PURPOSE: Dual-energy computed tomography (DECT) has been presented as a valid alternative to single-energy CT to reduce the uncertainty of the conversion of patient CT numbers to proton stopping power ratio (SPR) of tissues relative to water. The aim of this work was to optimize DECT acquisition protocols from simulations of X-ray images for the treatment planning of proton therapy using a projection-based dual-energy decomposition algorithm. METHODS: We have investigated the effect of various voltages and tin filtration combinations on the SPR map accuracy and precision, and the influence of the dose allocation between the low-energy (LE) and the high-energy (HE) acquisitions. For all spectra combinations, virtual CT projections of the Gammex phantom were simulated with a realistic energy-integrating detector response model. Two situations were simulated: an ideal case without noise (infinite dose) and a realistic situation with Poisson noise corresponding to a 20 mGy total central dose. To determine the optimal dose balance, the proportion of LE-dose with respect to the total dose was varied from 10% to 90% while keeping the central dose constant, for four dual-energy spectra. SPR images were derived using a two-step projection-based decomposition approach. The ranges of 70 MeV, 90 MeV, and 100 MeV proton beams onto the adult female (AF) reference computational phantom of the ICRP were analytically determined from the reconstructed SPR maps. RESULTS: The energy separation between the incident spectra had a strong impact on the SPR precision. Maximizing the incident energy gap reduced image noise. However, the energy gap was not a good metric to evaluate the accuracy of the SPR. In terms of SPR accuracy, a large variability of the optimal spectra was observed when studying each phantom material separately. The SPR accuracy was almost flat in the 30-70% LE-dose range, while the precision showed a minimum slightly shifted in favor of lower LE-dose. Photon noise in the SPR images (20 mGy dose) had lower impact on the proton range accuracy as comparable results were obtained for the noiseless situation (infinite dose). Root-mean-square range errors averaged over all irradiation angles associated to dual-energy imaging were comprised between 0.50 mm and 0.72 mm for the noiseless situation and between 0.51 mm and 0.77 mm for the realistic scenario. CONCLUSIONS: The impact of the dual-energy spectra and the dose allocation between energy levels on the SPR accuracy and precision determined through a projection-based dual-energy algorithm were evaluated to guide the choice of spectra for dual-energy CT for proton therapy. The dose balance between energy levels was not found to be sensitive for the SPR estimation. The optimal pair of dual-energy spectra was material dependent but on a heterogeneous anthropomorphic phantom, there was no significant difference in range accuracy and the choice of spectra could be driven by the precision, i.e., the energy gap.
PURPOSE: Dual-energy computed tomography (DECT) has been presented as a valid alternative to single-energy CT to reduce the uncertainty of the conversion of patient CT numbers to proton stopping power ratio (SPR) of tissues relative to water. The aim of this work was to optimize DECT acquisition protocols from simulations of X-ray images for the treatment planning of proton therapy using a projection-based dual-energy decomposition algorithm. METHODS: We have investigated the effect of various voltages and tin filtration combinations on the SPR map accuracy and precision, and the influence of the dose allocation between the low-energy (LE) and the high-energy (HE) acquisitions. For all spectra combinations, virtual CT projections of the Gammex phantom were simulated with a realistic energy-integrating detector response model. Two situations were simulated: an ideal case without noise (infinite dose) and a realistic situation with Poisson noise corresponding to a 20 mGy total central dose. To determine the optimal dose balance, the proportion of LE-dose with respect to the total dose was varied from 10% to 90% while keeping the central dose constant, for four dual-energy spectra. SPR images were derived using a two-step projection-based decomposition approach. The ranges of 70 MeV, 90 MeV, and 100 MeV proton beams onto the adult female (AF) reference computational phantom of the ICRP were analytically determined from the reconstructed SPR maps. RESULTS: The energy separation between the incident spectra had a strong impact on the SPR precision. Maximizing the incident energy gap reduced image noise. However, the energy gap was not a good metric to evaluate the accuracy of the SPR. In terms of SPR accuracy, a large variability of the optimal spectra was observed when studying each phantom material separately. The SPR accuracy was almost flat in the 30-70% LE-dose range, while the precision showed a minimum slightly shifted in favor of lower LE-dose. Photon noise in the SPR images (20 mGy dose) had lower impact on the proton range accuracy as comparable results were obtained for the noiseless situation (infinite dose). Root-mean-square range errors averaged over all irradiation angles associated to dual-energy imaging were comprised between 0.50 mm and 0.72 mm for the noiseless situation and between 0.51 mm and 0.77 mm for the realistic scenario. CONCLUSIONS: The impact of the dual-energy spectra and the dose allocation between energy levels on the SPR accuracy and precision determined through a projection-based dual-energy algorithm were evaluated to guide the choice of spectra for dual-energy CT for proton therapy. The dose balance between energy levels was not found to be sensitive for the SPR estimation. The optimal pair of dual-energy spectra was material dependent but on a heterogeneous anthropomorphic phantom, there was no significant difference in range accuracy and the choice of spectra could be driven by the precision, i.e., the energy gap.