RayStation Treatment Planning System Research Articles

Development and validation of an automated Tomotherapy planning method for cervical cancer

PurposeThis study aimed to develop an automated Tomotherapy (TOMO) planning method for cervical cancer treatment, and to validate its feasibility and effectiveness.Materials and methodsThe study enrolled 30 cervical cancer patients treated with TOMO at our center. Utilizing scripting and Python environment within the RayStation (RaySearch Labs, Sweden) treatment planning system (TPS), we developed automated planning methods for TOMO and volumetric modulated arc therapy (VMAT) techniques. The clinical manual TOMO (M-TOMO) plans for the 30 patients were re-optimized using automated planning scripts for both TOMO and VMAT, creating automated TOMO (A-TOMO) and automated VMAT (A-VMAT) plans. We compared A-TOMO with M-TOMO and A-VMAT plans. The primary evaluated relevant dosimetric parameters and treatment plan efficiency were assessed using the two-sided Wilcoxon signed-rank test for statistical analysis, with a P-value < 0.05 indicating statistical significance.ResultsA-TOMO plans maintained similar target dose uniformity compared to M-TOMO plans, with improvements in target conformity and faster dose drop-off outside the target, and demonstrated significant statistical differences (P+ < 0.01). A-TOMO plans also significantly outperformed M-TOMO plans in reducing V50Gy, V40Gy and Dmean for the bladder and rectum, as well as Dmean for the bowel bag, femoral heads, and kidneys (all P+ < 0.05). Additionally, A-TOMO plans demonstrated better consistency in plan quality. Furthermore, the quality of A-TOMO plans was comparable to or superior than A-VMAT plans. In terms of efficiency, A-TOMO significantly reduced the time required for treatment planning to approximately 20 min.ConclusionWe have successfully developed an A-TOMO planning method for cervical cancer. Compared to M-TOMO plans, A-TOMO plans improved target conformity and reduced radiation dose to OARs. Additionally, the quality of A-TOMO plans was on par with or surpasses that of A-VMAT plans. The A-TOMO planning method significantly improved the efficiency of treatment planning.

Comprehensively evaluating the performance of Elekta high-definition dynamic radiosurgery for hypofractionated stereotactic radiotherapy of multiple brain metastases

PurposeTo evaluate the dosimetric and delivery performance of Elekta high-definition dynamic radiosurgery (HDRS) in hypofractionated stereotactic radiotherapy (HSRT) for multiple brain metastases (BMs) by comparison with a conventional single-isocenter noncoplanar volumetric modulated arc therapy (VMAT) technique using the RayStation treatment planning system (TPS). Materials and methodsFrom June 2022 to October 2023, thirty-two patients (a total of 140 BMs) treated with HSRT (30–48 Gy/3-6f) via HDRS-based single-isocenter noncoplanar VMAT (HDRS-VMAT) were retrospectively selected for this study. Each patient was replanned using RayStation TPS-based single-isocenter noncoplanar VMAT (RayStation-VMAT). HDRS-VMAT and RayStation-VMAT plans were compared in terms of the gradient index (GI), conformity index (CI), normal brain tissue (NBT) dose exposure, monitor units (MUs), homogeneity index (HI), delivery accuracy, and beam-on time (BOT). ResultsCompared with the RayStation-VMAT plan, the HDRS-VMAT plan achieved superior CI (1.14 ± 0.09 vs. 1.23 ± 0.12, P < 0.001) and GI (5.23 ± 1.18 vs. 7.83 ± 2.75, p < 0.001) but had greater HI values. Compared with the RyaStation-VMAT plan, the HDRS-VMAT plan also yielded significantly lower NBT dose exposures (V23Gy, V21Gy, V18Gy, V12Gy and Dmean) but at the cost of increased MUs (3659.16 ± 1225.28 vs. 2536.23 ± 785.80, p < 0.001). The difference in BOTs was minimal (<1 min), which was not considered clinically significant. Furthermore, the HDRS-VMAT exhibited a higher gamma passing rate across all criteria (P < 0.001), particularly under stricter criteria (2%/1 mm), achieving an approximately 3% increase. ConclusionCompared with RaySation-VMAT, HDRS-VMAT offers superior target conformity, better NBT sparing, and higher delivery accuracy while maintaining comparable delivery efficiency. This represents a promising approach for HSRT of multiple BMs.

Multileaf collimator characterization and modeling for a 1.5 T MR-linac using static synchronous and asynchronous sweeping gaps

Objective. The Elekta unity MR-linac delivers step-and-shoot intensity modulated radiotherapy plans using a multileaf collimator (MLC) based on the Agility MLC used on conventional Elekta linacs. Currently, details of the physical Unity MLC and the computational model within its treatment planning system (TPS) Monaco are lacking in published literature. Recently, a novel approach to characterize the physical properties of MLCs was introduced using dynamic synchronous and asynchronous sweeping gap (aSG) tests. Our objective was to develop a step-and-shoot version of the dynamic aSG test to characterize the Unity MLC and the computational MLC models in the Monaco and RayStation TPSs. Approach. Dynamic aSG were discretized into a step-and-shoot aSG by investigating the number of segments/sweep and the minimal number of monitor units (MU) per segment. The step-and-shoot aSG tests were compared to the dynamic aSG tests on a conventional linac at a source-to-detector distance of 143.5 cm, mimicking the Unity configuration. the step-and-shoot aSG tests were used to characterize the Unity MLC through measurements and dose calculations in both TPSs. Main results. The step-and-shoot aSGs tests with 100 segments and 5 MU/segment gave results very similar to the dynamic aSG experiments. The effective tongue-and-groove width of the Unity gradually increased up to 1.4 cm from the leaf tip end. The MLC models in RayStation and Monaco agreed with experimental data within 2.0% and 10%, respectively. The largest discrepancies in Monaco were found for aSG tests with >10 mm leaf interdigitation, which are non-typical for clinical plans. Significance. The step-and-shoot aSG tests accurately characterize the MLC in step-and-shoot delivery mode. The MLC model in RayStation 2023B accurately describes the tongue-and-groove and leaf tip effects whereas Monaco overestimates the tongue-and-groove shadowing further away from the leaf tip end.

Multi-institutional investigation into the robustness of intra-cranial multi-target stereotactic radiosurgery plans to delivery errors.

The use of modulated techniques for intra-cranial stereotactic radiosurgery (SRS) results in highly modulated fields with small apertures, which may be susceptible to uncertainties in the delivery device. This study aimed to quantify the impact of simulated delivery errors on treatment plan dosimetry and how this is affected by treatment planning system (TPS), plan geometry, delivery technique, and plan complexity. A beam modelling error was also included as context to the dose uncertainties due to treatment delivery errors. Delivery errors were assessed for multiple-target brain SRS plans obtained through the Trans-Tasman Radiation Oncology Group (TROG) international treatment planning challenge (2018). The challenge dataset consisted of five intra-cranial targets, each with a prescription of 20Gy. Of the final dataset of 54 plans, 51 were created using the volumetric modulated arc therapy (VMAT) technique and three used intensity modulated arc therapy (IMRT). Thirty-five plans were from the Varian Eclipse TPS, 17 from Elekta Monaco TPS, and one plan each from RayStation and Philips Pinnacle TPS. The errors introduced included: monitor unit calibration errors, multi-leaf collimator (MLC) bank offset, single MLC leaf offset, couch rotations, and collimator rotations. Dosimetric leaf gap (DLG) error was also included as a beam modelling error. Dose to targets was assessed via dose covering 98% of planning target volume (PTV) (D98%), dose covering 2% of PTV (D2%), and dose covering 99% of gross tumor volume (GTV) (D99%). Dose to organs at risk (OARs) was assessed using the volume of normal brain receiving 12Gy (V12Gy), mean dose to normal brain, and maximum dose covering 0.03cc brainstem (D0.03cc). Plan complexity was also assessed via edge metric, modulation complexity score (MCS), mean MLC gap, mean MLC speed, and plan modulation (PM). PTV D98% showed high robustness on average to most errors with the exception of a bank shift of 1.0mm and large rotational errors ≥1.0° for either the couch or collimator. However, in some cases, errors close to or within generally accepted machine tolerances resulted in clinically relevant impacts. The greatest impact upon normal brain V12Gy, mean dose to normal brain, and D0.03cc brainstem was found for DLG error in alignment with other recent studies. All delivery errors had on average a minimal impact across these parameters. Comparing plans from the Monaco TPS and the Eclipse TPS, showed a lesser increase to V12Gy, mean dose to normal brain, and D0.03cc brainstem for Monaco plans (p<0.01) when DLG error was simulated. Monaco plans also correlated to lower plan complexity. Using Spearman's correlation coefficient (r) a strong negative correlation (r≤-0.8) was found between the mean MLC gap and dose to OARs for DLG errors. Reducing MLC complexity and using larger mean MLC gaps is recommended to improve plan robustness and reduce sensitivity to delivery and modelling errors. For cases in which the calculated dose distribution or dose indices are close to the clinically acceptable limits, this is especially important.

Assessment of interfraction dose variation in pancreas SBRT using daily simulation MR images

Pancreatic Cancer is associated with poor treatment outcomes compared to other cancers. High local control rates have been achieved by using hypofractionated stereotactic body radiotherapy (SBRT) to treat pancreatic cancer. Challenges in delivering SBRT include close proximity of several organs at risk (OARs) and target volume inter and intra fraction positional variations. Magnetic resonance image (MRI) guided radiotherapy has shown potential for online adaptive radiotherapy for pancreatic cancer, with superior soft tissue contrast compared to CT. The aim of this study was to investigate the variability of target and OAR volumes for different treatment approaches for pancreatic cancer, and to assess the suitability of utilizing a treatment-day MRI for treatment planning purposes. Ten healthy volunteers were scanned on a Siemens Skyra 3 T MRI scanner over two sessions (approximately 3 h apart), per day over 5 days to simulate an SBRT daily simulation scan for treatment planning. A pretreatment scan was also done to simulate patient setup and treatment. A 4D MRI scan was taken at each session for internal target volume (ITV) generation and assessment. For each volunteer a treatment plan was generated in the Raystation treatment planning system (TPS) following departmental protocols on the day one, first session dataset (D1S1), with bulk density overrides applied to enable dose calculation. This treatment plan was propagated through other imaging sessions, and the dose calculated. An additional treatment plan was generated on each first session of each day (S1) to simulate a daily replan process, with this plan propagated to the second session of the day. These accumulated mock treatment doses were assessed against the original treatment plan through DVH comparison of the PTV and OAR volumes. The generated ITV showed large variations when compared to both the first session ITV and daily ITV, with an average magnitude of 22.44% ± 13.28% and 25.83% ± 37.48% respectively. The PTV D95 was reduced by approximately 23.3% for both plan comparisons considered. Surrounding OARs had large variations in dose, with the small bowel V30 increasing by 128.87% when compared to the D1S1 plan, and 43.11% when compared to each daily S1 plan. Daily online adaptive radiotherapy is required for accurate dose delivery for pancreas cancer in the absence of additional motion management and tumour tracking techniques.

Fully automated volumetric modulated arc therapy planning for locally advanced rectal cancer: feasibility and efficiency

BackgroundVolumetric modulated arc therapy (VMAT) for locally advanced rectal cancer (LARC) has emerged as a promising technique, but the planning process can be time-consuming and dependent on planner expertise. We aimed to develop a fully automated VMAT planning program for LARC and evaluate its feasibility and efficiency.MethodsA total of 26 LARC patients who received VMAT treatment and the computed tomography (CT) scans were included in this study. Clinical target volumes and organs at risk were contoured by radiation oncologists. The automatic planning program, developed within the Raystation treatment planning system, used scripting capabilities and a Python environment to automate the entire planning process. The automated VMAT plan (auto-VMAT) was created by our automated planning program with the 26 CT scans used in the manual VMAT plan (manual-VMAT) and their regions of interests. Dosimetric parameters and time efficiency were compared between the auto-VMAT and the manual-VMAT created by experienced planners. All results were analyzed using the Wilcoxon signed-rank sum test.ResultsThe auto-VMAT achieved comparable coverage of the target volume while demonstrating improved dose conformity and uniformity compared with the manual-VMAT. V30 and V40 in the small bowel were significantly lower in the auto-VMAT compared with those in the manual-VMAT (p < 0.001 and < 0.001, respectively); the mean dose of the bladder was also significantly reduced in the auto-VMAT (p < 0.001). Furthermore, auto-VMAT plans were consistently generated with less variability in quality. In terms of efficiency, the auto-VMAT markedly reduced the time required for planning and expedited plan approval, with 93% of cases approved within one day.ConclusionWe developed a fully automatic feasible VMAT plan creation program for LARC. The auto-VMAT maintained target coverage while providing organs at risk dose reduction. The developed program dramatically reduced the time to approval.

The effect of the tongue and groove of the multileaf collimator on dose distribution: examination of results of measurements and treatment planning system

Multileaf collimators play an important role in the field of radiotherapy and are widely used today. The effect of multileaf collimator structure on dose distribution should be well investigated and whether treatment planning systems reflect these effects on dose distribution should be examined. In our study, we examined the effect of tongue-and-groove on irregular fields and intensity-modulated radiotherapy plan. We also investigated the depth dependence of the tongue-and-groove effect. All fields are created in RayStation treatment planning system. Data obtained from treatment planning systems were compared with data obtained with 2-dimensional dose-measuring devices. We found the tongue-and-groove effect consistent in both measurements in single field measurements. We calculated dose reductions due to tongue-and-groove effect between 6% and 14%. When we examined the tongue-and-groove effect at different depths, we observed that the tongue-and-groove effect decreased as the depth increased. Although the tongue-and-groove effect did not create significant results on the dose distribution in multi-field use, we observed that this effect could occur at the edge of the field. Dose differences due to multileaf collimator structure should be examined by clinics. In addition, the extent to which treatment planning system takes these effects into account should be checked with some measurements. Otherwise, undesirable dose differences may be seen in the patient.

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.

Impact of delivery time factor on treatment time and plan quality in tomotherapy

Delivery time factor (DTF) is a new parameter introduced by the RayStation treatment planning system for tomotherapy treatment planning. This study investigated the effects of this factor on various tomotherapy plans. Twenty-five patients with cancer (head and neck, 6; lung, 9; prostate, 10) were enrolled in this study. Helical tomotherapy plans with a field width of 2.5 cm, pitch of 0.287, and DTF of 2.0 were created. All the initial plans were recalculated by changing the DTF parameter from 1.0 to 3.0 in increments of 0.1. Then, DTF’s impact on delivery efficiency and plan quality was evaluated. Treatment time and modulation factor increased monotonically with increasing DTF. Increasing the DTF by 0.1 increased the treatment time and modulation factor by almost 10%. This relationship was similar for all treatment sites. Conformity index (CI), homogeneity index, and organ at risk doses were improved compared to plans with a DTF of 1.0, except for the CI in the lung cancer case. However, the improvement in most indices ceased at a certain DTF; nevertheless, treatment time continued to increase following an increase in DTF. DTF is a critical parameter for improving the quality of tomotherapy plans.

Evaluation of Dosimetry Metrics in Single Isocenter Multiple Targets and Single Isocenter Single Target in the Treatment of Brain Metastases

Purpose: This study compares two LINAC-based techniques for treating multiple brain lesions using quantitative evaluation of plan dosimetric indices. Material and Methods: Twenty-one patients with a total of 168 targets were selected. All plans were designed with five non-coplanar arcs in the RayStation treatment planning system (TPS). The composite dose of Multiple Isocenter Multiple Targets (MIMT) was compared to that of single isocenter multiple targets (SIMT) by evaluating conformity indices, Paddick gradient-index (PGI), V8, V12, and Delivery Time (DT).

Dosimetric comparison of VMAT standard optimization (SO) and multi-criteria optimization (MCO) treatment plans with standard mode delivery (STD) or sliding window (SW) for head and neck cancer.

A new development on the RayStation treatment planning system (TPS) allows a plan to be planned by imposing a constraint on the leaf sequencing: all leaves move in the same direction before moving again in the opposite direction to create a succession of sliding windows (SWs). The study aims to investigate this new leaf sequencing, coupled with standard optimization (SO) and multi-criteria optimization (MCO) and to compare it with the standard sequencing (STD). Sixty plans were replanned for 10 head and neck cancer patients (two dose levels simultaneously SIB, 56 and 70Gy in 35 fractions). All plans were compared, and a Wilcoxon signed-rank test was performed. Pre-processing QA and metrics of multileaf collimator (MLC) complexity were studied. All methodologies met the dose requirements for the planning target volumes (PTVs) and organs at risk (OARs). SO demonstrates significantly best results for homogeneity index (HI), conformity index (CI), and target coverage (TC). SO-SW gives best results for PTVs (D98% and D2% ) but the differences between techniques are less than 1%. Only the D2%,PTV-56Gy is higher with both MCO methods. MCO-STD offer the best sparing OARs (parotids, spinal cord, larynx, oral cavity). The gamma passing rates (GPRs) with 3%/3mm criteria between the measured and calculated dose distributions are higher than 95%, slightly lowest with SW. The number of monitor units (MUs) and MLC metrics are higher in SW show a higher modulation. All plans are feasible for the treatment. A clear advantage of SO-SW is that the treatment plan is more straightforward to planning by the user due to the more advanced modulation. MCO stands out for its ease of use and will allow a less experienced user to offer a better plan than in SO. In addition, MCO-STD will reduce the dose to the OARs while maintaining good TC.

PO-1716 End-to-end tests for Cyberknife treatment delivery with RayStation treatment planning system

PO-1716 End-to-end tests for Cyberknife treatment delivery with RayStation treatment planning system

A novel automated planning approach for multi-anatomical sites cancer in Raystation treatment planning system

PurposeTo develop an automated planning approach in Raystation and evaluate its feasibility in multiple clinical application scenarios. MethodsAn automated planning approach (Ruiplan) was developed by using the scripting platform of Raystation. Radiotherapy plans were re-generated both automatically by using Ruiplan and manually. 60 patients, including 20 patients with nasopharyngeal carcinoma (NPC), 20 patients with esophageal carcinoma (ESCA), and 20 patients with rectal cancer (RECA) were retrospectively enrolled in this study. Dosimetric and planning efficiency parameters of the automated plans (APs) and manual plans (MPs) were statistically compared. ResultsFor target coverage, APs yielded superior dose homogeneity in NPC and RECA, while maintaining similar dose conformity for all studied anatomical sites. For OARs sparing, APs led to significant improvement in most OARs sparing. The average planning time required for APs was reduced by more than 43% compared with MPs. Despite the increased monitor units (MUs) for NPC and RECA in APs, the beam-on time of APs and MPs had no statistical difference. Both the MUs and beam-on time of APs were significantly lower than that of MPs in ESCA. ConclusionsThis study developed a new automated planning approach, Ruiplan, it is feasible for multi-treatment techniques and multi-anatomical sites cancer treatment planning. The dose distributions of targets and OARs in the APs were similar or better than those in the MPs, and the planning time of APs showed a sharp reduction compared with the MPs. Thus, Ruiplan provides a promising approach for realizing automated treatment planning in the future.

Optimization of proton pencil beam positioning in collimated fields.

The addition of static or dynamic collimator systems to the pencil beam scanning delivery technique increases the number of options for lateral field shaping. The collimator shape needs to be optimized together with the intensity modulation ofspots. To minimize the proton field's lateral penumbra by investigating the fundamental relations between spot and collimating aperture edgeposition. Analytical approaches describing the effect of spot position on the resulting spot profile are presented. The theoretical description is then compared with Monte Carlo simulations in TOPAS and in the RayStation treatment planning system, as well as with radiochromic film measurements at a clinical proton therapy facility. In the model, one single spot profile is analyzed for various spot positions in air. Further, irradiation setups in water with different energies, the combination with a range shifter, and two-dimensional proton fields were investigated in silico. The further the single spot is placed beyond the collimating aperture edge ('overscanning'), the sharper the relative lateral dose fall-off and thus the lateral penumbra. Overscanning up to reduced the lateral penumbra by about 20% on average after a propagation of in air. This benefit from overscanning is first predicted by the analytical proofs and later verified by simulations and measurements. Corresponding analyses in water confirm the benefit in lateral penumbra with spot position optimization as observed theoretically and in air. The combination of spot overscanning with fluence modulation facilitated an additionalimprovement. The lateral penumbra of single spots in collimated scanned proton fields can be improved by the method of spot overscanning. This suggests a better sparing of proximal organs at risk in smaller water depths at higher energies, especially in the plateau of the depth dose distribution. All in all, spot overscanning in collimated scanned proton fields offers particular potential in combination with techniques such as fluence modulation or dynamic collimation for optimizing the lateral penumbra to spare normaltissue.

Commissioning of Helium Ion Therapy and the First Patient Treatment With Active Beam Delivery

Helium ions offer intermediate physical and biological properties to the clinically used protons and carbon ions. This work presents the commissioning of the first clinical treatment planning system (TPS) for helium ion therapy with active beam delivery to prepare the first patients' treatment at the Heidelberg Ion-Beam Therapy Center (HIT). Through collaboration between RaySearch Laboratories and HIT, absorbed and relative biological effectiveness (RBE)-weighted calculation methods were integrated for helium ion beam therapy with raster-scanned delivery in the TPS RayStation. At HIT, a modified microdosimetric kinetic biological model was chosen as reference biological model. TPS absorbed dose predictions were compared against measurements with several devices, using phantoms of different complexities, from homogeneous to heterogeneous anthropomorphic phantoms. RBE and RBE-weighted dose predictions of the TPS were verified against calculations with an independent RBE-weighted dose engine. The patient-specific quality assurance of the first treatment at HIT using helium ion beam with raster-scanned delivery is presented considering standard patient-specific measurements in a water phantom and 2 independent dose calculations with a Monte Carlo or an analytical-based engine. TPS predictions were consistent with dosimetric measurements and independent dose engines computations for absorbed and RBE-weighted doses. The mean difference between dose measurements to the TPS calculation was 0.2% for spread-out Bragg peaks in water. Verification of the first patient treatment TPS predictions against independent engines for both absorbed and RBE-weighted doses presents differences within 2% in the target and with a maximum deviation of 3.5% in the investigated critical regions of interest. Helium ion beam therapy has been successfully commissioned and introduced into clinical use. Through comprehensive validation of the absorbed and RBE-weighted dose predictions of the RayStation TPS, the first clinical TPS for helium ion therapy using raster-scanned delivery was employed to plan the first helium patient treatment at HIT.

Dosimetric benefits of 3D-printed modulated electron bolus following lumpectomy and whole-breast radiotherapy for left breast cancer.

Radiotherapy with electrons is commonly applied to the tumor bed after whole-breast radiotherapy following breast conservation surgery for breast cancer patients. However, the radiation dose to adjacent organs-at-risk (OARs) and conformity of planning target volume (PTV) cannot be optimized. In this study, we examine the feasibility of using modulated electron bolus (MEB) to improve PTV conformity and reduce the dose to these OARs. Twenty-seven patients with left breast cancer were retrospectively selected in this study. For each patient, a tangential photon plan in RayStation treatment planning system with prescription of 26 Gy in 5 fractions was created as base plan. Two electron plans, one without bolus and one with MEB using Adaptiiv software based on the PTV were created. Various dosimetric parameters of OARs including left lung, heart, left anterior descending artery (LAD) and ribs and the conformity indices of PTV of these 2 electron plans together with the base plans were compared. Statistically significant decreases in the dosimetric parameters (V5Gy, V10Gy, V20Gy, and mean dose) of the ipsilateral left lung and the heart were observed with MEB. The median maximum dose to the LAD and the ribs decreased by 6.2% and 4.5% respectively. The median conformity index was improved by 14.3% with median increases of monitor units by 1.7%. Our results show that MEB is feasible resulting in reduction of doses to the predefined OARs and an improved conformity of PTV. By using 3D printing, MEB might be considered as an alternative to conventional electron boost.

Validating a double Gaussian source model for small proton fields in a commercial Monte-Carlo dose calculation engine

PurposeThe primary fluence of a proton pencil beam exiting the accelerator is enveloped by a region of secondaries, commonly called “spray”. Although small in magnitude, this spray may affect dose distributions in pencil beam scanning mode e.g., in the calculation of the small field output, if not modelled properly in a treatment planning system (TPS). The purpose of this study was to dosimetrically benchmark the Monte Carlo (MC) dose engine of the RayStation TPS (v.10A) in small proton fields and systematically compare single Gaussian (SG) and double Gaussian (DG) modeling of initial proton fluence providing a more accurate representation of the nozzle spray. MethodsThe initial proton fluence distribution for SG/DG beam modeling was deduced from two-dimensional measurements in air with a scintillation screen with electronic readout. The DG model was either based on direct fits of the two Gaussians to the measured profiles, or by an iterative optimization procedure, which uses the measured profiles to mimic in-air scan-field factor (SF) measurements. To validate the DG beam models SFs, i.e. relative doses to a 10 × 10 cm2 field, were measured in water for three different initial proton energies (100MeV, 160MeV, 226.7MeV) and square field sizes from 1×1cm2 to 10×10cm2 using a small field ionization chamber (IBA CC01) and an IBA ProteusPlus system (universal nozzle). Furthermore, the dose to the center of spherical target volumes (diameters: 1cm to 10cm) was determined using the same small volume ionization chamber (IC). A comprehensive uncertainty analysis was performed, including estimates of influence factors typical for small field dosimetry deduced from a simple two-dimensional analytical model of the relative fluence distribution. Measurements were compared to the predictions of the RayStation TPS. ResultsSFs deviated by more than 2% from TPS predictions in all fields <4×4cm2 with a maximum deviation of 5.8% for SG modeling. In contrast, deviations were smaller than 2% for all field-sizes and proton energies when using the directly fitted DG model. The optimized DG model performed similarly except for slightly larger deviations in the 1×1cm2 scan-fields. The uncertainty estimates showed a significant impact of pencil beam size variations (±5%) resulting in up to 5.0% standard uncertainty. The point doses within spherical irradiation volumes deviated from calculations by up to 3.3% for the SG model and 2.0% for the DG model. ConclusionProperly representing nozzle spray in RayStation’s MC-based dose engine using a DG beam model was found to reduce the deviation to measurements in small spherical targets to below 2%. A thorough uncertainty analysis shows a similar magnitude for the combined standard uncertainty of such measurements.

Using machine learning to predict gamma passing rate in volumetric-modulated arc therapy treatment plans.

This study aims to develop an algorithm to predict gamma passing rate (GPR) in the volumetric-modulated arc therapy (VMAT) technique. A total of 118 clinical VMAT plans, including 28 mediastina, 25 head and neck, 40 brains intensity-modulated radiosurgery, and 25 prostate cases, were created in RayStation treatment planning system for Edge and TrueBeam linacs. In-house scripts were developed to compute Modulation indices such as plan-averaged beam area (PA), plan-averaged beam irregularity (PI), total monitor unit (MU), leaf travel/arc length, mean dose rate variation, and mean gantry speed variation. Pretreatment verifications were performed on ArcCHECK phantom with SNC software. GPR was calculated with 3%/2mm and 10% threshold. The dataset was randomly split into a training (70%) and a test (30%) dataset. A random forest regression (RFR) model and support vector regression (SVR) with linear kernel were trained to predict GPR using the complexity metrics as input. The prediction performance was evaluated by calculating the mean absolute error (MAE), R2 , and root mean square error (RMSE). RMSEs at γ 3%/2mm for RFR and SVR were 1.407±0.103 and 1.447±0.121, respectively. MAE was 1.14±0.084 for RFR and 1.101±0.09 for SVR. R2 was equal to 0.703±0.027 and 0.689±0.053 for RFR and SVR, respectively. GPR of 3%/2mm with a 10% threshold can be predicted with an error smaller than 3% for 94% of plans using RFR and SVR models. The most important metrics that had the greatest impact on how accurately GPR can be predicted were determined to be the PA, PI, and total MU. In terms of its prediction values and errors, SVR (linear) appeared to be comparable with RFR for this dataset. Based on our results, the PA, PI, and total MU calculations may be useful in guiding VMAT plan evaluation and ultimately reducing uncertainties in planning and radiation delivery.

Target and organ-at-risk (OAR) delineation for VMAT craniospinal irradiation using Raystation's Automatic Atlas Based Segmentation

<h3>Objectives</h3> VMAT Craniospinal irradiation (CSI-VMAT) requires extensive contouring of multiple targets and OARs. Manual contouring of these structures is time consuming (3-5 hours). Using an automatic contouring module within Raystation treatment planning system there is potential to automate outlining and streamline planning. The aim of this project was to produce and evaluate an automatic contouring atlas to facilitate CSI-VMAT planning. <h3>Methods</h3> Two atlases were created using Raystation's atlas-based initialisation (ABI) module; Craniospinal_Ph1_Localise_Adult_Atlas (Atlas 1) and Craniospinal_Ph1_Localise_PaedYA_Atlas (Atlas 2). Automatic contouring was attempted for the following targets and OARs: whole brain, optic nerves, cervical spine, thoracic spine, and lumbar spine, adjacent vertebrae, optic chiasm, globes, lenses, parotids, cochlea's, kidneys, lungs, heart, liver, thyroid gland and oesophagus. 28 anonymised image sets were incorporated into Atlas 1. The paediatric and young adults (YA) atlas (Atlas 2) included an additional ‘Vertebral Body Adjacent' structure for 28 anonymised image sets. The quality of the auto contours was compared to SIOPE consensus atlas for target volume delineation for craniospinal irradiation [1] with institutional peer review and OAR contouring guidelines. <h3>Results</h3> The final Atlases included automation of all CTVs and the following OARs: Chiasm, Globes, Lenses, Cochlea's, Kidneys, Lungs, Heart, Liver and Thyroid. The quality of contouring produced was deemed clinically acceptable except for oesophagus and parotid contours, which were omitted due to inferior contouring. The atlases segmented all structures within 15 minutes. Following minor edits and manual delineation by experienced dosimetrists of omitted contours, delineation time is reduced to 1.5 – 2.5 hours. Further clinician review and approval is undertaken prior to planning. <h3>Conclusion</h3> Atlas's 1 and 2 are now implemented clinically for paediatric and adult CSI-VMAT, providing valuable time saving tools for the planning of these patients. There is the potential for this to be applied to other non-craniospinal paediatric cases, or different techniques including Proton Therapy.

From Nuclear Reactor-Based to Proton Accelerator-Based Therapy: The Finnish Boron Neutron Capture Therapy Experience.

The authors review the results of 249 patients treated with boron neutron capture therapy (BNCT) at the Helsinki University Hospital, Helsinki, Finland, from May 1999 to January 2012 with neutrons obtained from a nuclear reactor source (FiR 1) and using l-boronophenylalanine-fructose (l-BPA-F) as the boron delivery agent. They also describe a new hospital BNCT facility that hosts a proton accelerator-based neutron source for BNCT. Most of the patients treated with nuclear reactor-derived neutrons had either inoperable, locally recurrent head and neck cancer or malignant glioma. In general, l-BPA-F-mediated BNCT was relatively well tolerated with adverse events usually similar to those of conventional radiotherapy. Twenty-eight (96.6%) out of the evaluable 29 patients with head and neck cancer and treated within a clinical trial either responded to BNCT or had tumor growth stabilization for at least 5 months, suggesting efficacy of BNCT in the treatment of this patient population. The new accelerator-based BNCT facility houses a nuBeam neutron source that consists of an electrostatic Cockcroft-Walton-type proton accelerator and a lithium target that converts the proton beam to neutrons. The proton beam energy is 2.6 MeV operating with a current of 30 mA. Treatment planning is based on Monte Carlo simulation and the RayStation treatment planning system. Patient positioning is performed with a 6-axis robotic image-guided system, and in-room imaging is done with a rail-mounted computed tomography scanner. Under normal circumstances, the personnel can enter the treatment room almost immediately after shutting down the proton beam, which improves the unit capacity. ClinicalTrials.gov ID: NCT00114790.