IEEE Rev Biomed Eng. 2016;9:163-76. doi: 10.1109/RBME.2016.2583404. Epub 2016 Jun 21.
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 cataract, 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 review chronologically looks at 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.
我们的视觉感知能力在很大程度上取决于晶状体的清晰度。晶状体透明度丧失的最常见原因是与年龄相关的核性白内障，这是由于该组织的累积性氧化损伤所致。由于眼球晶状体是一种无血管组织，它必须使用水微循环系统来维持其生理内稳态和抗氧化水平。已经使用不同的模态在动物晶状体中对该系统进行了实验成像。基于这些数据，已经开发了计算模型来预测人类晶状体中该系统的特性及其随年龄变化的情况。尽管这些基于计算机的模型在预测晶状体流体动力学的许多方面至少在动物模型中取得了成功，但它们仍然需要进一步改进，以使其更准确并能代表人类眼球晶状体。在过去的十年中，我们一直在收集实验数据，并同时开发晶状体微循环的计算模型。本综述按时间顺序回顾了晶状体微循环模型的数据驱动计算基础的发展、其当前状态和未来的发展方向。全面的晶状体流体动力学模型对于理解该组织的生理光学以及白内障发病和进展的潜在机制至关重要。
