The objective of this study was to examine the use of proton pencil beam scanning for the treatment of moving lung tumors. A single-field uniform dose proton pencil beam scanning (PBS) plan was generated for the standard thorax phantom designed by the Imaging and Radiation Oncology Core (IROC) Houston QA Center. Robust optimization, including range and setup uncertainties as well as volumetric repainting, was used for the plan. Patient-specific quality assurance (QA) measurements were performed using both a water tank and a custom heterogeneous QA phantom. A custom moving phantom was used to find the optimal number of volumetric repainting. Both analytical and Monte Carlo (MC) algorithms were used for dose calculation and their accuracies were compared with actual measurements. A single ionization chamber, a 2-dimensional ionization chamber array, thermoluminescent dosimeters (TLDs), and films were used for dose measurements. The optimal number of volumetric repainting was found to be 4 times in our system. The mean dose overestimations on a moving target by analytical and MC algorithms based on a time-averaged computed tomography (CT) image of the phantom were found to be 4.8% and 2.4%, respectively. The mean gamma indexes for analytical and MC algorithms were 91% and 96%, respectively. The MC dose algorithm calculation was found to have a better agreement with measurements compared with the analytical algorithm. When treating moving lung tumors using proton PBS, the techniques of robust optimization, volumetric repainting, and MC dose calculation were found effective. Extra care needs to be taken when an analytical dose calculation algorithm is used.

Purpose This study aimed to evaluate the effectiveness of four-dimensional (4D) robust optimization for proton pencil-beam scanning (PBS) treatment of lung tumors. Patients and methods In seven patients with lung cancer, proton beam therapy was planned using 4D robust optimization over 4D computed tomography (CT) data sets. The gross target volume (GTV) was contoured based on individual breathing phases, and a 5-mm expansion was used to generate the clinical target volume (CTV) for each phase. The 4D optimization was conducted directly on the 4D CT data set. The robust optimization settings included a CT Hounsfield unit (HU) uncertainty of 4% and a setup uncertainty of 5 mm to obtain the CTV. Additional target dose objectives such as those for the internal target volume (ITV) as well as the organ-at-risk (OAR) dose requirements were placed on the average CT. For comparison, three-dimensional (3D) robust optimization was also performed on the average CT. An additional verification 4D CT was performed to verify plan robustness against inter-fractional variations. Results Target coverages were generally higher for 4D optimized plans. The difference was most pronounced for ITV V70Gy when evaluating individual breathing phases. The 4D optimized plans were shown to be able to maintain the ITV coverage at full prescription, while 3D optimized plans could not. More importantly, this difference in ITV V70Gy between the 4D and 3D optimized plans was also consistently observed when evaluating the verification 4D CT, indicating that the 4D optimized plans were more robust against inter-fractional variations. Less difference was seen between the 4D and 3D optimized plans in the lungs criteria: V5Gy and V20Gy. Conclusion The proton PBS treatment plans optimized directly on the 4D CT were shown to be more robust when compared to those optimized on a regular 3D CT. Robust 4D optimization can improve the target coverage for the proton PBS lung treatments.

The purpose of this study was to evaluate the differences between volumetric modulated arc therapy (VMAT) and intensity-modulated radiation therapy (IMRT) in the treatment of nasal cavity carcinomas. The treatment of 10 patients, who had completed IMRT treatment for resected tumors of the nasal cavity, was replanned with the Philips Pinnacle3 Version 9 treatment-planning system. The IMRT plans used a 9-beam technique whereas the VMAT (known as SmartArc) plans used a 3-arc technique. Both types of plans were optimized using Philips Pinnacle3 Direct Machine Parameter Optimization algorithm. IMRT and VMAT plans' quality was compared by evaluating the maximum, minimum, and mean doses to the target volumes and organs at risk, monitor units (MUs), and the treatment delivery time. Our results indicate that VMAT is capable of greatly reducing treatment delivery time and MUs compared with IMRT. The reduction of treatment delivery time and MUs can decrease the effects of intrafractional uncertainties that can occur because of patient movement during treatment delivery. VMAT's plans further reduce doses to critical structures that are in close proximity to the target volume.