John Pauline, Vasa Nilesh J, Zam Azhar
Division of Engineering, New York University Abu Dhabi (NYUAD), Abu Dhabi 129188, United Arab Emirates.
Department of Engineering Design, Indian Institute of Technology Madras, Chennai 600036, India.
Diagnostics (Basel). 2023 Jul 20;13(14):2418. doi: 10.3390/diagnostics13142418.
The sudden outbreak of the COVID-19 pandemic led to a huge concern globally because of the astounding increase in mortality rates worldwide. The medical imaging computed tomography technique, whole-genome sequencing, and electron microscopy are the methods generally used for the screening and identification of the SARS-CoV-2 virus. The main aim of this review is to emphasize the capabilities of various optical techniques to facilitate not only the timely and effective diagnosis of the virus but also to apply its potential toward therapy in the field of virology. This review paper categorizes the potential optical biosensors into the three main categories, spectroscopic-, nanomaterial-, and interferometry-based approaches, used for detecting various types of viruses, including SARS-CoV-2. Various classifications of spectroscopic techniques such as Raman spectroscopy, near-infrared spectroscopy, and fluorescence spectroscopy are discussed in the first part. The second aspect highlights advances related to nanomaterial-based optical biosensors, while the third part describes various optical interferometric biosensors used for the detection of viruses. The tremendous progress made by lab-on-a-chip technology in conjunction with smartphones for improving the point-of-care and portability features of the optical biosensors is also discussed. Finally, the review discusses the emergence of artificial intelligence and its applications in the field of bio-photonics and medical imaging for the diagnosis of COVID-19. The review concludes by providing insights into the future perspectives of optical techniques in the effective diagnosis of viruses.
由于全球死亡率惊人上升，新冠疫情的突然爆发引发了全球的高度关注。医学成像计算机断层扫描技术、全基因组测序和电子显微镜是通常用于筛查和鉴定新冠病毒的方法。本综述的主要目的是强调各种光学技术的能力，这些技术不仅有助于及时有效地诊断病毒，还能在病毒学领域发挥其治疗潜力。本综述文章将潜在的光学生物传感器分为三大类，即基于光谱、纳米材料和干涉测量的方法，用于检测包括新冠病毒在内的各种类型的病毒。第一部分讨论了光谱技术的各种分类，如拉曼光谱、近红外光谱和荧光光谱。第二方面重点介绍了基于纳米材料的光学生物传感器的进展，而第三部分描述了用于检测病毒的各种光学干涉生物传感器。还讨论了芯片实验室技术与智能手机相结合在改善光学生物传感器的即时检测和便携性方面所取得的巨大进展。最后，综述讨论了人工智能的出现及其在生物光子学和医学成像领域用于新冠诊断的应用。综述最后对光学技术在有效诊断病毒方面的未来前景进行了展望。
