Modeling cone-beam CT and industrial X-ray tube spectra using SpekPy software toolkit

Authors

  • Lian Angelo B. Ramos ⋅ PH Department of Physical Sciences, Polytechnic University of the Philippines
  • Renniel B. Bautista ⋅ PH Department of Physical Sciences, Polytechnic University of the Philippines
  • Jason Carl Martin A. Tupas ⋅ PH Department of Physical Sciences, Polytechnic University of the Philippines

Abstract

X-ray source modeling is a significant task to properly characterize an X-ray beam for improved imaging and dosimetry calculations. This study demonstrates the use of SpekPy v2.0, a newly developed semi-empirical-based software toolkit, in modeling cone-beam computed tomography (CBCT) and industrial X-ray unit. Specifically, we modeled the Elekta XVI CBCT and Comet-MXR-320 X-ray systems by incorporating the tube potential, anode material and angle, filtration material, and filtration thickness of the X-ray units in the SpekPy simulations. The generated X-ray spectra were validated against Monte Carlo (MC) simulations using the EGSnrc software toolkit. Spectral distribution and correlation plots between the MC and SpekPy fluence spectra were obtained. Good agreement was found between the SpekPy and MC-calculated spectra with linear regression slope close to unity and correlation coefficient of R2 = 0.9921 and R2 = 0.9996 for Elekta XVI and Comet-MXR-320, respectively. Half-value layers (HVL) were also validated against the MC model and experimental measurements present in the literature. Good agreement was obtained between the SpekPy-calculated HVLs and experimental HVLs with a maximum difference of 5.17%.

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Issue

Article ID

SPP-2022-PB-12

Section

Poster Session B (Complex Systems, Simulations, and Theoretical Physics)

Published

2022-09-18

How to Cite

[1]
LAB Ramos, RB Bautista, and JCMA Tupas, Modeling cone-beam CT and industrial X-ray tube spectra using SpekPy software toolkit, Proceedings of the Samahang Pisika ng Pilipinas 40, SPP-2022-PB-12 (2022). URL: https://proceedings.spp-online.org/article/view/SPP-2022-PB-12.