Abstract:
Our sense of vision is critically dependent on the clarity of the crystalline lens. The most common cause of transparency loss in the lens is age-related nuclear cataracts, which is due to accumulative oxidative damage to this tissue. Since the ocular lens is an avascular tissue, it has to maintain its physiological homeostasis and antioxidant levels using a system of water microcirculation. This system has been experimentally imaged in animal lenses using different modalities. Based on these data, computational models have been developed to predict the properties of this system in human lenses and its changes due to aging. Although successful in predicting many aspects of lens fluid dynamics, at least in animal models, these in-silica models still need further improvement to become more accurate and representative of human ocular lens. We have been working on gathering experimental data and simultaneously developing computational models of lens microcirculation for the past decade. This paper chronologically reviews the development of data-driven computational foundations of lens microcirculation model, its current state, and future advancement directions. A comprehensive model of lens fluid dynamics is essential to understand the physiological optics of this tissue and ultimately the underlying mechanisms of cataract onset and progression.