scholarly journals Considerations on the Castrop formula for calculation of intraocular lens power

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252102
Author(s):  
Achim Langenbucher ◽  
Nóra Szentmáry ◽  
Alan Cayless ◽  
Johannes Weisensee ◽  
Ekkehard Fabian ◽  
...  
Keyword(s):  
Test Data ◽  
Prediction Error ◽  
Training Data ◽  
Power Calculation ◽  
Large Dataset ◽  
Marquardt Algorithm ◽  
Intraocular Lens Power ◽  
Squared Prediction Error ◽  
Data Points ◽  
Lens Power

Background To explain the concept of the Castrop lens power calculation formula and show the application and results from a large dataset compared to classical formulae. Methods The Castrop vergence formula is based on a pseudophakic model eye with 4 refractive surfaces. This was compared against the SRKT, Hoffer-Q, Holladay1, simplified Haigis with 1 optimized constant and Haigis formula with 3 optimized constants. A large dataset of preoperative biometric values, lens power data and postoperative refraction data was split into training and test sets. The training data were used for formula constant optimization, and the test data for cross-validation. Constant optimization was performed for all formulae using nonlinear optimization, minimising root mean squared prediction error. Results The constants for all formulae were derived with the Levenberg-Marquardt algorithm. Applying these constants to the test data, the Castrop formula showed a slightly better performance compared to the classical formulae in terms of prediction error and absolute prediction error. Using the Castrop formula, the standard deviation of the prediction error was lowest at 0.45 dpt, and 95% of all eyes in the test data were within the limit of 0.9 dpt of prediction error. Conclusion The calculation concept of the Castrop formula and one potential option for optimization of the 3 Castrop formula constants (C, H, and R) are presented. In a large dataset of 1452 data points the performance of the Castrop formula was slightly superior to the respective results of the classical formulae such as SRKT, Hoffer-Q, Holladay1 or Haigis.

Microincision cataract surgery with implantation of a bitoric intraocular lens using an enhanced program for intraocular lens power calculation

2019 ◽  
Vol 30 (6) ◽  
pp. 1308-1313
Author(s):  
Gilles Lesieur
Keyword(s):  
Cataract Surgery ◽  
Intraocular Lens ◽  
Prediction Error ◽  
Power Calculation ◽  
Spherical Equivalent ◽  
Toric Intraocular Lens ◽  
Intraocular Lens Power Calculation ◽  
Intraocular Lens Power ◽  
Lens Power ◽  
Lens Power Calculation

Purpose: To evaluate the potential benefit of a new version of an online toric intraocular lens calculator in eyes implanted with a bitoric intraocular lens. Patients and methods: Retrospective observational comparative study in patients that underwent cataract surgery with implantation of the bitoric intraocular lens AT TORBI 709M (Carl Zeiss Meditec AG, Jena, Germany). Visual and refractive outcomes were evaluated at 1 month after surgery. The selection of the toric intraocular lens power was performed with the software Z CALC 2.0 (Carl Zeiss Meditec AG). The absolute refractive prediction errors for the spherical equivalent and cylinder were calculated and compared with the values that would have been obtained using version 1.5 of the same software. Results: A total of 393 eyes of 276 patients were evaluated. Mean postoperative sphere and cylinder were +0.03 ± 0.54 and −0.19 ± 0.30 D, respectively. A total of 95.67%, 98.22%, and 95.17% of eyes had a postoperative sphere, cylinder, and spherical equivalent within ±1.00 D, respectively. Mean absolute refractive prediction error for spherical equivalent was 0.34 ± 0.27 D with the two versions of the Z CALC software. In contrast, a significantly higher absolute refractive prediction error value for the cylinder was found with Z CALC 1.5 compared to version 2.0 (0.35 ± 0.32 vs 0.28 ± 0.30 D, p < 0.001). The absolute refractive prediction error for cylinder was ⩽0.25 D in 62.3% and 47.5% when using the versions 2.0 and 1.5, respectively. Conclusion: The use of an optimized software for toric intraocular lens power calculation, considering the contribution of posterior corneal astigmatism, improved the astigmatic outcome with a bitoric intraocular lens.

scholarly journals Accuracy of intraocular lens power calculation formulas after laser refractive surgery in myopic eyes: A meta-analysis

2019 ◽  
Author(s):  
Hongyu Li ◽  
Jun Li ◽  
Hui Song
Keyword(s):  
Intraocular Lens ◽  
Prediction Error ◽  
Refractive Surgery ◽  
Meta Analysis ◽  
Cochrane Library ◽  
Power Calculation ◽  
Intraocular Lens Power Calculation ◽  
Intraocular Lens Power ◽  
Lens Power ◽  
Lens Power Calculation

Abstract Background: To compare the accuracy of intraocular lens power calculation formulas after refractive surgery in myopic eyes. Methods: We searched the databases on the PubMed, EMBASE, Web of science and Cochrane library to select relevant studies published between Jan 1, 2009 and Aug 11, 2019. Primary outcomes were the percentages of refractive prediction error within ±0.5D and ±1.0D. Results: The results of this meta-analysis were investigated from 16 studies, including 7 common methods (Haigis-L, Shammas-PL, Double-K SRK/T, Barrett true K no history, Wang-Koch-Maloney, ASCRS average and OCT formula). ASCRS average yielded significantly higher percentage of refractive prediction error within ±0.5D than Haigis-L, Shammas-PL and W-K-M (P=0.009, 0.01, 0.008, respectively). Barrett true K no history also yielded significantly higher percentage of refractive prediction error within ±0.5D than Shammas-PL and W-K-M (P=0.01, <0.0001, respectively), and the same result was found by comparing OCT formula with Hiaigi-L and Shammas-PL (P=0.03, 0.01, respectively). Only the Haigis-L had significantly higher percentages than W-K-M method in the ±1.0D group (P = 0.04). Conclusion: We suggest that the ASCRS average and Barrett true K no history formula should be used to calculate the IOL power in eyes after myopic refractive surgery.

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

Intraocular lens power calculation in virgin eyes: Accuracy of the Barrett Universal II formula and a Ray tracing software

2021 ◽  
pp. 112067212110655
Author(s):  
Joaquim Fernández-Rosés ◽  
José Lamarca ◽  
David P. Piñero ◽  
Rafael I. Barraquer
Keyword(s):  
Ray Tracing ◽  
Intraocular Lens ◽  
Prediction Error ◽  
Pupil Diameter ◽  
Absolute Error ◽  
Power Calculation ◽  
Intraocular Lens Power Calculation ◽  
Intraocular Lens Power ◽  
Lens Power ◽  
Lens Power Calculation

Purpose To compare the accuracy of Sirius ray tracing software with the Barrett Universal II formula for intraocular lens power prediction in virgin eyes. Methods Retrospective case series including 86 eyes that have undergone uneventful cataract surgery with SN60WF implantation. The median absolute error, mean prediction error, variance, and the percentage of eyes within ± 0.25 D, ± 0.50 D, ± 0.75 D, and ± 1.00 D of the prediction error in refraction were calculated. The correlation of prediction error with different baseline parameters was investigated. Results No differences were found between the median absolute error of the Barrett Universal II formula (0.226 D) and the ray tracing software with different intraocular lens centerings; apex (0.331 D), limbus (0.345 D), and pupil (0.342 D) ( p = 0.084). The variance, from lowest to highest, was the Barrett Universal II (0.144 D2), ray tracing-limbus (0.285 D2), ray tracing-pupil (0.285 D2), and ray tracing-apex (0.287 D2) ( p = 0.027). The Barrett Universal II formula showed a higher percentage of eyes within ± 0.25 D (56.98%), ± 0.50 D (82.56%), and ± 0.75 D (93.02%) compared to ray tracing software ( p < 0.01). A significant correlation between the prediction error of the Barrett Universal II formula and corneal diameter (r = 0.322, p = 0.002) and pupil diameter (r = 0.230, p = 0.033) was found. Also, a positive correlation between the prediction error of Sirius ray tracing and axial length ( p < 0.001) and pupil diameter ( p = 0.01) was found. Conclusion There is a trend of the Barrett Universal II formula to be more accurate than Sirius ray tracing software for intraocular lens power calculation in virgin eyes. This should be confirmed in future prospective comparative studies.

Comparison of six methods for the intraocular lens power calculation in high myopic eyes

2019 ◽  
pp. 112067211988901 ◽  
Author(s):  
Jiali Ji ◽  
Yan Liu ◽  
Jing Zhang ◽  
Xinhua Wu ◽  
Wanyu Shao ◽  
...  
Keyword(s):  
Radial Basis Function ◽  
Intraocular Lens ◽  
Basis Function ◽  
Prediction Error ◽  
Power Calculation ◽  
Intraocular Lens Power Calculation ◽  
Intraocular Lens Power ◽  
Radial Basis ◽  
Lens Power ◽  
Lens Power Calculation

Purpose: The aim of this study was to compare the accuracy of Barrett Universal II and Hill-Radial Basis Function with other four popular formulas for the calculation of intraocular lens power in high myopic eyes. Methods: A total of 56 eyes with an axial length of more than 26.0 mm were retrospectively reviewed. Six intraocular lens power calculation methods, including Barrett Universal II, Hill-Radial Basis Function, SRK/T, Haigis, Holladay 2 and Holladay 1, were evaluated. The difference between the postoperative actual refraction and the refraction predicted by the six methods was evaluated as the prediction error. The absolute prediction error was also calculated. Results: The mean numerical prediction error ± standard deviation of the six intraocular lens power calculation methods, in order of lowest to highest, was Barrett Universal II (0.37 ± 0.54 D), Hill-Radial Basis Function (0.40 ± 0.56 D), SRK/T (0.44 ± 0.56 D), Haigis (0.53 ± 0.54 D), Holladay 2 (0.88 ± 0.62 D) and Holladay 1 (1.00 ± 0.60 D). The median absolute errors predicted by the Barrett (0.46 D), Hill-Radial Basis Function (0.47 D), SRK/T (0.53 D) and Haigis (0.58 D) were significantly lower than those of the Holladay 1 (0.90 D) and Holladay 2(1.10 D; all p < 0.001). There was no significant difference among the median absolute errors of Barrett, Hill-Radial Basis Function, SRK/T and Haigis (all p > 0.05). Conclusion: The prediction errors differed for each method in the selection of intraocular lens power for the long eyes. In terms of overall accuracy, the Barrett Universal II formula provided the lowest prediction error. The Hill-Radial Basis Function method was comparable to the theoretical formulas, such as SRK/T and Haigis.

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