An In Silico Case Study on Patient-Specific Hemodynamics During Transarterial Radioembolization of Liver Cancer

In 2020, liver cancer was the fourth most prevalent form of cancer worldwide. Transarterial radioembolization (TARE) is a transcatheter procedure in which radioactive particles are delivered to a liver tumor. Pretreatment mapping studies utilize a surrogate particle to observe drug distribution as a function of catheter placement. However, discrepancies in distribution between the pretreatment tumor dose and the actual treatment tumor dose have been attributed to a mismatch in particle morphology and catheter placement between procedures. In this study, we develop an in silico model of a patient hepatic arterial network to understand the fundamental mechanisms behind these discrepancies. This model integrates flow information derived from patient medical imaging to quantify angiogenic effect on blood flow. Hemodynamics is solved using SimVascular, and particle trajectories are calculated using a Lagrangian model previously developed in house. Particle distribution to tumor-feeding vessel indicates size-dependent effects, potentially leading to mismatch between pretreatment and treatment dosing scenarios. With this framework in place, optimal catheter placement and differing injection rates can also be implemented to observe how clinical conditions can alter treatment accuracy.