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[en] Purpose: For electron cutouts of smaller sizes, it is necessary to verify electron cutout factors due to perturbations in electron scattering. Often, this requires a physical measurement using a small ion chamber, diode, or film. The purpose of this study is to develop a fast Monte Carlo based dose calculation framework that requires only a smart phone photograph of the cutout and specification of the SSD and energy to determine the electron cutout factor, with the ultimate goal of making this cloud-based calculation widely available to the medical physics community. Methods: The algorithm uses a pattern recognition technique to identify the corners of the cutout in the photograph as shown in Figure 1. It then corrects for variations in perspective, scaling, and translation of the photograph introduced by the user’s positioning of the camera. Blob detection is used to identify the portions of the cutout which comprise the aperture and the portions which are cutout material. This information is then used define physical densities of the voxels used in the Monte Carlo dose calculation algorithm as shown in Figure 2, and select a particle source from a pre-computed library of phase-spaces scored above the cutout. The electron cutout factor is obtained by taking a ratio of the maximum dose delivered with the cutout in place to the dose delivered under calibration/reference conditions. Results: The algorithm has been shown to successfully identify all necessary features of the electron cutout to perform the calculation. Subsequent testing will be performed to compare the Monte Carlo results with a physical measurement. Conclusion: A simple, cloud-based method of calculating electron cutout factors could eliminate the need for physical measurements and substantially reduce the time required to properly assure accurate dose delivery

[en] Purpose: We propose a workflow to improve access to stereotactic ablative radiation therapy (SABR) for rural patients. When implemented, a separate trip to the central facility for simulation can be eliminated. Two elements are required: (1) Fabrication of custom immobilization devices to match positioning on prior diagnostic CT (dxCT). (2) Remote radiation pre-planning on dxCT, with transfer of contours/plan to simulation CT (simCT) and initiation of treatment same-day or next day. In this retrospective study, we validated part 2 of the workflow using patients already treated with SABR for upper lobe lung tumors. Methods: Target/normal structures were contoured on dxCT; a plan was created and approved by the physician. Structures were transferred to simCT using deformable image registration and the plan was re-optimized on simCT. Plan quality was evaluated through comparison to gold-standard structures contoured on simCT and a gold-standard plan based on these structures. Workflow-generated plan quality in this study represents a worst-case scenario as these patients were not treated using custom immobilization to match dxCT position as would be done when the workflow is implemented clinically. Results: 5/6 plans created through the pre-planning workflow were clinically acceptable. For all six plans, the gold-standard GTV received full prescription dose, along with median PTV V95%=95.2% and median PTV D95%=95.4%. Median GTV DSC=0.80, indicating high degree of similarity between the deformed and gold-standard GTV contours despite small GTV sizes (mean=3.0cc). One outlier (DSC=0.49) resulted in inadequate PTV coverage (V95%=62.9%) in the workflow plan; in clinical practice, this mismatch between deformed/gold-standard GTV would be revised by the physician after deformable registration. For all patients, normal tissue doses were comparable to the gold-standard plan and well within constraints. Conclusion: Pre-planning SABR cases on diagnostic imaging generated clinically acceptable plans. Coupled with rapid-prototyped custom immobilization, this workflow may improve treatment access for rural patients.

[en] We propose a new type of treatment that employs a modulated tangential photon field to provide superior coverage of complex superficial targets when compared to other commonly employed methods, and drastically reduce dose to the underlying sensitive structures often present in these cases. TMAT plans were formulated for a set of four representative cases: 1. Scalp sarcoma, 2. Posterior chest-wall sarcoma, 3. Pleural mesothelioma with intact lung, 4. Chest-wall with deep inframammary nodes. For these cases, asymmetric jaw placement, angular limitations, and central isocenter placements were used to force optimization solutions with beam lines tangential to the body surface. When compared with unrestricted modulated arcs, the tangential arc scalp treatment reduced the max and mean doses delivered to the brain by 33Gy (from 55Gy to 22Gy) and 6Gy (from 14Gy to 8Gy), respectively. In the posterior chest wall case, the V10 for the ipsilateral lung was kept below 5% impressively while retaining the 45Gy target prescription coverage by over 97%. For the breast chest-wall case, the TMAT plan achieved reductions in high dose to the ipsilateral lung and heart by a factor of 2–3 when compared to classic, laterally opposed, tangents and reduced the V5 by 40% when compared to standard modulated arcs. TMAT has outperformed the conventional modalities of treatment for superficial lesions used in our clinic. We hope that with the advent of digitally controlled linear accelerators, we can uncover further benefits of this new technique and extend its applicability to a wider section of the patient population

[en] Purpose: The accuracy of dose calculation for lung stereotactic ablative radiotherapy (SABR) of small lesions critically depends on the proper modeling of the lateral scatter in heterogeneous media. In recent years, grid-based Boltzman solvers such as Acuros XB (AXB) have been introduced for enhanced modeling of radiation transport in heterogeneous media. The purpose of this study is to evaluate the dosimetric impact of dose calculation between AXB and convolution-superposition algorithms such as analytical anisotropic algorithm (AAA) for small lesion sizes and different beam energies. Methods: Five lung SABR VMAT cases with GTV ranged from 0.8cm to 2.5cm in diameter were studied. For each case, doses were calculated by AAA, AXB (V11031) and Monte Carlo simulation (MC) with the same plan parameters for 10MV and 6MV. The dose calculation accuracy were evaluated by comparing DVHs and dose distributions with MC as the benchmark. The accuracy of calculated dose was also validated by EBT3 film measurement with a field size of 3cmx3cm in a thorax phantom. Results: For 10MV and GTV less than 1cm, dose calculated by AXB agrees well with MC compared to AAA. Dose difference calculated with AXB and AAA could be up to 30%. For GTV greater than 2cm, calculation results of AXB and AAA agree within 5% in GTV. For 6MV, the difference between calculated doses by AXB and AAA is less 10% for GTV less than 1cm. Based on film measurements, lung dose was overestimated 10% and 20% by AAA for 6MV and 10MV. Conclusion: Lateral scatter and transport is modeled more accurately by AXB than AAA in heterogeneous media, especially for small field size and high energy beams. The accuracy depends on the assigned material in calculation. If grid-based Boltzman solvers or MC are not available for calculation, lower energy beams should be used for treatment

[en] Purpose: We propose a new type of treatment that employs a modulated and sliding tangential photon field to provide superior coverage of superficial targets when compared to other commonly employed methods while drastically reducing dose to the underlying sensitive structures often present in these cases. Methods: Modulated treatment plans were formulated for a set of three representative cases. The first was a revised treatment of a scalp sarcoma, while the second was a treatment of a right posterior chest wall sarcoma. For these cases, asymmetric jaw placement, angular limitations, and central isocenter placements were used to force the optimization algorithm into finding solutions with beamlines that were not perpendicular to the body surface. The final case targeted the chest wall of a breast cancer patient, in which standard treatments were compared to the use of modulated fields with multiple isocenters along the chest wall. Results: When compared with unrestricted modulated arcs, the tangential arc scalp treatment reduced the max and mean doses delivered to the brain by 33Gy (from 55 to 22Gy) and 6Gy (from 14Gy to 8Gy), respectively. In the right posterior chest wall case, the V10 in the ipsilateral lung was kept below 5% while retaining a Rx dose (45Gy) target coverage of over 97%. For the breast case, the modulated plan achieved reductions in high dose to the ipsilateral lung and heart by a factor of 2–3 when compared to classic laterally opposed tangents and reduced the V5 by 40% when compared to standard modulated arcs. Conclusion: Tangential modulated arc therapy has outperformed the conventional modalities of treatment for superficial lesions used in our clinic. We hope that with the advent of digitally controlled linear accelerators, we can uncover further benefits of this new technique and extend its applicability to a wider section of the patient population

[en] Purpose: Machine Performance Check (MPC) is a software application used to verify that the TrueBeam machine is operating within major specifications prior to treatment. Used in combination with a phantom named Isocal, it verifies beam output, beam uniformity, treatment isocenter size, coincidence of treatment and imaging isocenters, positioning accuracy of kV and MV imaging systems, accuracy of collimator and gantry rotation angle, positioning accuracy of jaws and MLC leafs, and couch positioning. The tests can be performed semi-automatically and requires approximately 10 minutes of machine time. It is the purpose of this study to report the performance of this program. Methods: A pre-release version of the MPC tool was installed on a Truebeam linac with 6D couch at our center. Baseline beam output measurements were taken for 5 photon beams (6–15 MV, 6 FFF, 10 FFF) and 5 electron beams (6–20 MeV). Deviations from the baseline output were subsequently recorded for several days and compared against independent measurements from a PTW farmer chamber and our daily QA device (Fluke Biomedical Tracker) as part of an ongoing evaluation. Results: The beam output deviations between the MPC and the PTW chamber measurements were within ±0.7% for photons beams and ±1.0% for electrons beams. This was similar to the tracker performance. There were some isolated incidents where the MPC measurements had unexplained spikes (>3%) that disappeared on a repeat measurement. MPC was also able to detect maximum positioning errors in the jaws (1.12 mm), MLCs (1.14 mm), and couch roll (0.11°). Conclusion: Overall, the ability of the MPC to monitor linac output stability was comparable to that of ionization chamber-based measurements. MPC also provided fast daily mechanical tests not currently available in the clinic. How best to utilize this previously unavailable data is still under investigation

[en] Purpose: Dosimetric verification of VMAT/SBRT is currently performed on one or two planes in a phantom with either film or array detectors. A robust and easy-to-use 3D dosimetric tool has been sought since the advent of conformal radiation therapy. Here we present such a strategy for independent 3D VMAT/SBRT plan verification system by a combined use of EPID and cloud-based Monte Carlo (MC) dose calculation. Methods: The 3D dosimetric verification proceeds in two steps. First, the plan was delivered with a high resolution portable EPID mounted on the gantry, and the EPID-captured gantry-angle-resolved VMAT/SBRT field images were converted into fluence by using the EPID pixel response function derived from MC simulations. The fluence was resampled and used as the input for an in-house developed Amazon cloud-based MC software to reconstruct the 3D dose distribution. The accuracy of the developed 3D dosimetric tool was assessed using a Delta4 phantom with various field sizes (square, circular, rectangular, and irregular MLC fields) and different patient cases. The method was applied to validate VMAT/SBRT plans using WFF and FFF photon beams (Varian TrueBeam STX). Results: It was found that the proposed method yielded results consistent with the Delta4 measurements. For points on the two detector planes, a good agreement within 1.5% were found for all the testing fields. Patient VMAT/SBRT plan studies revealed similar level of accuracy: an average γ-index passing rate of 99.2± 0.6% (3mm/3%), 97.4± 2.4% (2mm/2%), and 72.6± 8.4 % ( 1mm/1%). Conclusion: A valuable 3D dosimetric verification strategy has been developed for VMAT/SBRT plan validation. The technique provides a viable solution for a number of intractable dosimetry problems, such as small fields and plans with high dose gradient

[en] Purpose: Situated 20 miles from 5 major fault lines in California’s Bay Area, Stanford Universityhas a critical need for IT infrastructure planning to handle the high probability devastating earthquakes. Recently, a multi-million dollar project has been underway to overhaul Stanford’s radiation oncology information systems, maximizing planning system performance and providing true disaster recovery abilities. An overview of the project will be given with particular focus on lessons learned throughout the build. Methods: In this implementation, two isolated external datacenters provide geographical redundancy to Stanford’s main campus datacenter. Real-time mirroring is made of all data stored to our serial attached network (SAN) storage. In each datacenter, hardware/software virtualization was heavily implemented to maximize server efficiency and provide a robust mechanism to seamlessly migrate users in the event of an earthquake. System performance is routinely assessed through the use of virtualized data robots, able to log in to the system at scheduled times, perform routine planning tasks and report timing results to a performance dashboard. A substantial dose calculation framework (608 CPU cores) has been constructed as part of the implementation. Results: Migration to a virtualized server environment with a high performance SAN has resulted in up to a 45% speed up of common treatment planning tasks. Switching to a 608 core DCF has resulted in a 280% speed increase in dose calculations. Server tuning was found to further improved read/write performance by 20%. Disaster recovery tests are carried out quarterly and, although successful, remain time consuming to perform and verify functionality. Conclusion: Achieving true disaster recovery capabilities is possible through server virtualization, support from skilled IT staff and leadership. Substantial performance improvements are also achievable through careful tuning of server resources and disk read/write operations. Developing a streamlined method to comprehensively test failover is a key requirement to the system’s success

[en] Purpose: Accurate and fast dose calculation is a prerequisite of precision radiation therapy in modern photon and particle therapy. While Monte Carlo (MC) dose calculation provides high dosimetric accuracy, the drastically increased computational time hinders its routine use. Deterministic dose calculation methods are fast, but problematic in the presence of tissue density inhomogeneity. We leverage the useful features of deterministic methods and MC to develop a hybrid dose calculation platform with autonomous utilization of MC and deterministic calculation depending on the local geometry, for optimal accuracy and speed. Methods: Our platform utilizes a Geant4 based “localized Monte Carlo” (LMC) method that isolates MC dose calculations only to volumes that have potential for dosimetric inaccuracy. In our approach, additional structures are created encompassing heterogeneous volumes. Deterministic methods calculate dose and energy fluence up to the volume surfaces, where the energy fluence distribution is sampled into discrete histories and transported using MC. Histories exiting the volume are converted back into energy fluence, and transported deterministically. By matching boundary conditions at both interfaces, deterministic dose calculation account for dose perturbations “downstream” of localized heterogeneities. Hybrid dose calculation was performed for water and anthropomorphic phantoms. Results: We achieved <1% agreement between deterministic and MC calculations in the water benchmark for photon and proton beams, and dose differences of 2%–15% could be observed in heterogeneous phantoms. The saving in computational time (a factor ∼4–7 compared to a full Monte Carlo dose calculation) was found to be approximately proportional to the volume of the heterogeneous region. Conclusion: Our hybrid dose calculation approach takes advantage of the computational efficiency of deterministic method and accuracy of MC, providing a practical tool for high performance dose calculation in modern RT. The approach is generalizable to all modalities where heterogeneities play a large role, notably particle therapy.