Evaluating a deep learning model for selecting implantable collamer lenses using eye images

Diagnostic Efficacy of Deep Neural Network Algorithm Based on Preoperative Scheimpflug-based Anterior Segment Image for Implantable Collamer Lens Selection and Prediction

This study is testing a new computer program that uses eye images to help doctors choose the best lens for people with nearsightedness.

Quick facts

• Study type: Observational
• Enrollment: 326 (estimated)
• Ages: 18 Years to 45 Years
• Sex: All
• Sponsor: Second Affiliated Hospital of Nanchang University (Academic / other)
• Locations: 1 site (Nanchang, Jiangxi)
• Trial ID: NCT06669728 on ClinicalTrials.gov

What this trial studies

This observational study aims to assess the diagnostic efficacy of a deep learning network model in selecting and predicting the appropriate implantable collamer lens (ICL) for myopia correction. By utilizing eye images, the study seeks to optimize the selection process for ICL design, which is often complicated by varying biological parameters. The research will be conducted across multiple centers and aims to enhance the accuracy, safety, and predictability of ICL implantation, ultimately assisting physicians in their decision-making process.

Who should consider this trial

Good fit: Ideal candidates for this study are individuals aged 18-45 with myopia and stable vision parameters.

Not a fit: Patients with a history of corneal refractive surgery or those with systemic diseases may not benefit from this study.

Why it matters

Potential benefit: If successful, this study could significantly improve the precision of ICL selection, leading to better surgical outcomes for patients with myopia.

How similar studies have performed: While the use of deep learning in medical diagnostics is gaining traction, this specific application for ICL selection is relatively novel and has not been extensively tested in prior studies.

Eligibility criteria

Inclusion Criteria:

1. Aged 18-45 years ;
2. Myopia, with or without astigmatism, annual diopter change ≤ 0.50 D for 2 consecutive years ;
3. Anterior chamber depth ≥ 2.80 mm ;
4. Corneal endothelial cell count ≥ 2000 / mm2, stable cell morphology ;
5. There were no other ocular diseases that significantly affected vision and / or systemic organic lesions that affected surgical recovery.

Exclusion Criteria:

1. There were no other ocular diseases that significantly affected vision and / or systemic organic lesions that affected surgical recovery;
2. Have a history of corneal refractive surgery or intraocular surgery ;
3. Corneal endothelial cell count is low ;
4. Those with systemic diseases ;
5. Lactating or pregnant women.

Where this trial is running

Nanchang, Jiangxi

• The Second Affiliated Hospital of Nanchang University — Nanchang, Jiangxi, China (Recruiting)

Study contacts

• Study coordinator: Jian Xiong doctor

Conditions Posterior Chamber Phakic Intraocular Lens; Vault; Deep Neural Network; Myopia; Anterior Chamber Angle