NCT05260775

Brief 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.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
344

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started Jan 2019

Typical duration for all trials

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

January 1, 2019

Completed
2.7 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

September 30, 2021

Completed
3 months until next milestone

Study Completion

Last participant's last visit for all outcomes

December 30, 2021

Completed
2 months until next milestone

First Submitted

Initial submission to the registry

February 27, 2022

Completed
3 days until next milestone

First Posted

Study publicly available on registry

March 2, 2022

Completed
Last Updated

March 2, 2022

Status Verified

February 1, 2022

Enrollment Period

2.7 years

First QC Date

February 27, 2022

Last Update Submit

February 27, 2022

Conditions

Cataract

Keywords

cataract surgery

Outcome Measures

Primary Outcomes (1)

  • Accuracy

    The investigators will calculate accuracy of deep learning system and compare this index between deep learning system and human doctors

    baseline

Secondary Outcomes (1)

  • kappa

    baseline

Study Arms (3)

Development Dataset

12 cataract surgery steps including(1) main incision formation, (2) side incision formation, (3) ophthalmic viscoelastic device (OVD) injection, (4) capsulorrhexis formation, (5) hydrodissection, (6) phaco, (7) cortical material removal, (8) intraocular lens (IOL) implantation, (9) OVD removal, (10) IOL centration and (11) wound closure through corneal hydration, and (12) idle phases.

Other: Evaluation test: cataract surgery steps

Validation Dataset

12 cataract surgery steps including(1) main incision formation, (2) side incision formation, (3) ophthalmic viscoelastic device (OVD) injection, (4) capsulorrhexis formation, (5) hydrodissection, (6) phaco, (7) cortical material removal, (8) intraocular lens (IOL) implantation, (9) OVD removal, (10) IOL centration and (11) wound closure through corneal hydration, and (12) idle phases.

Other: Evaluation test: cataract surgery steps

Test Dataset

12 cataract surgery steps including(1) main incision formation, (2) side incision formation, (3) ophthalmic viscoelastic device (OVD) injection, (4) capsulorrhexis formation, (5) hydrodissection, (6) phaco, (7) cortical material removal, (8) intraocular lens (IOL) implantation, (9) OVD removal, (10) IOL centration and (11) wound closure through corneal hydration, and (12) idle phases.

Other: Evaluation test: cataract surgery steps

Interventions

Evaluation test: cataract surgery stepsOTHER

The development datasets were used to train the deep learning model. The validation and test group were used to optimize hyperparameters

Development DatasetTest DatasetValidation Dataset

Eligibility Criteria

Age50 Years - 100 Years
Sexall
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodProbability Sample
Study Population

Participants who had senile cataracts and phacoemulsification and IOL implantation in the Zhongshan Ophthalmic Centre (ZOC, Guangzhou, Guangdong, China) and Shenzhen Eye Hospital (Shenzhen, Guangdong, China)

You may qualify if:

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

You may not qualify if:

  • 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.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Zhognshan Ophthalmic Center, Sun Yat-sen University

Guangzhou, Guangdong, 510060, China

Location

MeSH Terms

Conditions

Cataract

Condition Hierarchy (Ancestors)

Lens DiseasesEye Diseases

Study Officials

  • Yizhi Liu, M.D., Ph.D.

    Zhongshan Ophthalmic Center, Sun Yat-sen University

    STUDY CHAIR

Study Design

Study Type
observational
Observational Model
OTHER
Time Perspective
RETROSPECTIVE
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
principal investigator

Study Record Dates

First Submitted

February 27, 2022

First Posted

March 2, 2022

Study Start

January 1, 2019

Primary Completion

September 30, 2021

Study Completion

December 30, 2021

Last Updated

March 2, 2022

Record last verified: 2022-02

Locations

CN(1)