Plan complexity metrics for head and neck VMAT competition plans.

Previous plan competitions have largely focused on dose metric assessments. However, whether the submitted plans were realistic and reasonable from a quality assurance (QA) perspective remains unclear. This study aimed to investigate the relationship between aperture-based plan complexity metrics (PCM) in volumetric modulated arc therapy (VMAT) competition plans and clinical treatment plans verified through patient-specific QA (PSQA). In addition, the association of PCMs with plan quality was examined. A head and neck (HN) plan competition was held for Japanese institutions from June 2019 to July 2019, in which 210 competition plans were submitted. Dose distribution quality was quantified based on dose-volume histogram (DVH) metrics by calculating the dose distribution plan score (DDPS). Differences in PCMs between the two VMAT treatment plan groups (HN plan competitions held in Japan and clinically accepted HN VMAT plans through PSQA) were investigated. The mean (± standard deviation) DDPS for the 98 HN competition plans was 158.5 ± 20.6 (maximum DDPS: 200). DDPS showed a weak correlation with PCMs with a maximum r of 0.45 for monitor unit (MU); its correlation with some PCMs was "very weak." Significant differences were found in some PCMs between plans with the highest 20% DDPSs and the remaining plans. The clinical VMAT and competition plans revealed similar distributions for some PCMs. Deviations in PCMs for the two groups were comparable, indicating considerable variability among planners regarding planning skills. The plan complexity for HN VMAT competition plans increased for high-quality plans, as shown by the dose distribution. Direct comparison of PCMs between competition plans and clinically accepted plans showed that the submitted HN VMAT competition plans were realistic and reasonable from the QA perspective. This evaluation may provide a set of criteria for evaluating plan quality in plan competitions.

[Establishment of an On-Site Dosimetric Audit Program with a Plastic Phantom].

The quality assurance (QA) of the output constancy of linear accelerators (linacs) is one of the most basic items for radiation therapy. The necessity and demand of the dosimetric audit is on the rise. We aimed at establishing an on-site dosimetric audit program with a plastic phantom in order to enrich the availability of dosimetric audit in Japan. By this, we developed and evaluated an on-site audit program in multiple institutions in 120 cases for photon and electron standard dosimetry and intensity modulated radiation therapy (IMRT) condition. For photon standard dosimetry, we evaluated the accuracies of institutional measured absorbed dose in 50 cases by this on-site audit program. For the electron standard dosimetry, we evaluated the accuracies of institutional measured absorbed dose in 25 cases. For IMRT condition, we evaluated the accuracies of the institutional calculated dose in radiation treatment planning systems in 45 cases. The agreements of the measured absorbed dose between our audit and the institutions were within±1.1% for photon standard dosimetry. The agreements of the measured absorbed dose between our audit and the institutions were within±2.1% for electron standard dosimetry. The agreements between the measured absorbed dose of our audit and the institutional calculated dose were within±2.1% for IMRT condition. We established an on-site dosimetric audit program with a plastic phantom and this program is suitable with tight criteria similar to criteria required for clinical QA.

Evaluation of differences and dosimetric influences of beam models using golden and multi-institutional measured beam datasets in radiation treatment planning systems.

PURPOSE: The beam model in radiation treatment planning systems (RTPSs) plays a crucial role in determining the accuracy of calculated dose distributions. The purpose of this study was to ascertain differences in beam models and their dosimetric influences when a golden beam dataset (GBD) and multi-institution measured beam datasets (MBDs) are used for beam modeling in RTPSs. METHODS: The MBDs collected from 15 institutions, and the MBDs' beam models, were compared with a GBD, and the GBD's beam model, for Varian TrueBeam linear accelerator. The calculated dose distributions of the MBDs' beam models were compared with those of the GBD's beam model for simple geometries in a water phantom. Calculated dose distributions were similarly evaluated in volumetric modulated arc therapy (VMAT) plans for TG-119 C-shape and TG-244 head and neck, at several dose constraints of the planning target volumes (PTVs), and organs at risk. RESULTS: The agreements of the MBDs with the GBD were almost all within ±1%. The calculated dose distributions for simple geometries in a water phantom also closely corresponded between the beam models of GBD and MBDs. Nevertheless, there were considerable differences between the beam models. The maximum differences between the mean energy of the energy spectra of GBD and MBDs were -0.12 MeV (-10.5%) in AcurosXB (AXB, Eclipse) and 0.11 MeV (7.7%) in collapsed cone convolution (CCC, RayStation). The differences in the VMAT calculated dose distributions varied for each dose region, plan, X-ray energy, and dose calculation algorithm. The ranges of the differences in the dose constraints were -5.6% to 3.0% for AXB and -24.1% to 2.8% for CCC. In several VMAT plans, the calculated dose distributions of GBD's beam model tended to be lower in high-dose regions and higher in low-dose regions than those of the MBDs' beam models. CONCLUSIONS: We found that small differences in beam data have large impacts on the beam models, and on calculated dose distributions in clinical VMAT plan, even if beam data correspond within ±1%. GBD's beam model was not a representative beam model. The beam models of GBD and MBDs and their calculated dose distributions under clinical conditions were significantly different. These differences are most likely due to the extensive variation in the beam models, reflecting the characteristics of beam data. The energy spectrum and radial energy in the beam model varied in a wide range, even if the differences in the beam data were <±1%. To minimize the uncertainty of the calculated dose distributions in clinical plans, it was best to use the institutional MBD for beam modeling, or the beam model that ensures the accuracy of calculated dose distributions.

Density scaling of phantom materials for a 3D dose verification system.

In this study, the optimum density scaling factors of phantom materials for a commercially available three-dimensional (3D) dose verification system (Delta4) were investigated in order to improve the accuracy of the calculated dose distributions in the phantom materials. At field sizes of 10 × 10 and 5 × 5 cm2 with the same geometry, tissue-phantom ratios (TPRs) in water, polymethyl methacrylate (PMMA), and Plastic Water Diagnostic Therapy (PWDT) were measured, and TPRs in various density scaling factors of water were calculated by Monte Carlo simulation, Adaptive Convolve (AdC, Pinnacle3 ), Collapsed Cone Convolution (CCC, RayStation), and AcurosXB (AXB, Eclipse). Effective linear attenuation coefficients (µeff ) were obtained from the TPRs. The ratios of µeff in phantom and water ((µeff )pl,water ) were compared between the measurements and calculations. For each phantom material, the density scaling factor proposed in this study (DSF) was set to be the value providing a match between the calculated and measured (µeff )pl,water . The optimum density scaling factor was verified through the comparison of the dose distributions measured by Delta4 and calculated with three different density scaling factors: the nominal physical density (PD), nominal relative electron density (ED), and DSF. Three plans were used for the verifications: a static field of 10 × 10 cm2 and two intensity modulated radiation therapy (IMRT) treatment plans. DSF were determined to be 1.13 for PMMA and 0.98 for PWDT. DSF for PMMA showed good agreement for AdC and CCC with 6 MV x ray, and AdC for 10 MV x ray. DSF for PWDT showed good agreement regardless of the dose calculation algorithms and x-ray energy. DSF can be considered one of the references for the density scaling factor of Delta4 phantom materials and may help improve the accuracy of the IMRT dose verification using Delta4.

Variation of the prescription dose using the analytical anisotropic algorithm in lung stereotactic body radiation therapy.

PURPOSE: The aim of the present investigation was to evaluate the dosimetric variation regarding the analytical anisotropic algorithm (AAA) relative to other algorithms in lung stereotactic body radiation therapy (SBRT). We conducted a multi-institutional study involving six institutions using a secondary check program and compared the AAA to the Acuros XB (AXB) in two institutions. METHODS: All lung SBRT plans (128 patients) were generated using the AAA, pencil beam convolution with the Batho (PBC-B) and adaptive convolve (AC). All institutions used the same secondary check program (simple MU analysis [SMU]) implemented by a Clarkson-based dose calculation algorithm. Measurement was performed in a heterogeneous phantom to compare doses using the three different algorithms and the SMU for the measurements. A retrospective analysis was performed to compute the confidence limit (CL; mean±2SD) for the dose deviation between the AAA, PBC, AC and SMU. The variations between the AAA and AXB were evaluated in two institutions, then the CL was acquired. RESULTS: In comparing the measurements, the AAA showed the largest systematic dose error (3%). In calculation comparisons, the CLs of the dose deviation were 8.7±9.9% (AAA), 4.2±3.9% (PBC-B) and 5.7±4.9% (AC). The CLs of the dose deviation between the AXB and the AAA were 1.8±1.5% and -0.1±4.4%, respectively, in the two institutions. CONCLUSIONS: The CL of the AAA showed much larger variation than the other algorithms. Relative to the AXB, larger systematic and random deviations still appeared. Thus, care should be taken in the use of AAA for lung SBRT.

Multi-institutional Validation Study of Commercially Available Deformable Image Registration Software for Thoracic Images.

PURPOSE: To assess the accuracy of the commercially available deformable image registration (DIR) software for thoracic images at multiple institutions. METHODS AND MATERIALS: Thoracic 4-dimensional (4D) CT images of 10 patients with esophageal or lung cancer were used. Datasets for these patients were provided by DIR-lab (dir-lab.com) and included a coordinate list of anatomic landmarks (300 bronchial bifurcations) that had been manually identified. Deformable image registration was performed between the peak-inhale and -exhale images. Deformable image registration error was determined by calculating the difference at each landmark point between the displacement calculated by DIR software and that calculated by the landmark. RESULTS: Eleven institutions participated in this study: 4 used RayStation (RaySearch Laboratories, Stockholm, Sweden), 5 used MIM Software (Cleveland, OH), and 3 used Velocity (Varian Medical Systems, Palo Alto, CA). The ranges of the average absolute registration errors over all cases were as follows: 0.48 to 1.51 mm (right-left), 0.53 to 2.86 mm (anterior-posterior), 0.85 to 4.46 mm (superior-inferior), and 1.26 to 6.20 mm (3-dimensional). For each DIR software package, the average 3-dimensional registration error (range) was as follows: RayStation, 3.28 mm (1.26-3.91 mm); MIM Software, 3.29 mm (2.17-3.61 mm); and Velocity, 5.01 mm (4.02-6.20 mm). These results demonstrate that there was moderate variation among institutions, although the DIR software was the same. CONCLUSIONS: We evaluated the commercially available DIR software using thoracic 4D-CT images from multiple centers. Our results demonstrated that DIR accuracy differed among institutions because it was dependent on both the DIR software and procedure. Our results could be helpful for establishing prospective clinical trials and for the widespread use of DIR software. In addition, for clinical care, we should try to find the optimal DIR procedure using thoracic 4D-CT data.