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Multiscale Computational Fluid Dynamics Modeling for Personalized Liver Cancer Radioembolization Dosimetry.

Amirtahà Taebi1, Catherine T Vu2, Emilie Roncali1

  • 1Department of Biomedical Engineering, University of California Davis, One Shields Avenue, Davis, CA 95616.

Journal of Biomechanical Engineering
|July 1, 2020
PubMed
Summary

This study introduces a computational model for personalized Yttrium-90 (90Y) radioembolization dosimetry in liver cancer. The model predicts radiation dose distribution, improving treatment accuracy and safety for patients with hepatocellular carcinoma.

Keywords:
computational fluid dynamicsdosimetryhepatic arteryliver cancermultiscale modelingyttrium-90 radioembolization

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Area of Science:

  • Medical Physics
  • Interventional Radiology
  • Computational Biology

Background:

  • Yttrium-90 (90Y) radioembolization is a key treatment for advanced liver cancer.
  • Current dosimetry methods for 90Y radioembolization rely on simplified assumptions, leading to unreliable dose estimations.
  • Accurate dosimetry is crucial for maximizing tumor radiation dose and minimizing off-target exposure.

Purpose of the Study:

  • To develop and validate a computational model for personalized 90Y dosimetry in liver cancer treatment.
  • To predict radiation dose distribution based on 90Y activity in different liver segments.
  • To enhance the safety and efficacy of radioembolization through patient-specific treatment planning.

Main Methods:

  • A 3D computational fluid dynamics (CFD) model of the hepatic arterial tree was created from patient-specific cone-beam CT angiographic data.
  • Microsphere trajectories and volumetric distribution were simulated based on CFD-derived velocity fields.
  • 90Y radiation dose distribution was calculated from the predicted microsphere distribution.

Main Results:

  • Simulations predicted differential microsphere delivery to the tumor (22% for lobar, 82% for selective injection).
  • A combined injection strategy delivered 49% of total 90Y microspheres to the tumor.
  • Significant nonhomogeneous distribution of microspheres across liver segments was observed.

Conclusions:

  • Patient-specific dosimetry models are essential for optimizing 90Y radioembolization outcomes.
  • The developed computational model offers a more realistic approach to predicting radiation dose distribution.
  • Personalized dosimetry can improve tumor targeting and reduce radiation toxicity in liver cancer patients.