Detection of Keratoconus Progression Using Machine Learning
NCT ID: NCT06873399
Last Updated: 2025-03-12
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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ACTIVE_NOT_RECRUITING
200 participants
OBSERVATIONAL
2024-12-02
2025-05-31
Brief Summary
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KC can be categorized into different forms based on the stage of the disease. In clinical KC, there are both topographic and slit lamp findings of the disease.
The importance of corneal epithelial imaging in the diagnosis of keratoconus has been further demonstrated in several clinical studies. As new anterior segment optical coherence tomography (AS-OCT) devices provide more detailed measurements for instance of the corneal epithelium. This layer could therefore be an interesting marker for the prediction of KC progression and contribute to earlier diagnosis as well as better outcome of the disease.
The aim of this retrospective study is therefore to determine whether different topographical and volumetric data, for instance epithelial thickness maps (ETM), can be reliably used to predict the progression of KC using a machine learning algorithm.
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Detailed Description
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Conditions
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Study Design
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OTHER
RETROSPECTIVE
Study Groups
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Progressive Keratoconus
Patients with progressive keratokonus, based on a one-year change in Kmax values
MS-39
The MS-39 (Costruzione Strumenti Oftalmici, Firenze, Italy) is a device for anterior segment analysis of the eye, which combines Placido disc corneal topography and high-resolution SD-OCT. The device provides information on pachymetry, elevation, curvature, and dioptric power of both corneal surfaces. To obtain corneal topography, 22 Placido disc rings are emanated from a laser emitted diode (LED) light source at 635 nanometres (nm). The central 10 millimetres of the anterior corneal surface are covered. Epithelial thickness maps are calculated for different sectors (central, paracentral inferior/superior/nasal/temporal).
Non-progressive Keratoconus
Patients with non-progressive keratokonus, based on a one-year change in Kmax values
MS-39
The MS-39 (Costruzione Strumenti Oftalmici, Firenze, Italy) is a device for anterior segment analysis of the eye, which combines Placido disc corneal topography and high-resolution SD-OCT. The device provides information on pachymetry, elevation, curvature, and dioptric power of both corneal surfaces. To obtain corneal topography, 22 Placido disc rings are emanated from a laser emitted diode (LED) light source at 635 nanometres (nm). The central 10 millimetres of the anterior corneal surface are covered. Epithelial thickness maps are calculated for different sectors (central, paracentral inferior/superior/nasal/temporal).
Interventions
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MS-39
The MS-39 (Costruzione Strumenti Oftalmici, Firenze, Italy) is a device for anterior segment analysis of the eye, which combines Placido disc corneal topography and high-resolution SD-OCT. The device provides information on pachymetry, elevation, curvature, and dioptric power of both corneal surfaces. To obtain corneal topography, 22 Placido disc rings are emanated from a laser emitted diode (LED) light source at 635 nanometres (nm). The central 10 millimetres of the anterior corneal surface are covered. Epithelial thickness maps are calculated for different sectors (central, paracentral inferior/superior/nasal/temporal).
Eligibility Criteria
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Inclusion Criteria
o
1. Kmax \< 48 Dioptres (D): \>0.5 D per year o
2. Kmax 48.01-53 D: \>0.6 D per year o
3. Kmax 53.01-58 D: \>0.8 D per year o
4. Kmax \> 58 D: \>1.5 D per year - Non progressive group: Patients with stable KC (KC progression dependent on Kmax \< than the values described above/year)
Exclusion Criteria
* Too few measurements/too short follow-up to define progression of KC
ALL
No
Sponsors
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Vienna Institute for Research in Ocular Surgery
OTHER
Responsible Party
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Prim. Prof. Dr. Oliver Findl, MBA
Head of Department
Locations
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Vienna Institute for Research in Ocular Surgery (VIROS)
Vienna, Vienna, Austria
Countries
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Other Identifiers
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EK_24_158_VK
Identifier Type: -
Identifier Source: org_study_id
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