The influence of beam model differences in the comparison of dose calculation algorithms for lung cancer treatment planning

Variability of Low-Z Inhomogeneity Correction in IMRT/SBRT: A Multi-Institutional Collaborative Study

Dose-calculation algorithms are critical for radiation treatment outcomes that vary among treatment planning systems (TPS). Modern algorithms use sophisticated radiation transport calculation with detailed three-dimensional beam modeling to provide accurate doses, especially in heterogeneous medium and small fields used in IMRT/SBRT. While the dosimetric accuracy in heterogeneous mediums (lung) is qualitatively known, the accuracy is unknown. The aim of this work is to analyze the calculated dose in lung patients and compare the validity of dose-calculation algorithms by measurements in a low-Z phantom for two main classes of algorithms: type A (pencil beam) and type B (collapse cone). The CT scans with volumes (target and organs at risk, OARs) of a lung patient and a phantom build to replicate the human lung data were sent to nine institutions for planning. Doses at different depths and field sizes were measured in the phantom with and without inhomogeneity correction across multiple institutions to understand the impact of clinically used dose algorithms. Wide dosimetric variations were observed in target and OAR coverage in patient plans. The correction factor for collapsed cone algorithms was less than pencil beam algorithms in the small fields used in SBRT. The pencil beam showed ≈70% variations between measured and calculated correction factors for various field sizes and depths. For large field sizes the trends of both types of algorithms were similar. The differences in measured versus calculated dose for type-B algorithms were within ±10%. Significant variations in the target and OARs were observed among various TPS. The results suggest that the pencil beam algorithm does not provide an accurate dose and should not be considered with small fields (IMRT/SBRT). Type-B collapsed-cone algorithms provide better agreement with measurements, but still vary among various systems.

A GPU-based framework for modeling real-time 3D lung tumor conformal dosimetry with subject-specific lung tumor motion

In this paper, we present a graphics processing unit (GPU)-based simulation framework to calculate the delivered dose to a 3D moving lung tumor and its surrounding normal tissues, which are undergoing subject-specific lung deformations. The GPU-based simulation framework models the motion of the 3D volumetric lung tumor and its surrounding tissues, simulates the dose delivery using the dose extracted from a treatment plan using Pinnacle Treatment Planning System, Phillips, for one of the 3DCTs of the 4DCT and predicts the amount and location of radiation doses deposited inside the lung. The 4DCT lung datasets were registered with each other using a modified optical flow algorithm. The motion of the tumor and the motion of the surrounding tissues were simulated by measuring the changes in lung volume during the radiotherapy treatment using spirometry. The real-time dose delivered to the tumor for each beam is generated by summing the dose delivered to the target volume at each increase in lung volume during the beam delivery time period. The simulation results showed the real-time capability of the framework at 20 discrete tumor motion steps per breath, which is higher than the number of 4DCT steps (approximately 12) reconstructed during multiple breathing cycles.

Modeling simulation and visualization of conformal 3D lung tumor dosimetry

Lung tumors move during breathing depending on the patient's patho-physiological condition and orientation, thereby compromising the accurate deposition of the radiation dose during radiotherapy. In this paper, we present and validate a computer-based simulation framework to calculate the delivered dose to a 3D moving tumor and its surrounding normal tissues. The computer-based simulation framework models a 3D volumetric lung tumor and its surrounding tissues, simulates the tumor motion during a simulated dose delivery both as a self-reproducible motion and a random motion using the dose extracted from a treatment plan, and predicts the amount and location of radiation doses deposited. A radiation treatment plan of a small lung tumor (1-3 cm diameter) was developed in a commercial planning system (iPlan software, BrainLab, Munich, Germany) to simulate the radiation dose delivered. The dose for each radiation field was extracted from the software. The tumor motion was simulated for varying values of its rate, amplitude and direction within a single breath as well as from one breath to another. Such variations represent the variations in tumor motion induced by breathing variations. During the simulation of dose delivery, the dose on the target was summed to generate the real-time dose to the tumor for each beam independently. The simulation results show that the dose accumulated on the tumor varies significantly with both the tumor size and the tumor's motion rate, amplitude and direction. For a given tumor motion rate, amplitude and direction, the smaller the tumor size the smaller is the percentage of the radiation dose accumulated. The simulation results are validated by comparing the center plane of the 3D tumor with 2D film dosimetry measurements using a programmable 4D motion phantom moving in a self-reproducible pattern. The results also show the real-time capability of the framework at 40 discrete tumor motion steps per breath, which is higher than the number of four-dimensional computed tomography (CT) steps (approximately 20) during a single breath. The real-time capability enables the framework to be coupled with real-time tumor monitoring systems such as implanted fiducials for computing the dose delivered in real time during the treatment.

An anatomically realistic lung model for Monte Carlo-based dose calculations

Treatment planning for disease sites with large variations of electron density in neighboring tissues requires an accurate description of the geometry. This self-evident statement is especially true for the lung, a highly complex organ having structures with a wide range of sizes that range from about 10(-4) to 1 cm. In treatment planning, the lung is commonly modeled by a voxelized geometry obtained using computed tomography (CT) data at various resolutions. The simplest such model, which is often used for QA and validation work, is the atomic mix or mean density model, in which the entire lung is homogenized and given a mean (volume-averaged) density. The purpose of this paper is (i) to describe a new heterogeneous random lung model, which is based on morphological data of the human lung, and (ii) use this model to assess the differences in dose calculations between an actual lung (as represented by our model) and a mean density (homogenized) lung. Eventually, we plan to use the random lung model to assess the accuracy of CT-based treatment plans of the lung. For this paper, we have used Monte Carlo methods to make accurate comparisons between dose calculations for the random lung model and the mean density model. For four realizations of the random lung model, we used a single photon beam, with two different energies (6 and 18 MV) and four field sizes (1 x 1, 5 x 5, 10 x 10, and 20 x 20 cm2). We found a maximum difference of 34% of D(max) with the 1 x 1, 18 MV beam along the central axis (CAX). A "shadow" region distal to the lung, with dose reduction up to 7% of D(max), exists for the same realization. The dose perturbations decrease for larger field sizes, but the magnitude of the differences in the shadow region is nearly independent of the field size. We also observe that, compared to the mean density model, the random structures inside the heterogeneous lung can alter the shape of the isodose lines, leading to a broadening or shrinking of the penumbra region. For small field sizes, the mean lung doses significantly depend on the structures' relative locations to the beam. In addition to these comparisons between the random lung and mean density models, we also provide a preliminary comparison between dose calculations for the random lung model and a voxelized version of this model at 0.4 x 0.4 x 0.4 cm3 resolution. Overall, this study is relevant to treatment planning for lung tumors, especially in situations where small field sizes are used. Our results show that for such situations, the mean density model of the lung is inadequate, and a more accurate CT model of the lung is required. Future work with our model will involve patient motion, setup errors, and recommendations for the resolution of CT models.

Interinstitutional variations in planning for stereotactic body radiation therapy for lung cancer

PURPOSE

The aim of this study was to assess interinstitutional variations in planning for stereotactic body radiation therapy (SBRT) for lung cancer before the start of the Japan Clinical Oncology Group (JCOG) 0403 trial.

METHODS AND MATERIALS

Eleven institutions created virtual plans for four cases of solitary lung cancer. The created plans should satisfy the target definitions and the dose constraints for the JCOG 0403 protocol.

RESULTS

FOCUS/XiO (CMS) was used in six institutions, Eclipse (Varian) in 3, Cadplan (Varian) in one, and Pinnacle3 (Philips/ADAC) in one. Dose calculation algorithms of Clarkson with effective path length correction and superposition were used in FOCUS/XiO; pencil beam convolution with Batho power law correction was used in Eclipse and Cadplan; and collapsed cone convolution superposition was used in Pinnacle3. For the target volumes, the overall coefficient of variation was 16.6%, and the interinstitutional variations were not significant. For maximal dose, minimal dose, D95, and the homogeneity index of the planning target volume, the interinstitutional variations were significant. The dose calculation algorithm was a significant factor in these variations. No violation of the dose constraints for the protocol was observed.

CONCLUSION

There can be notable interinstitutional variations in planning for SBRT, including both interobserver variations in the estimate of target volumes as well as dose calculation effects related to the use of different dose calculation algorithms.

Method for Fast CT/SPECT-Based 3D Monte Carlo Absorbed Dose Computations in Internal Emitter Therapy

The DPM (Dose Planning Method) Monte Carlo electron and photon transport program, designed for fast computation of radiation absorbed dose in external beam radiotherapy, has been adapted to the calculation of absorbed dose in patient-specific internal emitter therapy. Because both its photon and electron transport mechanics algorithms have been optimized for fast computation in 3D voxelized geometries (in particular, those derived from CT scans), DPM is perfectly suited for performing patient-specific absorbed dose calculations in internal emitter therapy. In the updated version of DPM developed for the current work, the necessary inputs are a patient CT image, a registered SPECT image, and any number of registered masks defining regions of interest. DPM has been benchmarked for internal emitter therapy applications by comparing computed absorption fractions for a variety of organs using a Zubal phantom with reference results from the Medical Internal Radionuclide Dose (MIRD) Committee standards. In addition, the β decay source algorithm and the photon tracking algorithm of DPM have been further benchmarked by comparison to experimental data. This paper presents a description of the program, the results of the benchmark studies, and some sample computations using patient data from radioimmunotherapy studies using (131)I.

Accuracy of patient dose calculation for lung IMRT: A comparison of Monte Carlo, convolution/superposition, and pencil beam computations

The accuracy of dose computation within the lungs depends strongly on the performance of the calculation algorithm in regions of electronic disequilibrium that arise near tissue inhomogeneities with large density variations. There is a lack of data evaluating the performance of highly developed analytical dose calculation algorithms compared to Monte Carlo computations in a clinical setting. We compared full Monte Carlo calculations (performed by our Monte Carlo dose engine MCDE) with two different commercial convolution/superposition (CS) implementations (Pinnacle-CS and Helax-TMS's collapsed cone model Helax-CC) and one pencil beam algorithm (Helax-TMS's pencil beam model Helax-PB) for 10 intensity modulated radiation therapy (IMRT) lung cancer patients. Treatment plans were created for two photon beam qualities (6 and 18 MV). For each dose calculation algorithm, patient, and beam quality, the following set of clinically relevant dose-volume values was reported: (i) minimal, median, and maximal dose (Dmin, D50, and Dmax) for the gross tumor and planning target volumes (GTV and PTV); (ii) the volume of the lungs (excluding the GTV) receiving at least 20 and 30 Gy (V20 and V30) and the mean lung dose; (iii) the 33rd percentile dose (D33) and Dmax delivered to the heart and the expanded esophagus; and (iv) Dmax for the expanded spinal cord. Statistical analysis was performed by means of one-way analysis of variance for repeated measurements and Tukey pairwise comparison of means. Pinnacle-CS showed an excellent agreement with MCDE within the target structures, whereas the best correspondence for the organs at risk (OARs) was found between Helax-CC and MCDE. Results from Helax-PB were unsatisfying for both targets and OARs. Additionally, individual patient results were analyzed. Within the target structures, deviations above 5% were found in one patient for the comparison of MCDE and Helax-CC, while all differences between MCDE and Pinnacle-CS were below 5%. For both Pinnacle-CS and Helax-CC, deviations from MCDE above 5% were found within the OARs: within the lungs for two (6 MV) and six (18 MV) patients for Pinnacle-CS, and within other OARs for two patients for Helax-CC (for Dmax of the heart and D33 of the expanded esophagus) but only for 6 MV. For one patient, all four algorithms were used to recompute the dose after replacing all computed tomography voxels within the patient's skin contour by water. This made all differences above 5% between MCDE and the other dose calculation algorithms disappear. Thus, the observed deviations mainly arose from differences in particle transport modeling within the lungs, and the commissioning of the algorithms was adequately performed (or the commissioning was less important for this type of treatment). In conclusion, not one pair of the dose calculation algorithms we investigated could provide results that were consistent within 5% for all 10 patients for the set of clinically relevant dose-volume indices studied. As the results from both CS algorithms differed significantly, care should be taken when evaluating treatment plans as the choice of dose calculation algorithm may influence clinical results. Full Monte Carlo provides a great benchmarking tool for evaluating the performance of other algorithms for patient dose computations.

Testing of the analytical anisotropic algorithm for photon dose calculation

The analytical anisotropic algorithm (AAA) was implemented in the Eclipse (Varian Medical Systems) treatment planning system to replace the single pencil beam (SPB) algorithm for the calculation of dose distributions for photon beams. AAA was developed to improve the dose calculation accuracy, especially in heterogeneous media. The total dose deposition is calculated as the superposition of the dose deposited by two photon sources (primary and secondary) and by an electron contamination source. The photon dose is calculated as a three-dimensional convolution of Monte-Carlo precalculated scatter kernels, scaled according to the electron density matrix. For the configuration of AAA, an optimization algorithm determines the parameters characterizing the multiple source model by optimizing the agreement between the calculated and measured depth dose curves and profiles for the basic beam data. We have combined the acceptance tests obtained in three different departments for 6, 15, and 18 MV photon beams. The accuracy of AAA was tested for different field sizes (symmetric and asymmetric) for open fields, wedged fields, and static and dynamic multileaf collimation fields. Depth dose behavior at different source-to-phantom distances was investigated. Measurements were performed on homogeneous, water equivalent phantoms, on simple phantoms containing cork inhomogeneities, and on the thorax of an anthropomorphic phantom. Comparisons were made among measurements, AAA, and SPB calculations. The optimization procedure for the configuration of the algorithm was successful in reproducing the basic beam data with an overall accuracy of 3%, 1 mm in the build-up region, and 1%, 1 mm elsewhere. Testing of the algorithm in more clinical setups showed comparable results for depth dose curves, profiles, and monitor units of symmetric open and wedged beams below dmax. The electron contamination model was found to be suboptimal to model the dose around dmax, especially for physical wedges at smaller source to phantom distances. For the asymmetric field verification, absolute dose difference of up to 4% were observed for the most extreme asymmetries. Compared to the SPB, the penumbra modeling is considerably improved (1%, 1 mm). At the interface between solid water and cork, profiles show a better agreement with AAA. Depth dose curves in the cork are substantially better with AAA than with SPB. Improvements are more pronounced for 18 MV than for 6 MV. Point dose measurements in the thoracic phantom are mostly within 5%. In general, we can conclude that, compared to SPB, AAA improves the accuracy of dose calculations. Particular progress was made with respect to the penumbra and low dose regions. In heterogeneous materials, improvements are substantial and more pronounced for high (18 MV) than for low (6 MV) energies.