Intelligent Evaluation and Supervision of Cataract Surgery

Cataract Clinical Trial

Official title:

Intelligent Evaluation and Supervision of Cataract Surgery

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT05260775
• Other study ID #: CS-2022
• Status: Completed
• Start date: January 1, 2019
• Est. completion date: December 30, 2021

Study information

• Verified date: February 2022
• Source: Sun Yat-sen University
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Research purpose: intelligent identification and evaluation of cataract surgery steps Research methods: A total of 9 items (such as gender, age, visual acuity, etc.) were extracted from the surgical videos of senile cataract patients and the clinical data recorded by the electronic medical record system. The machine learning algorithm 3D-CNN was applied to identify the 11 steps in cataract surgery and the pictures (blank pictures) without instrument manipulation on the eyeball during the operation. Six key cataract surgery steps were scored using deep learning algorithms (probability smoothing window and softmax). We employ precision, precision, recall, and F1-score to evaluate the model's performance for recognizing surgical steps. To evaluate the reliability of the model's scoring of surgical steps, we used a human-machine comparison method to calculate the agreement (kappa value) between machine and expert scores.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 344
• Est. completion date: December 30, 2021
• Est. primary completion date: September 30, 2021
• Gender: All
• Age group: 50 Years to 100 Years

Eligibility

Inclusion Criteria:

-Videos of phacoemulsification and IOL implantation for senile cataracts will be included

Exclusion Criteria:

-The peak signal-to-noise ratio (PSNR) is utilized to assess whether a video was blurred. If the PSNR of a video was less than 20 decibels (dBs), the whole video was discarded.

Related Conditions & MeSH terms

• Cataract

Intervention

Other:
• Evaluation test: cataract surgery steps
The development datasets were used to train the deep learning model. The validation and test group were used to optimize hyperparameters

Locations

Country	Name	City	State
China	Zhognshan Ophthalmic Center, Sun Yat-sen University	Guangzhou	Guangdong

Sponsors (1)

Lead Sponsor	Collaborator
Sun Yat-sen University

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Accuracy	The investigators will calculate accuracy of deep learning system and compare this index between deep learning system and human doctors	baseline
Secondary	kappa	Cohen's kappa coefficient was calculated to assess the agreement between the grades given by human doctors and DeepSurgery	baseline