Monte Carlo evaluation of RapidArc oropharynx treatment planning strategies for sparing of midline structures

Optimizing volumetric modulated arc therapy prostate planning using an automated Fine-Tuning process through dynamic adjustment of optimization parameters

In radiotherapy treatment planning, optimization is essential for achieving the most favorable plan by adjusting optimization criteria. This study introduced an innovative approach to automatically fine-tune optimization parameters for volumetric modulated arc therapy prostate planning, ensuring all constraints were met. A knowledge-based planning model was invoked, and the fine-tuning process was applied through an in-house developed script. Among 25 prostate plans, this fine-tuning increased the number of plans meeting all constraints from 10/25 to 22/25, with a reduction in mean monitor units per gray without increasing plan's complexity. This automation improved efficiency by saving time and resources in treatment planning.

Maintaining dosimetric quality when switching to a Monte Carlo dose engine for head and neck volumetric-modulated arc therapy planning

Head and neck cancers present challenges in radiation treatment planning due to the large number of critical structures near the target(s) and highly heterogeneous tissue composition. While Monte Carlo (MC) dose calculations currently offer the most accurate approximation of dose deposition in tissue, the switch to MC presents challenges in preserving the parameters of care. The differences in dose‐to‐tissue were widely discussed in the literature, but mostly in the context of recalculating the existing plans rather than reoptimizing with the MC dose engine. Also, the target dose homogeneity received less attention. We adhere to strict dose homogeneity objectives in clinical practice. In this study, we started with 21 clinical volumetric‐modulated arc therapy (VMAT) plans previously developed in Pinnacle treatment planning system. Those plans were recalculated “as is” with RayStation (RS) MC algorithm and then reoptimized in RS with both collapsed cone (CC) and MC algorithms. MC statistical uncertainty (0.3%) was selected carefully to balance the dose computation time (1–2 min) with the planning target volume (PTV) dose‐volume histogram (DVH) shape approaching that of a “noise‐free” calculation. When the hot spot in head and neck MC‐based treatment planning is defined as dose to 0.03 cc, it is exceedingly difficult to limit it to 105% of the prescription dose, as we were used to with the CC algorithm. The average hot spot after optimization and calculation with RS MC was statistically significantly higher compared to Pinnacle and RS CC algorithms by 1.2 and 1.0 %, respectively. The 95% confidence interval (CI) observed in this study suggests that in most cases a hot spot of ≤107% is achievable. Compared to the 95% CI for the previous clinical plans recalculated with RS MC “as is” (upper limit 108%), in real terms this result is at least as good or better than the historic plans.

Feasibility of a GATE Monte Carlo platform in a clinical pretreatment QA system for VMAT treatment plans using TrueBeam with an HD120 multileaf collimator

Purpose

To evaluate the quality of patient‐specific complicated treatment plans, including commercialized treatment planning systems (TPS) and commissioned beam data, we developed a process of quality assurance (QA) using a Monte Carlo (MC) platform. Specifically, we constructed an interface system that automatically converts treatment plan and dose matrix data in digital imaging and communications in medicine to an MC dose‐calculation engine. The clinical feasibility of the system was evaluated.

Materials and Methods

A dose‐calculation engine based on GATE v8.1 was embedded in our QA system and in a parallel computing system to significantly reduce the computation time. The QA system automatically converts parameters in volumetric‐modulated arc therapy (VMAT) plans to files for dose calculation using GATE. The system then calculates dose maps. Energies of 6 MV, 10 MV, 6 MV flattening filter free (FFF), and 10 MV FFF from a TrueBeam with HD120 were modeled and commissioned. To evaluate the beam models, percentage depth dose (PDD) values, MC calculation profiles, and measured beam data were compared at various depths (D_max, 5 cm, 10 cm, and 20 cm), field sizes, and energies. To evaluate the feasibility of the QA system for clinical use, doses measured for clinical VMAT plans using films were compared to dose maps calculated using our MC‐based QA system.

Results

A LINAC QA system was analyzed by PDD and profile according to the secondary collimator and multileaf collimator (MLC). Values for MC calculations and TPS beam data obtained using CC13 ion chamber (IBA Dosimetry, Germany) were consistent within 1.0%. Clinical validation using a gamma index was performed for VMAT treatment plans using a solid water phantom and arbitrary patient data. The gamma evaluation results (with criteria of 3%/3 mm) were 98.1%, 99.1%, 99.2%, and 97.1% for energies of 6 MV, 10 MV, 6 MV FFF, and 10 MV FFF, respectively.

Conclusions

We constructed an MC‐based QA system for evaluating patient treatment plans and evaluated its feasibility in clinical practice. We observed robust agreement between dose calculations from our QA system and measurements for VMAT plans. Our QA system could be useful in other clinical settings, such as small‐field SRS procedures or analyses of secondary cancer risk, for which dose calculations using TPS are difficult to verify.

The effects of the orthopedic metal artifact reduction (O-MAR) algorithm on contouring and dosimetry of head and neck radiotherapy patients

Metallic objects, such as dental fillings, cause artifacts in computed tomography (CT) scans. We quantify the contouring and dosimetric effects of Orthopedic Metal Artifact Reduction (O-MAR), in head and neck radiotherapy. The ease of organ contouring was assessed by having a radiation oncologist identify the CT data set with or without O-MAR for each of 28 patients that was easier to contour. The effect on contouring was quantified further by having the physician recontour parotid glands, previously drawn by him on the O-MAR scans, on uncorrected scans, and calculating the Dice coefficent (a measure of overlap) for the contours. Radiotherapy plans originally generated on scans reconstructed with O-MAR were recalculated on scans without metal artifact correction. The study was done using the Analytical Anisotropic Algorithm (AAA) dose calculation algorithm. The 15 patients with a planning target volume (PTV) extending to the same slice as the artifacts were used for this part of the study. The normal tissue doses were not significantly affected. The PTV mean dose and V95 were not affected, but the cold spots became less severe in the O-MAR corrected plans, with the minimum point dose on average being 4.1% higher. In 79% of the cases, the radiation oncologist identified the O-MAR scan as easier to contour; in 11% he chose the uncorrected scan and in 11% the scans were judged to have equal quality. A total of nine parotid glands (on both scans-18 contours in total) in 5 patients were recontoured. The average Dice coefficient for parotids drawn with and without O-MAR was found to be 0.775 +/- 0.045. The O-MAR algorithm does not produce a significant dosimetric effect in head and neck plans when using the AAA dose calculation algorithm. It can therefore be used for improved contouring accuracy without updating the critical structure tolerance doses and target coverage expectations.

Penalization of aperture complexity in inversely planned volumetric modulated arc therapy

PURPOSE

Apertures obtained during volumetric modulated arc therapy (VMAT) planning can be small and irregular, resulting in dosimetric inaccuracies during delivery. Our purpose is to develop and integrate an aperture-regularization objective function into the optimization process for VMAT, and to quantify the impact of using this objective function on dose delivery accuracy and optimized dose distributions.

METHODS

An aperture-based metric ("edge penalty") was developed that penalizes complex aperture shapes based on the ratio of MLC side edge length and aperture area. To assess the utility of the metric, VMAT plans were created for example paraspinal, brain, and liver SBRT cases with and without incorporating the edge penalty in the cost function. To investigate the dose calculation accuracy, Gafchromic EBT2 film was used to measure the 15 highest weighted apertures individually and as a composite from each of two paraspinal plans: one with and one without the edge penalty applied. Films were analyzed using a triple-channel nonuniformity correction and measurements were compared directly to calculations.

RESULTS

Apertures generated with the edge penalty were larger, more regularly shaped and required up to 30% fewer monitor units than those created without the edge penalty. Dose volume histogram analysis showed that the changes in doses to targets, organs at risk, and normal tissues were negligible. Edge penalty apertures that were measured with film for the paraspinal plan showed a notable decrease in the number of pixels disagreeing with calculation by more than 10%. For a 5% dose passing criterion, the number of pixels passing in the composite dose distributions for the non-edge penalty and edge penalty plans were 52% and 96%, respectively. Employing gamma with 3% dose/1 mm distance criteria resulted in a 79.5% (without penalty)/95.4% (with penalty) pass rate for the two plans. Gradient compensation of 3%/1 mm resulted in 83.3%/96.2% pass rates.

CONCLUSIONS

The use of the edge penalty during optimization has the potential to markedly improve dose delivery accuracy for VMAT plans while still maintaining high quality optimized dose distributions. The penalty regularizes aperture shape and improves delivery efficiency.

Experimental validation of deterministic Acuros XB algorithm for IMRT and VMAT dose calculations with the Radiological Physics Center's head and neck phantom

PURPOSE

The purpose of this study was to verify the dosimetric performance of Acuros XB (AXB), a grid-based Boltzmann solver, in intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT).

METHODS

The Radiological Physics Center (RPC) head and neck (H&N) phantom was used for all calculations and measurements in this study. Clinically equivalent IMRT and VMAT plans were created on the RPC H&N phantom in the Eclipse treatment planning system (version 10.0) by using RPC dose prescription specifications. The dose distributions were calculated with two different algorithms, AXB 11.0.03 and anisotropic analytical algorithm (AAA) 10.0.24. Two dose report modes of AXB were recorded: dose-to-medium in medium (D(m,m)) and dose-to-water in medium (D(w,m)). Each treatment plan was delivered to the RPC phantom three times for reproducibility by using a Varian Clinac iX linear accelerator. Absolute point dose and planar dose were measured with thermoluminescent dosimeters (TLDs) and GafChromic® EBT2 film, respectively. Profile comparison and 2D gamma analysis were used to quantify the agreement between the film measurements and the calculated dose distributions from both AXB and AAA. The computation times for AAA and AXB were also evaluated.

RESULTS

Good agreement was observed between measured doses and those calculated with AAA or AXB. Both AAA and AXB calculated doses within 5% of TLD measurements in both the IMRT and VMAT plans. Results of AXB_D(m,m) (0.1% to 3.6%) were slightly better than AAA (0.2% to 4.6%) or AXB_D(w,m) (0.3% to 5.1%). The gamma analysis for both AAA and AXB met the RPC 7%/4 mm criteria (over 90% passed), whereas AXB_D(m,m) met 5%/3 mm criteria in most cases. AAA was 2 to 3 times faster than AXB for IMRT, whereas AXB was 4-6 times faster than AAA for VMAT.

CONCLUSIONS

AXB was found to be satisfactorily accurate when compared to measurements in the RPC H&N phantom. Compared with AAA, AXB results were equal to or better than those obtained with film measurements for IMRT and VMAT plans. The AXB_D(m,m) reporting mode was found to be closer to TLD and film measurements than was the AXB_D(w,m) mode. AXB calculation time was found to be significantly shorter (× 4) than AAA for VMAT.

Impact of the calculation resolution of AAA for small fields and RapidArc treatment plans

PURPOSE

To investigate the impact of the calculation resolution of the anisotropic analytical algorithms (AAA) for a variety of small fields in homogeneous and heterogeneous media and for RapidArc plans.

METHODS

Dose distributions calculated using AAA version 8.6.15 (AAA8) and 10.0.25 (AAA10) were compared to measurements performed with GafChromic EBT film, using phantoms made of polystyrene or a combination of polystyrene and cork. The accuracy of the algorithms calculated using grid resolutions of 2.5 and 1.0 mm was investigated for different field sizes, and for a limited selection of RapidArc plans (head and neck, small meningioma, and lung). Additional plans were optimized to create excessive multileaf collimator modulation and measured on a homogenous phantom. Gamma evaluation criterion of 3% dose difference and 2- or 1-mm distance to agreement (DTA) were applied to evaluate the accuracy of the algorithms.

RESULTS

For fields < or = 3 x 3 cm2, both versions of AAA predicted lower peak doses and broader penumbra widths than the measurements. However, AAA10 and a finer calculation grid improved the agreement. For RapidArc plans with many small multileaf collimator (MLC) segments and relatively high number of monitor units (MU), AAA8 failed to identify small dose peaks within the target. Both versions performed better in polystyrene than in cork. In homogeneous cork layers, AAA8 underestimated the average target dose for a clinical lung plan. This was improved with AAA10 calculated using a 1 mm grid.

CONCLUSIONS

AAA10 improves the accuracy of dose calculations, and calculation grid of 1.0 mm is superior to using 2.5 mm, although calculation times increased by factor of 5. A suitable upper MU constraint should be assigned during optimization to avoid plans with high modulation. For plans with a relative high number of monitor units, calculations using 1 mm grid resolution are recommended. For planning target volume (PTV) which contains relatively large area of low density tissue, users should be aware of possible dose underestimation in the low density region and recalculation with AAA10 grid 1.0 mm is recommended.

Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure

Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on-demand from a third party, is a new approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC package in a commercial cloud environment. Launched from a single local computer with Internet access, a Python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47× speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed.

Dosimetric validation of Acuros XB with Monte Carlo methods for photon dose calculations

PURPOSE

The dosimetric accuracy of the recently released Acuros XB advanced dose calculation algorithm (Varian Medical Systems, Palo Alto, CA) is investigated for single radiation fields incident on homogeneous and heterogeneous geometries, and a comparison is made to the analytical anisotropic algorithm (AAA).

METHODS

Ion chamber measurements for the 6 and 18 MV beams within a range of field sizes (from 4.0 x 4.0 to 30.0 x 30.0 cm2) are used to validate Acuros XB dose calculations within a unit density phantom. The dosimetric accuracy of Acuros XB in the presence of lung, low-density lung, air, and bone is determined using BEAMnrc/DOSXYZnrc calculations as a benchmark. Calculations using the AAA are included for reference to a current superposition/convolution standard.

RESULTS

Basic open field tests in a homogeneous phantom reveal an Acuros XB agreement with measurement to within +/- 1.9% in the inner field region for all field sizes and energies. Calculations on a heterogeneous interface phantom were found to agree with Monte Carlo calculations to within +/- 2.0% (sigmaMC = 0.8%) in lung (p = 0.24 g cm(-3)) and within +/- 2.9% (sigmaMC = 0.8%) in low-density lung (p = 0.1 g cm(-3)). In comparison, differences of up to 10.2% and 17.5% in lung and low-density lung were observed in the equivalent AAA calculations. Acuros XB dose calculations performed on a phantom containing an air cavity (p = 0.001 g cm(-3)) were found to be within the range of +/- 1.5% to +/- 4.5% of the BEAMnrc/DOSXYZnrc calculated benchmark (sigmaMC = 0.8%) in the tissue above and below the air cavity. A comparison of Acuros XB dose calculations performed on a lung CT dataset with a BEAMnrc/DOSXYZnrc benchmark shows agreement within +/- 2%/2mm and indicates that the remaining differences are primarily a result of differences in physical material assignments within a CT dataset.

CONCLUSIONS

By considering the fundamental particle interactions in matter based on theoretical interaction cross sections, the Acuros XB algorithm is capable of modeling radiotherapy dose deposition with accuracy only previously achievable with Monte Carlo techniques.