Modeling aqueous humour outfow based on digital twin of the anterior eye imaged by robotic OCT - Project Summary Glaucoma care requires treatments that are safe, efficacious, and predictable. Glaucomatous optic neuropathy is a leading cause of irreversible blindness worldwide, and so far, no direct optic nerve treatment can reverse glaucoma. Thus, glaucoma treatment is risk factor modification. The only modifiable risk factor is elevated intraocular pressure (IOP). IOP reduction has been proven to mitigate glaucoma progression. Yet current medical and surgical methods often fail to provide long-term IOP reduction to prevent blindness. Researchers attribute this to a lack of a comprehensive understanding of pathologic IOP in glaucoma. To reduce IOP, drugs (such as muscarinic agonists, rho-kinase inhibitors, or nitric-oxide donors) and Minimally Invasive Glaucoma Surgeries (MIGSs) target the trabecular meshwork (TM) to decrease aqueous humor outflow (AHO) resistance. Unfortunately, pathological AHO resistance in glaucoma is progressive, and medications become less effective over time, leading to patients becoming medically non-responsive. In addition, patient compliance remains a key limitation for medications, eventually leading to surgical interventions. MIGS are a quick and safe alternative to lower IOP by surgically ablating or bypassing pathological TM. However, in large-scale, well-controlled clinical trials, average MIGS efficacy was lacking, providing only few mmHg of total IOP reduction. Therefore, improving MIGS efficacy remains a unmet clinical need. We argue that the lack of trabecular MIGS efficacy is caused by a poor understanding of the circumferential AHO anatomy and pathophysiology, which leads to a lack of surgical planning. Clinically, focal trabecular bypass and ablation in glaucoma patients near-universally target the TM in the nasal iridocorneal angle; there is no tools available for surgeons to tailor MIGS to suit individual patient’s needs. We will develop a robotic anterior-segment optical coherence (AS-OCT) to visualize the circumferential AHO pathways and create the digital twin of the AHO pathway anatomy. Using the digital twin, we will further develop an eye-specific hydrodynamic model to predict IOP reduction under different MIGS plans. The robotic AS-OCT will enable researchers to visualize the entire AHO pathways for the first time. The AHO pathway’s in vivo circumferential anatomic features, including segmental Schlemm's canal size distribution, the total number of collector channels and their circumferential distribution, have not been accessible to researchers before. The concept of a digital twin of the eye is principally new, providing new ways to visualize and track ocular anatomical alterations and allowing ophthalmologists to perform surgical planning for the first time. Finally, integrating the hydrodynamic model with the digital twin allows for predicting the effects of different MIGS plans to achieve optimal patient outcomes, leading to personalized, precision glaucoma care. We will also deposit the hydrodynamic model at our GitHub website to ensure broad dissemination to the research community.
