[Evaluation of the accuracy of modern intraocular lens calculation formulas when optical biometry is not possible]. / Otsenka tochnosti sovremennykh formul rascheta intraokulyarnykh linz pri nevozmozhnosti vypolneniya opticheskoi biometrii.

PURPOSE: This study evaluates the accuracy of modern intraocular lens (IOL) calculation formulas using axial length (AL) data obtained by ultrasound biometry (UBM) compared to the third-generation SRK/T calculator. MATERIAL AND METHODS: The study included 230 patients (267 eyes) with severe lens opacities that prevented optical biometry, who underwent phacoemulsification (PE) with IOL implantation. IOL power calculation according to the SRK/T formula was based on AL and anterior chamber depth obtained by UBM (Tomey Biometer Al-100) and keratometry on the Topcon KR 8800 autorefractometer. To adapt AL for new generation calculators - Barrett Universal II (BUII), Hill RBF ver. 3.0 (RBF), Kane and Ladas Super Formula (LSF) - the retinal thickness (0.20 mm) was added to the axial length determined by UBM, and then the optical power of the artificial lens was calculated. The mean error and its modulus value were used as criteria for the accuracy of IOL calculation. RESULTS: A significant difference (p=0.008) in the mean IOL calculation error was found between the formulas. Pairwise analysis revealed differences between SRK/T (-0.32±0.58 D) and other formulas - BUII (-0.16±0.52 D; p=0.014), RBF (-0.17±0.51 D; p=0.024), Kane (-0.17±0.52 D; p=0.029), but not with the LSF calculator (-0.19±0.53 D; p=0.071). No significant differences between the formulas were found in terms of mean error modulus (p=0.238). New generation calculators showed a more frequent success in hitting target refraction (within ±1.00 D in more than 95% of cases) than the SRK/T formula (86%). CONCLUSION: The proposed method of adding 0.20 mm to the AL determined by UBM allows using this parameter in modern IOL calculation formulas and improving the refractive results of PE, especially in eyes with non-standard anterior segment structure.

Ocular Biometric Components in Hyperopic Children and a Machine Learning-Based Model to Predict Axial Length.

Purpose: The purpose of this study was to investigate the development of optical biometric components in children with hyperopia, and apply a machine-learning model to predict axial length. Methods: Children with hyperopia (+1 diopters [D] to +10 D) in 3 age groups: 3 to 5 years (n = 74), 6 to 8 years (n = 102), and 9 to 11 years (n = 36) were included. Axial length, anterior chamber depth, lens thickness, central corneal thickness, and corneal power were measured; all participants had cycloplegic refraction within 6 months. Spherical equivalent (SEQ) was calculated. A mixed-effects model was used to compare sex and age groups and adjust for interocular correlation. A classification and regression tree (CART) analysis was used to predict axial length and compared with the linear regression. Results: Mean SEQ for all 3 age groups were similar but the 9 to 11 year old group had 0.49 D less hyperopia than the 3 to 5 year old group (P < 0.001). With the exception of corneal thickness, all other ocular components had a significant sex difference (P < 0.05). The 3 to 5 year group had significantly shorter axial length and anterior chamber depth and higher corneal power than older groups (P < 0.001). Using SEQ, age, and sex, axial length can be predicted with a CART model, resulting in lower mean absolute error of 0.60 than the linear regression model (0.76). Conclusions: Despite similar values of refractive errors, ocular biometric parameters changed with age in hyperopic children, whereby axial length growth is offset by reductions in corneal power. Translational Relevance: We provide references for optical components in children with hyperopia, and a machine-learning model for convenient axial length estimation based on SEQ, age, and sex.

Convolutional Neural Network-Based Prediction of Axial Length Using Color Fundus Photography.

Purpose: To develop convolutional neural network (CNN)-based models for predicting the axial length (AL) using color fundus photography (CFP) and explore associated clinical and structural characteristics. Methods: This study enrolled 1105 fundus images from 467 participants with ALs ranging from 19.91 to 32.59 mm, obtained at National Taiwan University Hospital between 2020 and 2021. The AL measurements obtained from a scanning laser interferometer served as the gold standard. The accuracy of prediction was compared among CNN-based models with different inputs, including CFP, age, and/or sex. Heatmaps were interpreted by integrated gradients. Results: Using age, sex, and CFP as input, the mean ± standard deviation absolute error (MAE) for AL prediction by the model was 0.771 ± 0.128 mm, outperforming models that used age and sex alone (1.263 ± 0.115 mm; P < 0.001) and CFP alone (0.831 ± 0.216 mm; P = 0.016) by 39.0% and 7.31%, respectively. The removal of relatively poor-quality CFPs resulted in a slight MAE reduction to 0.759 ± 0.120 mm without statistical significance (P = 0.24). The inclusion of age and CFP improved prediction accuracy by 5.59% (P = 0.043), while adding sex had no significant improvement (P = 0.41). The optic disc and temporal peripapillary area were highlighted as the focused areas on the heatmaps. Conclusions: Deep learning-based prediction of AL using CFP was fairly accurate and enhanced by age inclusion. The optic disc and temporal peripapillary area may contain crucial structural information for AL prediction in CFP. Translational Relevance: This study might aid AL assessments and the understanding of the morphologic characteristics of the fundus related to AL.

Myopia prevalence and ocular biometry in children and adolescents at different altitudes: a cross-sectional study in Chongqing and Tibet, China.

OBJECTIVE: To investigate the differences in myopia prevalence and ocular biometry in children and adolescents in Chongqing and Tibet, China. DESIGN: Cross-sectional study. SETTING: The study included children and adolescents aged 6-18 years in Chongqing, a low-altitude region, and in Qamdo, a high-altitude region of Tibet. PARTICIPANTS: A total of 448 participants in Qamdo, Tibet, and 748 participants in Chongqing were enrolled in this study. METHODS: All participants underwent uncorrected visual acuity assessment, non-cycloplegic refraction, axial length (AL) measurement, intraocular pressure (IOP) measurement and corneal tomography. And the participants were grouped according to age (6-8, 9-11, 12-14 and 15-18 years group), and altitude of location (primary school students: group A (average altitude: 325 m), group B (average altitude: 2300 m), group C (average altitude: 3250 and 3170 m) and group D (average altitude: 3870 m)). RESULTS: There was no statistical difference in mean age (12.09±3.15 vs 12.2±3.10, p=0.549) and sex distribution (males, 50.4% vs 47.6%, p=0.339) between the two groups. The Tibet group presented greater spherical equivalent (SE, -0.63 (-2.00, 0.13) vs -0.88 (-2.88, -0.13), p<0.001), shorter AL (23.45±1.02 vs 23.92±1.19, p<0.001), lower prevalence of myopia (39.7% vs 47.6%, p=0.008) and flatter mean curvature power of the cornea (Km, 43.06±1.4 vs 43.26±1.36, p=0.014) than the Chongqing group. Further analysis based on age subgroups revealed that the Tibet group had a lower prevalence of myopia and higher SE in the 12-14, and 15-18 years old groups, shorter AL in the 9-11, 12-14 and 15-18 years old groups, and lower AL to corneal radius of curvature ratio (AL/CR) in all age subgroups compared with the Chongqing group, while Km was similar between the two groups in each age subgroup. Simple linear regression analysis showed that SE decreased with age in both the Tibet and Chongqing groups, with the Tibet group exhibiting a slower rate of decrease (p<0.001). AL and AL/CR increased with age in both the Tibet and Chongqing groups, but the rate of increase was slower in the Tibet group (p<0.001 of both). Multiple linear regression analysis revealed that AL had the greatest effect on SE in both groups, followed by Km. In addition, the children and adolescents in Tibet presented thinner corneal thickness (CCT, p<0.001), smaller white to white distance (WTW, p<0.001), lower IOP (p<0.001) and deeper anterior chamber depth (ACD, p=0.015) than in Chongqing. Comparison of altitude subgroups showed that the prevalence of myopia (p=0.002), SE (p=0.031), AL (p=0.001) and AL/CR (p<0.001) of children at different altitudes was statistically different but the Km (p=0.189) were similar. The highest altitude, Tengchen County, exhibited the lowest prevalence of myopia and greatest SE among children, and the mean AL also decreased with increasing altitude. CONCLUSIONS: Myopia prevalence in Tibet was comparable with that in Chongqing for students aged 6-8 and 9-11 years but was lower and myopia progressed more slowly for students aged 12-14 and 15-18 years than in Chongqing, and AL was the main contributor for this difference, which may be related to higher ultraviolet radiation exposure and lower IOP in children and adolescents at high altitude in Tibet. Differences in AL and AL/CR between Tibet and Chongqing children and adolescents manifested earlier than in SE, underscoring the importance of AL measurement in myopia screening.

Eye morphometry, body size, and flexibility parameters in myopic adolescents.

The aim of this study was to investigate the anatomical and physiological ocular parameters in adolescents with myopia and to examine the relations between refractive error (SER), ocular biometry, body size and flexibility parameters in myopic adolescents. A cross-sectional study of 184 myopic adolescents, aged 15 to 19 years was conducted. Refractive error and corneal curvature measures of the eye were evaluated using an autorefractometer under cycloplegia. Central corneal thickness was determined by contact pachymetry. The ocular axial length, anterior and vitreous chamber depth, and lens thickness were measured using A-scan biometry ultrasonography. Height and body weight were measured according to a standardized protocol. Body mass index (BMI) was subsequently calculated. Beighton scale was used to measure joint flexibility. Body stature was positively correlated with ocular axial length (r = 0.39, p < 0.001) and vitreous chamber depth (r = 0.37, p < 0.001). There was a negative correlation between height and SER (r = - 0.46; p < 0.001). Beighton score and body weight had weak positive correlations with axial length and vitreous chamber depth, and a weak negative correlation with SER. A significantly more negative SER was observed in the increased joint mobility group (p < 0.05; U = 5065.5) as compared to normal joint mobility group: mean - 4.37 ± 1.85 D (median - 4.25; IQR - 6.25 to - 3.25 D) and mean - 3.72 ± 1.66 D (median - 3.50; IQR - 4.75 to - 2.25 D) respectively. There was a strong association between height and axial length, as well as SER. Higher degree of myopia significantly correlated with greater Beighton score (increased joint mobility).

Impact of segmented optical axial length on the performance of intraocular lens power calculation formulas.

PURPOSE: To investigate the difference between the segmented axial length (AL) and the composite AL on a swept-source optical coherence tomography biometer and to evaluate the subsequent effects on artificial intelligence intraocular lens (IOL) power calculations: the Kane and Hill-RBF 3.0 formulas compared with established vergence formulas. SETTING: National Hospital Organization, Tokyo Medical Center, Japan. DESIGN: Retrospective case series. METHODS: Consecutive patients undergoing cataract surgery with a single-piece IOL were reviewed. The prediction accuracy of the Barrett Universal II, Haigis, Hill-RBF 3.0, Hoffer Q, Holladay 1, Kane, and SRK/T formulas based on 2 ALs were compared for each formula. The heteroscedastic test was used with the SD of prediction errors as the endpoint for formula performance. RESULTS: The study included 145 eyes of 145 patients. The segmented AL (24.83 ± 1.89) was significantly shorter than the composite AL (24.88 ± 1.96, P < .001). Bland-Altman analysis revealed a negative proportional bias for the differences between the segmented AL and the composite AL. The SD values obtained by Hoffer Q, Holladay 1, and SRK/T formulas based on the segmented AL (0.52 diopters [D], 0.54 D, and 0.50 D, respectively) were significantly lower than those based on the composite AL (0.57 D, 0.60 D, and 0.52 D, respectively, P < .01). CONCLUSIONS: The segmented ALs were longer in short eyes and shorter in long eyes than the composite ALs. The refractive accuracy can be improved in the Hoffer Q, Holladay 1, and SRK/T formulas by changing the composite ALs to the segmented ALs.

The long and short of it: a comprehensive assessment of axial length estimation in myopic eyes from ocular and demographic variables.

BACKGROUND/OBJECTIVES: Axial length, a key measurement in myopia management, is not accessible in many settings. We aimed to develop and assess machine learning models to estimate the axial length of young myopic eyes. SUBJECTS/METHODS: Linear regression, symbolic regression, gradient boosting and multilayer perceptron models were developed using age, sex, cycloplegic spherical equivalent refraction (SER) and corneal curvature. Training data were from 8135 (28% myopic) children and adolescents from Ireland, Northern Ireland and China. Model performance was tested on an additional 300 myopic individuals using traditional metrics alongside the estimated axial length vs age relationship. Linear regression and receiver operator characteristics (ROC) curves were used for statistical analysis. The contribution of the effective crystalline lens power to error in axial length estimation was calculated to define the latter's physiological limits. RESULTS: Axial length estimation models were applicable across all testing regions (p ≥ 0.96 for training by testing region interaction). The linear regression model performed best based on agreement metrics (mean absolute error [MAE] = 0.31 mm, coefficient of repeatability = 0.79 mm) and a smooth, monotonic estimated axial length vs age relationship. This model was better at identifying high-risk eyes (axial length >98th centile) than SER alone (area under the curve 0.89 vs 0.79, respectively). Without knowing lens power, the calculated limits of axial length estimation were 0.30 mm for MAE and 0.75 mm for coefficient of repeatability. CONCLUSIONS: In myopic eyes, we demonstrated superior axial length estimation with a linear regression model utilising age, sex and refractive metrics and showed its clinical utility as a risk stratification tool.

Quantitative analysis of dynamic iris changes in primary angle-closure disease with long axial lengths: the Handan Eye Study.

OBJECTIVE: To investigate dynamic iris changes in patients with primary angle-closure disease (PACD) with long axial length (AL) compared to those with short and medium AL. METHODS: This observational cross-sectional study enrolled participants aged 35 years or older from the Handan Eye Study follow-up examination who were diagnosed with PACD and underwent Visante anterior segment optical coherence tomography (ASOCT) imaging under light and dark conditions. The right eye of each participant was included in the analysis. AL was categorized as short (<22.0 mm), medium (≥22.0 to ≤23.5 mm), or long (>23.5 mm). Anterior segment parameters, including iris dynamic changes, were compared among the three groups with different ALs. RESULTS: Data from 448 patients with PACD were analyzed. We found that 10.9% of included eyes had a long AL with a flatter cornea; larger central anterior chamber depth, angle opening distance, anterior chamber width, anterior chamber area, and volume; and smaller lens thickness and lens vault (LV) (P < 0.05) than those with short AL. No significant difference existed between the three groups in iris thickness, iris cross-sectional area (IA), iris curvature, or pupil diameter (PD) change between light and dark (P > 0.05). The significant associated factors for IA changes were area recess area (ARA) in the dark, LV in the dark, and PD change from light to dark (P < 0.05). CONCLUSIONS: Dynamic and static iris parameters were consistent across patients with PACD with short, medium, or long AL and may contribute to the pathogenesis of angle closure in atypical PACD.

Guided Trocar Insertion in Highly Myopic Eyes.

PURPOSE: To demonstrate through a diagnostic test used as a new preoperative assessment that trocar insertion for pars plana vitrectomy could be safely placed at a distance >4.0 mm in highly myopic eyes to facilitate the surgical maneuvers. METHODS: Thirty eyes of 30 patients were tested with a biometer for the axial length measurement and with ultrasound biomicroscopy to measure the pars plana length. Pars plana lengths of highly myopic eyes were then compared with those of emmetropic eyes. The surgeon also measured the pars plana of highly myopic eyes intraoperatively and compared it with ultrasound measurements to assess ultrasound biomicroscopy reliability. RESULTS: The mean axial length was 23.81 mm (SD ± 0.30) in the control group and 31.11 mm (SD ± 0.56) in the myopic group. The mean pars plana length was 4.96 mm (SD ± 0.19) in control eyes and 6.65 (SD ± 0.36) in myopic eyes. An extremely significant statistical difference ( P < 0.001) was obtained by comparing the length of pars plana between control eyes and myopic eyes. The results of pars plana measurements were 6.65 mm (SD ± 0.36, ultrasound biomicroscopy) and 6.66 mm (SD ± 0.34, intraoperative measurements) in myopic eyes. The statistical comparison of the measurements in these two groups did not give a statistically significant result ( P = 0.950). CONCLUSION: Ultrasound biomicroscopy is a reliable technique to calculate the length of pars plana in highly myopic eyes, where this parameter is significantly greater than that of emmetropic eyes. Trocars insertion for pars plana vitrectomy may be performed, in eyes with axial length >30 mm, in relative safety at a distance to limbus higher than 4 mm.

Development and validation of a deep learning model to predict axial length from ultra-wide field images.

BACKGROUND: To validate the feasibility of building a deep learning model to predict axial length (AL) for moderate to high myopic patients from ultra-wide field (UWF) images. METHODS: This study included 6174 UWF images from 3134 myopic patients during 2014 to 2020 in Eye and ENT Hospital of Fudan University. Of 6174 images, 4939 were used for training, 617 for validation, and 618 for testing. The coefficient of determination (R2), mean absolute error (MAE), and mean squared error (MSE) were used for model performance evaluation. RESULTS: The model predicted AL with high accuracy. Evaluating performance of R2, MSE and MAE were 0.579, 1.419 and 0.9043, respectively. Prediction bias of 64.88% of the tests was under 1-mm error, 76.90% of tests was within the range of 5% error and 97.57% within 10% error. The prediction bias had a strong negative correlation with true AL values and showed significant difference between male and female (P < 0.001). Generated heatmaps demonstrated that the model focused on posterior atrophy changes in pathological fundus and peri-optic zone in normal fundus. In sex-specific models, R2, MSE, and MAE results of the female AL model were 0.411, 1.357, and 0.911 in female dataset and 0.343, 2.428, and 1.264 in male dataset. The corresponding metrics of male AL models were 0.216, 2.900, and 1.352 in male dataset and 0.083, 2.112, and 1.154 in female dataset. CONCLUSIONS: It is feasible to utilize deep learning models to predict AL for moderate to high myopic patients with UWF images.

Comparison of the ocular ultrasonic and optical biometry devices in the different quality measurements.

PURPOSE: To compare the reliability and agreement of axial length (AL), anterior chamber depth (ACD), and lens thickness (LT) measurements obtained with optical biometry based on swept-source optical coherence tomography (IOLMaster 700; Carl Zeiss, Germany) and an ultrasound biometry device (Nidek; US-4000 Echoscan, Japan) in different qualities of AL measurement. METHODS: A total of 239 consecutive eyes of 239 cataract surgery candidates with a mean age of 56 ± 14 years were included. The quality measurements were grouped according to the quartiles of SD of the measured AL by IOLMaster 700. The first and fourth quartile's SD are defined as high and low-quality measurement, respectively, and the second and third quartiles' SD is defined as moderate-quality. RESULTS: The reliability of AL and ACD between the two devices in all patients and in different quality measurement groups was excellent with highly statistically significant (AL: all ICC=0.999 and P<0.001, ACD: all ICC>0.920 and P<0.001). AL and ACD in all quality measurements showed a very strong correlation between devices with highly statistically significant. However, there was poor (ICC=0.305), moderate (ICC=0.742), and good (ICC=0.843) reliability in measuring LT in low-, moderate-, and high-quality measurements, respectively. LT showed a very strong correlation (r = 0.854) with highly statistically significant (P<0.001) between devices only in patients with high-quality measurements. CONCLUSIONS: AL and ACD of the IOLMaster700 had outstanding agreements with the US-4000 ultrasound in different quality measurements of AL and can be used interchangeably. But LT should be used interchangeably cautiously only in the high-quality measurements group.

Retrospective Comparison of the Myopia Master and the Lenstar LS900 Axial Length Measurements in Children with Myopia.

BACKGROUND: This study is a retrospective analysis to compare ocular biometry measurements of axial length in children with myopia using Myopia Master (OCULUS, Wetzlar, Germany) and Lenstar LS900 (HAAG-STREIT AG, Köniz, Switzerland). PATIENTS AND METHODS: Axial length measurements obtained with both instruments within a 3-week period were collected retrospectively. Measurements were visualized with a Bland-Altman plot. For statistical evaluation, a paired t-test was applied, and the Pearson correlation coefficient (r) was established. RESULTS: Sixty-one eyes from 31 myopic patients (59% male, 41% female) with a mean age of 11.34 ± 3.25 years (range: 6 - 18 years) were identified. Mean axial length was 24.7 mm (SD 1.29) with the Myopia Master and 24.69 mm (SD 1.30) with the Lenstar LS900 (Pearson correlation: r = 0.9991). The average difference of the axial length measurement between the two biometers was 0.00 064 mm ± 0.056 SD (p = 0.9293). CONCLUSION: The axial length measured by Myopia Master and Lenstar LS900 did not differ significantly. Thus, previous values obtained with the Lenstar LS900 can be applied to assess myopia progression.

Comparison of the accuracy of nine intraocular lens power calculation formulas using partial coherence interferometry.

Cataract surgery is the most performed procedure in the world. To achieve the target refraction, several intraocular lens (IOL) power calculation formulas have been developed to improve the accuracy of IOL power predictions. We compared the accuracy of 9 IOL power calculation formulas (SRK/T, Hoffer Q, Holladay 1, Haigis, Barrett Universal II, Kane, EVO 2.0, Ladas Super formula and Hill-RBF 3.0) using partial coherence interferometry (PCI). We collected data from patients who underwent uncomplicated cataract surgery with implantation of 1 of 3 IOL types currently used in our center. All preoperative biometric measurements were performed using PCI. Prediction errors (PE) were deduced from refractive outcomes evaluated 3 months after surgery. The mean prediction error (ME), mean absolute prediction error (MAE), median absolute prediction error (MedAE), and standard deviation of prediction error (SD) were calculated, as well as the percentage of eyes with a PE within ± 0.25, ± 0.50, ± 0.75 and ± 1.00D for each formula. We included 126 eyes of 126 patients. Kane achieved the lowest MAE and SD across the entire sample as well as the highest percentage of PE within ± 0.50D and was shown to be more accurate than Haigis and Hoffer Q (P<001). For an axial length of more than 26.0mm, EVO 2.0 and Barrett obtained the lowest MAEs, with EVO 2.0 and Kane showing a higher percentage of prediction at ±0.50D compared to old generation formulas except for SRK/T (P=04). All investigated formulas achieved good results; there was a tendency toward better outcomes with new generation formulas, especially in atypical eyes.

Deep Learning-based Prediction of Axial Length Using Ultra-widefield Fundus Photography.

PURPOSE: To develop a deep learning model that can predict the axial lengths of eyes using ultra-widefield (UWF) fundus photography. METHODS: We retrospectively enrolled patients who visited the ophthalmology clinic at the Seoul National University Hospital between September 2018 and December 2021. Patients with axial length measurements and UWF images taken within 3 months of axial length measurement were included in the study. The dataset was divided into a development set and a test set at an 8:2 ratio while maintaining an equal distribution of axial lengths (stratified splitting with binning). We used transfer learning-based on EfficientNet B3 to develop the model. We evaluated the model's performance using mean absolute error (MAE), R-squared (R2), and 95% confidence intervals (CIs). We used vanilla gradient saliency maps to illustrate the regions predominantly used by convolutional neural network. RESULTS: In total, 8,657 UWF retinal fundus images from 3,829 patients (mean age, 63.98 ±15.25 years) were included in the study. The deep learning model predicted the axial lengths of the test dataset with MAE and R2 values of 0.744 mm (95% CI, 0.709-0.779 mm) and 0.815 (95% CI, 0.785-0.840), respectively. The model's accuracy was 73.7%, 95.9%, and 99.2% in prediction, with error margins of ±1.0, ±2.0, and ±3.0 mm, respectively. CONCLUSIONS: We developed a deep learning-based model for predicting the axial length from UWF images with good performance.

Repeatability and agreement of swept-source optical coherence tomography and partial coherence interferometry biometers in myopes.

CLINICAL RELEVANCE: Biometric measurements in the context of myopia are fundamental to detect eyes at risk of developing myopia and during the follow-up of patients with myopia control treatment. Thus, the accuracy of biometers has high clinical relevance. BACKGROUND: The Myopia Master is a new biometer based on partial coherence interferometry especially dedicated to the follow-up of myopic patients. This study aims to assess the repeatability of the Myopia Master and evaluate its agreement with a swept-source optical coherence interferometry biometer (IOL Master 700). METHODS: This cross-sectional prospective study assessed the biometric parameters of two groups of myopes (age range: 8-16 years old), spectacle corrected (n = 60) and orthokeratology contact lens wearers (n = 60). One senior optometrist performed two consecutive measurements per instrument, which included axial length, mean keratometry and horizontal visible iris diameter (HVID). The repeatability of each device and the agreement between devices were assessed by the dispersion of the measurement differences, for AL, mean keratometry, corneal astigmatism and HVID. RESULTS: The two biometers measured approximately the same value in both measurements. Test-retest repeatability tended to be lower than clinical significant thresholds, in particular, for AL and mean keratometry. Corneal-related parameters tended to have lower repeatability in the orthokeratology group, especially mean keratometry. The agreement between instruments revealed statistically significant differences between devices with the SS-OCT measuring longer eyes, steeper corneas and larger HVID. CONCLUSIONS: In a paediatric population, the Myopia Master showed clinically acceptable repeatability levels, but the IOL Master 700 demonstrated superior repeatability. Eyes treated with orthokeratology may compromise the repeatability of the corneal-related parameters. The Myopia Master and the IOL Master 700 are repeatable devices appropriate for monitoring myopia progression, but the differences observed do not allow their use interchangeably.

Repeatability and comparability of a new swept-source optical coherence tomographer in optical biometry.

PURPOSE: To evaluate the reproducibility in the measurement of ocular biometric parameters using a new swept-source optical coherence tomographer and its comparability with an optical low coherence reflectometry biometer. DESIGN: An observational, descriptive, cross-sectional study. METHODS: 45 right eyes of 45 patients diagnosed with cataract were included. Three successive biometric measurements with Anterion and one with Lenstar LS900 were performed on each patient. The following variables were collected: axial length (AXL), anterior chamber depth (ACD), flat K (K1), steep K (K2), central corneal thickness (CCT), lens thickness (LT) and white-to-white distance (WTW). The intrasubject standard deviation (Sw) and the coefficient of Pearson "R" were calculated in order to assess the repeatability. The intraclass correlation coefficient (ICC) and the concordance correlation coefficient (CCC) were obtained to evaluate the comparability between devices. A Bland-Altman plot was performed for each variable. RESULTS: The coefficient of Pearson was excellent and statistically significant in the evaluation of the repeatability in all the variables. The highest values were 0.987 (AXL), 0.983 (CCT) and 0.942 (ACD). There were no statically significant differences between repeated measurements with Anterion in all the parameters. The ICC and CCC were excellent in the evaluation of AXL, CCT and ACD, and were also good in regard to K1, K2, LT and WTW. CONCLUSIONS: Performing biometry with the SS-OCT Anterion is a reliable and reproducible procedure, and it is comparable with the Lenstar LS900.

Update on Biometry and Lens Calculation - A Review of the Basic Principles and New Developments. / Update Biometrie und Linsenberechnung ­ ein Review zu Grundlagen und neuen Entwicklungen.

These days, accurate calculation of artificial lenses is an important aspect of patient management. In addition to the classic theoretical optical formulae there are a number of new approaches, most of which are available as online calculators. This review aims to explain the background of artificial lens calculation and provide an update on study results based on the latest calculation approaches. Today, optical biometry provides the computational basis for theoretical optical formulae, ray tracing, and also empirical approaches using artificial intelligence. Manufacturer information on IOL design and IOL power recorded as part of quality control could improve calculations, especially for higher IOL powers. With modern measurement data, there is further potential for improvement in the determination of the axial length to the retinal pigment epithelium and by adopting a sum-of-segment approach. With the available data, the cornea can be assumed to be a thick lens. The Kane formula, the EVO 2.0 formula, the Castrop formula, the PEARL-DGS, formula and the OKULIX calculation software provide consistently good results for artificial lens calculations. Excellent refractive results can be achieved using these tools, with approximately 80% having an absolute prediction error within 0.50 dpt, at least in highly selected study populations. The Barrett Universal II formula also produces excellent results in the normal and long axial length range. For eyes with short axial lengths, the use of Barrett Universal II should be reconsidered; in this case, one of the methods mentioned above is preferable. Second Eye Refinement can also be considered in this patient population, in conjunction with established classic third generation formulae.

[Alternative method of intraocular lens power calculation in eyes with short axial length]. / Al'ternativnyi sposob rascheta opticheskoi sily intraokulyarnykh linz pri korotkoi perednezadnei osi glaza.

PURPOSE: To develop an alternative method of intraocular lens (IOL) power calculation in eyes with mature cataract and axial length (AL) of less than 22.0 mm using modern formulas Barrett Universal II and Hill RBF. MATERIAL AND METHODS: The study enrolled 41 patients (41 eyes) who underwent phacoemulsification (PE). Ultrasound biometry (Tomey Biometer Al-100) and keratometry (Topcon-8800) were used for IOL power calculation by SRK/T and Haigis formulas. To calculate IOL power by Barrett Universal II and Hill RBF formulas, 0.2 mm were added to AL measured with ultrasonography (retinal thickness). One month after PE, spherical equivalent of refraction was compared with target refraction (calculated by the formulas listed above), and based on that a conclusion was made on the accuracy of calculations. RESULTS: Haigis formula was found to be the least accurate (IOL calculation error -0.39±0.79 D). The calculation error in SRK/T (0.04±0.79 D), Barrett Universal II (0.02±0.79 D) and Hill RBF (-0.05±0.73 D) formulas was much lower. However, among them Hill RBF had the lowest spread of the mean absolute IOL calculation error. Pairwise comparison revealed significant difference of mean IOL calculation error by Haigis formula versus the others. There was no significant difference in the following pairs: SRK/T - Barrett Universal II (p=0.855), and SRK/T - Hill RBF (p=0.167), but there was a significant difference (p=0.043) in the Barrett Universal II - Hill RBF pairdue to the tendency for slight hypermetropic calculation error in the former and the inherent slight myopic shift in the latter.. CONCLUSION: The proposed alternative method of IOL power calculation in eyes with mature cataract and short AL using modern formulas (Barrett Universal II and Hill RBF) shows higher accuracy compared to the formulas embedded in ultrasound biometer (SRK/T and Haigis), and can be recommended for use in everyday practice.

Evaluation of ocular biometry in primary angle-closure disease with two swept source optical coherence tomography devices.

PURPOSE: To investigate agreement between 2 swept source OCT biometers, IOL Master700 and Anterion, in various ocular biometry and intraocular lens (IOL) calculations of primary angle-closure disease (PACD). SETTING: Rajavithi Hospital, Bangkok, Thailand. DESIGN: Prospective comparative study. METHODS: This study conducted in a tertiary eye care center involving biometric measurements obtained with 2 devices in phakic eye with diagnosis of PACD. Mean difference and intraclass correlation coefficient (ICC) with confidence limits were assessed, and calculations of estimated residual refraction of the IOL were analysed using Barrett's formula. RESULTS: Sixty-nine eyes from 45 PACD patients were enrolled for the study. Excellent agreement of various parameters was revealed, with ICC (confidence limits) of K1 = 0.953 (0.861-0.979), K2 = 0.950 (0.778-0.98), ACD = 0.932 (0.529-0.978), WTW = 0.775 (0.477-0.888), and LT = 0.947 (0.905-0.97). Mean difference of axial length (AL) was -0.01 ± 0.02 mm with ICC of 1.000. IOL calculation was assessed with Barrett's formula, and Bland-Altman plot showed excellent agreement in the results of the 2 devices for the IOL power and estimated post-operative residual refraction (EPR). CONCLUSIONS: Mean differences of biometric parameters, obtained with IOL Master700 and Anterion, were small, and ICC showed excellent concordance. No clinical relevance in calculation of IOL power was found, and the two devices appeared to be comparably effective in clinical practice.

Measuring axial length of the eye from magnetic resonance brain imaging.

BACKGROUND: Metrics derived from the human eye are increasingly used as biomarkers and endpoints in studies of cardiovascular, cerebrovascular and neurological disease. In this context, it is important to account for potential confounding that can arise from differences in ocular dimensions between individuals, for example, differences in globe size. METHODS: We measured axial length, a geometric parameter describing eye size from T2-weighted brain MRI scans using three different image analysis software packages (Mango, ITK and Carestream) and compared results to biometry measurements from a specialized ophthalmic instrument (IOLMaster 500) as the reference standard. RESULTS: Ninety-three healthy research participants of mean age 51.0 ± SD 5.4 years were analyzed. The level of agreement between the MRI-derived measurements and the reference standard was described by mean differences as follows, Mango - 0.8 mm; ITK - 0.5 mm; and Carestream - 0.1 mm (upper/lower 95% limits of agreement across the three tools ranged from 0.9 mm to - 2.6 mm). Inter-rater reproducibility was between - 0.03 mm and 0.45 mm (ICC 0.65 to 0.93). Intra-rater repeatability was between 0.0 mm and - 0.2 mm (ICC 0.90 to 0.95). CONCLUSIONS: We demonstrate that axial measurements of the eye derived from brain MRI are within 3.5% of the reference standard globe length of 24.1 mm. However, the limits of agreement could be considered clinically significant. Axial length of the eye obtained from MRI is not a replacement for the precision of biometry, but in the absence of biometry it could provide sufficient accuracy to act as a proxy. We recommend measuring eye axial length from MRI in studies that do not have biometry but use retinal imaging to study neurodegenerative changes so as to control for differing eye size across individuals.