AI (Artificial Intelligence), Deep Learning, ICL, Vault
Conditions
Keywords
Implantable Collamer Lens (ICL) implantation surgery, Corneal tomography, vault, Artificial Intelligence, Deep Learning
Brief summary
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_TESTCorneal 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.
Sponsors
Second Affiliated Hospital of Nanchang University
Study design
Observational model
OTHER
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Age
18 Years to 45 Years
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| AUROC of convolutional neural network in predicting vault after ICL surgery | Day 7 | The area under the receiver operating characteristic of convolutional neural network in predicting vault after ICL surgery |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Sensitivity and specificity of convolutional neural network in predicting Vault after ICL implantation | Day 7 | Sensitivity and specificity of convolutional neural network in predicting Vault after ICL implantation |
Countries
China
Contacts
Primary ContactFu F Gui
Outcome results
None listed