# The Implementation and Application of a Saudi Voxel-Based Anthropomorphic Phantom in OpenMC for Radiological Imaging and Dosimetry

**Authors:** Ali A. A. Alghamdi

PMC · DOI: 10.3390/diagnostics15141764 · 2025-07-12

## TL;DR

This paper describes creating a detailed 3D Saudi body model for radiation simulations, showing its usefulness in calculating radiation doses and imaging.

## Contribution

A high-resolution Saudi voxel-based anthropomorphic phantom was implemented in OpenMC for radiological simulations and dosimetry.

## Key findings

- The phantom was successfully modeled in OpenMC with accurate anatomical representation.
- Optimal radiographic contrast was observed at 70 keV.
- Effective dose calculations showed good agreement with other methods despite higher RMSEs.

## Abstract

Objectives: This study aimed to implement a high-resolution Saudi voxel-based anthropomorphic phantom in the OpenMC Monte Carlo (MC) simulation framework. The objective was to evaluate its applicability in radiological simulations, including radiographic imaging and effective dose calculations, tailored to the Saudi population. Methods: A voxel phantom comprising 30 segmented organs/tissues and over 32 million voxels were constructed from full-body computed tomography data and integrated into OpenMC. The implementation involved detailed voxel mapping, material definition using ICRP/ICRU-116 recommendations, and lattice geometry construction. The simulations included X-ray radiography projections using mesh tallies and anterior–posterior effective dose calculations across 20 photon energies (10 keV–1 MeV). The absorbed dose was calculated using OpenMC’s heating tally and converted to an effective dose using tissue weighting factors. Results: The phantom was successfully modeled and visualized in OpenMC, demonstrating accurate anatomical representation. Radiographic projections showed optimal contrast at 70 keV. The effective dose values for 29 organs were calculated and compared with MCNPX, the ICRP-116 reference phantom, and XGBoost-based machine learning (ML) predictions. OpenMC results showed good agreement, with maximum deviations of −35.5% against ICRP-116 at 10 keV. Root mean square error (RMSE) comparisons confirmed reasonable alignment, with OpenMC displaying higher RMSEs relative to other methods due to expanded organ modeling and material definitions. Conclusions: The integration of the Saudi voxel phantom into OpenMC demonstrates its utility for high-resolution dosimetry and radiographic simulations. OpenMC’s Python (version 3.10.14) interface and open-source nature make it a promising tool for radiological research. Future work will focus on combining MC and ML approaches for enhanced predictive dosimetry.

## Full-text entities

- **Genes:** VIP (vasoactive intestinal peptide) [NCBI Gene 7432] {aka PHM27}
- **Diseases:** cancer (MESH:D009369), injury to (MESH:D014947)
- **Chemicals:** Lu-177 (MESH:C000615061), ICRP-116 (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]
- **Cell lines:** ICRP-116 — Homo sapiens (Human), Invasive breast carcinoma of no special type, Cancer cell line (CVCL_RW19)

## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12293311/full.md

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Source: https://tomesphere.com/paper/PMC12293311