Improving Human fMRI through Modeling and Imaging Microvascular Dynamics

通过微血管动力学建模和成像改善人类功能磁共振成像

基本信息

批准号：
9974595
负责人：
Jonathan Rizzo Polimeni
金额：
$ 93万
依托单位：
MASSACHUSETTS GENERAL HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-15 至 2023-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9974595
关键词：
Anatomy Angiography Architecture Back Belief Blood Blood Vessels Blood capillaries Blood flow Brain Brain Mapping Caliber Cerebral cortex Contracts Coupling Data Development Dictionary Distal Diving Exhibits Formulation Functional Magnetic Resonance Imaging Future Human Image Imaging Techniques Individual Knowledge Link Magnetic Resonance Imaging Maps Measurement Measures Methods Modeling Neurons Population Procedures Psyche structure Regulation Resolution Rest Rodent Signal Transduction Slice Specificity Specimen Stimulus Surface Techniques Technology Testing Time Trees Validation Visual Cortex area V1 area striata arteriole base blood oxygenation level dependent response cerebral blood volume connectome hemodynamics human model imaging study improved in vivo in vivo evaluation in vivo imaging monocular neuroimaging novel optical imaging predictive modeling reconstruction response spatiotemporal two photon microscopy two-photon venule

项目摘要

PROJECT SUMMARY/ABSTRACT All fMRI signals have a vascular origin, and this has been believed to be a major limitation to precise spatiotemporal localization of neuronal activation when using hemodynamic functional contrast such as BOLD. However, significant recent discoveries made using powerful ultrahigh-resolution optical imaging techniques have challenged this belief. Unfortunately these measures require invasive procedures and therefore cannot be performed in humans. Our aim is to transfer knowledge gained from these invasive studies into interpreting human fMRI data in order to help fMRI reach its full potential. In this proposal we plan to combine detailed maps of human macro- and meso-scale vasculature measured with high-resolution MRI with maps of the micro-scale vasculature measured in human brain specimens with CLARITY-assisted microimaging. We will then link this anatomical information with dynamic models built from 2-photon microscopy performed in rodents where the changes in vessel diameter, blood flow and oxygenation can be measured directly in each vessel type across all stages of the vascular hierarchy. We hypothesize that newly introduced models of hemo- and vaso-dynamics built from 2-photon microscopy, linked with a detailed micro- and macroscopically mapped human microvascular anatomy, can be exploited to improve the spatial and temporal specificity of human fMRI. To supply human vasculature reconstructions to our models, we propose a two-scale approach. We first advance 7 Tesla MR Angiography (MRA) techniques to image the pial vascular network as well as intracortical vessels and vascular layers of the cerebral cortex to achieve a mesoscopic model. To form the micron-scale model of vasculature at the capillary level, we will use the CLARITY technique to image the full vascular tree (from arterioles through capillaries to venules) in human primary visual cortex. To predict vasodynamic changes driven by neuronal activation, we will adapt a model derived from dynamic in vivo 2-photon microscopy of vessel diameters in rodents to human microvascular anatomy. To adapt this to human microvasculature requires a careful multi-stage transferal. First we will measure bulk changes in microvessel diameter, a.k.a. cerebral blood volume (CBV), across multiple levels of the vascular hierarchy and confirm that the model can predict the CBV-fMRI signal. The CBV-fMRI signal is used because it is a vasodynamic signal directly reflecting vessel diameter changes occurring alongside local neuronal activity (rather than the subsequent hemodynamic changes). After performing this validation we will build a dynamic model of the microvascular tree in human cortex based on our vascular reconstruction, and again measure CBV-fMRI changes across multiple levels of the vascular hierarchy. We will finally test the ability of this model to improve the neuronal specificity of fMRI by imaging the functional architecture in human visual cortex. This model will also enable the formulation and testing of hypotheses about the discriminability of fMRI responses elicited from nearby neuronal populations, and guide development of future advanced acquisition technologies.

项目概要/摘要所有功能磁共振成像信号都有血管起源，这被认为是精确定位的主要限制使用血流动力学功能对比（例如 BOLD）时神经元激活的时空定位。然而，最近使用强大的超高分辨率光学成像技术取得的重大发现挑战了这一信念。不幸的是，这些措施需要侵入性手术，因此不能在人类身上进行。我们的目标是将这些侵入性研究中获得的知识转化为口译人类功能磁共振成像数据，以帮助功能磁共振成像充分发挥其潜力。在这个提案中，我们计划结合详细的使用高分辨率 MRI 测量的人体宏观和中观尺度脉管系统图使用 CLARITY 辅助显微成像技术测量人脑样本中的微尺度脉管系统。我们将然后将这些解剖信息与在啮齿类动物中进行的双光子显微镜建立的动态模型联系起来可以直接测量每条血管的血管直径、血流量和氧合变化跨血管层次结构所有阶段的类型。我们假设新引入的血液和由 2 光子显微镜构建的血管动力学，与详细的微观和宏观映射相联系人体微血管解剖学，可用于提高人体功能磁共振成像的空间和时间特异性。为了向我们的模型提供人体脉管系统重建，我们提出了一种两尺度方法。我们首先先进的 7 种 Tesla MR 血管造影 (MRA) 技术对软脑膜血管网络以及皮质内进行成像大脑皮层的血管和血管层以实现细观模型。形成微米级毛细血管水平的脉管系统模型，我们将使用 CLARITY 技术对完整的血管树进行成像（从小动脉到毛细血管再到小静脉）人类初级视觉皮层。为了预测由神经元激活驱动的血管动力学变化，我们将采用衍生自的模型啮齿动物血管直径的动态体内 2 光子显微镜到人体微血管解剖学。到使其适应人体微脉管系统需要仔细的多阶段转移。首先我们将测量体积血管多个层面的微血管直径（又名脑血容量（CBV））的变化层次结构并确认该模型可以预测 CBV-fMRI 信号。使用 CBV-fMRI 信号是因为它是直接反映伴随局部神经元活动发生的血管直径变化的血管动力学信号（而不是随后的血流动力学变化）。执行此验证后，我们将构建一个动态的基于我们的血管重建的人类皮层微血管树模型，并再次测量 CBV-fMRI 在血管层次结构的多个层面上发生变化。我们最终会测试这个模型的能力通过对人类视觉皮层的功能结构进行成像来提高功能磁共振成像的神经元特异性。这模型还将能够制定和测试有关功能磁共振成像反应可辨别性的假设从附近的神经元群体中提取，并指导未来先进采集技术的开发。