EAGER: Compact Field Portable Biophotonics Instrument for Real-Time Automated Analysis and Identification of Blood Cells Impact Impacted by COVID-19

EAGER：紧凑型现场便携式生物光子学仪器，用于实时自动分析和识别受 COVID-19 影响的血细胞

• 批准号: 2141473
• 负责人: Bahram Javidi
• 金额: $ 22万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2141473&HistoricalAwards=false
• 关键词: EAGER; Compact; Field; Portable; Biophotonics

COVID-19 pandemic quickly overwhelmed the healthcare resources in even advanced economies with large scale global fatalities not seen since the Spanish Flu of 1918. This project intends to investigate the impact of the COVID-19 virus on human red blood cells using an automated low-cost, field portable bio-photonics instrument. These studies can lead to better understanding of the impacted blood cells and precise measurement of cell anomalies for potential early detection of COVID-19. Accurate, rapid, and low-cost analysis and diagnosis of COVID-19 from blood cells with a compact field portable bio-photonics instrument interfaced with mobile devices will be a substantial advance toward widespread testing, medical diagnosis, early detection, disease prevention, and relevant data collection, particularly in remote areas without access to dedicated healthcare facilities. The proposed cross disciplinary project is based on a transformative biophotonics sensing approach for real-time analysis and disease detection and offers an alternative to conventional labor- and resource- intensive bio-molecular approaches. This analysis and capability would enable medical researchers to study and gain increased understanding of the effects of COVID-19 infections on blood cells. The proposed approach may provide a fast and reliable testing mechanism with the potential for widespread deployment, which is critical in dealing with pandemics, such as COVID-19, with high rates of infection and mortality. The success of the proposed approach would allow for automated low cost, rapid and highly accurate assessment of the impact of COVID-19 on blood cells, which is not currently possible using conventional methods. The proposed research provides new capabilities and benefits including real-time sensing and diagnosis; early detection with high accuracy, specificity, and sensitivity, and low cost field portable deployment in under resourced healthcare systems for real-time monitoring of pandemics.Investigating the impact of COVID-19 on blood cells and making detailed real-time measurements of the COVID-19 induced changes and anomalies of the blood cells at sub-micron scales would provide valuable research insights to fight COVID-19 and future pandemics. The proposed approach employs computational multi-dimensional sensing and imaging at sub-micron scales to analyze morphology and motility of blood cells. Specially embedded algorithms are integrated with mobile devices to analyze opto-biological signatures of blood cells in real time to find potential clues to the impact and presence of COVID-19 for rapid (real-time) COVID analysis and detection. The measurements and analysis of the infected cells will be performed at sub-micron scale lateral resolution and nano scale longitudinal resolution. The proposed project investigates blood cells morphology and temporal motility quantitatively with high precision using high resolution self-referencing digital holographic in compact 3D-printed platforms. Multidimensional bio-optical signature data, including spatial structure, refractive index, stiffness, and dynamic temporal behavior of the blood cells will be investigated to understand the influence of COVID-19 in blood cells. The use of dedicated machine learning algorithms associated with the analysis of anomalies in blood cells due to COVID-19 are intended to produce accurate detection and analysis.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

COVID-19 大流行甚至迅速压垮了发达经济体的医疗资源，导致全球范围内出现自 1918 年西班牙流感以来从未见过的大规模死亡事件。该项目旨在使用自动化的低通量检测系统来研究 COVID-19 病毒对人类红细胞的影响。成本，现场便携式生物光子仪器。这些研究可以帮助我们更好地了解受影响的血细胞并精确测量细胞异常，以便尽早发现 COVID-19。使用与移动设备连接的紧凑型现场便携式生物光子仪器对血细胞中的 COVID-19 进行准确、快速和低成本的分析和诊断，将是广泛检测、医疗诊断、早期检测、疾病预防和治疗方面的重大进步。相关数据收集，特别是在无法获得专门医疗设施的偏远地区。拟议的跨学科项目基于用于实时分析和疾病检测的变革性生物光子传感方法，并为传统的劳动力和资源密集型生物分子方法提供了替代方案。这种分析和能力将使医学研究人员能够研究并加深对 COVID-19 感染对血细胞影响的了解。所提出的方法可以提供一种快速、可靠的测试机制，并具有广泛部署的潜力，这对于应对感染率和死亡率较高的流行病（例如 COVID-19）至关重要。该方法的成功将允许对 COVID-19 对血细胞的影响进行自动化、低成本、快速且高度准确的评估，而这目前使用传统方法是不可能实现的。拟议的研究提供了新的功能和好处，包括实时传感和诊断；在资源匮乏的医疗保健系统中以高精度、特异性和灵敏度进行早期检测，并以低成本进行现场便携式部署，以实时监测流行病。研究 COVID-19 对血细胞的影响并对 COVID 进行详细的实时测量-19 在亚微米尺度引起的血细胞变化和异常将为对抗 COVID-19 和未来的流行病提供有价值的研究见解。所提出的方法采用亚微米尺度的计算多维传感和成像来分析血细胞的形态和运动性。专门嵌入的算法与移动设备集成，可实时分析血细胞的光生物学特征，找到有关 COVID-19 影响和存在的潜在线索，从而实现快速（实时）COVID 分析和检测。受感染细胞的测量和分析将以亚微米级横向分辨率和纳米级纵向分辨率进行。该项目利用紧凑型 3D 打印平台中的高分辨率自参考数字全息技术，高精度定量研究血细胞形态和时间运动性。将研究多维生物光学特征数据，包括血细胞的空间结构、折射率、刚度和动态时间行为，以了解 COVID-19 对血细胞的影响。使用专用机器学习算法与 COVID-19 引起的血细胞异常分析相关，旨在产生准确的检测和分析。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值进行评估，被认为值得支持以及更广泛的影响审查标准。

项目成果

3D integral imaging depth estimation of partially occluded objects using mutual information and Bayesian optimization

使用互信息和贝叶斯优化对部分遮挡物体进行 3D 积分成像深度估计

• DOI: 10.1364/oe.492160
• 发表时间: 2023-06
• 期刊: Optics Express
• 影响因子: 3.8
• 作者: Wani, Pranav;Javidi, Bahram
• 通讯作者: Javidi, Bahram

Assessment of lateral resolution of single random phase encoded lensless imaging systems

单随机相位编码无透镜成像系统的横向分辨率评估

• DOI: 10.1364/oe.480591
• 发表时间: 2023-03
• 期刊: Optics Express
• 影响因子: 3.8
• 作者: Goswami, Saurabh;Wani, Pranav;Gupta, Gaurav;Javidi, Bahram
• 通讯作者: Javidi, Bahram

Generalization of the two-point-source resolution criterion in the presence of noise

存在噪声时两点源分辨率准则的推广

• DOI: 10.1364/ol.494910
• 发表时间: 2023-07
• 期刊: Optics Letters
• 影响因子: 3.6
• 作者: Wani, Pranav;Usmani, Kashif;Javidi, Bahram
• 通讯作者: Javidi, Bahram