Predicted vs measured posterior corneal astigmatism for toric intraocular lens calculations

Comparative Accuracy of Barrett Integrated Keratometry Toric Calculator With Predicted Versus Measured Posterior Corneal Astigmatism

PURPOSE

To compare the prediction accuracy of the Barrett toric calculator using standard or integrated keratometry (IK) mode in combination with predicted or measured posterior corneal astigmatism (PCA) in a group of patients with cataract implanted with non-toric IOLs.

METHODS

In this retrospective clinical cohort study, the medical records of patients with age-related cataract who underwent phacoemulsification with the implantation of an aspheric monofocal IOL were reviewed. Four methods, including standard keratometry with predicted PCA (PPCA), IK combined with predicted PCA (IK-PPCA), and IK combined with measured PCA derived from IOLMaster 700 (Carl Zeiss Meditec AG) or CASIA2 (Tomey) (IK-MMPCA or IK-CMPCA), were applied to the Barrett toric calculator to calculate the predicted residual astigmatism. The mean absolute prediction error (MAPE), centroid of the prediction error, and proportion of eyes within the prediction error of ±0.50, ±0.75, and ±1.00 diopters (D) were all ciphered out from the four methods, respectively.

RESULTS

Data from 129 eyes of 129 patients were included in this study. The MAPE of the IK-PPCA method (0.57 ± 0.36 D) was significantly smaller than that of the PPCA (0.62 ± 0.38 D) and IK-CMPCA (0.63 ± 0.46 D) methods (P = .048 and .014, respectively). There were no significant differences in the centroid vectors of prediction errors and predictability rates among the four methods (all P > .05).

CONCLUSIONS

In the current version of the Barrett toric calculator, the predictive accuracy of the IK mode incorporating PPCA was slightly superior to using the standard keratometry mode or incorporating MPCA. [J Refract Surg. 2024;40(7):e453-e459.].

Accuracy of Toric Intraocular Lens Calculators with Predicted and Measured Posterior Corneal Astigmatism Across Different Types of Astigmatism

INTRODUCTION

This study is a retrospective case series to compare the accuracy of the Barrett toric calculator using predicted posterior corneal astigmatism (PCA) and PCA measurements using swept-source optical coherence tomography (SS-OCT) and a Scheimpflug camera. This evaluation was conducted across different types of anterior and posterior astigmatism.

METHODS

A total of 146 eyes from 146 patients implanted with toric intraocular lenses were included. Mean absolute prediction error, standard deviation of prediction error, and the percentage of eyes with prediction errors within ±0.50 diopters (D) were calculated using vector analysis. Biometric measurements were conducted using the IOLMaster 700 and Pentacam HR. A subgroup analysis was conducted based on the orientation of both anterior and posterior corneal astigmatism.

RESULTS

The Barrett toric calculator with predicted PCA yielded the best results, with 78.1% having a prediction error ≤ 0.50 D, which was a significantly higher percentage than the Barrett formula with the two versions of measured PCA (P < 0.05). In the subgroup with a horizontally steep meridian PCA using the IOLMaster 700, the Barrett formula with predicted PCA yielded the best results, with 78.3% of cases having a prediction error of less than 0.5 D. This percentage was significantly higher than the other two measured PCA subgroups (P < 0.05).

CONCLUSION

The Barrett toric formula with predicted PCA demonstrated a statistically significantly higher proportion of cases with a prediction error ≤ 0.5 D compared to the two measured PCA formulas (from the IOLMaster 700 or Pentacam). This trend persisted even when the posterior corneal astigmatism was horizontally steep.

Accuracy of Toric Intraocular Lens Calculations Using Estimated Versus Measured Posterior Corneal Astigmatism

PURPOSE

To compare the prediction accuracy of toric intraocular lens calculations using estimated vs measured posterior corneal astigmatism (PCA).

DESIGN

Retrospective case series.

METHODS

A total of 110 eyes of 110 patients with uncomplicated toric intraocular lens implantation were included in this study. Predicted postoperative refractive astigmatism was calculated with the Barrett Toric Calculator using the estimated PCA (E-PCA), the measured IOLMaster 700 PCA (I-PCA), and the measured Pentacam PCA (P-PCA). Refractive astigmatism prediction errors (RA-PEs), including their trimmed (tr-) centroid (mean vector), spread (precision), tr-mean absolute RA-PE (accuracy), and percentage within a certain threshold, were determined using vector analysis and compared between groups.

SETTING

University Eye Clinic, Maastricht University Medical Center+, the Netherlands.

RESULTS

The tr-centroid RA-PEs of the E-PCA (0.02 diopter [D] at 82.2°), the I-PCA (0.08 D at 35.5°), and the P-PCA (0.09 D at 69.1°) were significantly different from each other (P < .01), but not significantly different from zero (P = .75, P = .05, and P = .05, respectively). The E-PCA had the best precision (tr-mean 0.40 D), which was not significantly lower than the I-PCA (0.42 D, P = .53) and P-PCA (0.43 D, P = .06). The E-PCA also had the best accuracy (0.40 D), which was not significantly different from the I-PCA (0.42 D, P = .26) and significantly better than the P-PCA (0.44 D, P < .01). The precision and accuracy of the I-PCA did not significantly differ from those of the P-PCA. There were no statistically significant differences in the percentage of eyes within a certain absolute RA-PE threshold.

CONCLUSIONS

The Barrett Toric Calculator using the E-PCA, I-PCA, or P-PCA showed a comparable prediction of postoperative refractive astigmatism in standard clinical practice.

Accuracy of Toric Intraocular Lens Formulas With Measured Posterior Corneal Astigmatism of Different Orientations

PURPOSE

To assess whether the use of measured posterior corneal astigmatism (PCA) values improves the prediction accuracy of toric intraocular lens power formulas, compared to predicted PCA values, when the orientation of the steep axis of PCA is non-vertical.

DESIGN

Retrospective observational cohort study.

METHODS

Four hundred eighteen eyes of 344 patients were included in the study. Prediction errors (PE) for postoperative refractive astigmatism at 4 weeks postoperatively were determined using vector analysis and compared for the following toric intraocular lens power formulas: Barrett Toric with predicted posterior corneal astigmatism (PPCA); Barrett Toric with measured posterior corneal astigmatism (MPCA); EVO Toric PPCA; EVO Toric MPCA; Holladay I with Abulafia-Koch regression. Subgroup analysis compared PEs for eyes with a vertically orientated steep axis of PCA (60-120°) to eyes with a non-vertically orientated steep axis of PCA.

SETTING

Cathedral Eye Clinic, Belfast, United Kingdom and Tan Tock Seng Hospital, Singapore.

RESULTS

Standard keratometry was with-the-rule in 48% of eyes, while the steep PCA axis was vertically orientated in 91% of eyes. For all eyes, EVO-PPCA had a smaller mean absolute error than Barrett-MPCA, Barrett-PPCA, and Abulafia-Koch (P < .01 for all). EVO-PPCA had the highest percentage of eyes within 0.50D of predicted postoperative astigmatism for eyes with vertical PCA (61%), while EVO-MPCA had the highest percentage for eyes with non-vertical PCA (54%). EVO-MPCA had the smallest centroid error for all eyes, and the subgroups (P < .01 for all). Eyes with non-vertical PCA had a lower percentage within 0.50D than eyes with vertical PCA when using PPCA (43% vs 61%, P = .034), but there was no significant difference between these groups when MPCA is used for eyes with non-vertical PCA (54% vs 61%, P = .40).

CONCLUSIONS

When the steep axis of posterior corneal astigmatism is not vertically orientated, the use of measured posterior keratometry values improves prediction accuracy.

Online intraocular lens calculation

PURPOSE OF REVIEW

To showcase the majority of online intraocular lens (IOL) calculation tools and highlight some of their characteristics.

RECENT FINDINGS

Online tools are available for preoperative and postoperative IOL-related calculations, including IOL power and toricity selection for standard patients, patients who underwent prior refractive surgery, keratoconus, limbal relaxing incisions for astigmatism management, realignment of a misplaced or rotated toric IOL, surgical induced astigmatism (SIA), formulae comparison, and other tools.

SUMMARY

As there are new online developments and technology is advancing rapidly, we hope that this review will assist ophthalmologists in becoming acquainted with a large variety of online tools.

Comparison of the Barrett toric calculator using measured and predicted posterior corneal astigmatism and the Kane and Abulafia-Koch calculators

PURPOSE

To compare the accuracy of the Barrett toric calculator with measured and predicted posterior corneal astigmatism (MPCA and PPCA, respectively), the Abulafia-Koch (AK) formula, and the toric Kane formula.

SETTING

Ein-Tal Eye Center, Tel-Aviv, Israel.

DESIGN

Retrospective cohort.

METHODS

Consecutive cases of patients who underwent uneventful cataract extraction surgery with implantation of a toric intraocular lens between March 2015 and July 2019 were retrospectively reviewed. 1 eligible eye from each patient was included. The predicted postoperative refractive astigmatism was calculated using each method and compared with the postoperative refractive astigmatism to give the prediction error.

RESULTS

80 eyes of 80 patients were included in this study. The mean centroid and the mean and median absolute prediction errors using Kane (0.25 diopters [D] ± 0.54 @ 6 degrees, 0.50 D ± 0.31 and 0.45 D, respectively) were significantly different compared with MPCA (0.12 D ± 0.52 @ 16 degrees, P < .001, .44 D ± 0.28 and 0.36 D, P = .027, respectively), PPCA (0.09 D ± 0.49 @ 12 degrees, P < .001, .41 D ± 0.27 and 0.35 D, P < .001, respectively), and AK (0.11 D ± 0.49 @ 11 degrees, P < .001, .42 D ± 0.27 and 0.35 D, P = .004, respectively). No significant differences were found between the calculators in the predictability rates within ±0.25 D, ±0.50 D, ±0.75 D, and ±1.00 D.

CONCLUSIONS

The measured posterior corneal curvature in the Barrett calculator yielded comparable outcomes to its prediction by the Barrett and AK formulas. The Kane calculator showed a slight against-the-rule prediction error compared with the other methods, resulting in a small higher median absolute error with marginal clinical importance.

Comparison of biometry measurements and intraocular lens power prediction between 2 SS-OCT-based biometers

PURPOSE

To evaluate the agreement in biometry measurements and intraocular lens (IOL) power prediction between the Eyestar 900 and the IOLMaster 700.

SETTING

Institutional.

DESIGN

Retrospective comparative study.

METHODS

Patients were evaluated before cataract surgery using both devices on the same visit. Axial length, anterior and posterior keratometry, anterior chamber depth, corneal diameter (CD), central corneal thickness, and lens thickness were recorded by both devices. The agreement in measurements and in IOL power calculations was evaluated using the Barrett Universal II (BU-II) formula with either predicted or measured posterior keratometry.

RESULTS

In total, 402 eyes of 402 consecutive patients were included. The mean age was 72.0 ± 9.2 years. Clinically, mean differences in measured variables were small, albeit slightly larger for posterior flat and steep keratometry (0.43 diopters [D] and 0.42 D, respectively). The measurement correlation and agreement between the devices were good for all variables with slightly lower agreement in CD measurements. Consistent bias was seen in measurements of posterior flat and steep keratometry. Good agreement was also found in anterior and posterior astigmatism measurements. Good IOL power calculation agreement was found using either predicted posterior keratometry (95% limits of agreement [LoA] of -0.40 to +0.30 D) or measured posterior keratometry (95% LoA of -0.45 to +0.40 D). The agreement was within ±0.5 D in 394 eyes (98.0%) using predicted posterior keratometry and in 386 eyes (96.0%) using measured posterior keratometry.

CONCLUSIONS

The Eyestar 900 and the IOLMaster 700 show strong agreement in biometry measurements and IOL power prediction by the BU-II formula using either standard or total corneal keratometry and can be used interchangeably.

Accuracy of Intraocular Lens Power Calculation Based on Total Keratometry in Patients With Flat and Steep Corneas

PURPOSE

To analyze the accuracy of the current intraocular lens power calculation formulas using standard keratometry (K) and total keratometry (TK) data in patients with flat and steep corneas.

DESIGN

Retrospective consecutive cross-sectional study.

METHODS

An optical biometer with swept-source optical coherence tomography was used in this retrospective study. The standard deviation (SD), mean absolute error (MAE), median absolute error (MedAE), and the proportion of eyes with prediction error (PE) within ±0.25 diopter (D), ±0.5 D, ±0.75 D, and ±1.00 D were calculated to evaluate the refractive outcomes of each formula.

RESULTS

A total of 231 eyes from 231 patients were included. In the entire study cohort, the Emmetropia Verifying Optical (EVO) formula using TK data showed the lowest SD (0.383) and MAE (0.30) and the highest percentage of cases with a PE within ±0.5 D (81.4%). In the flat keratometry group, the EVO (P = .042), Haigis (P = .043), Hoffer Q (P = .038) and Holladay 1 (P = .013) formulas using TK data had significantly lower SD than using K data. The EVO formula using TK data showed the lowest SD (0.357) and MAE (0.28). In the steep keratometry group, the Hoffer Q (P = .036) and SRK/T (P = .029) formulas using TK data had significantly lower SD than using K data. The BUII TK formula showed the lowest SD (0.431), MedAE (0.26), and MAE (0.32).

CONCLUSION

The TK data set showed a better trend of refractive outcomes, especially in the flat and steep keratometry groups. EVO (TK) and BUII TK formulas were suggested for eyes with K values lower than 42 D and K values higher than 46 D, respectively.

Clinical applications of anterior segment swept-source optical coherence tomography: A systematic review

Optical coherence tomography (OCT) is a non-invasive method that provides the opportunity to examine tissues by taking cross-sectional images. OCT is increasingly being used to evaluate anterior segment (AS) pathologies. Swept-source (SS) OCT allows greater penetration and achieves better visualization of the internal configuration of AS tissues due to the longer wavelength employed and high scan speeds. We reviewed the utilization of AS SS-OCT in various conditions including glaucoma, ocular surface pathologies, iris tumors, refractive surgery, cataract surgery, and scleral diseases. A systematic literature search was carried out on PubMed, Scopus, and Web of Science databases between January 1, 2008, and September 1, 2022 using the following keywords: AS SS-OCT; dry eye and SS-OCT; ocular surface and SS-OCT; cornea and SS-OCT; dystrophy and SS-OCT; glaucoma and SS-OCT; ocular surface tumors and SS-OCT; conjunctival tumors and SS-OCT; refractive surgery and SS-OCT; cataract and SS-OCT; biometry and SS-OCT; sclera and SS-OCT; iris and SS-OCT; ciliary body and SS-OCT; artificial intelligence and SS-OCT. A total of 221 studies were included in this review. Review of the existing literature shows that SS-OCT offers several advantages in the diagnosis of AS diseases. Exclusive features of SS-OCT including rapid scanning, deeper tissue penetration, and better image quality help improve our understanding of various AS pathologies.

The 10,000 Eyes Study: Analysis of Keratometry, Abulafia-Koch regression transformation, and Biometric Eye Parameters Obtained With Swept-Source Optical Coherence Tomography

PURPOSE

To analyze Abulafia-Koch regression (AKRT), anterior and posterior astigmatism (K and TK), and evaluate biometry data in a large population.

DESIGN

Retrospective cross-sectional study.

METHODS

This multicenter (2 tertiary care centers) study analyzed datasets acquired between 2017 and 2020. Axial length (AL), corneal front and back radii (including meridians for K and TK conversion), horizontal corneal diameter, anterior chamber depth, lens thickness, and central corneal thickness were measured using telecentric keratometry and swept-source optical coherence tomography-based biometry (IOLMaster 700; Carl Zeiss Meditec AG). Cooke-modified axial length (CMAL) and AKRT were calculated. Difference vectors between K and TK astigmatism and between AKRT and TK astigmatism were compared.

RESULTS

A total of 10,300 eyes from 6388 patients were assessed. Difference vectors for K and TK were significantly smaller than for AKRT and TK. K measurement showed a configuration of 51.49% of with-the-rule astigmatism and 30.51% against-the-rule astigmatism, TK measurement showed a configuration of 41.60% of with-the-rule astigmatism and 40.21% against-the-rule astigmatism. Mean total astigmatism was -0.94 ± 0.74 dpt. Mean values for AL and CMAL were 23.70 ± 1.39 mm and 23.70 ± 1.34 mm, respectively. Anterior chamber depth, lens thickness, horizontal corneal diameter, AL, and age were all correlated with each other.

CONCLUSION

Astigmatism analysis showed less difference between K and TK than between AKRT and TK. There were significantly fewer eyes with with-the-rule astigmatism and more eyes with against-the-rule astigmatism configuration in TK-derived than in K-derived keratometry. The study provides data on gender and generational differences in biometry. Significant intersexual differences in AL and CMAL were observed, with CMAL providing lower standard deviation compared with AL.