AI-Driven IOL Prediction Using SS-OCT Biometry

This prospective, multicenter, non-interventional observational study aims to evaluate the agreement between a novel swept-source optical coherence tomography (SS-OCT) biometer and the IOLMaster 700 for ocular biometric measurements and to develop and validate an artificial intelligence (AI)-driven intraocular lens (IOL) power prediction model. The primary research questions are: Does the novel SS-OCT biometer provide ocular biometric measurements that are comparable to those obtained using the IOLMaster 700? Can an AI-driven IOL power prediction model developed from multicenter biometric, imaging, surgical, and postoperative refractive data improve the accuracy of postoperative refractive prediction? Adult patients with age-related cataract who are scheduled to undergo routine phacoemulsification with posterior chamber IOL implantation will be consecutively recruited from participating study centers. Participants will undergo routine preoperative clinical assessments together with additional non-contact biometric measurements using the novel SS-OCT biometer before cataract surgery. Cataract surgery and postoperative care will follow standard clinical practice and will not be influenced by the study. Postoperative refractive and visual outcomes at approximately one month after surgery will be collected for analysis. The AI model and research device measurements will be used for research purposes only and will not be used to guide clinical decision-making during the study.