Evidence map›Paper›PMID 39786628›Full record

ArticleJournal of ophthalmic inflammation and infection2025

Automated quantification of anterior chamber cells using swept-source anterior segment optical coherence tomography.

Shani Pillar, Shin Kadomoto, Keren Chen, Saitiel Sandoval Gonzalez, Nina Cherian, Joseph K Privratsky, Nicolette Zargari, Nicholas J Jackson, Giulia Corradetti, Judy L Chen and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of ophthalmic inflammation and infection, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Shani PillarOcular Inflammatory Disease Center, UCLA Jules Stein Eye Institute, Los Angeles, USA.
Shin KadomotoDepartment of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Keren ChenDepartment of Medicine, Statistics Core, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, USA.
Saitiel Sandoval GonzalezOcular Inflammatory Disease Center, UCLA Jules Stein Eye Institute, Los Angeles, USA.
Nina CherianOcular Inflammatory Disease Center, UCLA Jules Stein Eye Institute, Los Angeles, USA.
Joseph K PrivratskyOcular Inflammatory Disease Center, UCLA Jules Stein Eye Institute, Los Angeles, USA.
Nicolette ZargariOcular Inflammatory Disease Center, UCLA Jules Stein Eye Institute, Los Angeles, USA.
Nicholas J JacksonDepartment of Medicine, Statistics Core, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, USA.
Giulia CorradettiDoheny Eye Institute, Pasadena, CA, USA.
Judy L ChenOcular Inflammatory Disease Center, UCLA Jules Stein Eye Institute, Los Angeles, USA.
SriniVas R SaddaDepartment of Ophthalmology, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, USA.
Gary N HollandOcular Inflammatory Disease Center, UCLA Jules Stein Eye Institute, Los Angeles, USA.
Edmund TsuiOcular Inflammatory Disease Center, UCLA Jules Stein Eye Institute, Los Angeles, USA. etsui@mednet.ucla.edu.

Funding

Objective Measures of Intraocular Inflammation in Pediatric Anterior UveitisK23EY032990 · NEI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI TSUI, EDMUND · 2021 to 2025
$1.2M
NEI NIH HHS K23 EY032990NIH HHS K23EY032990
6 · The paper itself

Abstract

purposeTo validate automated counts of presumed anterior chamber (AC) cells in eyes with histories of uveitis involving the anterior segment using swept-source (SS) anterior segment optical coherence tomography (AS-OCT) against manual counts and compare automated counts against Standardized Uveitis Nomenclature (SUN) criteria.

methodsEyes were imaged with the ANTERION SS AS-OCT device (Heidelberg Engineering). A fully automated custom algorithm quantified the number of hyper-reflective foci (HRF) in line-scan images. Automated and manual counts were compared using interclass correlation (ICC) and Pearson correlation coefficient. Automated counts were compared to SUN grades using a mixed-effects linear regression model.

results90 eyes (54 participants) were included; 67 eyes (41 participants) had histories of uveitis, while 23 eyes (13 healthy participants) served as controls. ICC comparing automated to manual counts was 0.99 and the Pearson correlation coefficient was 0.98. Eyes at each SUN grade with corresponding median HRF (interquartile range [IQR]) were: Grade 0, 42 eyes, 2 HRF (0,4); 0.5+, 10 eyes, 10 HRF (8,15); 1+, 9 eyes, 22 HRF (15,33); 2+, 3 eyes, 27 HRF; 3+, 2 eyes, 128 HRF; 4+, 1 eye, 474 HRF. For every 1-step increase in grade, automated count increased by 38 (p < 0.001) or 293% (Pearson correlation coefficient 0.80, p < 0.001). Automated counts differed significantly between clinically inactive eyes (2 HRF [0,4]) and controls (0 HRF [0,1], p = 0.02).

conclusionsOur algorithm accurately counts HRF when compared to manual counts, with strong correlation to SUN clinical grades. SS AS-OCT offers the advantage of imaging of the entire AC and may allow detection of subclinical inflammation in eyes that appear clinically inactive.

Indexed as

Anterior chamber inflammationImage analysisOptical coherence tomography (OCT)Standardization of Uveitis nomenclature (SUN)Uveitis

Identifiers

PMID39786628
PMCPMC11717729

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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.