Purpose: This study compares the predictions of three parameterization models used in previously published works, implementing the stoichiometric CT calibration for proton therapy, and a further two alternative parameterizations suggested here.
Methods: Stoichiometric calibrations of patient CT-number to stopping-power ratio (SPR) were performed for four CT protocols using tissue substitutes supplied by CIRS (CIRS Inc., Norfolk, VA, USA). To evaluate robustness of the five models (Sch96/Sch00/Mar12/Karol/Spek), the calibration was repeatedly simulated by randomly perturbing the measured CT-numbers of the tissue substitutes (1σ:10 HU). The impact of high-Z content was assessed through calibrations where the two substitutes with barium content were replaced by hypothetical materials without barium.
Results: The stoichiometric calibrations generally agreed within 1% between the models, for non-bony tissues. For higher CT-numbers, a well-known 2-parameter model (Sch00) generated larger SPRs compared to the other models, with inter-model discrepancies of up to 3%. The 95% coverage interval of the calibrations obtained from the robustness analysis varied substantially. The well-known 2- and 3-parameter models (Sch00/Sch96) had the largest intervals. However, the partly-hypothetical (i.e. no barium) input data generated calibrations that agreed within 1% over the whole CT scale for all models and improved the 95% coverage interval of the well-known models (Sch00/Sch96).
Conclusion: All parameterization models performed comparably if the scanned materials only contained elements with Z ≤ 20. However, the two alternative models proposed here (Karol/Spek), together with a previously published 1-parameter model (Mar12), generated robust calibrations in close agreement even when tissue substitutes contain elements with higher atomic number.
Keywords: CT calibration; Proton therapy; Stoichiometric method; Stopping-power ratios.
Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.