Abstract. A method to establish the relationship between CT number and effective density for therapeutic radiations is proposed. We approximated body tissues to mixtures of muscle, air, fat, and bone. Consequently, the relationship can be calibrated only with a CT scan of their substitutes, for which we chose water, air, ethanol, and potassium phosphate solution, respectively. With simple and specific corrections for non-equivalencies of the substitutes, the calibration accuracy of 1% will be achieved. We tested the calibration method with some biological materials to verify that the proposed method would offer accuracy, simplicity, and specificity required for a standard in radiotherapy treatment planning, in particular, with heavy charged particles.
Secondary neutron ambient dose equivalents per the treatment absorbed dose in passive carbon-ion and proton radiotherapies were measured using a rem meter, WENDI-II at two carbon-ion radiotherapy facilities and four proton radiotherapy facilities in Japan. Our measured results showed that (1) neutron ambient dose equivalent in carbon-ion radiotherapy is lower than that in proton radiotherapy, and (2) the difference to the measured neutron ambient dose equivalents among the facilities is within a factor of 3 depending on the operational beam setting used at the facility and the arrangement of the beam line, regardless of the method for making a laterally uniform irradiation field: the double scattering method or the single-ring wobbling method. The reoptimization of the beam line in passive particle radiotherapy is an effective way to reduce the risk of secondary cancer because installing an adjustable precollimator and designing the beam line devices with consideration of their material, thickness and location, etc., can significantly reduce the neutron exposure. It was also found that the neutron ambient dose equivalent in passive particle radiotherapy is equal to or less than that in the photon radiotherapy. This result means that not only scanning particle radiotherapy but also passive particle radiotherapy can provide reduced exposure to normal tissues around the target volume without an accompanied increase in total body dose.
It is important for proton therapy to calculate dose distributions accurately in treatment planning. Dose calculations in the body for treatment planning are converted to dose distributions in water, and the converted calculations are then generally evaluated by the dose measurements in water. In this paper, proton dose calculations were realized for a phantom simulating a clinical heterogeneity. Both dose calculations in the phantom calculated by two dose calculation methods, the range-modulated pencil beam algorithm (RMPBA) and the simplified Monte Carlo (SMC) method, and dose calculations converted to dose distributions in water by the same two methods were verified experimentally through comparison with measured distributions, respectively. For the RMPBA, though the converted calculations in water agreed moderately well with the measured ones, the calculated results in the actual phantom produced large errors. This meant that dose calculations in treatment planning should be evaluated by the dose measurements not in water but in the body with heterogeneity. On the other hand, the results calculated in the phantom, even by the less rigorous SMC method, reproduced the experimental ones well. This finding showed that actual dose distributions in the body should be predicted by the SMC method.
Treatment planning for proton tumor therapy requires a fast and accurate dose-calculation method. We have implemented a simplified Monte Carlo (SMC) method in the treatment planning system of the National Cancer Center Hospital East for the double-scattering beam delivery scheme. The SMC method takes into account the scattering effect in materials more accurately than the pencil beam algorithm by tracking individual proton paths. We confirmed that the SMC method reproduced measured dose distributions in a heterogeneous slab phantom better than the pencil beam method. When applied to a complex anthropomorphic phantom, the SMC method reproduced the measured dose distribution well, satisfying an accuracy tolerance of 3 mm and 3% in the gamma index analysis. The SMC method required approximately 30 min to complete the calculation over a target volume of 500 cc, much less than the time required for the full Monte Carlo calculation. The SMC method is a candidate for a practical calculation technique with sufficient accuracy for clinical application.
We implemented the simplified Monte Carlo (SMC) method on graphics processing unit (GPU) architecture under the computer-unified device architecture platform developed by NVIDIA. The GPU-based SMC was clinically applied for four patients with head and neck, lung, or prostate cancer. The results were compared to those obtained by a traditional CPU-based SMC with respect to the computation time and discrepancy. In the CPU- and GPU-based SMC calculations, the estimated mean statistical errors of the calculated doses in the planning target volume region were within 0.5% rms. The dose distributions calculated by the GPU- and CPU-based SMCs were similar, within statistical errors. The GPU-based SMC showed 12.30-16.00 times faster performance than the CPU-based SMC. The computation time per beam arrangement using the GPU-based SMC for the clinical cases ranged 9-67 s. The results demonstrate the successful application of the GPU-based SMC to a clinical proton treatment planning.
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