Ocular residual astigmatism and topographic disparity vector indexes in normal healthy eyes

Purpose: To define a range of normality for the vectorial parameters Ocular Residual Astigmatism (ORA) and topography disparity (TD) and to evaluate their relationship with visual, refractive, anterior and posterior corneal curvature, pachymetric and corneal volume data in normal healthy eyes. Methods: This study comprised a total of 101 consecutive normal healthy eyes of 101 patients ranging in age from 15 to 64 years old. In all cases, a complete corneal analysis was performed using a Scheimpflug photography-based topography system (Pentacam system Oculus Optikgeräte GmbH). Anterior corneal topographic data were imported from the Pentacam system to the iASSORT software (ASSORT Pty. Ltd.), which allowed the calculation of the ocular residual astigmatism (ORA) and topography disparity (TD). Linear regression analysis was used for obtaining a linear expression relating ORA and posterior corneal astigmatism (PCA). Results: Mean magnitude of ORA was 0.79 D (SD: 0.43), with a normality range from 0 to 1.63 D. 90 eyes (89.1%) showed against-the-rule ORA. A weak although statistically significant correlation was found between the magnitudes of posterior corneal astigmatism and ORA (r = 0.34, p < 0.01). Regression analysis showed the presence of a linear relationship between these two variables, although with a very limited predictability (R2: 0.08). Mean magnitude of TD was 0.89 D (SD: 0.50), with a normality range from 0 to 1.87 D. Conclusion: The magnitude of the vector parameters ORA and TD is lower than 1.9 D in the healthy human eye.

Clinical Validation of Adjusted Corneal Power in Patients with Previous Myopic Lasik Surgery

Purpose. To validate clinically a new method for estimating the corneal power (P,) using a variable keratometric index (nkadj) in eyes with previous laser refractive surgery. Setting. University of Alicante and Medimar International Hospital (Oftalmar), Alicante, (Spain). Design. Retrospective case series. Methods. This retrospective study comprised 62 eyes of 62 patients that had undergone myopic LASIK surgery. An algorithm for the calculation of 11kadj was used for the estimation of the adjusted keratometric corneal power (Pkadj). This value was compared with the classical keratometric corneal power (Pk), the True Net Power (TNP), and the Gaussian corneal power (PcGauss). Likewise, Pkadj was compared with other previously described methods. Results. Differences between PcGauss and P, values obtained with all methods evaluated were statistically significant (p < 0.01). Differences between Pkadj and PcGauss were in the limit of clinical significance (p < 0.01, loA [ - 0.33,0.60] D). Differences between Pkadj and TNP were not statistically and clinically significant (p = 0.319, loA [- 0.50,0.44] D). Differences between Pkadj and previously described methods were statistically significant (p < 0.01), except with PcHaigisL (p = 0.09, loA [ - 0.37,0.29] D). Conclusion. The use of the adjusted keratometric index (nkadj) is a valid method to estimate the central corneal power in corneas with previous myopic laser refractive surgery, providing results comparable to PcHaigisL.

Comparison of the predictability of refractive cylinder correction by laser in situ keratomileusis in eyes with low or high ocular residual astigmatism

Purpose: To compare the manifest refractive cylinder (MRC) predictability of myopic astigmatism laser in situ keratomileusis (LASIK) between eyes with low and high ocular residual astigmatism (ORA). Setting: London Vision Clinic, London, United Kingdom. Design: Retrospective case study. Methods: The ORA was considered the vector difference between the MRC and the corneal astigmatism. The index of success (IoS), difference vector ÷ MRC, was analyzed for different groups as follows: stage 1, low ORA (ORA ÷ MRC <1), high ORA (ORA ÷ MRC ≥1); stage 2, low ORA group reduced to match the high ORA group for MRC; stage 3, grouped by ORA magnitude with low ORA (<0.50 diopters [D]), mid ORA (0.50 to 1.24 D), and high ORA (≥1.25 D); stage 4, high ORA group subdivided into low (<0.75 D) and high (≥0.75 D) corneal astigmatism. Results: For stage 1, the mean preoperative MRC and mean IoS were −1.32 D ± 0.65 (SD) (range −0.55 to −3.77 D) and 0.27, respectively, for low ORA and −0.79 ± 0.20 D (range −0.56 to −2.05 D) and 0.37, respectively, for high ORA. For stage 2, the mean IoS increased to 0.32 for low ORA. For stage 3, the mean IoS was 0.28, 0.29, and 0.31 for low ORA, mid ORA, and high ORA, respectively. For stage 4, the mean IoS was 0.20 for high ORA/low corneal astigmatism and 0.35 for high ORA/high corneal astigmatism. Conclusions: The MRC predictability was slightly worse in eyes with high ORA when grouped by the ORA ÷ MRC. Matching for the MRC and grouping by ORA magnitude resulted in similar predictability; however, eyes with high ORA and high corneal astigmatism were less predictable.

Clinical utility of ocular residual astigmatism and topographic disparity vector indexes in subclinical and clinical keratoconus

Purpose. We aimed to characterize the distribution of the vector parameters ocular residual astigmatism (ORA) and topography disparity (TD) in a sample of clinical and subclinical keratoconus eyes, and to evaluate their diagnostic value to discriminate between these conditions and healthy corneas. Methods. This study comprised a total of 43 keratoconic eyes (27 patients, 17–73 years) (keratoconus group), 11 subclinical keratoconus eyes (eight patients, 11–54 years) (subclinical keratoconus group) and 101 healthy eyes (101 patients, 15–64 years) (control group). In all cases, a complete corneal analysis was performed using a Scheimpflug photography-based topography system. Anterior corneal topographic data was imported from it to the iASSORT software (ASSORT Pty. Ltd), which allowed the calculation of ORA and TD. Results. Mean magnitude of the ORA was 3.23 ± 2.38, 1.16 ± 0.50 and 0.79 ± 0.43 D in the keratoconus, subclinical keratoconus and control groups, respectively (p < 0.001). Mean magnitude of the TD was 9.04 ± 8.08, 2.69 ± 2.42 and 0.89 ± 0.50 D in the keratoconus, subclinical keratoconus and control groups, respectively (p < 0.001). Good diagnostic performance of ORA (cutoff point: 1.21 D, sensitivity 83.7 %, specificity 87.1 %) and TD (cutoff point: 1.64 D, sensitivity 93.3 %, specificity 92.1 %) was found for the detection of keratoconus. The diagnostic ability of these parameters for the detection of subclinical keratoconus was more limited (ORA: cutoff 1.17 D, sensitivity 60.0 %, specificity 84.2 %; TD: cutoff 1.29 D, sensitivity 80.0 %, specificity 80.2 %). Conclusion. The vector parameters ORA and TD are able to discriminate with good levels of precision between keratoconus and healthy corneas. For the detection of subclinical keratoconus, only TD seems to be valid.

Positional accommodative intraocular lens power error induced by the estimation of the corneal power and the effective lens position

Purpose: To evaluate the predictability of the refractive correction achieved with a positional accommodating intraocular lenses (IOL) and to develop a potential optimization of it by minimizing the error associated with the keratometric estimation of the corneal power and by developing a predictive formula for the effective lens position (ELP). Materials and Methods: Clinical data from 25 eyes of 14 patients (age range, 52–77 years) and undergoing cataract surgery with implantation of the accommodating IOL Crystalens HD (Bausch and Lomb) were retrospectively reviewed. In all cases, the calculation of an adjusted IOL power (PIOLadj) based on Gaussian optics considering the residual refractive error was done using a variable keratometric index value (nkadj) for corneal power estimation with and without using an estimation algorithm for ELP obtained by multiple regression analysis (ELPadj). PIOLadj was compared to the real IOL power implanted (PIOLReal, calculated with the SRK-T formula) and also to the values estimated by the Haigis, HofferQ, and Holladay I formulas. Results: No statistically significant differences were found between PIOLReal and PIOLadj when ELPadj was used (P = 0.10), with a range of agreement between calculations of 1.23 D. In contrast, PIOLReal was significantly higher when compared to PIOLadj without using ELPadj and also compared to the values estimated by the other formulas. Conclusions: Predictable refractive outcomes can be obtained with the accommodating IOL Crystalens HD using a variable keratometric index for corneal power estimation and by estimating ELP with an algorithm dependent on anatomical factors and age.