Health; Research; Resolution; Role; Scanning; Senile Plaques; Sensitivity and Specificity; Sex Distribution; Small Business Technology Transfer Research; Standardization; Structure; Techniques; Technology; Testing; Time; Translating; Translations; Treatment Efficacy; United States National Aeronautics and Space Administration; Universities; Validation; Visual; amnestic mild cognitive impairment; base; brain health; clinical Diagnosis; clinical predictors; clinically significant; cohort; connectome; cost estimate; efficacy evaluation; human data; hyperphosphorylated tau; imaging biomarker; imaging study; in vivo; in vivo imaging; insight; interest; magnetic field; medical schools; neuroimaging; neurovascular; predictive modeling; prevent; protein aggregation; radiological imaging; radiologist; socioeconomics; success; tau Proteins; technology validation; tool; uptake; vascular cognitive impairment and dementia; wasting

Project Summary Alzheimer’s disease (AD) is a devastating disease that affects millions of Americans and imposes a huge socio- economic burden. AD-related cognitive decline is associated with the accumulation of Aβ (Amyloid beta) plaques and neurofibrillary tangles of hyperphosphorylated tau protein, which are insufficiently cleared and degraded by mechanisms such as the glia-lymphatic system or by transport across the blood-brain barrier (BBB). Animal research has shown that the glia-lymphatic pathway plays a substantial role in the net clearance of Aβ. In addition, reduction of interstitial fluid efflux to the cerebrospinal fluid, or reduction of transport across the BBB, could lessen the Aβ clearance. Human magnetic resonance imaging (MRI) studies have also shown that the integrity of the perivascular space (PVS), the pathway of glia-lymphatic system, is a marker of glia-lymphatic brain health and its alteration is an important feature of AD pathology. PVS alteration in AD has been shown to be independent of Amyloid uptake, implicating astroglial involvement specific to AD. Information about PVS integrity could assist clinicians with making specific diagnosis about patients AD status and mechanism. Therefore, a tool that allows non-invasive in-vivo mapping of PVS from clinical MRI is of high significance to aid AD diagnosis and disease monitoring but does not yet exist. Current clinical routine to investigate PVS is a relatively crude approach based on counting total number of observed PVS in MRI by neuro-radiologists, which is non-specific, rater-dependent, and does not capture the distribution, whole extent of PVS change nor volumetric features of the PVS. From a practical point of view, this technique is time consuming and laborious. These limitations in part have prevented neurologists from adopting PVS quantification into their clinical routine. We have developed computational techniques for mapping and quantifying PVS morphology from MRI, which enables automated and accurate quantification of PVS across the brain without the need for time consuming manual intervention. These techniques were developed on research data, which had slightly higher resolution than clinical MRI. The goal of this proposal is to validate and optimize this technology on clinical MRI data, which can be variable in quality and resolution. We also aim to develop a scanner- and hardware-agnostic deployable analytical solution for automated PVS quantification, so that PVS mapping can be performed independent of the radiology/imaging IT infrastructure. If successful, we will have a fully developed and validated backend software that enables automated assessment of PVS and aids specific AD diagnosis and disease monitoring. Upon the completion of this goal, our Phase II will focus on translation of the technology via implementation and testing of the technology in collaboration with our strategic partners in clinic (Neuroradiology division of Keck School of Medicine), industry (BioGen Inc.) and research (MarkVCID and NASA). Our ultimate goal will be to integrate PVS measures into clinical diagnosis, disease monitoring and intervention efficacy assessment, as a specific non-invasive and in-vivo imaging marker of AD pathology that can be automatically and reliably measured.

项目摘要 阿尔茨海默氏病（AD）是一种毁灭性疾病，影响数百万美国人，不可能巨大的社会 经济负担。与广告相关的认知下降与Aβ（淀粉样蛋白β）斑块的积累有关 和高磷酸化tau蛋白的神经纤维缠结，这些蛋白质不足和降解 诸如胶质淋巴系统或通过跨血脑屏障（BBB）运输的机制。动物 研究表明，胶质淋巴途径在Aβ的净清除率中起着重要作用。在 另外，减少了脑脊液的间隙流体外排或减少BBB的转运 可以降低Aβ清除率。人类磁共振成像（MRI）研究还表明 血管周空间（PVS）的完整性是胶质淋巴系统的途径，是胶质淋巴的标志物 大脑健康及其改变是AD病理学的重要特征。已显示AD的PVS改变已显示 独立于淀粉样蛋白的摄取，暗示着特定于AD的星形胶质涉及。有关PVS的信息 诚信可以帮助临床医生对患者AD状态和机制进行特定的诊断。 因此，一种允许从临床MRI对PV进行非侵入性体内映射的工具对于有助于 AD诊断和疾病监测，但尚不存在。当前研究PVS的临床常规是 基于对神经放射学家观察到的MRI观察到的PV总数的相关原油方法， 是非特异性的，依赖分数的，并且不捕获分布，PV的整个范围也会改变 PVS的体积特征。从实际的角度来看，这项技术是耗时且艰苦的。 这些局限性部分阻止了神经科医生在其临床常规中采用PVS定量。 我们开发了用于映射和量化MRI的PVS形态的计算技术， 启用无需耗时的自动和准确的PV量化大脑的PV 手动干预。这些技术是根据研究数据开发的，该数据的分辨率略高 比临床MRI。该建议的目的是在临床MRI数据上验证和优化该技术，该技术 质量和分辨率可能是可变的。我们还旨在开发扫描仪和硬件敏捷的可部署 自动PVS定量的分析解决方案，因此可以独立于PVS映射 放射学/成像IT基础架构。如果成功，我们将拥有一个完全开发和验证的后端软件 这样可以自动评估PVS和AIDS特定的AD诊断和疾病监测。在 完成此目标的完成，我们的第二阶段将通过实施和测试专注于技术的翻译 该技术与我们的临床战略合作伙伴合作（凯克学院神经放射学系 医学），工业公司（Biogen Inc.）和研究（Markvcid和NASA）。我们的最终目标是整合 PVS衡量临床诊断，疾病监测和干预效率评估，作为特定 可以自动且可靠的AD病理学的非侵入性和体内成像标记。