K Bush

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.

Clinical significance of multi-leaf collimator positional errors for volumetric modulated arc therapy.

BACKGROUND AND PURPOSE Multi-leaf collimator (MLC) positional errors occur during intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) deliveries. The impact of such errors has been evaluated for IMRT but not VMAT. The purpose of this work is to understand how random and systematic VMAT MLC positional errors affect the patient dose distribution. MATERIALS AND METHODS Eight head and neck single arc (360°) VMAT treatment plans were created. Random and two types of systematic MLC errors were simulated for error magnitudes of 0.25, 0.5, 1, 2 and 5mm. The two types of systematic MLC errors were: (1) MLC banks are shifted in the same direction (left or right) and (2) MLC banks are shifted in opposing directions resulting in smaller or larger field shapes. The MLC errors were simulated, for all control points, on both banks of active MLC leaves only. RESULTS There is a linear correlation of MLC errors with gEUD for all error types. The gEUD dose sensitivities with MLC error for the PTV70 were -0.2, -0.9, -2.8 and 1.9 Gy/mm for random, systematic shift, systematic close and systematic open MLC errors, respectively. The sensitivity of VMAT plans to MLC positional errors was similar to those of IMRT plans with less than 50 segments but much less than those created for a step and shoot with more than 50 segments or sliding-window delivery technique. To maintain the PTV70 to within 2% would require that MLC open/close errors be within 0.6mm. CONCLUSIONS Radiation therapy centers should have adequate quality assurance programs in place to assess open/close MLC errors (i.e. leaf gap errors) as they tend to be more impactful than random or systematic MLC shift errors.

Direct aperture optimization for IMRT using Monte Carlo generated beamlets

This work introduces an EGSnrc-based Monte Carlo (MC) beamlet does distribution matrix into a direct aperture optimization (DAO) algorithm for IMRT inverse planning. The technique is referred to as Monte Carlo-direct aperture optimization (MC-DAO). The goal is to assess if the combination of accurate Monte Carlo tissue inhomogeneity modeling and DAO inverse planning will improve the dose accuracy and treatment efficiency for treatment planning. Several authors have shown that the presence of small fields and/or inhomogeneous materials in IMRT treatment fields can cause dose calculation errors for algorithms that are unable to accurately model electronic disequilibrium. This issue may also affect the IMRT optimization process because the dose calculation algorithm may not properly model difficult geometries such as targets close to low-density regions (lung, air etc.). A clinical linear accelerator head is simulated using BEAMnrc (NRC, Canada). A novel in-house algorithm subdivides the resulting phase space into 2.5 X 5.0 mm2 beamlets. Each beamlet is projected onto a patient-specific phantom. The beamlet dose contribution to each voxel in a structure-of-interest is calculated using DOSXYZnrc. The multileaf collimator (MLC) leaf positions are linked to the location of the beamlet does distributions. The MLC shapes are optimized using direct aperture optimization (DAO). A final Monte Carlo calculation with MLC modeling is used to compute the final dose distribution. Monte Carlo simulation can generate accurate beamlet dose distributions for traditionally difficult-to-calculate geometries, particularly for small fields crossing regions of tissue inhomogeneity. The introduction of DAO results in an additional improvement by increasing the treatment delivery efficiency. For the examples presented in this paper the reduction in the total number of monitor units to deliver is approximately 33% compared to fluence-based optimization methods.

Understanding the impact of RapidArc therapy delivery errors for prostate cancer

The purpose of this study is to simulate random and systematic RapidArc delivery errors for external beam prostate radiotherapy plans in order to determine the dose sensitivity for each error type. Ten prostate plans were created with a single 360° arc. The DICOM files for these treatment plans were then imported into an in‐house computer program that introduced delivery errors. Random and systematic gantry position (0.25°, 0.5°, 1°), monitor unit (MU) (1.25%, 2.5%, 5%), and multileaf collimator (MLC) position (0.5, 1, 2 mm) errors were introduced. The MLC errors were either random or one of three types of systematic errors, where the MLC banks moved in the same (MLC gaps remain unchanged) or opposing directions (increasing or decreasing the MLC gaps). The generalized equivalent uniform dose (gEUD) was calculated for the original plan and all treatment plans with errors introduced. The dose sensitivity for the cohort was calculated using linear regression for the gantry position, MU, and MLC position errors. Because there was a large amount of variability for systematic MLC position errors, the dose sensitivity of each plan was calculated and correlated with plan MU, mean MLC gap, and the percentage of MLC leaf gaps less than 1 and 2 cm for each individual plan. We found that random and systematic gantry position errors were relatively insignificant (< 0.1% gEUD change) for gantry errors up to 1°. Random MU errors were also insignificant, and systematic MU increases caused a systematic increase in gEUD. For MLC position errors, random MLC errors were relatively insignificant up to 2 mm as had been determined in previous IMRT studies. Systematic MLC shift errors caused a decrease of approximately −1% in the gEUD per mm. For systematic MLC gap open errors, the dose sensitivity was 8.2%/mm and for MLC gap close errors the dose sensitivity was −7.2%/mm. There was a large variability for MLC gap open/close errors for the ten RapidArc plans which correlated strongly with MU, mean gap width, and percentage of MLC gaps less than 1 or 2 cm. This study evaluates the magnitude of various simulated RapidArc delivery errors by calculating gEUED on various prostate plans. PACS numbers: 87.55.x, 87.55.D, 87.55.de, 87.55.dk

Azimuthal particle redistribution for the reduction of latent phase-space variance in Monte Carlo simulations

It is well known that the use of a phase space in Monte Carlo simulation introduces a baseline level of variance that cannot be suppressed through the use of standard particle recycling techniques. This variance (termed latent phase-space variance by Sempau et al) can be a significant limiting factor in achieving accurate, low-uncertainty dose scoring results, especially near the surface of a phantom. A BEAMnrc component module (MCTWIST) has been developed to reduce the presence of latent variance in phase-space-based Monte Carlo simulations by implementing azimuthal particle redistribution (APR). For each recycled use of a phase-space particle a random rotation about the beams central axis is applied, effectively utilizing cylindrical symmetry of the particle fluence and therefore providing a more accurate representation of the source. The MCTWIST module is unique in that no physical component is actually added to the accelerator geometry. Beam modifications are made by directly transforming particle characteristics outside of BEAMnrc/EGSnrc particle transport. Using MCTWIST, we have demonstrated a reduction in latent phase-space variance by more than a factor of 20, for a 10 x 10 cm(2) field, when compared to standard phase-space particle recycling techniques. The reduction in latent variance has enabled the achievement of dramatically smoother in-water dose profiles. This paper outlines the use of MCTWIST in Monte Carlo simulation and quantifies for the first time the latent variance reduction resulting from exploiting cylindrical phase-space symmetry.

A technique for generating phase-space-based Monte Carlo beamlets in radiotherapy applications.

As radiotherapy treatment planning moves toward Monte Carlo (MC) based dose calculation methods, the MC beamlet is becoming an increasingly common optimization entity. At present, methods used to produce MC beamlets have utilized a particle source model (PSM) approach. In this work we outline the implementation of a phase-space-based approach to MC beamlet generation that is expected to provide greater accuracy in beamlet dose distributions. In this approach a standard BEAMnrc phase space is sorted and divided into beamlets with particles labeled using the inheritable particle history variable. This is achieved with the use of an efficient sorting algorithm, capable of sorting a phase space of any size into the required number of beamlets in only two passes. Sorting a phase space of five million particles can be achieved in less than 8 s on a single-core 2.2 GHz CPU. The beamlets can then be transported separately into a patient CT dataset, producing separate dose distributions (doselets). Methods for doselet normalization and conversion of dose to absolute units of Gy for use in intensity modulated radiation therapy (IMRT) plan optimization are also described.

Assessing the dosimetric impact of real-time prostate motion during volumetric modulated arc therapy.

PURPOSE To develop a method for dose reconstruction by incorporating the interplay effect between aperture modulation and target motion, and to assess the dosimetric impact of real-time prostate motion during volumetric modulated arc therapy (VMAT). METHODS AND MATERIALS Clinical VMAT plans were delivered with the TrueBeam linac for 8 patients with prostate cancer. The real-time target motion during dose delivery was determined based on the 2-dimensional fiducial localization using an onboard electronic portal imaging device. The target shift in each image was correlated with the control point with the same gantry angle in the VMAT plan. An in-house-developed Monte Carlo simulation tool was used to calculate the 3-dimensional dose distribution for each control point individually, taking into account the corresponding real-time target motion (assuming a nondeformable target with no rotation). The delivered target dose was then estimated by accumulating the dose from all control points in the plan. On the basis of this information, dose-volume histograms and 3-dimensional dose distributions were calculated to assess their degradation from the planned dose caused by target motion. Thirty-two prostate motion trajectories were analyzed. RESULTS The minimum dose to 0.03 cm(3) of the gross tumor volume (D0.03cc) was only slightly degraded after taking motion into account, with a minimum value of 94.1% of the planned dose among all patients and fractions. However, the gross tumor volume receiving prescription dose (V100%) could be largely affected by motion, dropping below 60% in 1 trajectory. We did not observe a correlation between motion magnitude and dose degradation. CONCLUSIONS Prostate motion degrades the delivered dose to the target in an unpredictable way, although its effect is reduced over multiple fractions, and for most patients the degradation is small. Patients with greater prostate motion or those treated with stereotactic body radiation therapy would benefit from real-time prostate tracking to reduce the margin.

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

The aim of the study was to perform the Monte Carlo (MC) evaluation of RapidArc (Varian Medical Systems, Palo Alto, CA) dose calculations for four oropharynx midline sparing planning strategies. Six patients with squamous cell cancer of the oropharynx were each planned with four RapidArc head and neck treatment strategies consisting of single and double photon arcs. In each case, RTOG0522 protocol objectives were used during planning optimization. Dose calculations performed with the analytical anisotropic algorithm (AAA) are compared against BEAMnrc/DOSXYZnrc dose calculations for the 24-plan dataset. Mean dose and dose-to-98%-of-structure-volume (D(98%)) were used as metrics in the evaluation of dose to planning target volumes (PTVs). Mean dose and dose-to-2%-of-structure-volume (D(2%)) were used to evaluate dose differences within organs at risk (OAR). Differences in the conformity index (CI) and the homogeneity index (HI) as well as 3D dose distributions were also observed. AAA calculated PTV mean dose, D(98%), and HIs showed very good agreement with MC dose calculations within the 0.8% MC (statistical) calculation uncertainty. Regional node volume (PTV-80%) mean dose and D(98%) were found to be overestimated (1.3%, sigma = 0.8% and 2.3%, sigma = 0.8%, respectively) by the AAA with respect to MC calculations. Mean dose and D(2%) to OAR were also observed to be consistently overestimated by the AAA. Increasing dose calculation differences were found in planning strategies exhibiting a higher overall fluence modulation. From the plan dataset, the largest local dose differences were observed in heavily shielded regions and within the esophageal and sinus cavities. AAA dose calculations as implemented in RapidArc demonstrate excellent agreement with MC calculations in unshielded regions containing moderate inhomogeneities. Acceptable agreement is achieved in regions of increased MLC shielding. Differences in dose are attributed to inaccuracies in the AAA-modulated fluence modeling, modeling of material inhomogeneities and dose deposition within low-density materials. The use of MC dose calculations leads to the same general conclusion as using AAA that a two arc delivery with limited collimator opening can provide the greatest amount of midline sparing compared to the other techniques investigated.

Nonisocentric Treatment Strategy for Breast Radiation Therapy: A Proof of Concept Study

PURPOSE To propose a nonisocentric treatment strategy as a special form of station parameter optimized radiation therapy, to improve sparing of critical structures while preserving target coverage in breast radiation therapy. METHODS AND MATERIALS To minimize the volume of exposed lung and heart in breast irradiation, we propose a novel nonisocentric treatment scheme by strategically placing nonconverging beams with multiple isocenters. As its name suggests, the central axes of these beams do not intersect at a single isocenter as in conventional breast treatment planning. Rather, the isocenter locations and beam directions are carefully selected, in that each beam is only responsible for a certain subvolume of the target, so as to minimize the volume of irradiated normal tissue. When put together, the beams will provide an adequate coverage of the target and expose only a minimal amount of normal tissue to radiation. We apply the nonisocentric planning technique to 2 previously treated clinical cases (breast and chest wall). RESULTS The proposed nonisocentric technique substantially improved sparing of the ipsilateral lung. Compared with conventional isocentric plans using 2 tangential beams, the mean lung dose was reduced by 38% and 50% using the proposed technique, and the volume of the ipsilateral lung receiving ≥ 20 Gy was reduced by a factor of approximately 2 and 3 for the breast and chest wall cases, respectively. The improvement in lung sparing is even greater compared with volumetric modulated arc therapy. CONCLUSIONS A nonisocentric implementation of station parameter optimized radiation therapy has been proposed for breast radiation therapy. The new treatment scheme overcomes the limitations of existing approaches and affords a useful tool for conformal breast radiation therapy, especially in cases with extreme chest wall curvature.

Independent calculation of monitor units for VMAT and SPORT

PURPOSE Dose and monitor units (MUs) represent two important facets of a radiation therapy treatment. In current practice, verification of a treatment plan is commonly done in dose domain, in which a phantom measurement or forward dose calculation is performed to examine the dosimetric accuracy and the MU settings of a given treatment plan. While it is desirable to verify directly the MU settings, a computational framework for obtaining the MU values from a known dose distribution has yet to be developed. This work presents a strategy to calculate independently the MUs from a given dose distribution of volumetric modulated arc therapy (VMAT) and station parameter optimized radiation therapy (SPORT). METHODS The dose at a point can be expressed as a sum of contributions from all the station points (or control points). This relationship forms the basis of the proposed MU verification technique. To proceed, the authors first obtain the matrix elements which characterize the dosimetric contribution of the involved station points by computing the doses at a series of voxels, typically on the prescription surface of the VMAT/SPORT treatment plan, with unit MU setting for all the station points. An in-house Monte Carlo (MC) software is used for the dose matrix calculation. The MUs of the station points are then derived by minimizing the least-squares difference between doses computed by the treatment planning system (TPS) and that of the MC for the selected set of voxels on the prescription surface. The technique is applied to 16 clinical cases with a variety of energies, disease sites, and TPS dose calculation algorithms. RESULTS For all plans except the lung cases with large tissue density inhomogeneity, the independently computed MUs agree with that of TPS to within 2.7% for all the station points. In the dose domain, no significant difference between the MC and Eclipse Anisotropic Analytical Algorithm (AAA) dose distribution is found in terms of isodose contours, dose profiles, gamma index, and dose volume histogram (DVH) for these cases. For the lung cases, the MC-calculated MUs differ significantly from that of the treatment plan computed using AAA. However, the discrepancies are reduced to within 3% when the TPS dose calculation algorithm is switched to a transport equation-based technique (Acuros™). Comparison in the dose domain between the MC and Eclipse AAA/Acuros calculation yields conclusion consistent with the MU calculation. CONCLUSIONS A computational framework relating the MU and dose domains has been established. The framework does not only enable them to verify the MU values of the involved station points of a VMAT plan directly in the MU domain but also provide a much needed mechanism to adaptively modify the MU values of the station points in accordance to a specific change in the dose domain.