2 resultados para Ion beam analysis

em DigitalCommons@The Texas Medical Center


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Although frequently cured of Hodgkin lymphoma, adolescents and young adults can develop radiation induced second cancers. These patients could potentially benefit from scanned ion radiotherapy yet likely would require motion mitigation strategies. In theory, four-dimensional (4D) optimization of ion beam fields for individual motion states of respiration can enable superior sparing of healthy tissue near moving targets, compared to other motion mitigation strategies. Furthermore, carbon-ion therapy can sometimes provide greater relative biological effectiveness (RBE) for cell sterilization in a target but nearly equivalent RBE in tissue upstream of the target, compared to proton therapy. Thus, we expected that for some patients with Hodgkin lymphoma, carbon-ion therapy would reduce the predicted risk of second cancer incidence in the breast compared with proton therapy. The purpose of this work was to determine whether 4D-optimized carbon-ion therapy would significantly reduce the predicted risk of radiation induced second cancers in the breast for female Hodgkin lymphoma patients while preserving tumor control compared with proton therapy. To achieve our goals, we first investigated whether 4D-optimized carbon beam tracking could reduce dose to volumes outside a moving target compared with 3D-optimized carbon beam tracking while preserving target dose coverage. To understand the reliability of scanned carbon beam tracking, we studied the robustness of dose distributions in thoracic targets to uncertainties in patient motion. Finally, we investigated whether using carbon-ion therapy instead of proton therapy would significantly reduce the predicted risk of second cancer in the breast for a sample of Hodgkin lymphoma patients. We found that 4D-optimized ion beam tracking therapy can reduce the maximum dose to critical structures near a moving target by as much as 53%, compared to 3D-optimized ion beam tracking therapy. We validated these findings experimentally using a scanned carbon ion synchrotron and a motion phantom. We found scanned carbon beam tracking to be sensitive to a number of motion uncertainties, most notably phase delays in tracking, systematic spatial errors, and interfractional motion changes. Our findings indicate that a lower risk of second cancer in the breast might be expected for some Hodgkin lymphoma patients using carbon-ion therapy instead of proton therapy. For our reference scenario, we found the ratio of risk to be 0.77 ± 0.35 for radiogenic breast cancer after carbon-ion therapy versus proton therapy. Our findings were dependent on the RBE values for tumor induction and the radiosensitivity of breast tissue, as well as the physical dose distribution.

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Proton therapy is growing increasingly popular due to its superior dose characteristics compared to conventional photon therapy. Protons travel a finite range in the patient body and stop, thereby delivering no dose beyond their range. However, because the range of a proton beam is heavily dependent on the tissue density along its beam path, uncertainties in patient setup position and inherent range calculation can degrade thedose distribution significantly. Despite these challenges that are unique to proton therapy, current management of the uncertainties during treatment planning of proton therapy has been similar to that of conventional photon therapy. The goal of this dissertation research was to develop a treatment planning method and a planevaluation method that address proton-specific issues regarding setup and range uncertainties. Treatment plan designing method adapted to proton therapy: Currently, for proton therapy using a scanning beam delivery system, setup uncertainties are largely accounted for by geometrically expanding a clinical target volume (CTV) to a planning target volume (PTV). However, a PTV alone cannot adequately account for range uncertainties coupled to misaligned patient anatomy in the beam path since it does not account for the change in tissue density. In order to remedy this problem, we proposed a beam-specific PTV (bsPTV) that accounts for the change in tissue density along the beam path due to the uncertainties. Our proposed method was successfully implemented, and its superiority over the conventional PTV was shown through a controlled experiment.. Furthermore, we have shown that the bsPTV concept can be incorporated into beam angle optimization for better target coverage and normal tissue sparing for a selected lung cancer patient. Treatment plan evaluation method adapted to proton therapy: The dose-volume histogram of the clinical target volume (CTV) or any other volumes of interest at the time of planning does not represent the most probable dosimetric outcome of a given plan as it does not include the uncertainties mentioned earlier. Currently, the PTV is used as a surrogate of the CTV’s worst case scenario for target dose estimation. However, because proton dose distributions are subject to change under these uncertainties, the validity of the PTV analysis method is questionable. In order to remedy this problem, we proposed the use of statistical parameters to quantify uncertainties on both the dose-volume histogram and dose distribution directly. The robust plan analysis tool was successfully implemented to compute both the expectation value and its standard deviation of dosimetric parameters of a treatment plan under the uncertainties. For 15 lung cancer patients, the proposed method was used to quantify the dosimetric difference between the nominal situation and its expected value under the uncertainties.