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 阿尔茨海默病（AD）是一种毁灭性的疾病，影响数百万美国人，并施加了巨大的社会， 经济负担。AD相关的认知功能下降与Aβ（淀粉样蛋白β）斑块的积累有关 和过度磷酸化的tau蛋白的神经细胞缠结，其不能被充分清除和降解， 通过神经胶质-淋巴系统或通过血脑屏障（BBB）转运，可以抑制细胞内的凋亡。动物 研究表明，胶质-淋巴通路在Aβ的净清除中起重要作用。在 此外，减少间质液流出到脑脊液，或减少通过BBB的转运， 可降低Aβ清除率。人体磁共振成像（MRI）研究也表明， 血管周围间隙（PVS）是胶质-淋巴系统的通路，其完整性是胶质-淋巴系统的标志。 脑健康及其改变是AD病理学的重要特征。已证明AD中的PVS改变 不依赖于淀粉样蛋白摄取，暗示AD特异性的星形胶质细胞参与。关于PVS的信息 完整性可以帮助临床医生对患者的AD状态和机制做出具体的诊断。 因此，允许来自临床MRI的PVS的非侵入性体内标测的工具对于辅助诊断具有重要意义。 AD诊断和疾病监测，但还不存在。目前研究PVS的临床常规是 基于神经放射科医生在MRI中观察到的PVS总数的相对粗糙的方法， 是非特异性的、评级依赖性的，并且不能捕获PVS变化的分布、整体程度， PVS的体积特征。从实用的角度来看，这种技术是费时费力的。 这些局限性在一定程度上阻碍了神经科医生将PVS量化纳入其临床常规。 我们已经开发了计算技术，用于映射和量化来自MRI的PVS形态， 能够自动和准确地量化整个大脑中的PVS，而无需耗时 人工干预。这些技术是在研究数据的基础上发展起来的， 比临床MRI更好该提案的目标是在临床MRI数据上验证和优化该技术， 在质量和分辨率上可以是可变的。我们的目标还在于开发一种与扫描仪和硬件无关的 自动PVS定量的分析解决方案，因此可以独立于 放射学/成像IT基础设施。如果成功，我们将拥有一个完全开发和验证的后端软件 这使得能够自动评估PVS并帮助特定的AD诊断和疾病监测。于 为了完成这一目标，我们的第二阶段将重点放在通过实施和测试技术的翻译上， 该技术与我们的战略合作伙伴在临床（凯克学院神经放射学部， 医药）、工业（BioGen Inc.）（MarkVCID和NASA）。我们的最终目标是整合 PVS措施纳入临床诊断、病情监测和干预效果评估，作为一项具体的 可以自动和可靠地测量的AD病理学的非侵入性和体内成像标记物。