AAPM Task Group 329: Reference dose specification for dose calculations: Dose‐to‐water or dose‐to‐muscle?

Treatment planning and delivery practice of lung SBRT: Results of the 2022 ESTRO physics survey

BACKGROUND AND PURPOSE

The use of Stereotactic Body Radiation Therapy (SBRT) in lung cancer is increasing. However, there is no consensus on the most appropriate treatment planning and delivery practice for lung SBRT. To gauge the range of practice, quantify its variability and identify where consensus might be achieved, ESTRO surveyed the medical physics community.

MATERIALS AND METHODS

An online survey was distributed to ESTRO's physicist membership in 2022, covering experience, dose and fractionation, target delineation, dose calculation and planning practice, imaging protocols, and quality assurance.

RESULTS

Two-hundred and forty-four unique answers were collected after data cleaning. Most respondents were from Europe the majority of which had more than 5 years' experience in SBRT. The large majority of respondents deliver lung SBRT with the VMAT technique on C-arm Linear Accelerators (Linacs) employing daily pre-treatment CBCT imaging. A broad spectrum of fractionation schemes were reported, alongside an equally wide range of dose prescription protocols. A clear preference was noted for prescribing to 95% or greater of the PTV. Several issues emerged regarding the dose calculation algorithm: 22% did not state it while 24% neglected to specify the conditions under which the dose was calculated. Contouring was usually performed on Maximum or Average Intensity Projection images while dose was mainly computed on the latter. No clear indications emerged for plan homogeneity, complexity, and conformity assessment. Approximately 40% of the responders participated in inter-centre credentialing of SBRT in the last five years. Substantial differences emerged between high and low experience centres, with the latter employing less accurate algorithms and older equipment.

CONCLUSION

The survey revealed an evident heterogeneity in numerous aspects of the clinical implementation of lung SBRT treatments. International guidelines and codes of practice might promote harmonisation.

Technical note: Radiological clinical equivalence for phantom materials in carbon ion therapy

PURPOSE

As carbon ion radiotherapy increases in use, there are limited phantom materials for heterogeneous or anthropomorphic phantom measurements. This work characterized the radiological clinical equivalence of several phantom materials in a therapeutic carbon ion beam.

METHODS

Eight materials were tested for radiological material-equivalence in a carbon ion beam. The materials were computed tomography (CT)-scanned to obtain Hounsfield unit (HU) values, then irradiated in a monoenergetic carbon ion beam to determine relative linear stopping power (RLSP). The corresponding HU and RLSP for each phantom material were compared to clinical carbon ion calibration curves. For absorbed dose comparison, ion chamber measurements were made in the center of a carbon ion spread-out Bragg peak (SOBP) in water and in the phantom material, evaluating whether the material perturbed the absorbed dose measurement beyond what was predicted by the HU-RLSP relationship.

RESULTS

Polyethylene, solid water (Gammex and Sun Nuclear), Blue Water (Standard Imaging), and Techtron HPV had measured RLSP values that agreed within ±4.2% of RLSP values predicted by the clinical calibration curve. Measured RLSP for acrylic was 7.2% different from predicted. The agreement for balsa wood and cork varied between samples. Ion chamber measurements in the phantom materials were within 0.1% of ion chamber measurements in water for most materials (solid water, Blue Water, polyethylene, and acrylic), and within 1.9% for the rest of the materials (balsa wood, cork, and Techtron HPV).

CONCLUSIONS

Several phantom materials (Blue Water, polyethylene, solid water [Gammex and Sun Nuclear], and Techtron HPV) are suitable for heterogeneous phantom measurements for carbon ion therapy. Low density materials should be carefully characterized due to inconsistencies between samples.

A low-cost phantom design for evaluating spine SABR calculations in the presence of prosthetic vertebral stabilization

Dose-perturbation characteristics are important to consider during the calculation of radiation therapy protocols for patients who are going to receive high doses that would reach the tolerance limits of the spinal cord [1]. Several studies have investigated dose perturbations introduced by metal implants in close proximity to spine SABR treatments [2-7]. However, there is a lack of work assessing this effect using the RayStation TPS [8]. We present an initial design for a low-cost phantom to evaluate spine stereotactic ablative radiotherapy (SABR) in the presence of prosthetic vertebral stabilization. The phantom is modular, allowing the prosthetic at the centre of the phantom to be removed by exchanging the central block. It also includes space to insert ion chamber and film. The agreement of the RayStation TPS (v8.0B) collapsed cone convolution (CCC) calculation and measurement was determined for phantom versions with and without prosthetic. There was little to no change in the agreement between the measured and calculated dose when introducing metallic hardware. This suggests that our Raystation-based SABR planning approach for patients with spinal hardware meets clinical expectations. Departments without access to anthropomorphic phantoms may find this design useful but should test their phantom design in typical clinical settings to ensure it is robust to real world situations.

Experimental validation of absorbed dose-to-medium calculation algorithms in heterogeneous media

Objective.The aim of this work was to determine heterogeneous correction factorshQclin,Qreffclin,frefdetm,wto validate absorbed dose-to-mediumDm,Qclinm,fclincalculation algorithms from detector readings. The impact of detector orientation perpendicular and parallel to the beam central axis on the correction factors was also investigated.Approach.ThehQclin,Qreffclin,frefdetm,wfactors were calculated for four types of detectors (PTW PinPoint T31016, PTW microDiamond T60019, PTW microSilicon T60023 and EBT3 film) placed in different media (cortical bone, lung, adipose tissue, Teflon and RW3) for the 6 MV energy beam with a 10 × 10 cm2field size. These corrections were then applied to the detector measurements performed at different depths in heterogeneous phantoms.Main results.ThehQclin,Qreffclin,frefdetm,wfactors mainly depended on the media and slightly on the type of detector. Considering all detectors, the largest corrections were found in high-density media with values ranging from 0.911 to 0.934 in cortical bone. For comparison, the corrections in other media were closer to unity with values from 0.966 (lung and RW3) to 0.991 (adipose tissue). Except for the PinPoint T31016, detector orientation-dependence was observed especially in high-density media. A good agreement (≤1.5%) was found betweenDm,Qclinm,fclincalculations and the detector readings corrected with thehQclin,Qreffclin,frefdetm,wfactor for all studied heterogeneous phantoms.Significance.This paper could serve as an initial guideline for medical physicists involved in the validation of the advanced type-b dose calculation algorithms reportingDm,Qclinm,fclin. To our knowledge, this is the first study to assess the impact of the orientation of different detectors in heterogeneous media. The orientation dependence of the detector response observed in water may not reflect what is observed in heterogeneous media, especially in high-density media. The knowledge of thehQclin,Qreffclin,frefdetm,wfactors becomes mandatory for accurate interpretation of detector readings and comparisons withDm,Qclinm,fclincalculations.

Inverse planning of lung radiotherapy with photon and proton beams using a discrete ordinates Boltzmann solver

Objective. A discrete ordinates Boltzmann solver has recently been developed for use as a fast and accurate dose engine for calculation of photon and proton beams. The purpose of this study is to apply the algorithm to the inverse planning process for photons and protons and to evaluate the impact that this has on the quality of the final solution.Approach.The method was implemented into an iterative least-squares inverse planning optimiser, with the Boltzmann solver used every 20 iterations over the total of 100 iterations. Elemental dose distributions for the intensity modulation and the dose changes at the intermediate iterations were calculated by a convolution algorithm for photons and a simple analytical model for protons. The method was evaluated for 12 patients in the heterogeneous tissue environment encountered in radiotherapy of lung tumours. Photon arc and proton arc treatments were considered in this study. The results were compared with those for use of the Boltzmann solver solely at the end of inverse planning or not at all.Main results.Application of the Boltzmann solver at the end of inverse planning shows the dose heterogeneity in the planning target volume to be greater than calculated by convolution and empirical methods, with the median root-mean-square dose deviation increasing from 3.7 to 5.3 for photons and from 1.9 to 3.4 for proton arcs. Use of discrete ordinates throughout inverse planning enables homogeneity of target coverage to be maintained throughout, the median root-mean-square dose deviation being 3.6 for photons and 2.3 for protons. Dose to critical structures is similar with discrete ordinates and conventional methods. Time for inverse planning with discrete ordinates takes around 1-2 h using a contemporary computing environment.Significance.By incorporating the Boltzmann solver into an iterative least squares inverse planning optimiser, accurate dose calculation in a heterogeneous medium is obtained throughout inverse planning, with the result that the final dose distribution is of the highest quality.

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 and validation of a Monte Carlo algorithm for spine stereotactic radiosurgery

PURPOSE

A 6FFF Monte Carlo (MC) dose calculation algorithm was commissioned for spine stereotactic radiosurgery (SRS). Model generation, validation, and ensuing model tuning are presented.

METHODS

The model was generated using in-air and in-water commissioning measurements of field sizes between 10 and 400 mm2 . Commissioning measurements were compared to simulated water tank MC calculations to validate output factors, percent depth doses (PDDs), profile sizes and penumbras. Previously treated Spine SRS patients were re-optimized with the MC model to achieve clinically acceptable plans. Resulting plans were calculated on the StereoPHAN phantom and subsequently delivered to the microDiamond and SRSMapcheck to verify calculated dose accuracy. Model tuning was performed by adjusting the model's light field offset (LO) distance between physical and radiological positions of the MLCs, to improve field size and StereoPHAN calculation accuracy. Following tuning, plans were generated and delivered to an anthropomorphic 3D-printed spine phantom featuring realistic bone anatomy, to validate heterogeneity corrections. Finally, plans were validated using polymer gel (VIPAR based formulation) measurements.

RESULTS

Compared to open field measurements, MC calculated output factors and PDDs were within 2%, profile penumbra widths were within 1 mm, and field sizes were within 0.5 mm. Calculated point dose measurements in the StereoPHAN were within 0.26% ± 0.93% and -0.10% ± 1.37% for targets and spinal canals, respectively. Average SRSMapcheck per-plan pass rates using a 2%/2 mm/10% threshold relative gamma analysis was 99.1% ± 0.89%. Adjusting LOs improved open field and patient-specific dosimetric agreement. Anthropomorphic phantom measurements were within -1.29% ± 1.00% and 0.27% ± 1.36% of MC calculated for the vertebral body (target) and spinal canal, respectively. VIPAR gel measurements confirmed good dosimetric agreement near the target-spine junction.

CONCLUSION

Validation of a MC algorithm for simple fields and complex SRS spine deliveries in homogeneous and heterogeneous phantoms has been performed. The MC algorithm has been released for clinical use.

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.

Measuring dose in lung identifies peripheral tumour dose inaccuracy in SBRT audit

PURPOSE

Stereotactic Body Radiotherapy (SBRT) for lung tumours has become a mainstay of clinical practice worldwide. Measurements in anthropomorphic phantoms enable verification of patient dose in clinically realistic scenarios. Correction factors for reporting dose to the tissue equivalent materials in a lung phantom are presented in the context of a national dosimetry audit for SBRT. Analysis of dosimetry audit results is performed showing inaccuracies of common dose calculation algorithms in soft tissue lung target, inhale lung material and at tissue interfaces.

METHODS

Monte Carlo based simulation of correction factors for detectors in non-water tissue was performed for the soft tissue lung target and inhale lung materials of a modified CIRS SBRT thorax phantom. The corrections were determined for Gafchromic EBT3 Film and PTW 60019 microDiamond detectors used for measurements of 168 SBRT lung plans in an end-to-end dosimetry audit. Corrections were derived for dose to medium (Dm,m) and dose to water (Dw,w) scenarios.

RESULTS

Correction factors were up to -3.4% and 9.2% for in field and out of field lung respectively. Overall, application of the correction factors improved the measurement-to-plan dose discrepancy. For the soft tissue lung target, agreement between planned and measured dose was within average of 3% for both film and microDiamond measurements.

CONCLUSIONS

The correction factors developed for this work are provided for clinical users to apply to commissioning measurements using a commercially available thorax phantom where inhomogeneity is present. The end-to-end dosimetry audit demonstrates dose calculation algorithms can underestimate dose at lung tumour/lung tissue interfaces by an average of 2-5%.

AAPM WGDCAB Report 372: A joint AAPM, ESTRO, ABG, and ABS report on commissioning of model-based dose calculation algorithms in brachytherapy

The introduction of model-based dose calculation algorithms (MBDCAs) in brachytherapy provides an opportunity for a more accurate dose calculation and opens the possibility for novel, innovative treatment modalities. The joint AAPM, ESTRO, and ABG Task Group 186 (TG-186) report provided guidance to early adopters. However, the commissioning aspect of these algorithms was described only in general terms with no quantitative goals. This report, from the Working Group on Model-Based Dose Calculation Algorithms in Brachytherapy, introduced a field-tested approach to MBDCA commissioning. It is based on a set of well-characterized test cases for which reference Monte Carlo (MC) and vendor-specific MBDCA dose distributions are available in a Digital Imaging and Communications in Medicine-Radiotherapy (DICOM-RT) format to the clinical users. The key elements of the TG-186 commissioning workflow are now described in detail, and quantitative goals are provided. This approach leverages the well-known Brachytherapy Source Registry jointly managed by the AAPM and the Imaging and Radiation Oncology Core (IROC) Houston Quality Assurance Center (with associated links at ESTRO) to provide open access to test cases as well as step-by-step user guides. While the current report is limited to the two most widely commercially available MBDCAs and only for 192 Ir-based afterloading brachytherapy at this time, this report establishes a general framework that can easily be extended to other brachytherapy MBDCAs and brachytherapy sources. The AAPM, ESTRO, ABG, and ABS recommend that clinical medical physicists implement the workflow presented in this report to validate both the basic and the advanced dose calculation features of their commercial MBDCAs. Recommendations are also given to vendors to integrate advanced analysis tools into their brachytherapy treatment planning system to facilitate extensive dose comparisons. The use of the test cases for research and educational purposes is further encouraged.

Using density computed tomography images for photon dose calculations in radiation oncology: A patient study

Background and purpose

Conventional workflows for dose calculations require conversions between Hounsfield Units (HU) and the mass or electron density for Computed Tomography (CT) images in the Treatment Planning System (TPS). These conversions are scanner- and mostly kVp-dependent. A density representation or reconstruction at the CT level can potentially simplify the workflow. This study aimed to investigate the agreement between these two methods for patients and different calculation algorithms.

Materials and methods

Density conversions for conventional HU-density conversions were first established using two phantoms with appropriate inserts. Next, the differences in density and dose calculations between both methods were assessed using 95% Limits of Agreement (LOA) Bland-Altman analysis for 44 consecutive clinical patient cases. These cases represented a mix of indications, algorithms (collapsed cone, convolution superposition, ray tracing, finite-size pencil beam, and Monte Carlo), and scan kVp (80 to 140) in two different commercial TPS.

Results

No statistically significant bias in density or dose calculations was found between the two methods. Furthermore, 95% LOAs between both methods were ±0.05 g/cm³ and ±0.1 Gy for density and dose, respectively. Small but clinically irrelevant dose differences were found in high-density gradient regions for convolution superposition calculations or CT scans with non-delayed contrast agent injections with targets nearby vessels.

Conclusions

The in vivo density-reconstructed images at the CT level were assessed to be equivalent. Therefore, they can simplify and improve clinical workflows, allowing patient-specific acquisitions for contouring and density-reconstructed images for dose calculations.

Post-mastectomy radiotherapy: Impact of bolus thickness and irradiation technique on skin dose

PURPOSE

To determine 10 MV IMRT and VMAT based protocols with a daily bolus targeting a skin dose of 45 Gy in order to replace the 6 MV tangential fields with a 5 mm thick bolus on alternate days method for post-mastectomy radiotherapy.

METHOD

We measured the mean surface dose along the chest wall PTV as a function of different bolus thicknesses for sliding window IMRT and VMAT plans. We analyzed surface dose profiles and dose homogeneities and compared them to our standard 6 MV strategy. All measurements were performed on a thorax phantom with Gafchromic films while dosimetric plans were computed using the Acuros XB algorithm (Varian).

RESULTS

We obtained the best compromise between measured surface dose (mean dose and homogeneity) and skin toxicity threshold obtained from the literature using a daily 3 mm thick bolus. Mean surface doses were 91.4 ± 2.8% [85.7% - 95.4%] and 92.2 ± 2.3% [85.6% - 95.2%] of the prescribed dose with IMRT and VMAT techniques, respectively. Our standard 6 MV alternate days 5 mm thick bolus leads to 89.0 ± 3.7% [83.6% - 95.5%]. Mean dose differences between measured and TPS results were < 3.2% for depths as low as 2 mm depth.

CONCLUSION

10 MV IMRT-based protocols with a daily 3 mm thick bolus produce a surface dose comparable to the standard 6 MV 5 mm thick bolus on alternate days method but with an improved surface dose homogeneity. This allows for a better control of skin toxicity and target volume coverage.

Tissues margin-based analytical anisotropic algorithm boosting method via deep learning attention mechanism with cervical cancer

PURPOSE

Speed and accuracy are two critical factors in dose calculation for radiotherapy. Analytical Anisotropic Algorithm (AAA) is a rapid dose calculation algorithm but has dose errors in tissue margin area. Acuros XB (AXB) has high accuracy but takes long time to calculate. To improve the dose accuracy on the tissue margin area for AAA, we proposed a novel deep learning-based dose accuracy improvement method using Margin-Net combined with Margin-Loss.

METHODS

A novel model 'Margin-Net' was designed with a Margin Attention Mechanism to generate special margin-related features. Margin-Loss was introduced to consider the dose errors and dose gradients in tissues margin area. Ninety-five VMAT cervical cancer cases with paired AAA and AXB dose were enrolled in our study: 76 cases for training and 19 cases for testing. Tissues Margin Masks were generated from RT contours with 6 mm extension. Tissues Margin Mask, AAA dose and CTs were input data; AXB dose was used as reference dose for model training and evaluation. Comparison experiments were performed to evaluated effectiveness of Margin-Net and Margin-Loss.

RESULTS

Compared to AXB dose, the 3D gamma passing rate (1%/1 mm, 10% threshold) for 19 test cases 95.75 ± 1.05% using Margin-Net with Margin-Loss, which was significantly higher than the original AAA dose (73.64 ± 3.46%). The passing rate reduced to 94.07 ± 1.16% without Margin-Loss and 87.3 ± 1.18% if Margin-Net key structure 'MAM' was also removed.

CONCLUSION

The proposed novel tissues margin-based dose conversion method can significantly improve the dose accuracy of Analytical Anisotropic Algorithm to be comparable to AXB algorithm. It can potentially improve the efficiency of treatment planning process with low demanding of computation resources.

Characterizing the interplay of treatment parameters and complexity and their impact on performance on an IROC IMRT phantom using machine learning

AIM OF THE STUDY

To elucidate the important factors and their interplay that drive performance on IMRT phantoms from the Imaging and Radiation Oncology Core (IROC).

METHODS

IROC's IMRT head and neck phantom contains two targets and an organ at risk. Point and 2D dose are measured by TLDs and film, respectively. 1,542 irradiations between 2012-2020 were retrospectively analyzed based on output parameters, complexity metrics, and treatment parameters. Univariate analysis compared parameters based on pass/fail, and random forest modeling was used to predict output parameters and determine the underlying importance of the variables.

RESULTS

The average phantom pass rate was 92% and has not significantly improved over time. The step-and-shoot irradiation technique had significantly lower pass rates that significantly affected other treatment parameters' pass rates. The complexity of plans has significantly increased with time, and all aperture-based complexity metrics (except MCS) were associated with the probability of failure. Random forest-based prediction of failure had an accuracy of 98% on held-out test data not used in model training. While complexity metrics were the most important contributors, the specific metric depended on the set of treatment parameters used during the irradiation.

CONCLUSION

With the prevalence of errors in radiotherapy, understanding which parameters affect treatment delivery is vital to improve patient treatment. Complexity metrics were strongly predictive of irradiation failure; however, they are dependent on the specific treatment parameters. In addition, the use of one complexity metric is insufficient to monitor all aspects of the treatment plan.

Considerations for radiotherapy planning with MV photons using dose-to-medium

Background and purpose

Radiotherapy planning considerations were developed for the previous calculation algorithms yielding dose to water-in-water (D_w,w). Advanced algorithms improve accuracy, but their dose values in terms of dose to medium-in-medium (D_m,m) depend on the medium considered. This work aimed to show how mimicking D_w,w planning with D_m,m can introduce new issues.

Materials and methods

A head and neck case involving bone and metal heterogeneities outside the CTV was considered. Two different commercial algorithms were used to obtain D_m,m and D_w,w distributions. First, a plan was optimised to irradiate the PTV uniformly and get a homogeneous D_w,w distribution. Second, another plan was optimised to achieve homogeneous D_m,m. Both plans were calculated with D_w,w and D_m,m, and the differences between their dose distributions, clinical impact, and robustness were evaluated.

Results

Uniform irradiation produced D_m,m cold spots in bone (-4%) and implants (-10%). Uniform D_m,m compensated them by increasing fluence but, when recalculated in D_w,w, the fluence compensations produced higher doses that affected homogeneity. Additionally, doses were 1% higher for the target, and + 4% for the mandible, thus increasing toxicity risk. Robustness was impaired when increased fluence regions and heterogeneities mismatched.

Conclusion

Planning with D_m,m as with D_w,w can impact clinical outcome and impair robustness. In optimisation, uniform irradiation instead of homogeneous D_m,m distributions should be pursued when media with different D_m,m responses are involved. However, this requires adapting evaluation criteria or avoiding medium effects. Regardless of the approach, there can be systematic differences in dose prescription and constraints.

Uncertainties in the dosimetric heterogeneity correction and its potential effect on local control in lung SBRT

Objective. Dose calculation in lung stereotactic body radiation therapy (SBRT) is challenging due to the low density of the lungs and small volumes. Here we assess uncertainties associated with tissue heterogeneities using different dose calculation algorithms and quantify potential associations with local failure for lung SBRT.Approach. 164 lung SBRT plans were used. The original plans were prepared using Pencil Beam Convolution (PBC, n = 8) or Anisotropic Analytical Algorithm (AAA, n = 156). Each plan was recalculated with AcurosXB (AXB) leaving all plan parameters unchanged. A subset (n = 89) was calculated with Monte Carlo to verify accuracy. Differences were calculated for the planning target volume (PTV) and internal target volume (ITV) Dmean[Gy], D99%[Gy], D95%[Gy], D1%[Gy], and V100%[%]. Dose metrics were converted to biologically effective doses (BED) usingα/β= 10Gy. Regression analysis was performed for AAA plans investigating the effects of various parameters on the extent of the dosimetric differences. Associations between the magnitude of the differences for all plans and outcome were investigated using sub-distribution hazards analysis.Main results. For AAA cases, higher energies increased the magnitude of the difference (ΔDmean of -3.6%, -5.9%, and -9.1% for 6X, 10X, and 15X, respectively), as did lung volume (ΔD99% of -1.6% per 500cc). Regarding outcome, significant hazard ratios (HR) were observed for the change in the PTV and ITV D1% BEDs upon univariate analysis (p = 0.042, 0.023, respectively). When adjusting for PTV volume and prescription, the HRs for the change in the ITV D1% BED remained significant (p = 0.039, 0.037, respectively).Significance. Large differences in dosimetric indices for lung SBRT can occur when transitioning to advanced algorithms. The majority of the differences were not associated with local failure, although differences in PTV and ITV D1% BEDs were associated upon univariate analysis. This shows uncertainty in near maximal tumor dose to potentially be predictive of treatment outcome.

Variability of Low-Z Inhomogeneity Correction in IMRT/SBRT: A Multi-Institutional Collaborative Study

Dose-calculation algorithms are critical for radiation treatment outcomes that vary among treatment planning systems (TPS). Modern algorithms use sophisticated radiation transport calculation with detailed three-dimensional beam modeling to provide accurate doses, especially in heterogeneous medium and small fields used in IMRT/SBRT. While the dosimetric accuracy in heterogeneous mediums (lung) is qualitatively known, the accuracy is unknown. The aim of this work is to analyze the calculated dose in lung patients and compare the validity of dose-calculation algorithms by measurements in a low-Z phantom for two main classes of algorithms: type A (pencil beam) and type B (collapse cone). The CT scans with volumes (target and organs at risk, OARs) of a lung patient and a phantom build to replicate the human lung data were sent to nine institutions for planning. Doses at different depths and field sizes were measured in the phantom with and without inhomogeneity correction across multiple institutions to understand the impact of clinically used dose algorithms. Wide dosimetric variations were observed in target and OAR coverage in patient plans. The correction factor for collapsed cone algorithms was less than pencil beam algorithms in the small fields used in SBRT. The pencil beam showed ≈70% variations between measured and calculated correction factors for various field sizes and depths. For large field sizes the trends of both types of algorithms were similar. The differences in measured versus calculated dose for type-B algorithms were within ±10%. Significant variations in the target and OARs were observed among various TPS. The results suggest that the pencil beam algorithm does not provide an accurate dose and should not be considered with small fields (IMRT/SBRT). Type-B collapsed-cone algorithms provide better agreement with measurements, but still vary among various systems.

AAPM MEDICAL PHYSICS PRACTICE GUIDELINE 5.b: Commissioning and QA of treatment planning dose calculations-Megavoltage photon and electron beams

The American Association of Physicists in Medicine (AAPM) is a nonprofit professional society whose primary purposes are to advance the science, education, and professional practice of medical physics. The AAPM has more than 8000 members and is the principal organization of medical physicists in the United States. The AAPM will periodically define new practice guidelines for medical physics practice to help advance the science of medical physics and to improve the quality of service to patients throughout the United States. Existing medical physics practice guidelines will be reviewed for the purpose of revision or renewal, as appropriate, on their fifth anniversary or sooner. Each medical physics practice guideline represents a policy statement by the AAPM, has undergone a thorough consensus process in which it has been subjected to extensive review, and requires the approval of the Professional Council. The medical physics practice guidelines recognize that the safe and effective use of diagnostic and therapeutic radiology requires specific training, skills, and techniques, as described in each document. Reproduction or modification of the published practice guidelines and technical standards by those entities not providing these services is not authorized. The following terms are used in the AAPM practice guidelines:

Must and Must Not: Used to indicate that adherence to the recommendation is considered necessary to conform to this practice guideline. While must is the term to be used in the guidelines, if an entity that adopts the guideline has shall as the preferred term, the AAPM considers that must and shall have the same meaning.

Should and Should Not: Used to indicate a prudent practice to which exceptions may occasionally be made in appropriate circumstances.

Commissioning and validation of RayStation treatment planning system for CyberKnife M6

Background

RaySearch (AB, Stockholm) has released a module for CyberKnife (CK) planning within its RayStation (RS) treatment planning system (TPS).

Purpose

To create and validate beam models of fixed, Iris, and multileaf collimators (MLC) of the CK M6 for Monte Carlo (MC) and collapsed cone (CC) algorithms in the RS TPS.

Methods

Measurements needed for the creation of the beam models were performed in a water tank with a stereotactic PTW 60018 diode. Both CC and MC models were optimized in RS by minimizing the differences between the measured and computed profiles and percentage depth doses. The models were then validated by comparing dose from the plans created in RS with both single and multiple beams in different phantom conditions with the corresponding measured dose. Irregular field shapes and off‐axis beams were also tested for the MLC. Validation measurements were performed using an A1SL ionization chamber, EBT3 Gafchromic films, and a PTW 1000 SRS detector. Finally, patient‐specific QAs with gamma criteria of 3%/1 mm were performed for each model.

Results

The models were created in a straightforward manner with efficient tools available in RS. The differences between computed and measured doses were within ±1% for most of the configurations tested and reached a maximum of 3.2% for measurements at a depth of 19.5‐cm. With respect to all collimators and algorithms, the maximum averaged dose difference was 0.8% when considering absolute dose measurements on the central axis. The patient‐specific QAs led to a mean result of 98% of points fulfilling gamma criteria.

Conclusions

We created both CC and MC models for fixed, Iris, and MLC collimators in RS. The dose differences for all collimators and algorithms were within ±1%, except for depths larger than 9 cm. This allowed us to validate both models for clinical use.

Radiobiological Comparison of Acuros External Beam and Anisotropic Analytical Algorithm on Esophageal Carcinoma Radiotherapy Treatment Plans

Objective

The present study aimed to investigate the dose differences and radiobiological assessment between Anisotropic Analytical Algorithm (AAA) and Acuros External Beam (AXB) with its 2 calculation models, namely, dose-to-water (AXB-Dw) and dose-to-medium (AXB-Dm), on esophageal carcinoma radiotherapy treatment plans.

Materials and methods

The AXB-Dw and AXB-Dm plans were generated by recalculating the initial 66 AAA plans using the AXB algorithm with the same monitor units and beam parameters as those in the original plan. The dosimetric and radiobiological assessment parameters were calculated for the planning target volume (PTV) and organs at risk (OARs). The gamma agreement for the PTV and the correlation between it and the volume of the air cavity and bone among the different algorithms were compared simultaneously. The dose discrepancy between the theoretical calculation and treatment planning system (TPS) when switching from AXB-Dm to AXB-Dw was analyzed according to the composition of the structures.

Results

The PTV dose of AXB-Dm plans was significantly smaller than that of the AAA and AXB-Dw plans (P < .05), except for D₂. The difference values for AAA vs AXB-Dm (∆D_{x,(AAA-AXB,Dm)}) and AXB-Dw vs AXB-Dm (∆D_{x,(AXB,Dw-AXB,Dm)}) were 1.94% [1.27%, 2.64%] and 1.95% [1.56%, 2.27%], respectively. For the spinal cord and heart, there were obvious differences between the AAA vs AXB-Dm (spinal cord: 1.15%, heart: 2.89%) and AXB-Dw vs AXB-Dm (spinal cord: 1.88%, heart: 3.25%) plans. For the lung, the differences between AAA vs AXB-Dm and AAA vs AXB-Dw were significantly larger than those of AXB-Dm vs AXB-Dw. Compared to the case of AAA and AXB-Dw, the decrease in biologically effective dose (BED¹⁰, αβ=10 ) of AXB-Dm due to dose non-uniformity exceeded 6.5%, even for a small σ. The average values of equivalent uniform dose in the AAA, AXB-Dw, and AXB-Dm plans were 52.03±.39 Gy, 52.24 ± .81 Gy, and 51.13 ± .47 Gy, respectively. The tumor control probability (TCP) results for PTV in the AAA, AXB-Dw, and AXB-Dm plans were 62.29 ± 1.57%, 62.82 ± 1.69%, and 58.68±1.88%, respectively. With the 2%/2 mm and 3%/3 mm acceptance criteria, the mean values of  ΔγAAAAXB−Dw, ΔγAAAAXB−Dm, and  ΔγAXB−DmAXB−Dw were 87.24, 63.3, and 64.81% vs 97.86, 91.77, and 89.25%, respectively. The dose discrepancy between the theoretical calculation and TPS when switching from AXB-Dm to AXB-Dw was approximately 1.63%.

Conclusions

The AAA and AXB-Dw algorithms overestimated the radiobiological parameters when the tumor particularly consisted of nonuniform tissues. A relatively small dose difference could cause a significant reduction in the corresponding TCP. Dose distribution algorithms should be carefully chosen by physicists and oncologists to improve tumor control, as well as to optimize OARs protection.

The current status and shortcomings of stereotactic radiosurgery

Background

Stereotactic radiosurgery (SRS) is a common treatment for intracranial lesions. This work explores the state of SRS treatment delivery to characterize current treatment accuracy based on treatment parameters.

Methods

NCI clinical trials involving SRS rely on an end-to-end treatment delivery on a patient surrogate (credentialing phantom) from the Imaging and Radiation Oncology Core (IROC) to test their treatment accuracy. The results of 1072 SRS phantom irradiations between 2012 and 2020 were retrospectively analyzed. Univariate analysis and random forest models were used to associate irradiation conditions with phantom performance. The following categories were evaluated in terms of how they predicted outcomes: year of irradiation, TPS algorithm, machine model, energy, and delivered field size.

Results

Overall, only 84.6% of irradiations have met the IROC/NCI acceptability criteria. Pass rate has remained constant over time, while dose calculation accuracy has slightly improved. Dose calculation algorithm (P < .001), collimator (P = .024), and field size (P < .001) were statistically significant predictors of pass/fail. Specifically, pencil beam algorithms and cone collimators were more likely to be associated with failing phantom results. Random forest modeling identified the size of the field as the most important factor for passing or failing followed by algorithm.

Conclusion

Constant throughout this retrospective study, approximately 15% of institutions fail to meet IROC/NCI standards for SRS treatment. In current clinical practice, this is particularly associated with smaller fields that yielded less accurate results. There is ongoing need to improve small field dosimetry, beam modeling, and QA to ensure high treatment quality, patient safety, and optimal clinical trials.

Plan quality in radiotherapy treatment planning - Review of the factors and challenges

A high-quality treatment plan aims to best achieve the clinical prescription, balancing high target dose to maximise tumour control against sufficiently low organ-at-risk dose for acceptably low toxicity. Treatment planning (TP) includes multiple steps from simulation/imaging and segmentation to technical plan production and reporting. Consistent quality across this process requires close collaboration and communication between clinical and technical experts, to clearly understand clinical requirements and priorities and also practical uncertainties, limitations and compromises. TP quality depends on many aspects, starting from commissioning and quality management of the treatment planning system (TPS), including its measured input data and detailed understanding of TPS models and limitations. It requires rigorous quality assurance of the whole planning process and it links to plan deliverability, assessable by measurement-based verification. This review highlights some factors influencing plan quality, for consideration for optimal plan construction and hence optimal outcomes for each patient. It also indicates some challenges, sources of difference and current developments. The topics considered include: the evolution of TP techniques; dose prescription issues; tools and methods to evaluate plan quality; and some aspects of practical TP. The understanding of what constitutes a high-quality treatment plan continues to evolve with new techniques, delivery methods and related evidence-based science. This review summarises the current position, noting developments in the concept and the need for further robust tools to help achieve it.

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.

Impact of the dose quantity used in MV photon optimization on dose distribution, robustness, and complexity

PURPOSE

Convolution/superposition algorithms used in megavoltage (MV) photon radiotherapy model radiation transport in water, yielding dose to water-in-water (D_w,w ). Advanced algorithms constitute a step forward, but their dose distributions in terms of dose to medium-in-medium (D_m,m ) or dose to water-in-medium (D_w,m ) can be problematic when used in plan optimization due to their different dose responses to some atomic composition heterogeneities. Failure to take this into account can lead to undesired overcorrections and thus to unnoticed suboptimal and unrobust plans. Dose to reference-like medium (D_ref,m* ) was recently introduced to overcome these limitations while ensuring accurate transport. This work evaluates and compares the performance of these four dose quantities in planning target volume (PTV)-based optimization.

METHODS

We considered three cases with heterogeneities inside the PTV: virtual phantom with water surrounded by bone; head and neck; and lung. These cases were planned with volumetric modulated arc therapy (VMAT) technique, optimizing with the same setup and objectives for each dose quantity. We used different algorithms of the Varian Eclipse treatment planning system (TPS): Acuros XB (AXB) for D_m,m and D_w,m , and Analytical Anisotropic Algorithm (AAA) for D_w,w . D_ref,m* was obtained from D_m,m distributions using an in-house software considering water as the reference medium (D_w,m* ). The optimization process consisted of: (1) common first optimization, (2) dose distribution computed for each quantity, (3) re-optimization, and (4) final calculation for each dose quantity. The dose distribution, robustness to patient setup errors, and complexity of the plans were analyzed and compared.

RESULTS

The quantities showed similar dose distributions after the optimization but differed in terms of plan robustness. The cases with soft tissue and high-density heterogeneities followed the same pattern. For AXB D_m,m , cold regions appeared in the heterogeneities after the first optimization. They were compensated in the second optimization through local fluence increases, but any positional mismatch impacted robustness, with clinical target volume (CTV) variations from the nominal scenario around +3% for bone and up to +7% for metal. For AXB D_w,m the pattern was inverse (hot regions compensated by fluence decreases) and more pronounced, with CTV dose variations around -7% for bone and up to -17% for metal. Neither AXB D_w,m* nor AAA D_w,w presented these dose inhomogeneities, which resulted in more robust plans. However, D_w,w differed markedly from the other quantities in the lung case because of its lower radiation transport accuracy. AXB D_m,m was the most complex of the four dose quantities and AXB D_w,m* the least complex, though we observed no major differences in this regard.

CONCLUSIONS

The dose quantity used in MV photon optimization can affect plan robustness. D_w,w distributions from convolution/superposition algorithms are robust but may not provide sufficient radiation transport accuracy in some cases. D_m,m and D_w,m from advanced algorithms can compromise robustness because their different responses to some composition heterogeneities introduce additional fluence compensations. D_ref,m* offers advantages in plan optimization and evaluation, producing accurate and robust plans without increasing complexity. D_ref,m* can be easily implemented as a built-in feature of the TPS and can facilitate and simplify the treatment planning process when using advanced algorithms. Final reporting can be kept in D_m,m or D_w,m for clinical correlations.

Investigating dose homogeneity in radiotherapy of oral cancers in the presence of a dental implant system: an in vitro phantom study

Background

Materials with high atomic numbers are part of the composition of dental implant systems. In radiotherapy of oral cavity cancers, an implant can cause dose perturbations that affect target definition, dose calculation, and dose distribution. In consequence, this may result in poor tumor control and higher complications. In this study, we evaluated dose homogeneity when a dental implant replaced a normal tooth. We also aimed to evaluate the concordance of dose calculations with dose measurements.

Materials and methods

In this study, 2 sets of planning CT scans of a phantom with a normal tooth and the same phantom with the tooth replaced by a Z1 TBR dental implant system were used. The implant system was composed of a porcelain-fused-to-metal crown and titanium with a zirconium collar. Three radiotherapy plans were designed when the density of the implant material was corrected to match their elements, or when all were set to the density of water, or when using the default density conversion. Gafchromic EBT-3 films at the level of isocenter and crowns were used for measurements.

Results

At the level of crowns, upstream and downstream dose calculations were reduced when metal kernels were applied (M-plan). Moreover, relatively measured dose distribution patterns were most similar to M-plan. At this level, relative to the non-implanted phantom, mean doses values were higher with the implant (215.93 vs. 192.25), also, new high-dose areas appeared around a low-dose streak forward to the implant (119% vs. 95%).

Conclusions

Implants can cause a high dose to the oral cavity in radiotherapy because of extra scattered radiation. Knowledge of the implant dimensions and defining their material enhances the accuracy of calculations.

A comparative analysis of Acuros XB and the analytical anisotropic algorithm for volumetric modulation arc therapy

Background

This study aimed to verify the dosimetric impact of Acuros XB (AXB) (AXB, Varian Medical Systems Palo Alto CA, USA), a two model-based algorithm, in comparison with Anisotropic Analytical Algorithm (AAA ) calculations for prostate, head and neck and lung cancer treatment by volumetric modulated arc therapy (VMAT ), without primary modification to AA. At present, the well-known and validated AA algorithm is clinically used in our department for VMAT treatments of different pathologies. AXB could replace it without extra measurements. The treatment result and accuracy of the dose delivered depend on the dose calculation algorithm.

Materials and method

Ninety-five complex VMAT plans for different pathologies were generated using the Eclipse version 15.0.4 treatment planning system (TPS). The dose distributions were calculated using AA and AXB (dose-to-water, AXB_w and dose-to-medium, AXB_m), with the same plan parameters for all VMAT plans. The dosimetric parameters were calculated for each planning target volume (PTV) and involved organs at risk (OA R). The patient specific quality assurance of all VMAT plans has been verified by Octavius^®-4D phantom for different algorithms.

Results

The relative differences among AA, AXB_w and AXB_m, with respect to prostate, head and neck were less than 1% for PTV D_95%. However, PTV D_95% calculated by AA tended to be overestimated, with a relative dose difference of 3.23% in the case of lung treatment. The absolute mean values of the relative differences were 1.1 ± 1.2% and 2.0 ± 1.2%, when comparing between AXB_w and AA, AXB_m and AA, respectively. The gamma pass rate was observed to exceed 97.4% and 99.4% for the measured and calculated doses in most cases of the volumetric 3D analysis for AA and AXB_m, respectively.

Conclusion

This study suggests that the dose calculated to medium using AXB_m algorithm is better than AAA and it could be used clinically. Switching the dose calculation algorithm from AA to AXB does not require extra measurements.

Report of AAPM Task Group 155: Megavoltage photon beam dosimetry in small fields and non-equilibrium conditions

Small-field dosimetry used in advance treatment technologies poses challenges due to loss of lateral charged particle equilibrium (LCPE), occlusion of the primary photon source, and the limited choice of suitable radiation detectors. These challenges greatly influence dosimetric accuracy. Many high-profile radiation incidents have demonstrated a poor understanding of appropriate methodology for small-field dosimetry. These incidents are a cause for concern because the use of small fields in various specialized radiation treatment techniques continues to grow rapidly. Reference and relative dosimetry in small and composite fields are the subject of the International Atomic Energy Agency (IAEA) dosimetry code of practice that has been published as TRS-483 and an AAPM summary publication (IAEA TRS 483; Dosimetry of small static fields used in external beam radiotherapy: An IAEA/AAPM International Code of Practice for reference and relative dose determination, Technical Report Series No. 483; Palmans et al., Med Phys 45(11):e1123, 2018). The charge of AAPM task group 155 (TG-155) is to summarize current knowledge on small-field dosimetry and to provide recommendations of best practices for relative dose determination in small megavoltage photon beams. An overview of the issue of LCPE and the changes in photon beam perturbations with decreasing field size is provided. Recommendations are included on appropriate detector systems and measurement methodologies. Existing published data on dosimetric parameters in small photon fields (e.g., percentage depth dose, tissue phantom ratio/tissue maximum ratio, off-axis ratios, and field output factors) together with the necessary perturbation corrections for various detectors are reviewed. A discussion on errors and an uncertainty analysis in measurements is provided. The design of beam models in treatment planning systems to simulate small fields necessitates special attention on the influence of the primary beam source and collimating devices in the computation of energy fluence and dose. The general requirements for fluence and dose calculation engines suitable for modeling dose in small fields are reviewed. Implementations in commercial treatment planning systems vary widely, and the aims of this report are to provide insight for the medical physicist and guidance to developers of beams models for radiotherapy treatment planning systems.

Dosimetric Impact of Acuros XB Dose-to-Water and Dose-to-Medium Reporting Modes on Lung Stereotactic Body Radiation Therapy and Its Dependency on Structure Composition

Purpose

Our purpose was to assess the dosimetric effect of switching from the analytical anisotropic algorithm (AAA) to Acuros XB (AXB), with dose-to-medium (Dm) and dose-to-water (Dw) reporting modes, in lung stereotactic body radiation therapy patients and determine whether planning-target-volume (PTV) dose prescriptions and organ-at-risk constraints should be modified under these circumstances.

Methods and Materials

We included 54 lung stereotactic body radiation therapy patients. We delineated the PTV, the ipsilateral lung, the contralateral lung, the heart, the spinal cord, the esophagus, the trachea, proximal bronchi, the ribs, and the great vessels. We performed dose calculations with AAA and AXB, then compared clinically relevant dose-volume parameters. Paired t tests were used to analyze differences of means. We propose a method, based on the composition of the involved structures, for predicting differences between AXB Dw and Dm calculations.

Results

The largest difference between the algorithms was 4%. Mean dose differences between AXB Dm and AXB Dw depended on the average composition of the volumes. Compared with AXB, AAA underestimated all PTV dose-volume parameters (-0.7 Gy to -0.1 Gy) except for gradient index, which was significantly higher (4%). It also underestimated V₅ of the contralateral lung (-0.3%). Significant differences in near-maximum doses (D₂) to the ribs were observed between AXB Dm and AAA (1.7%) and between AXB Dw and AAA (-1.6%). AAA-calculated D₂ was slightly higher in the remaining organs at risk.

Conclusions

Differences between AXB and AAA are below the threshold of clinical detectability (5%) for most patients. For a small subgroup, the difference in maximum doses to the ribs between AXB Dw and AXB Dm may be clinically significant. The differences in dose volume parameters between AXB Dw and AXB Dm can be predicted with reference to structure composition.

Report dose-to-medium in clinical trials where available; a consensus from the Global Harmonisation Group to maximize consistency

PURPOSE

To promote consistency in clinical trials by recommending a uniform framework as it relates to radiation transport and dose calculation in water versus in medium.

METHODS

The Global Quality Assurance of Radiation Therapy Clinical Trials Harmonisation Group (GHG; www.rtqaharmonization.org) compared the differences between dose to water in water (D_w,w), dose to water in medium (D_w,m), and dose to medium in medium (D_m,m). This was done based on a review of historical frameworks, existing literature and standards, clinical issues in the context of clinical trials, and the trajectory of radiation dose calculations. Based on these factors, recommendations were developed.

RESULTS

No framework was found to be ideal or perfect given the history, complexity, and current status of radiation therapy. Nevertheless, based on the evidence available, the GHG established a recommendation preferring dose to medium in medium (D_m,m).

CONCLUSIONS

Dose to medium in medium (D_m,m) is the preferred dose calculation and reporting framework. If an institution's planning system can only calculate dose to water in water (D_w,w), this is acceptable.

Dose accuracy improvement on head and neck VMAT treatments by using the Acuros algorithm and accurate FFF beam calibration

Background

The purpose of this study was to assess dose accuracy improvement and dosimetric impact of switching from the anisotropic analytical algorithm (AA) to the Acuros XB algorithm (AXB) when performing an accurate beam calibration in head and neck (H&N) FFF-VMAT treatments.

Materials and methods

Twenty H&N cancer patients treated with FFF-VMAT techniques were included. Calculations were performed with the AA and AXB algorithm (dose-to-water - AXB_w- and dose-to-medium - AXB_m-). An accurate beam calibration was used for AXB calculations. Dose prescription to the tumour (PTV70) and at-risk-nodal region (PTV58.1) were 70 Gy and 58.1 Gy, respectively. A PTV70_{_bone} including bony structures in PTV70 was contoured. Dose-volume parameters were compared between the algorithms. Statistical tests were used to analyze the differences in mean values and the correlation between compliance with the D95 > 95% requirement and occurrence of local recurrence.

Results

AA systematically overestimated the dose compared to AXB algorithm with mean dose differences within 1.3 Gy/2%, except for the PTV70_{_bone} (2.2 Gy/3.2%). Dose differences were significantly higher for AXB_m calculations when including accurate beam calibration (maximum dose differences up to 2.8 Gy/4.1% and 4.2 Gy/6.3% for PTV70 and PTV70_{_bone}, respectively). 80% of AA-calculated plans did not meet the D95 > 95% requirement after recalculation with AXB_m and accurate beam calibration. The reduction in D95 coverage in the tumour was not clinically relevant.

Conclusions

Using the AXB_m algorithm and carefully reviewing the beam calibration procedure in H&N FFF-VMAT treatments ensures (1) dose accuracy increase by approximately 3%; (2) a consequent dose increase in targets; and (3) a dose reporting mode that is consistent with the trend of current algorithms.

Towards the standardization of the absorbed dose report mode in high energy photon beams

The benefits of using an algorithm that reports absorbed dose-to-medium have been jeopardized by the clinical experience and the experimental protocols that have mainly relied on absorbed dose-to-water. The aim of the present work was to investigate the physical aspects that govern the dosimetry in heterogeneous media using Monte Carlo method and to introduce a formalism for the experimental validation of absorbed dose-to-medium reporting algorithms. Particle fluence spectra computed within the sensitive volume of two simulated detectors (T31016 Pinpoint 3D ionization chamber and EBT3 radiochromic film) placed in different media (water, RW3, lung and bone) were compared to those in the undisturbed media for 6 MV photon beams. A heterogeneity correction factor that takes into account the difference between the detector perturbation in medium and under reference conditions as well as the stopping-power ratios was then derived for all media using cema calculations. Furthermore, the different conversion approaches and Eclipse treatment planning system algorithms were compared against the Monte Carlo absorbed dose reports. The detectors electron fluence perturbation in RW3 and lung media were close to that in water (≤1.5%). However, the perturbation was greater in bone (∼4%) and impacted the spectral shape. It was emphasized that detectors readings should be corrected by the heterogeneity correction factor that ranged from 0.932 in bone to 0.985 in lung. Significant discrepancies were observed between all the absorbed dose reports and conversions, especially in bone (exceeding 10%) and to a lesser extent in RW3. Given the ongoing advances in dose calculation algorithms, it is essential to standardize the absorbed dose report mode with absorbed dose-to-medium as a favoured choice. It was concluded that a retrospective conversion should be avoided and switching from absorbed dose-to-water to absorbed dose-to-medium reporting algorithm should be carried out by a direct comparison of both algorithms.

Technical Note: Vendor miscalibration of preclinical orthovoltage irradiator identified through independent output check

PURPOSE

Accurate radiation dosimetry in radiobiological experiments is crucial for preclinical research in advancement of cancer treatment. Vendors of cell irradiators often perform calibration for end-users. However, calibration accuracy remains unclear due to missing detailed information on calibration equipment and procedures. In this study, we report our findings of a vender miscalibration of the radiation output and our investigation on the root cause of the discrepancy.

METHODS

Independent calibration verification for a commercial preclinical orthovoltage irradiator was conducted. Initially, in the absence of ionization chambers calibrated at kV energy, radiochromic films (EBT3) was first calibrated at MV energy. Energy correction factors from literature were used to create an in-house kV dosimetry system. The miscalibration identified with the in-house kV EBT3 dosimetry was later confirmed by ADCL calibrated ionization chambers (Exradin A1SL and PTW 30013) at kV energy. Ionization chambers were suspended in-air following TG-61 recommendation for output calibration. To investigate the root cause of the miscalibration, additional measurements were performed with ionization chambers placed on the shelf. A validated Monte Carlo simulation code was also used to investigate the impact of placing the ionization chamber on the shelf instead of suspending it in air during the vendor-performed calibration process.

RESULTS

Up to a 6% dosimetry error was observed when comparing the vendor calibrated output of the preclinical irradiator with our independent calibration check. Further investigation showed incorrect setups in the vendor's calibration procedure which may result in dose errors up to 11% from the backscatter of the shelf board during calibration, and up to 5% from omitting temperature and pressure corrections to ionization chamber readings.

CONCLUSION

Our study revealed large dose calibration errors caused by incorrect setup and the omission of temperature/pressure correction in the vendor's calibration procedure. The findings also highlighted the importance of performing an independent check of the dose calibration for preclinical kV irradiators. More absolute dosimetry training is needed for both vendors and end users for establishing accurate absolute dosimetry.

A new dose quantity for evaluation and optimisation of MV photon dose distributions when using advanced algorithms: proof of concept and potential applications

Advanced algorithms used in MV photon radiotherapy model radiation transport in any media. They represent a step forward but introduce new uncertainties and questions, including whether to report the doses to water (D_w,m) or medium (D_m,m) voxels, and the impact of fluence changes introduced by surrounding media. These aspects can compromise consistency between both reporting modes and with previous algorithms in which clinical experience is based. This study introduces a new dose quantity, the dose-to-reference-like medium, to overcome the aforementioned shortcomings. It is linked to a reference medium, water in this study (D_w,m*), and defined as the absorbed dose in a voxel of this reference medium surrounded by a reference-like medium with the same radiation transport characteristics as the original one. We propose to derive D_w,m* distributions by post-processing D_w,m or D_m,m applying a correction factor (CF) to each voxel which depends on its composition. We present and justify a simple and straightforward method to obtain CFs that only involves two phantoms with the same density: one with the considered composition and the other with that of the reference medium. A proof of concept was performed in a clinical environment for Acuros XB (AXB) advanced algorithm and 6 MV photon beams. The CFs were derived for the tissues characterised in Acuros. D_w,m* was compared to D_w,m, D_m,m, and D_w,w from AAA analytical algorithm for some virtual and clinical cases. All the previous quantities presented limitations that can be solved by D_w,m*. This new quantity allows the applicability of evaluation parameters, traceability to clinical experience, and isolation of heterogeneity effects to identify optimum plans, offering useful characteristics for plan evaluation and optimisation in clinical practice. Additionally, it also has potential applications in automated treatment planning and multi-centre activities such as clinical trials, audits, benchmarking, and shared models for automation.

Integration of automation into an existing clinical workflow to improve efficiency and reduce errors in the manual treatment planning process for total body irradiation (TBI)

Purpose

To identify causes of error, and present the concept of an automated technique that improves efficiency and helps to reduce transcription and manual data entry errors in the treatment planning of total body irradiation (TBI).

Methods

Analysis of incidents submitted to incident learning system (ILS) was performed to identify potential avenues for improvement by implementation of automation of the manual treatment planning process for total body irradiation (TBI). Following this analysis, it became obvious that while the individual components of the TBI treatment planning process were well implemented, the manual ‘bridging’ of the components (transcribing data, manual data entry etc.) were leading to high potential for error. A C#‐based plug‐in treatment planning script was developed to remove the manual parts of the treatment planning workflow that were contributing to increased risk.

Results

Here we present an example of the implementation of “Glue” programming, combining treatment planning C# scripts with existing spreadsheet calculation worksheets. Prior to the implementation of automation, 35 incident reports related to the TBI treatment process were submitted to the ILS over a 6‐year period, with an average of 1.4 ± 1.7 reports submitted per quarter. While no incidents reached patients, reports ranged from minor documentation issues to potential for mistreatment if not caught before delivery. Since the implementation of automated treatment planning and documentation, treatment planning time per patient, including documentation, has been reduced; from an average of 45 min pre‐automation to <20 min post‐automation.

Conclusions

Manual treatment planning techniques may be well validated, but they are time‐intensive and have potential for error. Often the barrier to automating these techniques becomes the time required to “re‐code” existing solutions in unfamiliar computer languages. We present the workflow here as a proof of concept that automation may help to improve clinical efficiency and safety for special procedures.

Differences in the Patterns of Failure Between IROC Lung and Spine Phantom Irradiations

PURPOSE

Our purpose was to investigate and classify the reasons why institutions fail the Imaging and Radiation Oncology Core (IROC) stereotactic body radiation therapy (SBRT) spine and moving lung phantoms, which are used to credential institutions for clinical trial participation.

METHODS AND MATERIALS

All IROC moving lung and SBRT spine phantom irradiation failures recorded from January 2012 to December 2018 were evaluated in this study. A failure was a case where the institution did not meet the established IROC criteria for agreement between planned and delivered dose. We analyzed the reports for all failing irradiations, including point dose disagreement, dose profiles, and gamma analyses. Classes of failure patterns were created and used to categorize each instance.

RESULTS

There were 158 failing cases analyzed: 116 of 1052 total lung irradiations and 42 of 263 total spine irradiations. Seven categories were required to describe the lung phantom failures, whereas 4 were required for the spine. Types of errors present in both phantom groups included systematic dose and localization errors. Fifty percent of lung failures were due to a superior-inferior localization error, that is, error in the direction of major motion. Systematic dose errors, however, contributed to only 22% of lung failures. In contrast, the majority (60%) of spine phantom failures were due to systematic dose errors, with localization errors (in any direction) accounting for only 14% of failures.

CONCLUSIONS

There were 2 distinct patterns of failure between the IROC moving lung and SBRT spine phantoms. The majority of the lung phantom failures were due to localization errors, whereas the spine phantom failures were largely attributed to systematic dose errors. Both of these errors are clinically relevant and could manifest as errors in patient cases. These findings highlight the value of independent end-to-end dosimetry audits and can help guide the community in improving the quality of radiation therapy by focusing attention on where errors manifest in the community.