Health TrialsbyHealthPanel

Study on the Diagnostic Efficacy of ICL Selection and Prediction Depth Model Based on Eye Images

ConditionsPosterior Chamber Phakic Intraocular LensVaultDeep Neural NetworkMyopiaAnterior Chamber Angle
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18-45
SponsorSecond Affiliated Hospital of Nanchang University

About this trial

To evaluate the diagnostic efficacy of deep learning network model in implantable collamer lens selection and prediction in a multicenter cross-sectional study

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

Aged 18-45 years ;

Myopia, with or without astigmatism, annual diopter change ≤ 0.50 D for 2 consecutive years ;

Anterior chamber depth ≥ 2.80 mm ;

Corneal endothelial cell count ≥ 2000 / mm2, stable cell morphology ;

Disqualifiers

There were no other ocular diseases that significantly affected vision and / or systemic organic lesions that affected surgical recovery;

Have a history of corneal refractive surgery or intraocular surgery ;

Corneal endothelial cell count is low ;

Those with systemic diseases ;

Trial population

Patients from clinics in different eye centers across China. Each subject must with complete surgical video recording and medical records.

Trial design

Design model

Other

Time perspective

Cross-sectional

Treatments tested in this trial

  • AI diagnostic algorithm

    Diagnostic test

    The ICL procedures collected would be assessed by the algorithm. The performance of the algorithm would be assessed, including accuracy, AUC, sensitivity and specificity.

Treatment groups

326 Participants
are divided into 1 treatment group
Group A: Eyes with ICL surgeries1 intervention

Trial outcomes

Primary outcomes

1

AUROC of convolutional neural network in predicting vault after ICL surgery

The area under the receiver operating characteristic of convolutional neural network in predicting vault after ICL surgery

Time frame
Day 7
2

AUROC of convolutional neural network in predicting anterior chamber angle after ICL implantation

The area under the receiver operating characteristic of convolutional neural network in predicting anterior chamber angle after ICL implantation

Time frame
Day 7

Secondary outcomes

1

Sensitivity and specificity of convolutional neural network in predicting Vault after ICL implantation

Sensitivity and specificity of convolutional neural network in predicting Vault after ICL implantation

Time frame
Day 7
2

Sensitivity and specificity of convolutional neural network in predicting anterior chamber angle after ICL implantation

Sensitivity and specificity of convolutional neural network in predicting anterior chamber angle after ICL implantation

Time frame
Day 7

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

Second Affiliated Hospital of Nanchang University

Lead sponsor

Source ClinicalTrials.gov
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