Monte Carlo dose calculation in presence of low-density media: Application to lung SBRT treated during DIBH

PurposeCommercial algorithms used in Radiotherapy include approximations that are generally acceptable. However their limits can be seen when confronted with small fields and low-density media. These conditions exist during the treatment of lung cancers with Stereotactic Body Radiation Therapy (SBRT) achieved with the “Deep Inspiration Breath Hold” (DIBH) technique. A Monte Carlo (MC) model of a linear accelerator was used to assess the performance of two algorithms (Varian Acuros and AAA) in these conditions. This model is validated using phantoms with different densities. Lastly, results for SBRT cases are compared to both Acuros and AAA.MethodsA Varian TrueBeam linac was modeled using GATE/Geant4 and validated by comparing dose distributions for simple fields to measurements in water and in heterogeneous phantoms composed of PMMA and two types of cork (corresponding to lung densities during free-breathing and DIBH). Experimental measurements are also compared to AAA and Acuros. Finally, results of Acuros/AAA are compared to MC for a clinical case (SBRT during DIBH).ResultsBased on 1D gamma index comparisons with measurements in water, the TrueBeam model was validated (>97% of points passed this test). In heterogeneous phantoms, and in particular for small field sizes, very low density (0.12 g.cm⁻³) and at the edge of the field, MC model was still in good agreement with measurements whilst AAA and Acuros showed discrepancies. With the patient CT, similar differences between MC and AAA/Acuros were observed for static fields but disappeared using an SBRT arc field.ConclusionsOur MC model is validated and limits of commercial algorithms are shown in very low densities.     

Generation of clinical 177Lu SPECT/CT images based on Monte Carlo simulation with GATE

PurposePatient-specific dosimetry in MRT relies on quantitative imaging, pharmacokinetic assessment and absorbed dose calculation. The DosiTest project was initiated to evaluate the uncertainties associated with each step of the clinical dosimetry workflow through a virtual multicentric clinical trial. This work presents the generation of simulated clinical SPECT datasets based on GATE Monte Carlo modelling with its corresponding experimental CT image, which can subsequently be processed by commercial image workstations.MethodsThis study considers a therapy cycle of 6.85 GBq ¹⁷⁷Lu-labelled DOTATATE derived from an IAEA-Coordinated Research Project (E23005) on “Dosimetry in Radiopharmaceutical therapy for personalised patient treatment”. Patient images were acquired on a GE Infinia-Hawkeye 4 gamma camera using a medium energy (ME) collimator. Simulated SPECT projections were generated based on experimental time points and validated against experimental SPECT projections using flattened profiles and gamma index. The simulated projections were then incorporated into the patient SPECT/CT DICOM envelopes for processing and their reconstruction within a commercial image workstation.ResultsGamma index passing rate (2% − 1 pixel criteria) between 95 and 98% and average gamma between 0.28 and 0.35 among different time points revealed high similarity between simulated and experimental images. Image reconstruction of the simulated projections was successful on HERMES and Xeleris workstations, a major step forward for the initiation of a multicentric virtual clinical dosimetry trial based on simulated SPECT/CT images.ConclusionsRealistic ¹⁷⁷Lu patient SPECT projections were generated in GATE. These modelled datasets will be circulated to different clinical departments to perform dosimetry in order to assess the uncertainties in the entire dosimetric chain.     

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.     

Development of a four-dimensional Monte Carlo dose calculation system for real-time tumor-tracking irradiation with a gimbaled X-ray head

PurposeTo develop a four-dimensional (4D) dose calculation system for real-time tumor tracking (RTTT) irradiation by the Vero4DRT.MethodsFirst, a 6-MV photon beam delivered by the Vero4DRT was simulated using EGSnrc. A moving phantom position was directly measured by a laser displacement gauge. The pan and tilt angles, monitor units, and the indexing time indicating the phantom position were also extracted from a log file. Next, phase space data at any angle were created from both the log file and particle data under the dynamic multileaf collimator. Irradiation both with and without RTTT, with the phantom moving, were simulated using several treatment field sizes. Each was compared with the corresponding measurement using films. Finally, dose calculation for each computed tomography dataset of 10 respiratory phases with the X-ray head rotated was performed to simulate the RTTT irradiation (4D plan) for lung, liver, and pancreatic cancer patients. Dose-volume histograms of the 4D plan were compared with those calculated on the single reference respiratory phase without the gimbal rotation [three-dimensional (3D) plan].ResultsDifferences between the simulated and measured doses were less than 3% for RTTT irradiation in most areas, except the high-dose gradient. For clinical cases, the target coverage in 4D plans was almost identical to that of the 3D plans. However, the doses to organs at risk in the 4D plans varied at intermediate- and low-dose levels.ConclusionsOur proposed system has acceptable accuracy for RTTT irradiation in the Vero4DRT and is capable of simulating clinical RTTT plans.     

Effects of lung tissue characterization in radiotherapy of breast cancer under deep inspiration breath hold when using Monte Carlo dosimetry

PurposeTo investigate the sensitivity of Monte Carlo (MC) calculated lung dose distributions to lung tissue characterization in external beam radiotherapy of breast cancer under Deep Inspiration Breath Hold (DIBH).MethodsEGSnrc based MC software was employed. Mean lung densities for one hundred patients were analysed. CT number frequency and clinical dose distributions were calculated for 15 patients with mean lung density below 0.14 g/cm³. Lung volume with a pre-defined CT numbers was also considered. Lung tissue was characterized by applying different CT calibrations in the low-density region and air-lung tissue thresholds. Dose impact was estimated by Dose Volume Histogram (DVH) parameters.ResultsMean lung densities below 0.14 g/cm³ were found in 10% of the patients. CT numbers below −960 HU dominated the CT frequency distributions with a high rate of CT numbers at −990 HU. Mass density conversion approach influenced the DVH shape. V_4Gy and V_8Gy varied by 7% and 5% for the selected patients and by 9% and 3.5% for the pre-defined lung volume. V_16Gy and V_20Gy, were within 2.5%. Regions above 20 Gy were affected. Variations in air- lung tissue differentiation resulted in DVH parameters within 1%. Threshold at −990 HU was confirmed by the CT number frequency distributions.ConclusionsLung dose distributions were more sensitive to variations in the CT calibration curve below lung (inhale) density than to air-lung tissue differentiation. Low dose regions were mostly affected. The dosimetry effects were found to be potentially important to 10% of the patients treated under DIBH.     

Comparison of PRIMO Monte Carlo code and Eclipse treatment planning system in calculation of dosimetric parameters in brain cancer radiotherapy

BackgroundIt is important to evaluate the dose calculated by treatment planning systems (TPSs) and dose distribution in tumor and organs at risk (OARs). The aim of this study is to compare dose calculated by the PRIMO Monte Carlo code and Eclipse TPS in radiotherapy of brain cancer patients.Materials and methodsPRIMO simulation code was used to simulate a Varian Clinac 600C linac. The simulations were validated for the linac by comparison of the simulation and measured results. In the case of brain cancer patients, the dosimetric parameters obtained by the PRIMO code were compared with those calculated by Eclipse TPS. Gamma function analysis with 3%, 3 mm criteria was utilized to compare the dose distributions. The evaluations were based on the dosimetric parameters for the planning target volume (PTV) and OAR including D_min, D_mean, and D_max, homogeneity index (HI), and conformity index (CI).ResultsThe gamma function analysis showed a 98% agreement between the results obtained by the PRIMO code and measurement for the percent depth dose (PDD) and dose profiles. The corresponding value in comparing the dosimetric parameters from PRIMO code and Eclipse TPS for the brain patients was 94%, on average. The results of the PRIMO simulation were in good agreement with the measured data and Eclipse TPS calculations.ConclusionsBased on the results of this study, the PRIMO code can be utilized to simulate a medical linac with good accuracy and to evaluate the accuracy of treatment plans for patients with brain cancer.     

Assessment of skin dose in breast cancer radiotherapy: on-phantom measurement and Monte Carlo simulation

AimThe main purpose of the present study is assessment of skin dose in breast cancer radiotherapy.BackgroundAccurate assessment of skin dose in radiotherapy can provide useful information for clinical considerations.Materials and methodsA RANDO phantom was irradiated using a 6 MV Siemens Primus linac with medial and tangential radiotherapy fields for simulating breast cancer treatment. Dosimetry was also performed on various positions across the fields using an EBT3 radiochromic film. Similar conditions of measurement on the RANDO phantom including field size, irradiation angle, number of fields, etc. were subsequently simulated via the Monte Carlo N-Particle Transport code (MCNP). Ultimately, dose values for corresponding points from both methods were compared.ResultsConsidering dosimetry using radiochromic films on the RANDO phantom, there were points having underdose and overdose based on the prescribed dose and skin tolerance levels. In this respect, 81.25% and 18.75% of the points had underdose and overdose, respectively. In some cases, several differences were observed between the measurement and the MCNP simulation results associated with skin dose.ConclusionBased on the results of the points which had underdose, it was suggested that a bolus should be used for the given points. With regard to overdose points, it was advocated to consider skin tolerance dose in treatment planning. Differences between the measurement and the MCNP simulation results might be due to voxel size of tally cells in simulations, effect of beam’s angle of incidence, validation time of linac’s head, lack of electronic equilibrium in the build-up region, as well as MCNP tally type.     

Dosimetric impact of statistical uncertainty on Monte Carlo dose calculation algorithm in volumetric modulated arc therapy using Monaco TPS for three different clinical cases

AimTo study the dosimetric impact of statistical uncertainty (SU) per plan on Monte Carlo (MC) calculation in Monaco? treatment planning system (TPS) during volumetric modulated arc therapy (VMAT) for three different clinical cases.BackgroundDuring MC calculation SU is an important factor to decide dose calculation accuracy and calculation time. It is necessary to evaluate optimal acceptance of SU for quality plan with reduced calculation time.Materials and methodsThree different clinical cases as the lung, larynx, and prostate treated using VMAT technique were chosen. Plans were generated with Monaco? V5.11 TPS with 2% statistical uncertainty. By keeping all other parameters constant, plans were recalculated by varying SU, 0.5%, 1%, 2%, 3%, 4%, and 5%. For plan evaluation, conformity index (CI), homogeneity index (HI), dose coverage to PTV, organ at risk (OAR) dose, normal tissue receiving dose ≥5 Gy and ≥10 Gy, integral dose (NTID), calculation time, gamma pass rate, calculation reproducibility and energy dependency were analyzed.ResultsCI and HI improve as SU increases from 0.5% to 5%. No significant dose difference was observed in dose coverage to PTV, OAR doses, normal tissue receiving dose ≥5 Gy and ≥10 Gy and NTID. Increase of SU showed decrease in calculation time, gamma pass rate and increase in PTV max dose. No dose difference was seen in calculation reproducibility and dependent on energy.ConclusionFor VMAT plans, SU can be accepted from 1% to 3% per plan with reduced calculation time without compromising plan quality and deliverability by accepting variations in point dose within the target.     

Predictive value of vascular calcification identified in 4D planning CT of lung cancer patients treated with stereotactic body radiation therapy

PurposeThe aim was to identify vascular calcification in 4DCT scan of lung cancer patients and establish the association between overall survival (OS) and vascular calcification, as surrogate for vascular health.MethodsVascular calcification within the thoracic cavity were segmented in 334 lung cancer patients treated with stereotactic body radiation therapy (SBRT). This has been done automatically on 4D planning CT and average reconstruction scans. Correlation between cardiac comorbidity and calcification volumes was evaluated for patients with recorded Adult Co-Morbidity Evaluation (n = 303). Associations between the identified calcifications and OS were further investigated.ResultsThe volume of calcification from the average scan was significantly lower than from each phase (p < 0.001). The highest level of correlations between cardiac comorbidity and volume of the calcifications were found for one phase representing inhale and two phases representing exhale with the least motion blurring due to respiration (p < 0.005). The volume of the calcifications was subsequently averaged over these three phases. The average of calcification volumes over the three phases (denoted by inhale-exhale) showed the highest likelihood in univariate analysis and was chosen as vascular calcification measure. Cox-model suggested that tumor volume (Hazard Ratio [HR] = 1.46, p < 0.01) and inhale-exhale volume (HR = 1.05, p < 0.05) are independent factors predicting OS after adjusting for age, sex, and performance status.ConclusionIt was feasible to use. It 4DCT scan for identifying thoracic calcifications in lung cancer patients treated with SBRT. Calcification volumes from inhale-exhale phases had the highest correlation with overall cardiac comorbidity and the average of the calcification volume obtained from these phases was an independent predictive factor for OS.