Clinical implementation of a Monte Carlo based treatment plan QA platform for validation of Cyberknife and Tomotherapy treatments

Clinical application of a GPU-accelerated monte carlo dose verification for cyberknife M6 with Iris collimator

PURPOSE

To apply an independent GPU-accelerated Monte Carlo (MC) dose verification for CyberKnife M6 with Iris collimator and evaluate the dose calculation accuracy of RayTracing (TPS-RT) algorithm and Monte Carlo (TPS-MC) algorithm in the Precision treatment planning system (TPS).

METHODS

GPU-accelerated MC algorithm (ArcherQA-CK) was integrated into a commercial dose verification system, ArcherQA, to implement the patient-specific quality assurance in the CyberKnife M6 system. 30 clinical cases (10 cases in head, and 10 cases in chest, and 10 cases in abdomen) were collected in this study. For each case, three different dose calculation methods (TPS-MC, TPS-RT and ArcherQA-CK) were implemented based on the same treatment plan and compared with each other. For evaluation, the 3D global gamma analysis and dose parameters of the target volume and organs at risk (OARs) were analyzed comparatively.

RESULTS

For gamma pass rates at the criterion of 2%/2 mm, the results were over 98.0% for TPS-MC vs.TPS-RT, TPS-MC vs. ArcherQA-CK and TPS-RT vs. ArcherQA-CK in head cases, 84.9% for TPS-MC vs.TPS-RT, 98.0% for TPS-MC vs. ArcherQA-CK and 83.3% for TPS-RT vs. ArcherQA-CK in chest cases, 98.2% for TPS-MC vs.TPS-RT, 99.4% for TPS-MC vs. ArcherQA-CK and 94.5% for TPS-RT vs. ArcherQA-CK in abdomen cases. For dose parameters of planning target volume (PTV) in chest cases, the deviations of TPS-RT vs. TPS-MC and ArcherQA-CK vs. TPS-MC had significant difference (P < 0.01), and the deviations of TPS-RT vs. TPS-MC and TPS-RT vs. ArcherQA-CK were similar (P > 0.05). ArcherQA-CK had less calculation time compared with TPS-MC (1.66 min vs. 65.11 min).

CONCLUSIONS

Our proposed MC dose engine (ArcherQA-CK) has a high degree of consistency with the Precision TPS-MC algorithm, which can quickly identify the calculation errors of TPS-RT algorithm for some chest cases. ArcherQA-CK can provide accurate patient-specific quality assurance in clinical practice.

Commissioning and clinical implementation of the first commercial independent Monte Carlo 3D dose calculation to replace CyberKnife M6™ patient-specific QA measurements

PURPOSE

To report on the commissioning and clinical validation of the first commercially available independent Monte Carlo (MC) three-dimensional (3D) dose calculation for CyberKnife robotic radiosurgery system® (Accuray, Sunnyvale, CA).

METHODS

The independent dose calculation (IDC) by SciMoCa® (Scientific RT, Munich, Germany) was validated based on water measurements of output factors and dose profiles (unshielded diode, field-size dependent corrections). A set of 84 patient-specific quality assurance (QA) measurements for multi-leaf collimator (MLC) plans, using an Octavius two-dimensional SRS1000 array (PTW, Freiburg, Germany), was compared to results of respective calculations. Statistical process control (SPC) was used to detect plans outside action levels.

RESULTS

Of all output factors for the three collimator systems of the CyberKnife, 99% agreed within 2% and 81% within 1%, with a maximum deviation of 3.2% for a 5-mm fixed cone. The profiles were compared using a one-dimensional gamma evaluation with 2% dose difference and 0.5 mm distance-to-agreement (Γ(2,0.5)). The off-centre ratios showed an average pass rate >99% (92-100%). The agreement of the depth dose profiles depended on field size, with lowest pass rates for the smallest MLC field sizes. The average depth dose pass rate was 88% (35-99%). The IDCs showed a Γ(2,1) pass rate of 98%. Statistical process control detected six plans outside tolerance levels in the measurements, all of which could be attributed the measurement setup. Independent dose calculations showed problems in five plans, all due to differences in the algorithm between TPS and IDC. Based on these results changes were made in the class solution for treatment plans.

CONCLUSION

The first commercially available MC 3D dose IDC was successfully commissioned and validated for the CyberKnife and replaced all routine patient-specific QA measurements in our clinic.

Monte Carlo calculations of radiotherapy dose in "homogeneous" anatomy

Given the substantial literature on the use of Monte Carlo (MC) simulations to verify treatment planning system (TPS) calculations of radiotherapy dose in heterogeneous regions, such as head and neck and lung, this study investigated the potential value of running MC simulations of radiotherapy treatments of nominally homogeneous pelvic anatomy. A pre-existing in-house MC job submission and analysis system, built around BEAMnrc and DOSXYZnrc, was used to evaluate the dosimetric accuracy of a sample of 12 pelvic volumetric arc therapy (VMAT) treatments, planned using the Varian Eclipse TPS, where dose was calculated with both the Analytical Anisotropic Algorithm (AAA) and the Acuros (AXB) algorithm. In-house TADA (Treatment And Dose Assessor) software was used to evaluate treatment plan complexity, in terms of the small aperture score (SAS), modulation index (MI) and a novel exposed leaf score (ELS/ELA). Results showed that the TPS generally achieved closer agreement with the MC dose distribution when treatments were planned for smaller (single-organ) targets rather than larger targets that included nodes or metastases. Analysis of these MC results with reference to the complexity metrics indicated that while AXB was useful for reducing dosimetric uncertainties associated with density heterogeneity, the residual TPS dose calculation uncertainties resulted from treatment plan complexity and TPS model simplicity. The results of this study demonstrate the value of using MC methods to recalculate and check the dose calculations provided by commercial radiotherapy TPSs, even when the treated anatomy is assumed to be comparatively homogeneous, such as in the pelvic region.

Clinical implementation of a Monte Carlo based independent TPS dose checking system

The increase in complexity of treatment plans over time through modalities such as intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) has often not been met with an increase in capability of the secondary dose calculation checking systems typically used to verify the treatment planning system. Monte Carlo (MC) codes such as EGSnrc have become easily available and are capable of performing calculations of highly complex radiotherapy treatments. This educational note demonstrates a method for implementing and using a fully automated system for performing and analysing full MC calculations of conformal, IMRT and VMAT radiotherapy plans. Example calculations were based on BEAMnrc/DOSXYZnrc and are performed automatically after either uploading exported plan DICOM data through a Python-based web interface, or exporting DICOM data to a monitored network location. This note demonstrates how completed MC calculations can then be analysed using an automatically generated dose point comparison report, or easily re-imported back into the treatment planning system. Agreement between the TPS and MC calculation was an improvement on agreement between RadCalc and the TPS, with differences ranging from 1.2 to 5.5% between RadCalc and the treatment planning system (TPS), and 0.1-1.7% between MC and TPS. Comparison of the dose-volume histogram (DVH) parameters [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] for the example VMAT plans showed agreement for the mean planning target volume dose within [Formula: see text], [Formula: see text] and [Formula: see text] generally within [Formula: see text] with the exception of a brain case, and [Formula: see text] within [Formula: see text]. Overall, this note provides a demonstration of a system that has been integrated well into existing clinical workflow, and has been shown to be a valuable additional tool in the secondary checking of treatment plan calculations.

Integration of the M6 Cyberknife in the Moderato Monte Carlo platform and prediction of beam parameters using machine learning

PURPOSE

This work describes the integration of the M6 Cyberknife in the Moderato Monte Carlo platform, and introduces a machine learning method to accelerate the modelling of a linac.

METHODS

The MLC-equipped M6 Cyberknife was modelled and integrated in Moderato, our in-house platform offering independent verification of radiotherapy dose distributions. The model was validated by comparing TPS dose distributions with Moderato and by film measurements. Using this model, a machine learning algorithm was trained to find electron beam parameters for other M6 devices, by simulating dose curves with varying spot size and energy. The algorithm was optimized using cross-validation and tested with measurements from other institutions equipped with a M6 Cyberknife.

RESULTS

Optimal agreement in the Monte Carlo model was reached for a monoenergetic electron beam of 6.75 MeV with Gaussian spatial distribution of 2.4 mm FWHM. Clinical plan dose distributions from Moderato agreed within 2% with the TPS, and film measurements confirmed the accuracy of the model. Cross-validation of the prediction algorithm produced mean absolute errors of 0.1 MeV and 0.3 mm for beam energy and spot size respectively. Prediction-based simulated dose curves for other centres agreed within 3% with measurements, except for one device where differences up to 6% were detected.

CONCLUSIONS

The M6 Cyberknife was integrated in Moderato and validated through dose re-calculations and film measurements. The prediction algorithm was successfully applied to obtain electron beam parameters for other M6 devices. This method would prove useful to speed up modelling of new machines in Monte Carlo systems.

Benchmarking Monte-Carlo dose calculation for MLC CyberKnife treatments

Background

Vendor-independent Monte Carlo (MC) dose calculation (IDC) for patient-specific quality assurance of multi-leaf collimator (MLC) based CyberKnife treatments is used to benchmark and validate the commercial MC dose calculation engine for MLC based treatments built into the CyberKnife treatment planning system (Precision MC).

Methods

The benchmark included dose profiles in water in 15 mm depth and depth dose curves of rectangular MLC shaped fields ranging from 7.6 mm × 7.7 mm to 115.0 mm  × 100.1 mm, which were compared between IDC, Precision MC and measurements in terms of dose difference and distance to agreement. Dose distributions of three phantom cases and seven clinical lung cases were calculated using both IDC and Precision MC. The lung PTVs ranged from 14 cm³ to 93 cm³. Quantitative comparison of these dose distributions was performed using dose-volume parameters and 3D gamma analysis with 2% global dose difference and 1 mm distance criteria and a global 10% dose threshold. Time to calculate dose distributions was recorded and efficiency was assessed.

Results

Absolute dose profiles in 15 mm depth in water showed agreement between Precision MC and IDC within 3.1% or 1 mm. Depth dose curves agreed within 2.3% / 1 mm. For the phantom and clinical lung cases, mean PTV doses differed from − 1.0 to + 2.3% between IDC and Precision MC and gamma passing rates were > =98.1% for all multiple beam treatment plans. For the lung cases, lung V20 agreed within ±1.5%. Calculation times ranged from 2.2 min (for 39 cm³ PTV at 1.0 × 1.0 × 2.5 mm³ native CT resolution) to 8.1 min (93 cm³ at 1.1 × 1.1 × 1.0 mm³), at 2% uncertainty for Precision MC for the 7 examined lung cases and 4–6 h for IDC, which, however, is not optimized for efficiency but used as a gold standard for accuracy.

Conclusions

Both accuracy and efficiency of Precision MC in the context of MLC based planning for the CyberKnife M6 system were benchmarked against MC based IDC framework. Precision MC is used in clinical practice at our institute.

Novel Monte Carlo dose calculation algorithm for robotic radiosurgery with multi leaf collimator: Dosimetric evaluation

PURPOSE

At introduction in 2014, dose calculation for the first MLC on a robotic SRS/SBRT platform was limited to a correction-based Finite-Size Pencil Beam (FSPB) algorithm. We report on the dosimetric accuracy of a novel Monte Carlo (MC) dose calculation algorithm for this MLC, included in the Precision™ treatment planning system.

METHODS

A phantom was built of one slab (5.0 cm) of lung-equivalent material (0.09…0.29 g/cc) enclosed by 3.5 cm (above) and 5 cm (below) slabs of solid water (1.045 g/cc). This was irradiated using rectangular (15.4 × 15.4 mm² to 53.8 × 53.7 mm²) and two irregular MLC-fields. Radiochromic film (EBT3) was positioned perpendicular to the slabs and parallel to the beam. Calculated dose distributions were compared to film measurements using line scans and 2D gamma analysis.

RESULTS

Measured and MC calculated percent depth dose curves showed a characteristic dose drop within the low-density region, which was not correctly reproduced by FSPB. Superior average gamma pass rates (2%/1 mm) were found for MC (91.2 ± 1.5%) compared to FSPB (55.4 ± 2.7%). However, MC calculations exhibited localized anomalies at mass density transitions around 0.15 g/cc, which were traced to a simplification in electron transport. Absence of these anomalies was confirmed in a modified build of the MC engine, which increased gamma pass rates to 96.6 ± 1.2%.

CONCLUSIONS

The novel MC algorithm greatly improves dosimetric accuracy in heterogeneous tissue, potentially expanding the clinical use of robotic radiosurgery with MLC. In-depth, independent validation is paramount to identify and reduce the residual uncertainties in any software solution.

Multi-institutional comparison of secondary check of treatment planning using computer-based independent dose calculation for non-C-arm linear accelerators

PURPOSE

This report covers the first multi-institutional study of independent monitor unit (MU)/dose calculation verification for the CyberKnife, Vero4DRT, and TomoTherapy radiotherapy delivery systems.

METHODS

A total of 973 clinical treatment plans were collected from 12 institutions. Commercial software employing the Clarkson algorithm was used for verification after a measurement validation study, and the doses from the treatment planning systems (TPSs) and verification programs were compared on the basis of the mean value ± two standard deviations. The impact of heterogeneous conditions was assessed in two types of sites: non-lung and lung.

RESULTS

The dose difference for all locations was 0.5 ± 7.2%. There was a statistically significant difference (P < 0.01) in dose difference between non-lung (-0.3 ± 4.4%) and lung sites (3.5 ± 6.7%). Inter-institutional comparisons showed that various systematic differences were associated with the proportion of different treatment sites and heterogeneity correction.

CONCLUSIONS

This multi-institutional comparison should help to determine the departmental action levels for CyberKnife, Vero4DRT, and TomoTherapy, as patient populations and treatment sites may vary between the modalities. An action level of ±5% could be considered for intensity-modulated radiation therapy (IMRT), non-IMRT, and volumetric modulated arc radiotherapy using these modalities in homogenous and heterogeneous conditions with a large treatment field applied to a large region of homogeneous media. There were larger systematic differences in heterogeneous conditions with a small treatment field because of differences in heterogeneity correction with the different dose calculation algorithms of the primary TPS and verification program.

[MRI-based radiotherapy planning]

MRI-based radiotherapy planning is a topical subject due to the introduction of a new generation of treatment machines combining a linear accelerator and a MRI. One of the issues for introducing MRI in this task is the lack of information to provide tissue density information required for dose calculation. To cope with this issue, two strategies may be distinguished from the literature. Either a synthetic CT scan is generated from the MRI to plan the dose, or a dose is generated from the MRI based on physical underpinnings. Within the first group, three approaches appear: bulk density mapping assign a homogeneous density to different volumes of interest manually defined on a patient MRI; machine learning-based approaches model local relationship between CT and MRI image intensities from multiple data, then applying the model to a new MRI; atlas-based approaches use a co-registered training data set (CT-MRI) which are registered to a new MRI to create a pseudo CT from spatial correspondences in a final fusion step. Within the second group, physics-based approaches aim at computing the dose directly from the hydrogen contained within the tissues, quantified by MRI. Excepting the physics approach, all these methods generate a synthetic CT called "pseudo CT", on which radiotherapy planning will be finally realized. This literature review shows that atlas- and machine learning-based approaches appear more accurate dosimetrically. Bulk density approaches are not appropriate for bone localization. The fastest methods are machine learning and the slowest are atlas-based approaches. The less automatized are bulk density assignation methods. The physical approaches appear very promising methods. Finally, the validation of these methods is crucial for a clinical practice, in particular in the perspective of adaptive radiotherapy delivered by a linear accelerator combined with an MRI scanner.

Use of an in-house Monte Carlo platform to assess the clinical impact of algorithm-related dose differences on DVH constraints

PURPOSE

The aim of the present work is to evaluate a semi-automatic prescription and validation system of treatment plans for complex delivery techniques, integrated in a Monte Carlo platform, and to investigate the clinical impact of dose differences due to the calculation algorithms, by assessing the changes in DVH constraints.

METHODS

A new prescription module was implemented into the Moderato system, an in-house Monte Carlo platform, with corresponding dose constraints generated depending on the anatomical region and fractionation scheme considered. The platform was tested on 83 cases treated with Cyberknife and Tomotherapy machines, to assess whether dose variations between the re-calculated dose and the Treatment Planning System might impact the dose constraints on the sensitive structures.

RESULTS

Dose differences were small (within 3%) between calculation algorithms in most of the thoracic, pelvic and abdominal cases, both for the Cyberknife and Tomotherapy machines. On the other hand, spinal and head and neck treatments presented a few significant dose deviations for constraints on small volumes, such as the optic pathways and the spinal cord. These differences range from -11% to +6%, inducing constraint violations of up to 8% over the dose limit.

CONCLUSIONS

The Moderato platform offers an interesting tool for plan quality validation, with a prescription module highlighting crucial features in the structures list, and a Monte Carlo dose re-calculation for complex modern techniques. Due to the high number of warnings appearing in some situations, display optimization is required in practice.