Validation of AI-based Software for Objectification of Conjunctival Provocation Test

Background: Provocation tests are widely used in allergology to objectively reveal patients' sensitivity to specific allergens. The objective quantification of an allergic reaction is a crucial characteristic of these tests. Because of the absence of objective quantitative measurements, the conjunctival provocation test (CPT) is a less frequently used method despite its sensitivity and simplicity.

Objective: We developed a new artificial intelligence (AI)-based method, called AllergoEye, for quantitative evaluation of conjunctival allergic reactions and validated it in a clinical study.

Methods: AllergoEye was implemented as a 2-component system. The first component is based on an Android smartphone camera for screening and imaging the patient's eye, and the second is personal computer-based for image analysis and quantification. For the validation of AllergoEye, an open-label, prospective, monocentric study was carried out on 41 patients. Standardized CPT was performed with sequential titration of grass allergens in 4 dilutions, with the reaction evaluated by subjective/qualitative symptom scores and by quantitative AllergoEye scores.

Results: AllergoEye demonstrated high sensitivity (98%) and specificity (90%) as compared with human estimation of allergic reaction. Tuning cutoff thresholds allowed us to increase the specificity of AllergoEye to 97%, at which point the correlation between detected sensitivity to allergen and specific IgE carrier-polymer system class becomes obvious. Strikingly, such correlation was not found with sensitivity to allergen detected on the basis of subjective and qualitative symptom scores.

Conclusion: The clinical validation demonstrated that AllergoEye is a sensitive and efficient instrument for objective measurement of allergic reactions in CPT for clinical studies as well as for routine therapy control.