Related Experiment Video
Updated: Dec 29, 2025

Y-90 Radioembolization and PD-1 Inhibitor as Neoadjuvant Treatment in Hepatocellular Carcinoma
Published on: May 24, 2024
Personalized Dosimetry for Liver Cancer Y-90 Radioembolization Using Computational Fluid Dynamics and Monte Carlo
Emilie Roncali1, Amirtahà Taebi2, Cameron Foster3
1Department of Biomedical Engineering, University of California, Davis, One Shields Avenue, Davis, CA, 95616, USA. eroncali@ucdavis.edu.
Abstract:
Yttrium-90 (Y-90) transarterial radioembolization uses radioactive microspheres injected into the hepatic artery to irradiate liver tumors internally. One of the major challenges is the lack of reliable dosimetry methods for dose prediction and dose verification. We present a patient-specific dosimetry approach for personalized treatment planning based on computational fluid dynamics (CFD) simulations of the microsphere transport combined with Y-90 physics modeling called CFDose. The ultimate goal is the development of a software to optimize the amount of activity and injection point for optimal tumor targeting. We present the proof-of-concept of a CFD dosimetry tool based on a patient's angiogram performed in standard-of-care planning. The hepatic arterial tree of the patient was segmented from the cone-beam CT (CBCT) to predict the microsphere transport using multiscale CFD modeling. To calculate the dose distribution, the predicted microsphere distribution was convolved with a Y-90 dose point kernel. Vessels as small as 0.45 mm were segmented, the microsphere distribution between the liver segments using flow analysis was predicted, the volumetric microsphere and resulting dose distribution in the liver volume were computed. The patient was imaged with positron emission tomography (PET) 2 h after radioembolization to evaluate the Y-90 distribution. The dose distribution was found to be consistent with the Y-90 PET images. These results demonstrate the feasibility of developing a complete framework for personalized Y-90 microsphere simulation and dosimetry using patient-specific input parameters.

