Development of a Keratoconus Detection Algorithm by Deep Learning Analysis and Its Validation on Eyestar Images (DKDA)

September 29, 2021 updated by: University Hospital Inselspital, Berne
Monocentric clinical study to develop an imaging analysis algorithm for the Eyestar 900 to identify keratoconus corneas and improve biometry for intraocular lens calculations

Study Overview

Status

Active, not recruiting

Conditions

Intervention / Treatment

Detailed Description

Keratoconus is a progressive corneal ectatic disorder, characterised by thinning, protrusion and irregularity. Corneal imaging is crucial in keratoconus detection and progression analysis. Detection of keratoconus in early stages is important and has therapeutic consequence, whether to plan a surgical intervention or calculating an intraocular lens, before cataract surgery, as standard lens calculation techniques may lead to wrong results in patients with a keratoconus.

The Eyestar 900 is a swept-source OCT biometer and has the potential to be used for early keratoconus identification and progression analysis.

Study Type

Observational

Enrollment (Anticipated)

4800

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Switzerland
      • Bern, Switzerland, 3010
        • Universitatsklinik fur Augenheilkunde, Inselspital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

retrospective part: anonymised picture-data of 4500 patients prospective part: 150 keratoconus patients and 150 healthy participants

Description

Inclusion Criteria:

  1. Patients with all stages of keratoconus
  2. Patients with healthy corneas

Exclusion Criteria:

  1. Keratoconus patients with hydrops, status following hydrops
  2. Patients with degenerative corneal diseases
  3. Patients after corneal surgery

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Cohort
  • Time Perspectives: Prospective

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Patients with keratoconus corneas
Corneal tomography on patients with keratoconus diagnosis
Device: Corneal tomography with Eyestar 900
Non-invasive corneal tomography to develop an imaging analysis algorithm for keratoconus corneas
Device: Corneal tomography with Pentacam
Non-invasive corneal tomography to develop an imaging analysis algorithm for keratoconus corneas
Device: Biometry with IOL-Master
Non-invasive biometry for presurgical intraocular lens calculation
participants with healthy corneas
Corneal tomography on healthy participants
Device: Corneal tomography with Eyestar 900
Non-invasive corneal tomography to develop an imaging analysis algorithm for keratoconus corneas
Device: Corneal tomography with Pentacam
Non-invasive corneal tomography to develop an imaging analysis algorithm for keratoconus corneas
Device: Biometry with IOL-Master
Non-invasive biometry for presurgical intraocular lens calculation
retrospective part
fully anonymised Picture data of existing 4500 patients
Other: retrospective analysis, no intervention
retrospective analysis of 4500 existing, fully anonymised picture data

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Keratoconus identification
Time Frame: 2.5 years
Classification accuracy of the keratoconus identification algorithm for the Eyestar device in comparison to the gold standard (Belin-Ambrosio Enhanced Extasia Deviation Index) BAD_D in Pentacam images.
2.5 years

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Feasibility in clinical practice
Time Frame: 2.5 years
Evaluation of the feasibility (percentage of valid measurements without errors and/or problems in image aquisition) of cornea measurements in keratoconus and healthy eyes.
2.5 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

University Hospital Inselspital, Berne

Investigators

  • Principal Investigator: Früh Beatrice, Prof.Dr. med., Universitätsklinik für Augenheilkunde, Inselspital Bern

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

May 11, 2021

Primary Completion (Anticipated)

June 1, 2023

Study Completion (Anticipated)

December 1, 2023

Study Registration Dates

First Submitted

February 14, 2021

First Submitted That Met QC Criteria

February 18, 2021

First Posted (Actual)

February 21, 2021

Study Record Updates

Last Update Posted (Actual)

September 30, 2021

Last Update Submitted That Met QC Criteria

September 29, 2021

Last Verified

June 1, 2021

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • DKDA-E900-2020

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

No

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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