Patient-specific optimization of locoregional drug delivery for liver cancer

Clinical context

Hepatocellular carcinoma (HCC) is the most common form of primary liver cancer and the second-highest leading cause of cancer-related deaths. Effective and site-specific strategies for the administration of therapeutic drugs are urgently needed, especially for patients with unresectable tumors.

For the treatment of unresectable hepatocellular carcinoma (HCC), transarterial therapies such as transarterial radioembolization (TARE) and transarterial chemoembolization (TACE) aim at maximally damaging tumor tissue. During these therapies, the patient is catheterized through the femoral artery and the catheter is advanced via the aorta towards the liver. Microspheres, which contain chemotherapeutic (TACE) or radioactive agents (TARE), are injected in the proper hepatic artery or, ideally, closer to the tumor.

However, during treatment, severe side-effects can occur as a result of unwanted drug delivery to the healthy tissue instead of the tumor tissue. Since clinical response to these transarterial therapies is very heterogenous, the question can be raised if the drug particles are even being delivered to the tumor. Therefore, methods to steer drug particles more efficiently to the tumor must be investigated.

Project outline

The focus of this project is to build patient-specific computational tools that model blood flow and drug particle trajectories inside the hepatic arteries of the patient, and to validate these models using a variety of novel in vivo imaging and in vitro experimental techniques.

A key focus of the research is the use of computational fluid dynamics (CFD) to model the patient-specific blood flow and drug particle transport inside the hepatic arteries. The aim is developing a patient-specific framework that allows to identify the therapy parameters (i.e. injection location, injection velocity, particle size and density, etc.) which are most suitable for steering drugs particles to the tumor (i.e. tumor fraction) in each individual case.

Figure 1: Patient-specific optimization framework

One of the current validation approaches includes overlapping numerical results with SPECT-CT images. The radioactive hotspots on the SPECT-CT scans show where microspheres deposited in the tissue during the (pre-)treatment, which should correspond with particle deposition as predicted by the model. This is visualized in the panel on the left side of Figure 2. A different approach entails experimental simulations of drug delivery in patient-inspired in-vitro models using 3D prints of patient-specific hepatic arterial geometries connected to a perfusion pump. The set-up is visualized in the right panel of Figure 2.

Figure 2: Patient-specific validation methods

Video material

  • A clear and concise explanation of the project outline on this link.
  • What is the impact of injection timing and injection location on the particle distribution?
    This video was presented at the OncoDot.1 virtual conference organized by Cancer Research Institute Ghent (CRIG).


All current publications on this topic are available at:

IBiTech researchers currently active on the project

  • Tim Bomberna ()
  • Charlotte Debbaut ()
  • Geert Maleux (KULeuven / UZLeuven)

Funding sources

  • Doctoral grant strategic basic research of the research foundation-Flanders (FWO-Vlaanderen) – grant 1S10421N 2020-2024 (Tim Bomberna)
  • Postdoctoral fellowship of the research foundation-Flanders (FWO-Vlaanderen) – grant 1202418N 2017-2020 (Charlotte Debbaut)
  • BOF starting grant – grant BOFSTA201909015 2019-2023 (Charlotte Debbaut)

Relevant links