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Screening for subclinical keratoconus

Oman Journal of Ophthalmology
Medknow Publications
Publication Date
DOI: 10.4103/0974-620x.111891
  • Editorial Commentary
  • Computer Science
  • Medicine


Identification of subclinical keratoconus (KC) is a primary concern when screening patients for refractive surgery as performing laser-assisted in situ keratomileusis on undiagnosed KC has been identified as the leading cause of ectasia after refractive surgery. Although clinical diagnosis of advanced KC is relatively easy to determine with biomicroscopic and keratometric data, it is rather complicated to rule out subclinical KC before surgery. With improving technology for corneal topography, many methods have been proposed for discriminating between corneas with subclinical KC and a normal cornea.[12] However, recognizing subclinical KC is difficult as there is a lack of defined threshold criteria to define this entity. There is still a persistent ambiguity regarding the exact definition of a KC suspect (KCS) and there are no widely accepted criteria to categorize an eye as subclinical KC.[34] Besides, several terms have also been used to describe this condition, including subclinical KC, KCS, and forme fruste KC. At the outset, the term KCS was introduced to describe corneal curvature data that the clinician considered high risk for progression to KC based solely on subjective impression. With the evolution of a number of quantitative videokeratography-derived indices, a more reproducible way of quantifying KC and its early phenotypes developed easing the complexity of proper classification. In the past, most classification criteria for KC were based on anterior corneal curvature data derived from corneal topography.[56] Recently, Scheimpflug cameras and slit scanning corneal technology have enabled analysis, not only of the anterior, but also of the posterior corneal curvature and corneal thickness. These measurements are presently being used in the formulation of new algorithms for the diagnosis of KC and in the creation of builtin softwares that are capable of categorizing cornea as normal or as a KCS. An example of this is the new software adaptation to the Pentacam Scheimpflug Tomography (Oculus,

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