Anterior chamber cell grading by optical coherence tomography

Yan Li, Careen Lowder, Xinbo Zhang, David Huang

Research output: Contribution to journalArticlepeer-review

52 Scopus citations


PURPOSE. To quantify cells in the ocular anterior chamber (AC) by optical coherence tomography (OCT). METHODS. A time-domain anterior segment OCT system was used to image latex microsphere suspensions in vitro and the AC of uveitis and normal subjects in vivo. The OCT scan pattern, consisting of 2- and 4-mm-diameter concentric circular scans, was divided into central, superior, and inferior regions. A computer algorithm was developed to automatically identify particles in OCT images. A uveitis specialist used slit-lamp biomicroscopy to grade the AC cells on a scale of 0 to 4+. RESULTS. Latex microspheres and AC cells were visualized as reflective spots in OCT images. OCT latex microsphere concentration measurements were highly correlated to known particle concentrations (r = 1.000) and had an efficiency of 0.72. In 30 nongranulomatous and 12 granulomatous eyes, the OCT cell counts correlated well with slit-lamp grades in all three regions (Spearman's rho coefficient: >0.63). The average OCT cell count was 3.7 cells/grade in nongranulomatous eyes and 2.0 cells/grade in granulomatous eyes. OCT revealed significant amounts of inferior AC cells in 5 of 16 quiescent uveitis eyes (mean ± SD: 19.9 ± 7.4 cells). OCT captured rare cells in normal eyes (1.1 ± 1.1 cells centrally). CONCLUSIONS. OCT provided quantitative information on AC inflammatory cells. The OCT cell counts correlated well with clinical grading, and particles in the inferior AC that were missed by slit-lamp examination were detected by OCT. OCT could be a valuable tool for the diagnosis and management of anterior uveitis.

Original languageEnglish (US)
Pages (from-to)258-265
Number of pages8
JournalInvestigative Ophthalmology and Visual Science
Issue number1
StatePublished - Jan 2013

ASJC Scopus subject areas

  • Ophthalmology
  • Sensory Systems
  • Cellular and Molecular Neuroscience


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