Comparison of different cell-cluster models for cell-level dosimetry

Area of Science:

• Medical Physics
• Radiotherapy
• Computational Biology

Background:

• Accurate dose calculations are crucial for targeted radionuclide therapy effectiveness.
• The choice of cell-cluster model significantly impacts absorbed dose estimations.
• Existing models like the lattice and CellPacker have limitations in representing tissue interfaces and density.

Purpose of the Study:

• To develop and evaluate a novel cell-cluster model for targeted radionuclide therapy.
• To compare the geometric and dosimetric properties of the new model against traditional and existing computational models.
• To assess the impact of different cell-cluster models on absorbed dose calculations.

Main Methods:

• A new cell-cluster model was developed using mechanical hard-sphere collision optimization.
• Geometrical properties and dosimetric effects were compared with the traditional lattice model and the CellPacker model.
• Simulations were performed to analyze absorbed dose distributions and tissue interface characteristics.

Main Results:

• The new cell-cluster model demonstrates distinct geometrical and dosimetric properties compared to previous models.
• The developed model allows for tighter cell packing, enabling the simulation of higher cellular density tissues.
• Unlike CellPacker, the new model can generate diffuse tumor-healthy tissue interfaces, improving biological realism.

Conclusions:

• The choice of cell-cluster model critically influences dose calculations in targeted radionuclide therapy.
• The novel hard-sphere optimized model provides enhanced capabilities for modeling tissue architecture and interfaces.
• This new model facilitates more accurate and tissue-specific dose calculations for improved radiotherapy treatment planning.