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Updated: Jun 10, 2025

Whole Vitreous Humor Dissection for Vitreodynamic Analysis
Published on: May 24, 2015
Effective Prediction of Drug Transport in a Partially Liquefied Vitreous Humor: Physics-informed Neural Network
Shuqi Zhang1, Anita Penkova2, Xiaodong Jia3
1University of Southern California, Los Angeles, CA, USA.; Convergent Science, Madison, WI, USA.
None:
As the medium for intravitreal drug delivery, the vitreous body can significantly influence drug delivery because of various possible liquefaction geometries. This work innovatively proposes a varying-porosity approach that is capable of solving the pressure and velocity fields in the heterogeneous vitreous with randomly-shaped liquefaction geometry, validated with a finite difference model. Doing so enables patient-specific treatment for intravitreal drug delivery and can significantly improve treatment efficacy. A physics-informed neural network (PINN) model is also established for the simulation, and three cases are used for validation. Despite limited information, the PINN model, together with the varying-porosity approach, captured fluid and drug transport in the partially liquefied vitreous. This opens the possibility for optimizing intravitreal drug delivery based on ultrasonography in clinical practice.
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