Evidence map›Paper›PMID 42020698›Full record

ArticleScientific reports2026

Anterior chamber inflammation grading with automatized image processing software.

Halil İbrahim Aydoğdu, Fatime Nilüfer Yalçindağ

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Halil İbrahim AydoğduKozluk State Hospital, Batman, Turkey. ibrahimaydogdu@live.com.ORCID http://orcid.org/0009-0000-6361-7313
Fatime Nilüfer YalçindağDepartment of Ophthalmology, Ankara University Faculty of Medicine, Ankara, Turkey.ORCID http://orcid.org/0000-0002-8963-5146

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anterior segment optical coherence tomography (AS-OCT) is a non-invasive imaging modality to assess anterior ocular structures at micron levels. AS-OCT image processing has been implemented in evaluating anterior chamber inflammation with differing approaches and biomarkers across studies. The primary objective of this study was to evaluate the agreement between AS-OCT–derived cell count and cell density and slit-lamp based anterior chamber cell grading using the Standardization of Uveitis Nomenclature (SUN) criteria. Secondarily, we aimed to integrate multiple AS-OCT–based biomarkers reported in prior studies into a single rule-based computational framework. We analyzed 450 images from 92 AS-OCT scans of 79 eyes (48 non-infectious, 10 infectious, 21 control) for cell count, density, morphology (area, eccentricty), aqueous-to-air relative intensity (ARI) index and anterior chamber (AC) area. Cell count and cell density were significantly different for each SUN grading score (p < 0.001). There was a significant positive correlation between the SUN grading score and ARI index (Spearman’s p < 0.001 rho = 0.410) and cell area (Spearman’s p < 0.001 rho = 0.22). Eyes with active inflammation demonstrated significantly higher ARI index (100.48[5.14] vs. 99.12[2.57] p < 0.001 r = 0.25, %95 CI [1.22, 2.71]) and eccentricity ( 0.57[0.19] vs. 0.00[0.75], p = 0.05, r = 0.11, %95 CI [0.00, 0.52]) than control eyes. No significant differences were found in cell morphology (area, eccentricity) between infectious and non-infectious uveitis. Automated AS-OCT based image processing provided a rule-based, device-specific computational framework for quantifying AC inflammation that alings with clinical grading and it may serve as a complementary tool for assessing anterior chamber inflammation in uveitis.

Indexed as

Anterior ChamberImage Processing, Computer-AssistedInflammationSoftwareTomography, Optical CoherenceUveitisCell CountHumansAnterior chamber inflammationImage processingMATLABSUN gradingUveitis

Identifiers

PMID42020698
PMCPMC13269993

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.