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Multiple Mesh-type Real Human Cell Models for Dosimetric Application Coupled with Monte Carlo Simulations.

YiDi Wang1,2,3, Dong Kong4, Han Gao1,2,3

  • 1State Key Laboratory of Radiation Medicine and Protection, Suzhou, China.

Radiation Research
|July 6, 2023
PubMed
Summary
This summary is machine-generated.

Mesh-type models improve cellular dose assessment for Monte Carlo simulations. These advanced models, based on real human cells, offer greater versatility than voxel models for various irradiation scenarios and radiation biology applications.

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Area of Science:

  • Medical Physics
  • Computational Biology
  • Radiation Dosimetry

Background:

  • Voxel models present limitations in cellular dose assessment accuracy.
  • Monte Carlo (MC) codes require detailed cellular models for precise radiation dosimetry.
  • Mesh-type models offer a more refined approach to representing cellular structures.

Purpose of the Study:

  • To develop and optimize micron-scale mesh-type models of real human cells.
  • To evaluate the feasibility of these mesh models with various MC codes and irradiation scenarios.
  • To compare the performance of mesh models against voxel models for cellular dose assessment.

Main Methods:

  • Reconstruction and optimization of six human cell line models using laser confocal tomography.
  • Transformation of mesh models into polygon (GATE) and tetrahedral (PHITS) formats.
  • Dose assessment using MC simulations with electrons, protons, and radioisotopes under different irradiation conditions.

Main Results:

  • Mesh-type models can be directly applied to MC codes (GATE, PHITS) after surface reduction, bypassing voxelization.
  • Significant dose variations were observed between different cell types and irradiation scenarios.
  • Smaller cell nuclei showed greater sensitivity to physical codes, with notable nanoscale dose deviations.

Conclusions:

  • Mesh-type real cell models are more versatile and accurate than voxel or mathematical models for MC simulations.
  • These models facilitate RBE estimations and biological effect predictions in radiotherapy and radiation protection.
  • The developed models are extendable to other cell types and irradiation scenarios, advancing radiation research.