Diagnostic Efficacy of Convolutional Neural Network Based Algorithm in Predicting Intraoperative Complications and Postoperative Outcomes in Small Incision Lenticule Extraction
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 1,250
- 试验地点
- 1
- 主要终点
- AUROC of convolutional neural network in predicting progressive suction loss
研究概览
简要总结
To evaluate the diagnostic efficiency of the neural network in predicting complications of Small Incision Lenticule Extraction in a multi-center cross-sectional study.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Cross Sectional
入排标准
- 年龄范围
- 18 Years 至 45 Years（Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •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.
排除标准
- •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.
研究组 & 干预措施
Eyes with SMILE surgeries
Eyes with SMILE surgeries which were performed by surgeons with experiences.
干预措施: AI diagnostic algorithm (Diagnostic Test)
结局指标
主要结局
AUROC of convolutional neural network in predicting progressive suction loss
时间窗: Day 0
The area under the receiver operating characteristic of convolutional neural network in predicting progressive suction loss during the SMILE surgeries
AUROC of convolutional neural network in predicting effective optical zone
时间窗: Day 7
The area under the receiver operating characteristic of convolutional neural network in predicting effective optical zone after the SMILE surgeries
AUROC of convolutional neural network in predicting OBL area
时间窗: Day 0
The area under the receiver operating characteristic of convolutional neural network in predicting opaque bubble layer area during the SMILE surgeries
AUROC of convolutional neural network in predicting postoperative refractive error
时间窗: Day 7
The area under the receiver operating characteristic of convolutional neural network in predicting refractive error after the SMILE surgeries
AUROC of convolutional neural network in predicting postoperative central corneal thickness
时间窗: Day 7
The area under the receiver operating characteristic of convolutional neural network in predicting central corneal thickness after the SMILE surgeries
次要结局
- Sensitivity and specificity of convolutional neural network in predicting OBL area(Day 0)
- Sensitivity and specificity of convolutional neural network in predicting progressive suction loss(Day 0)
- Sensitivity and specificity of convolutional neural network in predicting effective optical zone(Day 7, Day 30, Day 90)
研究者
Jian Xiong
Associate research fellow; Attending physician
Second Affiliated Hospital of Nanchang University