ABSTRACT
There are so many biomechanical risk factors related with glaucoma and their relationship is much complex. This paper reviewed the state-of-the-art research works on glaucoma related mechanical effects. With regards to the development perspectives of studies on glaucoma biomechanics, a completely novel biomechanical evaluation factor -- Fractional Flow Reserve (FPR) for glaucoma was proposed, and developing clinical application oriented glaucoma risk assessment algorithm and application system by using the new techniques such as artificial intelligence and machine learning were suggested.
Subject(s)
Humans , Algorithms , Artificial Intelligence , Biomechanical Phenomena , Glaucoma , Diagnosis , Intraocular Pressure , Machine Learning , Risk Assessment , Risk FactorsABSTRACT
A set of device for the measurement of the pressure difference between the anterior and the posterior chambers (PDAP) was designed to investigate the temporal varying rules of PDAP in the anterior segment of rabbit eyes. A platform was established for the measurement of PDPA according to the mechanism of joint implement. Rabbit models with high intraocular pressure (IOP) were constructed by means of injecting Carbomer into anterior chamber to increase IOP. The 24 hours continuous measurements of PDAP were performed for normal rabbit eye and eye with high IOP. The developed device could sensitively response to the small pressure difference in eye. The pressure difference in the normal rabbit eye varied with time, and the variation range during a whole day was 5.84-96.84 Pa which reflected the existence of physiological rule. For the rabbit eye with high IOP, pressure in anterior chamber was higher than that in posterior chamber which was in consistence with the theory of self-adaptation adjustment. The present study indicates that the approaches and device designed in this paper can well implement the measurement of PDAP as well as the temporal varying rules of PDAP in the anterior segment during a whole day.