Point-of-Care Carotid Ultrasound and Cardiovascular Risk Assessment Device

描述（由申请人提供）：该提案描述了一种新颖、低成本、高性能的紧凑颈动脉超声成像系统，以满足基于共识实践标准指南的临床护理点狭窄评估需求。同时，该系统将满足日益增长的高级心血管（CV）风险评估的需求。这项研究将成熟的基础技术与现代技术相结合。提出的设备重新审视了标准超声测量技术，但显著改进了它们。这些改进是通过采用创新的工程设计、精确的跟踪和保持前端、低成本的模数转换器、创新的电磁换能器驱动系统和分布式信号处理架构来实现的，以低制造成本实现高性能颈动脉成像仪。基于美国国立卫生研究院赞助的超声智能传感器（NHLBI授予5RC1HL101881， William Weitzel， PI）的转化研究项目的成功，并利用我们专有的射频（RF）超声斑点跟踪算法，我们将开发用于颈动脉的特定应用3D测量工具。我们利用现代、小型化、可重构电子元件和高带宽无线技术，在传感器显示模块中集成低级超声信号的产生、采集和预处理，然后分发（远程执行）高级信号处理、图像构建和图像处理。我们在现有系统硬件架构的基础上：1)将数据采集扩展到3D，满足颈动脉狭窄评估的护理点需求；2)开发服务器端系统算法，使用先进的信号处理和射频跟踪改进操作员独立测量狭窄；3)利用我们的技术优势，利用我们的创新平台精确测量颈动脉扩张性，扩展心血管风险评估的诊断能力。

DESCRIPTION (provided by applicant): This proposal describes a novel, low-cost, high-performance compact carotid ultrasound imaging system to meet the clinical point-of-care needs for stenosis assessment based upon consensus practice criteria guidelines. At the same time, this system will meet the growing need for advanced cardiovascular (CV) risk assessment. This research integrates proven fundamental techniques with modern technology. The proposed device revisits standard ultrasound measurement techniques, but significantly improves on them. These improvements are achieved by using an innovative engineering design, accurate track and hold front-end, low-cost analog to digital converters, and an innovative electro-magnetic transducer drive system and distributed signal processing architecture to realize a high performance carotid imager at low manufacturing cost. Building upon the success of an NIH sponsored translational research project to make an ultrasound smart sensor (NHLBI grant 5RC1HL101881, William Weitzel, PI) and leveraging our proprietary radiofrequency (RF) ultrasound speckle tracking algorithms, we will develop application specific 3D measurement tools for the carotid artery. We leverage modern, miniaturized reconfigurable electronic components and high bandwidth wireless technology, to integrate low-level ultrasound signal generation, acquisition and pre-processing in the transducer-display module and then distribute (remotely perform) the higher-level signal processing, image construction and image processing. We build upon our current system hardware architecture to: 1) extend data acquisition into 3D meeting the point-of-care needs for carotid stenosis assessment, 2) develop server side system algorithms for improved operator independent measurements of stenosis using advanced signal processing and RF tracking, and 3) expand diagnostic capabilities for CV risk assessment by leveraging our technical advantages for accurately measuring carotid distensability using our innovative platform.