Higher order aberrations in keratoconus .

INTRODUCTION: Keratoconus is a progressive disorder of the cornea that causes thinning (Sedaghat et al. in Sci Rep 11(1):11971, 2021), ectasia, and irregular astigmatism, resulting in poor visual acuity that cannot be corrected with standard sphero-cylindrical spectacle lenses. One feature distinguishing keratoconic corneas is ocular aberrations, manifesting up to five or six times the amount of higher-order aberrations than a normal, healthy eye. These aberrations can cause visual disturbances even at the very early stages of the disease. METHODS: In the past, a diagnosis was derived from clinical symptoms, but technological advances have revealed multiple pre-clinical features, allowing for the differentiation between keratoconic and normal eyes at a much earlier stage. These include anterior and posterior corneal surface elevations, the corneal pachymetry profile, corneal epithelial patterns, wavefront aberration metrics, and corneal biomechanics (Sedaghat et al. in Sci Rep 11(1):11971, 2021).This review discusses the aberrations associated with keratoconus, how to measure them, and treatment methods to minimize their negative influence. CONCLUSIONS: Early diagnosis can lead to early treatment and may allow for arresting progression, thereby improving the long-term prognosis. With the acceleration of refractive surgery, it is important to identify patients with keratoconus, as they are usually contraindicated for refractive surgery.

Vector analysis of corneal astigmatism in cataractous eyes based on IOLMaster 700 biometry.

PURPOSE: The purpose of this study was to investigate the effect of the corneal back surface by comparing the keratometric astigmatism (K, derived from the corneal front surface) of a modern optical biometer against astigmatism of Total Keratometry (TK, derived from both corneal surfaces) in a large population with cataractous eyes. The results were then used to define linear prediction models to map K to TK. METHODS: From a large dataset containing bilateral biometric measurements (IOLMaster 700) in 9736 patients prior to cataract surgery, the total corneal astigmatism was decomposed into vectors for K, corneal back surface (BS), and TK. A multivariate prediction model (MV), simplified model with separation of vector components (SM) and a constant model (CM) were defined to map K to TK vector components. RESULTS: The K centroid (X/Y) showed some astigmatism with-the-rule (0.1981/-0.0211 dioptre (dpt)) whereas the TK centroid was located around zero (-0.0071/-0.0381 dpt against-the-rule) and the BS centroid showed systematic astigmatism against-the-rule (-0.2367/-0.0145 dpt). The respective TK-K centroid was located at -0.2052/-0.0302 dpt. The MV model showed the same performance (i.e. mean absolute residuum) as the SM did (0.1098 and 0.1099 dpt respectively) while the CM performed only slightly worse (0.1121 dpt mean absolute residuum). CONCLUSION: In cases where tomographic data are unavailable statistical models could be used to consider the overall contribution of the back surface to the total corneal astigmatism. Since the performance of the CM is sufficiently close to that of MV and SM we recommend using the CM which can be directly considered e.g. as surgically induced astigmatism.

Prevalence and risk factors for astigmatism in 7 to 19-year-old students in Xinjiang, China: a cross-sectional study.

BACKGROUND: To investigate the prevalence and risk factors for astigmatism in 7-19-year-old students in Xinjiang, China. METHODS: A school-based, cross-sectional study was conducted on students who underwent refraction examination in Xinjiang, China, between May and December 2019. The prevalence of astigmatism was determined. Astigmatism was defined as cylinder power (C) ≤-0.75 D, undefined astigmatism as ≤-1.50 D, and high astigmatism as C ≤-3.00 D. Astigmatism types were: against-the-rule astigmatism (maximum refraction of the main meridian in 180° ± 30°), with-the-rule astigmatism (maximum refraction of the main meridian at 90°±30°), and oblique astigmatism (all other cases). RESULTS: Of the 71,838 students examined (51.0% boys, 7 - 19 years old), 25,945 (36.1%, 95%CI: 35.52-36.68%) had astigmatism and 1267 (1.8%, 95%CI: 1.07-2.53%) had high astigmatism. The prevalence of astigmatism was greater in Han individuals (39.6%) compared with the Hui (34.0%), Kazakh (34.0%), Kyrgyz (32.1%), and Uyghur (26.4%) populations. Among the 25,945 students with astigmatism, 19,947 had with-the-rule astigmatism (76.9%), 3405 had against-the-rule astigmatism (13.1%), and 2593 had oblique astigmatism (10.0%). Multivariable logistic regression analysis showed that ethnicity (Han individuals more susceptible), male gender, age, and refractive errors (myopia and hyperopia) were independently associated with astigmatism, high astigmatism, and with-the-rule astigmatism (all P < 0.05). CONCLUSIONS: The prevalence of astigmatism among children and adolescents in Xinjiang was 36.1%, including 1.8% of high astigmatism. In this population, astigmatism was mainly of the with-the-rule astigmatism type (76.9%). Han ethnicity, male gender, and myopia or hyperopia were independently associated with a high risk of astigmatism.

Measurement of the distance between corneal apex and pupil center in patients following small-incision lenticule extraction or implantable collamer lens implantation and its correlation with the surgical-induced astigmatism.

BACKGROUND: To investigate the change in the distance between corneal apex and pupil center after small-incision lenticule extraction (SMILE) or implantable collamer lens (ICL) implantation and its correlation with surgical-induced astigmatism (SIA). METHODS: This study included patients who had undergone SMILE (n = 112) or ICL implantation (n = 110) to correct myopia and myopic astigmatism. The angle kappa was measured using a Scheimpflug imaging device (Pentacam) and represented as Cartesian values between the pupil center and the corneal vertex (X, Y) and chord u ([Formula: see text]orientation), and was compared pre- and post-operative. RESULTS: Following SMILE, the magnitude of chord u[Formula: see text]) significantly increased in both eyes (Wilcoxon signed-rank test, OD: P<0.001; OS: P=0.007), while no significant change was observed in the orientation. A significant correlation was found between the J0 component of SIA and the change in the magnitude of chord u for both eyes (OD: R2=0.128, P<0.001; OS: R2=0.033, P=0.004). After ICL implantation, the orientation of the chord u was significantly different in the right eye (Wilcoxon signed-rank test, P = 0.008), and the Y-intercept significantly decreased in both eyes (Wilcoxon signed-rank test, P<0.001). A significant correlation was found between J0 of SIA and the change in the magnitude of chord u for the right eyes (R2=0.066, P=0.002). A significant correlation was found between J45 of SIA and the change in the magnitude of chord u for the left eyes (R2=0.037, P=0.044). CONCLUSIONS: The magnitude of the chord u increased following the SMILE procedure, whereas the Y-intercept significantly decreased after ICL implantation. SIA was related to the change in the magnitude of chord u.

Detection of significant vision conditions in children using QuickSee wavefront autorefractor.

PURPOSE: This study evaluated the ability of QuickSee to detect children at risk for significant vision conditions (significant refractive error [RE], amblyopia and strabismus). METHODS: Non-cycloplegic refraction (using QuickSee without and with +2 dioptre (D) fogging lenses) and unaided binocular near visual acuity (VA) were measured in 4- to 12-year-old children. Eye examination findings (VA, cover testing and cycloplegic retinoscopy) were used to determine the presence of vision conditions. QuickSee performance was summarised by area under the receiver operating characteristic curve (AUC), sensitivity and specificity for various levels of RE. QuickSee referral criteria for each vision condition were chosen to maximise sensitivity at a specificity of approximately 85%-90%. Sensitivity and specificity to detect vision conditions were calculated using multiple criteria. Logistic regression was used to evaluate the benefit of adding near VA (6/12 or worse) for detecting hyperopia. A paired t-test compared QuickSee without and with fogging lenses. RESULTS: The mean age was 8.2 (±2.5) years (n = 174). RE ranged up to 9.25 D myopia, 8 D hyperopia, 5.25 D astigmatism and 3.5 D anisometropia. The testability of the QuickSee was 94.3%. AUC was ≥0.92 (excellent) for each level of RE. For the detection of any RE, sensitivity and specificity were 84.2% and 87.3%, respectively, using modified Orinda criteria and 94.5% and 78.2%, respectively, using the American Academy for Pediatric Ophthalmology and Strabismus (AAPOS) guidelines. For the detection of any significant vision condition, the sensitivity and specificity of QuickSee were 81.1% and 87.9%, respectively, using modified Orinda criteria and 93% and 78.6%, respectively, using AAPOS criteria. There was no significant benefit of adding near VA to QuickSee for the detection of hyperopia ≥+2.00 (p = 0.34). There was no significant difference between QuickSee measurements of hyperopic refractive error with and without fogging lenses (difference = -0.09 D; p = 0.51). CONCLUSIONS: QuickSee had high discriminatory power for detecting children with hyperopia, myopia, astigmatism, anisometropia, any significant refractive error or any significant vision condition.

Predictive accuracy of Barrett TK toric calculator compared to measured posterior corneal astigmatism using Pentacam in toric IOL power calculation.

PURPOSE: To compare the predictive accuracy of Barrett total keratometry (Barrett TK) toric calculator with the measured posterior corneal astigmatism (PCA) by using Pentacam in toric intraocular lens (IOL) power calculation. METHODS: A prospective analysis was done on 118 eyes requiring toric IOL power implantation. The absolute prediction error of the Barrett TK toric calculator and the measured PCA in the online toric calculator were assessed and compared to the standard Alcon toric calculator (with Barrett toric calculator incorporated). RESULTS: The mean absolute prediction error of the online toric calculator (0.32 D) (with Barrett toric calculator incorporated), Barrett TK Toric (0.34 D), and measured PCA of Pentacam in Barrett toric calculator (0.33 D) were found to be similar with no statistically significant difference. Subanalysis in eyes with with-the-rule astigmatism, against-the-rule astigmatism, and oblique astigmatism showed similar results. Alpins analysis showed that all three methods overcorrected corneal astigmatism. CONCLUSION: The Barrett TK toric calculator and the measured PCA of Pentacam in the Barrett toric calculator have similar predictive accuracy to the online toric calculator (with Barrett toric calculator incorporated).

Evaluation of early period changes in intraocular pressure, ocular biometry and anterior segment after upper eyelid blepharoplasty.

PURPOSE: To investigate the acute effects of upper eyelid blepharoplasty on intraocular pressure (IOP) and ocular biometric parameters. METHOD: This prospective cross sectional study examined the eyes of 49 patients with dermatochalasis. Following a detailed ophthalmological examination, corneal topography was used to evaluate the eyes mesopic and photopic pupil diameter, anterior chamber depth, and corneal astigmatism on the day of surgery and on days first and seventh postoperatively. Ocular biometry was used to assess axial length and intraocular lens power. Goldmann applanation tonometry was used to measure intraocular pressure. RESULTS: Forty-nine eyes (26 males and 23 females) of 49 patients aged between 44 and 76 years (mean 61 ± 7.9) were included in our study. The mean anterior chamber depth (ACD) was 2.90 ± 0.37 mm preoperatively, 3.00 ± 0.29 mm at postoperative day first, and 3.04 ± 0.29 mm at postoperative day seventh, and the increase in anterior chamber depth was statistically significant (p < 0.001). The mean astigmatism values were measured as preoperative 0.73 ± 0.69 D, postoperative first day 0.93 ± 0.81 D, and postoperative seventh day 1.26 ± 0.90 D. The increase in astigmatism values was statistically significant (p < 0.001). The mean pupil diameter measurements in the mesopic environment were 4.20 ± 0.61 mm preoperatively, 4.40 ± 0.59 mm on the first postoperative day, and 4.39 ± 0.57 mm on the seventh postoperative day, and there was a statistically significant difference between the three measurements (p = 0.03). The mean IOP measurements of the patients were 15.91 ± 3.51 mmHg preoperatively, 16.81 ± 3.36 mmHg on the first postoperative day, and 16.97 ± 3.13 mmHg on the seventh postoperative day. The increase between these three measurements was statistically significant (p = 0.013). CONCLUSION: This study includes important insights into the potential acute phase impact of blepharoplasty surgery on ocular findings. Patients undergoing upper eyelid surgery should be informed about the possible change in ocular biometric parameters, intraocular pressure, and pupil diameter.

The Effects of Whole-Corneal and Whole-Eye Higher Order Aberrations on the Discrepancy Between Refractive and Corneal Astigmatism in Otherwise Healthy Candidates for Refractive Surgery.

PURPOSE: To evaluate the effect of different whole-corneal and whole-eye higher order aberrations (HOAs) on levels of axis discrepancy. METHODS: This was a retrospective study including healthy candidates for refractive surgery, with one eye being randomly selected. A total of 360 eyes were included. Whole-corneal and whole-eye HOAs were measured twice with a Pentacam AXL Wave (Oculus Optikgeräte GmbH), and subjective manifest refraction was obtained. Axis discrepancy was defined as the absolute difference between Total Corneal Refractive Power flat keratometry axis and manifest refractive axis. Two multiple linear regression models that sought to explore the effect of HOAs in predicting axis discrepancy while adjusting for corneal and refractive confounders were built. RESULTS: Mean age was 29.1 ± 5.8 years and 63.9% of the patients were women. Mean manifest sphere and cylinder were -3.09 ± 2.36 and -1.45 ± 1.37 diopters (D), respectively. Mean cylinder axis discrepancy was 14.4 ± 14.5°. On multiple linear regression, the only variables significantly associated with axis discrepancy were corneal cylinder and corneal lower order aberrations [F(5,339) = 29.746; P < .001; adjusted R2 = 0.295]. Lower levels of corneal cylinder are by far the main contributor to astigmatism axis mismatch (ß = -1.164). There was not a single HOA, either corneal or ocular, that significantly loaded into any models. CONCLUSIONS: Astigmatism axis mismatch decreases rapidly with increasing levels of corneal astigmatism. Corneal and whole-eye HOAs have no role in astigmatism axis mismatch in healthy candidates for refractive surgery. [J Refract Surg. 2024;40(2):e89-e97.].

Calculation of the total corneal astigmatism using the virtual cross cylinder method on the secondary principal plane of the cornea.

This study aimed to establish a virtual cross cylinder method to calculate the total corneal astigmatism by combining the anterior and posterior corneal astigmatism on the secondary principal plane of the cornea based on Gaussian optics. The meridian with the least refractive power, namely, the flattest meridian of the virtual cross cylinder of a ± 0.5 × C diopter, is set as the reference meridian, and the power (F) at an angle of φ between an arbitrary meridian and the reference meridian is defined as F(φ) = - 0.5 × C × cos2φ. The magnitude and axis of the total corneal astigmatism were calculated by applying trigonometric functions and the atan2 function based on the combination of the virtual cross cylinders of the anterior corneal astigmatism and the posterior corneal astigmatism. To verify the performance of the virtual cross cylinder method, a verification experiment with two Jackson cross cylinders and a lensmeter was performed, and the measured and calculated values were compared. The limit of the natural domain of the arctangent function is circumvented by using the atan2 function. The magnitude and axis of the total corneal astigmatism are determined through generalized mathematical expressions. The verification experiment results showed good agreement between the measured and calculated values. Compared to the vector analysis method, the virtual cross cylinder method is mathematically sound and straightforward. A novel technique for calculating total corneal astigmatism, the virtual cross cylinder method, was developed and verified.

Accurate, automatic determination of astigmatism and phase with Ctfplotter in IMOD.

Ctfplotter in the IMOD software package is a flexible program for determination of CTF parameters in tilt series images. It uses a novel approach to find astigmatism by measuring defocus in one-dimensional power spectra rotationally averaged over a series of restricted angular ranges. Comparisons with Ctffind, Gctf, and Warp show that Ctfplotter's estimated astigmatism is generally more reliable than that found by these programs that fit CTF parameters to two-dimensional power spectra, especially at higher tilt angles. In addition to that intrinsic advantage, Ctfplotter can reduce the variability in astigmatism estimates further by summing results over multiple tilt angles (typically 5), while still finding defocus for each individual image. Its fitting strategy also produces better phase estimates. The program now includes features for tuning the sampling of the power spectrum so that it is well-represented for analysis, and for determining an appropriate fitting range that can vary with tilt angle. It can thus be used automatically in a variety of situations, not just for fitting tilt series, and has been integrated into the SerialEM acquisition software for real-time determination of focus and astigmatism.

The effect of pterygium on front and back corneal astigmatism and aberrations in natural-light and low-light conditions.

BACKGROUND: To investigate the effect of different sizes of pterygium on the front and back corneal topography, refractive changes and aberrations in natural-light and low-light conditions. METHODS: Sixty subjects with unilateral primary nasal pterygium were enrolled in this study. All the patients' uncorrected, best spectacle-corrected visual acuity, corneal topographic aberration data in 3 mm and 7 mm areas were collected. The pterygium size was evaluated by the slit-lamp photography and Sirius Scheimpflug Analyzer. RESULTS: The front topographic astigmatism values, corneal total aberrations, and higher-order aberrations in 3 mm and 7 mm areas were higher in the pterygium group than those in the control group. The pterygium horizontal length and thickness were moderately to strongly correlated with astigmatism and RMS of aberrations, while pterygium vertical length showed no or just mild correlation with the corneal astigmatism and aberrations. Compared to the readings in 3 mm area, the front and back corneal astigmatism and aberrations were larger in 7 mm area. CONCLUSIONS: Pterygium led to visual impairment by inducing astigmatism and aberrations. In low-light condition, the visual function worsened due to increased corneal astigmatism values and aberrations.

Comparison of Capsular Tension Ring Implantation before vs. after Toric Intraocular Lens for Rotational Stability.

PURPOSE: To compare the effect of implanting the capsular tension ring (CTR) before or after a toric intraocular lens (IOL) on rotational stability in patients with cataract and astigmatism. METHODS: This is a randomized retrospective study. Patients who underwent phacoemulsification combined with toric IOL implantation due to cataract and astigmatism between February 2018 and October 2019 were enrolled in the study. Group 1 consisted of 53 eyes of 53 patients in whom the CTR was placed into the capsular bag after the implantation of the toric IOL. On the other hand, group 2 consisted of 55 eyes of 55 patients in whom the CTR was placed into the capsular bag before implantation of the toric IOL. The two groups were compared in terms of preoperative and postoperative astigmatism, uncorrected visual acuity (UCVA), best-corrected visual acuity (BCVA), and postoperative IOL rotation degree. RESULTS: There were no significant differences between the two groups related to age and sex (p > 0.05) or the mean preoperative spherical value, UCVA, BCVA, and corneal astigmatism (p > 0.05). Although the mean postoperative residual astigmatism of the first group (- 0.29 ± 0.26) was lower than that of the second (- 0.43 ± 0.31), the difference was not statistically significant (p = 0.16). The mean degree of rotation was 0.75 ± 2.66° in group 1 and 2.90 ± 6.57° in group 2, which was found to be statistically significant (p = 0.02). CONCLUSION: The implantation of CTR after a toric IOL provides further rotational stability and more effective astigmatic correction.

The predictive accuracy of Barrett toric calculator using measured posterior corneal astigmatism derived from swept source-OCT and Scheimpflug camera.

PURPOSE: To compare the performance of Barrett toric calculator incorporated with measured posterior corneal astigmatism (PCA) derived from IOL Master 700 and Pentacam HR versus predicted PCA. METHODS: The predicted residual astigmatism using Barrett toric IOL calculator with predicted PCA, measured PCA from IOL Master 700 and measured PCA from Pentacam were calculated with the preoperative keratometry and intended IOL axis with modification. The vector analysis was performed to calculate the mean absolute prediction error (MAE), the centroid of the prediction error and the percentage of eyes with a prediction error within ±0.50 D, ±0.75 D, and ±1.00 D. RESULTS: In 57 eyes of 57 patients with mean age of 70.42 ± 10.75 years, the MAE among the three calculation methods were 0.59 ± 0.38 D (Predicted PCA), 0.60 ± 0.38 D (Measured PCA from IOL Master 700) and 0.60 ± 0.36 D (Measured PCA from Pentacam) with no significant difference, either in the whole sample, the WTR eyes and the ATR eyes (F = 0.078, 0.306 and 0.083, p = 0.925, 0.739 and 0.920, respectively). Measured PCA obtained from IOL Master 700 resulted in one level reduction (from Tn to Tn-1) in 49.12% eyes in cylindrical model selection, while measured PCA obtained from Pentacam resulted in one level reduction of toric model selection in 18.18% eyes. CONCLUSION: The present study suggested that the incorporation of measured PCA values derived from IOL Master 700 and Pentacam produce comparable clinical outcome with the predicted PCA mode in Barrett toric calculator.

Corneal refractive error and astigmatism in patients aged 6 to 18 years with a history of retinopathy of prematurity and birth weight of <1500 g.

PURPOSE: To investigate corneal refractive power (CR) and astigmatism (AS) in 6- to 18-year-old children with a history of retinopathy of prematurity (ROP) and birth weight of <1500 g who either did or did not undergo retinal photocoagulation (PC). STUDY DESIGN: Retrospective study. METHODS: We examined 143 eyes of 77 children in 2021. The children were divided into three groups for evaluation of CR and AS: those with a birth weight of ≥2500 g (normal birth weight [NBW] group, 13 eyes) as controls, those with spontaneously resolved ROP (sr-ROP group, 27 eyes), and those who underwent PC for treatment of ROP (PC-ROP group, 103 eyes). Swept-source anterior segment optical coherence tomography was used to analyze the cornea. RESULTS: The median CR in the NBW, sr-ROP, and PC-ROP groups was 42.2 (41.3, 42.8) diopters (D), 44.5 (43.2, 45.5) D, and 45.2 (43.8, 46.6) D, respectively. The median AS in the NBW, sr-ROP, and PC-ROP groups was 1.2 (1.0, 1.5) D, 1.1 (0.8, 1.6) D, and 2.1 (1.4, 2.7) D. In the PC-ROP group, the with-the-rule astigmatic axis was 97%. In all three groups, a strong positive correlation was found between the mean anterior and posterior CR (NBW: r=0.795, sr-ROP: r=0.842, PC-ROP: r=0.890) and AS (NBW: r=0.883, sr-ROP: r=0.841, PC-ROP: r=0.860). CONCLUSION: CR was significantly higher in the sr-ROP (p=0.013) and PC-ROP (p<0.001) groups than in the NBW group. The PC-ROP group had significantly more AS than the sr-ROP group. There was a strong correlation between the anterior and posterior CR and AS.

Optimizing Refractive Outcomes of SMILE: Artificial Intelligence versus Conventional State-of-the-Art Nomograms.

PURPOSE: AI (artificial intelligence)-based methodologies have become established tools for researchers and physicians in the entire field of ophthalmology. However, the potential of AI to optimize the refractive outcome of keratorefractive surgery by means of machine learning (ML)-based nomograms has not been exhausted yet. In this study, we wanted to comprehensively compare state-of-the-art conventional nomograms for Small-Incision-Lenticule-Extraction (SMILE) with a novel ML-based nomogram regarding both their spherical and astigmatic predictability. METHODS: A total of 1,342 eyes were analyzed for creation of three different nomograms based on a linear model (LM), a generalized additive mixed model (GAMM) and an artificial-neuronal-network (ANN), respectively. A total of 16 patient- and treatment-related features were included. Each model was trained by 895 eyes and validated by the remaining 447 eyes. Predictability was assessed by the difference between attempted and achieved change in spherical equivalent (SE) and the difference between target induced astigmatism (TIA) and surgically induced astigmatism (SIA). The root mean squared error (RMSE) of each model was computed as a measure of overall model performance. RESULTS: The RMSE of LM, GAMM and ANN were 0.355, 0.348 and 0.367 for the prediction of SE and 0.279, 0.278 and 0.290 for the astigmatic correction, respectively. By applying the created models, the theoretical yield of eyes within ±0.50 D of SE from target refraction improved from 82 to 83% (LM), 84% (GAMM) and 83% (ANN), respectively. Astigmatic outcomes showed an improvement of eyes within ±0.50 D from TIA from 90 to 93% (LM), 93% (GAMM) and 92% (ANN), respectively. Subjective manifest refraction was the single most influential covariate in all models. CONCLUSION: Machine learning endorsed the validity of state-of-the-art linear and non-linear SMILE nomograms. However, improving the accuracy of subjective manifest refraction seems warranted for optimizing ±0.50 D SE predictability beyond an apparent methodological 90% limit.

Revisiting Javal's rule: a fresh and improved power vector approach according to age.

PURPOSE: The scientific community has established Javal's rule as a model linking refractive (RA) and keratometric (KA) astigmatism since its appearance more than 100 years ago. The aim was to improve the accuracy of this relationship according to subject's age by applying the power vector analysis. Posterior corneal curvature has also been studied. METHODS: The IOLMaster 700 optical biometer was used to measure the corneal thickness and the radius of curvature of the anterior and posterior corneal surfaces. Refractive error was determined by a non-cycloplegic subjective refraction process with trial lenses. Linear regression analyses were applied using J0 and J45 power vector components. An evaluation was carried out according to the subject's age resulting into eight regression relationships for each astigmatic vector component for each relationship. RESULTS: A total of 2254 right eyes from 2254 healthy subjects were evaluated. A trend towards against-the-rule astigmatism (ATR) was found with aging, both for refractive astigmatism (RA) and keratometric astigmatism (KA), with 95.2% of subjects under 20 years old having with-the-rule (WTR) KA, and only 22.8% above 79 years old. The following regression equations were found between RA and KA: [Formula: see text] = 0.73 × [Formula: see text] - 0.18 (R = 0.78) and [Formula: see text] = 0.70 × [Formula: see text] + 0.04 (R = 0.69) and between RA and total corneal astigmatism (TCA): [Formula: see text] = 0.73 × [Formula: see text] + 0.13 (R=0.78) and [Formula: see text] = 0.70 × [Formula: see text] - 0.06 (R = 0.68) for the whole sample, but with sensible differences among age groups, both in the slope and in the intercept. CONCLUSION: Ignoring the age of the subject when using Javal's rule could lead to an error in the final cylinder calculation that would increase in high astigmatisms. Applying this new power vector approach based on subject's age could improve the accuracy of the astigmatism prediction.

Reliability and Agreement of Keratometry Measurements Obtained With Eye Surface Profilometry and Partial Coherence Interferometry.

PURPOSE: The aim of this study was to assess the repeatability of keratometry parameters obtained using the Eye Surface Profiler (ESP) system and their agreement with the IOL Master 500 device. METHODS: Seventy-one eyes of 71 healthy participants were evaluated. Three repeated measurements were performed using the ESP system. Simulated keratometry in the flat (SimKf) and steep (SimKs) meridians, astigmatism, and axis were obtained. The same parameters were measured using the IOL Master 500 device. The J0 and J45 vector components of the astigmatism were calculated. The intrasession repeatability was analyzed using within-subject SD (Sw) and intraclass correlation coefficient (ICC). Agreement was assessed using paired statistical tests and the Bland-Altman method. RESULTS: The Sw was 0.07 mm, 0.04 mm, 0.51 D, 0.33 D, and 0.22 D, and the ICC was 0.96, 0.98, 0.74, 0.61, and 0.55 for SimKf, SimKs, astigmatism, J0, and J45, respectively. The mean difference and limits of agreement when comparing the ESP system with the IOL Master 500 device were 0.37 mm (0.08/0.66) for SimKf ( P < 0.001), 0.18 mm (0.00/0.35) for SimKs ( P < 0.001), -0.93 D (-2.42/0.56) for astigmatism ( P < 0.001), 0.51 D (-0.22/1.24) for J0 ( P < 0.001), and 0.06 D (-0.48/0.60) for J45 ( P = 0.09). CONCLUSIONS: The ESP system provides consistent values for simulated keratometry, showing moderate consistency for astigmatism parameters. Contact lens practitioners should be aware that the ESP system and IOL Master 500 device provide different simulated keratometry from a clinically viewpoint.

Evaluation of a New All-in-One Optical Biometer and Comparison With a Validated Swept-source OCT Biometer.

PURPOSE: To assess agreement between a new all-in-one non-contact optical biometer based on optical low coherence reflectometry (SW-9000 µm Plus; Suoer) and a swept-source optical coherence tomography biometer (OA-2000; Tomey). METHODS: Each eye was scanned three times in a row by each device at random. The measured ocular parameters included central corneal thickness (CCT), anterior chamber depth (ACD), lens thickness (LT), axial length (AL), flat keratometry (Kf), steep keratometry (Ks), mean keratometry (Km), astigmatism, corneal diameter (CD), and pupil diameter (PD). The paired t test was used to show the differences between the SW-9000 and OA-2000. Bland-Altman plots and the 95% limits of agreement (LoA) were applied to assess the consistency of the measurements. RESULTS: Sixty eyes from 60 healthy participants were examined, with a mean spherical equivalent refraction of -5.58 ± 2.31 diopters and a mean age of 30.40 ± 6.07 years. The Bland-Altman plots showed high agreement for AL, ACD, LT, Kf, Ks, Km, astigmatism, and CD measurements (95% LoA: -0.06 to 0.04 mm, -0.10 to 0.06 mm, -0.12 to 0.11 mm, -0.30 to 0.29 D, -0.35 to 0.38 D, -0.29 to 0.30 D, -0.30 to 0.34 D, and -0.50 to 0.06 mm, respectively), whereas the agreement for CCT and PD were moderate (95% LoA: 7.12 to 20.43 µm, -0.75 to 1.19 mm, respectively). CONCLUSIONS: The new all-in-one non-contact biometer had high agreement with the OA-2000 biometer on the AL, ACD, LT, Kf, Ks, Km, astigmatism, and CD measurements. For most of the ocular parameters assessed, they were clinically interchangeable. [J Refract Surg. 2023;39(12):825-830.].