Diagnosing glaucoma in primary eye care and the role of Artificial Intelligence applications for reducing the prevalence of undetected glaucoma in Australia

Abstract

Glaucoma is the commonest cause of irreversible blindness worldwide, with over 70% of people affected remaining undiagnosed. Early detection is crucial for halting progressive visual impairment in glaucoma patients, as there is no cure available. This narrative review aims to: identify reasons for the significant under-diagnosis of glaucoma globally, particularly in Australia, elucidate the role of primary healthcare in glaucoma diagnosis using Australian healthcare as an example, and discuss how recent advances in artificial intelligence (AI) can be implemented to improve diagnostic outcomes. Glaucoma is a prevalent disease in ageing populations and can have improved visual outcomes through appropriate treatment, making it essential for general medical practice. In countries such as Australia, New Zealand, Canada, USA, and the UK, optometrists serve as the gatekeepers for primary eye care, and glaucoma detection often falls on their shoulders. However, there is significant variation in the capacity for glaucoma diagnosis among eye professionals. Automation with Artificial Intelligence (AI) analysis of optic nerve photos can help optometrists identify high-risk changes and mitigate the challenges of image interpretation rapidly and consistently. Despite its potential, there are significant barriers and challenges to address before AI can be deployed in primary healthcare settings, including external validation, high quality real-world implementation, protection of privacy and cybersecurity, and medico-legal implications. Overall, the incorporation of AI technology in primary healthcare has the potential to reduce the global prevalence of undiagnosed glaucoma cases by improving diagnostic accuracy and efficiency. 青光眼是全球最常见的不可逆失明性疾病, 超过70%的患者尚未确诊。目前尚无治愈方法。对于青光眼患者来说, 早期诊断对于阻止视力恶化至关重要, 本综述旨在: 找出全球范围内, 特别是澳大利亚普遍存在的青光眼患病率严重被低估的原因；以澳大利亚的医疗保健为例阐明初级医疗保健在青光眼诊断中的作用；讨论如何利用最新的人工智能 (AI) 技术来提高诊断的准确性。青光眼在人口老龄化的国家普遍存在, 通过适当的治疗可以改善视力结局, 因此对于医疗实践至关重要。在澳大利亚、新西兰、加拿大、美国和英国等国家, 验光师是初级眼科保健的守护者, 青光眼检测通常由他们负责。然而, 眼科专业人员在青光眼诊断能力上存在显著差异。利用AI对眼底彩色照片的视神经进行自动化识别技术可帮助验光师快速、高诊断效能地识别高风险变化, 并降低图像解读方面的挑战。尽管具有潜力, 但在将AI应用于初级保健场景之前, 还需要解决一些重要的屏障和挑战, 包括外部验证、高质量的实际应用、保护隐私和网络安全以及医疗法律问题。总之, 将AI纳入初级保健中将通过提高诊断准确性和效率来减少未确诊的青光眼病例的全球发病率。