Digital Colorimetric Scale for Recurrent Pterygium Scar Assessment

Pterygium is a common ocular surface disorder characterized by a fibrovascular proliferation of conjunctival tissue extending onto the cornea. Despite surgical treatment, recurrence remains a frequent complication, and postoperative conjunctival scarring is often associated with disease recurrence and ocular surface inflammation. Currently, the clinical evaluation of conjunctival scarring and hyperemia is largely subjective and depends on slit-lamp examination, which may lead to variability between observers.

The objective evaluation of conjunctival vascularization and scar-related changes could improve the standardization of postoperative assessments and allow better monitoring of disease progression or recurrence. Digital image analysis has emerged as a useful tool for quantifying ocular surface features such as vascular density, redness, and tissue morphology.

The purpose of this observational study is to evaluate and validate a digital colorimetric scale designed to objectively quantify conjunctival scarring associated with recurrent pterygium. The study will analyze anterior segment photographs obtained during routine ophthalmologic examinations.

Digital slit-lamp photographs will be collected from patients diagnosed with recurrent pterygium. Images will be analyzed using the open-source software Fiji/ImageJ, which allows quantitative analysis of colorimetric and vascular parameters. Image processing algorithms will be applied to extract objective measurements related to conjunctival redness and vascular density within the scarred conjunctival tissue.

Measurements will be obtained from standardized regions of interest within the conjunctiva. Quantitative parameters will include colorimetric intensity values, vascular pixel density, and other digital markers of conjunctival hyperemia. These measurements will be compared with clinical assessments performed by ophthalmologists in order to evaluate the reliability and reproducibility of the proposed colorimetric scale.

Statistical analyses will be performed to determine the correlation between the digital measurements and clinical grading systems. Interobserver agreement and measurement reproducibility will also be evaluated.

The findings of this study may contribute to the development of standardized digital tools for the objective assessment of conjunctival scarring in patients with recurrent pterygium. Such tools may improve clinical monitoring and facilitate future research on ocular surface diseases and postoperative outcomes.

Primary outcomes

• Quantitative Assessment of Conjunctival Vascularization Using Digital Colorimetric Image Analysis [Baseline (at time of clinical image acquisition)]: Conjunctival vascularization associated with pterygium will be quantified using digital image analysis of slit-lamp photographs. Images will be processed with Fiji/ImageJ software to measure vascular pixel density and colorimetric intensity values within a defined conjunctival region of interest.

Secondary outcomes

• Correlation Between Digital Vascular Density and Clinical Hyperemia Grading [Baseline]: Correlation between vascular density quantified through digital image analysis and clinical grading of conjunctival hyperemia performed during slit-lamp examination.

Sex: All, ages: 18 Years to any

Inclusion Criteria:

* Adults aged 18 years or older.
* Patients diagnosed with primary or recurrent pterygium.
* Availability of slit-lamp anterior segment photographs suitable for digital image analysis.
* Ability to provide informed consent for participation in the study.

Exclusion Criteria:

* Presence of other ocular surface diseases that may interfere with conjunctival vascularization assessment.
* Previous ocular surgery unrelated to pterygium that may alter conjunctival anatomy.
* Poor quality slit-lamp photographs that do not allow reliable digital image analysis.
* Incomplete clinical data.

• Jose Adrian Negrete, MD, Principal investigator, ✔ Instituto de Oftalmología Fundación Conde de Valenciana IAP