Evolution and Applications of Artificial Intelligence to Cataract Surgery

• Published in: Ophthalmology science (Online) Vol. 2; no. 3; p. 100164
• Main Authors: Lindegger, Daniel Josef, Wawrzynski, James, Saleh, George Michael
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01-09-2022; Elsevier
• Subjects: Artificial intelligence; Cataract surgery; Video analysis; Cataract surgery; Video analysis; EPR; IOL; AI; NHS; Artificial intelligence
• ISSN: 2666-9145; 2666-9145
• DOI: 10.1016/j.xops.2022.100164

Despite significant recent advances in artificial intelligence (AI) technology within several ophthalmic subspecialties, AI seems to be underutilized in the diagnosis and management of cataracts. In this article, we review AI technology that may soon become central to the cataract surgical pathway, from diagnosis to completion of surgery.
This review describes recent advances in AI in the preoperative, intraoperative, and postoperative phase of cataract surgery, demonstrating its impact on the pathway and the surgical team.
A systematic search of PubMed was conducted to identify relevant publications on the topic of AI for cataract surgery. Articles of high quality and relevance to the topic were selected.
Before surgery, diagnosis and grading of cataracts through AI-based image analysis has been demonstrated in several research settings. Optimal intraocular lens (IOL) power to achieve the desired postoperative refraction can be calculated with a higher degree of accuracy using AI-based modeling compared with traditional IOL formulae. During surgery, innovative AI-based video analysis tools are in development, promoting a paradigm shift for documentation, storage, and cataloging libraries of surgical videos with applications for teaching and training, complication review, and surgical research. Situation-aware computer-assisted devices can be connected to surgical microscopes for automated video capture and cloud storage upload. Artificial intelligence-based software can provide workflow analysis, tool detection, and video segmentation for skill evaluation by the surgeon and the trainee. Mixed reality features, such as real-time intraoperative warnings, may have a role in improving surgical decision-making with the key aim of reducing complications by recognizing surgical risks in advance and alerting the operator to them. For the management of patient flow through the pathway, AI-based mathematical models generating patient referral patterns are in development, as are simulations to optimize operating room use. In the postoperative phase, AI has been shown to predict the posterior capsule status with reasonable accuracy, and can therefore improve the triage pathway in the treatment of posterior capsular opacification.
Artificial intelligence for cataract surgery will be as relevant as in other subspecialties of ophthalmology and will eventually constitute a future cornerstone for an enhanced cataract surgery pathway.