51 EyeWorld Asia-Pacific | December 2024 NEWS & OPINION Myopia – A Global Public Health Issue Myopia is now recognised as a growing global health issue - over 2 billion people worldwide have myopia, which is expected to rise to almost 5 billion by 2050.1 The rising incidence of myopia amongst schoolchildren is exacerbated by reduced outdoor time and more screen time indoors from not only in Asia, but worldwide. Progression to high myopia (HM) is associated with irreversible, sight-threatening complications such as myopic macular degeneration (MMD) and myopia-related optic neuropathy. The health burden and economic impact of myopia and its complications are exponentially increasing, with a global cost of myopia care projected to rise to USD$870 billion by 2050.2 As most cases of myopia develop during childhood, myopia control interventions are only effective if they are instituted early and appropriately.3 Thus, myopia control strategies should include early detection of children with myopia, identification of children at higher risk of myopia progression; and timely, personalised intervention to prevent progression in such ‘high-risk’ children.4 Environmental and behavioural modifications, such as increasing outdoor time and reducing indoor near work or screen time, remain essential strategies. In addition, numerous myopia control interventions, such as atropine eye drops, specialised contact lenses and designed spectacles have been shown to effectively slow the progression of myopia.5 As axial elongation from myopia is irreversible, adults with HM are at risk of developing pathologic myopia (PM) and other myopia-related complications. This includes increased risk of developing early onset cataracts, retinal detachment and peripheral retinal degeneration. Unfortunately, there are limited treatment options for complications associated with PM – such as posterior staphyloma, MMD or myopia-associated optic neuropathy. Role of Artificial Intelligence in Myopia Management Artificial intelligence (AI) is emerging as a potential adjunctive tool to aid clinicians in the early detection and management of myopia.6, 7 These algorithms could be used to support various myopia control strategies: (1) Detection – facilitating rapid, scalable evaluation of myopia and/ or its complications; (2) Prediction – prognosticate at risk children or individuals who are more likely to develop HM or PM; (3) Response – determining which individuals would respond to the various treatments available, allowing for personalised myopia management.8 For example, we previously described using a single, baseline fundus image alone, algorithms with >90% predictive performance that could predict the development of high myopia 5 years later, in a multi-ethnic group of schoolchildren aged between 6 to 12 years old. This has the potential to be implemented into community or schoolbased screening programs to identify at-risk children for further assessment and intervention if required.8 by Marcus Ang, MD Role of Artificial Intelligence in Myopia Control
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