EyeWorld Korea March 2021 Issue

A Fresh Perspective on SMILE in the time of COVID-19 Optical Quality and Intraocular Scattering after Femtosecond Laser SMILE Mathematical and Predictive Modeling in SMILE Surgery Another precautionary technique is to perform a betadine gargle and nasal spray before procedures as it kills all the germs in the mucosa, even in COVID-19 positive patients. Dr. Gaurav Luthra Dr. Xingtao Zhou presented next on optical quality and intraocular scat- tering after SMILE procedures. In his study, Dr. Zhou assessed the devel- opment of the continuous curvilinear lenticulerrhexis (CCL) technique for SMILE. Out of 31 eyes (20 patients), the CCL technique was utilized in 16 eyes while the traditional technique was used in 15 eyes. CCL depends on laser scanning quality and is per- formed by using forceps to separate both the anterior surface and poste- rior surface of the lenticule from the cap. Then, the forceps are used to extract the lenticule without irrigation. Follow-up was performed at one day and one month following surgery. The results showed that CCL technique exhibited excellent safety and efficacy for myopia correction compared with the traditional technique. In a different study, Dr. Zhou studied 66 eyes with stable refrac- tion for 2 years undergoing SMILE. Dr. Zhou utilized the optical quality analysis system (OQAS) to obtain retinal image quality and intraocular scattering parameters. At 3-month follow-up, the results showed that the objective scattering index (OSI) initial- ly increased, but decreased signifi- cantly over time. Modulation transfer function (MTF) cutoff also improved at 3 months. From Dr. Zhou’s research, he dis- cussed that since the high order ab- errations (HOAs) and the scatterings are two independent factors affecting retinal image quality, an assessment of optical quality after refractive sur- gery needs to take into consideration the influence of intraocular scattering. Additionally, patients with lower intra- ocular scattering tend to get higher MTF cutoff scores and a lower OSI value after SMILE. OSI actually is a reliable parameter in predicting MTF cutoff scores, and thus a similar result was also reported in LASIK. The next presentation was given by Dr. Abhijit Sinha Roy, who discussed predictions of the biomechanical status of the cornea after surgery. The OCULUS Corvis® ST combines an air FIgure 2. Intra-class correlation efficient of predicted postoperative corneal stiffness compared to artificial intelligence (AI) predicted corneal stiffness shows higher correlation with AI. Source: Francis M et al. Invest Ophthalmol Vis Sci 2018. “ ” pulse tonometer with an ultra-high- speed Scheimpflug camera allowing clinicians to visualize in-vivo corneal biomechanical index (CBI) and the stress strain index (SSI). However, it is currently still not possible to predict post-operative biomechanics using these parameters. Dr. Roy’s research has been focusing on predicting post refractive surgery biomechanics in the last few years. If one builds a mathematical model using OCULUS Corvis ® and OCULUS Pentacam® using both of the data sets, one can derive the corneal biomechanical properties. Additionally, Dr. Roy can use the preoperative biomechanical status of the cornea to perform virtual SMILE on patients and in turn predict the postoperative deformation curve. Although SMILE and LASIK are structurally two different surger- ies, acute biomechanical effects of flap and cap cuts did not influence 1-week and 1-month measurements in both surgeries. However, visualizing the biomechanical response of the cornea using OCULUS Corvis ® intra- operatively, the LASIK-flap caused more weakening than the SMILE-cap. In an ongoing study conducted by Dr. Roy, predicted postoperative corneal stiffness was compared to in-vivo measurements and showed an intra-class correlation coefficient of 0.91 with LASIK, SMILE, and PRK. Including artificial intelligence adjusted predicted corneal stiffness resulted in an even higher intra-class correlation coefficient of 0.95. In application, if postoperative outcome does not match the parameters that the computational model provides, there may be an indication of ectasia or other abnormality. Media placement sponsored by Carl Zeiss Meditec AG Not all products, services or offers are approved or offered in every market and approved labeling and instructions may vary from one country to another. The statements of the authors of this supplement reflect only their personal opinion and experience and do not necessarily reflect the opinion of Carl Zeiss Meditec AG or any institution with whom they are affiliated. Carl Zeiss Meditec AG has not necessarily access to clinical data backing the statements of the authors.The statements made by the authors may not yet been scientifically proven and may have to be proven and/or clarified in further clinical studies. Some information presented in this supplement may only be about the current state of clinical research and may not be part of the official product labeling and approved indications of the product. The authors alone are responsible for the content of this supplement and any potential resulting infringements resulting from, in particular, but not alone, copyright, trademark or other intellectual property right infringements as well as unfair competition claims. Carl Zeiss Meditec AG does not accept any responsibility or liability of its content. EN_34_021_0064I