Updates on Keratoconus Diagnosis Publisher



Mohammadpour M¹ ; Heidari Z^{2, 3} Show Affiliations
Source: Keratoconus: Optical and Surgical Management Published:2024

Abstract

This chapter provides a comprehensive overview of advances in the detection of keratoconus (KC), which is characterized by corneal thinning and steepening. Detection of KC, particularly in its early stages when clinical signs are subtle, is challenging. Recent advances in corneal imaging technologies, such as topography, tomography, aberrometry, and biomechanics have revolutionized the diagnosis of KC. In addition, the integration of AI algorithms into these imaging modalities has shown promising results in improving diagnostic accuracy and efficiency. This chapter focuses on the critical role of corneal imaging indices derived from advanced diagnostic modalities, providing diagnostic criteria for KC, subclinical KC (SKC), and normal corneas. A surgical algorithm for different stages of KC is also presented. Key indices, including the posterior Sirius symmetry index, the Pentacam inferior-superior difference, and the Random Forest index, demonstrate high performances in detecting SKC. Wavefront parameters such as the anterior Baiocchi–Calossi–Versaci index and the vertical coma show high diagnostic accuracy for SKC. Evaluation of integrated indices based on AI analysis shows high agreement with expert opinion, particularly for Sirius Phoenix, Belin–Ambrosio enhanced ectasia total deviation, Pentacam topographical keratoconus classification, and the OPD-SCAN III Corneal Navigator. In addition, central corneal thickness was found to be highly discriminative in distinguishing between mild and severe KC from normal eyes based on analysis of optical coherence topography data. The inferior and inferotemporal sectors of the cornea show significant thickness changes in keratoconic corneas, with central corneal stromal thinning serving as the most sensitive diagnostic index for early detection of SKC. In a systematic review and meta-analysis, we compared the different corneal imaging modalities using AI for the early detection of KC, and found that simultaneous Scheimpflug and Placido corneal imaging methods showed high diagnostic accuracy. Overall, this chapter highlights the evolving landscape of KC diagnosis and emphasizes the key role of advanced imaging techniques and AI-driven approaches in overcoming diagnostic challenges and improving patient outcomes. © 2025 selection and editorial matter, Mehrdad Mohammadpour and Masoud Khorrami-Nejad; individual chapters, the contributors.