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Updated: Jun 24, 2025

Y-90 Radioembolization and PD-1 Inhibitor as Neoadjuvant Treatment in Hepatocellular Carcinoma
Published on: May 24, 2024
A microscopic model of the dose distribution in hepatocellular carcinoma after selective internal radiation therapy
Elena Cutrì1, Ewan Morel-Corlu2, Yan Rolland2
1Univ Rennes, CLCC Eugène Marquis, Inserm, LTSI - UMR 1099, F-35000, Rennes, France; Université de technologie de Compiègne, CNRS, Biomechanics and Bioengineering, 60203 Compiègne Cedex, France; Inria, Saclay Ile-de-France, Palaiseau, 91120, France.
Abstract:
The dosimetry evaluation for the selective internal radiation therapy is currently performed assuming a uniform activity distribution, which is in contrast with literature findings. A 2D microscopic model of the perfused liver was developed to evaluate the effect of two different 90Y microspheres distributions: i) homogeneous partitioning with the microspheres equally distributed in the perfused liver, and ii) tumor-clustered partitioning where the microspheres distribution is inferred from the patient specific images.
Methods:
Two subjects diagnosed with liver cancer were included in this study. For each subject, abdominal CT scans acquired prior to the SIRT and post-treatment 90Y positron emission tomography were considered. Two microspheres partitionings were simulated namely homogeneous and tumor-clustered partitioning. The homogeneous and tumor-clustered partitionings were derived starting from CT images. The microspheres radiation is simulated by means of Russell's law.
Results:
In homogenous simulations, the dose delivery is uniform in the whole liver while in the tumor-clustered simulations a heterogeneous distribution of the delivered dose is visible with higher values in the tumor regions. In addition, in the tumor-clustered simulation, the delivered dose is higher in the viable tumor than in the necrotic tumor, for all patients. In the tumor-clustered case, the dose delivered in the non-tumoral tissue (NTT) was considerably lower than in the perfused liver.
Conclusions:
The model proposed here represents a proof-of-concept for personalized dosimetry assessment based on preoperative CT images.

