Assessment of the Vault After Implantable Collamer Lens Implantation Using the KS Formula

The optimization of the vault-predicting formula based on the anterior segment measurements from artemis insight 100

To optimize and evaluate the accuracy of the vault-predicting formula generated from a very high-frequency digital ultrasound robotic scanner (Artemis Insight 100). The relationship between the achieved lens vault (LVa) at one month after intraocular collamer lens (ICL) implantation surgery and the predicted vault (LVp) was analyzed by a retrospective study, and an optimized formula was built up. Then, the accuracy of the optimized vault-predicting formula was evaluated in a prospective study by comparing the LVa and the predicted vault from the optimized formula (LVop). The retrospective study included 77 patients (133 eyes) while the prospective study enrolled 90 patients (170 eyes). The difference between LVp and LVa at one month after surgery was statistically significant (P < 0.05), and the linear regression analysis of LVa against LVp yielded a good fit (R2 = 0.68). The optimized vault-predicting formula was LVop (μm) = 1.21 × LVp (μm) + 124.73. In the validation study, the difference between LVop and LVa was not statistically significant (P = 0.10), and a good agreement between LVop and LVa was shown by Bland-Altman analysis. The optimized vault-predicting formula could predict the actual LV after ICL implantation surgery, help to select an appropriate ICL size and reduce the need for re-operation.

Bibliometric and visualized analysis of posterior chamber phakic intraocular lens research between 2003 and 2023

Introduction

Myopia is causing a major public health concern, with its prevalence increasing globally. This study aimed to discuss posterior chamber phakic intraocular lens (pIOL) research publication trends and hotspots over the past 20 years.

Methods

Bibliometric analysis was performed using the Web Science Core Collection to investigate posterior-chamber pIOL research publication trends. The extracted records were analyzed, and a knowledge map was built using VOSviewer v.1.6.20. The analysis included visualizing the annual publication count, countries/regions distribution, international and institutional collaborations, author productivity, and journal contribution, in addition to identifying knowledge bases and hotspots. Burst keywords were extracted using CiteSpace v.6.1.R.

Results

In total, 791 articles on posterior chamber pIOLs published between 2003 and 2023 were retrieved. China had the highest number of publications, whereas Japanese papers received the most citations. Fudan University had the highest number of publications, with articles from Kitasato University having the highest number of citations. Regarding individual research, Xingtao Zhou has published the most significant number of articles, and Shimizu Kimiya had the highest number of citations. The top productive/influential journal was 'Journal of Cataract & Refractive Surgery'. The top cited references primarily focused on reporting the clinical outcomes of implantable collamer lens (ICL) for individuals with moderate to high myopia. The keywords primarily formed four clusters: posterior chamber pIOL clinical outcomes for myopic astigmatism correction, posterior chamber pIOL implantation complications, ICL size selection and postoperative vault predictions, and postoperative visual quality following posterior chamber pIOL implantation.

Conclusion

This study presents the first bibliometric analysis of research trends in posterior chamber pIOL over the past two decades. We investigated the current state and emerging trends of global collaboration and research focal points in this field, offering fresh insights and guidance for researchers.

Code-Free Machine Learning Approach for EVO-ICL Vault Prediction: A Retrospective Two-Center Study

Purpose

Establishing a development environment for machine learning is difficult for medical researchers because learning to code is a major barrier. This study aimed to improve the accuracy of a postoperative vault value prediction model for implantable collamer lens (ICL) sizing using machine learning without coding experience.

Methods

We used Orange data mining, a recently developed open-source, code-free machine learning tool. This study included eye-pair data from 294 patients from the B&VIIT Eye Center and 26 patients from Kim's Eye Hospital. The model was developed using OCULUS Pentacam data from the B&VIIT Eye Center and was internally evaluated through 10-fold cross-validation. External validation was performed using data from Kim's Eye Hospital.

Results

The machine learning model was successfully trained using the data collected without coding. The random forest showed mean absolute errors of 124.8 µm and 152.4 µm for the internal 10-fold cross-validation and the external validation, respectively. For high vault prediction (>750 µm), the random forest showed areas under the curve of 0.725 and 0.760 for the internal and external validation datasets, respectively. The developed model performed better than the classic statistical regression models and the Google no-code platform.

Conclusions

Applying a no-code machine learning tool to our ICL implantation datasets showed a more accurate prediction of the postoperative vault than the classic regression and Google no-code models.

Translational Relevance

Because of significant bias in measurements and surgery between clinics, the no-code development of a customized machine learning nomogram will improve the accuracy of ICL implantation.

Comparative evaluation of multiple nomograms for predicting postoperative vault after implantable collamer lens surgery

PURPOSE

To compare the vault predictability of most available implantable collamer lens (ICL) sizing nomograms and identify which preoperative measurements are predictive of vault.

SETTING

Private practice in Draper, Utah.

DESIGN

Retrospective chart review.

METHODS

This study was a retrospective analysis of 209 eyes of 106 patients who underwent STAAR Surgical ICL implantation. Analyses were performed based on the availability of preoperative parameters, varying the number of eyes for each test. Mean absolute error (MAE) of predicted vs actual postoperative vault was calculated for each nomogram. The frequency of Kim, Rocamora (least absolute shrinkage and selection operator-optical coherence tomography), Russo, and Reinstein recommending the correct ICL size in instances when Parkhurst, optimized white-to-white (WTW), and STAAR could not recommend a definitive ICL size was determined. Univariate and multivariate linear regression analysis was performed between preoperative measurements and vault.

RESULTS

The Kim, Rocamora, Russo, and Reinstein nomograms had significantly lower MAE of predicted vs actual postoperative vault than the KSV2 and Nakamura V3 nomograms. The Russo formula most frequently recommended the correct ICL size when the Parkhurst, Optimized WTW, and STAAR nomograms could not provide ICL size recommendations. At the 0.05 significance level, anterior chamber depth (ACD), ciliary body inner diameter (CBID), and pupil diameter were the parameters found to have significant correlation with postoperative vault.

CONCLUSIONS

The Kim, Rocamora, Russo, and Reinstein nomograms were the most predictive of vault. Additionally, ACD, CBID, and pupil diameter were found to be significantly correlated with vault and should be considered for use in future ICL sizing nomograms.

Assessing the efficacy of four methods established by four parameters in ICL size selection and relevant influencing factors: a prospective cohort study

PURPOSE

To compare the efficacy and relevant influencing factors of four ICL size selection methods established by four different parameters.

METHODS

This prospective study included 60 patients (120 eyes) who underwent bilateral ICL implantation. Patients were equally divided into four groups, and each group used the Parkhurst nomogram based on sulcus-to-sulcus (STS), the manufacturer's Online Calculation & Ordering System (OCOS) nomogram based on white-to-white (WTW), the KS formula based on angle-to-angle (ATA) and the NK formula based on anterior chamber width (ACW) to determine the ICL size. Recorded the vault one month after operation and compared the consistency between STS and WTW, ATA and ACW and their effects on the vault of different groups.

RESULTS

The Parkhurst nomogram, OCOS nomogram, KS formula and NK formula determined 86.7%, 70.0%, 83.3% and 66.7% of properly sized ICL, respectively. STS and ATA were correlated (P < 0.05). The mean difference between the STS and WTW, ATA and ACW was -0.37 ± 0.62 mm, -0.42 ± 0.53 mm and -0.44 ± 0.52 mm, respectively. The vault in the OCOS group was negatively correlated with △STS-WTW, and the vault in the NK group was negatively correlated with △STS-WTW, △STS-ATA and △STA-ACW. The vault in the Parkhurst group and KS group was not affected by anterior segment biometry variables.

CONCLUSION

ATA can be served as an alternative parameter to STS, and STS-based Parkhurst nomogram and ATA-based KS formula determined the most appropriate ICL size. When using OCOS nomogram and NK formula to select ICL size, postoperative abnormal vault was associated with a larger difference between STS and other anterior segment parameters.

Exploring Nomograms for Implantable Collamer Lens Size Selection in Myopia: A Literature-based Compilation

Purpose

To provide a comprehensive guide of all implantable collamer lens (ICL) sizing nomograms and the respective preoperative diagnostic devices that are required. This guide would help clinicians in choosing the appropriate ICL size for myopic patients to optimize postoperative vault height.

Methods

A literature search of peer-reviewed journals describing methods and postoperative outcomes of ICL sizing was conducted. Research articles containing ICL nomograms or formulas were identified from this search. Preoperative variables necessary for these nomograms and the required diagnostic devices to measure these parameters such as topography, biometry, or ultrasound biomicroscopy (UBM) were noted. An additional search was conducted to identify artificial intelligence (AI) or machine learning (ML)-derived nomograms.

Results

Eighteen ICL sizing nomograms were identified through literature search. Five of these nomograms are available for use and require topography or biometry devices. Of these, four include the manufacturer's, optimized white-to-white (WTW), Kang, Kim, and Rocamora Nomograms. Eight of the 18 nomograms available for use require UBM. Eight of these include the Kojima, Nakamura, KS, ZZ, Dougherty, Parkhurst, Russo, and Reinstein Nomograms. Four of the 18 nomograms are ML-derived including Shen, Rocamora, Russo, and Kang Nomograms.

Conclusion

ICL nomograms are a vital tool in helping clinicians select the right ICL size for myopic patients to optimize postoperative vault reducing risk of postoperative complications. Based on available diagnostic devices such as topography, biometry, or UBM clinicians can integrate specific nomograms into practice.

Analysis of vault prediction in phakic implantable phakic collamer lenses: manufacturer's calculator vs theoretical formulae vs clinical practice

BACKGROUND

Implantable collamer phakic (ICL) intraocular lens sizing calculations are necessary to avoid complications associated to inadequate sizing. Historically, Holladay R, Dougherty, Hernández-Matamoros, and other authors have tried to create new formulas that solve calculation problems and provide higher reliability. In addition, in recent years, the appearance of new equipment, parameters, and formulas have led to significant progress. This paper compares the sizing according to manufacturer's method and other methods.

METHODS

Forty-three eyes of 24 patients with EVO ICL implanted, with at least 1 year of follow-up, were analysed. The analysed variables were white to white (WTW), anterior chamber depth (ACD), ACW (angle-to-angle), crystalline lens rise (CLR), ICL size, vault measured at 1 week and 1 year after surgery, ICL size, and vault predicted by Nakamura-2 as well as vault size predicted by Igarashi.

RESULTS

Sizing calculation with Online Calculation and Ordering System according to WTW and ACD is a good indicator with 86% success rate. The calculation with Nakamura 2 suggests larger ICL sizes in 32.5% of cases and smaller in 18.6% of cases, while the resulting Vault according to Igarashi obtains better results without significant differences.

CONCLUSIONS

ICL sizing according WTW and ACD, using the manufacturer's algorithm, seems to be the most predictable method compared to other algorithms using other variables. The surgeon's expertise also has a high importance in the final ICL size election.

Diagnostic Techniques to Increase the Safety of Phakic Intraocular Lenses

Preoperative and postoperative diagnostics play an important role in ensuring the safety of patients with phakic intraocular lenses (pIOLs). The risk of endothelial cell loss can be addressed by regularly measuring the endothelial cell density using specular microscopy and considering the endothelial cell loss rate and the endothelial reserve in accordance with the patient's age when deciding whether to explant a pIOL. The anterior chamber morphometrics, including the anterior chamber depth and the distance between the pIOL and the endothelium, measured using Scheimpflug tomography and anterior segment optical coherence tomography (AS-OCT), can help to assess the risk of the endothelial cell loss. In patients undergoing posterior chamber pIOL implantation, accurate prediction of the vault and its postoperative measurements using AS-OCT or Scheimpflug tomography are important when assessing the risk of anterior subcapsular cataract and secondary glaucoma. Novel approaches based on ultrasound biomicroscopy and AS-OCT have been proposed to increase the vault prediction accuracy and to identify eyes in which prediction errors are more likely. Careful patient selection and regular postoperative follow-up visits can reduce the complication risk and enable early intervention if a complication occurs.

Evaluation of the Performance of Two Nomograms and Four Vault Prediction Formulas for Implantable Collamer Lens Size Selection

PURPOSE

To evaluate the performance of different nomograms and vault prediction formulas in predicting the optimal Implantable Collamer Lens (ICL; STAAR Surgical) size and vault.

METHODS

This retrospective study included 108 participants (214 eyes) who underwent ICL implantation. The efficacy of the manufacturer's nomogram, Parkhurst nomogram, NK formula, KS formula, Zhu formula, and ZZ formula was assessed by comparing the indicated ICL sizes to the postoperative vault measurements. Additionally, Bland-Altman plots and the Friedman test were used to assess the agreement and absolute error between the actual vault and predicted vault.

RESULTS

The proportions of the ideal ICL category recommended by the manufacturer's nomogram, Parkhurst nomogram, NK formula, KS formula, Zhu formula, and ZZ formula were 50.5%, 45.3%, 46.7%, 42.5%, 50.0%, and 28.5%, respectively. The mean differences between the actual vault and the predicted vault using the NK, KS, Zhu, and ZZ formulas were 144.1 ± 261.1, -19.3 ± 179.6, 70.8 ± 284.2, and 182.6 ± 361.5 μm, respectively. The predicted ICL vault tended to overestimate the actual ICL vault, particularly when choosing a larger ICL size. The KS formula shows the smallest deviation in prediction error and is least affected by variation in ICL size.

CONCLUSIONS

White-to-white distance from the Pentacam (Oculus Optikgeräte GmbH) coupled with the manufacturer's nomogram performed well for ICL size selection. Four vault prediction formulas tended to overestimate the actual ICL vault, particularly when selecting a larger ICL size. The KS formula appeared to have the least bias of the formulas. Simultaneously, vault prediction formulas need to be modified according to the ICL size. [J Refract Surg. 2023;39(7):456-461.].

The Non-uniform Distribution of Horizontal and Vertical Crystalline Lens Rise Using Optical Coherence Tomography

PURPOSE

To observe the crystalline lens rise (CLR) in horizontal and vertical orientations using anterior segment optical coherence tomography (AS-OCT).

METHODS

Non-invasive swept-source AS-OCT was used to measure the lens thickness, CLR, and angle-to-angle distance (ATA) in both the horizontal and vertical orientations. Anterior chamber depth (ACD) and horizontal white-to-white corneal diameter were obtained using the Pentacam HR (Oculus Optikgeräte GmbH). Axial length was obtained using the IOLMaster 700 (Carl Zeiss Meditec AG). The paired t test was used to analyze the difference in CLR between the two orientations. Pearson correlation analysis was performed to investigate the correlations between CLR and other ocular variables.

RESULTS

This prospective observational study comprised 99 eyes (99 patients) that underwent Visian Implantable Collamer Lens (STAAR Surgical) implantation for myopic correction. The mean CLR was 64.29 ± 168.04 and 208.09 ± 173.12 µm in the horizontal and vertical orientations, respectively. The vertical CLR (VCLR) was significantly greater than the horizontal CLR (HCLR) (P < .05). Both the HCLR and VCLR were positively correlated with lens thickness and negatively correlated with ACD (all P < .05). The difference in CLR (VCLR-HCLR) was positively correlated with the axial length and the difference in ATA between the two orientations (P < .05).

CONCLUSIONS

VCLR was greater than HCLR in most patients with myopia, especially in the longer eyes. This nonuniform distribution in CLR implied different placements of the iridocorneal angles in the horizontal and vertical orientations and should be considered for the selection of ICL size and placement position. [J Refract Surg. 2023;39(5):354-359.].

Development of an implantable collamer lens sizing model: a retrospective study using ANTERION swept-source optical coherence tomography and a literature review

BACKGROUND

Optimal sizing for phakic intraocular lens (EVO-ICL with KS-AquaPort) implantation plays an important role in preventing postoperative complications. We aimed to formulate optimal lens sizing using ocular biometric parameters measured with a Heidelberg anterior segment optical coherence tomography (AS-OCT) device.

METHODS

We retrospectively analyzed 892 eyes of 471 healthy subjects treated with an intraocular collamer lens (ICL) and assigned them to either the development (80%) or validation (20%) set. We built vault prediction models using the development set via classic linear regression methods as well as partial least squares and least absolute shrinkage and selection operator (LASSO) regression techniques. We evaluated prediction abilities based on the Bayesian information criterion (BIC) to select the best prediction model. The performance was measured using Pearson's correlation coefficient and the mean squared error (MAE) between the achieved and predicted results.

RESULTS

Measurements of aqueous depth (AQD), anterior chamber volume, anterior chamber angle (ACA) distance, spur-to-spur distance, crystalline lens thickness (LT), and white-to-white distance from ANTERION were highly associated with the ICL vault. The LASSO model using the AQD, ACA distance, and LT showed the best BIC results for postoperative ICL vault prediction. In the validation dataset, the LASSO model showed the strongest correlation (r = 0.582, P < 0.001) and the lowest MAE (104.7 μm).

CONCLUSION

This is the first study to develop a postoperative ICL vault prediction and lens-sizing model based on the ANTERION. As the measurements from ANTERION and other AS-OCT devices are not interchangeable, ANTERION may be used for optimal ICL sizing using our formula. Because our model was developed based on the East Asian population, further studies are needed to explore the role of this prediction model in different populations.

Predicting Postoperative Anterior Chamber Angle for Phakic Intraocular Lens Implantation Using Preoperative Anterior Segment Metrics

Purpose

The anterior chamber angle (ACA) is a critical factor in posterior chamber phakic intraocular lens (EVO Implantable Collamer Lens [ICL]) implantation. Herein, we predicted postoperative ACAs to select the optimal ICL size to reduce narrow ACA-related complications.

Methods

Regression models were constructed using pre-operative anterior segment optical coherence tomography metrics to predict postoperative ACAs, including trabecular-iris angles (TIAs) and scleral-spur angles (SSAs) at 500 µm and 750 µm from the scleral spur (TIA500, TIA750, SSA500, and SSA750). Data from three expert surgeons were assigned to the development (N = 430 eyes) and internal validation (N = 108 eyes) datasets. Additionally, data from a novice surgeon (N = 42 eyes) were used for external validation.

Results

Postoperative ACAs were highly predictable using the machine-learning (ML) technique (extreme gradient boosting regression [XGBoost]), with mean absolute errors (MAEs) of 4.42 degrees, 3.77 degrees, 5.25 degrees, and 4.30 degrees for TIA500, TIA750, SSA500, and SSA750, respectively, in internal validation. External validation also showed MAEs of 3.93 degrees, 3.86 degrees, 5.02 degrees, and 4.74 degrees for TIA500, TIA750, SSA500, and SSA750, respectively. Linear regression using the pre-operative anterior chamber depth, anterior chamber width, crystalline lens rise, TIA, and ICL size also exhibited good performance, with no significant difference compared with XGBoost in the validation sets.

Conclusions

We developed linear regression and ML models to predict postoperative ACAs for ICL surgery anterior segment metrics. These will prevent surgeons from overlooking the risks associated with the narrowing of the ACA.

Translational Relevance

Using the proposed algorithms, surgeons can consider the postoperative ACAs to increase surgical accuracy and safety.

Improvement in the ideal range of vault after implantable collamer lens implantation: a new vault prediction formula

Background

To derive and validate a novel vault prediction formula to improve the predictability and safety of implantable collamer lens (ICL) implantation.

Methods

Thirty-five patients (61 eyes) with previous posterior chamber intraocular lens implantation were included. Various parameters, such as horizontal-visible iris diameter (HVID), photopic pupil diameter (PPD), axial length (AL), white-to-white (WTW), anterior chamber width (ACW), angle-to-angle (ATA), crystalline lens rise (CLR), anterior chamber depth (ACD), horizontal sulcus-to-sulcus (HSTS), and ciliary sulcus angle (CSA) were measured. Vault was measured at 3 months after surgery using CASIA2 anterior segment optical coherence tomography. The formula was derived using multiple linear regression analysis and named as WH formula. It was validated in 65 patients (118 eyes) to determine the percentage of the ideal postoperative vault range and to compare the differences between the WH formula and the NK, KS, and STAAR formulas.

Results

Final ICL size, ATA, CSA, and CLR were included in the prediction formula model (adjusted R² = 0.67, p < 0.001). The achieved vault 1 month after the surgery was 556.19 μm ± 166.98 μm in the validation group, and the ideal vault range was 200-800 μm (92%). The difference between the achieved vault and that predicted using the WH formula was not statistically significant (p = 0.165), whereas the difference between the achieved vault and that predicted using the NK and KS formulas was statistically significant (p < 0.001 and p < 0.001, respectively). The 95% agreement limit range of the achieved vault and the vault predicted using the WH formula was narrower than those predicted using the NK and KS formulas (-295.20-258.82 μm).

Conclusion

This study combined the results of optical coherence tomography and ultrasound biomicroscopy measurements of the anterior segment of the eye and incorporated ciliary sulcus morphology quantification into the prediction formula. The study derived a prediction formula for vault by combining ICL size, ATA, and CLR. The derived formula was found to be superior to the currently available formulas.

Validation of the vault prediction model based on the sulcus-to-sulcus diameter and lens thickness: a 925-eye prospective study

BACKGROUND

To verify the accuracy and stability of the prediction formula based on the ciliary sulcus diameter and lens thickness and to analyse factors influencing the prediction results.

METHODS

In total, 925 eyes from 506 subjects were enrolled in this prospective study between July 1, 2020, and June 30, 2021. Subjects were divided into four seasons, each spanning three months. The target vault was set to be between 300 μm and 700 μm according the prediction formula. The actual vault was measured one month postoperatively. The Bland-Altman test, 95% confidence intervals (95% CI) and 95% limits of agreement (95% LoA) were used to evaluate the agreement between the predicted vault and the actual vault. Eyes with absolute prediction errors greater than 300 μm were further analysed.

RESULTS

The mean predicted vaults for the four seasons were 503 ± 99, 494 ± 96, 481 ± 92 and 502 ± 93 μm, while the mean actual vaults were 531 ± 189, 491 ± 179, 464 ± 179 and 529 ± 162 μm, respectively. The predicted and actual vaults of the overall subjects were 493 ± 95 and 500 ± 180 μm, respectively. Of the 925 eyes, 861 eyes (93.08%), 42 eyes (4.54%), and 22 eyes (2.38%) showed a normal vault, high vault, and low vault, respectively. Bland-Altman plots showed that the mean difference between the actual vault and predicted vault overall (± 95% LoA) was 6.43 ± 176.2 μm (-339 to 352 μm). Three UBM features may lead to large prediction errors (more than 300 μm): wide iris-ciliary angle (ICA), iris concavity and anteriorly positioned ciliary body.

CONCLUSIONS

This study demonstrated the accuracy and stability of the prediction formula through the validation of a large sample size and a long time span. Wide ICA, iris concavity and anteriorly positioned ciliary body may have an effect on vault.