CORRELATION OF ANTERIOR SEGMENT OCT INFLAMMATION MEASUREMENT, CLINICAL GRADING AND FLOW CYTOMETRY
Published 2023
- 27th ESCRS Winter Meeting
Reference: MP5
| Type: Presented Poster & Poster Submission
| DOI:
10.82333/z8s3-nn89
Authors:
Ivan Potapenko* 1
, Martin Sorkhabi 1
, Maria Kyhn 1
, Christel Jørgensen 1
, Srdjan Zelenbabic 1
, Javier Cabrerizo 2
1Dept. of Ophthalmology, Rigshospitalet, Copenhagen, Denmark,Copenhagen,Denmark, 2Dept. of Ophthalmology, Rigshospitalet, Copenhagen, Denmark,Copenhagen,Denmark;Department of Clinical Medicine, University of Copenhagen,Copenhagen,Denmark;Copenhagen Eye Foundation,Copenhagen,Denmark
Purpose
Assessment of inflammation using the Standardisation of Uveitis Nomenclature (SUN) guidelines is prone to subjectivity and inter-grader variability. We attempt to correlate an artificial intelligence (AI) based anterior segment (AS) OCT analysis method of quantifying inflammation to SUN grading and flow cytometry.
Setting
Dept. of Ophthalmology, Rigshospitalet, Copenhagen, Denmark
Methods
In total 180 eyes of 148 patients undergoing anterior segment surgery were included in the study. Each eye was assessed with three inflammation assessment procedures: a pre-operative Standardisation of Uveitis Nomenclature (SUN) grading (evaluated by an experienced clinician) and AS-OCT analysis (using a novel AI-based approach), as well as flow cytometry of the aqueous humour aspirated per-operatively (measuring the total leucocytic cell concentration). To determine relationship between the measurements Spearman’s rank correlation coefficient was used.
Results
Correlation was low but statistically significant between SUN grading and AI-based OCT particle density (rho=0.31, p<0.001), SUN and flow cytometry (rho=0.27, p=0.001), and OCT and flow cytometry (rho=0.18, p=0.014).
Conclusion
The AI AS-OCT analysis is a novel, objective, method for quantification of inflammation, but further research needs to determine its place in the clinical practice.