Comparison of proton, helium-ion, and carbon-ion CT imaging for hadron radiotherapy using Monte Carlo simulations

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• Picked for Medical Physics (top studies of the week, 4 October 2026): Monte‑Carlo comparison of particle CT imaging modalities

Abstract

To perform a comprehensive comparative analysis of proton, helium-ion, and carbon-ion computed tomography (CT) as direct imaging modalities for hadron therapy treatment planning, focusing on Relative Stopping Power (RSP) reconstruction accuracy and patient radiation dose.&#xD;Approach: High-fidelity Monte Carlo simulations were conducted using the GATE/Geant4 platform to model a standard CTP404 phantom. RSP maps were reconstructed using two iterative algorithms: the Simultaneous Algebraic Reconstruction Technique (SART) and the Richardson-Lucy (RL) deconvolution. Imaging performance was evaluated by comparing reconstructed RSP values against ground truth data for various tissue-equivalent inserts, while integral doses were estimated for a human head geometry using a Shepp-Logan-like phantom.&#xD;Main results: All investigated particle modalities demonstrated a significant dose reduction compared to conventional X-ray CT protocols (which are approximately 40 mGy). The estimated imaging doses were 0.5 mGy for protons, 1.3 mGy for helium ions, and 7.5 mGy for carbon ions. &#xD;In terms of accuracy, carbon-ion imaging achieved promising accuracy for soft-tissue materials (mean absolute error <0.5%). Helium ions offered a balanced performance with sub-1% errors for most materials and a dose burden significantly lower than carbon ions. Protons exhibited the widest range of RSP deviations.&#xD;Significance: Direct particle imaging eliminates the systematic uncertainties inherent in photon-to-hadron conversion, which typically introduce RSP deviations of 1.6%-3.5% in standard single-energy X-ray CT. While carbon ions provide better RSP reconstruction precision essential for complex treatment plans in heterogeneous anatomy, helium and proton imaging offer exceptional dose sparing, making them particularly advantageous for pediatric patients and frequent adaptive replanning scenarios.

Abstract as published, via PubMed.