Diagnostic Efficacy of CNN in Predicting Intraoperative Complications and Postoperative Outcomes in SMILE

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

1250 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-06-15

Study Completion Date

2025-12-31

Brief Summary

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To evaluate the diagnostic efficiency of the neural network in predicting complications of Small Incision Lenticule Extraction in a multi-center cross-sectional study.

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Detailed Description

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The primary cause of global visual impairment currently is refractive error, and Small Incision Lenticule Extraction (SMILE) using femtosecond laser for corneal stromal lenticule extraction can alter the refractive power. However, complications such as opaque bubble layer (OBL), negative pressure detachment, and black spots may arise during the SMILE laser scanning process due to individual differences in corneal characteristics, significantly affecting the normal course of surgery and postoperative recovery. Experienced docters can often predict intraoperative complications based on scan images, patient cooperation, and other factors, but the learning curve is relatively long. At present, artificial intelligence has achieved the accuracy comparable to human physicians in the interpretation of medical imaging of many different diseases.Previously, we have trained a deep convolutional neural network for predicting intraoperative complications in SMILE procedures. The current multi-center study is designed to evaluate the efficacy of the convolutional neural network based algorithm in predicting intraoperative complications and to assess its utility in the real world.

Conditions

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Deep Convolutional Neural Network Small-incision Lenticule Extraction (SMILE) Surgery Intraoperative Complications Postoperative Outcomes

Study Design

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Observational Model Type

OTHER

Study Time Perspective

CROSS_SECTIONAL

Study Groups

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Eyes with SMILE surgeries

Eyes with SMILE surgeries which were performed by surgeons with experiences.

AI diagnostic algorithm

Intervention Type DIAGNOSTIC_TEST

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

Interventions

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AI diagnostic algorithm

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

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* A condition in which the spherical equivalent refractive error of an eye is ≤-0.50 D when ocular accommodation is relaxed;
* Age ≥18 years;
* Spherical equivalent (SE) ≥-10.0D;
* Corrected distance visual acuity (CDVA) ≥16/20;
* Stable myopia for at least 2 years;
* No contact lenses wearing for at least 2 weeks.

Exclusion Criteria

* The presence or history of eye conditions other than myopia and astigmatism, such as keratoconus or external eye injury;
* A history of eye surgery;
* The presence or history of systemic diseases.

Minimum Eligible Age

18 Years

Maximum Eligible Age

45 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes