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

项目摘要 阿尔茨海默病(AD)是一种毁灭性的疾病，影响着数以百万计的美国人，并给 经济负担。AD相关认知功能减退与β(淀粉样β蛋白)斑块积聚有关 和过度磷酸化的tau蛋白的神经原纤维缠结，这些蛋白不能被充分清除和降解 如胶质细胞淋巴系统或通过血脑屏障(BBB)的运输机制。动物 研究表明，神经胶质细胞-淋巴通路在A-β的净清除中起着重要作用。在……里面 此外，减少间质液体向脑脊液的外流，或减少跨血脑屏障的运输， 可能会减少Aβ的通行证。人类磁共振成像(MRI)研究也表明， 血管周围间隙的完整性是神经胶质细胞淋巴系统的通路，是神经胶质细胞淋巴系统的标志。 脑健康及其改变是AD病理的一个重要特征。AD的PVS改变已显示为 独立于淀粉样蛋白的摄取，暗示AD特定的星形胶质细胞参与。关于PVS的信息 诚信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，一种可以从临床MRI中无创地进行PVS活体标测的工具具有重要的辅助意义 AD诊断和疾病监测，但还不存在。目前研究PVS的临床常规是 相对粗略的方法是基于神经放射科医生在MRI中观察到的PVS总数的计数，这 是非特定的、依赖于评分者的，并且没有捕捉到分布、PVS的整个变化范围或 PVS的体积特征。从实用的角度来看，这项技术既耗时又费力。 这些局限性在一定程度上阻碍了神经科医生将PVS量化纳入他们的临床常规。 我们已经开发了用于从MRI映射和量化PVS形态的计算技术，这 能够自动准确地量化大脑中的PVS，而不需要耗费时间 人工干预。这些技术是基于研究数据开发的，这些数据的分辨率略高 而不是临床核磁共振。这项建议的目标是验证和优化这项技术在临床MRI数据上的应用 质量和分辨率可以是可变的。我们还致力于开发一种与扫描仪和硬件无关的可部署 用于自动PVS量化的解析解决方案，使PVS映射可以独立于 放射学/成像IT基础设施。如果成功，我们将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和艾滋病特定的AD诊断和疾病监测。在此之前 完成这一目标后，我们的第二阶段将专注于通过实施和测试 与我们的临床战略合作伙伴合作的技术(凯克医学院神经放射学部 医药)、工业(Biogen Inc.)和研究(MarkVCID和NASA)。我们的最终目标将是整合 PVS措施应用于临床诊断、疾病监测和干预效果评估 AD病理的非侵入性和活体成像标记物，可以自动和可靠地测量。

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.