Advances in Biomedical Applications of Raman Microscopy and Data Processing: A Mini Review. (4th March 2023)

• Record Type: Journal Article
• Authors: Krishna, Ram; Colak, Ilhami
• Is Part Of: Analytical letters. Volume 56:Number 4(2023)
• Page Start: 576
• Page End: 617
• Publication Date: 2023-03-04
• Subjects: Biological tissue characterization -- machine learning -- multivariant analysis -- principal component analysis -- Raman imaging; Chemistry, Analytic -- Periodicals; Chemistry, Analytic -- Abstracts; 543
• DOI: 10.1080/00032719.2022.2094391
• Languages: English
• ISSNs: 0003-2719

Abstract

Abstract: Raman spectroscopy is a powerful, noninvasive, and non-contactual vibrational spectroscopic technique. As an optical surface scanning technique, it is capable of detecting endogenous biomolecules inside cells and tissues and used to detect changes in structure and composition during the dysplastic transformation of cellular components. A combination of Raman spectroscopy and microscopy has also been used to study biomolecular processes at the cellular level. Moreover, Raman microscopy may be used to diagnose diseases noninvasively because it offers features such as in vivo and ex vivo imaging, rapid spectral acquisition, superior molecular sensing, deeper depth profiling, and superior chemical sensitivity. Additionally, it has capabilities for 3D sectioning, non-label imaging, pharmacokinetics analysis, and in situ monitoring of diseases and drugs. Raman microscopy has been shown to be successful in biomedical applications because healthy tissues differ significantly from diseased tissues in terms of chemical composition. Furthermore, various tags have been examined for the identification, diagnosis, and control of disease development based on a fundamental understanding of chemical processes with Raman imaging and spectroscopic measurements. This article provides an overview of Raman microscopy in biomedical research and applications. An emphasis is placed on how Raman imaging has been applied to different biomedical domains, such as disease monitoring and medical diagnostics. Further, the article discusses technological developments, data processing, and emerging technologies such as machine learning, before concluding with a discussion of the potential uses of these methods.