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.

Comparing Efficacy Between Robust and PTV Margin-based Optimizations for Interfractional Anatomical Variations in Prostate Tomotherapy

BACKGROUND/AIM

Interfractional anatomical variations cause considerable differences between planned and actual radiotherapy doses. This study aimed to investigate the efficacy of robust and planning target volume (PTV) margin-based optimizations for the anatomical variations in helical tomotherapy for prostate cancer.

PATIENTS AND METHODS

Ten patients underwent treatment-planning kilovolt computed tomography (kVCT) and daily megavolt computed tomography (MVCT). Two types of nominal plans, with a prescription of 60 Gy/20 fractions, were created using robust and PTV margin-based optimizations on kVCT for each patient. Subsequently, the daily estimated doses were recalculated using nominal plans, and all available MVCTs modified the daily patient-setup errors. Due to the difference in dose calculation accuracy between kVCT and MVCT, three scenarios with dose corrections of 1, 2, and 3% were considered in the recalculation process. The dosimetric metrics, including target coverage with the prescription dose, Paddick's conformity index, homogeneity index, and mean dose to the rectum, were analyzed.

RESULTS

A dosimetric comparison of the nominal plans demonstrated that the robust plans had better dose conformity, lower target coverage, and dose homogeneity than the PTV plans. In the daily estimated doses of any dose-corrected scenario, the target coverage and dose sparing to the rectum in the robust plans were significantly higher than those in the PTV plans, whereas dose conformity and homogeneity were identical to those of the nominal case.

CONCLUSION

Robust optimization is recommended as it accounts for anatomical variations during treatment regarding target coverage in helical tomotherapy plans for prostate cancer.

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.

Commissioning of a RayStation structure template for the iBEAM evo Couchtop

Accurate radiotherapy treatment planning requires attenuation through the treatment couch to be accounted for in dose calculation. This is commonly performed by using contouring tools to add a virtual structure in the shape of the treatment couch and assigning the preferred absorption properties. The RayStation treatment planning system (TPS) allows users to assign a material that comprises both an elemental structure and a physical density. The selection of such parameters should be made so that modelled attenuation through the couch closely matches measured data. When these measurements involve the use of plastic phantoms and rotational beams, the validity of the data is dependent upon aspects of TPS and linear accelerator performance that can be difficult to quantify. A fundamental measure of couch attenuation using an ionisation chamber in water and perpendicular beam geometry that required no gantry movement was implemented to eliminate the identified uncertainties. This data was used to determine the combination of elemental composition and density assigned to a modelled couch structure that provided the most accurate representation of beam attenuation in this simple geometry. The preferred material was then validated using a cylindrical phantom and rotational beams. The findings were equivalent between the static gantry with water phantom and rotating gantry with cylindrical phantom. Of the elemental compositions investigated, it was possible to achieve suitable agreement with the measured data for each option provided the density was optimised. Choice of the elemental composition was not observed to be an important factor in achieving a good model.

Treatment planning of scanned proton beams in RayStation

The use of scanned proton beams in external beam radiation therapy has seen a rapid development over the past decade. This technique places new demands on treatment planning, as compared to conventional photon-based radiation therapy. In this article, several proton specific functions as implemented in the treatment planning system RayStation are presented. We will cover algorithms for energy layer and spot selection, basic optimization including the handling of spot weight limits, optimization of the linear energy transfer (LET) distribution, robust optimization including the special case of 4D optimization, proton arc planning, and automatic planning using deep learning. We will further present the Monte Carlo (MC) proton dose engine in RayStation to some detail, from the material interpretation of the CT data, through the beam model parameterization, to the actual MC transport mechanism. Useful tools for plan evaluation, including robustness evaluation, and the versatile scripting interface are also described. The overall aim of the paper is to give an overview of some of the key proton planning functions in RayStation, with example usages, and at the same time provide the details about the underlying algorithms that previously have not been fully publicly available.

Validation of the relative biological effectiveness of active-energy scanning carbon-ion radiotherapy on a commercial treatment planning system with a microdosimetic kinetic model

BACKGROUND

The study objective was to validate the relative biological effectiveness (RBE) calculated by the modified microdosimetric kinetic model in RayStation (Ray-MKM) for active-energy scanning carbon-ion radiotherapy.

METHODS

The Ray-MKM was benchmarked using a spread-out Bragg-peak (SOBP) plan, which was suggested in literature from the National Institute of Radiobiological Science (NIRS) in Japan. The residual RBE differences from the MKM at NIRS (NIRS-MKM) were derived using several SOBP plans with different ranges, SOBP widths, and prescriptions. To investigate the origins of the differences, we compared the saturation-corrected dose-mean specific energy [Formula: see text] of the aforementioned SOBPs. Furthermore, we converted the RBE-weighted doses with the Ray-MKM to those with local effect model I (LEM doses). The purpose was to investigate whether the Ray-MKM could reproduce the RBE-weighted conversion study.

RESULTS

The benchmark determined the value of the clinical dose scaling factor, [Formula: see text], as 2.40. The target mean RBE deviations between the Ray-MKM and NIRS-MKM were median: 0.6 (minimum: 0.0 to maximum: 1.69) %. The [Formula: see text] difference in-depth led to the RBE difference in-depth and was remarkable at the distal end. The converted LEM doses from the Ray-MKM doses were comparable (the deviation being - 1.8-0.7%) to existing literature.

CONCLUSION

This study validated the Ray-MKM based on our active-energy scanning carbon-ion beam via phantom studies. The Ray-MKM could generate similar RBEs as the NIRS-MKM after benchmarking. Analysis based on [Formula: see text] indicated that the different beam qualities and fragment spectra caused the RBE differences. Since the absolute dose differences at the distal end were small, we neglected them. Furthermore, each centre may determine its centre-specific [Formula: see text] based on this approach.

Calibration and evaluation of the relative biological effectiveness for carbon-ion radiotherapy in a new relative to a clinically applied treatment planning system

BACKGROUND

The study objective was to validate the relative biological effectiveness (RBE) in RayStation for carbon-ion radiotherapy (CIRT) using the Syngo treatment planning system as reference.

METHODS

Local effect model I was established in RayStation (Ray-LEM) with the same parameters as in LEM I in Syngo (Syngo-LEM). Three cube plans covering most of the tumors treated at our center were generated with Syngo-LEM. Ray-LEM re-calculated the Syngo plans and compared the RBEs to the Syngo counterparts. The results showed that RayStation RBE was smaller than Syngo RBE. To ensure that Ray-LEM reproduced Syngo RBE, the observed deviations were used to scale the maximum RBE (RBEmax) in Ray-LEM. After this calibration, we further compared the RayStation RBE to Syngo RBE using additional plans in both homogeneous phantoms and patients, to ensure that the calibrated Ray-LEM reproduced Syngo RBE even with more complex planning features.

RESULTS

The calibration increased the RBEmax by 2.3% to raise the Ray-LEM RBE. The target mean RBE deviations in the phantom evaluation plans were median: 0.0 (minimum: - 1.1 to maximum: 0.7) %, and the target mean RBE deviations of the clinical target volumes of 16 patient cases were - 0.4 (- 1.5 to 0.2) %.

CONCLUSIONS

The residual RBE difference between RayStation and Syngo was found to be ≤ 1.0%. Thus, we can propose to use RayStation for clinical CIRT treatment planning. However, the potential differences due to the absorbed beam model warrants further exploration.

Robust optimization of VMAT for prostate cancer accounting for geometric uncertainty

The aim of this study was to propose optimal robust planning by comparing the robustness with setup error with the robustness of a conventional planning target volume (PTV)‐based plan and to compare the robust plan to the PTV‐based plan for the target and organ at risk (OAR). Data from 13 patients with intermediate‐to‐high‐risk localized prostate cancer who did not have T3b disease were analyzed. The dose distribution under multiple setup error scenarios was assessed using a conventional PTV‐based plan. The clinical target volume (CTV) and OAR dose in moving coordinates were used for the dose constraint with the robust plan. The hybrid robust plan added the dose constraint of the PTV‐rectum to the static coordinate system. When the isocenter was shifted by 10 mm in the superior–inferior direction and 8 mm in the right‐left and anterior directions, the doses to the CTV, bladder, and rectum of the PTV‐based plan, robust plan, and hybrid robust plan were compared. For the CTV D_99% in the PTV‐based plan and hybrid robust plan, over 95% of the prescribed dose was secured in all directions, except in the inferior direction. There was no significant difference between the PTV‐based plan and the hybrid robust plan for rectum V_70Gy, V_60Gy, and V_40Gy. This study proposed an optimization method for patients with prostate cancer. When the setup error occurred within the PTV margin, the dose robustness of the CTV for the hybrid robust plan was higher than that of the PTV‐based plan, while maintaining the equivalent OAR dose.

Interinstitutional beam model portability study in a mixed vendor environment

A 6 MV flattened beam model for a Varian TrueBeamSTx c‐arm treatment delivery system in RayStation, developed and validated at one institution, was implemented and validated at another institution. The only parameter value adjustments were to accommodate machine output at the second institution. Validation followed MPPG 5.a. recommendations, with particular attention paid to IMRT and VMAT deliveries. With this minimal adjustment, the model passed validation across a broad spectrum of treatment plans, measurement devices, and staff who created the test plans and executed the measurements. This work demonstrates the possibility of using a single template model in the same treatment planning system with matched machines in a mixed vendor environment.

Intra-fractional per-beam adaptive workflow to mitigate the need for a rotating gantry during MRI-guided proton therapy

The integration of real-time magnetic resonance imaging (MRI)-guidance and proton therapy would potentially improve the proton dose steering capability by reducing daily uncertainties due to anatomical variations. The use of a fixed beamline coupled with an axial patient couch rotation would greatly simplify the proton delivery with MRI-guidance. Nonetheless, it is mandatory to assure that the plan quality is not deteriorated by the anatomical deformations due to patient rotation. In this work, an in-house tool allowing for intra-fractional per-beam adaptation of intensity-modulated proton plans (BeamAdapt) was implemented through features available in RayStation. A set of three MRIs was acquired for two healthy volunteers (V1, V2): (1) no rotation/static, (2) rotation to the right and (3) left. V1 was rotated by 15º, to simulate a clinical pediatric abdominal case and V2 by 45º, to simulate an extreme patient rotation case. For each volunteer, a total of four intensity-modulated pencil beam scanning plans were optimized on the static MRI using virtual abdominal targets and 2-3 posterior-oblique beams. Beam angles were defined according to the angulations on the rotated MRIs. With BeamAdapt, each original plan was first converted into separate plans with one beam per plan. In an iterative order, individual beam doses were non-rigidly deformed to the rotated anatomies and re-optimized accounting for the consequent deformations and the beam doses delivered so far. For evaluation, the final adapted dose distribution was propagated back to the static MRI. Planned and adapted dose distributions were compared by computing relative differences between dose-volume histogram (DVH) metrics. Absolute target dose differences were on average below 1% and mean dose organs-at-risk differences were below 3%. With BeamAdapt, not only intra-fractional per-beam proton plan adaptation coupled with axial patient rotation is possible but also the need for a rotating gantry during MRI-guidance might be mitigated.

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

PURPOSE

This work compares Monte Carlo dose calculations performed using the RayStation treatment planning system against data measured on a Varian Truebeam linear accelerator with 6 MV and 10 MV FFF photon beams.

METHODS

The dosimetric performance of the RayStation Monte Carlo calculations was evaluated in a variety of irradiation geometries employing homogeneous and heterogeneous phantoms. Profile and depth dose comparisons against measurement were carried out in relative mode using the gamma index as a quantitative measure of similarity within the central high dose regions.

RESULTS

The results demonstrate that the treatment planning system dose calculation engine agrees with measurement to within 2%/1 mm for more than 95% of the data points in the high dose regions for all test cases. A systematic underestimation was observed at the tail of the profile penumbra and out of field, with mean differences generally <0.5 mm or 1% of curve dose maximum respectively. Out of field agreement varied between evaluated beam models.

CONCLUSIONS

The RayStation implementation of photon Monte Carlo dose calculations show good agreement with measured data for the range of scenarios considered in this work and is deemed sufficiently accurate for introduction into clinical use.

Validation and practical implementation of seated position radiotherapy in a commercial TPS for proton therapy

PURPOSE

This work aims to validate new 6D couch features and their implementation for seated radiotherapy in RayStation (RS) treatment planning system (TPS).

MATERIALS AND METHODS

In RS TPS, new 6D couch features are (i) chair support device, (ii) patient treatment option of "Sitting: face towards the front of the chair", and (iii) patient support pitch and roll capabilities. The validation of pitch and roll was performed by comparing TPS generated DRRs with planar x-rays. Dosimetric tests through measurement by 2D ion chamber array were performed for beams created with varied scanning and treatment orientation and 6D couch rotations. For the implementation of 6D couch features for treatments in a seated position, the TPS and oncology information system (Mosaiq) settings are described for a commercial chair. An end-to-end test using an anthropomorphic phantom was performed to test the complete workflow from simulation to treatment delivery.

RESULTS

The 6D couch features were found to have a consistent implementation that met IEC 61712 standard. The DRRs were found to have an acceptable agreement with planar x-rays based on visual inspection. For dose map comparison between measured and calculated, the gamma index analysis for all the beams was >95% at a 3% dose-difference and 3 mm distance-to-agreement tolerances. For an end-to end-testing, the phantom was successfully set up at isocenter in the seated position and treatment was delivered.

CONCLUSIONS

Chair-based treatments in a seated position can be implemented in RayStation through the use of newly released 6D couch features.

A standardized commissioning framework of Monte Carlo dose calculation algorithms for proton pencil beam scanning treatment planning systems

PURPOSE

Treatment planning systems (TPSs) from different vendors can involve different implementations of Monte Carlo dose calculation (MCDC) algorithms for pencil beam scanning (PBS) proton therapy. There are currently no guidelines for validating non-water materials in TPSs. Furthermore, PBS-specific parameters can vary by 1-2 orders of magnitude among different treatment delivery systems (TDSs). This paper proposes a standardized framework on the use of commissioning data and steps to validate TDS-specific parameters and TPS-specific heterogeneity modeling to potentially reduce these uncertainties.

METHODS

A standardized commissioning framework was developed to commission the MCDC algorithms of RayStation 8A and Eclipse AcurosPT v13.7.20 using water and non-water materials. Measurements included Bragg peak depth-dose and lateral spot profiles and scanning field outputs for Varian ProBeam. The phase-space parameters were obtained from in-air measurements and the number of protons per MU from output measurements of 10 × 10 cm² square fields at a 2 cm depth. Spot profiles and various PBS field measurements at additional depths were used to validate TPS. Human tissues in TPS, Gammex phantom materials, and artificial materials were used for the TPS benchmark and validation.

RESULTS

The maximum differences of phase parameters, spot sigma, and divergence between MCDC algorithms are below 4.5 µm and 0.26 mrad in air, respectively. Comparing TPS to measurements at depths, both MC algorithms predict the spot sigma within 0.5 mm uncertainty intervals, the resolution of the measurement device. Beam Configuration in AcurosPT is found to underestimate number of protons per MU by ~2.5% and requires user adjustment to match measured data, while RayStation is within 1% of measurements using Auto model. A solid water phantom was used to validate the range accuracy of non-water materials within 1% in AcurosPT.

CONCLUSIONS

The proposed standardized commissioning framework can detect potential issues during PBS TPS MCDC commissioning processes, and potentially can shorten commissioning time and improve dosimetric accuracies. Secondary MCDC can be used to identify the root sources of disagreement between primary MCDC and measurement.

Automatic Planning for Nasopharyngeal Carcinoma Based on Progressive Optimization in RayStation Treatment Planning System

OBJECTIVE

To evaluate and quantify the planning performance of automatic planning (AP) with manual planning (MP) for nasopharyngeal carcinoma in the RayStation treatment planning system (TPS).

METHODS

A progressive and effective design method for AP of nasopharyngeal carcinoma was realized through automated scripts in this study. A total of 30 patients with nasopharyngeal carcinoma with initial treatment was enrolled. The target coverage, conformity index (CI), homogeneity index (HI), organs at risk sparing, and the efficiency of design and execution were compared between automatic and manual volumetric modulated arc therapy (VMAT) plans.

RESULTS

The results of the 2 design methods met the clinical dose requirement. The differences in D95 between the 2 groups in PTV1 and PTV2 showed statistical significance, and the MPs are higher than APs, but the difference in absolute dose was only 0.21% and 0.16%. The results showed that the conformity index of planning target volumes (PTV1, PTV2, PTVnd and PGTVnx+rpn [PGTVnx and PGTVrpn]), homogeneity index of PGTVnx+rpn, and HI of PTVnd in APs are better than that in MPs. For organs at risk, the APs are lower than the MPs, and the difference was statistically significant (P < .05). The manual operation time in APs was 83.21% less than that in MPs, and the computer processing time was 34.22% more.

CONCLUSION

IronPython language designed by RayStation TPS has clinical application value in the design of automatic radiotherapy plan for nasopharyngeal carcinoma. The dose distribution of tumor target and organs at risk in the APs was similar or better than those in the MPs. The time of manual operation in the plan design showed a sharp reduction, thus significantly improving the work efficiency in clinical application.

Evaluation of the RayStation electron Monte Carlo dose calculation algorithm

The aim of this work was to evaluate the accuracy of the RayStation treatment planning system electron Monte Carlo algorithm against measured data for a range of clinically relevant scenarios. This was done by comparing measured percentage depth dose data (PDD) in water, profiles at oblique incidence and with heterogeneities in the beam path, and output factor data and that generated using the RayStation treatment planning system Monte Carlo VMC++ based calculation algorithm. While electron treatments are widely employed in the radiotherapy setting accurate modelling is challenging (TPS) in the presence of patient being both heterogeneous and nonrectangular. Watertank-based measurements were made on a Varian TrueBeam linear accelerator covering electron beam energies 6 to 18 MeV. These included both normal and oblique incidence, heterogeneous geometries, and irregular shaped cut-outs. The measured geometries were replicated in RayStation and the Monte Carlo dose calculation engine used to generate dosimetric data for comparison against measurement in what were considered clinically relevant settings. Water-based PDDs and profile comparisons showed excellent agreement for all electron beam energies. Profiles measured with oblique beam incidence demonstrated acceptable agreement to the treatment planning system calculations although the correspondence worsened as the angle increased with the planning system overestimating the dose in the shoulder region. Profile measurements under inhomogeneities were generally good. The planning system had a tendency to overestimate dose under the heterogeneity and also demonstrated a broader penumbra than measurement. Of the 170 different output factors calculated in RayStation over the range of electron energies commissioned, 141 were within ± 3% of measured values and 164 within ± 5%. Four of the 6 comparisons beyond 5% were at 18 MeV and all had a cut-out edge within 3 cm of the beam central axis/measurement point. The RayStation implementation of a VMC++ electron Monte Carlo dose calculation algorithm shows good agreement with measured data for a range of scenarios studied and represented sufficient accuracy for clinical use.

End-to-end testing of automatic plan optimization using RayStation scripting for hypofractionated multimetastatic brain stereotactic radiosurgery

For external beam stereotactic radiosurgery of multiple brain metastatic lesions, it is difficult to select optimal treatment isocenters because the orientation and volume of each planning target volume (PTV) and its proximity to critical structures are unique for each patient. The RayStation treatment planning system offers Python-based scripting to optimize the placement of the treatment isocenter by comparing scenario-based plans. This can improve the plan quality by reducing the dose to the normal brain and increasing planning efficiency. The purpose of the current study was to compare the isocenter-optimized plans generated by RayStation with clinical plans created by the Pinnacle treatment planning system and to validate the RayStation treatment planning and delivery with end-to-end testing. Ten patient plans were automatically regenerated using the script in RayStation. For each patient, 4 plans with 4 different types of isocenters were generated: (1) 2 separate isocenters at the PTV centroids, (2) a single isocenter at the mid-point of 2 centroids, (3) a single isocenter at PTV1, and (4) a single isocenter at PTV2. The best plans were compared with paired Pinnacle plans using plan quality parameters, including normal brain volume excluding PTVs receiving 4 Gy (V_4Gy), normal brain volume excluding PTVs receiving 12 Gy (V_12Gy), maximum dose to the brainstem, homogeneity index, conformity indices, gradient index of each PTV, and monitor units per fraction. All plans were verified with a cylindrical quality assurance phantom, and end-to-end testing was performed with an anthropomorphic head phantom with a radiochromic film. The script was executed within 5-6 minutes to generate 4 scenario-based automatic plans. The homogeneity index and conformity indices showed small but statistically significant improvement with the RayStation plans. The gradient index (3.9 ± 0.9 for Pinnacle and 3.5 ± 0.6 for RayStation, p = 0.04) was also more favorable in the RayStation plans. V_12Gy was significantly reduced by 13% and V_4Gy was reduced by 5%. The total monitor units per fraction was significantly reduced by 20% for the RayStation plans. Plan optimization time using RayStation was reduced by 64%. The measured doses at each PTV centroid agreed within 3%, and all RayStation plans passed quality assurance verification tests. Scenario-based automatic plan generation using Python scripting helps identify an optimal treatment isocenter to reduce the dose to the normal brain and improve planning efficiency. RayStation plans provided better plan quality, especially lower doses to the normal brain, than Pinnacle plans. Thus, RayStation is a suitable planning modality for hypofractionated stereotactic radiosurgery for multiple brain metastases.

RayStation: External beam treatment planning system

RaySearch Laboratories is a world leader in the field of advanced software and creator of the RayStation treatment planning system for radiation therapy. The aim with RayStation is to deliver an unmatched user experience and leading functionality. Unique features described here include multiatlas based autosegmentation for contouring, deformable registration with 2 different algorithms, multicriteria optimization, Plan Explorer, fallback planning, ultrafast computation speed, and 4-dimensional (4D) adaptive radiation therapy. RayStation can be used to plan for electrons and photons on traditional linacs, for protons on various delivery systems, and for Accuray's helical TomoTherapy system. This paper describes some of these modalities, with reference to clinical cases and including descriptions of the impact on workflow.

Robust optimization in lung treatment plans accounting for geometric uncertainty

Robust optimization generates scenario‐based plans by a minimax optimization method to find optimal scenario for the trade‐off between target coverage robustness and organ‐at‐risk (OAR) sparing. In this study, 20 lung cancer patients with tumors located at various anatomical regions within the lungs were selected and robust optimization photon treatment plans including intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) plans were generated. The plan robustness was analyzed using perturbed doses with setup error boundary of ±3 mm in anterior/posterior (AP), ±3 mm in left/right (LR), and ±5 mm in inferior/superior (IS) directions from isocenter. Perturbed doses for D₉₉, D₉₈, and D₉₅ were computed from six shifted isocenter plans to evaluate plan robustness. Dosimetric study was performed to compare the internal target volume‐based robust optimization plans (ITV‐IMRT and ITV‐VMAT) and conventional PTV margin‐based plans (PTV‐IMRT and PTV‐VMAT). The dosimetric comparison parameters were: ITV target mean dose (D_mean), R₉₅(D₉₅/D_prescription), Paddick's conformity index (CI), homogeneity index (HI), monitor unit (MU), and OAR doses including lung (D_mean, V_{20 Gy} and V_{15 Gy}), chest wall, heart, esophagus, and maximum cord doses. A comparison of optimization results showed the robust optimization plan had better ITV dose coverage, better CI, worse HI, and lower OAR doses than conventional PTV margin‐based plans. Plan robustness evaluation showed that the perturbed doses of D₉₉, D₉₈, and D₉₅ were all satisfied at least 99% of the ITV to received 95% of prescription doses. It was also observed that PTV margin‐based plans had higher MU than robust optimization plans. The results also showed robust optimization can generate plans that offer increased OAR sparing, especially for normal lungs and OARs near or abutting the target. Weak correlation was found between normal lung dose and target size, and no other correlation was observed in this study.

Helical tomotherapy to LINAC plan conversion utilizing RayStation Fallback planning

RaySearch RayStation Fallback (FB) planning module can generate an equivalent backup radiotherapy treatment plan facilitating treatment on other linear accelerators. FB plans were generated from the RayStation FB module by simulating the original plan target and organ at risk (OAR) dose distribution and delivered in various backup linear accelerators. In this study, helical tomotherapy (HT) backup plans used in Varian TrueBeam linear accelerator were generated with the RayStation FB module. About 30 patients, 10 with lung cancer, 10 with head and neck (HN) cancer, and 10 with prostate cancer, who were treated with HT, were included in this study. Intensity‐modulated radiotherapy Fallback plans (FB‐IMRT) were generated for all patients, and three‐dimensional conformal radiotherapy Fallback plans (FB‐3D) were only generated for lung cancer patients. Dosimetric comparison study evaluated FB plans based on dose coverage to 95% of the PTV volume (R₉₅), PTV mean dose (D_mean), Paddick's conformity index (CI), and dose homogeneity index (HI). The evaluation results showed that all IMRT plans were statistically comparable between HT and FB‐IMRT plans except that PTV HI was worse in prostate, and PTV R₉₅ and HI were worse in HN multitarget plans for FB‐IMRT plans. For 3D lung cancer plans, only the PTV R₉₅ was statistically comparable between HT and FB‐3D plans, PTV D_mean was higher, and CI and HI were worse compared to HT plans. The FB plans using a TrueBeam linear accelerator generally offer better OAR sparing compared to HT plans for all the patients. In this study, all cases of FB‐IMRT plans and 9/10 cases of FB‐3D plans were clinically acceptable without further modification and optimization once the FB plans were generated. However, the statistical differences between HT and FB‐IMRT/3D plans might not be of any clinically significant. One FB‐3D plan failed to simulate the original plan without further optimization.