PROJECT SUMMARY/ABSTRACT Alzheimer’s disease (AD) is the most common cause of dementia and impacts the lives of 6 million Americans. With a worldwide aging population and absence of effective therapies, a global epidemic of AD is looming. At present, a key challenge for developing effective AD therapies is the complex pathophysiological processes inherent to AD. In particular, emerging evidence points to vascular dysfunction as an early and ubiquitous feature of AD. However, despite the importance of vascular contributions to AD, there currently exists a large gap in understanding the exact mechanisms underlying the vascular-Abeta interactions. This knowledge gap fundamentally limits our capabilities to understand key mechanisms underlying AD pathogenesis and ultimately develop effective AD therapies. To fill this knowledge gap, it is essential to conduct mechanistic in vivo studies that are hypothesis-driven, providing detailed understanding of the relationship between cerebrovascular impairments and AD pathophysiologies. To that end, cerebrovascular imaging will play an essential and increasingly important role. However, existing cerebrovascular imaging technologies fall short of providing adequate imaging spatial resolution and depth of penetration to provide measurements of vascular biomarkers in deep brain regions that contain AD microvascular pathologies. This significant technical gap limits our ability to answer important questions about neurovascular pathology in AD. Therefore, the goal of this proposal is to develop an ultrasound-based, high-resolution cerebral microvascular imaging (HCMI) technique to fill this important technical gap and ultimately provide a viable, noninvasive imaging tool to answer hypothesis-driven questions about AD vascular dysfunction and pathologies. If successfully developed, HCMI will achieve whole- brain, micron-scale, and dynamic microvascular mapping for AD mouse models. In Aim 1, we will develop innovative solutions for HCMI to enable fast and robust whole-brain microvascular imaging through intact skull for longitudinal AD studies. We will focus on developing viable solutions that allow reliable longitudinal monitoring of whole-brain microvasculature through intact skull. We will also extend HCMI from 2D to 3D imaging based on ultrafast 3D ultrasound. In Aim 2, we will accelerate HCMI with FPGA- and GPU-based parallel computing techniques. We will develop an FPGA-based ultrafast beamformer for continuous, high-speed ultrasound data acquisition to support 3D HCMI. We will also develop GPU-based parallel computing method to maximize HCMI post-processing speed. In Aim 3, we will validate the in vivo performance of HCMI on AD mouse models. We will use brain histology and cognitive behavioral testing to validate HCMI performance in measuring microvascular alterations associated with AD. Based on recent evidence indicating the feasibility of in vivo transcranial microvascular imaging in humans with ultrasound,...