Hyperopic Q-optimized algorithms: a theoretical study on factors influencing optical quality

Jiménez, José María López; Alarcón, Aixa; Anera, Rosario G.; Barco, Luis Jiménez del

doi:10.1364/boe.8.001405

Cited by 6 publications

(4 citation statements)

References 36 publications

(52 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In LASIK, monovision is a method of presbyopic correction, in which one eye is corrected for distance vision and the other eye for near vision, and this procedure is based on Q factor modulation. In addition, the Q factor was adjusted in both eyes, which induced an increase in the negative Q factor and improved the prolate shape (hyperprolateness) of the cornea 20 , and using Q-optimized algorithms improves visual quality for myopia in terms of the modulation transfer function (MTF) 21 , 22 . Our analysis showed that NaF strip application did not cause a statistically significant change in the measurement of Q value; therefore, we considered that NaF strip intervention would not significantly influence the preoperative planning in LASIK with a custom Q-ablation profile.…”

Section: Discussionmentioning

confidence: 99%

Effect of sodium fluorescein strip application on cornea parameters commonly used in laser-assisted in-situ keratomileusis

Han,

Xie,

Yuan

et al. 2023

Sci Rep

View full text Add to dashboard Cite

To assess the effect of sodium fluorescein (NaF) strip on corneal parameters commonly used in Laser-assisted in-situ keratomileusis (LASIK). Eighty-six subjects (172 eyes) scheduled for LASIK were recruited between January and March 2022. The study and statistical analysis test were conducted in April 2022. Topographic measurements of corneal parameters, including central corneal thickness (CCT), anterior keratometric (K) readings (K1, flat keratometry; K2, steep keratometry), horizontal corneal diameter (white to white, WTW), and corneal asphericity (Q value), were obtained using a Scheimpflug device (Pentacam) before and 10 min after NaF strip treatmentThe Pentacam recorded a small significant increase in CCT (mean 538.88 ± 28.78 μm to 547.90 ± 29.94 μm; p < .001), with no differences in K1 and K2 (mean 42.24 ± 1.35D to 42.24 ± 1.35D, and mean 43.34 ± 1.50D to 43.32 ± 1.51D; P > .05, for all) as well as WTW(mean 11.58 ± 0.32 mm to 11.58 ± 0.32 mm, P > .05) before and after NaF strip intervention. Furthermore, there was no significant difference was observed in Q value (mean − 0.30 ± 0.13 to − 0.30 ± 0.14, P > .05). These results indicate that clinicians should avoid NaF strip application before obtaining precise topographic measurements of cornea parameters using the Pentacam.

show abstract

Section: Discussionmentioning

confidence: 99%

Effect of sodium fluorescein strip application on cornea parameters commonly used in laser-assisted in-situ keratomileusis

Han,

Xie,

Yuan

et al. 2023

Sci Rep

View full text Add to dashboard Cite

show abstract

“…The main focus of this study was the optical performance, but we will consider the effect of the interactive optical-neural performance on visual perception in our following studies. Although designed for Femto-LASIK, this eye modeling method could be utilized in other types of myopic surgeries 4 and corneal surgeries, such as treatments of hyperopia 61 and keratoconus 62 .…”

Section: Discussionmentioning

confidence: 99%

Customized eye modeling for optical quality assessment in myopic femto-LASIK surgery

Lan

Zeng

et al. 2021

Sci Rep

View full text Add to dashboard Cite

Refractive surgery is recognized as an effective method for myopia treatment, but it can induce night vision disturbances such as glare. We present an eye modeling method for the optical quality assessment in response to the structural changes in the eyes by femto-LASIK surgery. Customized eye models were built from the measurements of 134 right eyes pre- and post-operatively. Optical performance was evaluated using spot diagrams, point spread functions (PSFs), modulation transfer functions (MTFs), and chromatic aberrations at various fields (0°–30°), different pupil diameters (2–6 mm), and initial myopias (− 1.25 to − 10.5 D). Pupil size and initial myopia are the two major factors that affect visual performance of post-operative eyes. The results of spot diagrams, PSFs, and MTFs indicated that post-operative visual performance deteriorated as the visual field and pupil size increased, and it was significantly influenced by initial myopia. Post-operative chromatic aberrations were also affected by initial myopia. As pupil size increased, the post-operative longitudinal chromatic aberrations tended to decrease slightly, while the transverse chromatic aberrations remained similar. The use of eye modeling for refractive surgery assessment could possibly provide a more personalized surgical approach, could improve the prediction accuracy of refractive surgery outcomes, and promote the invention and development of better surgical methods.

show abstract

“…Differing from our comprehensive approach, several studies have emphasized the optimization of specific postoperative outcomes to improve visual quality. 23,24 Previous researches have tried to minimize differences between the real ablation and the predicted one using a quadratic term in the formulae. 25 The recent study demonstrated that a surgeon should consider the nonlinear relationships between optical variables using the Q-optimized algorithm.…”

Section: Discussionmentioning

confidence: 99%

Adopting machine learning to automatically identify candidate patients for corneal refractive surgery

et al. 2019

View full text Add to dashboard Cite

Recently, it has become more important to screen candidates that undergo corneal refractive surgery to prevent complications. Until now, there is still no definitive screening method to confront the possibility of a misdiagnosis. We evaluate the possibilities of machine learning as a clinical decision support to determine the suitability to corneal refractive surgery. A machine learning architecture was built with the aim of identifying candidates combining the large multi-instrument data from patients and clinical decisions of highly experienced experts. Five heterogeneous algorithms were used to predict candidates for surgery. Subsequently, an ensemble classifier was developed to improve the performance. Training (10,561 subjects) and internal validation (2640 subjects) were conducted using subjects who had visited between 2016 and 2017. External validation (5279 subjects) was performed using subjects who had visited in 2018. The best model, i.e., the ensemble classifier, had a high prediction performance with the area under the receiver operating characteristic curves of 0.983 (95% CI, 0.977–0.987) and 0.972 (95% CI, 0.967–0.976) when tested in the internal and external validation set, respectively. The machine learning models were statistically superior to classic methods including the percentage of tissue ablated and the Randleman ectatic score. Our model was able to correctly reclassify a patient with postoperative ectasia as an ectasia-risk group. Machine learning algorithms using a wide range of preoperative information achieved a comparable performance to screen candidates for corneal refractive surgery. An automated machine learning analysis of preoperative data can provide a safe and reliable clinical decision for refractive surgery.

show abstract

Hyperopic Q-optimized algorithms: a theoretical study on factors influencing optical quality

Cited by 6 publications

References 36 publications

Effect of sodium fluorescein strip application on cornea parameters commonly used in laser-assisted in-situ keratomileusis

Effect of sodium fluorescein strip application on cornea parameters commonly used in laser-assisted in-situ keratomileusis

Customized eye modeling for optical quality assessment in myopic femto-LASIK surgery

Adopting machine learning to automatically identify candidate patients for corneal refractive surgery

Contact Info

Product

Resources

About