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Updated: Jun 2, 2025

Full-Field Optical Coherence Microscopy for Histology-Like Analysis of Stromal Features in Corneal Grafts
Published on: October 21, 2022
Biochemical components of corneal stroma: a study on myopia classification based on Raman spectroscopy and deep
Zhe Yu1, Yong Li1, Tingyan Xing2,3,4
1Shaanxi Eye Hospital, Xi'an People's Hospital (Xi'an Fourth Hospital, Affiliated People's Hospital of Northwest University), No 4. Jiefang Road, Xin-Cheng District, Xi'an 710004, Shaanxi, China.
Abstract:
The study aimed to identify differences in the biochemical composition of corneal stroma lenses across varying degrees of myopia using Raman spectrum characteristics. Corneal stroma lens samples from 38 patients who underwent small incision lens extraction (SMILE) surgery, were categorized into low (n = 9, spherical power -3.00D), moderate (n = 23, spherical power < -3.00D and > -6.00D), and high myopia (n = 6, spherical power ≦-6.00D) groups. A custom-built microscopic confocal Raman system (MCRS) was used to collect Raman spectra, which were processed by smoothing, denoising, and baseline calibrating to refine raw data. Independent sample t-tests were used to analyze spectral feature peaks among sample types. Significant differences (P < 0.001) were found in multiple Raman spectral characteristic peaks (854 cm-1, 937 cm-1, 1002 cm-1, 1243 cm-1, 1448 cm-1, and 2940 cm-1) between low and high myopia samples, particularly at 2940 cm-1. Differences were also found between low and moderate, and moderate and high myopia samples, although fewer than between low and high myopia samples. The three-classification model, particularly with PLS-KNN training, exhibited superior discriminative performance with accuracy rates of 95%. Similarly, the two-classification model for low and high myopia achieved high accuracy with PLS-KNN (94.4%) compared to PCA-KNN (93.3%). PLS dimensionality reduction slightly outperformed PCA, enhancing classification accuracy. In addition, in both reduction methods, the KNN algorithm demonstrated the highest accuracy and performance. The optimal PLS-KNN classification model showed AUC values of 0.99, 0.98, and 1.00 for ROC curves corresponding to low, moderate, and high myopia, respectively. Classification accuracy rates were 89.7% and 96.9%, and 100% for low and high myopia, respectively. For the two-classification model, accuracy reached 94.4% with an AUC of 0.98, indicating strong performance in distinguishing between high and low myopic corneal stroma. We found significant biochemical differences such as collagen, lipids, and nucleic acids in corneal stroma lenses across varying degrees of myopia, suggesting that Raman spectroscopy holds substantial potential in elucidating the pathogenesis of myopia.
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