Abstract
Purpose :
Optic neuropathies such as glaucoma are often late-onset, progressive and incurable diseases.
Principally, these disorders are caused by pathogenic hemodynamics and biomechanics in the back of the eye.
Data on ocular posterior tissues are difficult to estimate non-invasively and their clinical interpretation remains challenging due to the interaction among multiple factors that are not easily isolated.
We have developed a user-friendly web interface that employs the Ocular Mathematical Virtual Simulator (OMVS) to perform real-time simulations estimating ocular hemodynamical and biomechanical conditions based on patient-specific input data.
Methods :
The OMVS (Fig. 1a) combines 1) a three-dimensional (3d) porous-media model for lamina cribrosa (LC) perfusion with 2) a circuit-based model for blood flow in retrobulbar and ocular posterior segments and 3) a 3d elastic model to simulate the biomechanics of LC, retina, choroid, sclera, and cornea.
Systems 1), 2) and 3) are solved using advanced computational methods (Feel++,OpenModelica) within a web simulation interface (Fig. 1c) that provides two applications: i) the OMVS View App (Fig. 1d), allowing the user to explore the simulation results that are stored in a private database, and ii) the OMVS Compare App (Fig. 1b), supporting a comparative analysis of multiple assessments of different patients or of the same patient at different visits.
Results :
A virtual patient database (Fig. 2a) made of synthetic data inspired by the clinical literature was generated to test the web interface, which is used as a virtual laboratory for hemodynamical and biomechanical analysis.
Fig. 2b suggests that virtual patients with high intraocular pressure (IOP) have a decrease (up to 66%) in central retinal vessels blood flow; however this reduction is less important in subjects suffering from high intracranial pressure (ICP) and/or high systolic/diastolic blood pressure (BP, Figs. 2c and 2d, up to 64% and 58%, respectively).
Conclusions :
The OMVS web-interface provides an accessible environment where the user can isolate single risk factors and inspect their influence on the overall system.
The proposed interface may serve as a complementary method of data analysis and visualization for clinical and experimental research and a training application for educational purposes.
This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.