Analysis of ocular inflammation in anterior chamber-involving uveitis using swept-source anterior segment OCT.
Int Ophthalmol
; 39(8): 1793-1801, 2019 Aug.
Article
em En
| MEDLINE
| ID: mdl-30238391
ABSTRACT
PURPOSE:
To evaluate the utility of swept-source (SS) optical coherence tomography (OCT) to objectively analyze the degree of anterior chamber (AC) inflammation.METHODS:
Thirty-eight eyes of 32 patients with uveitis and 20 control eyes were enrolled. SS OCT B-scans were obtained, and the number of cells in the B-scans was counted using twomethods:
(1) manual grading by Point Picker plug-in of Image J ( http//bigwww.epfl.ch/thevenaz/pointpicker/ ) and (2) automated grading by the Image J Particle Analysis algorithm ( http//imagej.net/Particle_Analysis ). The automated and manual AC cell counts were correlated with the Standardization of Uveitis Nomenclature score.RESULTS:
The average numbers of AC inflammatory cells counted by the automated method were 8 ± 4.0, 18 ± 3.0, 42 ± 14.0, 81 ± 32.0, 117 ± 57.0, and 275 ± 67.0 cells/mm2 for grades 0, 0.5 + , 1 + , 2 + , 3 + , and 4 + , respectively. For the same clinical categories, the average manual cell counts were 6 ± 4.0, 18 ± 3.0, 34 ± 14.0, 72 ± 32.0, 92 ± 43.0, and 168 ± 65.0 cells/mm2, respectively. Zero cells were detected in the AC of healthy eyes. The automated and manual methods were highly correlated (R = 0.98, p < 0.001) and showed good correlation with the clinical grading (R = 0.88, p < 0.001). A mean AC particle size of 117.4 ± 108.8 µm was obtained by the automated method.CONCLUSIONS:
Quantification of the AC cells imaged by SS AS-OCT shows good correlation with categorical clinical severity assessments in uveitis eyes. This approach may provide a more objective method for monitoring uveitis and response to uveitis therapy.Palavras-chave
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Base de dados:
MEDLINE
Assunto principal:
Uveíte Anterior
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Tomografia de Coerência Óptica
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Câmara Anterior
Tipo de estudo:
Diagnostic_studies
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Guideline
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Observational_studies
Limite:
Adolescent
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Adult
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Aged
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Aged80
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Child
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article