KeratoconusDKDANCT04763785
Development of a Keratoconus Detection Algorithm by Deep Learning Analysis and Its Validation on Eyestar Images
An observational study of Keratoconus and Eye Diseases, run by Insel Gruppe AG, University Hospital Bern at 1 site in Switzerland.
Trial summary
Monocentric clinical study to develop an imaging analysis algorithm for the Eyestar 900 to identify keratoconus corneas and improve biometry for intraocular lens calculations Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Keratoconus, Eye Diseases, Cataract
- What is being tested?
- Corneal tomography with Eyestar 900, Corneal tomography with Pentacam and Biometry with IOL-Master
- Type of treatment
- Medical device
- How many people
- 4,800 participants
- Where
- 1 siteSwitzerland
- Study dates
- 11 May 2021to 1 Dec 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: retrospective part: anonymised picture-data of 4500 patients prospective part: 150 keratoconus patients and 150 healthy participants
Who may be able to join
- Patients with all stages of keratoconus
- Patients with healthy corneas
Who cannot join
- Keratoconus patients with hydrops, status following hydrops
- Patients with degenerative corneal diseases
- Patients after corneal surgery
Trial locations and contacts
1 site in 1 country.
Switzerland1 site
Universitätsklinik für Augenheilkunde, Inselspital
Bern, 3010
About this study
Monocentric clinical study to develop an imaging analysis algorithm for the Eyestar 900 to identify keratoconus corneas and improve biometry for intraocular lens calculations
Read the 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.
- Conditions
- Keratoconus, Eye Diseases, Cataract, Corneal Ectasia
- Being tested
- Corneal tomography with Eyestar 900, Corneal tomography with Pentacam, Biometry with IOL-Master, retrospective analysis, no intervention
- Keywords
- Keratoconus, Eye Diseases, Cataract, Corneal Imaging, Corneal Topography, Corneal Tomography, Corneal Ectasia
- Medical subject headings
- Keratoconus, Eye Diseases, Cataract
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Corneal tomography with Eyestar 900Device
Non-invasive corneal tomography to develop an imaging analysis algorithm for keratoconus corneas
Corneal tomography with PentacamDevice
Non-invasive corneal tomography to develop an imaging analysis algorithm for keratoconus corneas
Biometry with IOL-MasterDevice
Non-invasive biometry for presurgical intraocular lens calculation
retrospective analysis, no interventionOther
retrospective analysis of 4500 existing, fully anonymised picture data
| Study group | Role | What they receive |
|---|---|---|
| Patients with keratoconus corneas | Corneal tomography on patients with keratoconus diagnosis Receives: Device: Corneal tomography with Eyestar 900; Device: Corneal tomography with Pentacam; Device: Biometry with IOL-Master | |
| participants with healthy corneas | Corneal tomography on healthy participants Receives: Device: Corneal tomography with Eyestar 900; Device: Corneal tomography with Pentacam; Device: Biometry with IOL-Master | |
| retrospective part | fully anonymised Picture data of existing 4500 patients Receives: Other: retrospective analysis, no intervention |
What is being measured
The primary outcome is the main question the study is designed to answer.
Keratoconus identification
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.
Measured: 2.5 years
Secondary outcomes (1)
Feasibility in clinical practice
Evaluation of the feasibility (percentage of valid measurements without errors and/or problems in image aquisition) of cornea measurements in keratoconus and healthy eyes.
Measured: 2.5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted21 Feb 2021
- Study start11 May 2021
- Primary completion1 Jun 2023 (estimated)
- Study completion1 Dec 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for KeratoconusStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 4,800 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Insel Gruppe AG, University Hospital Bern
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Früh Beatrice, Prof.Dr. med., Principal investigator, Universitätsklinik für Augenheilkunde, Inselspital Bern
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04763785
- Sponsor's protocol ID
- DKDA-E900-2020
- Acronym
- DKDA
- Status last verified
- Jun 2021
- First submitted
- 14 Feb 2021
- Last updated
- 30 Sep 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 30 Sep 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of a Keratoconus Detection Algorithm by Deep Learning Analysis and Its Validation on Eyestar Images
- ClinicalTrials.gov ID
- NCT04763785
- Acronym / sponsor ID
- DKDA / DKDA-E900-2020
- Conditions
- Keratoconus, Eye Diseases, Cataract, Corneal Ectasia
- Keywords
- Keratoconus, Eye Diseases, Cataract, Corneal Imaging, Corneal Topography, Corneal Tomography, Corneal Ectasia
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 4,800 participants (estimated)
- Lead sponsor
- Insel Gruppe AG, University Hospital BernUniversity, hospital or other
- Study start
- 11 May 2021 (actual)
- Primary completion
- 1 Jun 2023 (estimated)
- Study completion
- 1 Dec 2023 (estimated)
- First posted
- 21 Feb 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Monocentric clinical study to develop an imaging analysis algorithm for the Eyestar 900 to identify keratoconus corneas and improve biometry for intraocular lens calculations
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 design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Patients with keratoconus corneas | – | Device: Corneal tomography with Eyestar 900, Device: Corneal tomography with Pentacam, Device: Biometry with IOL-MasterCorneal tomography on patients with keratoconus diagnosis |
| participants with healthy corneas | – | Device: Corneal tomography with Eyestar 900, Device: Corneal tomography with Pentacam, Device: Biometry with IOL-MasterCorneal tomography on healthy participants |
| retrospective part | – | Other: retrospective analysis, no interventionfully anonymised Picture data of existing 4500 patients |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- Study population
- retrospective part: anonymised picture-data of 4500 patients prospective part: 150 keratoconus patients and 150 healthy participants
Key inclusion criteria (2 listed)
- Patients with all stages of keratoconus
- Patients with healthy corneas
Key exclusion criteria (3 listed)
- Keratoconus patients with hydrops, status following hydrops
- Patients with degenerative corneal diseases
- Patients after corneal surgery
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Corneal tomography with Eyestar 900Non-invasive corneal tomography to develop an imaging analysis algorithm for keratoconus corneas | Device | Patients with keratoconus corneas, participants with healthy corneas |
| Corneal tomography with PentacamNon-invasive corneal tomography to develop an imaging analysis algorithm for keratoconus corneas | Device | Patients with keratoconus corneas, participants with healthy corneas |
| Biometry with IOL-MasterNon-invasive biometry for presurgical intraocular lens calculation | Device | Patients with keratoconus corneas, participants with healthy corneas |
| retrospective analysis, no interventionretrospective analysis of 4500 existing, fully anonymised picture data | Other | retrospective part |
Primary outcome
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.
1 secondary outcome
Feasibility in clinical practice
Time frame: 2.5 years
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 30 Sep 2021.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Früh Beatrice, Prof.Dr. med. principal investigator
Universitätsklinik für Augenheilkunde, Inselspital Bern
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Keratoconus and Eye Diseases, run by Insel Gruppe AG, University Hospital Bern at 1 site in Switzerland.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 30 Sep 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Switzerland. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Keratoconus identification (time frame: 2.5 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 30 Sep 2021; AzTrials last refreshed its copy on 27 Oct 2026.