Analysis Of Ocular Surface Changes After Lenticule Extraction Using An Artificial Intelligence Based Non-Invasive Imaging Methodology.

Refractive surgery leads to dry eye disease (DED) and ocular discomfort characterised by loss of tear film homeostasis.  This study used a novel non-invasive artificial intelligence imaging methodology to assess changes in the ocular surface and impact on patient comfort after Lenticule extraction.

This was a prospective study of patients undergoing lenticule extraction.  A validated dry eye questionnaire was administered by a trained interviewer.

The assessment of the variability in ocular surface temperature using the Ocular Surface Imager (OSI) was done by an independent investigator blind to the questionnaire outcome. The compactness, convexity and severity scores were studied. Oculus keratograph (Oculus inc), Schirmer’s and Lipiview were done to assess the Ocular surface. Tests were performed prior to and one month after the procedure. OSI was additionally performed immediately after the procedure. Patients with history of ocular surgery, contact lens use and topical or systemic medication or diseases known to be associated with dry eye disease were excluded.  30 eyes of 30 patients were included in the study. Statistical analysis was performed using Mecalc Version 20.104.

Ocular surface imaging showed less severity, good compactness and convexity following lenticule extraction procedure. These findings showed better correlation with subjective patient comfort compared to traditional tear film metrics. Tear film metrics were well preserved post lenticule extraction.

Thermal imaging with OSI correlated better with patient complaints than traditional tear film metrics. Lenticule extraction does not cause significant worsening of tear film metrics. Further analysis and a larger sample size are required to further validate our findings