Purchase this article with an account.
James C H Tan, Edward Rickie Chu, Jose Miguel Gonzalez, Aleksandr Yelenskiy, MinHee K Ko, Stuart L Graham, Eun Kyoung Kim; Simulating the effect of trabecular meshwork resistance and episcleral venous pressure on conventional aqueous humor outflow dynamics. Invest. Ophthalmol. Vis. Sci. 2014;55(13):2885.
Download citation file:
© ARVO (1962-2015); The Authors (2016-present)
To simulate the effect of trabecular meshwork (TM) resistance and episcleral venous pressure (EVP) on conventional outflow dynamics in an artificial model.
We constructed an artificial perfusion model comprising a microsyringe on a pump (representing aqueous inflow) connected to needles of different caliber (33G and 35G; TM resistor) linked to a one-way valve (Schlemm’s canal inner wall endothelium barrier) and then a static fluid column (EVP). Three intervening pressure transducers (PT) were used: PT#1: between pump and needle (representing intraocular pressure (IOP)); PT#2: between needle and valve (TM/SC tissue pressure); and PT#3: between valve and fluid column (EVP). The pump and PT#1 were connected to an analogue voltage controller to control flow rate to maintain a predetermined pressure. Flow rates and pressure data were sampled in real time. Resistances of different needles (33G and 35G) at different EVP (9 and 12mmHg) were measured. Statistical significance between slopes of pressure to flow rate relationships was determined using linear regression analysis (Prism 6.03, GraphPad Software Inc.; p < 0.05).
35G needle resistance, as measured by PT#1 over a range of flow rates, was higher than that of 33G resistance (p=0.0005), while resistance measured by PT#2 over the same range of flow rates was similar for 33G and 35G needles (p=0.062). Incremental flow rate increases led to divergence of pressure readings at PT#1 (IOP) and PT#2 (tissue pressure) that was greater in the higher resistance system (35G). Increasing EVP from 9 to 12mmHg caused elevated pressure as measured at PT#1 and PT#2 but resistance remained the same (p=0.2).
Simulations produced expected fluid dynamic behavior that was quantifiable in an artificial model of the conventional aqueous outflow pathways. The model had components representing the TM, inner wall endothelium, and EVP. Higher needle resistance (representing greater TM resistance) and higher EVP, two glaucoma pathogenic scenarios, resulted in elevated IOP. The system may be used to model and quantify variables leading to elevated IOP to better understand aqueous dynamics and glaucoma pathophysiology.
This PDF is available to Subscribers Only