Deep Learning for Classification of Scheimpflug Corneal Tomography Images

Completed

• Conditions: Eye Diseases

• Registration Number: NCT04497207
• Lead Sponsor: Assiut University

Brief Summary

Keratoconus is a common disorder. An early diagnosis influences the disease prognosis in the affected patients and prevents postoperative complications in patients with keratoconus considering refractive surgery. Machine learning approaches have been widely used for image classification. Here, we will assess the ability of deep learning to enable high-performance image classification of the color-coded corneal maps obtained by Scheimpflug camera in patients with keratoconus, subclinical keratoconus, and normal individuals.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2020-07-30
• Study First Submitted QC: 2020-07-30
• Study First Posted: 2020-08-04
• Study Start: 2020-08-10
• Primary Completion: 2020-08-20
• Study Completion: 2020-08-25
• Status Verified: 2020-10
• Last Update Submitted: 2020-10-05
• Last Update Posted: 2020-10-06

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 1669

Inclusion Criteria

Keratoconus group:

• Presence of a central protrusion of the cornea with Fleischer ring, Vogt striae, or both by slitlamp examination.
• irregular cornea determined by distorted keratometry mires and distortion of retinoscopic red reflex or both in addition to the following topographic findings as summarized by Pińero and colleagues :
• focal steepening located in a zone of protrusion surrounded by concentrically decreasing power zones
• focal areas with diopteric (D) values >47.0D
• inferior- superior(I-S) asymmetry measured to be > 1.4 D
• Angling of the hemimeridians in an asymmetric or broken bowtie pattern with skewing of the steepest radial axis(SRAX) .

Suspicious group:

• Defined as subtle corneal tomographic changes as the aforementioned keratoconus abnormalities in the absence of slit- lamp or visual acuity changes typical of keratoconus (forme fruste keratoconus).

Normal group:

• Refractive surgery candidates
• Refractive error of less than 8.0 D sphere
• Less than 3.0 D of astigmatism
• without clinical, topographic or tomographic signs of keratoconus or suspect keratoconus.

Exclusion Criteria

• Systemic disease
• Other corneal disease such as pellucid marginal degeneration
• History of trauma
• Corneal surgery such as corneal cross- linking for progressive keratoconus.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Croppedm denoised, and resized to obtain four separate image stacks of 256×256 pixels	2 days

Trial Locations

Locations (1)

Faculty of Medicine; 🇪🇬 Assiut, Egypt