Ignite Creation Date:
2024-05-06 @ 3:48 PM
Last Modification Date:
2024-10-26 @ 1:57 PM
Study NCT ID:
NCT04763785
Status:
UNKNOWN
Last Update Posted:
2021-09-30
First Post:
2021-02-14
Brief Title:
Development of a Keratoconus Detection Algorithm by Deep Learning Analysis and Its Validation on Eyestar Images
Sponsor:
Insel Gruppe AG University Hospital Bern
Organization:
Insel Gruppe AG University Hospital Bern
Study Overview
Official Title:
Development of a Keratoconus Detection Algorithm by Deep Learning Analysis and Its Validation on Eyestar Images
Status:
UNKNOWN
Status Verified Date:
2021-06
Last Known Status:
ACTIVE_NOT_RECRUITING
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
DKDA
Brief 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
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
The Eyestar 900 is a swept-source OCT biometer and has the potential to be used for early keratoconus identification and progression analysis
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None