34 EyeWorld Asia-Pacific | March 2025 REFRACTIVE SURGERY What’s the latest addition to the refractive surgeon’s figurative ‘toolbox’? As with many fields from marketing to medicine, it’s artificial intelligence (AI). EyeWorld spoke with several surgeons to learn more about how AI is impacting refractive surgery, as well as some other areas of the anterior segment. “The field of refractive surgery has become incredibly complex,” said Ella Faktorovich, MD. There are different types of refractive procedures and important diagnostic tools coinciding with preop screening. “How do we decide, for example, whether a patient with mild inferior corneal steepening is best treated with a corneal or lens procedure? Is the steepening consistent with keratoconus and significant enough to benefit from crosslinking prior to refractive surgery? When planning the patient’s treatment, how can we use postoperative outcomes data from other patients who underwent similar treatments to plan this patient’s treatment? AI has become essential to help us answer these questions and navigate the increasingly complex field of refractive surgery diagnostics and treatments.” by Liz Hillman, Editorial Co-Director AI Expanding In Refractive Surgery Surgical nomogram software is an example of machine-learning AI. Postoperative outcomes need to be continuously entered into the software, allowing the machine to learn, thereby updating the nomogram. After a while, a surgeon-specific nomogram is generated. The nomogram is applied to the prospective surgical patient’s refraction, and the values to be programmed into the laser are generated. Source: Ella Faktorovich, MD AI In Diagnostics To determine a patient’s suitability for refractive surgery, various ocular parameters need to be carefully measured and analyzed, Dr. Faktorovich said. “We typically use five different methods to assess corneal health—topography, tomography, epithelial thickness mapping with widefield OCT, corneal biomechanics, and aberrometry to map higher order aberrations. Diagnostic software in topography and tomography uses [rule-based] AI to benchmark each individual’s corneal characteristics against the database in the software. Tomography performed with Pentacam [Oculus], for example, generates seven different corneal indices. The device’s AI then compares these indices to the software’s database and determines the likelihood of keratoconus. If keratoconus is likely, the
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