Comparison of the RayStation photon Monte Carlo dose calculation algorithm against measured data under homogeneous and heterogeneous irradiation geometries

Beam modeling and validation for a 1.5 T MR-linac in an alternative treatment planning system

Objective.MR-guided adaptive radiotherapy (MRgART) is ideally suited to adjust the treatment plan for anatomical changes. The online nature of MRgART involves multiple process steps during each treatment fraction, which may greatly benefit from automation. TheRayStationtreatment planning system incorporates automation features by design, but requires dose calculations in the presence of an external magnetic field and the modeling of the MRgART system. This study developed and commissioned a comprehensive model for the 1.5 T MR-guided linear accelerators (MR-linacs) inRayStation.Approach.MR-linac dose profiles and output factors were used to model the Unity MR-linac inRayStation. The MR cryostat was implemented in the Monte Carlo simulation as a multi-layer barrel, adjusted using simulations and in-air output measurements. The cryostat transmission variation with gantry angle was added as a fluence correction. Dose distributions of on-axis square, off-axis square, and 90 IMRT fields of ten prostate MR-linac treatment plans were evaluated with the PTW Octavius 1500MR detector array. The radiofrequency coils and couch were characterized with megavoltage imager transmission measurements. CT scans of the coils were used to model its geometry inRayStationand mass densities were assigned to match the measured attenuation.Results.Differences between measured and calculated depth dose showed aγ< 0.5 beyonddmax. For both the inline and crossline profiles, theγevaluation exhibited aγ< 1.0 for nearly all evaluated points. The maximum difference between the measured and calculated cryostat scatter was 0.6%. The averageγpass rate for the on-axis, off-axis, and IMRT fields was >98.3% (range: 91.2%-100%). The average coil transmissions were 0.6 (anterior) and 2.2% (posterior).Significance.We successfully modeled and commissioned the 1.5 T MR-linac inRayStationwell within tolerance limits as specified by the American Association of Physicists in Medicine TG-157 report.

Hybrid Monte Carlo model for efficient tissue Cherenkov emission estimation to assess changes from beam size, energy and incidence

PURPOSE

Cherenkov imaging in radiation therapy provides key knowledge of the delivery of treatment plans, but light-tissue interactions alter the emitted spectral signal and cause the modeling of emission relative to dose in highly modulated treatment plans to be complex.

METHODS

A 2-stage Monte Carlo approach to modeling Cherenkov emission was developed that leverages a traditional treatment planning system with an optical Monte Carlo simulation to provide a widely useable and efficient tool for modeling every beam control point for delivery interpretation of highly-modulated treatment plans. The emitted optical spectra were estimated for 6, 10, 15MV photon beams, 6 MeV electron beams, beam incidence in tissue, and square field sizes from 1 cm to 20 cm. The model was validated through comparison of measured Cherenkov emission from a blood and intralipid optical phantom.

RESULTS

The resulting hybrid model provides an efficient method of estimating Cherenkov emission for linac beams, showing a clear trend of decreasing emission intensity with increasing beam energy and strong emission intensity variation with beam type. The largest change in observed intensity was from altering field size, with a 76 % intensity decrease when going from 20 cm down to 1 cm square. The model showed agreement with experimental detected Cherenkov with an average percent difference of 6.2 % with the largest difference at the very smallest beam sizes.

CONCLUSION

The model potentially allows for modeling entire modulated treatment plans with high computational efficiency and is a key step to translate delivered dose and observed Cherenkov in highly modulated situations.

Dummy run study for outlining and plan quality of intensity-modulated radiotherapy in elderly patients with newly diagnosed glioblastoma: The Japan clinical oncology group study JCOG1910 (AgedGlio-PIII)

BACKGROUND

A dummy run was conducted to ensure the quality of intensity-modulated radiotherapy (IMRT) before registration in a randomized phase III study of elderly patients with newly diagnosed glioblastoma by the Japan Clinical Oncology Group 1910 (JCOG1910).

METHODS

All 41 institutions enrolled in this study were required to report outlining that included gross tumor volume (GTV), clinical target volume (CTV), planning target volume (PTV), and treatment planning for one benchmark case. First, deviations in outlining were evaluated using the Dice similarity coefficient (DSC) and mean distance agreement (MDA), compared to reference targets delineated by the research secretariat. Second, the participating institutions were required to create treatment plans for arms A (40.05 Gy in 15 fractions) and B (25 Gy in 5 fractions) using IMRT techniques. The quality of the outlining and dose-volume criteria for each target and organs at risk were evaluated.

RESULTS

Six institutions failed to adhere to the protocol and required revision due to insufficient GTV outlining, not considering anatomical barriers for CTV, and modifying PTV against protocols. Compared to the reference outlining, the means and standard deviations of DSC and MDA were 0.37 ± 0.19 and 9.41 ± 3.99 mm for GTV; 0.80 ± 0.08 and 4.31 ± 1.85 mm for CTV; and 0.83 ± 0.05 and 4.23 ± 1.45 mm for PTV, respectively. Regarding dose-volume criteria, 40 of the 41 institutions met the per-protocol limits; only one was within the acceptable limits.

CONCLUSIONS

Several institutions demonstrated deviations in outlining that necessitated revisions. Thus, appropriate feedback and periodic sharing of information with participating institutions is necessary in the upcoming prospective JCOG1910 study.

Comparative assessment and QA measurement array validation of Monte Carlo and Collapsed Cone dose algorithms for small fields and clinical treatment plans

PURPOSE

Many studies have demonstrated superior performance of Monte Carlo (MC) over type B algorithms in heterogeneous structures. However, even in homogeneous media, MC dose simulations should outperform type B algorithms in situations of electronic disequilibrium, such as small and highly modulated fields. Our study compares MC and Collapsed Cone (CC) dose algorithms in RayStation 12A. Under consideration are 6 MV and 6 MV flattening filter-free (FFF) photon beams, relevant for VMAT plans such as head-and-neck and stereotactic lung treatments with heterogeneities, as well as plans for multiple brain metastases in one isocenter, involving highly modulated small fields. We aim to investigate collimator angle dependence of small fields and performance differences between different combinations of ArcCHECK configuration and dose algorithm.

METHODS

Several verification tests were performed, ranging from simple rectangular fields to highly modulated clinical plans. To evaluate and compare the performance of the models, the agreements between calculation and measurement are compared between MC and CC. Measurements include water tank measurements for test fields, ArcCHECK measurements for test fields and VMAT plans, and film dosimetry for small fields.

RESULTS AND CONCLUSIONS

In very small or narrow fields, our measurements reveal a strong dependency of dose output to collimator angle for VersaHD with Agility MLC, reproduced by both dose algorithms. ArcCHECK results highlight a suboptimal agreement between measurements and MC calculations for simple rectangular fields when using inhomogeneous ArcCHECK images. Therefore, we advocate for the use of homogeneous phantom images, particularly for static fields, in ArcCHECK verification with MC. MC might offer performance benefits for more modulated treatment fields. In ArcCHECK results for clinical plans, MC performed comparable to CC for 6 MV. For 6 MV FFF and the preferred homogeneous phantom image, MC resulted in consistently better results (13%-64% lower mean gamma index) compared to CC.

Influence of dose calculation algorithms on the helical diode array using volumetric-modulated arc therapy for small targets

BACKGROUND

For patient-specific quality assurance (PSQA) for small targets, the dose resolution can change depending on the characteristics of the dose calculation algorithms.

PURPOSE

This study aimed to evaluate the influence of the dose calculation algorithms Acuros XB (AXB), anisotropic analytical algorithm (AAA), photon Monte Carlo (pMC), and collapsed cone (CC) on a helical diode array using volumetric-modulated arc therapy (VMAT) for small targets.

MATERIALS AND METHODS

ArcCHECK detectors were inserted with a physical depth of 2.9 cm from the surface. To evaluate the influence of the dose calculation algorithms for small targets, rectangular fields of 2×100, 5×100, 10×100, 20×100, 50×100, and 100×100 mm2 were irradiated and measured using ArcCHECK with TrueBeam STx. A total of 20 VMAT plans for small targets, including the clinical sites of 19 brain metastases and one spine, were also evaluated. The gamma passing rates (GPRs) were evaluated for the rectangular fields and the 20 VMAT plans using AXB, AAA, pMC, and CC.

RESULTS

For rectangular fields of 2×100 and 5×100 mm2, the GPR at 3%/2 mm of AXB was < 50% because AXB resulted in a coarser dose resolution with narrow beams. For field sizes > 10×100 mm2, the GPR at 3%/2 mm was > 88.1% and comparable for all dose calculation algorithms. For the 20 VMAT plans, the GPRs at 3%/2 mm were 79.1 ± 15.7%, 93.2 ± 5.8%, 94.9 ± 4.1%, and 94.5 ± 4.1% for AXB, AAA, pMC, and CC, respectively.

CONCLUSION

The behavior of the dose distribution on the helical diode array differed depending on the dose calculation algorithm for small targets. Measurements using ArcCHECK for VMAT with small targets can have lower GPRs owing to the coarse dose resolution of AXB around the detector area.

Dosimetric validation of SmART-RAD Monte Carlo modelling for x-ray cabinet radiobiology irradiators

Objective. Accuracy and reproducibility in the measurement of radiation dose and associated reporting are critically important for the validity of basic and preclinical radiobiological studies performed with kilovolt x-ray radiation cabinets. This is essential to enable results of radiobiological studies to be repeated, as well as enable valid comparisons between laboratories. In addition, the commonly used single point dose value hides the 3D dose heterogeneity across the irradiated sample. This is particularly true for preclinical rodent models, and is generally difficult to measure directly. Radiation transport simulations integrated in an easy to use application could help researchers improve quality of dosimetry and reporting.Approach. This paper describes the use and dosimetric validation of a newly-developed Monte Carlo (MC) tool, SmART-RAD, to simulate the x-ray field in a range of standard commercial x-ray cabinet irradiators used for preclinical irradiations. Comparisons are made between simulated and experimentally determined dose distributions for a range of configurations to assess the potential use of this tool in determining dose distributions through samples, based on more readily available air-kerma calibration point measurements.Main results. Simulations gave very good dosimetric agreement with measured depth dose distributions in phantoms containing both water and bone equivalent materials. Good spatial and dosimetric agreement between simulated and measured dose distributions was obtained when using beam-shaping shielding.Significance. The MC simulations provided by SmART-RAD provide a useful tool to go from a limited number of dosimetry measurements to detailed 3D dose distributions through a non-homogeneous irradiated sample. This is particularly important when trying to determine the dose distribution in more complex geometries. The use of such a tool can improve reproducibility and dosimetry reporting in preclinical radiobiological research.

Dosimetric verification of four dose calculation algorithms for spine stereotactic body radiotherapy

The applications of Type B [anisotropic analytical algorithm (AAA) and collapsed cone (CC)] and Type C [Acuros XB (AXB) and photon Monte Carlo (PMC)] dose calculation algorithms in spine stereotactic body radiotherapy (SBRT) were evaluated. Water- and bone-equivalent phantoms were combined to evaluate the percentage depth dose and dose profile. Subsequently, 48 consecutive patients with clinical spine SBRT plans were evaluated. All treatment plans were created using AXB in Eclipse. The prescription dose was 24 Gy in two fractions at a 10 MV FFF on TrueBeam. The doses were then recalculated with AAA, CC and PMC while maintaining the AXB-calculated monitor units and beam arrangement. The dose index values obtained using the four dose calculation algorithms were then compared. The AXB and PMC dose distributions agreed with the bone-equivalent phantom measurements (within ±2.0%); the AAA and CC values were higher than those in the bone-equivalent phantom region. For the spine SBRT plans, PMC, AAA and CC were overestimated compared with AXB in terms of the near minimum and maximum doses of the target and organ at risk, respectively; the mean dose difference was within 4.2%, which is equivalent with within 1 Gy. The phantom study showed that the results from AXB and PMC agreed with the measurements within ±2.0%. However, the mean dose difference ranged from 0.5 to 1 Gy in the spine SBRT planning study when the dose calculation algorithms changed. Users should incorporate a clinical introduction that includes an awareness of these differences.

Commissioning of Aktina SRS cones and dosimetric validation of the RayStation photon Monte Carlo dose calculation algorithm

Clinical implementation of SRS cones demands particular experimental care and dosimetric considerations in order to deliver precise and safe radiotherapy to patients. The purpose of this work was to present the commissioning data of recent Aktina cones combined with a 6MV flattened beam produced by an Elekta VersaHD linear accelerator. Additionally, the modelling process, and an assessment of dosimetric accuracy of the RayStation Monte Carlo dose calculation algorithm for cone based SRS was performed. There are currently no studies presenting beam data for this equipment and none that outlines the modelling parameters and validation of dose calculation using RayStation's photon Monte Carlo dose engine with cones. Beam data was measured using an SFD and a microDiamond and benchmarked against EBT3 film for cones of diameter 5-39 mm. Modelling was completed and validated within homogeneous and heterogeneous phantoms. End-to-end image-guided validation was performed using a StereoPHAN™ housing, an SRS MapCHECK and EBT3 film, and calculation time was investigated as a function of statistical uncertainty and field diameter. The TPS calculations agreed with measured data within their estimated uncertainties and clinical treatment plans could be calculated in under a minute. The data presented serves as a reference for others commissioning Aktina stereotactic cones and the modelling parameters serve similarly, while providing a starting point for those commissioning the same TPS algorithm for use with cones. It has been shown in this work that RayStation's Monte Carlo photon dose algorithm performs satisfactorily in the presence of SRS cones.

Impact of Dose Perturbations Around Brachytherapy Seeds in External-Beam Radiotherapy Planning: A Fundamental and Clinical Validation Using Treatment Planning System-Based Monte Carlo Simulations

Background This study evaluates dose perturbations caused by nonradioactive seeds in clinical cases by employing treatment planning system-based Monte Carlo (TPS-MC) simulation. Methodology We investigated dose perturbation using a water-equivalent phantom and 20 clinical cases of prostate cancer (10 cases with seeds and 10 cases without seeds) treated at Fujita Health University Hospital, Japan. First, dose calculations for a simple geometry were performed using the RayStation MC algorithm for a water-equivalent phantom with and without a seed. TPS-independent Monte Carlo (full-MC) simulations and film measurements were conducted to verify the accuracy of TPS-MC simulation. Subsequently, dose calculations using TPS-MC were performed on CT images of clinical cases of prostate cancer with and without seeds, and the dose distributions were compared. Results In clinical cases, dose calculations using MC simulations revealed hotspots around the seeds. However, the size of the hotspot was not correlated with the number of seeds. The maximum difference in dose perturbation between TPS-MC simulations and film measurements was 3.9%, whereas that between TPS-MC simulations and full-MC simulations was 3.7%. The dose error of TPS-MC was negligible for multiple beams or rotational irradiation. Conclusions Hotspots were observed in dose calculations using TPS-MC performed on CT images of clinical cases with seeds. The dose calculation accuracy around the seeds using TPS-MC simulations was comparable to that of film measurements and full-MC simulations, with differences within 3.9%. Although the clinical impact of hotspots occurring around the seeds is minimal, utilizing MC simulations on TPSs can be beneficial to verify their presence.

Dosimetric evaluation of high-Z inhomogeneity with modern algorithms: A collaborative study

PURPOSE

To evaluate modern dose calculation algorithms with high-Z prosthetic devices used in radiation treatment.

METHODS

A bilateral hip prosthetic patient was selected to see the effect of modern algorithms from the commercial system for plan comparisons. The CT data with dose constraints were sent to various institutions for dose calculations. The dosimetric parameters, D98%, D90%, D50% and D2% were compared. A water phantom with an actual prosthetic device was used to measure the dose using a parallel plate ionization chamber.

RESULTS

Dosimetric variability in PTV coverage was significant (>10%) among various treatment planning algorithms. The comparison of PTV dosimetric parameters, D98%, D90%, D50% and D2% as well as organs at risk (OAR) have large discrepancies compared to our previous publication with older algorithms (https://doi.org/10.1016/j.ejmp.2022.02.007) but provides realistic dose distribution with better homogeneity index (HI). Backscatter and forward scatter attenuation of the prosthesis was measured showing differences <15.7% at the interface among various algorithms.

CONCLUSIONS

Modern algorithms dose distributions have improved greatly compared to older generation algorithms. However, there is still significant differences at high-Z-tissue interfaces compared to the measurements. To ensure accuracy, it's important to take precautions avoiding placing any prosthesis in the beam direction and using type C algorithms.

Evaluation of the RadCalc collapsed cone dose calculation algorithm against measured data

This work describes the experimental validation of the RadCalc (Lifeline software Inc, Tyler) collapsed cone dose calculation algorithm against measured data for a range of scenarios. 6 MV photon beam data were measured in a large water tank on a Varian TrueBeam linear accelerator. These were input into the RadCalc software, in conjunction with head geometry and output calibration information, then used to create a collapsed cone beam model. The model performance was assessed by comparison against measurement, using a selection of homogeneous and inhomogeneous geometries not incorporated into the original beam model. Dose calculations generated using the collapsed cone algorithm are generally in good agreement with measurement. However, the primary collimating of the linac is not accounted for in the RadCalc model and hence dose in the corners of large fields is significantly overestimated. Percentage depth doses were within 0.5% beyond a depth of 2 cm. The dose in the build-up region was underestimated by RadCalc Version 7.1.4.1, with (Distance To Agreement) discrepancies of up to 3 mm which were corrected in Version 7.2.2.0. Beam profiles for homogeneous phantom comparisons were within 2% in the central 80% of the field with out of field dose underestimated by no more than 3%. Dose comparisons in heterogeneous geometries were acceptable and generally within 3.5%. The largest observed differences were found at density interfaces and a result of the RadCalc dose resolution of 2 mm against 1 mm measured. Absolute dose comparisons demonstrated that RadCalc agreed with measurement to within 1.2% under homogeneous media irradiation geometries. For static beam IMRT deliveries agreement was within 2% or 2 mm of measured data, and for complex VMAT deliveries within 3% or 2 mm. The implementation of the (model-based) photon collapsed cone algorithm in RadCalc shows generally good agreement with measured data over a range of simple and complex scenarios considered.

Validation of RayStation Monte Carlo dose calculation algorithm for multiple LINACs

PURPOSE

A photon Monte Carlo (MC) model was commissioned for flattened (FF) and flattening filter free (FFF) 6 MV beam energy. The accuracy of this model, as a single model to be used for three beam matched LINACs, was evaluated.

METHODS

Multiple models were created in RayStation v.10A for three linacs equipped with Elekta "Agility" collimator. A clinically commissioned collapsed cone (CC) algorithm (GoldCC), a MC model automatically created from the CC algorithm without further optimization (CCtoMC) and an optimized MC model (GoldMC) were compared with measurements. The validation of the model was performed by following the recommendations of IAEA TRS 430 and comprised of basic validation in a water tank, validation in a heterogeneous phantom and validation of complex IMRT/VMAT paradigms using gamma analysis of calculated and measured dose maps in a 2D-Array.

RESULTS

Dose calculation with the GoldMC model resulted in a confidence level of 3% for point measurements in water tank and heterogeneous phantom for measurements performed in all three linacs. The same confidence level resulted for GoldCC model. Dose maps presented an agreement for all models on par to each other with γ criteria 2%/2mm.

CONCLUSIONS

The GoldMC model showed a good agreement with measured data and is determined to be accurate for clinical use for all three linacs in this study.

Monte-Carlo techniques for radiotherapy applications I: introduction and overview of the different Monte-Carlo codes

Introduction:

The dose calculation plays a crucial role in many aspects of contemporary clinical radiotherapy treatment planning process. It therefore goes without saying that the accuracy of the dose calculation is of very high importance. The gold standard for absorbed dose calculation is the Monte-Carlo algorithm.

Methods:

This first of two papers gives an overview of the main openly available and supported codes that have been widely used for radiotherapy simulations.

Results:

The paper aims to provide an overview of Monte-Carlo in the field of radiotherapy and point the reader in the right direction of work that could help them get started or develop their existing understanding and use of Monte-Carlo algorithms in their practice.

Conclusions:

It also serves as a useful companion to a curated collection of papers on Monte-Carlo that have been published in this journal.

Comparison of four commercial dose calculation algorithms in different evaluation tests

BACKGROUND

Accurate and fast dose calculation is crucial in modern radiation therapy. Four dose calculation algorithms (AAA, AXB, CCC, and MC) are available in Varian Eclipse and RaySearch Laboratories RayStation Treatment Planning Systems (TPSs).

OBJECTIVES

This study aims to evaluate and compare dosimetric accuracy of the four dose calculation algorithms applying to homogeneous and heterogeneous media, VMAT plans (based on AAPM TG-119 test cases), and the surface and buildup regions.

METHODS

The four algorithms are assessed in homogeneous (IAEA-TECDOCE 1540) and heterogeneous (IAEA-TECDOC 1583) media. Dosimetric evaluation accuracy for VMAT plans is then analyzed, along with the evaluation of the accuracy of algorithms applying to the surface and buildup regions.

RESULTS

Tests conducted in homogeneous media revealed that all algorithms exhibit dose deviations within 5% for various conditions, with pass rates exceeding 95% based on recommended tolerances. Additionally, the tests conducted in heterogeneous media demonstrate high pass rates for all algorithms, with a 100% pass rate observed for 6 MV and mostly 100% pass rate for 15 MV, except for CCC, which achieves a pass rate of 94%. The results of gamma index pass rate (GIPR) for dose calculation algorithms in IMRT fields show that GIPR (3% /3 mm) for all four algorithms in all evaluated tests based on TG119, are greater than 97%. The results of the algorithm testing for the accuracy of superficial dose reveal variations in dose differences, ranging from -11.9% to 7.03% for 15 MV and -9.5% to 3.3% for 6 MV, respectively. It is noteworthy that the AXB and MC algorithms demonstrate relatively lower discrepancies compared to the other algorithms.

CONCLUSIONS

This study shows that generally, two dose calculation algorithms (AXB and MC) that calculate dose in medium have better accuracy than other two dose calculation algorithms (CCC and AAA) that calculate dose to water.

Adaptive dose painting for prostate cancer

Purpose

Dose painting (DP) is a radiation therapy (RT) strategy for patients with heterogeneous tumors delivering higher dose to radiation resistant regions and less to sensitive ones, thus aiming to maximize tumor control with limited side effects. The success of DP treatments is influenced by the spatial accuracy in dose delivery. Adaptive RT (ART) workflows can reduce the overall geometric dose delivery uncertainty. The purpose of this study is to dosimetrically compare ART and non-adaptive conventional RT workflows for delivery of DP prescriptions in the treatment of prostate cancer (PCa).

Materials and methods

We performed a planning and treatment simulation study of four study arms. Adaptive and conventional workflows were tested in combination with DP and Homogeneous dose. We used image data from 5 PCa patients that had been treated on the Elekta Unity MR linac; the patients had been imaged in treatment position before each treatment fraction (7 in total). The local radiation sensitivity from apparent diffusion coefficient maps of 15 high-risk PCa patients was modelled in a previous study. these maps were used as input for optimization of DP plans aiming for maximization of tumor control probability (TCP) under rectum dose constraints. A range of prostate doses were planned for the homogeneous arms. Adaptive plans were replanned based on the anatomy-of-the-day, whereas conventional plans were planned using a pre-treatment image and subsequently recalculated on the anatomy-of-the-day. The dose from 7 fractions was accumulated using dose mapping. The endpoints studied were the TCP and dose-volume histogram metrics for organs at risk.

Results

Accumulated DP doses (adaptive and conventional) resulted in high TCP, between 96-99%. The largest difference between adaptive and conventional DP was 2.6 percentage points (in favor of adaptive DP). An analysis of the dose per fraction revealed substantial target misses for one patient in the conventional workflow that—if systematic—could jeopardize the TCP. Compared to homogeneous prescriptions with equal mean prostate dose, DP resulted in slightly higher TCP.

Conclusion

Compared to homogeneous dose, DP maintains or marginally increases the TCP. Adaptive DP workflows could avoid target misses compared to conventional workflows.

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.

Dose Calculation Algorithms for External Radiation Therapy: An Overview for Practitioners

Radiation therapy (RT) is a constantly evolving therapeutic technique; improvements are continuously being introduced for both methodological and practical aspects. Among the features that have undergone a huge evolution in recent decades, dose calculation algorithms are still rapidly changing. This process is propelled by the awareness that the agreement between the delivered and calculated doses is of paramount relevance in RT, since it could largely affect clinical outcomes. The aim of this work is to provide an overall picture of the main dose calculation algorithms currently used in RT, summarizing their underlying physical models and mathematical bases, and highlighting their strengths and weaknesses, referring to the most recent studies on algorithm comparisons. This handy guide is meant to provide a clear and concise overview of the topic, which will prove useful in helping clinical medical physicists to perform their responsibilities more effectively and efficiently, increasing patient benefits and improving the overall quality of the management of radiation treatment.