Monte Carlo Dose Calculation Research Articles

TOPAS Monte Carlo simulation for a scanning proton therapy system in SPHIC

PurposeThis study aims to use TOPAS Monte Carlo (MC) code to model the beamline of a scanned proton therapy system in Shanghai Proton and Heavy Ion Center (SPHIC). This tool can be useful for treatment plan quality assurance. Methods and materialsIn-air lateral profiles of single proton spots at five positions along the Z-axis were measured, which can then be used to calculate the angular variance, spatial angular covariance, and spatial variance at the beam exit position. The mean energy and energy spread of the primary incident beam for 15 energies were tuned by comparing with measured relative integrated depth dose at the central axis. Three spread-out Bragg peak plans in homogeneous water cubes and one plan with a half anthropomorphic head phantom were created to verify the accuracy of the model. In addition, the comparison was also performed to RayStation TPS with an MC dose calculation engine for the plans. ResultsThe average difference of spot sizes was 1.3% for all five energies. For all 15 energies, the average range (D90) difference was 0.04 mm, the mean distal-fall-off (DDF) difference was 0.04 mm, and the mean full width at half maximum (FWHM) difference was 0.10 mm. For the three homogeneous cube plans, a maximum difference of 0.2 mm for the D90 was observed, and the absolute differences in the lateral penumbras for each plan all agreed within 1 mm. For the plan on the anthropomorphic half head phantom, the mean dose deviation is less than 1.2% compared to measurements. ConclusionWe successfully developed an MC model for the proton scanning system used in SPHIC, which can be helpful for dose verification of the Treatment Planning System (TPS) and quality assurance in the future.

Maintaining dosimetric quality when switching to a Monte Carlo dose engine for head and neck volumetric-modulated arc therapy planning.

Head and neck cancers present challenges in radiation treatment planning due to the large number of critical structures near the target(s) and highly heterogeneous tissue composition. While Monte Carlo (MC) dose calculations currently offer the most accurate approximation of dose deposition in tissue, the switch to MC presents challenges in preserving the parameters of care. The differences in dose‐to‐tissue were widely discussed in the literature, but mostly in the context of recalculating the existing plans rather than reoptimizing with the MC dose engine. Also, the target dose homogeneity received less attention. We adhere to strict dose homogeneity objectives in clinical practice. In this study, we started with 21 clinical volumetric‐modulated arc therapy (VMAT) plans previously developed in Pinnacle treatment planning system. Those plans were recalculated “as is” with RayStation (RS) MC algorithm and then reoptimized in RS with both collapsed cone (CC) and MC algorithms. MC statistical uncertainty (0.3%) was selected carefully to balance the dose computation time (1–2 min) with the planning target volume (PTV) dose‐volume histogram (DVH) shape approaching that of a “noise‐free” calculation. When the hot spot in head and neck MC‐based treatment planning is defined as dose to 0.03 cc, it is exceedingly difficult to limit it to 105% of the prescription dose, as we were used to with the CC algorithm. The average hot spot after optimization and calculation with RS MC was statistically significantly higher compared to Pinnacle and RS CC algorithms by 1.2 and 1.0 %, respectively. The 95% confidence interval (CI) observed in this study suggests that in most cases a hot spot of ≤107% is achievable. Compared to the 95% CI for the previous clinical plans recalculated with RS MC “as is” (upper limit 108%), in real terms this result is at least as good or better than the historic plans.

Abstract P3-19-10: Subcutaneous layer dosimetry of the breast and chest wall at clinical beam energies without bolus: A Monte Carlo and analytical anisotropic algorithm (AAA) calculation study

Abstract PURPOSE: Breast skin thickness is 3 mm (1). The subcutaneous layer (SL) lies immediately beneath the skin and is at risk for local recurrence after breast cancer surgery and adjuvant radiotherapy. As the SL lies within the buildup region for megavoltage radiation treatment, placement of bolus for patients receiving chest wall (CW) radiotherapy (RT) is routine at many centers. The dermal toxicity of bolus is well known: in 12 studies of CW RT, the pooled risk of Grade 3 acute toxicity is 9.6% with bolus and 1.2% without bolus (2). Meanwhile, bolus is rarely used after breast-conserving surgery (BCS) RT for patients with similar cancers. This study examines variation in tangential RT dose coverage of the SL in the intact breast and bolus-free CW with clinically relevant photon beam energies using Monte Carlo (MC) calculations and a commercial treatment planning system (TPS). METHODS: Thirty CT datasets from patients without skin involvement were identified. There were two groups of patients: 15 treated with BCS RT and 15 treated with CW RT. In each group, 5-patient subgroups had tangent-beam RT planned without bolus with 6, 10, and 15 MV photons, respectively, using the Analytical Anisotropic Algorithm (AAA) algorithm (v.13.6.23) in Eclipse v.15.6 (Varian Medical Systems Inc., Palo Alto, CA). On each CT, the SL was segmented as a high-resolution shell from 3 to 5 mm below the body contour in the Eclipse TPS v.15.6 (Varian Medical Systems Inc., Palo Alto, CA). A 1x1x1 mm MC dose simulation was performed using EGSnrc code (BEAMnrc/DOSXYZnrc). The MC dose distributions were imported back into the TPS for comparison with AAA calculations. The V95% and V90% for the SL were calculated for each case and the mean V95% and V90% were reported for each subgroup. A t-test was used with a two-sided alpha = 0.05 for statistical analysis. RESULTS: The mean separation increased with use of higher energies for both BCS and CW RT. The MC-calculated mean SL V90% and V95% were higher for CW RT than for BCS RT at each energy. The V90% coverage was 91.5% for CW and 74.4 % for BCS at 6 MV (p<0.001), 89.3% for CW and 61.3% for BCS (p<0.001) at 10 MV and 87.1% for CW and 60.9% for BCS (p<0.001) at 15 MV (Table 1). For SL V95% the CW coverage was higher than the BCS coverage for every energy. For SL V90% at 6 MV, the AAA and MC calculations agreed within 2.5%, with the MC being slightly higher. The agreement between AAA and MC decreased for higher energies with MC reporting higher SL V90% coverage by up to 16.3%. The higher MC-calculated dose to the SL is consistent with the literature (3). CONCLUSION: MC and AAA SL dose calculations agreed well for 6 MV, but AAA underestimated the dose for 10 and 15 MV. For 6-15 MV photons, the MC-calculated dosimetric coverage of the SL is higher for CW RT than BCS RT. Since radiation oncologists are satisfied with the SL coverage by BCS RT, bolus is not needed for CW RT, because, without bolus, CW RT delivers a higher SL dose than BCS RT. REFERENCES:. 1.Pope TL Jr, et al.J Can Assoc Radiol. 1984 Dec;35(4):365-8. PMID: 6526847. 2.Dahn HM, et al. Crit Rev Oncol Hematol. 2021 Jun 5;163:10339. PMID: 34102286. 3.Panettieri V, et al., Radiother Oncol 2009; 93: 94-101 Table 1.Monte Carlo calculated mean V90% and V95% for Breast and Chest Wall for each energyV95%V95%V95%V90%V90%V90%Energy(MV)Chest Wall(Mean)Breast. (Mean)p-valueChest Wall(Mean)Breast. (Mean)p-value661.9%35.1%<0.00191.5%74.4%<0.0011065.2%39.7%<0.00189.3%61.3%<0.0011561.7%38.9%0.01287.1%60.9%<0.001 Citation Format: Dylan Narinesingh, Alan Nichol, Alanah Bergman, Tony Popescu. Subcutaneous layer dosimetry of the breast and chest wall at clinical beam energies without bolus: A Monte Carlo and analytical anisotropic algorithm (AAA) calculation study [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-19-10.

A feasibility study for in vivo treatment verification of IMRT using Monte Carlo dose calculation and deep learning-based modelling of EPID detector response

BackgroundThis paper describes the development of a predicted electronic portal imaging device (EPID) transmission image (TI) using Monte Carlo (MC) and deep learning (DL). The measured and predicted TI were compared for two-dimensional in vivo radiotherapy treatment verification.MethodsThe plan CT was pre-processed and combined with solid water and then imported into PRIMO. The MC method was used to calculate the dose distribution of the combined CT. The U-net neural network-based deep learning model was trained to predict EPID TI based on the dose distribution of solid water calculated by PRIMO. The predicted TI was compared with the measured TI for two-dimensional in vivo treatment verification.ResultsThe EPID TI of 1500 IMRT fields were acquired, among which 1200, 150, and 150 fields were used as the training set, the validation set, and the test set, respectively. A comparison of the predicted and measured TI was carried out using global gamma analyses of 3%/3 mm and 2%/2 mm (5% threshold) to validate the model's accuracy. The gamma pass rates were greater than 96.7% and 92.3%, and the mean gamma values were 0.21 and 0.32, respectively.ConclusionsOur method facilitates the modelling process more easily and increases the calculation accuracy when using the MC algorithm to simulate the EPID response, and has potential to be used for in vivo treatment verification in the clinic.

Dose calculations for preclinical radiobiology experiments conducted with single-field cabinet irradiators.

To provide percentage depth dose (PDD) data along the central axis for dosimetry calculations in small-animal radiation biology experiments performed in cabinet irradiators. The PDDs are provided as a function of source-to-surface distance (SSD), field size, and animal size. The X-ray tube designs for four biological cabinet irradiators, the RS2000, RT250, MultiRad350, and XRAD320, were simulated using the BEAMnrc Monte Carlo code to generate 160, 200, 250, and 320kVp photon beams, respectively. The 320kVp beam was simulated with two filtrations: a soft F1 aluminium filter and a hard F2 thoraeus filter made of aluminium, tin, and copper. Beams were collimated into circular fields with diameters of 0.5-10cm at SSDs of 10-60cm. Monte Carlo dose calculations in 1-5-cm diameter homogeneous (soft tissue) small-animal phantoms as well as in heterogeneous phantoms with 3-mm diameter cylindrical lung and bone inserts (rib and cortical bone) were performed using DOSXYZnrc. The calculated depth doses in three test-cases were estimated by applying SSD, field size, and animal size correction factors to a reference case (40-cm SSD, 1-cm field, and 5-cm animal size), and these results were compared with the specifically simulated (i.e., expected) doses to assess the accuracy of this method. Dosimetry for two test-case scenarios of 160 and 250 kVp beams (representative of end-user beam qualities) was also performed, whereby the simulated PDDs at two different depths were compared with the results based on the interpolation from reference data. The depth doses for three test-cases calculated at 200, 320kVp F1, and 320kVp F2 with half value layers (HVLs) ranging from ∼0.6to 3.6mm Cu, agreed well with the expected doses, yielding dose differences of 1.2%, 0.1%, and 1.0%, respectively. The two end-user test-cases for 160 and 250 kVp beams with respective HVLs of ∼0.8 and 1.8mm Cu yielded dose differences of 1.4% and 3.2% between the simulated and the interpolated PDDs. The dose increase at the bone-tissue proximal interface ranged from 1.2 to 2.5 times the dose in soft tissue for rib and 1.3 to 3.7 times for cortical bone. The dose drop-off at 1-cm depth beyond the bone ranged from 1.3% to 6.0% for rib and 3.2% to 11.7% for cortical bone. No drastic dose perturbations occurred in the presence of lung, with lung-tissue interface dose of>99% of soft tissue dose and<3% dose increase at 1-cm depth beyond lung. The developed dose estimation method can be used to translate the measured dose at a point to dose at any depth in small-animal phantoms, making it feasible for preclinical calculation of dose distributions in animals irradiated with cabinet-style irradiators. The dosimetric impact of bone must be accurately quantified as dramatic dose perturbations at and beyond the bone interfaces can occur due to the relative importance of the photoelectric effect at kilovoltage energies. These results will help improve dosimetric accuracy in preclinical experiments.

Treatment Planning Study for Microbeam Radiotherapy Using Clinical Patient Data.

Simple SummaryMicrobeam radiotherapy is a novel dose delivery technique in radiation oncology. Preclinical studies have demonstrated preferable dose distributions with reduced damage to normal tissue but similar tumor control compared to conventional radiotherapy. For future clinical applications, realistic treatment plans for patient data are required as well as a method for comparing the spatially fractionated MRT doses with conventional broad beam doses. In this study, we performed MRT treatment planning on real patient data for relevant clinical scenarios. We successfully implemented a sophisticated dose comparison concept based on the equivalent uniform dose. For most scenarios and parameters studied, the clinical dose constraints were met. However, limitations were caused by the lack of treatment plan optimization and dose optimization. Altogether, we demonstrated the feasibility of achieving clinically acceptable MRT dose distributions based on real patient data as a primary major step towards clinical application of MRT.Microbeam radiotherapy (MRT) is a novel, still preclinical dose delivery technique. MRT has shown reduced normal tissue effects at equal tumor control rates compared to conventional radiotherapy. Treatment planning studies are required to permit clinical application. The aim of this study was to establish a dose comparison between MRT and conventional radiotherapy and to identify suitable clinical scenarios for future applications of MRT. We simulated MRT treatment scenarios for clinical patient data using an inhouse developed planning algorithm based on a hybrid Monte Carlo dose calculation and implemented the concept of equivalent uniform dose (EUD) for MRT dose evaluation. The investigated clinical scenarios comprised fractionated radiotherapy of a glioblastoma resection cavity, a lung stereotactic body radiotherapy (SBRT), palliative bone metastasis irradiation, brain metastasis radiosurgery and hypofractionated breast cancer radiotherapy. Clinically acceptable treatment plans were achieved for most analyzed parameters. Lung SBRT seemed the most challenging treatment scenario. Major limitations comprised treatment plan optimization and dose calculation considering the tissue microstructure. This study presents an important step of the development towards clinical MRT. For clinical treatment scenarios using a sophisticated dose comparison concept based on EUD and EQD2, we demonstrated the capability of MRT to achieve clinically acceptable dose distributions.

Reconstructive dosimetry and radiation dose evaluation of workers and public due to a Brazilian radiological accident in industrial radiography

Radiological accidents occur mainly in the practices recognized as high risk and which are classified by the International Atomic Energy Agency (IAEA) as Categories 1 and 2: radiotherapy, industrial irradiators and industrial radiography. In Brazil, five important cases in industrial gamma radiography occurred from 1985 to 2018, involving seven radiation workers and 19 members of the public. The accidents caused localized radiation lesions on the hands and fingers. One of these accidents is the focus of this paper. In this accident, a 3.28 TBq 192Ir radioactive source was left unshielded for 9 h in a non-destructive testing (NDT) company parking lot, and many radiation workers, employees and public, including teachers of a primary school were exposed. The radioactive source was also directly handled by a security worker for about 1.5 min causing severe radiation injuries in the hand and fingers. This paper presents radiation dose estimates for all accidentally exposed individuals. Four scenarios were considered, and three internationally recognised and updated reconstructive dosimetry techniques were used, named, Brazilian visual Monte Carlo Dose Calculation (VMC), virtual environment for radiological and nuclear accidents simulation (AVSAR) and RADPRO Calculator®. The main radiation doses estimated by VMC were the absorbed dose of 34 Gy for the security worker’s finger and his effective dose of 91 mSv; effective doses from 43 to 160 mSv for radiation workers and NDT employees; and effective doses of 9 mSv for teachers in the schoolyard.

Monte Carlo Dose Calculation - A QA Method for SRT and SBRT Plans in Treating Multiple and Small Metastatic Lesions.

To provide accurate and fast 3-D dose verification for hypofractionated stereotactic radiotherapy (SRT/SBRT) of small and multi targets calculated with a Varian Eclipse treatment planning system (TPS) delivered on a Varian accelerator. Ten brain and lung hypofractionated SRT/SBRT linac-based and CyberKnife plans were generated by the Eclipse system for delivery on the accelerator with the Millenium-120 leaf multileaf collimator (MLC) and Multiplan for the CyberKnife machine. These clinical SRT/SBRT plans required accurate quality assurance measurements to obtain absolute point dose and 3-D dose distributions due to the low number of fractions and high fraction doses. For small-field and multi-target plans, the EGS4/MCSIM code was used to calculate the dose distribution. A 0.125 cc ion chamber, a 0.016 cc pin-point chamber and Kodak EDR2 film were used for the measurements and the results were compared with Monte Carlo (MC) calculations. The dosimetry for small-field and multi-target treatment plans is challenging due to the comparable range of secondary electrons and the field sizes defined by SRT/SBRT MLC segments. Our MC simulations can accurately reproduce the linac dose distributions (within 1%/1 mm) three dimensionally. For the clinical SRT/SBRT plans investigated in this work, the MC doses agreed within 3% with ion chamber measurements and within 2%/2 mm with film measurements. The doses calculated by the Eclipse AAA algorithm and Multiplan differed by no more than 5% from MC calculations for small (4–40 cc) Planning Target Volumes (PTVs). MC dose calculation provides accurate and fast 3-D dose verification for hypofractionated SRT for small and multi-target treatment plans generated by a Varian Eclipse TPS on a Varian accelerator and Multiplan treatment planning on the CyberKnife System.

Evaluating the accuracy of electron pencil beam dosimetry based on Monte Carlo simulations using homogeneous and heterogeneous phantoms

PurposeThis study aimed to assess the accuracy of the electron pencil beam algorithm (PBA) regarding Monte Carlo (MC) simulations for irradiating homogeneous and heterogeneous phantoms. MethodsThe PBA program was reproduced in the MATLAB software package. The lateral scattering factors were calculated using MC simulations and imported to the PBA program. The line dose values (profile curves) in various depths for a simple water phantom, a slab phantom with different layers, and a heterogeneous phantom with rods equivalent to bone tissue were calculated using PBA and compared to the MC simulation results for 6, 10, and 12 MeV electron beams. The mean differences and root mean square of error (RMSE) were obtained between the PBA and MC calculations. Furthermore, gamma analysis was used to compare the profile doses of PBA calculations with MC simulations. ResultsThe mean differences between the PBA and MC dose calculations were less than 1% for 10 and 12 MeV electron energies, and lower than 2% for the 6 MeV electron irradiation in all the assessed phantoms. The profile dose calculations showed that the separation of two isodose curves was less than 2 mm in central regions of the fields and less than 3 mm in the fields’ edge/penumbra regions and inhomogeneity interfaces. The gamma pass rate values ranged from 94.1 to 100% (average of 96.4%) in different phantoms, depths, and energy ranges. ConclusionThe PBA provided acceptable accuracy for radiotherapy electron dose calculations in a water phantom, slab phantom (with different materials), and heterogeneous phantom compared to MC dose simulations, as a reference dose calculation method.

A Systematic Approach to Optimise the Number of Beams for Intensity Modulated Radiotherapy in Pituitary Adenoma using Radiobiological Parameters

Introduction: The number of beams used in a Radiotherapy (RT) plan effects the overall quality of the plan and hence the treatment. The inclusion of radiobiological concepts in finding the optimum number of beams for a particular planning technique has the potential to provide a step ahead of the routine clinical practice where clinical decisions are more dependent on the physical dose parameters. Aim: To optimise the number of beams for Intensity Modulated Radiotherapy (IMRT) plan based on Tumour Control Probability (TCP) and Normal Tissue Complication Probability (NTCP) biological parameters. Materials and Methods: This retrospective study was done on 30 patients with pituitary macro-adenoma who underwent radiotherapy with a prescribed dose of 50.4 Gy in 28 fractions in Delhi State Cancer Institutes, Delhi, India from December 2012 to August 2018. The study data was collected and analysed between June 2018 and April 2020. These patients were treated with step and shoot IMRT technique on ONCORTM Expression linear accelerator (Siemens Healthineers, USA). But, the number of beams used to deliver IMRT plans were different as decided by the medical physicist and hence planner dependent rather than the disease. Being a centrally located disease, a symmetric beam arrangement was adopted for IMRT planning. For dosimetric comparison, three IMRT plans with five, seven, and nine equispaced beams were generated in Monaco treatment planning system for each patient and thus, a total of 90 IMRT plans were created and evaluated. For fair comparison, same IMRT planning parameters were utilized in all three plans of each patient. Monte Carlo (MC) dose calculation algorithm was used for all the plans. Resulting Cumulative Dose Volume Histograms (CDVHs) were exported to MATLAB, where these cDVHs were processed as per Niemierko’s radiobiological model to calculate the values of TCP and NTCP based on the Equivalent Uniform Dose (EUD). After this, the analysis of variance, ANOVA test was conducted over the resulting values of EUD, TCP, and NTCP to assess the difference of quality among plans having different beam arrangements at 0.05 level of significance. Results: The mean tumour control probability (TCP) for IMRT plans with seven and nine beams were found to be 89.0±0.8% and 89.1±0.9% respectively for planning target volume (PTV). These values were not significantly different from each other. However, the mean TCP value for IMRT plans with five beams was found to be 88.4±1.1% for PTV. Further, this TCP value was proved to be significantly lower as compared to IMRT plans with seven and nine beams with a p-value of 0.008 and 0.004 respectively. On the other hand, the mean Normal Tissue Complication Probability (NTCP) was assessed to be less than 1% for all critical organs irrespective of the beam arrangement, indicating almost no probability of radiation induced toxicity in any of the organ. Conclusion: This study concludes that the plan efficiency can be improved by using optimum number of beams for IMRT planning of pituitary adenoma.

Improving dose calculation accuracy in preclinical radiation experiments using multi-energy element resolved cone-beam CT

Objective. Cone-beam CT (CBCT) in modern pre-clinical small-animal radiation research platforms provides volumetric images for image guidance and experiment planning purposes. In this work, we implemented multi-energy element-resolved (MEER) CBCT using three scans with different kVps on a SmART platform (Precision x-ray Inc.) to determine images of relative electron density (rED) and elemental composition (EC) that are needed for Monte Carlo-based radiation dose calculation. Approach. We performed comprehensive calibration tasks to achieve sufficient accuracy for this quantitative imaging purpose. For geometry calibration, we scanned a ball bearing phantom and used an analytical method together with an optimization approach to derive gantry angle specific geometry parameters. Intensity calibration and correction included the corrections for detector lag, glare, and beam hardening. The corrected CBCT projection images acquired at 30, 40, and 60 kVp in multiple scans were used to reconstruct CBCT images using the Feldkamp–Davis–Kress reconstruction algorithm. After that, an optimization problem was solved to determine images of rED and EC. We demonstrated the effectiveness of our CBCT calibration steps by showing improvements in image quality and successful material decomposition in cases with a small animal CT calibration phantom and a plastinated mouse phantom. Main results. It was found that artifacts induced by geometry inaccuracy, detector lag, glare, and beam hardening were visually reduced. CT number mean errors were reduced from 19% to 5%. In the CT calibration phantom case, median errors in H, O, and Ca fractions for all the inserts were below 1%, 2%, and 4% respectively, and median error in rED was less than 5%. Compared to the standard approach deriving material type and rED via CT number conversion, our approach improved Monte Carlo simulation-based dose calculation accuracy in bone regions. Mean dose error was reduced from 47.5% to 10.9%. Significance. The MEER-CBCT implemented on an existing CBCT system of a small animal irradiation platform achieved accurate material decomposition and significantly improved Monte Carlo dose calculation accuracy.

Validation of Monte Carlo dose calculation algorithm for CyberKnife multileaf collimator.

PurposeTo commission and evaluate the Monte Carlo (MC) dose calculation algorithm for the CyberKnife equipped with a multileaf collimator (MLC).MethodsWe created a MC model for the MLC using an integrated module of the CyberKnife treatment planning software (TPS). Two parameters could be optimized: the maximum energy and the source full width at half‐maximum (FWHM). The optimization was performed by minimizing the differences between the measured and the MC calculated tissue phantom ratios and profiles. MLC plans were calculated in the TPS with the MC algorithm and irradiated on different phantoms. The dose was measured using an A1SL ionization chamber and EBT3 Gafchromic films, and then compared to the TPS dose to obtain dose differences (ΔD). Finally, patient‐specific quality assurances (QA) were performed with global gamma index criteria of 3%/1 mm.ResultsThe maximum energy and source FWHM showing the best agreement with measurements were 6.4 MeV and 1.8 mm. The output factors calculated with these parameters gave an agreement within ±1% with measurements. The ΔD showed that MC model systematically underestimated the dose with an average of −1.5% over all configurations tested. For depths deeper than 12 cm, the ΔD increased, up to −3.0% (maximum at 15.5 cm depth).ConclusionsThe MC model for MLC of CyberKnife is clinically acceptable but underestimates the delivered dose by an average of −1.5%. Therefore, we recommend using the MC algorithm with the MLC only in heterogeneous regions and for shallow‐seated tumors.

Evaluation of a treatment planning system developed for clinical boron neutron capture therapy and validation against an independent Monte Carlo dose calculation system

Boron neutron capture therapy (BNCT) for the treatment of unresectable, locally advanced, and recurrent carcinoma of the head and neck cancer has been approved by the Japanese government for reimbursement under the national health insurance as of June 2020. A new treatment planning system for clinical BNCT has been developed by Sumitomo Heavy Industries, Ltd. (Sumitomo), NeuCure® Dose Engine. To safely implement this system for clinical use, the simulated neutron flux and gamma ray dose rate inside a water phantom was compared against experimental measurements. Furthermore, to validate and verify the new planning system, the dose distribution inside an anthropomorphic head phantom was compared against a BNCT treatment planning system SERA and an in-house developed Monte Carlo dose calculation program. The simulated results closely matched the experimental results, within 5% for the thermal neutron flux and 10% for the gamma ray dose rate. The dose distribution inside the head phantom closely matched with SERA and the in-house developed dose calculation program, within 3% for the tumour and a difference of 0.3 Gyw for the brain.

Magnetic Resonance Image Guided Adaptive Radiation Therapy: Clinical Applications in the Pediatric and Adolescent and Young Adult Population

<h3>Purpose/Objective(s)</h3> To demonstrate the feasibility of online adaptive magnetic resonance (MR) image guided radiotherapy in the pediatric, adolescent and young adult (AYA) population. <h3>Materials/Methods</h3> All pediatric (age < 18) and AYA patients (age < 30), treated on an MR linear accelerator (MRL) from 2019 to 2021 were enrolled onto a prospective registry. The system is used with a related treatment planning system which employs a Monte Carlo dose calculation algorithm to account for effects of the magnetic field on the dose distribution. Step-and-Shoot intensity-modulated radiation treatment (IMRT) plans were generated for all Unity patients with a dose grid of 3 mm and a statistical uncertainty of ≤ 1% per plan. CT and MR images were obtained for each patient for initial radiation treatment planning. Daily treatment setup consisted of a volumetric MRI scan followed by rigid registration used to evaluate the agreement between the reference plan contours and daily shifts in internal anatomy. If necessary, based on evaluation of the daily anatomy, online recontouring and plan re-optimization was performed. <h3>Results</h3> A total of 14 pediatric and AYA patients have been treated. The median patient age is 13 years (range: 14 mo -27 yrs). Four patients were ≤ 8 years old. Reasons for treatment on the MRL were improved visualization of the primary tumor, re-irradiation in a critical area, and need for daily adaptive replanning to minimize dose to critical structures The clinical applications of MR-guided radiotherapy included Ewing sarcoma (primary and metastatic, n = 3), recurrent diffuse intrinsic pontine glioma (DIPG, n = 2), nasopharyngeal carcinoma (n = 1), clival chordoma (n = 1), primitive neuroectodermal tumor of the pancreas (n = 1), recurrent gluteo-sacral germ cell tumor (n = 1), Wilms tumor with unresectable IVC thrombus (n = 1), C-spine ependymoma (n = 1), and posterior fossa ependymoma (n = 1). Only one child (age 14 mo. with Wilms tumor required anesthesia. One AYA patient with Ewing sarcoma of C1 could not complete the treatment course due to pain related to longer treatment times and was transferred to a conventional linear accelerator. No patient experienced treatment interruptions or unexpected toxicity. Reasons for plan adaptation included changes in stomach and small bowel anatomy, target shape change on a near-daily basis, critical location adjacent to the brainstem, and manipulation of hot spots near the spinal cord. <h3>Conclusion</h3> Radiotherapy on the MRL was well-tolerated by pediatric and AYA patients. There was no increased use of anesthesia outside of our usual practice. Significant dosimetric advantages were seen for patients with tumors in critical locations such as adjacent to or involving the brainstem, spinal cord or near abdominal organs that change shape and location daily.

Cone Beam CT-Based Online Evaluation in Two Minutes Using a Commercial Treatment Planning Software for Proton Therapy

Daily online treatment evaluation is essential for proton therapy, which is sensitive to daily anatomy and setup uncertainties. We have developed a program based on a commercial treatment planning system (TPS) to streamline the online evaluation process using pre-treatment cone-beam CT (CBCT) images. Herein, we evaluate the speed and accuracy of the tool based on clinical proton plans.Data from 25 previously treated proton patients (7 HN, 11 lung, and 7 prostate) at our institution were evaluated. Corrected CBCT (cCBCT) images were generated using a research version of the TPS, which removes artifacts and calibrates HU for proton dose calculation. A quality assurance simulation CT (QACT) scanned on the same day as the CBCT is deformed to the cCBCT and used as a reference (dQACT). The cCBCT is deformed to the treatment planning CT (TPCT), and all contours on the initial TPCT were deformed to the cCBCT and then rigidly copied to the dQACT. Original clinical treatment plans were applied to both the cCBCT and dQACT, and the doses were calculated with the GPU-based Monte-Carlo dose calculation engine at 0.5% statistical uncertainty. The entire evaluation time (Eval_time) from importing CBCT image to completing final dose calculation for cCBCT was recorded. Plan parameters, including the number of beams (N_bm), proton spot number (N_sp), dose grid voxel numbers (N_voxel), were collected. Pearson correlation coefficient between the Eval_time and the N_bm, N_sp, and N_vosel were calculated. Dosimetric parameters were calculated for the cCBCT and compared to those calculated from the reference dQACT. Dosimetric parameters of interest included the following: for all, CTV D99, D95, and V100, and plan maximum dose (Dmax); for H&N cases, parotid mean dose (P_Dmean) and V30Gy (P_V30), and oral cavity mean dose (C_Dmean); and for H&N and lung cases, spinal cord max dose (SC_Dmax).Mean online Eval_time is 106.6 ± 24.9s for all patients, with HN as the fastest site 87.9 ± 17.5s for HN, 104.5 ± 15.9s for lung, 128.5 ± 28.0s for prostate, P < 0.01. The corresponding (N_bm, N_sp, N_voxel) were (3.9, 7781, 2.6E6) for HN, (3.3, 11080, 2.4E6) for lung, and (3.0, 10484, 3.8E6) for prostate. Eval_time was significantly correlated to N_sp (P = 0.02), but not to N_bm and N_voxel. The absolute differences for CTV D99, D95, V100, plan Dmax, HN P_Dmean, P_V30, C_Dmean, and SC_Dmax are 0.85 ± 0.60%, 0.39 ± 0.22%, 0.48 ± 0.41%, 0.46 ± 0.48%, 0.08 ± 0.05Gy, 0.05 ± 0.06%, 0.21 ± 0.20 Gy, and 0.57 ± 0.53Gy, respectively.Online evaluation can be achieved within 2 minutes for most clinical proton cases (80% in this study) with the commercial TPS. The speed can be further increased with reduced OAR mapping, fine-tuned deformable registration, optimized and reduced spot number in the initial plans, and upgraded computer server. This proposed method may optimize the efficiency and quality of care for proton radiotherapy.

Experimental validation of Fastcat kV and MV cone beam CT (CBCT) simulator.

To experimentally validate the Fastcat cone beam computed tomography (CBCT) simulator against kV and MV CBCT images acquired with a Varian Truebeamlinac. kV and MV CBCT images of a Catphan 504 phantom were acquired using a 100 kVp beam with the on-board imager (OBI) and a 6 MV treatment beam with the electronic portal imaging device (EPID), respectively. The kV Fastcat simulation was performed using detailed models of the x-ray source, bowtie filter, a high resolution voxelized virtual Catphan phantom, anti-scatter grid, and the CsI scintillating detector. Likewise, an MV Fastcat CBCT was simulated with detailed models for the beam energy spectrum, flattening filter, a high-resolution voxelized virtual Catphan phantom, and the gadolinium oxysulfide (GOS) scintillating detector. Experimental and simulated CBCT images of the phantom were compared with respect to HU values, contrast to noise ratio (CNR), and dose linearity. Detector modulation transfer function (MTF) for the two detectors were also experimentally validated. Fastcat's dose calculations were compared to Monte Carlo (MC) dose calculations performed with Topas. For the kV and MV simulations, respectively: Contrast agreed within 14 and 9 HUs and detector MTF agreed within 4.2% and 2.5%. Likewise, CNR had a root mean squared error (RMSE) of 2.6% and 1.4%. Dose agreed within 2.4% and 1.6% of MC values. The kV and MV CBCT images took 71 and 72 s to simulate in Fastcat with 887 and 493 projections, respectively. We present a multienergy experimental validation of a fast and accurate CBCT simulator against a commercial linac. The simulator is open source and all models found in this work can be downloaded from https://github.com/jerichooconnell/fastcat.git.

Efficient uncertainty quantification for Monte Carlo dose calculations using importance (re-)weighting

Objective. To present an efficient uncertainty quantification method for range and set-up errors in Monte Carlo (MC) dose calculations. Further, we show that uncertainty induced by interplay and other dynamic influences may be approximated using suitable error correlation models. Approach. We introduce an importance (re-)weighting method in MC history scoring to concurrently construct estimates for error scenarios, the expected dose and its variance from a single set of MC simulated particle histories. The approach relies on a multivariate Gaussian input and uncertainty model, which assigns probabilities to the initial phase space sample, enabling the use of different correlation models. Through modification of the phase space parameterization, accuracy can be traded between that of the uncertainty or the nominal dose estimate. Main results. The method was implemented using the MC code TOPAS and validated for proton intensity-modulated particle therapy (IMPT) with reference scenario estimates. We achieve accurate results for set-up uncertainties (γ 2 mm/2% ≥ 99.01% (E[ d ]), γ 2 mm/2% ≥ 98.04% (σ( d ))) and expectedly lower but still sufficient agreement for range uncertainties, which are approximated with uncertainty over the energy distribution. Here pass rates of 99.39% (E[ d ])/ 93.70% (σ( d )) (range errors) and 99.86% (E[ d ])/ 96.64% (σ( d )) (range and set-up errors) can be achieved. Initial evaluations on a water phantom, a prostate and a liver case from the public CORT dataset show that the CPU time decreases by more than an order of magnitude. Significance. The high precision and conformity of IMPT comes at the cost of susceptibility to treatment uncertainties in particle range and patient set-up. Yet, dose uncertainty quantification and mitigation, which is usually based on sampled error scenarios, becomes challenging when computing the dose with computationally expensive but accurate MC simulations. As the results indicate, the proposed method could reduce computational effort while also facilitating the use of high-dimensional uncertainty models.

Dose calculation accuracy in particle therapy: Comparing carbon ions with protons.

PurposeThis work presents the validation of an analytical pencil beam dose calculation algorithm in a commercial treatment planning system (TPS) for carbon ions by measurements of dose distributions in heterogeneous phantom geometries. Additionally, a comparison study of carbon ions versus protons is performed considering current best solutions in commercial TPS.MethodsAll treatment plans were optimized and calculated using the RayStation TPS (RaySearch, Sweden). The dose distributions calculated with the TPS were compared with measurements using a 24‐pinpoint ionization chamber array (T31015, PTW, Germany). Tissue‐like inhomogeneities (bone, lung, and soft tissue) were embedded in water, while a target volume of 4 x 4 x 4 cm3 was defined at two different depths behind the heterogeneities. In total, 10 different test cases, with and without range shifter as well as different air gaps, were investigated. Dose distributions inside as well as behind the target volume were evaluated.ResultsInside the target volume, the mean dose difference between calculations and measurements, averaged over all test cases, was 1.6% for carbon ions. This compares well to the final agreement of 1.5% obtained in water at the commissioning stage of the TPS for carbon ions and is also within the clinically acceptable interval of 3%. The mean dose difference and maximal dose difference obtained outside the target area were 1.8% and 13.4%, respectively. The agreement of dose distributions for carbon ions in the target volumes was comparable or better to that between Monte Carlo (MC) dose calculations and measurements for protons. Percentage dose differences of more than 10% were present outside the target area behind bone–lung structures, where the carbon ion calculations systematically over predicted the dose. MC dose calculations for protons were superior to carbon ion beams outside the target volumes.ConclusionThe pencil beam dose calculations for carbon ions in RayStation were found to be in good agreement with dosimetric measurements in heterogeneous geometries for points of interest located within the target. Large local discrepancies behind the target may contribute to incorrect dose predictions for organs at risk.

Technical note: A fast and accurate analytical dose calculation algorithm for 125 I seed-loaded stent applications.

The safety and clinical efficacy of 125 I seed-loaded stent for the treatment of portal vein tumor thrombosis (PVTT) have been shown. Accurate and fast dose calculation of the 125 I seeds with the presence of the stent is necessary for the plan optimization and evaluation. However, the dosimetric characteristics of the seed-loaded stents remain unclear and there is no fast dose calculation technique available. This paper aims to explore a fast and accurate analytical dose calculation method based on Monte Carlo (MC) dose calculation, which takes into account the effect of stent and tissue inhomogeneity. A detailed model of the seed-loaded stent was developed using 3D modeling software and subsequently used in MC simulations to calculate the dose distribution around the stent. The dose perturbation caused by the presence of the stent was analyzed, and dose perturbation kernels (DPKs) were derived and stored for future use. Then, the dose calculation method from AAPM TG-43 was adapted by integrating the DPK and appropriate inhomogeneity correction factors (ICF) to calculate dose distributions analytically. To validate the proposed method, several comparisons were performed with other methods in water phantom and voxelized CT phantoms for three patients. The stent has a considerable dosimetric effect reducing the dose up to 47.2% for single-seed stent and 11.9%-16.1% for 16-seed stent. In a water phantom, dose distributions from MC simulations and TG-43-DP-ICF showed a good agreement with the relative error less than 3.3%. In voxelized CT phantoms, taking MC results as the reference, the relative errors of TG-43 method can be up to 33%, while those of TG-43-DP-ICF method were less than 5%. For a dose matrix with 256 × 256 × 46 grid (corresponding to a phantom of 17.2 × 17.2 × 11.5cm3 ) for 16-seed-loaded stent, it only takes 17s for TG-43-DP-ICF to compute, compared to 25h for the full MC calculation. The combination of DPK and inhomogeneity corrections is an effective approach to handle both the presence of stent and tissue heterogeneity. Exhibiting good agreement with MC calculation and computational efficiency, the proposed TG-43-DP-ICF method is adequate for dose evaluation and optimization in seed-loaded stent implantation treatment planning.

Dose calculation accuracy for photon small fields in treatment planning systems with comparison by Monte Carlo simulations

Abstract Purpose: Advanced radiation therapy techniques use small fields in treatment planning and delivery. Small fields have the advantage of more accurate dose delivery, but with the cost of some complications in dosimetry. Different dose calculation algorithms imported in various treatment planning systems (TPSs) which each of them has different accuracy. Monte Carlo (MC) simulation has been reported as one of the accurate methods for calculating dose distribution in radiation therapy. The aim of this study was the evaluation of TPS dose calculation algorithms in small fields against 2 MC codes. Methods: A linac head was simulated in 2 MC codes, MCNPX, and GATE. Then three small fields (0.5×0.5, 1×1 and 1.5×1.5 cm2) were simulated with 2 MC codes, and also these fields were planned with different dose calculation algorithms in Isogray and Monaco TPS. PDDs and lateral dose profiles were extracted and compared between MC simulations and dose calculation algorithms. Results: For 0.5×0.5 cm2 field mean differences in PDDs with MCNPX were 2.28, 4.6, 5.3, and 7.4% and with GATE were -0.29, 2.3, 3 and 5% for CCC, superposition, FFT and Clarkson algorithms respectively. For 1×1 cm2 field mean differences in PDDs with MCNPX were 1.58, 0.6, 1.1 and 1.4% and with GATE were 0.77, 0.1, 0.6 and 0.9% for CCC, superposition, FFT and Clarkson algorithms respectively. For 1.5×1.5 cm2 field mean differences in PDDs with MCNPX were 0.82, 0.4, 0.6 and -0.4% and with GATE were 2.38, 2.5, 2.7 and 1.7% for CCC, superposition, FFT and Clarkson algorithms respectively. Conclusions: Different dose calculation algorithms were evaluated and compared with MC simulation in small fields. Mean differences with MC simulation decreased with the increase of field sizes for all algorithms.