{"doi":"10.1167/tvst.14.4.7","title":"Characterization of Directional Reflectance in Corneal Tissue: A Comprehensive Optical Coherence Tomography Analysis","abstract":"Purpose: To characterize the directional reflectance properties of the cornea using optical coherence tomography (OCT) imaging and develop a mathematical model describing corneal reflectance as a function of depth and incidence angle across different corneal layers. Methods: A retrospective analysis was conducted on OCT scans from normal subjects using the Visionix Avanti OCT system (840 nm). Reflectance values for the epithelium, Bowman's layer, stroma, and endothelium/Descemet's membrane were extracted and analyzed as functions of incidence angle and corneal depth. Reflectance distributions were assessed for normality. Exponential functions were fitted to the mean and 97th percentile reflectance data to model directional reflectance for each corneal layer. Results: Reflectance values exhibited non-normal leptokurtic distributions with right-tailed skewness, requiring non-parametric methods for percentile calculations. The exponential model incorporating angular dependence achieved R² values of 0.987 and 0.963 for mean and 97th percentile reflectance, respectively. The mean reflectance of the epithelium was modeled by a single exponential function, with half-reflectance angles of 15.9° to 26.6°. The stromal layers required two exponential components, with the anterior stroma exhibiting the highest reflectance and most pronounced directionality (half-reflectance angle of 0.17°). The 97th percentile reflectance differed, with higher reflectance values in the middle and posterior stroma. No statistically significant age or gender related variability in reflectance was measured. Conclusions: This study provides a detailed mathematical model of corneal directional reflectance, highlighting the importance of incidence angle and layer depth in OCT image analysis. Translational Relevance: The developed cornea reflectance model may improve OCT-based diagnostics by identifying early microstructural changes, aiding in the diagnosis and management of corneal diseases.","journal":"Translational Vision Science & Technology","year":2025,"id":543617,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.0,"corpus_percentile":22.178386323199504,"corpus_rank":9377,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.512,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1433187,"name":"Jiachi Hong","orcid":"0000-0003-4862-2928","position":1,"is_corresponding":false},{"id":1433188,"name":"Yan Li","orcid":"0000-0003-2052-6862","position":2,"is_corresponding":false},{"id":85579,"name":"David Huang","orcid":"0000-0002-5569-6442","position":3,"is_corresponding":false},{"id":1388702,"name":"Jad F. Assaf","orcid":"0000-0003-4963-7339","position":0,"is_corresponding":true}],"reference_count":32,"raw_metadata":null,"created_at":"2026-07-19T02:53:04.088079Z","pmid":"40178474","pmcid":"PMC11977791","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}