Grading Image Scale (G.I.S) for anterior chamber cell count in patients with anterior chamber inflammation
Purpose
To develop a systematic tool to be used by clinicians during diagnosis and follow-up of ocular anterior chamber inflammation. Anterior uveitis is composed of few inflammatory conditions (i.e. traumatic, post-surgical, Idiopathic, associated with rheumatic diseases and other autoimmune diseases) with a common denominator of white cells infiltrating the anterior chamber (AC) of the eye. Often, damaged AC vessels secrete proteins, resulting in milky appearance of the anterior chamber called flare. The prognosis of untreated anterior uveitis is guarded, often leading to severe visual impairment and even blindness. One of the major challenges in uveitis is a proper evaluation of disease severity based on the extent of cell infiltration to the anterior chamber, and to a lesser extent, changing levels of flare when relevant. Moreover, lack of systematic tools of AC cell counting result in a significant challenge in clinical studies accurately measuring the impact of drug therapy on anterior chamber inflammation.
Methods
A set of images representing different scores of Anterior Chamber Cells (ACC) grades were created according to the following scale: Grade 0 – zero cells; grade 1 – 1-5 cells; grade 2 – 6-15 cells; grade 3 – 16-30 cells and grade 4 – more than 30 cells. For each grade, 3 different images were created. Tarsius Grading Image Scale (GIS) software was implemented using Python. User software interaction was through intuitive graphical user interface and fluid transition between (1) test phase in which the user is learning the score mechanics, and (2) main scoring phase in which the user grade randomized images representing different ACC grades. Uveitis experts used the software to grade the different images and the consistency between experts was calculated. The consistency threshold was set to > 75%.
Results
Grading results of 11 uveitis experts were analyzed and the scoring of the images were found to be consistent between experts and above the set threshold. The higher consistency was found for the lower ACC grades of 0, 1 and 2 (98%, 93% and 91% respectively) and lower consistency for ACC grades 3 and 4 (77% and 83% respectively).
Conclusion
Tarsius ACC Grading Image Scale is an important step toward a systematic AC cell counting. Further analysis of the applicability of this tool for clinical studies is needed.
Conflict of interest
No
Authors 1
Last name
DE SMET
Initials of first name(s)
M
Country
Switzerland
Authors 2
Last name
NEUMANN
Initials of first name(s)
R
Country
Israel
Authors 3
Last name
HAIM-LANGFORD
Initials of first name(s)
D
Country
Israel
Authors 4
Last name
MILMAN
Initials of first name(s)
Z
Authors 5
Last name
KREMER
Initials of first name(s)
M
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