ArticleClinical ophthalmology (Auckland, N.Z.)2026
Retrospective Validation of an AI Based Tool for Vault Prediction After Implantable Collamer Lens Surgery for High Myopia.
Article in Clinical ophthalmology (Auckland, N.Z.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Purpose: Our study evaluated a cohort of patients who previously underwent EVO Implantable Collamer Lens (ICL) implantation to assess the retrospective performance of the ICLGuru™ artificial intelligence (AI) sizing tool in predicting postoperative vault. Additionally, biometric factors associated with vault prediction error were identified. Methods: This retrospective single-center study included 104 eyes from 56 patients who underwent EVO V4c or V5 ICL implantation between May 2023 and June 2025. Preoperative ultrasound biomicroscopy (UBM) images, from patients who had already undergone ICL surgery, were retrospectively analyzed using ICLGuru to generate predicted postoperative vaults. Actual postoperative vault was measured at 1-, 3-, or 6-month follow-up visits, with 3-month measurements preferentially included for analysis. Mixed-effects regression models were used to evaluate associations between biometric variables and vault prediction error. Results: Mean absolute error was 135 ± 110 µm, indicating a tendency for ICLGuru to overestimate postoperative vault ( Conclusion: ICLGuru demonstrated useful postoperative vault predictions with performance comparable to existing machine learning and UBM-based nomograms, though it appeared to overestimate longer term vault in our cohort. The tool may be valuable in identifying eyes at risk for excessive vault. aRISE and iridocorneal angle were significant predictors of vault prediction error, supporting their importance in future ICL sizing models.
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