Diagnosing glaucoma remains a complex and evolving challenge, despite substantial research contributions on the topic annually. Several new tools and technologies have emerged in recent years, advancing diagnostic capabilities and aiding clinicians in assessing glaucoma progression and risk more accurately. This article will review some of the most promising recent developments in glaucoma diagnostics, focusing on advancements in IOP measurement, ocular imaging techniques and the application of artificial intelligence (AI) in the field.
Advances in IOP measurement
IOP remains one of the most important and modifiable risk factors for glaucoma progression, with innovations in its measurement focusing on continuous, patient-friendly solutions. Traditional Goldmann applanation tonometry remains the clinical gold standard for IOP measurement, but it only provides a single, in-office reading. Recent advances emphasize continuous and ambulatory monitoring to capture IOP fluctuations over time, which may better reflect the true IOP profile and risk in patients.
Contact lens sensors
The Triggerfish Sensor (Sensimed SA) represents a novel approach to IOP monitoring through a wearable contact lens sensor. This device allows indirect, 24-hour IOP monitoring by capturing minute changes in corneal curvature as a surrogate for true IOP changes within the eye. This continuous data provides insights into IOP variability that may otherwise go undetected during routine, single-time-point measurements.
Implantable sensors
Eyemate-IO (Implandata Ophthalmic Products) offers an implanted sensor for direct, true IOP monitoring. Typically implanted during cataract surgery in the ciliary sulcus, this device provides on-demand, real-time IOP data, which patients can transmit to their physicians. This approach is particularly promising for high-risk patients needing close monitoring or those with known IOP variability. A second version has been designed for the suprachoroidal space (Eyemate-SC). Neither version of the device is FDA approved yet.
Home-based tonometry
The iCare HOME (Icare USA) tonometer is a portable version of the clinic rebound tonometer that allows patients to measure their own IOP, on demand, in any location. This device provides patients the ability to track their IOP, offering real-time data for physicians to analyze. This approach fosters a more personalized glaucoma management approach, empowering patients and enabling more precise control of IOP fluctuations outside the clinic. These tonometers are available for rent or purchase in the United States with physician approval.
The staff, technicians role in diagnostics
Health-care staff and technicians are crucial in ensuring accurate and efficient glaucoma diagnostics with advanced technologies. They must be trained to properly handle and maintain advanced equipment and ensure proper application. Building a multidisciplinary approach with well-trained technicians and knowledgeable support staff helps ensure that new diagnostic advancements translate effectively into improved patient outcomes.
Innovations in ocular imaging
While optical coherence tomography (OCT) has been a staple in glaucoma diagnosis since its introduction nearly two decades ago, recent improvements have primarily focused on refining OCT image analysis. These advancements offer clinicians deeper insights into retinal structure and function, facilitating earlier and more accurate glaucoma diagnosis.1
OCTA
Optical coherence tomography angiography (OCTA) is a non-invasive imaging technique that visualizes retinal blood flow, potentially highlighting microvascular changes that have been linked to glaucoma. OCTA has demonstrated promise in detecting early glaucoma-related changes in retinal microvasculature, although its exact role in routine glaucoma diagnostics remains under evaluation.
Polarization-sensitive and visible-light OCT
Emerging forms of OCT, such as polarization-sensitive OCT and visible-light OCT, provide enhanced detail on specific retinal layers and structural changes. Polarization-sensitive OCT, for example, enhances the detection of nerve fiber layer alterations, which are significant in glaucoma. Visible-light OCT offers improved imaging resolution, potentially allowing for earlier detection of glaucoma-related structural damage.
Adaptive optics
Adaptive optics technology compensates for optical aberrations, allowing for visualization of retinal cells at the cellular level. Applied to OCT, adaptive optics can potentially improve the detection of subtle retinal ganglion cell layer changes before significant glaucomatous damage occurs, paving the way for even earlier diagnosis.
AI in glaucoma diagnostics
AI applications in glaucoma diagnostics are burgeoning, particularly in the realms of image analysis, disease prediction and risk stratification. AI holds promise for refining the detection of subtle disease indicators, predicting progression and personalizing management.2
Image segmentation and quantification
AI-based image segmentation algorithms improve the analysis of OCT images by delineating retinal layers and identifying early glaucomatous changes with high precision. Automated quantification of retinal nerve fiber layer (RNFL) thickness and ganglion cell complex damage supports clinicians in tracking disease progression more accurately and objectively.
Glaucoma prediction models
AI has shown potential in developing predictive models for glaucoma, especially in high-risk populations. By analyzing large datasets of patient demographics, clinical history, and imaging findings, AI-driven models can help identify patients likely to develop glaucoma, facilitating early intervention and potentially reducing the incidence of vision loss.
Fundus image analysis
Traditional fundus photography continues to play a vital role in glaucoma diagnosis. A promising advancement in this area is RNFL Optical Texture Analysis, which utilizes machine learning algorithms to identify subtle nerve fiber layer texture changes indicative of early glaucoma. This technique could provide a non-invasive, cost-effective tool for glaucoma screening, particularly in resource-limited settings.
Future of glaucoma diagnostics
Despite the advancements mentioned, several of these emerging technologies and approaches are still in the early stages of clinical validation. Research continues to integrate multiple diagnostic modalities, such as combining IOP measurement data with advanced OCT and fundus imaging analyses, for a more comprehensive risk assessment. Additionally, hybrid AI models that combine image data with clinical parameters are being explored to provide personalized, actionable insights into patient-specific glaucoma risk and progression.
The convergence of these innovations — particularly AI integration, continuous and at-home IOP monitoring, and refined imaging techniques — represents a significant step toward earlier, more accurate glaucoma diagnosis and personalized treatment strategies. As these technologies become more accessible and affordable, the hope is that they will reduce the global burden of glaucoma-related vision loss. OP
References
1. Lommatzsch C, van Oterendorp C. Current Status and Future Perspectives of Optic Nerve Imaging in Glaucoma. J Clin Med. 2024;13(7):1966. Published 2024 Mar 28.
2. AlShawabkeh M, AlRyalat SA, Al Bdour M, Alni'mat A, Al-Akhras M. The utilization of artificial intelligence in glaucoma: diagnosis versus screening. Front Ophthalmol (Lausanne). 2024;4:1368081. Published 2024 Mar 6.
The authors report no relevant disclosures.
