Purpose: This study aims to develop a kernel-based dose calculation algorithm for carbon beam therapy using DECT image and to verify the plausibility of the dose calculation algorithm.
Methods: At first, the carbon beam kernels of 100-430 MeV/u are assessed using Geant4 Monte Carlo toolkit. The pencil beam dose calculation algorithm of matRAD software is revised for using the calculated beam kernel and dual energy computed tomographic (DECT) image. The DECT and single energy CT (SECT) images of abdomen case are obtained by Philips IQon Spectral double-layer CT and given algorithm. And then, the images are converted to relative stopping power ratio (RSP) maps for the dose calculation. In order to evaluate the influence of DECT based dose calculation method, the doses on DECT and SECT images are compared with each other.
Results: The RSP maps obtained by DECT and SECT images basically show similar tendency, however, the SECT image overestimates RSP up to 5% compared to that of DECT even in homogeneous media. Moreover, the physical dose calculation results show slight range disagreements due to the RSP differences. The carbon range in the target on SECT image is shorter than the range of DECT up to 2 mm in the same treatment plan.
Conclusion: The plausibility of the beam kernel-based dose calculation algorithm has been verified in this study. We figured out that DECT can be used to correct the range uncertainty due to the CT conversion of conventional SECT about 2 mm. This work does not consider the biological effectiveness of the carbon beam, in further, the influence of DECT on biologically effective dose will be quantitatively evaluated with more patient cases in the other therapeutic regions.
Funding Support, Disclosures, and Conflict of Interest: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (No. NRF-2019 M2A2B4095126 & NRF-2019M2A2B4096540).
Dual-energy Imaging, Heavy Ions, Dose
TH- External Beam- Particle/high LET therapy: Dual energy/spectral CT-based stopping power mapping