Dataset Information

Intraocular Lens Power Calculation after Small Incision Lenticule Extraction.

ABSTRACT: With more than 1.5 million Small Incision Lenticule Extraction (SMILE) procedures having already been performed worldwide in an ageing population, intraocular lens (IOL) power calculation in post-SMILE eyes will inevitably become a common challenge for ophthalmologists. Since no refractive outcomes of cataract surgery following SMILE have been published, there is a lack of empirical data for optimizing IOL power calculation. Using the ray tracing as the standard of reference - a purely physical method that obviates the need for any empirical optimization - we analyzed the agreement of various IOL power calculation formulas derived from the American Society of Cataract and Refractive Surgeons (ASCRS) post-keratorefractive surgery online calculator. In our study of 88 post-SMILE eyes, the Masket formula showed the smallest mean prediction error [-0.36?±?0.32 diopters (D)] and median absolute error (0.33D) and yielded the largest percentage of eyes within ±0.50D (70%) in reference to ray tracing. Non-inferior refractive prediction errors and ±0.50D accuracies were achieved by the Barrett True K, Barrett True K No History and the Potvin-Hill formula. Use of these formulas in conjunction with ray tracing is recommended until sufficient data for empirical optimization of IOL power calculation after SMILE is available.

SUBMITTER: Luft N

PROVIDER: S-EPMC7136233 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Intraocular Lens Power Calculation after Small Incision Lenticule Extraction.

Luft Nikolaus N Siedlecki Jakob J Schworm Benedikt B Kreutzer Thomas C TC Mayer Wolfgang J WJ Priglinger Siegfried G SG Dirisamer Martin M

Scientific reports 20200406 1

With more than 1.5 million Small Incision Lenticule Extraction (SMILE) procedures having already been performed worldwide in an ageing population, intraocular lens (IOL) power calculation in post-SMILE eyes will inevitably become a common challenge for ophthalmologists. Since no refractive outcomes of cataract surgery following SMILE have been published, there is a lack of empirical data for optimizing IOL power calculation. Using the ray tracing as the standard of reference - a purely physical ...[more]

PMID: 32249851

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Project description:AimTo evaluate the accuracy of the raytracing method for the calculation of intraocular lens (IOL) power in myopic eyes after small incision extraction of the lenticule (SMILE).MethodsRetrospective study. All patients undergoing surgery for myopic SMILE between May 1, 2020, and December 31, 2020, with Scheimpflug tomography optical biometry were eligible for inclusion. Manifest refraction was performed before and 6 months after refractive surgery. One eye from each patient was included in the final analysis. A theoretical model was invited to predict the accuracy of multiple methods of lens power calculation by comparing the IOL-induced refractive error at the corneal plane (IOL-Dif) and the SMILE-induced change of spherical equivalent (SMILE-Dif) before and after SMILE surgery. The prediction error (PE) was calculated as the difference between SMILE-Dif-IOL-Dif. IOL power calculations were performed using raytracing (Olsen Raytracing, Pentacam AXL, software version 1.22r05, Wetzlar, Germany) and other formulae with historical data (Barrett True-K, Double-K SRK/T, Masket, Modified Masket) and without historical data (Barrett True-K no history, Haigis-L, Hill Potvin Shammas PM, Shammas-PL) for the same IOL power and model. In addition, subgroup analysis was performed in different anterior chamber depths, axial lengths, back-to-front corneal radius ratio, keratometry, lens thickness, and preoperative spherical equivalents.ResultsA total of 70 eyes of 70 patients were analyzed. The raytracing method had the smallest mean absolute PE (0.26 ± 0.24 D) and median absolute PE (0.16 D), and also had the largest percentage of eyes within a PE of ± 0.25 D (64.3%), ± 0.50 D (81.4%), ± 0.75 D (95.7%), and ± 1.00 D (100.0%). The raytracing method was significantly better than Double-K SRK/T, Haigis, Haigis-L, and Shammas-PL formulae in postoperative refraction prediction (all p < 0.001), but not better than the following formulae: Barrett True-K (p = 0.314), Barrett True-K no history (p = 0.163), Masket (p = 1.0), Modified Masket (p = 0.806), and Hill Potvin Shammas PM (p = 0.286). Subgroup analysis showed that refractive outcomes exhibited no statistically significant differences in the raytracing method (all p < 0.05).ConclusionRaytracing was the most accurate method in predicting target refraction and had a good consistency in calculating IOL power for myopic eyes after SMILE.

Project description:BackgroundSmall-incision lenticule extraction (SMILE) is a surgical procedure for the refractive correction of myopia and astigmatism, which has been reported as safe and effective. However, over- and under-correction still occur after SMILE. The necessity of nomograms is emphasized to achieve optimal refractive results. Ophthalmologists diagnose nomograms by analyzing the preoperative refractive data with their individual knowledge which they accumulate over years of experience. Our aim was to predict the nomograms of sphere, cylinder, and astigmatism axis for SMILE accurately by applying machine learning algorithm.MethodsWe retrospectively analyzed the data of 3,034 eyes composed of four categorical features and 28 numerical features selected from 46 features. The multiple linear regression, decision tree, AdaBoost, XGBoost, and multi-layer perceptron were employed in developing the nomogram models for sphere, cylinder, and astigmatism axis. The scores of the root-mean-square error (RMSE) and accuracy were evaluated and compared. Subsequently, the feature importance of the best models was calculated.ResultsAdaBoost achieved the highest performance with RMSE of 0.1378, 0.1166, and 5.17 for the sphere, cylinder, and astigmatism axis, respectively. The accuracies of which error below 0.25 D for the sphere and cylinder nomograms and 25° for the astigmatism axis nomograms were 0.969, 0.976, and 0.994, respectively. The feature with the highest importance was preoperative manifest refraction for all the cases of nomograms. For the sphere and cylinder nomograms, the following highly important feature was the surgeon.ConclusionsAmong the diverse machine learning algorithms, AdaBoost exhibited the highest performance in the prediction of the sphere, cylinder, and astigmatism axis nomograms for SMILE. The study proved the feasibility of applying artificial intelligence (AI) to nomograms for SMILE. Also, it may enhance the quality of the surgical result of SMILE by providing assistance in nomograms and preventing the misdiagnosis in nomograms.

Project description:PurposeTo quantitatively evaluate outcomes after small incision lenticule extraction (SMILE) combined with allogeneic intrastromal lenticule inlay for hyperopia with astigmatism.MethodsIt's a retrospective cohort study. Twenty-four eyes of 15 patients with more than 0.75 diopters (D) of astigmatism in hyperopic eyes were enrolled in this study. The hyperopic eye with astigmatism was first treated with SMILE to correct astigmatism; then a lenticule was extracted from a donor myopic eye and subsequently implanted into the hyperopic eye with astigmatism. Patients were examined preoperatively and 1 day, 1 week, 1,3 months and 1 year after surgery. The main outcome measures were the uncorrected and corrected distance visual acuity (UDVA and CDVA), uncorrected near visual acuity (UNVA), spherical equivalent (SE), corneal topography, anterior segment optical coherence topography (OCT) and ocular response analyzer (ORA) parameters: corneal hysteresis (CH) and corneal resistance factor (CRF). Repeated-measures analyses of variance (ANOVA) and post hoc tests were used to analyze data of different follow-up visits.ResultsThe mean preoperative cylinder was 1.95±1.04(D). The UDVA (from 0.37±0.23 to 0.09±0.09), UNVA (from 0.49±0.21 to 0.08±0.06), SE (from +7.42±3.12 to -0.75±0.79) and astigmatism (+1.95±1.04 to -0.65±0.63) postoperatively were obviously better than those before surgery. Five eyes (26.3%) gained one line of CDVA, and 3 eyes (15.8%) gained two lines of CDVA one year after surgery compared with preoperative levels. The average corneal curvature was changed from (43.19±4.37) D to (49.19±3.87) D one year after surgery. The anterior segment OCT images of corneas with lenticule inlays at each follow-up visit showed that the implanted lenticule was shaped like a crescent in the corneal stroma. The CH and CRF didn't change significantly after surgery (p = 0.189 and p = 0.107respectively).ConclusionsSMILE combined with intrastromal lenticule inlay can be used to correct high hyperopia with astigmatism with good safety, efficacy and reproducibility.

Dataset Information

Intraocular Lens Power Calculation after Small Incision Lenticule Extraction.

Publications

Intraocular Lens Power Calculation after Small Incision Lenticule Extraction.

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