Detection of Keratoconus Progression Using Machine Learning

Vienna Institute for Research in Ocular Surgery

Status: Active, not recruiting

Conditions: Keratoconus; Machine Learning

Treatments: Diagnostic Test: MS-39

Study type: Observational

Funder types: Other

Identifiers

NCT06873399

EK_24_158_VK

Details and patient eligibility

About

Keratoconus (KC) is a bilateral ocular disease characterized by progressive thinning and steepening of the cornea, usually in its inferotemporal region. The disease often occurs asymmetrically as one eye is more severely affected by the condition. The changes underlying KC lead to the generation of irregular astigmatism resulting in diminished visual acuity of the patients and can even lead to axial corneal scarring in advanced stages. The disease usually occurs in the second or third decade of life, but can develop at any age. KC is a complex condition involving environmental factors such as age, eye rubbing, contact lens use, atopy, sun exposure, hormones, toxins, as well as a genetic component. However, how these factors contribute to the disease is still unknown and intraindividual differences might exist.

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.

Enrollment: 200 estimated patients

Sex: All

Volunteers: No Healthy Volunteers

Inclusion criteria

• Patients with KC progression as defined dependent on Kmax/year:

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

• Relevant other ophthalmic diseases that are likely to influence the measurement outcome like corneal scars or epithelial dystrophies
• Too few measurements/too short follow-up to define progression of KC

Trial design

200 participants in 2 patient groups

Progressive Keratoconus

Description:

Patients with progressive keratokonus, based on a one-year change in Kmax values

Treatment:

Diagnostic Test: MS-39

Non-progressive Keratoconus

Description:

Patients with non-progressive keratokonus, based on a one-year change in Kmax values

Treatment:

Diagnostic Test: MS-39