Impact of a Displaced Corneal Apex in Small Incision Lenticule Extraction

Optimizing Refractive Outcomes of SMILE: Artificial Intelligence versus Conventional State-of-the-Art Nomograms

PURPOSE

AI (artificial intelligence)-based methodologies have become established tools for researchers and physicians in the entire field of ophthalmology. However, the potential of AI to optimize the refractive outcome of keratorefractive surgery by means of machine learning (ML)-based nomograms has not been exhausted yet. In this study, we wanted to comprehensively compare state-of-the-art conventional nomograms for Small-Incision-Lenticule-Extraction (SMILE) with a novel ML-based nomogram regarding both their spherical and astigmatic predictability.

METHODS

A total of 1,342 eyes were analyzed for creation of three different nomograms based on a linear model (LM), a generalized additive mixed model (GAMM) and an artificial-neuronal-network (ANN), respectively. A total of 16 patient- and treatment-related features were included. Each model was trained by 895 eyes and validated by the remaining 447 eyes. Predictability was assessed by the difference between attempted and achieved change in spherical equivalent (SE) and the difference between target induced astigmatism (TIA) and surgically induced astigmatism (SIA). The root mean squared error (RMSE) of each model was computed as a measure of overall model performance.

RESULTS

The RMSE of LM, GAMM and ANN were 0.355, 0.348 and 0.367 for the prediction of SE and 0.279, 0.278 and 0.290 for the astigmatic correction, respectively. By applying the created models, the theoretical yield of eyes within ±0.50 D of SE from target refraction improved from 82 to 83% (LM), 84% (GAMM) and 83% (ANN), respectively. Astigmatic outcomes showed an improvement of eyes within ±0.50 D from TIA from 90 to 93% (LM), 93% (GAMM) and 92% (ANN), respectively. Subjective manifest refraction was the single most influential covariate in all models.

CONCLUSION

Machine learning endorsed the validity of state-of-the-art linear and non-linear SMILE nomograms. However, improving the accuracy of subjective manifest refraction seems warranted for optimizing ±0.50 D SE predictability beyond an apparent methodological 90% limit.

Methods of Corneal Vertex Centration and Evaluation of Effective Optical Zone in Small Incision Lenticule Extraction

Inappropriate small incision lenticule extraction (SMILE) centration methods can affect the decentration of the effective optical zone (EOZ) after operation, which can subsequently lead to the decline of postoperative visual quality. We aimed to provide an overview of corneal vertex (CV) centration methods and an evaluation of the size and decentration of the EOZ in SMILE. We described the CV centration methods for patients with myopia, myopic astigmatism, hyperopia, and large kappa angle. The measurement methods of the EOZ were evaluated from the aspects of corneal morphology and corneal refractive power. Additionally, we summarized the advantages and disadvantages of measuring decentration based on topographic mapping and intraoperative video-captured images. Finally, we discussed the relationship between the EOZ and visual quality. Based on our review, clinicians should consider the following when choosing CV centration methods and evaluating EOZ postoperatively. First, the tear film mark center or topographic map comparison method is preferred for the correction of myopia, low myopic astigmatism, hyperopia, and large kappa angle (>0.2 mm). Triple marking centration is recommended for high myopic astigmatism (-3.5 diopters). Second, the total corneal power better reflects the change in refractive power than the topographic method. The measurement of the area rather than the diameter of the total corneal refractive power is more suitable for the evaluation of noncircular EOZs after high myopia astigmatism (<-2.0 diopters). Third, for the evaluation of decentration, the tangential curvature difference map method is preferred as it is not influenced by offset pupils. Finally, a large EOZ after SMILE may improve patient tolerance to decentration.

Effect of keratometric astigmatism on visual outcomes following small incision lenticule extraction

Purpose

To investigate the influence of keratometric astigmatism on visual outcomes following small incision lenticule extraction (SMILE).

Methods

Eighty eyes undergoing SMILE for myopia correction were classified into two groups based on preoperative keratometric astigmatism: low keratometric astigmatism (LA) and high keratometric astigmatism (HA) groups. Refractive outcomes, vector components, and changes in higher order aberrations (HOAs) were evaluated preoperatively and 6 months postoperatively.

Results

At the postoperative 6-month visit, no significant difference was observed in the decentered distance between the HA and LA groups (HA: 0.17 ± 0.08 mm, LA: 0.16 ± 0.08 mm, P = 0.189). No significant differences in the correction index (P = 0.481), absolute angle of error (P = 0.104), or index of success (P = 0.147) were observed between the two groups. There was no significant difference in the induction of corneal aberrations between the two groups. Furthermore, there were no significant associations between the decentered distance and the vector components of astigmatic correction or induction of higher-order aberration in the HA group (P ≥ 0.294, P ≥ 0.112) or the LA group (P ≥ 0.323, P ≥ 0.080).

Conclusions

SMILE for high keratometric astigmatism could achieve comparable treatment centration and visual quality to that of low keratometric astigmatism

Determinants of subjective patient-reported quality of vision after small-incision lenticule extraction

PURPOSE

To characterize patient-reported long-term quality of vision (QoV) after small-incision lenticule extraction (SMILE), and to identify potential clinical parameters that might predispose to experiencing deteriorated visual quality.

SETTING

University Eye Hospital, Ludwig-Maximilians-University, Munich, Germany.

DESIGN

Prospective cross-sectional study.

METHODS

For the assessment and scoring of visual symptoms, the Quality of Vision questionnaire was employed, which constitutes a clinically validated, linear-scaled 30-item instrument providing a QoV score on three scales (symptom frequency, severity, and bothersome). Subgroup analyses were performed for patient subgroups stratified by baseline characteristics (eg, age) and treatment parameters (eg, surgical refractive correction) as well as refractive outcomes (eg, residual refraction) and visual outcomes (eg, uncorrected distance visual acuity [UDVA]).

RESULTS

The study comprised 394 eyes of 197 patients (117 women [59.4%], 80 men [40.6%]) were included with a mean postoperative follow-up of 24.4 months ± 14.1 (SD). The QoV scores for symptom frequency, severity, and bothersome were 34.63 ± 13.69, 29.60 ± 12.38, and 24.56 ± 16.00, respectively. Patients with a preoperative binocular corrected distance visual acuity (CDVA) of 20/12.5 or better, patients who lost 1 or more lines of UDVA as compared with preoperative CDVA, patients older than the age of 40, and patients with inadvertent anisometropia more than 0.375 diopters reported worse QoV scores.

CONCLUSION

The relationship between objective clinical parameters and patient-reported subjective QoV after SMILE seems complex. Defined prognostic factors that convey a higher risk for experiencing visual disturbances were identifiable and should be discussed with patients seeking SMILE treatment during preoperative counseling.