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. 2025 Jan 9;15(1):3.
doi: 10.1186/s12348-025-00456-y.

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

Shani Pillar  1   2 , Shin Kadomoto  3 , Keren Chen  4 , Saitiel Sandoval Gonzalez  1   2 , Nina Cherian  1   2 , Joseph K Privratsky  1   2 , Nicolette Zargari  1   2 , Nicholas J Jackson  4 , Giulia Corradetti  5 , Judy L Chen  1   2 , SriniVas R Sadda  2   5 , Gary N Holland  1   2 , Edmund Tsui  6   7   8
Affiliations

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

Shani Pillar et al. J Ophthalmic Inflamm Infect. .

Abstract

Purpose: To 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.

Methods: Eyes 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.

Results: 90 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).

Conclusions: Our 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.

Keywords: Anterior chamber inflammation; Image analysis; Optical coherence tomography (OCT); Standardization of Uveitis nomenclature (SUN); Uveitis.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: The study was approved by the UCLA Health Institutional Review Board (IRB#19-001732). Consent for publication: Written informed consent was obtained from all study participants, unless they were < 18 years of age, in which case written informed consent was obtained from a parent of the study participant and an additional assent document was signed by study participants 7 years of age and older. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Images of swept-source anterior segment optical coherence tomography single line-scans obtained just below the apex of the cornea, to avoid the apical light reflex. A representative scan is shown for eyes in each Standardized Uveitis Nomenclature (SUN) grade, as assigned by one of two uveitis experts using slit lamp biomicroscopy. Yellow spots in the anterior chambers represent hyperreflective foci counted automatically by a software algorithm
Fig. 2
Fig. 2
Scatter plot comparing manual versus automated counts of hyperreflective foci on the same set of single line-scan images obtained by swept-source anterior chamber OCT. The investigator who counted HRF manually was masked to SUN grades and automated counts. Interclass correlation is 0.99. The grey region in the plot represents the confidence interval (CI) for the estimated regression line
Fig. 3
Fig. 3
Box-and-whisker plot showing automated counts of hyperreflective foci on single line-scan images obtained by swept-source anterior chamber OCT grouped by clinician-assigned Standardized Uveitis Nomenclature (SUN) grades. Lines inside the boxes represent medians. Boxes identify the first and third quartiles. Red dots in the box-and-whisker plot reflect the representative examples seen in Fig. 1. There was a significant correlation between automated counts and SUN grades (Pearson correlation coefficient = 0.80, p < 0.001)
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