scholarly journals Keratometry using hand-held and automated keratometers with and without speculum in Indian pediatric cataract – A comparative study

2022 ◽  
Vol 7 (4) ◽  
pp. 663-666
Author(s):  
Neha Singh Jat ◽  
Sumaiya Hasan ◽  
Dheerendra Singh ◽  
Vivek Paul Buddhe
Keyword(s):  
Indian Pediatric ◽  
Power Calculation ◽  
Pediatric Cataract ◽  
Cross Sectional ◽  
Iol Power Calculation ◽  
Significant Difference ◽  
Iol Power ◽  
Males And Females ◽  
Power Measurements ◽  
Age Range

To study the keratometry of Indian pediatric eyes, the effect of speculum on keratometry reading, the concordance of hand held and automated keratometry and the effect of unilateral and bilateral cataract on keratometry and IOL power calculation. This was conducted as a cross- sectional observational study on 101 eyes of children in the age range of 41 post-conceptional weeks to 144 months. All cooperative patients were subject to automated keratometry followed by keratometry using hand held keratometer with and without speculum. Hand held keratometer with and without speculum documented significantly increased average K as well as astigmatism and decreased calculated IOL power when compared to automated keratometry (p<0.01). No significant difference in K readings was observed between unilateral and bilateral cataracts and among males and females (p>0.05). As the age increased, astigmatism increased significantly (R=0.07; p=0.007) whereas no such correlation was observed for keratometry (p>0.05). Hand held keratometry offers the convenience of obtaining accurate keratometry, astigmatism and IOL power measurements in children.

scholarly journals Use of a Machine Learning Method in Predicting Refraction after Cataract Surgery

2021 ◽  
Vol 10 (5) ◽  
pp. 1103
Author(s):  
Tomofusa Yamauchi ◽  
Hitoshi Tabuchi ◽  
Kosuke Takase ◽  
Hiroki Masumoto
Keyword(s):  
Machine Learning ◽  
Cataract Surgery ◽  
Test Data ◽  
Training Data ◽  
Gradient Boosting ◽  
Support Vector ◽  
Power Calculation ◽  
Iol Power Calculation ◽  
Significant Difference ◽  
Iol Power

The present study aims to describe the use of machine learning (ML) in predicting the occurrence of postoperative refraction after cataract surgery and compares the accuracy of this method to conventional intraocular lens (IOL) power calculation formulas. In total, 3331 eyes from 2010 patients were assessed. The objects were divided into training data and test data. The constants for the IOL power calculation formulas and model training for ML were optimized using training data. Then, the occurrence of postoperative refraction was predicted using conventional formulas, or ML models were calculated using the test data. We evaluated the SRK/T formula, Haigis formula, Holladay 1 formula, Hoffer Q formula, and Barrett Universal II formula (BU-II); similar to ML methods, we assessed support vector regression (SVR), random forest regression (RFR), gradient boosting regression (GBR), and neural network (NN). Among the conventional formulas, BU-II had the lowest mean and median absolute error of prediction. Therefore, we compared the accuracy of our method with that of BU-II. The absolute errors of some ML methods were lower than those of BU-II. However, no statistically significant difference was observed. Thus, the accuracy of our method was not inferior to that of BU-II.

scholarly journals Comparing the Lenstar Optical Biometer and the Verion Image-Guided System for intraocular lens power calculation

2020 ◽  
Vol 1 (4) ◽  
pp. 236-243
Author(s):  
Mun Wai Lee
Keyword(s):  
Intraocular Lens ◽  
Pearson Correlation ◽  
Case Series ◽  
Power Calculation ◽  
Image Guided ◽  
Iol Power Calculation ◽  
Significant Difference ◽  
Iol Calculation ◽  
Iol Power ◽  
Optical Biometer

Introduction: This study aims to evaluate the accuracy of the measurement parameters of the new Verion Image Guided System compared with an established standard of care. Purpose: To compare the keratometry (K) and white-to-white (WTW) measurements obtained from the Lenstar Optical Biometer (LS) with those from the Verion Image-Guided System (VR) and their effect on intraocular lens (IOL) power calculation. Design: Prospective comparative case series. Materials and methods: Sixty patients going for cataract surgery had biometry measurements and IOL calculation with the LS. Axial length from LS was used together with K and WTW measurements from VR for IOL calculation as well. IOL selection was done using the Barrett Universal II formula targeting emmetropia. The prediction error (PE) within 0.25 D, 0.5 D, and 1 D of refractive target and the mean absolute error (MAE) were calculated for both the LS and VR. Results: Keratometry measurements and steep axis from the VR were closely correlated with the LS (Pearson correlation coefficient K1, r = 0.958; K2, r = 0.952; axis, r = 0.950). The WTW measurements were less so (WTW, r = 0.471). The MAE was 0.317 and 0.347 for LS and VR, respectively. PE within 0.25 D was 48.3% and 40%; within 0.5 D was 83.3% and 76.7%; and within 1 D was 98.3% and 96.7% for LS and VR, respectively. There was no statistically significant difference in MAE between the LS and VR (p = 0.74) Conclusion: Using the K and WTW measurements from the Verion Image-Guided System for IOL power calculation did provide comparable results with the Lenstar. The Lenstar had a higher proportion of eyes within 0.5 D of refractive target but the difference was not statistically significant.  

scholarly journals Accuracy of Intraocular Lens Power Calculation Using Anterior Chamber Depth from Two Devices with Barrett Universal II Formula

2019 ◽  
Vol 2019 ◽  
pp. 1-5
Author(s):  
Hannah Muniz Castro ◽  
Audrey X. Tai ◽  
Samuel J. Sampson ◽  
Matthew Wade ◽  
Marjan Farid ◽  
...  
Keyword(s):  
Anterior Chamber ◽  
Anterior Chamber Depth ◽  
Absolute Error ◽  
Power Calculation ◽  
Intraocular Lens Power Calculation ◽  
Iol Power Calculation ◽  
Significant Difference ◽  
Iol Power ◽  
Retrospective Comparative Study ◽  
Lens Power

Purpose. To compare the preoperative measurements of the anterior chamber depth (ACD) by the IOLMaster and Catalys; additionally, to compare the accuracy of the IOL power calculated by the Barrett Universal II formula using the two different measurements. Setting. University of California, Irvine, Gavin Herbert Eye Institute in Irvine, California. Design. Retrospective comparative study. Methods. This study included 144 eyes of 90 patients with a mean age of 72.0 years (range 40.8 to 92.1 years) that underwent femtosecond laser-assisted cataract surgery using Catalys. Preoperative measurements of ACD were taken by the IOLMaster and Catalys. Manifest refraction and refractive spherical equivalent were measured 1 month postoperatively. Expected refractive results were compared with actual postoperative refractive results. Results. The correlation between the ACD values from the two devices was good (r = 0.80). The Catalys ACD measurements yielded a larger ACD compared to the IOLMaster, with a mean difference of 0.22 mm (P<0.0001). The correlation between the postoperative and predicted RSE of the implanted IOL power was excellent (r = 0.96). There was no statistically significant difference between the mean absolute error derived from the IOLMaster, 0.37 diopter (D) ± 0.34 (SD), and the Catalys, 0.37 ± 0.35 D (P=0.50). Conclusions. The Catalys biometry yielded a significantly larger ACD value than the IOLMaster. This difference in ACD value, however, did not reflect in a statistically significant difference in IOL power calculation and refractive prediction error using the Barrett Universal II Formula.

scholarly journals Accuracy of intraocular lens power calculation in pediatric cataracts with less than a 20 mm axial length of the eye

2014 ◽  
Vol 6 (1) ◽  
pp. 56-64 ◽  
Author(s):  
Purushottam Joshi ◽  
Raman Mehta ◽  
Suma Ganesh
Keyword(s):  
Axial Length ◽  
Prediction Error ◽  
Power Calculation ◽  
Pediatric Cataract ◽  
Intraocular Lens Power Calculation ◽  
Iol Power Calculation ◽  
Intraocular Lens Power ◽  
Iol Power ◽  
The Absolute ◽  
Lens Power

Introduction: Selection of an appropriately-powered IOL is a complex issue, especially in eyes with an axial length of less than 20 mm in pediatric cataract. Objective: To assess the accuracy of IOL power calculation formulae in pediatric cataracts in eyes with an axial length of less than 20 mm. Materials and methods: The records of children less than 15 years old with congenital cataract who had undergone primary IOL implantation were analyzed. Main outcome measures: The variables studied were axial length, keratometric values and the prediction error. The data were analyzed for prediction error determination using the SRK II, SRK T, Holladay 1 and Hoffer Q IOL power calculation formulae. The formula that gave the best prediction error was identified. Results: Twenty-eight eyes of 19 children were included in the study. The absolute prediction error was found to be 1.84 ± 2.09 diopters (D) with SRK II, 2.93±3.55D with SRK T, 3.63±4.06D with Holladay 1, and 4.83±5.02D with Hoffer Q. The number of eyes with the absolute prediction error within 0.5 D was 6 (21.42%) with SRK II, 4 (14.28%) with SRK T, 1 (3.57%) with Holladay 1, and 3 (10.71%) with Hoffer Q. The absolute prediction error with SRK II formula was significantly better than that with other formulae (P < .001). The axial length influenced the absolute prediction error with Hoffer Q formula (P = 0.04). The mean keratometry influenced the prediction error with SRK T formula (P = 0.02), Holladay 1 formula (P = 0.02) and Hoffer Q formula (P = 0.02). Conclusion: Although the absolute prediction error tends to remain high with all the present IOL power calculation formulae, SRK II was the most predictable formula in this study. DOI: http://dx.doi.org/10.3126/nepjoph.v6i1.10773 Nepal J Ophthalmol 2014; 6 (2): 56-64

scholarly journals Improving clinical refractive results of cataract surgery by machine learning

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7202 ◽  
Author(s):  
Martin Sramka ◽  
Martin Slovak ◽  
Jana Tuckova ◽  
Pavel Stodulka
Keyword(s):  
Clinical Results ◽  
Support Vector ◽  
Power Calculation ◽  
Prediction Errors ◽  
Neural Network Ensemble ◽  
Clinical Workflow ◽  
Clinical Method ◽  
Iol Power Calculation ◽  
Significant Difference ◽  
Iol Power

Aim To evaluate the potential of the Support Vector Machine Regression model (SVM-RM) and Multilayer Neural Network Ensemble model (MLNN-EM) to improve the intraocular lens (IOL) power calculation for clinical workflow. Background Current IOL power calculation methods are limited in their accuracy with the possibility of decreased accuracy especially in eyes with an unusual ocular dimension. In case of an improperly calculated power of the IOL in cataract or refractive lens replacement surgery there is a risk of re-operation or further refractive correction. This may create potential complications and discomfort for the patient. Methods A dataset containing information about 2,194 eyes was obtained using data mining process from the Electronic Health Record (EHR) system database of the Gemini Eye Clinic. The dataset was optimized and split into the selection set (used in the design for models and training), and the verification set (used in the evaluation). The set of mean prediction errors (PEs) and the distribution of predicted refractive errors were evaluated for both models and clinical results (CR). Results Both models performed significantly better for the majority of the evaluated parameters compared with the CR. There was no significant difference between both evaluated models. In the ±0.50 D PE category both SVM-RM and MLNN-EM were slightly better than the Barrett Universal II formula, which is often presented as the most accurate calculation formula. Conclusion In comparison to the current clinical method, both SVM-RM and MLNN-EM have achieved significantly better results in IOL calculations and therefore have a strong potential to improve clinical cataract refractive outcomes.

scholarly journals The comparative study of applanation and optical coherence biometry methods for the intra ocular lens power calculation

2018 ◽  
Vol 6 (03) ◽  
pp. 01-08
Author(s):  
Mahesh Chandra ◽  
Jitendra Singh ◽  
Mahesh Chandra Agarwal ◽  
Govind Singh Titiyal
Keyword(s):  
Comparative Study ◽  
Axial Length ◽  
Age Groups ◽  
Power Calculation ◽  
Optical Coherence ◽  
Perfect Agreement ◽  
Iol Power Calculation ◽  
Significant Difference ◽  
Iol Power ◽  
Lens Power

Purpose: To compare applanation biometry (A-Scan) and optical coherence biometry (AL-Scan) methods for IOL power calculation based on Axial Length and post operative refractive outcome. Methodology: Prospective and Interventional Randomized Comparative Study, Sample size of 400, studied under two sub groups, for Axial Length readings and IOL power calculation by A-Scan (Biomedix) and AL-Scan (Nidek). Keratometry readings are taken only by AL-Scan.Results: Mean ± St. dev. of A.L. measured by App. Biometry was low (22.79 ± 0.9 mm) than Opt. Coh. Biometry (23.16 ± 0.78 mm) to be significant (P= .0001). Mean ± St. dev. IOL power was higher (21.75 ± 2.1D) than App. Biometry (20.88 ± 1.59 D) to be significant (P= 0.0001). Mean ± St. dev. of refractive status for Myopia is higher -0.97 ± 0.53 by App. Biometry than Opt. Coh. Biometry -0.5 ± 0.19, to be significant (P= 0.0001) and Mean ± St.dev. for Hyperopia is higher 0.98 ± 0.59 by App. Biometry than Opt. Coh. Biometry 0.46 ± 0.18, to be significant (P= 0.0001). Bland–Altman plots showed perfect agreement between both methods regarding A.L. and calculated IOL power. Further subgroup analysis revealed a statistically significant difference in different age groups and types of cataract for Posterior Sub capsular cataract alone and Nuclear Sclerosis with Posterior Sub capsular cataract (P= 0.001). Conclusion: There is significant difference between App. and Opt. Coh. Biometry; however, certain situations of Cataract is demanding mandatory role of App. Biometry.

scholarly journals Accuracy of Intraocular Lens Power Calculation Formulas in Pediatric Cataract Patients: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 8 ◽  
Author(s):  
Yueyang Zhong ◽  
Yibo Yu ◽  
Jinyu Li ◽  
Bing Lu ◽  
Su Li ◽  
...  
Keyword(s):  
Systematic Review ◽  
Intraocular Lens ◽  
Prediction Error ◽  
Meta Analysis ◽  
Power Calculation ◽  
Pediatric Cataract ◽  
Iol Power Calculation ◽  
Iol Power ◽  
The Mean ◽  
Cataract Patients

Background: Among the various intraocular lens (IOL) power calculation formulas available in clinical settings, which one can yield more accurate results is still inconclusive. We performed a meta-analysis to compare the accuracy of the IOL power calculation formulas used for pediatric cataract patients.Methods: Observational cohort studies published through April 2021 were systematically searched in PubMed, Web of Science, and EMBASE databases. For each included study, the mean differences of the mean prediction error and mean absolute prediction error (APE) were analyzed and compared using the random-effects model.Results: Twelve studies involving 1,647 eyes were enrolled in the meta-analysis, and five formulas were compared: Holladay 1, Holladay 2, Hoffer Q, SRK/T, and SRK II. Holladay 1 exhibited the smallest APE (0.97; 95% confidence interval [CI]: 0.92–1.03). For the patients with an axial length (AL) less than 22 mm, SRK/T showed a significantly smaller APE than SRK II (mean difference [MD]: −0.37; 95% CI: −0.63 to −0.12). For the patients younger than 24 months, SRK/T had a significantly smaller APE than Hoffer Q (MD: −0.28; 95% CI: −0.51 to −0.06). For the patients aged 24–60 months, SRK/T presented a significantly smaller APE than Holladay 2 (MD: −0.60; 95% CI: −0.93 to −0.26).Conclusion: Due to the rapid growth and high variability of pediatric eyes, the formulas for IOL calculation should be considered according to clinical parameters such as age and AL. The evidence obtained supported the accuracy and reliability of SRK/T under certain conditions.Systematic Review Registration: PROSPERO, identifier: INPLASY202190077.

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