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光学成像光谱法快速初步筛查 SARS-CoV-2:概念验证。

Optical imaging spectroscopy for rapid, primary screening of SARS-CoV-2: a proof of concept.

机构信息

Department of Applied Physics III, ETSI School of Engineering, Universidad de Sevilla, Camino de los Descubrimientos s/n, 41092, Sevilla, Spain.

Institute of Biomedicine of Seville (IBIS), 41013, Sevilla, Spain.

出版信息

Sci Rep. 2022 Feb 18;12(1):2356. doi: 10.1038/s41598-022-06393-3.

Abstract

Effective testing is essential to control the coronavirus disease 2019 (COVID-19) transmission. Here we report a-proof-of-concept study on hyperspectral image analysis in the visible and near-infrared range for primary screening at the point-of-care of SARS-CoV-2. We apply spectral feature descriptors, partial least square-discriminant analysis, and artificial intelligence to extract information from optical diffuse reflectance measurements from 5 µL fluid samples at pixel, droplet, and patient levels. We discern preparations of engineered lentiviral particles pseudotyped with the spike protein of the SARS-CoV-2 from those with the G protein of the vesicular stomatitis virus in saline solution and artificial saliva. We report a quantitative analysis of 72 samples of nasopharyngeal exudate in a range of SARS-CoV-2 viral loads, and a descriptive study of another 32 fresh human saliva samples. Sensitivity for classification of exudates was 100% with peak specificity of 87.5% for discernment from PCR-negative but symptomatic cases. Proposed technology is reagent-free, fast, and scalable, and could substantially reduce the number of molecular tests currently required for COVID-19 mass screening strategies even in resource-limited settings.

摘要

有效检测对于控制 2019 年冠状病毒病(COVID-19)的传播至关重要。在此,我们报告了一项概念验证研究,即在可见和近红外范围内进行高光谱图像分析,以在 SARS-CoV-2 的即时护理点进行初步筛查。我们应用光谱特征描述符、偏最小二乘判别分析和人工智能,从 5 µL 液体样本的光漫反射测量中提取信息,分别在像素、液滴和患者水平上进行。我们辨别了在盐溶液和人工唾液中用 SARS-CoV-2 刺突蛋白假型化的工程化慢病毒颗粒制剂与用水疱性口炎病毒 G 蛋白假型化的制剂。我们报告了对 SARS-CoV-2 病毒载量范围内 72 个鼻咽分泌物样本的定量分析,以及对另外 32 个新鲜人唾液样本的描述性研究。渗出物分类的敏感性为 100%,特异性峰值为 87.5%,可与 PCR 阴性但有症状的病例区分开来。所提出的技术是无试剂的、快速的和可扩展的,即使在资源有限的情况下,也可以大大减少当前 COVID-19 大规模筛查策略所需的分子检测数量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f3/8857323/26a9ce07483a/41598_2022_6393_Fig1_HTML.jpg

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