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.

Pencil beam algorithms for proton therapy cannot accurately predict doses in heterogeneous media. Monte-Carlo dose algorithms may improve the accuracy of dose calculations through use of statistical simulation methods where a particle undergoes interactions based on probability distributions of physical processes. In this investigation, we compare the newly implemented RayStationTM v4.0 Monte Carlo (MC) algorithm against the measurements and simulations performed in a highly validated Geant4 (G-MC) software package. Comparisons are also provided against the clinical RayStationTM v4.0 pencil beam algorithm (RS-PBA). Two phantom geometries were constructed by placing a bone or lung slab in a water tank. The slabs were placed at 15 cm depth and laterally positioned such that the edge of the slab was matched with the central-axis of the proton beam. A proton spread-out Bragg peak with 20 cm range and 10 cm modulation was used for simulation and measurement. A 1-D profile measurement perpendicular to the beam direction was made using a diamond detector at 20 cm for bone and 21.5 cm for lung slab. The measurement geometries were simulated in G-MC and lateral dose profiles were obtained with statistical uncertainty of <2%. This geometry was mimicked in the RayStation TPS to calculate doses using the RS-PBA and RS-MC dose engines. Dose profiles from G-MC/RS-MC/RS-PBA were compared to measurements using a 1-D gamma analysis. For bone slab, both G-MC and RS-MC had 100% gamma index (1%/1mm) when compared against measurements. Similarly for the lung slab, G-MC and RS-MC had a 100% and 94.4% gamma index respectively. All the gamma indexes for G-MC and R-MC had a 100% pass rate using 2%/1mm. The gamma indexes for RS-PBA were much worse with only 22.2% points for bone and 27.8% points for lung using 1%/1mm criteria. Dose differences greater than 15% were seen at the distal edge interface for both lung and bone slabs using RS-PBA. Both RS-MC and G-MC were able to match the measured lateral dose profile. RS-PBA showed significant deviations from the measurements and simulations that may be not be clinically acceptable. For anatomic sites where heterogeneity is expected such as head and neck, lung, and chestwall, the RS-MC algorithm should be used for accurate dose calculations.Abstract 3709Results of gamma index analysis of 1-D dose profiles. The profiles are obtained at the interface of bone (or lung) with water near the distal edgeBone SlabLung Slab1%/1mm2%/1mm3%/1mm1%/1mm2%/1mm3%/1mmG-MC vs Meas10010010097.2100100RS-MC vs Meas10010010094.4100100RS-PBA vs Meas22.238.95027.833.344.4 Open table in a new tab

Pencil beam algorithms for proton therapy cannot accurately predict doses in heterogeneous media. Monte Carlo algorithms may improve the accuracy of dose calculations through use of statistical simulation methods where a particle undergoes interactions based on probability distributions of physical processes. We compared dose planes measured in an anthropomorphic Alderson-Rando (AR) phantom against dose calculated in RayStationTM Monte Carlo 4.0 (RS-MC) and Pencil Beam 4.0 (RS-PBA) algorithms. A thorax section consisting of high tissue heterogeneity due to lung, soft tissue and bone interfaces of the AR phantom was imaged using in-house CT and the resulting images were transferred to the planning system. A cylindrical target with diameter 10 cm and height 10 cm was created in the mediastinum region of the phantom. The target was optimized to deliver uniform dose of 40 Gy in 10 fractions using RS-PBA. The same plan was also re-calculated using RS-MC. Dose measurements were made in the AR phantom after every slice using Gafchromic film. Measured and calculated dose profiles were compared through gamma index analysis. A comparison of point doses in the high dose uniform region after every slice was also performed. The gamma index for RS-MC was greater than 90% (3%/3 mm) at all depths except for the most distal plane which had a gamma index of74.3%. For RS-PBA, 4 of 7 planes had gamma indexes less than 90% while the most distal layer had a gamma index of 45.7%. Using a 7%/4 mm (IROC credentialing criteria) tolerance for the most distal plane, the gamma index was 87.5% and 50.1% for RS-MC and RS-PBA, respectively. The RS-MC point doses matched the measurement within +/-3% at all depths. For RS-PBA, all the point dose measurements were within +/-4% except at the most distal depth of 17.5 cm where deviation was 33%. In heterogeneous geometries such as lung, RS-PBA is not able to accurately predict doses towards the distal side of the target and dose errors of up to ∼30% can be observed. Compared to RS-PBA, RS-MC matches measurements better as only one plane in the high gradient distal edge had a <90% gamma index at 3%/3mm.Abstract 3708Gamma index analysisDepth (cm)3%/3mm5%/3mm7%/3mm7%/4mmRS-MC2.596.598.899.599.8RS-PBA95.498.499.499.6RS-MC593.897.59999.5RS-PBA90.395.598.198.3RS-MC7.593.797.699.399.6RS-PBA87.493.797.697.9RS-MC1096.499.399.8100RS-PBA90.597.19999.1RS-MC12.59798.999.399.7RS-PBA89.795.697.797.8RS-MC1593.996.597.799.1RS-PBA71.478.884.185.3RS-MC17.574.379.583.588.3RS-PBA45.750.555.761.3Point DosesDepth (cm)MeasuredRS-PBARS-MCRS-PBA/MeasuredRS-MC/Measured2.5336.7334.3335.60.991.005354.3356.6351.01.010.997.5389.1382.6386.50.980.9910385.5392.7375.51.020.9712.5388.7403.0390.01.041.0015381.6387.4375.71.020.9817.5350.0235.2357.90.671.02 Open table in a new tab

Purpose/Objective(s): Leptomeningeal carcinomatosis (LMC) is a rare manifestation of metastatic cancer and occurs in 5-10% of patients with brain metastases.The current literature remains limited in its understanding of the predictive factors for the development of LMC after stereotactic radiosurgery (SRS) for brain metastases.This case-control study explored multiple risk factors that may predispose patients to LMC after SRS treatment.Materials/Methods: Under an IRB approved protocol, a case-control study of patients with brain metastases who underwent single-fraction SRS between March 2011 and June 2016 at one institution was conducted.Demographic, clinical, and brain lesion information were collected retrospectively from patients' electronic medical records for 19 LMC cases and 30 controls out of 413 patients, including baseline recursive partitioning analysis (RPA) classification, location of brain metastases, tumor size, tumor volume, history of surgical resection of brain metastases, and WBRT.Controls were matched for age at treatment (AE3 years), gender, primary cancer, histology, and race.Risk factors of interest were evaluated by univariate and multivariate logistic regression analyses and overall survival were evaluated by Kaplan-Meier survival analysis.Results: About 5% of our patients with brain metastases who received SRS developed LMC.Overall in cases and controls, the 1-year survival rate after SRS was 33.3% while the 2-year survival rate after SRS was 6.7%.Patients with LMC (median 154 days, 95% CI: 33-203 days) demonstrated a poorer overall survival than matched controls (median 417 days, 95% CI: 121-512 days, pZ0.002).The most common primary tumor histologies for LMC were non-small cell lung cancer (36.8%), breast cancer (26.3%), and melanoma (21.1%).No significant association was found between the risk of LMC and the location of the brain lesion or total brain volume of brain metastases with risk for LMC.Yet, a history of prior surgical brain lesion resection before SRS was associated with a 6.5 times higher odds (95% CI: 1.45-29.35,pZ0.01) of developing LMC post-radiosurgery.Conclusion: A history of prior surgical resection of brain metastases before SRS was associated with 6.5 times higher odds of LMC, than those who had no prior resections of brain metastases.Adjuvant WBRT may help to reduce the risk of LMC and can be considered in decision-making for patients who may have had brain metastasectomy.

RaySearch Americas Inc. (NY) has introduced a commercial Monte Carlo dose algorithm (RS-MC) for routine clinical use in proton spot scanning. In this report, we provide a validation of this algorithm against phantom measurements and simulations in the GATE software package. We also compared the performance of the RayStation analytical algorithm (RS-PBA) against the RS-MC algorithm. A beam model (G-MC) for a spot scanning gantry at our proton center was implemented in the GATE software package. The model was validated against measurements in a water phantom and was used for benchmarking the RS-MC. Validation of the RS-MC was performed in a water phantom by measuring depth doses and profiles for three spread-out Bragg peak (SOBP) beams with normal incidence, an SOBP with oblique incidence, and an SOBP with a range shifter and large air gap. The RS-MC was also validated against measurements and simulations in heterogeneous phantoms created by placing lung or bone slabs in a water phantom. Lateral dose profiles near the distal end of the beam were measured with a microDiamond detector and compared to the G-MC simulations, RS-MC and RS-PBA. Finally, the RS-MC and RS-PBA were validated against measured dose distributions in an Alderson-Rando (AR) phantom. Measurements were made using Gafchromic film in the AR phantom and compared to doses using the RS-PBA and RS-MC algorithms. For SOBP depth doses in a water phantom, all three algorithms matched the measurements to within  ±3% at all points and a range within 1 mm. The RS-PBA algorithm showed up to a 10% difference in dose at the entrance for the beam with a range shifter and  >30 cm air gap, while the RS-MC and G-MC were always within 3% of the measurement. For an oblique beam incident at 45°, the RS-PBA algorithm showed up to 6% local dose differences and broadening of distal fall-off by 5 mm. Both the RS-MC and G-MC accurately predicted the depth dose to within  ±3% and distal fall-off to within 2 mm. In an anthropomorphic phantom, the gamma index (dose tolerance  =  3%, distance-to-agreement  =  3 mm) was greater than 90% for six out of seven planes using the RS-MC, and three out seven for the RS-PBA. The RS-MC algorithm demonstrated improved dosimetric accuracy over the RS-PBA in the presence of homogenous, heterogeneous and anthropomorphic phantoms. The computation performance of the RS-MC was similar to the RS-PBA algorithm. For complex disease sites like breast, head and neck, and lung cancer, the RS-MC algorithm will provide significantly more accurate treatment planning.

Purpose: Several shortcomings of the current implementation of the analytic anisotropic algorithm (AAA) may lead to dose calculation errors in highly modulated treatments delivered to highly heterogeneous geometries. Here we introduce a set of dosimetric error predictors that can be applied to a clinical treatment plan and patient geometry in order to identify high risk plans. Once a problematic plan is identified, the treatment can be recalculated with more accurate algorithm in order to better assess its viability. Methods: Here we focus on three distinct sources dosimetric error in the AAA algorithm. First, due to a combination of discrepancies in smallfield beam modeling as well as volume averaging effects, dose calculated through small MLC apertures can be underestimated, while that behind small MLC blocks can overestimated. Second, due the rectilinear scaling of the Monte Carlo generated pencil beam kernel, energy is not properly transported through heterogeneities near, but not impeding, the central axis of the beamlet. And third, AAA overestimates dose in regions very low density (< 0.2 g/cm 3 ). We have developed an algorithm to detect the location and magnitude of each scenario within the patient geometry, namely the field‐size index (FSI), the heterogeneous scatter index (HSI), and the lowdensity index (LDI) respectively. Results: Error indices successfully identify deviations between AAA and Monte Carlo dose distributions in simple phantom geometries. Algorithms are currently implemented in the MATLAB computing environment and are able to run on a typical RapidArc head & neck geometry in less than an hour. Conclusion: Because these error indices successfully identify each type of error in contrived cases, with sufficient benchmarking, this method can be developed into a clinical tool that may be able to help estimate AAA dose calculation errors and when it might be advisable to use Monte Carlo calculations.

Purpose: Monte Carlo (MC) models of radiotherapy beams can be used as a comparison benchmark for other dose calculation methods. In any such comparison process, the degree to which an identified deviation represents an actual error will depend upon the accuracy of the benchmark. As part of an ongoing dosimetric study, we have sought to model the standard Varian Clinac 6MV beam as accurately as possible with the BEAMnrc MC code. Methods: In order to insure the reproducibility of our results, the accelerator head geometry was modeled exactly as specified by the manufacturer, with only the electron source parameters and jaw positions varied. Similarly, the widely available Eclipse ' tGolden Beam' t data was used for open field comparisons with a target matching criteria of 1% of local dose or 1 mm distance‐to‐agreement for all depths >= Dmax and field sizes ranging from 3×3 to 40×40 cm2. Except for target bremsstrahlung settings, all other transport parameters were left at their default values. Simulations were run for varied monoenergetic electron energy [5.6:0.05:6.2]MeV, Gaussian intensity distribution FWHM [0.0:0.05:0.25]cm, and beam divergence [0.0:0.2:1.2]°. Results: As has been previously established in the literature, matching was found to be strongly dependent on electron beam energy, intensity FWHM, and choice of bremsstrahlung settings. However, as matching approached the target criteria, results became increasingly sensitive to beam divergence as well. It was also found that when using the default bremsstrahlung settings, accuracy better than ∼2% was unobtainable. Under the specified parameter resolution, matching of all points within 1.4%/1.0mm was achieved when using the NRC bremsstrahlung cross section, the higher termed Koch and Motz bremsstrahlung angular sampling, and electron beam parameters of 5.9MeV, 0.1cm, and 0.8°. Conclusion: Under the listed constraints, significant improvements (e.g. matching ∼ 1%/1mm) in Golden Beam modeling are not likely achievable.

Purpose: To develop a proton beam wheel-modulated, double-scattering (WMDS) apparatus which will produce a robust selection of proton fields for the support of radiobiology research goals at the University of Pennsylvania. Methods and Materials: A passively spread double-scattering design was chosen for its affordability, and wheel modulation was chosen for its established reliability. The proposed beam line apparatus will allow for a wide range of beam configurations due to its modular design. Beam specific modulation wheel, contoured second scatterer, and compensator design will be supported by the NEU code developed at the Harvard Cyclotron Laboratory. Component milling and construction will be carried out at the Roberts Proton Therapy Center (RPTC) where the finished device will be tested and ultimately utilized. An existing 230 MeV IBA cyclotron currently supporting clinical proton treatments at RPTC will supply an energy-selectable pencil beam to the WMDS apparatus. The WMDS apparatus will then passively shape this pencil beam to the desired modulated field. The apparatus will eventually be installed in the research-dedicated vault at RPTC. Results: It is expected that field sizes up to 100×100 cm2. with maximum water penetrations of up to 7 cm, will be obtainable given the available beam energies, apparatus dimensions, and 5 meter throw available at the proposed location. Smaller fields could bring maximum water penetrations of up to 30 cm with the possibility of full Bragg peak modulation. Conclusion: This beam line apparatus is currently under construction at the RPTC and is expected to be ready for testing by May 2010. Presently beam components are being designed to configure the apparatus for a very large, low dose rate, field to study the biological effects of low dose rate proton fields on astronauts. More clinically relevant configurations will eventually be employed for oncological radiobiology studies.

A variant of the popular nonparametric nonuniform intensity normalization (N3) algorithm is proposed for bias field correction. Given the superb performance of N3 and its public availability, it has been the subject of several evaluation studies. These studies have demonstrated the importance of certain parameters associated with the B-spline least-squares fitting. We propose the substitution of a recently developed fast and robust B-spline approximation routine and a modified hierarchical optimization scheme for improved bias field correction over the original N3 algorithm. Similar to the N3 algorithm, we also make the source code, testing, and technical documentation of our contribution, which we denote as "N4ITK," available to the public through the Insight Toolkit of the National Institutes of Health. Performance assessment is demonstrated using simulated data from the publicly available Brainweb database, hyperpolarized (3)He lung image data, and 9.4T postmortem hippocampus data.

The low-aspect ratio, low magnetic field and wide range of plasma beta of NSTX plasmas provide new insight into the origins and effects of magnetic field errors. An extensive array of magnetic sensors has been used to analyse error fields, to measure error-field amplification and to detect resistive wall modes (RWMs) in real time. The measured normalized error-field threshold for the onset of locked modes shows a linear scaling with plasma density, a weak to inverse dependence on toroidal field and a positive scaling with magnetic shear. These results extrapolate to a favourable error-field threshold for ITER. For these low-beta locked-mode plasmas, perturbed equilibrium calculations find that the plasma response must be included to explain the empirically determined optimal correction of NSTX error fields. In high-beta NSTX plasmas exceeding the n = 1 no-wall stability limit where the RWM is stabilized by plasma rotation, active suppression of n = 1 amplified error fields and the correction of recently discovered intrinsic n = 3 error fields have led to sustained high rotation and record durations free of low-frequency core MHD activity. For sustained rotational stabilization of the n = 1 RWM, both the rotation threshold and the magnitude of the amplification are important. At fixed normalized dissipation, kinetic damping models predict rotation thresholds for RWM stabilization to scale nearly linearly with particle orbit frequency. Studies for NSTX find that orbit frequencies computed in general geometry can deviate significantly from those computed in the high-aspect ratio and circular plasma cross-section limit, and these differences can strongly influence the predicted RWM stability. The measured and predicted RWM stability is found to be very sensitive to the E × B rotation profile near the plasma edge, and the measured critical rotation for the RWM is approximately a factor of two higher than predicted by the MARS-F code using the semi-kinetic damping model.

Purpose: To develop a miniature tissue‐equivalent proportional counter (TEPC), timing‐coincidence veto, and pulse‐height analysis system for the purpose of measuring neutron Microdosimetry spectra in a proton beam. Method and Materials: TEPC's were constructed with active volume geometry consisting of a 2.5mm right circular cylinder and employing a 10μm diameter stainless steel wire as the detector anode centered on the axis of an A150 tissue‐equivalent plastic cylinder with 2mm thick wall. Stainless steel field tubes define the active volume which is filled with propane based tissue‐equivalent gas to 168torr simulating a tissue density volume with 2μm diameter. Two fully depleted transmission‐type silicon detectors with diameter of 31.6mm will be operated in timing coincidence with the proportional counter as a charged particle veto system. Detector pulses are digitized in a 60MS/s sampling ADC and the data acquisition software is written in the LabVIEW graphical programming language which acquires and writes pulse waveforms to disk where pulse heights and timing information are extracted for further analysis. Results: A TEPC was tested in a mixed field produced in a proton treatment room with the proton beam incident on a closed tungsten MLC. The timing and energy resolutions for the TEPCs can be estimated from alpha spectra taken with a FWT LET‐1/2 detector attached to the data acquisition system. Timing and lineal energy resolution for the TEPCs are estimated to be 200ns and >15keV/μm, respectively. Conclusion: Preliminary testing shows that the TEPC and silicon detector timing‐coincidence veto system is a viable method for extracting neutron Microdosimetry spectra from the mixed fields present in a proton therapy treatment room. This work was supported by the US Army Medical Research and Materiel Command under Contract Agreement No. DAMD17‐W81XWH‐07‐2‐0121. Opinions, interpretations, conclusions and recommendations are those of the author and are not necessarily endorsed by the US Army.