An Innovative CFD-based Dosimetry and Pre-treatment Planning Platform to Support Personalized Transarterial Therapies for Liver Cancer

Transarterial radioembolization (TARE) is a key treatment option for patients with unresectable hepatocellular carcinoma (HCC), a primary form of liver cancer. TARE is a minimally invasive therapy in which radioactive microspheres are delivered through a microcatheter near the tumour into the liver's blood vessels. Although TARE can significantly improve survival, treatment outcomes remain variable and difficult to predict, mainly because of complex liver vasculature and unpredictable distribution of radioactive microspheres due to uncertain parameters such as catheter tip location, catheter orientation, and injection velocity. The long-term goal would be to make these treatments more predictable and effective by developing a patient-specific pre-treatment planning platform. Blood flow and microsphere transport will be modelled in a digital model of the patient-specific hepatic arterial tree (based on clinical imaging) using computational fluid dynamics (CFD), in combination with Monte Carlo-based radiation dosimetry. Using CFD simulations, we will investigate how variations in treatment parameters influence the microsphere distribution, aiming to better understand their role in treatment variability. This will allow us to predict the dose distribution of a certain treatment and determine potentially a more optimal set of treatment parameters. This research contributes to the broader field of cancer research by laying the foundations for a digital tool for personalized pre-treatment planning. The insights gained could support interventional radiologists in optimizing treatment planning, improving tumor targeting, and minimizing radiation exposure to healthy liver tissue in future TARE procedures.