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Quantitative Stain-Free Conjunctival Collagen Imaging in Cicatrizing Conjunctivitis Using Second Harmonic
Ralene Sim1, Andri K Riau2,3, Nuur Shahinda Humaira Binte Halim2
1Corneal and External Eye Diseases Department, Singapore National Eye Centre, Singapore.
This study introduces quantitative collagen measures for cicatrizing conjunctivitis (CC) severity. Collagen area ratio (CAR) may aid diagnosis, while collagen fiber number (CFN)/mm² could predict disease progression.
Area of Science:
- Ophthalmology
- Biomaterials Science
- Pathology
Background:
- Cicatrizing conjunctivitis (CC) causes significant morbidity, with current scarring assessment relying solely on clinical evaluation.
- Objective, quantitative measures are needed to assess CC progression and severity.
- Collagen structure alterations are implicated in conjunctival scarring.
Purpose of the Study:
- To investigate collagen structure in cicatrizing conjunctivitis (CC).
- To identify sensitive and quantitative measures for assessing CC scarring severity.
- To correlate collagen morphometry with clinical disease severity scores.
Main Methods:
- Conjunctival tissues from CC patients and controls were analyzed using two-photon excitation and second harmonic generation microscopy.
- Collagen morphometry, including collagen area ratio (CAR) and collagen fiber number (CFN)/mm², was quantified using FibroIndex software.
- Results were correlated with a validated clinical severity assessment tool.
Main Results:
- Diseased conjunctival tissue showed significantly lower CAR and CFN/mm² compared to controls.
- CAR positively correlated with inflammation, scarring, morbidity, and overall composite scores in CC patients.
- CFN/mm² negatively correlated with inflammation, scarring, morbidity, and overall composite scores across all groups.
Conclusions:
- Collagen area ratio (CAR) demonstrates significant correlation with clinical scores, suggesting its potential as a reliable diagnostic marker for CC.
- Collagen fiber number (CFN)/mm² exhibits significant negative correlation with all assessed scores, indicating its potential as a predictive marker for CC severity.
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