Validity of the keratometric index: Evaluation by the Pentacam rotating Scheimpflug camera

Can AI Predict the Magnitude and Direction of Ortho-K Contact Lens Decentration to Limit Induced HOAs and Astigmatism?

Background: The aim is to investigate induced higher-order aberrations (HOA)s and astigmatism as a result of non-toric ortho-k lens decentration and utilise artificial intelligence (AI) to predict its magnitude and direction. Methods: Medmont E300 Video topographer was used to scan 249 corneas before and after ortho-k wear. Custom-built MATLAB codes extracted topography data and determined lens decentration from the boundary and midpoint of the central flattened treatment zone (TZ). An evaluation was carried out by conducting Zernike polynomial fittings via a computer-coded digital signal processing procedure. Finally, an AI-based machine learning neural network algorithm was developed to predict the direction and magnitude of TZ decentration. Results: Analysis of the first 21 Zernike polynomial coefficients indicate that the four low-order and four higher-order aberration terms were changed significantly by ortho-k wear. While baseline astigmatism was not correlated with lens decentration (R = 0.09), post-ortho-k astigmatism was moderately correlated with decentration (R = 0.38) and the difference in astigmatism (R = 0.3). Decentration was classified into three groups: ≤0.50 mm, reduced astigmatism by -0.9 ± 1 D; 0.5~1 mm, increased astigmatism by 0.8 ± 0.1 D; >1 mm, increased astigmatism by 2.7 ± 1.6 D and over 50% of lenses were decentred >0.5 mm. For lenses decentred >1 mm, 29.8% of right and 42.7% of left lenses decentred temporal-inferiorly and 13.7% of right and 9.4% of left lenses decentred temporal-superiorly. AI-based prediction successfully identified the decentration direction with accuracies of 70.2% for right and 71.8% for left lenses and predicted the magnitude of decentration with root-mean-square (RMS) of 0.31 mm and 0.25 mm for right and left eyes, respectively. Conclusions: Ortho-k lens decentration is common when fitting non-toric ortho-k lenses, resulting in induced HOAs and astigmatism, with the magnitude being related to the amount of decentration. AI-based algorithms can effectively predict decentration, potentially allowing for better control over ortho-k fitting and, thus, preferred clinical outcomes.

The influence of variations in ocular biometric and optical parameters on differences in refractive error

PURPOSE

To present a paraxial method to estimate the influence of variations in ocular biometry on changes in refractive error (S) at a population level and apply this method to literature data.

METHODS

Error propagation was applied to two methods of eye modelling, referred to as the simple method and the matrix method. The simple method defines S as the difference between the axial power and the whole-eye power, while the matrix method uses more accurate ray transfer matrices. These methods were applied to literature data, containing the mean ocular biometry data from the SyntEyes model, as well as populations of premature infants with or without retinopathy, full-term infants, school children and healthy and diabetic adults.

RESULTS

Applying these equations to 1000 SyntEyes showed that changes in axial length provided the most important contribution to the variations in refractive error (57%-64%), followed by lens power/gradient index power (16%-31%) and the anterior corneal radius of curvature (10%-13%). All other components of the eye contributed <4%. For young children, the largest contributions were made by variations in axial length, lens and corneal power for the simple method (67%, 23% and 8%, respectively) and by variations in axial length, gradient lens power and anterior corneal curvature for the matrix method (55%, 21% and 14%, respectively). During myopisation, the influence of variations in axial length increased from 54.5% to 73.4%, while changes in corneal power decreased from 9.82% to 6.32%. Similarly, for the other data sets, the largest contribution was related to axial length.

CONCLUSIONS

This analysis confirms that the changes in ocular refraction were mostly associated with variations in axial length, lens and corneal power. The relative contributions of the latter two varied, depending on the particular population.

Differences Between Keratometry and Total Keratometry Measurements in a Large Dataset Obtained With a Modern Swept Source Optical Coherence Tomography Biometer

PURPOSE

This study aimed to explore the concept of total keratometry (TK) by analyzing extensive international datasets representing diverse ethnic backgrounds. The primary objective was to quantify the disparities between traditional keratometry (K) and TK values in normal eyes and assess their impact on intraocular lens (IOL) power calculations using various formulas.

DESIGN

Retrospective multicenter intra-instrument reliability analysis.

METHODS

The study involved the analysis of biometry data collected from ten international centers across Europe, the United States, and Asia. Corneal power was expressed as equivalent power and astigmatic vector components for both K and TK values. The study assessed the influence of these differences on IOL power calculations using different formulas. The results were analyzed and plotted using Bland-Altman and double angle plots.

RESULTS

The study encompassed a total of 116,982 measurements from 57,862 right eyes and 59,120 left eyes. The analysis revealed a high level of agreement between K and TK values, with 93.98% of eyes exhibiting an absolute difference of 0.25 D or less. Astigmatism vector differences exceeding 0.25 D and 0.50 D were observed in 39.43% and 1.08% of eyes, respectively.

CONCLUSIONS

This large-scale study underscores the similarity between mean K and TK values in healthy eyes, with rare clinical implications for IOL power calculation. Noteworthy differences were observed in astigmatism values between K and TK. Future investigations should delve into the practicality of TK values for astigmatism correction and their implications for surgical outcomes.

FEA-Based Stress-Strain Barometers as Forecasters for Corneal Refractive Power Change in Orthokeratology

PURPOSE

To improve the effectivity of patient-specific finite element analysis (FEA) to predict refractive power change (RPC) in rigid Ortho-K contact lens fitting. Novel eyelid boundary detection is introduced to the FEA model to better model the effects of the lid on lens performance, and stress and strain outcomes are investigated to identify the most effective FEA components to use in modelling.

METHODS

The current study utilises fully anonymised records of 249 eyes, 132 right eyes, and 117 left eyes from subjects aged 14.1 ± 4.0 years on average (range 9 to 38 years), which were selected for secondary analysis processing. A set of custom-built MATLAB codes was built to automate the process from reading Medmont E300 height and distance files to processing and displaying FEA stress and strain outcomes. Measurements from before and after contact lens wear were handled to obtain the corneal surface change in shape and power. Tangential refractive power maps were constructed from which changes in refractive power pre- and post-Ortho-K wear were determined as the refractive power change (RPC). A total of 249 patient-specific FEA with innovative eyelid boundary detection and 3D construction analyses were automatically built and run for every anterior eye and lens combination while the lens was located in its clinically detected position. Maps of four stress components: contact pressure, Mises stress, pressure, and maximum principal stress were created in addition to maximum principal logarithmic strain maps. Stress and strain components were compared to the clinical RPC maps using the two-dimensional (2D) normalised cross-correlation and structural similarity (SSIM) index measure.

RESULTS

On the one hand, the maximum principal logarithmic strain recorded the highest moderate 2D cross-correlation area of 8.6 ± 10.3%, and contact pressure recorded the lowest area of 6.6 ± 9%. Mises stress recorded the second highest moderate 2D cross-correlation area with 8.3 ± 10.4%. On the other hand, when the SSIM index was used to compare the areas that were most similar to the clinical RPC, maximum principal stress was the most similar, with an average strong similarity percentage area of 26.5 ± 3.3%, and contact pressure was the least strong similarity area of 10.3 ± 7.3%. Regarding the moderate similarity areas, all components were recorded at around 34.4% similarity area except the contact pressure, which was down to 32.7 ± 5.8%.

CONCLUSIONS

FEA is an increasingly effective tool in being able to predict the refractive outcome of Ortho-K treatment. Its accuracy depends on identifying which clinical and modelling metrics contribute to the most accurate prediction of RPC with minimal ocular complications. In terms of clinical metrics, age, Intra-ocular pressure (IOP), central corneal thickness (CCT), surface topography, lens decentration and the 3D eyelid effect are all important for effective modelling. In terms of FEA components, maximum principal stress was found to be the best FEA barometer that can be used to predict the performance of Ortho-K lenses. In contrast, contact pressure provided the worst stress performance. In terms of strain, the maximum principal logarithmic strain was an effective strain barometer.

Comparison of corneal tomographic parameters between Hispanic and non-Hispanic patients

PURPOSE

To compare corneal tomographic parameters between Hispanic White and non-Hispanic White patients using Pentacam data.

METHODS

This retrospective study evaluated preoperative Pentacam data from 641 patients 50 years or older who underwent surgery for senile cataract and self-identified as Hispanic or non-Hispanic White. Patients of non-White race or multiethnic groups, or a history of surgery, trauma, or any abnormality of the cornea or anterior segment were excluded. Cornea and anterior segment parameters, as measured with Pentacam, were then compared between Hispanics and non-Hispanics.

RESULTS

There were 352 Hispanic White and 289 non-Hispanic White patients. These included 231 men and 410 women, with a mean age of 69.5 ± 8.2 years. There were no significant differences between Hispanics and non-Hispanics in front or back keratometry or amount of front astigmatism. However, Hispanics had a greater amount of back astigmatism (0.36 ± 0.19 vs 0.32 ± 0.17 diopter, P = 0.04). Moreover, there was a statistically significant difference in front steep axis of the left eyes between Hispanics and non-Hispanics (97.8 ± 47.9 vs 108.2 ± 48.9 deg, P = 0.01), and a marginally significant difference in front steep axis of the right eyes (81.0 ± 48.2 vs 73.5 ± 49.9 deg, P = 0.06). Hispanics also had a lower vertex pachymetry (548.1 ± 34.5 vs 553.4 ± 37.4 μm, P = 0.04) and a smaller anterior chamber volume (134.7 ± 39.0 vs 146.1 ± 39.9 mm3, P < 0.001).

CONCLUSIONS

There are some differences in cornea and anterior segment parameters between Hispanics and non-Hispanics 50 years or older who underwent surgery for senile cataract. However, such differences may not be clinically significant.

Actual anterior-posterior corneal radius ratio in eyes with prior myopic laser vision correction according to axial length

We retrospectively evaluate the actual anterior-posterior (AP) corneal radius ratio in eyes with previous laser correction for myopia (M-LVC) according to axial length (AL) using biometry data exported from swept-source optical coherence tomography between January 2018 and October 2021 in a tertiary hospital (1018 eyes with a history of M-LVC and 19,841 control eyes). The AP ratio was significantly higher in the LVC group than in the control group. Further, it was significantly positively correlated with AL in the LVC group. We also investigated the impact of the AP ratio, AL and keratometry (K) on the absolute prediction error (APE) in 39 eyes that underwent cataract surgery after M-LVC. In linear regression analyses, there were significant correlations between APE and AL/TK, while APE and AP ratio had no correlation. The APE was significantly lower in the Barrett True-K with total keratometry (Barrett True-TK) than in the Haigis-L formula on eyes with AL above 26 mm and K between 38 and 40 D. In conclusion, in eyes with previous M-LVC, AP ratio increases with AL. The Barrett True-K or Barrett True-TK formulas are recommended rather than Haigis-L formula in M-LVC eyes with AL above 26 mm and K between 38 and 40D.

Comparison of Corneal Power Difference Maps with Achieved Myopic Correction Using Scheimpflug Tomography After LASIK, PRK, and SMILE

Purpose

To compare corneal power difference maps (∆maps) obtained from the Pentacam in patients with 1 year follow-up after LASIK, PRK, and SMILE with further stratification to low, moderate, and high myopia.

Patients and methods

This retrospective study was comprised of patients who had preoperative and 1-year postoperative power maps that were obtained-front sagittal (SagF), refractive power (RP), true net power (TNP), and total corneal refractive power (TCRP)-for evaluation. Measurements were recorded and compared at the 4mm, 5mm and 6mm pupil and apex zones. Comparisons were made between each specific power ∆map and the surgically induced refractive change (SIRC). Further analysis of the ∆maps was performed based on degree of myopia (high, moderate, and low). Correlation and agreement were also assessed with regression and limits of agreement (LoA).

Results

There were 172 eyes in the LASIK group, 187 eyes in the PRK group, and 46 eyes in the SMILE group. In the LASIK group, TNP ∆map at 5mm pupil zone had the least absolute mean difference with SIRC (0.007 ± 0.42D). In the PRK group, TNP ∆map at 5mm apex zone was most accurate compared to SIRC (0.066 ± 0.45D). In the SMILE group, TCRP ∆map at 4mm apex zone had the closest absolute value when compared to SIRC (0.011 ± 0.50D). There was good correlation and agreement for all three surgery groups, LASIK: r = 0.975, LoA -0.83D to +0.83D, PRK: r = 0.96, LoA -0.83D and +0.95D, and SMILE: r = 0.922, LoA -0.97 D to +0.99D.

Conclusion

TNP ∆maps most accurately measured corneal power in the LASIK and PRK groups while TCRP ∆maps were most accurate in the SMILE group. The degree of myopia may change which ∆map is most accurate.

The CRW1 Index: Identification of Eyes with Previous Myopic Laser Vision Correction Using Only a Swept-Source OCT Biometer

PURPOSE

To develop and test a novel index (Cooke-Riaz-Wendelstein [CRW1]) that uses swept-source optical coherence tomography (SS-OCT) biometry measurements (IOLMaster700, Zeiss Meditec), including total keratometry, to alert clinicians that previous myopic laser vision correction (M-LVC) was present in a measured eye.

DESIGN

Retrospective, multicenter, comparative diagnostic analysis.

METHODS

The study took place at 6 centers in the United States and Austria. Anonymized SS-OCT biometry datasets acquired between 2018 and 2020 and containing 49,199 eyes were analyzed. The LVC status, as identified by the biometrist, was used to segregate eyes into LVC and non-LVC eyes. Data were split into training (10,780 eyes) and validation (38,419 eyes) sets. Subset analysis was performed for CRW1 Index accuracy compared to posterior/anterior corneal curvature ratio (R_post/R_ant), topography with corneal analysis software (Atlas 9000 with Pathfinder II, Zeiss Meditec), tomography (Pentacam, Oculus), dual Scheimpflug-Placido system (Galilei G6, Ziemer), and a cloud-based platform for cataract surgery planning (Veracity, Zeiss Meditec). A positive predictive value (PPV) of ≥90% was targeted for the CRW1 index. True positives, true negatives, sensitivity, and specificity were recorded.

RESULTS

The CRW1 Index compared favorably against R_post/R_ant showing a higher PPV (93% vs 65%), with fewer false-positive results (29 vs 180). CRW1 performed similarly to topography software and better than the corneal imaging devices. The CRW1 cutoff value can be adjusted to increase sensitivity (CRW1-IS) to detect additional M-LVC eyes.

CONCLUSIONS

The CRW1 and CRW1-IS indices offer surgeons and researchers a readily accessible method to use only SS-OCT biometry measurements to detect eyes with a high probability of previous M-LVC.

Astigmatism Profile in a Large Series of Brazilian Patients

PURPOSE

To assess anterior, posterior, and total corneal astigmatism in a large sample of Brazilian patients.

METHODS

In this retrospective cross-sectional study, all patients whose corneas were imaged with the Galilei G6 (Ziemer Ophthalmology) between January 2017 and February 2019 at HOPE Eye Hospital, in Recife, Brazil, were eligible to participate. Anterior, posterior, and total corneal astigmatism values were collected and analyzed.

RESULTS

The study included 3,253 eyes of 1,919 patients. The mean magnitude of the anterior, posterior, and total corneal astigmatism was 1.50 ± 1.11, 0.34 ± 0.15, and 1.29 ± 0.98 diopters (D), respectively. Corneal astigmatism was greater than 0.50 D in the anterior cornea of 86.3% of eyes (2,807 eyes) and in the posterior cornea of 13.2% of eyes (429 eyes). Vertical alignment of the steepest corneal meridian was observed in the anterior cornea of 74.5% of eyes (2,423 eyes) and in the posterior cornea of 93.1% of eyes (3,029 eyes). The correlation between the astigmatism magnitude of the anterior and posterior cornea was strong when the steep anterior meridian was aligned vertically (r = 0.720; P < .001), and absent when it was aligned horizontally (r = 0.102; P = .036).

CONCLUSIONS

Corneal astigmatism values in the Brazilian population were similar to those found in other ethnicities, suggesting that toric calculators, nomograms, coefficients of adjustment, and formulas that were developed based on astigmatism values of other populations may be used in Brazilian patients with comparable accuracy. [J Refract Surg. 2023;39(1):56-60.].

Intraocular lens constant optimization in toric intraocular lens calculation using keratometry and total corneal power

PURPOSE

To evaluate intraocular lens (IOL) constant optimization in toric IOL calculation with keratometry (K) and total corneal refractive power (TCRP).

METHODS

Predicted spherical equivalent (SE) and residual astigmatism (RA) with K and TCRP were retrospectively calculated using the Haigis, Holladay 1, and SRK/T formulae and optimized IOL constants. The results of the Barrett calculator and the Abulafia-Koch formula with K were also calculated. The median absolute error in SE (MedAE-SE), mean absolute error in RA (MAE-RA), and centroid error (CE) were analyzed.

RESULTS

Seventy-nine eyes of 71 patients implanted with toric IOLs were included. With K, there were no significant differences between the results before and after constant optimization using all the formulae. With TCRP, constant optimization significantly reduced MedAE-SE; however, significantly increased MAE-RA and CE using the Holladay 1 and SRK/T formulae. MedAE-SE, MAE-RA, and CE using the Haigis formula did not show significant differences. The difference in the predicted RA before and after constant optimization increased with IOL toricity. The MedAE-SE predicted by TCRP was significantly higher than that predicted by K despite constant optimization. The MAE-RA and CE predicted by TCRP were significantly lower than those predicted by K without posterior corneal astigmatism optimization; however, were not significantly different from those predicted by the Barrett and Abulafia-Koch formulae.

CONCLUSIONS

Constant optimization is recommended when using the TCRP in toric IOL calculations, particularly for patients with large astigmatism. However, TCRP did not yield more accurate results than optimized K in toric IOL calculations despite constant optimization.

Limitations of Reconstructing Pentacam Rabbit Corneal Tomography by Zernike Polynomials

The study aims to investigate the likelihood of Zernike polynomial being used for reconstructing rabbit corneal surfaces as scanned by the Pentacam segment tomographer, and hence evaluate the accuracy of corneal power maps calculated from such Zernike fitted surfaces. The study utilised a data set of both eyes of 21 rabbits using a reverse engineering approach for deductive reasoning. Pentacam raw elevation data were fitted to Zernike polynomials of orders 2 to 20. The surface fitting process to Zernike polynomials was carried out using randomly selected 80% of the corneal surface data points, and the root means squared fitting error (RMS) was determined for the other 20% of the surface data following the Pareto principle. The process was carried out for both the anterior and posterior surfaces of the corneal surfaces that were measured via Pentacam scans. Raw elevation data and the fitted corneal surfaces were then used to determine corneal axial and tangential curvature maps. For reconstructed surfaces calculated using the Zernike fitted surfaces, the mean and standard deviation of the error incurred by the fitting were calculated. For power maps computed using the raw elevation data, different levels of discrete cosine transform (DCT) smoothing were employed to infer the smoothing level utilised by the Pentacam device. The RMS error was not significantly improved for Zernike polynomial orders above 12 and 10 when fitting the anterior and posterior surfaces of the cornea, respectively. This was noted by the statistically non-significant increase in accuracy when the order was increased beyond these values. The corneal curvature calculations suggest that a smoothing process is employed in the corneal curvature maps outputted by the Pentacam device; however, the exact smoothing method is unknown. Additionally, the results suggest that fitting corneal surfaces to high-order Zernike polynomials will incur a clinical error in the calculation of axial and tangential corneal curvature of at least 0.16 ± 01 D and 0.36 ± 0.02 D, respectively. Rabbit corneal anterior and posterior surfaces scanned via the Pentacam were optimally fitted to orders 12 and 10 Zernike polynomials. This is essential to get stable values of high-order aberrations that are not affected by Zernike polynomial fittings, such as comas for Intracorneal Ring Segments (ICRS) adjustments or spherical aberration for pre-cataract operations. Smoothing was necessary to replicate the corneal curvature maps outputted by the Pentacam tomographer, and fitting corneal surfaces to Zernike polynomials introduces errors in the calculation of both the axial and tangential corneal curvatures.

ANALYSIS OF CORNEAL ANTEROPOSTERIOR RATIO OF OPTICAL POWER USING OCT

AIMS

The aim of the study was to analyse the values of the anteroposterior corneal optical power ratio (AP ratio), to compare the resulting values with those of theoretical models of the eye, and to define the effect of using an individual ratio value on the approximation of the total corneal power.

MATERIAL AND METHODS

A total of 406 eyes were included. Each patient underwent an OCT (RTVue XR) examination, according to which the AP ratio of the cornea was determined, as well as the biometric parameters of the eye (Lenstar LS900). The correlation between the biometric parameters of the eye and the individual AP ratio values was evaluated using Pearsons correlation coefficient. In the analysis, the AP ratio results were compared with selected schematic models of the eye. Using Gaussian equations, a theoretical calculation of the total corneal optical power (KG) was performed, by fitting the AP ratio value and comparing it with the actually measured total corneal power (TCP).

RESULTS

The mean value of the individually determined AP ratio was 1.17 ±0.02. The most frequently represented interval (33.74 %) was 1.17 to 1.18 AP ratio values, with the vast majority of eyes (79.56 %) in the range of 1.15 to 1.20. Individual values of total corneal optical power were statistically significantly different (p &lt; 0.05) from the theoretical values of TCP (except in the Liu-Brennan eye model, where p = 0.06). The lowest mean difference of values was found for the Navarro schematic model. The dependence of the measured AP ratio values and biometric parameters reached a moderate negative correlation (r = -0.50 for p &lt; 0.05) with the parameter corneal posterior surface curvature (Rp), as well as a weak negative correlation with limbal diameter WtW (r = -0.26 for p &lt; 0.05) and a weak positive correlation with central corneal thickness CCT (r = 0.17 for p &lt; 0.05).

CONCLUSION

The assumption of a constant value of the AP ratio according to the selected schematic models of the eye is statistically significantly different from the actual measured values and was defined to have only a negative weak correlation with the size of the limbus diameter. Using the resulting average value of the determined AP ratio (1.17 ±0.02), a lower difference between real and calculated total corneal optical power was achieved.

Back-calculation of keratometer index based on OCT data and raytracing - a Monte Carlo simulation

PURPOSE

This study aims to develop a raytracing-based strategy for calculating corneal power from anterior segment optical coherence tomography data and extracting the individual keratometer index, which converts the corneal front surface radius to corneal power.

METHODS

A large OCT dataset (10,218 eyes of 8,430 patients) from the Casia 2 (Tomey, Japan) was post-processed in MATLAB (MathWorks, USA). Radius of curvature, asphericity of the corneal front and back surface, central corneal thickness and pupil size (aperture) were used to trace a bundle of rays through the cornea and derive the best focus plane. Corneal power was calculated with respect to the corneal front vertex plane, and the keratometer index was back-calculated using corneal power and front surface radius. Keratometer index was analysed in a multivariate linear model.

RESULTS

The averaged resulting keratometer index was 1.3317 ± 0.0017 with a median of 1.3317 and range from 1.3233 to 1.3390. In a univariate model, only the front surface asphericity affected the keratometer index. The multivariate model for modelling the keratometer index using all 6 input parameters performed very well (RMS error: 5.54e-4, R² : 0.90, significance vs. constant model: <0.0001).

CONCLUSIONS

In the classical calculation, the keratometer index used for converting corneal radius to dioptric power uses several model assumptions. As these assumptions are not generally satisfied, corneal power cannot be calculated from corneal front surface radius alone. Considering all 6 input variables, the linear prediction model performs well and can be used if all input parameters are measured with a tomographer.

The Efficiency of Using Mirror Imaged Topography in Fellow Eyes Analyses of Pentacam HR Data

Purpose: To investigate the effectiveness of flipping left corneas topography and analysethem quantitively along with fellow right corneas based on the assumption that they are mirror images of each other. Methods: The study involved scanning both eyes of 177 healthy participants (aged 35.3 ± 15.8) and 75 keratoconic participants (aged 33.9 ± 17.8). Clinical tomography data were collected for both eyes using the Pentacam HR and processed by a fully automated custom-built MATLAB code. For every case, the right eye was used as a datum fixed surface while the left cornea was flipped around in the superior–inferior direction. In this position, the root-mean-squared difference (RMS) between the flipped left cornea and the right cornea was initially determined for both the anterior and posterior corneal surfaces. Next, the iterative closest point transformation algorithm was applied on the three-dimensional flipped cornea to allow the flipped left corneal anterior surface to translate and rotate, minimising the difference between it and the right corneal anterior surface. Then, the RMS differences were recalculated and compared. Results: A comparison of the dioptric powers showed a significant difference between the RMS of both the flipped left eyes and the right eyes in the healthy and the KC groups (p < 0.001). The RMS of the surfaces of the flipped left corneas and the right corneas was 0.6 ± 0.4 D among the healthy group and 4.1 ± 2.3 among the KC group. After transforming the flipped left corneas, the RMS was recorded as 0.5 ± 0.3 D and 2.4 ± 2 D among the healthy and KC groups, respectively. Conclusions: Although fellow eyes are highly related in their clinical parameters, they should be treated with care when one eye topography is flipped and processed with the other eye topography in an optic-related research analysis where translation might be needed. In KC, an asymmetric disease, it was observed that a portion of the asymmetry was due to a corneal apex shift interfering with the image acquisition. Therefore, transforming the flipped left eyes by rotation and translation results in a fairer comparison between the fellow KC corneas.

Comparative Accuracy of Barrett Toric Calculator With and Without Posterior Corneal Astigmatism Measurements and the Kane Toric Formula

PURPOSE

To compare the accuracy of the Barrett toric calculator with and without posterior corneal astigmatism and the Kane toric calculator.

DESIGN

Retrospective cross-sectional study.

METHODS

The study included a total of 79 eyes of 79 patients who underwent toric intraocular lens (IOL) insertion during uncomplicated cataract surgery by a single surgeon. Using vector analysis, the mean absolute prediction error, the standard deviation of the prediction error, and the percentage of eyes with a prediction error within ±0.50 diopter (D), ± 0.75 D, and ± 1.00 D were calculated. The IOL Master 700 (Carl Zeiss Meditec AG, Jena, Germany) was used for measuring biometry including posterior corneal astigmatism. The main analysis was designed to provide the clinical outcomes with each formula using the postoperative keratometry values and the measured postoperative IOL axis. Real-world analysis was performed using the preoperative keratometry values and the intended IOL axis.

RESULTS

There was no significant difference in mean absolute prediction errors calculated with 2 versions of the Barrett toric formula (predicted posterior corneal astigmatism and measured posterior corneal astigmatism) and the Kane toric formula (P > .05). The Barrett toric calculator with predicted and measured posterior corneal astigmatism yielded the best results, with 60.8% <0.50 D prediction error in the main analysis. In the real-world analysis, the Barrett toric calculator with predicted posterior corneal astigmatism showed the best result, with 53.2% <0.50 D prediction error.

CONCLUSION

The Barrett toric formula with and without posterior corneal astigmatism measurements using the IOL Master 700 and the Kane toric formula yielded accurate and comparable outcomes in this single-surgeon analysis. Am J Ophthalmol 2021;221:•••-•••. © 2021 Elsevier Inc. All rights reserved.

Calculation of Toric Intraocular Lens Power with the Barrett Calculator and Data from Three Keratometers

Aim

To investigate the interdevice agreement for differences in toric power calculated using data on anterior corneal astigmatism obtained with corneal topography/ray-tracing aberrometry (iTrace), partial coherence interferometry (IOLMaster 500), and Scheimpflug imaging (Pentacam).

Methods

The analysis included 101 eyes (101 subjects) with regular astigmatism. The main outcome measures were corneal cylinder power, axis of astigmatism, and keratometry values. Toricity and toric IOL power were calculated using the online Barrett toric calculator. Interdevice agreement for measurement and calculation was assessed using a paired sample t-test and a nonparametric test.

Results

Significant interdevice differences were noted in the magnitude of astigmatism and flat, steep, and mean keratometry values between iTrace and IOLMaster (all P < 0.01); in flat, steep, and mean keratometry values (all P < 0.001) but not in the magnitude of astigmatism (P=0.325) between iTrace and Pentacam; and in the magnitude of astigmatism and steep and mean keratometry values (all P < 0.01) but not in flat keratometry values (P=0.310) between IOLMaster and Pentacam. The toric IOL power calculated using data from the three devices showed the following trend: iTrace > IOLMaster (0.49 ± 0.36, P < 0.001) and Pentacam (0.39 ± 0.42, P < 0.001) and Pentacam was <IOLMaster (-0.10 ± 0.39, P=0.009). There were differences in toricity calculated using data from the three devices (P=0.004).

Conclusions

Differences in toric IOL power and toricity calculated using anterior keratometry data from iTrace, IOLMaster 500, and Pentacam should be noted in clinical practice.

The role of posterior corneal power in 21st century biometry: A review

PURPOSE

Intraocular lens (IOL) calculation and biometry have evolved significantly in recent decades. However, present outcomes are still suboptimal. Our objective is to summarize the results reported in the literature with regard to a new variable, the value of the relationship between anterior and posterior corneal curvature in the biometric calculation of IOL power.

METHODS

We have created a narrative revision of the existing evidence regarding the posterior to anterior corneal curvature ratio in IOL calculation.

RESULTS

The corneal posterior/anterior ratio (P/A ratio), also called Gullstrand ratio, has a standard deviation of 2.4% in normal people, hence causing a possible IOL power miscalculation error of up to 0.75 diopters (D). This error is magnified in pathological corneas or in those with previous refractive surgery. Including the P/A ratio in the IOL formula reduces errors in the calculation of IOL power.

CONCLUSIONS

Measurement of the posterior corneal surface should be recommended prior to IOL calculation, given the demonstrated results regarding the P/A ratio for IOL power calculation. Regarding toric IOL calculation, we suggest incorporation of all internal astigmatic vectors, for instance, posterior corneal surface, IOL tilt induced toricity, and retinal astigmatism. All of these factors may improve surgical outcomes.

Distribution and internal correlations of corneal astigmatism in cataract patients

The aim of the study is to explore the distribution patterns and internal correlations of the morphological parameters of the cornea in patients with age-related cataract. The Pentacam HR was used to measure anterior corneal astigmatism (ACA), posterior corneal astigmatism (PCA), total corneal astigmatism (TCA) and keratometric corneal astigmatism (KCA). With age, the proportion of with-the-rule (WTR) ACA decreased from 65.31% to 23.63%, while the against-the-rule (ATR) ACA increased from 26.53% to 56.20%. PCA exceeded 0.50 D in 9.14% of eyes, while 76.35% of them were ATR. The magnitude of ACA was positively correlated with PCA in the whole sample, with a more significant correlation in WTR eyes (s_r = 0.349, P < 0.001). The vector summation effect of PCA to ACA changed from compensation to augmentation with aging. In 57.53% of WTR eyes, KCA was overestimated by an average of 0.21 ± 0.17 D, while it was underestimated by 0.38 ± 0.27 D in 87.62% of ATR eyes. In conclusion, among age-related cataract patients, ACA and TCA gradually shifted from WTR to ATR with aging, while most PCA remained as ATR. Ignoring the age-related changes and real PCA might cause overestimation of WTR astigmatism and underestimation of ATR astigmatism.

[Back-calculation of the keratometer index-Which value would have been correct in cataract surgery?]

BACKGROUND AND PURPOSE

In the clinical routine the conversion of corneal radii into corneal refractive power using a keratometer index is rarely discussed. The purpose of this study was to back-calculate the keratometer index in pseudophakic eyes based on the refractive power of the lens, biometric measurements and refraction, and to compare it to clinically established values.

PATIENTS AND METHODS

In this retrospective case series 99 eyes of 99 patients without pathological alterations, previous diseases, comorbidities or history of ocular surgery apart from the uneventful cataract surgery were enrolled. In all eyes a CT Asphina 409M(P) (Carl-Zeiss Meditec, Berlin, Germany) had been implanted by two surgeons (EF and PE). For calculation we used shape and power data of the intraocular lens and data from optical biometry (axial length, pseudophakic anterior chamber depth, lens thickness, corneal radius; IOLMaster 700, Carl-Zeiss Meditec, Jena, Germany). The refraction was derived manually with a trial frame (measurement distance 5 m) and autorefractometry (iProfiler, Carl-Zeiss, Jena, Germany). For this three model eyes were used: a thin lens with the nominal refractive power positioned in the equatorial plane (model A) or in the secondary principal plane of the thick lens (model B) as well as a model considering the intraocular lens as a thick lens located at its measured position (model C).

RESULTS

Back-calculation of the keratometer index using vergence formulas resulted in a keratometer index based on subjective refraction measurements considering lane distance correction of 1.3307 ± 0.0026/1.3312 ± 0.0026/1.332 ± 0.0027 for model A/model B/model C, respectively. Based on objective refraction measurements (autorefraction calibrated to infinity object distances) resulted in a keratometer index of 1.3301 ± 0.0021/1.3306 ± 0.0021/1.3315 ± 0.0021, for model A/model B/model C, respectively. The keratometer index did not show any trend in linear regression for axial length or corneal radius for any of the three models or for any refraction method.

CONCLUSION

The keratometer index derived from back-calculation matched with the Zeiss index (1.332) but was much lower compared to other established indexes, e.g. the Javal index (1.3375). The missing trend for axial length or corneal radius implies that simple vergence formulas for intraocular lens refractive power calculation without correction terms or fudge factors perform best with a keratometer index slightly below 1.332, if the biometrically measured position of the intraocular lens is used as the effective lens position.

Comparison of refractive outcomes using Scheimpflug Holladay equivalent keratometry or IOLMaster 700 keratometry for IOL power calculation

PURPOSE

This study aims to compare postoperative refractive error results using Pentacam (Oculus Optikgeräte GmbH) Holladay equivalent keratometry readings (EKR) or IOLMaster 700 (Carl Zeiss Meditec AG) keratometry (K) values in IOL power calculation.

MATERIAL AND METHODS

This retrospective study included 54 eyes of 31 patients who underwent cataract surgery. Preoperative biometric measurements of all patients were obtained using IOLMaster 700 followed by Pentacam measurements. IOLMaster 700 K measurements on horizontal (K1) and vertical (K2) axes and EKR measurements on 2 mm (EKR2mm), 3 mm (EKR3mm) and 4.5 mm (EKR4.5 mm) corneal zones were recorded. EKR4.5 mm value and IOLMaster 700 K values were used in Holladay-II, SRK/T, Haigis, and Hoffer-Q formulas to calculate predictive refractive error (PRE). Absolute refractive error (ARE) was calculated as the absolute difference between actual postoperative refractive error (APRE) and PRE values.

RESULTS

Mean age was 72.2 ± 8.3 (51-87) years and mean IOL power was 21.5 ± 2.9 D (18-23 D). There was no significant difference between PRE values when IOLMaster 700 K measurements and EKR4.5 mm K measurements were used in Holladay-II, SRK/T, Haigis, and Hoffer-Q formulas (p = 0.571, p = 0.833, p = 0.165, p = 0.347, respectively). There was no significant difference between APRE and ARE values (p = 0.124). According to mean ARE results, the closest estimate was achieved when the IOLMaster 700 K values were used in the Holladay-II formula (p = 0.271).

CONCLUSION

IOLMaster 700 K measurement and Pentacam EKR4.5 mm measurements can be used interchangeably. IOLMaster 700 K values yielded the most predictive measurement of the refractive result using the Holladay-II formula.

Fibril density reduction in keratoconic corneas

This study aims to estimate the reduction in collagen fibril density within the central 6 mm radius of keratoconic corneas through the processing of microstructure and videokeratography data. Collagen fibril distribution maps and topography maps were obtained for seven keratoconic and six healthy corneas, and topographic features were assessed to detect and calculate the area of the cone in each keratoconic eye. The reduction in collagen fibril density within the cone area was estimated with reference to the same region in the characteristic collagen fibril maps of healthy corneas. Together with minimum thickness and mean central corneal refractive power, the cone area was correlated with the reduction in the cone collagen fibrils. For the corneas considered, the mean area of keratoconic cones was 3.30 ± 1.90 mm². Compared with healthy corneas, fibril density in the cones of keratoconic corneas was lower by as much as 35%, and the mean reduction was 17 ± 10%. A linear approximation was developed to relate the magnitude of reduction to the refractive power, minimum corneal thickness and cone area (R² = 0.95, p < 0.001). Outside the cone area, there was no significant difference between fibril arrangement in healthy and keratoconic corneas. The presented method can predict the mean fibril density in the keratoconic eye's cone area. The technique can be applied in microstructure-based finite-element models of the eye to regulate its stiffness level and the stiffness distribution within the areas affected by keratoconus.

Contribution of Posterior Corneal Astigmatism to Total Corneal Astigmatism in a Sample of Egyptian Population

Purpose

To determine the percentage of contribution of the magnitude of posterior corneal astigmatism to total corneal astigmatism using Scheimpflug imaging.

Methods

This prospective cross-sectional study was conducted on 356 eyes of 356 patients, where the total corneal astigmatism was calculated by addition of anterior and posterior corneal astigmatism using vector analysis and then the percentage of posterior to total corneal astigmatism was calculated.

Results

The percentage of contribution of posterior to total corneal astigmatism was about 30% in patients with With The Rule astigmatism and about 8% in patients with Against The Rule astigmatism.

Conclusion

Posterior corneal astigmatism should not be neglected during calculation of total corneal astigmatism as neglecting posterior corneal astigmatism can result in errors during calculation and correction of astigmatism.

Comparison of Conventional Keratometry and Total Keratometry in Normal Eyes

Purpose

The relationship between conventional keratometry and total keratometry has not been fully investigated. This study was aimed at conventional keratometry measured with the automated keratometer and total keratometry with the corneal tomographer in ophthalmologically normal subjects.

Methods

We enrolled fifty eyes of 50 consecutive subjects (mean age ± standard deviation, 34.9 ± 8.0 years) who have no ophthalmologic diseases, other than refractive errors, with no history of ocular surgery. Conventional keratometry was measured with the automated keratometer. The total keratometry, the true net power (TNP), and the total corneal refractive power (TCRP) were measured with the Scheimpflug camera, and the real power (RP) was measured with anterior segment optical coherence tomography (As-OCT). Anterior keratometries (Km and AvgK) were also measured with the Scheimpflug camera and the As-OCT, respectively.

Results

Conventional keratometry was 43.64 ± 1.48 D, which was significantly higher than the TCRP (42.94 ± 1.45 D, p = 0.042), the TNP (42.13 ± 1.37 D, p < 0.001), and the RP (42.62 ± 1.39 D, p = 0.001, Dunnett's test). We found significant correlations between conventional keratometry and each total corneal power (the TCRP (Pearson's correlation coefficient r = 0.986, p < 0.001), the TNP (r = 0.986, p < 0.001), the RP (r = 0.987, p < 0.001), the Km (r = 0.990, p < 0.001), and the AvgK (r = 0.991, p < 0.001)). The intraclass correlations of conventional keratometry with the TCRP, the TNP, the RP, the Km, and the AvgK were 0.986, 0.983, 0.985, 0.990, and 0.990, respectively. We found no significant differences in the keratometric data measured with the automated keratometer, the Scheimpflug camera, and the As-OCT (ANOVA, p = 0.729).

Conclusions

Conventional keratometry was significantly larger than total keratometry, by approximately 0.70 to 1.52 D, in ophthalmologically normal subjects. By contrast, there were no significant differences in the keratometric data among the three devices. It is suggested that conventional keratometry overestimates the total corneal power in daily practice.

Comparison of Multicolored Spot Reflection Topographer and Scheimpflug-Placido System in Corneal Power and Astigmatism Measurements With Normal and Post-refractive Patients

PURPOSE

To evaluate the repeatability of corneal power and astigmatism derived by a novel multicolored spot reflection topographer system (Cassini; i-Optics, Hague, Netherlands) and compare its agreement with a Placido-Scheimpflug system (Sirius; Costruzione Strumenti Oftalmici, Florence, Italy) in normal and post-refractive patients.

METHODS

This prospective study comprised patients who underwent myopic excimer laser refractive surgery (96 eyes) and normal patients (102 eyes). Each patient was measured three times with the Cassini and Sirius. The simulated keratometry (SimK), total corneal power (TCP), and astigmatism were recorded. The repeatability was assessed by one-way analysis of variance. The paired t test was used to compare the differences, whereas the agreement was evaluated by Bland-Altman analysis.

RESULTS

All parameters obtained by the Cassini demonstrated high repeatability, except for total corneal astigmatism (TCA) in the post-refractive group. The intraclass correlation coefficients of all parameters were greater than 0.85, the correlation of variation values was less than 0.55%, and the test-retest repeatability was less than 0.85 diopters (D). The paired t test showed significant differences in steep keratometry, astigmatism, TCP, and TCA in the normal group and in J₀, TCP, and TCA in the post-refractive group. The 95% limits of agreement (LoA) in the normal group demonstrated good agreement, except for TCP. Only J₀ and J₄₅ of astigmatism and TCA remained narrow for 95% LoA in the post-refractive group.

CONCLUSIONS

These results suggested that the Cassini provided high repeatable measurements in corneal power and astigmatism, except the TCA of post-refractive patients. The parameters could be used interchangeably in normal patients, except for TCP, whereas only J₀ of astigmatism and J₀, J₄₅ of TCA showed good agreement in post-refractive patients. [J Refract Surg. 2019;35(6):370-376.].

Accuracy of corneal astigmatism correction with two Barrett Toric calculation methods

AIM

To compare the prediction error between Barrett Toric calculator and the new online AcrySof Toric calculator which incorporated Barrett astigmatism algorithm in Chinese cataract eyes with normal axial length and anterior chamber depth (ACD).

METHODS

Prospective case-control study. All the cases had axial length (21-26 mm) with ACD no less than 2.4 mm. Keratometric values were measured by LenSTAR 900. The Barrett Toric calculator was used in group 1. In group 2, SRK-T formula was used to determine the spherical power of the Toric lens, and subsequent calculation of the cylinder type was performed using the new online Alcon Toric calculator. At 1 and 3mo after surgery, a comprehensive subjective optometry was performed. The predicted residual astigmatism calculated by the two calculators was compared with that obtained by postoperative refraction, and the difference was defined as the astigmatism correction error [error of refractive astigmatism (ERA)]. The error magnitude (EM) refers to the algebraic deviation of ERA, and the error vector (EV) indicates the vector deviation of ERA. The influence of the two calculation methods on the correction accuracy of toric IOL was quantitatively analyzed.

RESULTS

The |EM| obtained at 1mo after surgery were 0.21±0.12 D, 0.22±0.18 D in group 1 and group 2 respectively, and correspondingly turned to be 0.19±0.13 D, 0.20±0.19 D at 3mo after surgery, with no statistical difference (P=0.633, P=0.877). The vector analysis showed that |EV| values in two groups at 1mo after surgery were 0.29±0.14@105 (D@angle) and 0.35±0.20@113 (D@angle), respectively, whereas |EV| values 3mo after surgery were 0.27±0.16@86 (D@angle) and 0.32±0.23@102 (D@angle), respectively. The differences between the groups were not statistically significant (P=0.119, P=0.261).

CONCLUSION

The clinical effect of Barrett Toric calculator has a much more accurate tendency than that of new online AcrySof Toric calculator, but is not evident in cases with normal axial length and normal anterior posterior ratio.

Posterior corneal astigmatism: a review article

Most human eyes show at least a small degree of corneal astigmatism and it can arise from both surfaces of the cornea. The shape of the anterior corneal surface provides no definitive basis for knowing the toricity of the posterior surface. In the previous studies, average astigmatism of the posterior corneal surface was -0.26 to -0.78 diopter. The radius of the posterior corneal surface is less than the radius of the anterior corneal surface. Most studies have found a clear correlation between the anterior and posterior corneal asphericities and the asphericity of the posterior surface is independent of the vertex radius of curvature, refractive error and gender. In contrast to the anterior corneal surface, the asphericity of the posterior corneal surface varies significantly between meridians. The anterior and posterior corneal surface would have approximately parallel principal meridians and both of these surfaces are often flatter in the horizontal meridian than the vertical one. This is especially true in the higher degrees of corneal astigmatism, and then about 10% of any anterior corneal astigmatism is neutralized by an astigmatism arising from the posterior corneal surface. Although the second corneal surface only contributes to about 10% of the total refractive power of the eye, a precise knowledge of its morphology is needed for the correct diagnosis and monitoring the corneal diseases or the surgical interventions and in many eyes neglecting the posterior corneal surface measurement may lead to significant deviations from the corneal astigmatism estimation. In this article, we have reviewed the shape and the toricity of the posterior corneal surface and also the effect of age on it. We investigated the contribution of posterior corneal astigmatism to the total corneal astigmatism and evaluated the accuracy of corneal astigmatism estimation by neglecting the posterior corneal surface measurement.

Residual Refractive Astigmatism following Toric Intraocular Lens Implantation without Consideration of Posterior Corneal Astigmatism during Cataract Surgery with Low Anterior Keratometric Astigmatism upto 2.5 Dioptres

Purpose: To determine the refractive astigmatism following toric intraocular lens (tIOL) implantation without consideration of posterior keratometric astigmatism with a conventional tIOL calculator for eyes with low keratometric astigmatism (0.75D to 2.5D) and to theoretically compare the outcomes with predicted refractive astigmatism using a calculator with Barrett's formula.Methods: 34 eyes (34 patients) were assessed with Scheimpflug imaging and underwent tIOL implantation employing conventional tIOL calculator. Eyes were grouped on preoperative keratometric astigmatism as against-the-rule (ATR), with-the-rule (WTR), and oblique (OB). The refractive astigmatism was assessed at 1, 3, 6 and 12 months postoperatively and was classified as ATR, WTR, and OB. Theoretical refractive astigmatism calculations were performed for the same eyes using Barrett's formula.Results: Preoperatively keratometric astigamtism was ATR, WTR, and OB in 32%, 53% and 15% of eyes. At 12 months, in ATR, WTR and OB groups, 45.5%, 16.7% and 60% had ATR refractive astigmatism; 16.7%, 0%, and 20% had WTR refractive astigmatism; 55.6%, 54.5% and 20% were emmetropic (no sphere and cylinder) respectively. There was a significant difference between the theoretical predicted postoperative refractive astigmatism using conventional tIOL calculator and Barrett's formula (P < .05). Postoperative refractive astigmatism was not significantly different from the theoretical predicted refractive astigmatism with Barrett's formula but it was significantly higher than that with a conventional tIOL calculator.Conclusions: At 12 months, with a conventional tIOL calculator, postoperative emmetropia is achieved in half, two third and one-fifth of eyes with preoperatively ATR, WTR, and OB keratometric astigamtism respectively. Around 1/4^th WTR keratometric astigamtism eyes preoperatively were overcorrected to ATR refractive astigmatism whereas ½ATR remained undercorrected at 12 months Outcomes achieved were dissimilar to predicted outcomes with a conventional tIOL calculator but similar to those with Barrett's formula.

Assessment of total corneal power after myopic corneal refractive surgery in Chinese eyes

PURPOSE

To develop a new regression formula based on the Gaussian thick lens formula and to verify the accuracy of the regression formula.

METHODS

In this prospective study, 207 eyes of 207 myopic subjects and 133 eyes of 67 postoperative subjects were included. For the 133 postoperative eyes, 127 eyes underwent laser-assisted in situ keratomileusis, and 6 eyes underwent photorefractive keratectomy. Subjective refraction and Pentacam HR were performed preoperatively and postoperatively, and IOLMaster was performed in the postoperative group. SimK, keratometry based on the Gaussian optic formula (K_GOF), K_CHM obtained using the clinical history method, and the regression formulas K_RF1 and K_RF2 were calculated.

RESULTS

(1) A statistically significant difference (t = 155.164, P = 0.000) between SimK and K_GOF of 1.24 ± 0.12 D was observed, and there was a good correlation between SimK and K_GOF (r = 0.996, P = 0.000). The first regression formula (K_RF1 = 0.351 + 1.021 × K_GOF) was obtained using linear regression. (2) Statistically significant differences (t = 19.114, - 25.184, 4.702, and all P = 0.000) between SimK and K_CHM, K_GOF and K_CHM and K_RF1 and K_CHM of 0.75 ± 0.45 D, 0.96 ± 0.44 D and 0.18 ± 0.43 D, respectively, were obtained. Good correlations between SimK and K_CHM, K_GOF and K_CHM and K_RF1 and K_CHM (all r ≧ 0.977, all Ps = 0.000) were also observed. The regression formula (K_RF2 = - 1.204 + 1.027 × K_RF1) was obtained using linear regression. (3) Six methods were used for the prediction of IOL power in the postoperative group. The highest results were obtained from the Shammas formula (without preoperative data) combining K_m (obtained by IOLMaster) followed by the K_CHM and K_RF2 combining Haigis formula. The third was obtained from the K_CHM and K_RF2 combining Hoffer Q formula; and the smallest was the K_m combining Haigis formula.

CONCLUSION

The IOL power predicted by K_RF2 in eyes after myopic CRS may be accurate.

Consensus on the management of astigmatism in cataract surgery

This project was aimed at achieving consensus on the management of astigmatism during cataract surgery by ophthalmologists from Latin America using modified Delphi technique. Relevant peer-reviewed literature was identified, and 21 clinical research questions associated with the definition, classification, measurement, and treatment of astigmatism during cataract surgery were formulated. Twenty participants were divided into seven groups, and each group was assigned three questions to which they had to respond in written form, after thoroughly reviewing the literature. The assigned questions with corresponding responses by each group were discussed with other participants in round 4 – presentation of findings. The consensus was achieved if approval was obtained from at least 80% of participants. The present paper provides several agreements and recommendations for management of astigmatism during cataract surgery, which could potentially minimize the variability in practice patterns and help ophthalmologists adopt optimal practices for cataract patients with astigmatism and improve patient satisfaction.

Anterior segment parameters in normal dogs using the Pentacam® HR Scheimpflug system

OBJECTIVE

To describe and compare normative anterior segment parameters between canine age groups using the Pentacam^® HR Scheimpflug camera (Pentacam).

ANIMALS STUDIED

Thirty-six sedated dogs (60 eyes) of varying ages and breeds were imaged with the Pentacam; only nondiseased anterior segments were included.

PROCEDURES

Dogs were divided into three age groups: Group 1 (1-5 years), Group 2 (6-10 years), and Group 3 (11-15 years). Values assessed included central corneal thickness (CCT), anterior and posterior corneal elevation (ACE/PCE), anterior and posterior corneal curvature metrics, corneal volume (CV), anterior and posterior corneal astigmatism (AA/PA), anterior chamber depth (ACD), anterior chamber volume (ACV), and anterior chamber angle (ACA). Tukey-adjusted pairwise comparisons were performed.

RESULTS

Overall CCT (mean ± SD) was 631.07 ± 59.91 µm. Central corneal thickness was 608.60 ± 48.63 µm for Group 1, 648.57 ± 51.06 µm for Group 2, and 635.37 ± 73.71 µm for Group 3. Anterior corneal elevation (ACE) measured 9.08 ± 0.58 mm, PCE measured 8.04 ± 0.50 mm, and CV was 58.13 ± 5.39 mm³ . Astigmatism values were 1.34 ± 0.94 D for AA and 0.46 ± 0.44 D for PA. Anterior chamber values were 3.76 ± 0.56 mm for ACD, 383.68 ± 66.24 mm³ for ACV, and 23.62 ± 29.33˚ for ACA. Significant differences were found between Groups 1 and 2 for CV (55.08 ± 4.08 mm³ and 60.32 ± 4.19 mm³ , respectively), (P = 0.02).

CONCLUSIONS

Corneal volume significantly increased between Group 1 and Group 2. Central corneal thickness increased from Group 1 to Group 3, but was not significant with the current sample size. There were no other differences between age groups.

Pentacam Accuracy in Discriminating Keratoconus From Normal Corneas: A Diagnostic Evaluation Study

OBJECTIVES

This study aims to determine the diagnostic ability of Pentacam indices for keratoconus and identifying the best index for differentiating diseased from normal cases.

METHOD

In this study, 150 keratoconus patients and 150 refractive surgery candidates with a definitive diagnosis of normal healthy corneas were enrolled. Initially, the placido disk topography imaging was performed. The keratoconus and normal corneas were defined based on placido disk topographic data from Rabinowitz-McDonnell. After complete eye examinations for all participants, they underwent Pentacam imaging, and corneal surface topographic indices were extracted. Multiple logistic regression was used to determine the best indices for differentiating diseased from healthy corneas, and the receiver operating curve was calculated to determine the diagnostic capability of each index.

RESULTS

Among the studied indices, the keratoconus index (KI), index of vertical asymmetry (IVA), thinnest point (TP), and maximum keratometry (Kmax) were found capable of detecting keratoconus. Among these, IVA was the best index, with an area under curve (AUC) of 95.24%. The best cutoff point for IVA was 0.20 μm, and its sensitivity and specificity were 87.50% and 96.30%, respectively. Comparison of the AUC of different indices showed that only TP and IVA significantly differed (P=0.002). The combination of KI, IVA, Kmax, and TP indices leads to correct detection in 78% of cases.

CONCLUSION

Measuring corneal topographic indices using Pentacam can be helpful in the diagnosis of keratoconus. According to the results of this study, IVA is the best diagnostic index for keratoconus. However, it is recommended to use a combination of Pentacam indices for more accurate differentiation of keratoconus from normal cases.

Keratometric measurements and IOL calculations in pseudophakic post-DSAEK patients

Background

To compare different K readings in pseudophakic patients post-Descemet’s stripping automated endothelial keratoplasty (DSAEK) and evaluate corresponding prediction errors in intraocular lens (IOL) power calculations.

Methods

Subjects that underwent cataract surgery and DSAEK surgery at least 3 and 6 months prior, respectively, and IOL implantation in the capsular bag were included in this study. Manifest refraction and IOL information were recorded. A Scheimpflug keratometer (Pentacam) was used for corneal measurements, including the mean anterior and posterior radii of curvature, simulated keratometer (SimK), true net power (TNP), and equivalent K reading (EKR) at the 4.0-mm zone. Conventional keratometry was acquired using the IOLMaster (K_Master). The four K measurements were evaluated for calculating the predicted refraction.

Results

The study included 20 eyes from 19 subjects. The ratio of the posterior to the anterior corneal radius was 74.1 ± 3.24%. Comparison of the four keratometric methods (K_Master, SimK, EKR, and TNP) revealed statistically significant differences among all the methods besides K_Master and SimK. Of the four IOL calculation methods(K_Master, SimK, EKR and TNP method),the arithmetic prediction error of the K_Master, SimK, and EKR methods featured nonsignificant differences from zero(p = 0.07, 0.19 and 0.84 respectively); the EKR method calculated the highest percentage of eyes with IOLs within the prediction error.

Conclusions

IOL calculations in post-DSAEK eyes using K_Master, SimK, and EKR can yield small refractive errors after surgery. The EKR (4.0-mm diameter) method was found to be the most accurate.

Toric intraocular lenses in eyes with with-the-rule, against-the-rule, and oblique astigmatism: One-year results

PURPOSE

To assess 1-year clinical results of toric intraocular lenses (IOLs) in eyes having with-the-rule (WTR), against-the-rule (ATR), or oblique corneal astigmatism.

SETTING

Four ophthalmic surgical sites, Japan.

DESIGN

Prospective case series.

METHODS

One of 3 toric IOLs or 1 nontoric IOL was implanted in eyes having phacoemulsification and IOL implantation.

RESULTS

The study comprised 218 eyes (155 patients). Based on the suggestion of an online toric calculator with anterior corneal curvature data, 63 eyes received the SN6AT3 IOL with a cylinder power of 1.50 diopters [D] at IOL plane (1.50 D cylinder IOL) 55 eyes the SN6AT4 IOL with a cylinder power of 2.25 D at IOL plane (2.25 D cylinder IOL), and 58 eyes the SN6AT5 IOL with a cylinder power of 3.00 D at IOL plane (3.00 D cylinder IOL) (all Acrysof IQ toric), and 42 eyes received the SN60WF IOL (nontoric IOL). One hundred ninety-four eyes (89.0%) completed 1-year of follow-up. The centroid error in predicted residual astigmatism calculated using vector analysis was close to the origin in eyes with WTR astigmatism (0.17 diopter [D] @ 174.9 ± 0.54 D), while those with ATR and oblique astigmatism were significantly shifted toward the ATR direction (P < .001). The distance from the origin was significantly smaller in the WTR group than in ATR and oblique groups (P < .05). The centroid errors were shifted toward ATR in all toric IOL groups (P < .001); however, the distance from the origin was not different between groups (P = .52). Postoperatively, the mean absolute misalignment of the IOLs was 5.92 degrees ± 5.59 (SD) at 1 day and 6.24 ± 5.87 degrees at 1 year. The results of other clinical parameters were excellent, with no significant differences between astigmatism categories or IOL models.

CONCLUSION

Based on anterior corneal curvature alone, toric IOLs undercorrected ATR and oblique astigmatism; however, 1-year clinical results of toric IOLs were highly stable and satisfactory.

FINANCIAL DISCLOSURE

None of the authors has a financial or proprietary interest in any material or method mentioned.

Impact of the anterior-posterior corneal radius ratio on intraocular lens power calculation errors

Purpose

To evaluate the distribution of the anterior-posterior corneal radius ratio (AP ratio; anterior corneal radius/posterior corneal radius) in patients before cataract surgery, and investigate which parameters can affect this ratio. We also investigated the impact of the AP ratio on the intraocular lens (IOL) power calculation error in cataract surgery.

Method

A total of 501 eyes of 501 consecutive patients who had no history of corneal diseases and had undergone cataract surgery were enrolled in this study. The patients' AP ratio was measured before surgery using anterior segment optical coherence tomography; using these data, we evaluated the correlation between the AP ratio and various parameters that can affect the corneal radius. For subgroup analyses, we investigated the correlation between the AP ratio and IOL power calculation error in 181 eyes of 181 patients. Stepwise multiple regression analysis was performed with the IOL power calculation errors of the SRK/T, Haigis, Holladay 1, and Hoffer Q formulas as the dependent variables and various parameters that can affect the postoperative IOL power calculation error as the independent variables.

Results

The mean AP ratio was 1.19±0.02, and it weakly correlated with corneal thickness, horizontal corneal diameter, and posterior corneal radius. The correlations between the AP ratio and IOL power calculation errors in the 4 calculation formulas were not statistically significant. Stepwise multiple regression analysis could not detect any significant parameters affecting this ratio.

Conclusion

The AP ratio has no major influence on IOL power calculation error in patients with any history of corneal disease.

Comparison of Holladay equivalent keratometry readings and anterior corneal surface keratometry measurements in keratoconus

PURPOSE

To compare the accuracy of the anterior corneal simulated keratometry (SimK) and the Holladay equivalent keratometry reading (EKR) provided by a Scheimpflug camera (Pentacam HR) with the keratometry (K) provided by a Placido system (T-Cone topography) in keratoconus and control eyes.

METHODS

This prospective study included 40 consecutive patients with keratoconus and 40 voluntary participants with no ocular complaints. Any patients with corneal scar, corneal trauma, history of corneal surgery or contact lens usage were excluded from the study. Mean SimK and Holladay EKR measurements were taken with Pentacam HR in the 2, 3, and 4.5 mm corneal zones, and these values were compared with the T-Cone mean K value with the Placido topography system attachment on the Lenstar LS 900. Statistical analysis was performed using the paired Student's t test and the Bland-Altman analysis.

RESULTS

A statistically significant difference was determined between the Placido K and the Scheimpflug EKR 2, 3, 4.5 mm and SimK values in the keratoconus group (p < 0.05). In the analyses which showed a difference between the SimK and Holladay EKR, it was observed that as the diameter of the corneal zone increased, the 95% LoA values were extended. No statistically significant difference was determined between the SimK and EKR 2 mm values (p > 0.05). In the control group, there was no statistically significant difference between any of the keratometric values.

CONCLUSION

In diseases which affect the posterior corneal surface, such as keratoconus, it is thought that because of the asymmetrical peripheral placement of the corneal apex, as the corneal diameter increases there could be an error increase of 1-3 mm in keratometric systems evaluating the anterior surface.

Effect of the posterior corneal surface on total corneal astigmatism in patients with age-related cataract

AIM

To explore the effect of the posterior astigmatism on total corneal astigmatism and evaluate the error caused by substituting the corneal astigmatism of the simulated keratometriy (simulated K) for the total corneal astigmatism in age-related cataract patients.

METHODS

A total of 211 eyes with age-related cataract from 164 patients (mean age: 66.8±9.0y, range: 45-83y) were examined using a multi-colored spot reflection topographer, and the total corneal astigmatism was measured. The power vector components J₀ and J₄₅ were analyzed. Correlations between the magnitude difference of the simulated K and total cornea astigmatism (magnitude difference_SimK-Tca), anterior J₀, and absolute meridian difference (AMD) between the anterior and posterior astigmatisms were calculated. To compare the astigmatism of the simulated K and total cornea both in magnitude and axial orientation, we drew double-angle plots and calculated the vector difference between the two measures using vector analysis. A corrective regression formula was used to adjust the magnitude of the simulated K astigmatism to approach that of the total cornea.

RESULTS

The magnitude difference_SimK-Tca was positively correlated with the anterior corneal J₀ (Spearman's rho= 0.539; P<0.001) and negatively correlated with the AMDR (Spearman's rho=-0.875, P<0.001). When the anterior J₀ value was larger than 1.3 D or smaller than -0.8 D, the errors caused by determining the total corneal astigmatism with the karatometric calculation tended to be greater than 0.25 D. An underestimation by 16% was observed for against the rule (ATR) astigmatism and an overestimation by 9% was observed for with the rule (WTR) astigmatism when ignoring the posterior measurements.

CONCLUSION

Posterior corneal astigmatism should be valued for more precise corneal astigmatism management, especially for higher ATR astigmatism of the anterior corneal surface. We suggest a 9% reduction in the magnitude of the simulated K in eyes with WTR astigmatism, and a 16% addition of the magnitude of the simulated K in eyes with ATR astigmatism.

Comparison of Anterior, Posterior, and Total Corneal Astigmatism Measured Using a Single Scheimpflug Camera in Healthy and Keratoconus Eyes

Purpose

To compare the effect of posterior corneal astigmatism on the estimation of total corneal astigmatism using anterior corneal measurements (simulated keratometry [K]) between eyes with keratoconus and healthy eyes.

Methods

Thirty-three eyes of 33 patients with keratoconus of grade I or II and 33 eyes of 33 age- and sex-matched healthy control subjects were enrolled. Anterior, posterior, and total corneal cylinder powers and flat meridians measured by a single Scheimpflug camera were analyzed. The difference in corneal astigmatism between the simulated K and total cornea was evaluated.

Results

The mean anterior, posterior, and total corneal cylinder powers of the keratoconus group (4.37 ± 1.73, 0.95 ± 0.39, and 4.36 ± 1.74 cylinder diopters [CD], respectively) were significantly greater than those of the control group (1.10 ± 0.68, 0.39 ± 0.18, and 0.97 ± 0.63 CD, respectively). The cylinder power difference between the simulated K and total cornea was positively correlated with the posterior corneal cylinder power and negatively correlated with the absolute flat meridian difference between the simulated K and total cornea in both groups. The mean magnitude of the vector difference between the astigmatism of the simulated K and total cornea of the keratoconus group (0.67 ± 0.67 CD) was significantly larger than that of the control group (0.28 ± 0.12 CD).

Conclusions

Eyes with keratoconus had greater estimation errors of total corneal astigmatism based on anterior corneal measurement than did healthy eyes. Posterior corneal surface measurement should be more emphasized to determine the total corneal astigmatism in eyes with keratoconus.

Agreement between total corneal astigmatism calculated by vector summation and total corneal astigmatism measured by ray tracing using Galilei double Scheimpflug analyzer

PURPOSE

To evaluate the agreement between total corneal astigmatism calculated by vector summation of anterior and posterior corneal astigmatism (TCA_Vec) and total corneal astigmatism measured by ray tracing (TCA_Ray).

METHODS

This study enrolled a total of 204 right eyes of 204 normal subjects. The eyes were measured using a Galilei double Scheimpflug analyzer. The measured parameters included simulated keratometric astigmatism using the keratometric index, anterior corneal astigmatism using the corneal refractive index, posterior corneal astigmatism, and TCA_Ray. TCA_Vec was derived by vector summation of the astigmatism on the anterior and posterior corneal surfaces. The magnitudes and axes of TCA_Vec and TCA_Ray were compared. The Pearson correlation coefficient and Bland-Altman plots were used to assess the relationship and agreement between TCA_Vec and TCA_Ray, respectively.

RESULTS

The mean TCA_Vec and TCA_Ray magnitudes were 0.76±0.57D and 1.00±0.78D, respectively (P<0.001). The mean axis orientations were 85.12±30.26° and 89.67±36.76°, respectively (P=0.02). Strong correlations were found between the TCA_Vec and TCA_Ray magnitudes (r=0.96, P<0.001). Moderate associations were observed between the TCA_Vec and TCA_Ray axes (r=0.75, P<0.001). Bland-Altman plots produced the 95% limits of agreement for the TCA_Vec and TCA_Ray magnitudes from -0.33 to 0.82D. The 95% limits of agreement between the TCA_Vec and TCA_Ray axes was -43.0 to 52.1°.

CONCLUSION

The magnitudes and axes of astigmatisms measured by the vector summation and ray tracing methods cannot be used interchangeably. There was a systematic error between the TCA_Vec and TCA_Ray magnitudes.

Precision (repeatability and reproducibility) of ocular parameters obtained by the Tomey OA-2000 biometer compared to the IOLMaster in healthy eyes

Purpose

To assess the precision (repeatability and reproducibility) of ocular parameters measured by the Tomey OA-2000 biometer, and to compare them with those measured by the IOLMaster.

Methods

In this prospective study, the right eyes of 108 healthy subjects were included. Three consecutive scans were obtained by 2 observers using the Tomey OA-2000, and in the same session one observer used the IOLMaster (version 5.4.4.0006) for the measurements. About 1 week later, 3 scans were obtained by one observer using the Tomey OA-2000. The axial length (AL), central corneal thickness (CCT), anterior chamber depth (ACD), lens thickness (LT), keratometer readings, pupil diameter (PD) and corneal diameter (CD) values measured by the Tomey OA-2000 and IOLMaster were analyzed. The coefficient of variation (CoV), intraclass correlation coefficient (ICC), within subject standard deviation (Sw) and 2.77Sw were calculated to assess the repeatability and reproducibility. The paired t test and Bland-Altman plots were used to analyze the differences and agreements of parameters measured by the two devices, respectively.

Results

Intraobserver repeatability, and interobserver and intersession reproducibility of the AL, CCT, ACD, LT, Kf, Ks, Km, PD and CD values measured by the Tomey OA-2000 biometer showed a CoV of less than 1% except that for PD, and an ICC of more than 0.97 except that for PD and CD. The AL, Kf, Ks, Km and CD values measured by the Tomey OA-2000 were 0.058 ± 0.094 mm, 0.088± 0.150 diopters (D), 0.163 ± 0.170 D, 0.127 ± 0.117 D and 0.171 ± 0.217 mm lower than those measured by the IOLMaster, respectively (all Ps < 0.05). However, the ACD values from the two devices were comparable (P = 0.169). The 95% linite of agreement (LoA) of the AL, ACD, CD and all keratometer readings were no more than 0.24 mm, 0.14 mm 0.60 mm and 0.5 D, respectively.

Conclusion

Except for the PD and CD, the ocular parameters measured by the Tomey OA-2000 were highly repeatable and reproducible. Except for the CD value, there was good agreement of ocular parameters measured by the Tomey OA-2000 and the IOLMaster in healthy eyes.

Non-Orthogonal Corneal Astigmatism among Normal and Keratoconic Brazilian and Chinese populations

PURPOSE

To investigate the prevalence of non-orthogonal astigmatism among normal and keratoconic Brazilian and Chinese populations.

METHODS

Topography data were obtained using the Pentacam High Resolution (HR) system ^® from 458 Brazilian (aged 35.6 ± 15.8 years) and 505 Chinese (aged 31.6 ± 10.8 years) eyes with no history of keratoconus or refractive surgery, and 314 Brazilian (aged 24.2 ± 5.7 years) and 74 Chinese (aged 22.0 ± 5.5 years) keratoconic eyes. Orthogonal values of optical flat and steep powers were determined by finding the angular positions of two perpendicular meridians that gave the maximum difference in power. Additionally, the angular positions of the meridians with the minimum and maximum optical powers were located while being unrestricted by the usual orthogonality assumption. Eyes were determined to have non-orthogonal astigmatism if the angle between the two meridians with maximum and minimum optical power deviated by more than 5° from 90°.

RESULTS

Evidence of non-orthogonal astigmatism was found in 39% of the Brazilian keratoconic eyes, 26% of the Chinese keratoconic eyes, 29% of the Brazilian normal eyes and 20% of the Chinese normal eyes.

CONCLUSIONS

The large percentage of participants with non-orthogonal astigmatism in both normal and keratoconic eyes illustrates the need for the common orthogonality assumption to be reviewed when correcting for astigmatism. The prevalence of non-orthogonality should be considered by expanding the prescription system to consider the two power meridians and their independent positions.

Correlation of Corneal Endothelial Cell Density with Corneal Tomographic Parameters in Eyes with Keratoconus

Objectives:

To examine changes in corneal endothelial cell density (ECD) in different stages of keratoconus and evaluate its correlation with corneal tomographic parameters.

Materials and Methods:

Two hundred six patients with keratoconus were enrolled in the study. Corneal topography was performed by Sirius (CSO, Italy), which has a rotating Scheimpflug camera and a Placido disc topographer. Automatic endothelial analysis was done with the non-contact endothelial microscope (20x probe) of Confoscan-4 (NIDEK, Japan). The eyes were classified into stages based on steepest keratometric value as follows: mild <45 D; moderate 45-52 D; severe >52 D and according to thinnest cornea thickness (TCT) as <400 μm, 400-450 μm, and >450 μm. Tomographic and endothelial cell parameters were compared among the groups using Kruskal-Wallis test and the correlations between them were analyzed using Spearman correlation.

Results:

The study included 391 eyes of 100 male (24.29±7.7 years, range 11-47 years) and 106 female (26.26±7.5 years, range 13-45 years) patients (p=0.07). Mean ECD values were 2628±262 cells/mm², 2541.9±260.4 cells/mm², and 2414.6±384.3 cells/mm² in mild, moderate, and severe keratoconus, respectively (p<0.001) and 2592.3±277 cells/mm², 2502±307 cells/mm² and 2348±296 cells/mm² in corneas with TCT values >450 µm, 400-450 µm, and <400 µm, respectively (p<0.001). ECD showed significant negative correlation with keratometric and elevation parameters and positive correlation with pachymetric parameters (p<0.05).

Conclusion:

As endothelial cell numbers seem to decrease with the progression of keratoconus, specular/confocal microscopy screening should be carried out, especially in eyes with advanced stages and corneas with TCT <400 µm.

Age-Related Changes in Corneal Astigmatism

PURPOSE

To analyze the changes in corneal astigmatism as a function of age and develop a novel model to estimate corneal astigmatic change according to age.

METHODS

This was a cross-sectional study of right eyes of 3,769 individuals. Total corneal astigmatism, keratometric astigmatism, anterior corneal astigmatism, and posterior corneal astigmatism were measured by a Scheimpflug tomographer. Smoothing fitting curves of polar values of corneal astigmatism as a function of age were drawn and average changes in corneal astigmatism at different ages were calculated.

RESULTS

Two turning points of age on total corneal astigmatism were 36 and 69 years. The average change of total corneal astigmatism toward against-the-rule astigmatism was 0.13 diopters (D)/10 years from 18 to 35 years, 0.45 D/10 years from 36 to 68 years, and decreased after 69 years, mainly caused by anterior corneal astigmatism. The mean magnitude of posterior corneal astigmatism was -0.33 D and exceeded 0.50 D in 14.27% of eyes. The vectorial difference between total corneal astigmatism and keratometric astigmatism was correlated with posterior corneal astigmatism, polar value of anterior corneal astigmatism, age, and corneal higher order aberrations (r = 0.636; standard partial regression coefficients were 0.479, -0.466, 0.282, and 0.196, respectively; all P < .001). Based on the non-linear model to estimate corneal astigmatic change with age, a formula was developed to calculate recommended correction of astigmatism according to age and astigmatic type.

CONCLUSIONS

The rate of change of total corneal astigmatism showed a non-linear trend toward against-the-rule astigmatism, which was low at young and old age, high at middle age, and should be taken into account when performing surgery to correct astigmatism. [J Refract Surg. 2017;33(10):696-703.].

Effects of single-segment Intacs implantation on visual acuity and corneal topographic indices of keratoconus

PURPOSE

To assess the changes in visual acuity and topographic indices after implantation of single-segment Intacs.

METHODS

Forty-two keratoconic eyes received Femtosecond-assisted single-segment Intacs. Uncorrected distance visual acuity (UDVA) and best spectacle corrected visual acuity (BSCVA), refractive error, keratometry (K1, K2, Km, and KMax.), and seven Pentacam measured topographical indices; index of surface variance (ISV), index of vertical asymmetry (IVA), keratoconus index (KI), central keratoconus index (CKI), index of height asymmetry (IHA), index of height decentration (IHD), and minimum radius of curvature (R Min) were assessed 4 months after surgery. Correlations between changes of visual acuity and topographical indices changes were evaluated.

RESULTS

UDVA increased from 0.92 ± 0.35 to 0.49 ± 0.31 logMAR (P < 0.001), and BSCVA increased from 0.39 ± 0.15 to 0.23 ± 0.11 logMAR (P < 0.001). Subjective refraction spherical equivalent (SRSE) decreased from -3.92 ± 1.66 diopters (D) to -2.00 ± 1.51 D (P < 0.001). Mean central Keratometry decreased 2.16 ± 1.09 D from the preoperative readings (P < 0.001). All Pentacam topographical indices except CKI significantly improved (for IHA P = 0.046, for five others P < 0.001). The correlation between improvement in topographical indices and visual acuity improvements was not week.

CONCLUSION

Intacs implantation in keratoconic eyes increased visual acuity and made corneal shape less irregular. However, the improvements of visual acuity and corneal shape were not strongly correlated.

Influence of posterior corneal astigmatism on postoperative refractive astigmatism in pseudophakic eyes after cataract surgery

Background

To examine the influence of posterior corneal astigmatism on postoperative refractive astigmatism in pseudophakic eyes after cataract surgery.

Methods

The study enrolled 64 pseudophakic eyes of 50 patients (71.8 ± 9.9 years old, mean ± standard deviation) who had undergone phacoemulsification with non-toric IOL implantation. Refractive astigmatism was measured using an auto ref-keratometer with a 0.01- diopter (D) scale. Two types of corneal astigmatism were calculated using anterior segment optical coherence tomography; keratometric and total corneal astigmatism. Keratometric astigmatism was obtained based on anterior corneal curvature alone and total corneal astigmatism was calculated using both anterior and posterior corneal curvatures. The difference between refractive and corneal astigmatism was computed as the vector difference using 1) refractive and keratometric astigmatism and 2) refractive and total corneal astigmatism.

Results

The mean refractive, keratometric, and total corneal astigmatism was 0.92 ± 0.48 D, 0.87 ± 0.44 D, and 0.94 ± 0.46 D, respectively. The difference between refractive and keratometric astigmatism (0.70 ± 0.40 D, mean vector of 0.30 D axis 164°) was significantly larger than the difference between refractive and total corneal astigmatism (0.63 ± 0.38 D, mean vector of 0.12 D axis 137°) (P = .019).

Conclusions

The difference between refractive and total corneal astigmatism, calculated using both anterior and posterior corneal curvatures, was significantly smaller than the difference between refractive and keratometric astigmatism using anterior corneal astigmatism alone, implying that the latter overestimates the true postoperative refractive astigmatism and can cause cylindrical inaccuracy after cataract surgery.

Long-term changes in intraocular lens position and corneal curvature after cataract surgery and their effect on refraction

PURPOSE

To evaluate the role of intraocular lens (IOL) position shift and changes in corneal curvature on long-term refractive shift after cataract surgery.

SETTING

Rotterdam Ophthalmic Institute, Rotterdam, the Netherlands.

DESIGN

Prospective cohort study.

METHODS

Patients who had routine cataract surgery with implantation of a hydrophobic acrylic 1-piece IOL (Acrysof SA60AT) in the capsular bag were enrolled. Measurements were performed preoperatively and 1 month, 3 months, and 1 year postoperatively. Refraction was measured with the ARK-530A autorefractor. The IOL position and corneal curvature were measured with the Lenstar LS-900 biometer. The refractive effect of changes in IOL position and corneal curvature was calculated with a Gaussian optics-based thin-lens formula and correlated with the measured refractive shift.

RESULTS

The study group comprised 59 eyes of 59 patients. The median measured absolute refractive change was 0.25 diopter (D). The IOL position showed a statistically significant mean posterior shift of 0.033 mm ± 0.060 (SD) between 1 month and 1 year postoperatively (P < .01), of which the median calculated absolute refractive effect was 0.05 D. This did not correlate with the measured refractive shift (Pearson r = 0.10, P = .46). Natural fluctuations in corneal curvature caused a median calculated absolute refractive effect of 0.17 D, which correlated well with the measured refractive shift (Pearson r = .55, P < .001).

CONCLUSIONS

Long-term changes in refraction after cataract surgery resulted from natural fluctuations in corneal curvature rather than from IOL position shift. These fluctuations limit the accuracy with which the refractive outcome can be planned.

FINANCIAL DISCLOSURE

No author has a financial or proprietary interest in any material or method mentioned.

Effects of posterior corneal astigmatism on the accuracy of AcrySof toric intraocular lens astigmatism correction

AIM

To evaluate the effects of posterior corneal surface measurements on the accuracy of total estimated corneal astigmatism.

METHODS

Fifty-seven patients with toric intraocular lens (IOL) implantation and posterior corneal astigmatism exceeding 0.5 diopter were enrolled in this retrospective study. The keratometric astigmatism (KA) and total corneal astigmatism (TA) were measured using a Pentacam rotating Scheimpflug camera to assess the outcomes of AcrySof IOL implantation. Toric IOLs were evaluated in 26 eyes using KA measurements and in 31 eyes using TA measurements. Preoperative corneal astigmatism and postoperative refractive astigmatism were recorded for statistical analysis. The cylindrical power of toric IOLs was estimated in all eyes.

RESULTS

In all cases, the difference of toric IOL astigmatism magnitude between KA and TA measurements for the estimation of preoperative corneal astigmatism was statistically significant. Of a total of 57 cases, the 50.88% decreased from Tn to Tn-1, and 10.53% decreased from Tn to Tn-2. In all cases, 5.26% increased from Tn to Tn+1. The mean postoperative astigmatism within the TA group was significantly lower than that in the KA group.

CONCLUSION

The accuracy of total corneal astigmatism calculations and the efficacy of toric IOL correction can be enhanced by measuring both the anterior and posterior corneal surfaces using a Pentacam rotating Scheimpflug camera.

Biomechanical Measurement of Rabbit Cornea by a Modified Scheimpflug Device

Purpose. To explore the probability and variation in biomechanical measurements of rabbit cornea by a modified Scheimpflug device. Methods. A modified Scheimpflug device was developed by imaging anterior segment of the model imitating the intact eye at various posterior pressures. The eight isolated rabbit corneas were mounted on the Barron artificial chamber and images of the anterior segment were taken at posterior pressures of 15, 30, 45, 60, and 75 mmHg by the device. The repeatability and reliability of the parameters including CCT, ACD, ACV, and CV were evaluated at each posterior pressure. All the variations of the parameters at the different posterior pressures were calculated. Results. All parameters showed good intraobserver reliability (Cronbach's alpha; intraclass correlation coefficient, α, ICC > 0.96) and repeatability in the modified Scheimpflug device. With the increase of posterior pressures, the ratio of CCT decreased linearly and the bulk modulus gradually reduced to a platform. The increase of ACD was almost linear with the posterior pressures elevated. Conclusions. The modified Scheimpflug device was a valuable tool to investigate the biomechanics of the cornea. The posterior pressure 15-75 mmHg range produced small viscoelastic deformations and nearly linear pressure-deformation response in the rabbit cornea.