Development of low laser energy levels in small-incision lenticule extraction: clinical results, black area, and ultrastructural evaluation

Comparing high and low energy outcomes on day one for SmartSight myopic-astigmatism treatments with the SCHWIND ATOS: a retrospective case series

BACKGROUND

Impact of low energy asymmetric spacings vs. high energy symmetric spacings on the immediate/early (postoperative day 1 (POD1)) outcomes of SmartSight lenticule extraction for myopic astigmatism with a new femtosecond laser system.

METHODS

The first 112 eyes of 56 patients consecutively treated using low energy asymmetric spacings (Group A; Study group) were compared at POD1 to the last 112 eyes of 56 patients consecutively treated using high energy symmetric spacings (Group S; Controls). Mean age of the patients was 28 ± 5 years with a mean spherical equivalent of -4.41 ± 1.76 diopters (D) and a mean magnitude of refractive astigmatism of 0.89 ± 0.82 D.

RESULTS

Laser Energy was -25 ± 1nJ lower for asymmetric treatments (p < .0001); Spot and Track distances were + 0.7 ± 0.1 µm larger and -0.8 ± 0.1 µm tighter for asymmetric treatments, respectively (p < .0001 for both). At POD1, astigmatism was -0.08 ± 0.02D lower for asymmetric treatments (p < .0003); uncorrected and corrected visual acuities (UDVA and CDVA, respectively) were -0.03 ± 0.01logMAR better for asymmetric treatments (p < .0007); differences between postop UDVA and preop CDVA along with change in CDVA were + 0.3 ± 0.1lines better for asymmetric treatments (p < .0003).

CONCLUSIONS

Lenticule extraction treatment using SmartSight is safe and efficacious already at POD1. Findings suggest that low energy asymmetric spacings may further improve the immediate and short-term outcomes of SmartSight lenticule extraction in the treatment of myopic astigmatism compared to conventional settings (high energy symmetric spacings).

Prediction of Early Visual Outcome of Small-Incision Lenticule Extraction (SMILE) Based on Deep Learning

INTRODUCTION

Deep learning (DL) has been widely used to estimate clinical images. The objective of this project was to create DL models to predict the early postoperative visual acuity after small-incision lenticule extraction (SMILE) surgery.

METHODS

We enrolled three independent patient cohorts (a retrospective cohort and two prospective SMILE cohorts) who underwent the SMILE refractive correction procedure at two different refractive surgery centers from July to September 2022. The medical records and surgical videos were collected for further analysis. Based on the uncorrected visual acuity (UCVA) at 24 h postsurgery, the eyes were divided into two groups: those showing good recovery and those showing poor recovery. We then trained a DL model (Resnet50) to predict eyes with early postoperative visual acuity of patients in the retrospective cohort who had undergone SMILE surgery from surgical videos and subsequently validated the model's performance in the two prospective cohorts. Finally, Gradient-weighted Class Activation Mapping (Grad-CAM) was performed for interpretation of the model.

RESULTS

Among the 318 eyes (159 patients) enrolled in the study, 10,176 good quality femtosecond laser scanning images were obtained from the surgical videos. We observed that the developed DL model achieved a high accuracy of 96% for image prediction. The area under the curve (AUC) value of the DL model in the retrospective cohort was 0.962 and 0.998 in the training and validation datasets, respectively. The AUC values in two prospective cohorts were 0.959 and 0.936. At the video level, the trained machine learning (ML) model (XGBoost) also accurately distinguished patients with good or poor recovery. The AUC value of the ML model was 0.998 and 0.889 in the retrospective cohort (training and test datasets, respectively) and 1.000 and 0.984 in the two prospective cohorts. We also trained a DL model which can accurately distinguish suction loss (100%), black spots (85%), and opaque bubble layer (96%). The Grad-CAM heatmap indicated that our models can recognize the area of scanning and precisely identify intraoperative complications.

CONCLUSIONS

Our findings suggest that artificial intelligence (DL and ML model) can accurately predict the early postoperative visual acuity and intraoperative complications after SMILE surgery just using surgical videos or images, which may display a great importance for artificial intelligence in application of refractive surgeries.

Twelve-month outcomes of a new refractive lenticular extraction procedure

BACKGROUND

To evaluate the 12-month refractive and visual outcomes of Small Incision Guided Human-cornea Treatment (SmartSight®, SCHWIND eye-tech-solutions, Kleinostheim, Germany) in the treatment of myopia corrections with low to moderate astigmatism with the use of a new femtosecond laser system.

METHODS

221 eyes of 114 patients consecutively treated with SmartSight lenticule extraction were assessed. The mean age of the patients was 28±6 years at the time of treatment with a mean spherical equivalent refraction of -6.26±2.17D and mean astigmatism of 0.92±0.68D. Monocular corrected distance visual acuity (CDVA), uncorrected distance visual acuity (UDVA) were assessed pre- and post-operatively. Refractive changes have been determined in terms of changes in refraction, as well as changes in keratometric readings. The changes in central epithelial thickness have been determined.

RESULTS

At twelve months post-operatively, mean UDVA was 20/21±2. Spherical equivalent showed a residual refraction of +0.48±0.31D with refractive astigmatism of 0.13±0.18D postoperatively. There was a slight decrease of -0.1 Snellen lines at 12-months follow-up. The same correction was determined using changes in refraction, as well as changes in keratometric readings. The central epithelial thickness increased by +3±2µm. Spherical equivalent correction within ±0.50D was achieved in 199 eyes (90%), and cylindrical correction in 221 (100%). Preoperative corrected distance visual acuity (CDVA) was 20/20 or better in 213 eyes (96%), and postoperative uncorrected (UDVA) was 20/20 or better in 205 eyes (93%). No eye had lost two or more Snellen lines of CDVA.

CONCLUSIONS

Myopic astigmatism correction with SmartSight provided good results for efficacy, safety, predictability, and visual outcomes at the twelve months of follow up. The central epithelial thickness barely increased by 3±2µm.

Analytical optimization of the cutting efficiency for generic cavitation bubbles

A theoretical method to determine the optimum laser parameters for maximizing the cutting efficiency for different materials (in particular human cornea) is proposed. The model is simple and reduced to laser beam characteristics and cavitation properties. The model further provides a method to convert energy fluctuations during the cutting process to equivalent deviations in the cavitation bubbles. The proposed model can be used for calibration, verification and validation purposes of laser systems used for cutting processes at relatively low cost and may improve the quality of the results.