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1. Ocular blood flow as a clinical observation: Value, limitations and data analysis

   Harris, A. (January 2020, Progress in retinal and eye research)

   Alterations in ocular blood flow have been identified as important risk factors for the onset and progression of numerous diseases of the eye. In particular, several population-based and longitudinal-based studies have provided compelling evidence of hemodynamic biomarkers as independent risk factors for ocular disease throughout several different geographic regions. Despite this evidence, the relative contribution of blood flow to ocular physiology and pathology in synergy with other risk factors and comorbidities (e.g., age, gender, race, diabetes and hypertension) remains uncertain. There is currently no gold standard for assessing all relevant vascular beds in the eye, and the heterogeneous vascular biomarkers derived from multiple ocular imaging technologies are non-interchangeable and difficult to interpret as a whole. As a result of these disease complexities and imaging limitations, standard statistical methods often yield inconsistent results across studies and are unable to quantify or explain a patient's overall risk for ocular disease. Combining mathematical modeling with artificial intelligence holds great promise for advancing data analysis in ophthalmology and enabling individualized risk assessment from diverse, multi-input clinical and demographic biomarkers. Mechanism-driven mathematical modeling makes virtual laboratories available to investigate pathogenic mechanisms, advance diagnostic ability and improve disease management. Artificial intelligence provides a novel method for utilizing a vast amount of data from a wide range of patient types to diagnose and monitor ocular disease. This article reviews the state of the art and major unanswered questions related to ocular vascular anatomy and physiology, ocular imaging techniques, clinical findings in glaucoma and other eye diseases, and mechanistic modeling predictions, while laying a path for integrating clinical observations with mathematical models and artificial intelligence. Viable alternatives for integrated data analysis are proposed that aim to overcome the limitations of standard statistical approaches and enable individually tailored precision medicine in ophthalmology. 

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2. Harnessing the power of longitudinal medical imaging for eye disease prognosis using Transformer-based sequence modeling

   https://doi.org/10.1038/s41746-024-01207-4  

   Holste, Gregory; Lin, Mingquan; Zhou, Ruiwen; Wang, Fei; Liu, Lei; Yan, Qi; Van_Tassel, Sarah H; Kovacs, Kyle; Chew, Emily Y; Lu, Zhiyong; et al (December 2024, npj Digital Medicine)

   Deep learning has enabled breakthroughs in automated diagnosis from medical imaging, with many successful applications in ophthalmology. However, standard medical image classi cation approaches only assess disease presence at the time of acquisition, neglecting the common clinical setting of longitudinal imaging. For slow, progressive eye diseases like age-related macular degeneration (AMD) and primary open-angle glaucoma (POAG), patients undergo repeated imaging over time to track disease progression and forecasting the future risk of developing a disease is critical to properly plan treatment. Our proposed Longitudinal Transformer for Survival Analysis (LTSA) enables dynamic disease prognosis from longitudinal medical imaging, modeling the time to disease from sequences of fundus photography images captured over long, irregular time periods. Using longitudinal imaging data from the Age-Related Eye Disease Study (AREDS) and Ocular Hypertension Treatment Study (OHTS), LTSA signi cantly outperformed a single-image baseline in 19/20 head-to- head comparisons on late AMD prognosis and 18/20 comparisons on POAG prognosis. A temporal attention analysis also suggested that, while the most recent image is typically the most in uential, prior imaging still provides additional prognostic value. 

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3. Choroidal Thickness and Primary Open-Angle Glaucoma—A Narrative Review

   https://doi.org/10.3390/jcm11051209  

   Verticchio Vercellin, Alice; Harris, Alon; Stoner, Ari M.; Oddone, Francesco; Mendoza, Kristen Ann; Siesky, Brent (March 2022, Journal of Clinical Medicine)

   The choroid provides the majority of blood flow to the ocular tissues and structures that facilitate the processes of retinal metabolism responsible for vision. Specifically, the choriocapillaris provides a structural network of small blood vessels that supplies the retinal ganglion cells and deep ocular tissues. Similar to retinal nerve fiber layer thickness, choroidal thickness (CT) has been suggested to represent a quantifiable health biomarker for choroidal tissues. Glaucoma is a disease with vascular contributions in its onset and progression. Despite its importance in maintaining ocular structure and vascular functionality, clinical assessments of choroidal tissues have been historically challenged by the inaccessibility of CT biomarker targets. The development of optical coherence tomography angiography and enhanced depth imaging created a framework for assessing CT and investigating its relationship to glaucomatous optic neuropathy onset and progression. Pilot studies on CT in glaucoma are conflicting—with those both in support of, and against, its clinical utility. Complicating the data are highly customized analysis methods, small sample sizes, heterogeneous patient groups, and a lack of properly designed controlled studies with CT as a primary outcome. Herein, we review the available data on CT and critically discuss its potential relevance and limitations in glaucoma disease management. 

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4. The Eye as the Window to the Heart: Optical Coherence Tomography Angiography Biomarkers as Indicators of Cardiovascular Disease

   https://doi.org/10.3390/jcm13030829  

   Kellner, Rebecca L; Harris, Alon; Ciulla, Lauren; Guidoboni, Giovanna; Verticchio_Vercellin, Alice; Oddone, Francesco; Carnevale, Carmela; Zaid, Mohamed; Antman, Gal; Kuvin, Jeffrey T; et al (February 2024, Journal of Clinical Medicine)

   Alterations in microvasculature represent some of the earliest pathological processes across a wide variety of human diseases. In many organs, however, inaccessibility and difficulty in directly imaging tissues prevent the assessment of microvascular changes, thereby significantly limiting their translation into improved patient care. The eye provides a unique solution by allowing for the non-invasive and direct visualization and quantification of many aspects of the human microvasculature, including biomarkers for structure, function, hemodynamics, and metabolism. Optical coherence tomography angiography (OCTA) studies have specifically identified reduced capillary densities at the level of the retina in several eye diseases including glaucoma. This narrative review examines the published data related to OCTA-assessed microvasculature biomarkers and major systemic cardiovascular disease. While loss of capillaries is being established in various ocular disease, pilot data suggest that changes in the retinal microvasculature, especially within the macula, may also reflect small vessel damage occurring in other organs resulting from cardiovascular disease. Current evidence suggests retinal microvascular biomarkers as potential indicators of major systemic cardiovascular diseases, including systemic arterial hypertension, atherosclerotic disease, and congestive heart failure. 

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5. The ocular mathematical virtual simulator: A validated multiscale model for hemodynamics and biomechanics in the human eye

   https://doi.org/10.1002/cnm.3791  

   Sala, Lorenzo; Prud'homme, Christophe; Guidoboni, Giovanna; Szopos, Marcela; Harris, Alon (November 2023, International Journal for Numerical Methods in Biomedical Engineering)

   Abstract We present our continuous efforts from a modeling and numerical viewpoint to develop a powerful and flexible mathematical and computational framework called Ocular Mathematical Virtual Simulator (OMVS). The OMVS aims to solve problems arising in biomechanics and hemodynamics within the human eye. We discuss our contribution towards improving the reliability and reproducibility of computational studies by performing a thorough validation of the numerical predictions against experimental data. The OMVS proved capable of simulating complex multiphysics and multiscale scenarios motivated by the study of glaucoma. Furthermore, its modular design allows the continuous integration of new models and methods as the research moves forward, and supports the utilization of the OMVS as a promising non‐invasive clinical investigation tool for personalized research in ophthalmology. 

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