The cornea is the outermost tissue of the eye, and it is crucial for maintaining the structure and vision of the eye. However, everyday activities can expose the cornea to trauma-associated injuries and infections that may compromise vision. Common corneal detection techniques, such as slit lamp imaging, optical coherence tomography, and confocal microscopy, are based on a morphological structural analysis of the physiological status of the corneal tissue. However, they cannot provide information on tissue composition. Raman spectroscopy can obtain biomolecular information without damaging the tissue structure and has important application value in the detection of corneal tissue composition.

Analysis of the hydration state of the cornea using Raman spectroscopy can be used to evaluate tissue function and vitality. In 1995, Siew et al. characterized the degree of corneal hydration using the ratio of the intensity integral of the O—H of water to the intensity integral of the C—H of the protein in the Raman spectrum, I_OH/I_CH. In 1998, Bauer et al. determined a positive correlation between the degree of hydration and distance from the corneal stroma to the tear film. Bauer et al. and Erckens et al. observed that the value of I_OH/I_CH decreased as the cornea was treated with dehydrating agent drugs in subsequent research studies. In 2003, Fisher et al. determined that I_OH/I_CH of a bovine cornea treated with lamellar keratectomy decreased faster than that of a manually debrided cornea when the cornea was subjected to forced flow drying.

The distribution and content of biomolecules in the cornea change during corneal development, aging, decellularization, and corneal cross-linking (CXL) processes. In 2012, Pang et al. analyzed the changes in the vibrational patterns of proteins, amino acids (tyrosine, proline, phenylalanine, and valine), and protein secondary structures (amide I and amide II) in embryonic chicken corneas over 18 days of development. In 2010, Yamamoto et al. determined that solar radiation causes fragmentation of type IV collagen in the cornea, thereby increasing the Raman spectral background. The effects of the osmotic pressure regulator, decellularization method, and CXL on collagen molecules and the secondary structure of collagen were also demonstrated via Raman spectroscopy. Other applications of Raman spectroscopy to reveal changes in tissue composition due to corneal calcification and infection with protozoa and microorganisms demonstrated its potential for pathological analysis. In 2016, Kim et al. showed that for hereditary corneal diseases, such as corneal dystrophy, Raman spectroscopy can not only be used to reveal pathological tissue composition abnormalities, but also to detect disease-related gene point mutations. Raman spectroscopy and the establishment of machine learning models to classify corneal diseases have become new diagnostic methods. In 2021, Guan et al. classified the Raman spectra of normal and diabetic keratopathy mouse corneas using a PLS-DA model. In 2023, Han et al. used the PCA-KNN model to classify the degree of myopia.

Raman spectroscopy provides a new method for studying ocular pharmacokinetics. In 1999, Bauer et al. examined the changes in drug-specific Raman signals of the corneal epithelium of living rabbit eyes after topical application of Truspot with varying drug concentration and time. They found that Raman spectroscopy has sufficient sensitivity and reproducibility to reveal these variations. Subsequent studies demonstrated the application of Raman spectroscopy in the pharmacokinetic analysis of drugs such as besifloxacin, hybrid peptide VR18, hybrid peptide VR18, and steroids. Raman spectroscopy can also be combined with imaging techniques, such as TPAF, SHG, and TSFG, to obtain multidimensional information about samples. In 2012, Mortati et al. examined the collagen production process of living human corneal fibroblasts and mesenchymal stem cells cultured in a fibrin hydrogel 3D scaffold by combining CARS and SHG microscopic imaging technology. Subsequently, CARS combined with TPAF, SHG, and TSFG techniques was used to image corneal cells and biomolecules, and SERS was used for the plasma membrane bimolecular imaging of corneal endothelial cells.

Raman spectroscopy technology has yielded significant results in the field of corneal tissue composition detection. However, its clinical application still faces certain problems. First, owing to the weak relative power of Raman scattering light to incident light, indicating changes in the biochemical composition of the cornea remains a challenge for spectral sensitivity below the safe threshold of incident laser power. Second, the disease diagnosis and model generalization abilities of Raman spectroscopy combined with machine learning must be further improved for clinical applications. In response to these two issues, the following strategies are proposed. First, for the detection of different tissue components, using incident light wavelengths with a higher signal-to-noise ratio and incident light with a power density of the Bessel distribution may be a potential method for improving the sensitivity of Raman spectroscopy. Additionally, designing and manufacturing eye probes that are safe to use and have low optical power loss for focusing and collecting Raman-scattered light also shows great potential for improving the detection sensitivity. Second, with the development and maturity of optoelectronic devices, miniaturized and low-cost Raman spectroscopy devices are expected to be increasingly applied in clinical research, and more sample data can become a driving force for improving the performance of artificial intelligence models. In summary, Raman spectroscopy technology still has great potential for development in the analysis of corneal tissue composition and even in the research and clinical application of ophthalmology, and it is expected to lead to new changes in biomedical detection.