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

Effective clinical applications of Monte Carlo-based independent secondary dose verification software for helical tomotherapy

PURPOSE

To investigate the scope of the effective clinical application of Monte Carlo (MC)-based independent dose verification software for helical tomotherapy.

METHODS

DoseCHECK was selected as the MC-based dose calculation software. First, the dose calculation accuracy of DoseCHECK was evaluated with film and chamber measurements in a water-equivalent phantom. Second, the dose calculation accuracy was examined in several heterogeneous materials. Finally, dosimetric comparisons between DoseCHECK and the treatment planning system (TPS) were performed for clinical patient plans. Prostate IMRT, head and neck IMRT (HN), total body irradiation (TBI), and brain stereotactic radiotherapy (SRT) were evaluated.

RESULT

The DoseCHECK calculations agreed with the chamber and film measurements in the homogenous phantom. For heterogeneous phantom cases, the dose differences between DoseCHECK and TPS were within 3 %, except in air, in which large dose differences of 20 % were observed. In clinical patient plans, the median dose differences between the lung D_mean in TBI cases and the normal brain D_mean in brain SRT cases were significantly >3 %. For HN and brain SRT cases, the median target dose differences were >3 %.

CONCLUSION

Our results show that independent dose verification with the MC algorithm can detect systematic errors caused by the lack of heterogeneity correction in the TPS. In particular, MC-based independent dose verification is required for HN, TBI, and brain SRT cases in helical tomotherapy.

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.

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.

An automated Monte Carlo QC system for volumetric modulated arc therapy: Possibilities and challenges

PURPOSE

To develop and implement an automated Monte Carlo (MC) system for patient specific VMAT quality control in a patient geometry that generates treatment planning system (TPS) compliant DICOM objects and includes a module for 3D analysis of dose deviations. Also, the aims were to recommend diagnose specific tolerance criteria and an evaluation procedure.

METHODS

The EGSnrc code package formed the basis for development of the MC system. The workflow consists of a number of modules connected to a TPS by means of manual DICOM exports and imports which were executed sequentially without user interaction. DVH comparison was performed in the TPS. In addition, MC- and TPS dose distributions were analysed by applying the normalized dose difference (NDD) formalism. NDD failure maps and a pass rate for a certain threshold were obtained. 170 clinical plans (prostate, thorax, head-and-neck and gynecological) were selected for analysis.

RESULTS

Agreement within 1.5% was found between clinical- and MC data for the mean dose to the target volumes and within 3% for parameters more sensitive to the shape of the DVH e.g. D_98% PTV. Regarding the NDD analysis, tolerance criteria 2%/3 mm were established for prostate plans and 3%/3 mm for the rest of the cases.

CONCLUSIONS

An automated MC system was developed and implemented. Evaluation procedure is recommended with NDD-analysis as a first step. For pass rate < 95%, the evaluation continues with comparison of DVH parameters. For deviations larger than 2%, a visual inspection of the clinical- and MC dose distributions is performed.