Next Generation Quantitative Acoustic Microscopy for Biomedical Application

用于生物医学应用的下一代定量声学显微镜

基本信息

批准号：
10707063
负责人：
JONATHAN MAMOU
金额：
$ 43.27万
依托单位：
WEILL MEDICAL COLL OF CORNELL UNIV
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-20 至 2026-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10707063
关键词：
Acoustic Microscopy Acoustics Biological Biological Testing Biomechanics Cancer Patient Cancerous Clinical Code Compensation Computing Methodologies Data Data Science Development Dictionary Disease Dyes Electronics Environment Fostering France Frequencies Generations Goals Hour Human Image Immunofluorescence Immunologic Industrialization Investigation Knowledge Laboratories Laboratory Research Machine Learning Maps Methods Microscope Microscopic Microscopy Modality Modeling Modulus Morphologic artifacts Motor Myopia National Institute of General Medical Sciences Pathogenesis Physics Play Property Relaxation Research Resolution Sampling Scanning Sclera Signal Transduction Specimen Speed Stains Structure System Techniques Technology Technology Development Study Testing Thick Thinness Time Tissue Sample Tissues Training Ultrafine Ultrasonography United Kingdom Universities clinical diagnostics cost data acquisition design electric impedance expectation experimental study flexibility guinea pig model image reconstruction imaging modality imaging properties imaging system improved innovation instrument interest light microscopy lymph nodes mechanical properties meter microscopic imaging next generation novel novel strategies pre-clinical prevent protein distribution prototype quantitative imaging restoration simulation sound success technology research and development tissue mapping ultra high resolution ultrasound user-friendly

项目摘要

Riverside Research, the University of Bristol (Bristol, United Kingdom), and the University Paul Sabatier (Toulouse, France) propose to develop the next generation of quantitative acoustic microscopy (QAM) systems. Specifically, data- science and coded-excitation approaches will be applied for the first time to QAM technology to yield better image quality, decreased scanning time, greater ease of use, as well as to pave the way for a new generation of novel, low-cost, user-friendly QAM instruments. QAM permits formation of fine-resolution (i.e., <7 µm at 250 MHz) maps of acoustic and mechanical properties of tissue sections that are <12 µm in thickness. These data can have great value in numerous preclinical investigations. Such property maps are not currently obtainable by any other microscopic-imaging modality, and the new generation of QAM technology made possible by success in this proposed project could become widespread in research laboratories and microscopy suites in commercial as well as academic research environments. Such new-generation QAM instruments could be used by technicians with limited knowledge of QAM and, in many ways, their use would be no more complicated than use of a conventional bright-field microscope. These novel approaches to QAM will be demonstrated using already available resolution targets, phantoms, and biological tissues (ocular-tissue samples from a guinea-pig model of myopia and cancerous human lymph nodes). During the course of this project, optimal methods will be incorporated in a prototype QAM (pQAM) instrument capable of producing ultra-fine spatial resolution (< 2 µm) images much faster (<1 min) and for a much lower cost (<$40k) than current state-of-the-art QAM systems. In addition, pQAM use will be ``turn-key'' (i.e., requiring no technical knowledge and less than 1 hour of training.)

河滨研究，布里斯托尔大学（布里斯托尔，英国）和大学保罗·萨巴蒂尔（图卢兹，图卢兹，法国）建议开发下一代的定量声学显微镜（QAM）系统。科学和编码方法将首次采用QAM技术，以产生更好的图像质量，减少扫描时间，更容易使用，为新一代新颖，低成本铺平道路用户友好的QAM仪器。在厚度<12 µm的组织秒的机械性能。临床前研究目前无法获得任何事件。新一代的QAM技术通过该项目的成功而成为可能在商业以及学术研究环境中的研究实验室和显微镜套件中广泛存在。这种新一代的QAM仪器可以由对QAM了解有限的技术人员使用方式，与传统的明亮场显微镜的使用相比，它们的使用不再复杂。使用Alredy可用的分辨率目标，幻影和生物组织证明的QAM方法（来自近视和癌性人淋巴结的几内亚猪模型的眼科组织样品）。项目，最佳方法将纳入能够产生超细节的原型QAM（PQAM）仪器空间分辨率（<2 µm）的图像要快得多（<1分钟），成本要低得多（<$ 40k） QAM系统。此外，使用PQAM将是``转键''（即，不需要技术知识，少于1个训练。）