Nir Erdinest, Dror Ben Ephraim-Noyman, Or Shmueli, David Landau, Itay Lavy, Abraham Solomon
{"title":"[KERATOCONUS: DIAGNOSIS AND INNOVATIONS].","authors":"Nir Erdinest, Dror Ben Ephraim-Noyman, Or Shmueli, David Landau, Itay Lavy, Abraham Solomon","doi":"","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>The importance of early detection of keratoconus lies in early treatment to prevent complications resulting from disease progression and in planning optimal follow-up or screening schedules for family members, considering the genetic component of the disease. In the past, with the absence of accessible, adequate imaging technology such as corneal topography to detect subtle manifestations of the disease, keratoconus was considered rare. This resulted in later detection when the disease had progressed to a more advanced, severe state, with many patients requiring corneal transplants. Currently, early detection can have significant consequences because of the possibility of early intervention, such as corneal cross-linking, which slows disease progression. Early detection of mild ectatic changes in the cornea is essential when screening candidates for refractive surgery to prevent postsurgical ectasia. In recent years, the detection of keratoconus has focused on the molecular level, such as identifying inflammatory biomarkers, and in corneal imaging. The progress in corneal imaging technology now provides detailed imaging of the epithelial and Bowman layers, which augment the ability to detect minimal changes, revealing disease development at a very early stage. Analyzing anterior corneal high-order aberrations also assists in identifying keratoconus. Corneal biomechanics evaluation likewise contributes to early keratoconus diagnosis. The latest frontier in keratoconus diagnosis is employing artificial intelligence, which has been combined in the past few years with corneal imaging devices. The following review will focus on the most current developments concerning keratoconus diagnosis, concentrating on the most novel tools and strategies.</p>","PeriodicalId":101459,"journal":{"name":"Harefuah","volume":"164 1","pages":"39-45"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Harefuah","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: The importance of early detection of keratoconus lies in early treatment to prevent complications resulting from disease progression and in planning optimal follow-up or screening schedules for family members, considering the genetic component of the disease. In the past, with the absence of accessible, adequate imaging technology such as corneal topography to detect subtle manifestations of the disease, keratoconus was considered rare. This resulted in later detection when the disease had progressed to a more advanced, severe state, with many patients requiring corneal transplants. Currently, early detection can have significant consequences because of the possibility of early intervention, such as corneal cross-linking, which slows disease progression. Early detection of mild ectatic changes in the cornea is essential when screening candidates for refractive surgery to prevent postsurgical ectasia. In recent years, the detection of keratoconus has focused on the molecular level, such as identifying inflammatory biomarkers, and in corneal imaging. The progress in corneal imaging technology now provides detailed imaging of the epithelial and Bowman layers, which augment the ability to detect minimal changes, revealing disease development at a very early stage. Analyzing anterior corneal high-order aberrations also assists in identifying keratoconus. Corneal biomechanics evaluation likewise contributes to early keratoconus diagnosis. The latest frontier in keratoconus diagnosis is employing artificial intelligence, which has been combined in the past few years with corneal imaging devices. The following review will focus on the most current developments concerning keratoconus diagnosis, concentrating on the most novel tools and strategies.