Predictive Performance of a Generative Model for Corneal Tomography After ICL Implantation
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In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Corneal tomography generation model after ICL surgery.
- Who it may be relevant to
- Registry conditions: ICL, Vault, Deep Learning, AI (Artificial Intelligence). Basic parameters: 18 years — 45 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Predictive Performance of a Generative Model for Corneal Tomography After Implantable Collamer Lens Implantation
Overview
To evaluate the efficacy of a corneal tomography Imaging model in predicting postoperative vault based on preoperative corneal topography in Implantable Collamer Lens (ICL) surgery.
Detailed description
Accurate vault prediction is crucial for Implantable Collamer Lens (ICL) surgery safety and efficacy. Current methods using preoperative biometrics and regression formulas show limited accuracy due to parameter variability and incomplete utilization of corneal topography data. To address this, we developed a deep learning model that predicts postoperative vault while generating anterior chamber morphology images from preoperative data, enabling personalized surgical planning.
Interventions
- Diagnostic test Corneal tomography generation model after ICL surgery
The ICL procedures collected would be assessed by the corneal tomography generation model. The performance of the model would be assessed, including accuracy,AUC, sensitivity and specificity.
Primary outcome measures
- AUROC of convolutional neural network in predicting vault after ICL surgery [Time frame: Day 7]
Secondary outcome measures (1)
- Sensitivity and specificity of convolutional neural network in predicting Vault after ICL implantation [Time frame: Day 7]
Eligibility criteria
Inclusion Criteria:(1) stable myopia (≤0.50D/year change for 2 years), (2) ACD ≥2.80mm, (3) intact corneal endothelium (≥2000 cells/mm²), and (4) no confounding ocular/systemic conditions.
Exclusion Criteria:(1) glaucoma-spectrum disorders or retinal vasculopathies, (2) prior corneal/intraocular surgery, (3) compromised corneal endothelium, (4) uncontrolled systemic diseases, and (5) pregnancy/lactation.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Other
Study locations
China · 1 center
- The Second Affiliated Hospital of Nanchang University — Nanchang
Identifiers
NCT: NCT07146737 · [2025] NO.(86)