Commissioning an Exradin W2 plastic scintillation detector for clinical use in small radiation fields.

PURPOSE: The purpose of this work is to evaluate the Standard Imaging Exradin W2 plastic scintillation detector (W2) for use in the types of fields used for stereotactic radiosurgery. METHODS: Prior to testing the W2 in small fields, the W2 was evaluated in standard large field conditions to ensure good detector performance. These tests included energy dependence, short-term repeatability, dose-response linearity, angular dependence, temperature dependence, and dose rate dependence. Next, scan settings and calibration of the W2 were optimized to ensure high quality data acquisition. Profiles of small fields shaped by cones and multi-leaf collimator (MLCs) were measured using the W2 and IBA RAZOR diode in a scanning water tank. Output factors for cones (4-17.5 mm) and MLC fields (1, 2, 3 cm) were acquired with both detectors. Finally, the dose at isocenter for seven radiosurgery plans was measured with the W2 detector. RESULTS: W2 exhibited acceptable warm-up behavior, short-term reproducibility, axial angular dependence, dose-rate linearity, and dose linearity. The detector exhibits a dependence upon energy, polar angle, and temperature. Scanning measurements taken with the W2 and RAZOR were in good agreement, with full-width half-maximum and penumbra widths agreeing to within 0.1 mm. The output factors measured by the W2 and RAZOR exhibited a maximum difference of 1.8%. For the seven point-dose measurements of radiosurgery plans, the W2 agreed well with our treatment planning system with a maximum deviation of 2.2%. The Cerenkov light ratio calibration method did not significantly impact the measurement of relative profiles, output factors, or point dose measurements. CONCLUSION: The W2 demonstrated dosimetric characteristics that are suitable for radiosurgery field measurements. The detector agreed well with the RAZOR diode for output factors and scanned profiles and showed good agreement with the treatment planning system in measurements of clinical treatment plans.

Diagnosing atmospheric communication of a sealed monitor chamber.

Daily output variations of up to ±2% were observed for a protracted time on a Varian TrueBeam® STx; these output variations were hypothesized to be the result of atmospheric communication of the sealed monitor chamber. Daily changes in output relative to baseline, measured with an ionization chamber array (DQA3) and the amorphous silicon flat panel detector (IDU) on the TrueBeam®, were compared with daily temperature-pressure corrections (PTP ) determined from sensors within the DQA3. Output measurements were performed using a Farmer® ionization chamber over a 5-hour period, during which there was controlled variation in the monitor chamber temperature. The root mean square difference between percentage output change from baseline measured with the DQA3 and IDU was 0.50% over all measurements. Over a 7-month retrospective review of daily changes in output and PTP , weak correlation (R2  = 0.30) was observed between output and PTP for the first 5 months; for the final 2 months, daily output changes were linearly correlated with changes in PTP , with a slope of 0.84 (R2  = 0.89). Ionization measurements corrected for ambient temperature and pressure during controlled heating and cooling of the monitor chamber differed from expected values for a sealed monitor chamber by up to 4.6%, but were consistent with expectation for an air-communicating monitor chamber within uncertainty (1.3%, k = 2). Following replacement of the depressurized monitor chamber, there has been no correlation between daily percentage change in output and PTP (R2  = 0.09). The utility of control charts is demonstrated for earlier identification of changes in the sensitivity of a sealed monitor chamber.

Radiation treatment planning and delivery strategies for a pregnant brain tumor patient.

The management of a pregnant patient in radiation oncology is an infrequent event requiring careful consideration by both the physician and physicist. The aim of this manuscript was to highlight treatment planning techniques and detail measurements of fetal dose for a pregnant patient recently requiring treatment for a brain cancer. A 27-year-old woman was treated during gestational weeks 19-25 for a resected grade 3 astrocytoma to 50.4 Gy in 28 fractions, followed by an additional 9 Gy boost in five fractions. Four potential plans were developed for the patient: a 6 MV 3D-conformal treatment plan with enhanced dynamic wedges, a 6 MV step-and-shoot (SnS) intensity-modulated radiation therapy (IMRT) plan, an unflattened 6 MV SnS IMRT plan, and an Accuray TomoTherapy HDA helical IMRT treatment plan. All treatment plans used strategies to reduce peripheral dose. Fetal dose was estimated for each treatment plan using available literature references, and measurements were made using thermoluminescent dosimeters (TLDs) and an ionization chamber with an anthropomorphic phantom. TLD measurements from a full-course radiation delivery ranged from 1.0 to 1.6 cGy for the 3D-conformal treatment plan, from 1.0 to 1.5 cGy for the 6 MV SnS IMRT plan, from 0.6 to 1.0 cGy for the unflattened 6 MV SnS IMRT plan, and from 1.9 to 2.6 cGy for the TomoTherapy treatment plan. The unflattened 6 MV SnS IMRT treatment plan was selected for treatment for this particular patient, though the fetal doses from all treatment plans were deemed acceptable. The cumulative dose to the patient's unshielded fetus is estimated to be 1.0 cGy at most. The planning technique and distance between the treatment target and fetus both contributed to this relatively low fetal dose. Relevant treatment planning strategies and treatment delivery considerations are discussed to aid radiation oncologists and medical physicists in the management of pregnant patients.

Comparison between proton boron fusion therapy (PBFT) and boron neutron capture therapy (BNCT): a monte carlo study.

The aim of this study is to compare between proton boron fusion therapy (PBFT) and boron neutron capture therapy (BNCT) and to analyze dose escalation using a Monte Carlo simulation. We simulated a proton beam passing through the water with a boron uptake region (BUR) in MCNPX. To estimate the interaction between neutrons/protons and borons by the alpha particle, the simulation yielded with a variation of the center of the BUR location and proton energies. The variation and influence about the alpha particle were observed from the percent depth dose (PDD) and cross-plane dose profile of both the neutron and proton beams. The peak value of the maximum dose level when the boron particle was accurately labeled at the region was 192.4% among the energies. In all, we confirmed that prompt gamma rays of 478 keV and 719 keV were generated by the nuclear reactions in PBFT and BNCT, respectively. We validated the dramatic effectiveness of the alpha particle, especially in PBFT. The utility of PBFT was verified using the simulation and it has a potential for application in radiotherapy.

Efficient independent planar dose calculation for FFF IMRT QA with a bivariate Gaussian source model.

The aim of this study is to perform a direct comparison of the source model for photon beams with and without flattening filter (FF) and to develop an efficient independent algorithm for planar dose calculation for FF-free (FFF) intensity-modulated radiotherapy (IMRT) quality assurance (QA). The source model consisted of a point source modeling the primary photons and extrafocal bivariate Gaussian functions modeling the head scatter, monitor chamber backscatter, and collimator exchange effect. The model parameters were obtained by minimizing the difference between the calculated and measured in-air output factors (Sc ). The fluence of IMRT beams was calculated from the source model using a backprojection and integration method. The off-axis ratio in FFF beams were modeled with a fourth degree polynomial. An analytical kernel consisting of the sum of three Gaussian functions was used to describe the dose deposition process. A convolution-based method was used to account for the ionization chamber volume averaging effect when commissioning the algorithm. The algorithm was validated by comparing the calculated planar dose distributions of FFF head-and-neck IMRT plans with measurements performed with a 2D diode array. Good agreement between the measured and calculated Sc was achieved for both FF beams (<0.25%) and FFF beams (<0.10%). The relative contribution of the head-scattered photons reduced by 34.7% for 6 MV and 49.3% for 10 MV due to the removal of the FF. Superior agreement between the calculated and measured dose distribution was also achieved for FFF IMRT. In the gamma comparison with a 2%/2 mm criterion, the average passing rate was 96.2 ± 1.9% for 6 MV FFF and 95.5 ± 2.6% for 10 MV FFF. The efficient independent planar dose calculation algorithm is easy to implement and can be valuable in FFF IMRT QA.

Technical Note: Impact of the geometry dependence of the ion chamber detector response function on a convolution-based method to address the volume averaging effect.

PURPOSE: To investigate the geometry dependence of the detector response function (DRF) of three commonly used scanning ionization chambers and its impact on a convolution-based method to address the volume averaging effect (VAE). METHODS: A convolution-based approach has been proposed recently to address the ionization chamber VAE. It simulates the VAE in the treatment planning system (TPS) by iteratively convolving the calculated beam profiles with the DRF while optimizing the beam model. Since the convolved and the measured profiles are subject to the same VAE, the calculated profiles match the implicit "real" ones when the optimization converges. Three DRFs (Gaussian, Lorentzian, and parabolic function) were used for three ionization chambers (CC04, CC13, and SNC125c) in this study. Geometry dependent/independent DRFs were obtained by minimizing the difference between the ionization chamber-measured profiles and the diode-measured profiles convolved with the DRFs. These DRFs were used to obtain eighteen beam models for a commercial TPS. Accuracy of the beam models were evaluated by assessing the 20%-80% penumbra width difference (PWD) between the computed and diode-measured beam profiles. RESULTS: The convolution-based approach was found to be effective for all three ionization chambers with significant improvement for all beam models. Up to 17% geometry dependence of the three DRFs was observed for the studied ionization chambers. With geometry dependent DRFs, the PWD was within 0.80 mm for the parabolic function and CC04 combination and within 0.50 mm for other combinations; with geometry independent DRFs, the PWD was within 1.00 mm for all cases. When using the Gaussian function as the DRF, accounting for geometry dependence led to marginal improvement (PWD < 0.20 mm) for CC04; the improvement ranged from 0.38 to 0.65 mm for CC13; for SNC125c, the improvement was slightly above 0.50 mm. CONCLUSIONS: Although all three DRFs were found adequate to represent the response of the studied ionization chambers, the Gaussian function was favored due to its superior overall performance. The geometry dependence of the DRFs can be significant for clinical applications involving small fields such as stereotactic radiotherapy.

Parameterization of photon beam dosimetry for a linear accelerator.

PURPOSE: In radiation therapy, accurate data acquisition of photon beam dosimetric quantities is important for (1) beam modeling data input into a treatment planning system (TPS), (2) comparing measured and TPS modeled data, (3) the quality assurance process of a linear accelerator's (Linac) beam characteristics, (4) the establishment of a standard data set for comparison with other data, etcetera. Parameterization of the photon beam dosimetry creates a data set that is portable and easy to implement for different applications such as those previously mentioned. The aim of this study is to develop methods to parameterize photon beam dosimetric quantities, including percentage depth doses (PDDs), profiles, and total scatter output factors (S(cp)). METHODS: S(cp), PDDs, and profiles for different field sizes, depths, and energies were measured for a Linac using a cylindrical 3D water scanning system. All data were smoothed for the analysis and profile data were also centered, symmetrized, and geometrically scaled. The S(cp) data were analyzed using an exponential function. The inverse square factor was removed from the PDD data before modeling and the data were subsequently analyzed using exponential functions. For profile modeling, one halfside of the profile was divided into three regions described by exponential, sigmoid, and Gaussian equations. All of the analytical functions are field size, energy, depth, and, in the case of profiles, scan direction specific. The model's parameters were determined using the minimal amount of measured data necessary. The model's accuracy was evaluated via the calculation of absolute differences between the measured (processed) and calculated data in low gradient regions and distance-to-agreement analysis in high gradient regions. Finally, the results of dosimetric quantities obtained by the fitted models for a different machine were also assessed. RESULTS: All of the differences in the PDDs' buildup and the profiles' penumbra regions were less than 2 and 0.5 mm, respectively. The differences in the low gradient regions were 0.20% ± 0.20% (<1% for all) and 0.50% ± 0.35% (<1% for all) for PDDs and profiles, respectively. For S(cp) data, all of the absolute differences were less than 0.5%. CONCLUSIONS: This novel analytical model with minimum measurement requirements was proved to accurately calculate PDDs, profiles, and S(cp) for different field sizes, depths, and energies.

A novel convolution-based approach to address ionization chamber volume averaging effect in model-based treatment planning systems.

The ionization chamber volume averaging effect is a well-known issue without an elegant solution. The purpose of this study is to propose a novel convolution-based approach to address the volume averaging effect in model-based treatment planning systems (TPSs). Ionization chamber-measured beam profiles can be regarded as the convolution between the detector response function and the implicit real profiles. Existing approaches address the issue by trying to remove the volume averaging effect from the measurement. In contrast, our proposed method imports the measured profiles directly into the TPS and addresses the problem by reoptimizing pertinent parameters of the TPS beam model. In the iterative beam modeling process, the TPS-calculated beam profiles are convolved with the same detector response function. Beam model parameters responsible for the penumbra are optimized to drive the convolved profiles to match the measured profiles. Since the convolved and the measured profiles are subject to identical volume averaging effect, the calculated profiles match the real profiles when the optimization converges. The method was applied to reoptimize a CC13 beam model commissioned with profiles measured with a standard ionization chamber (Scanditronix Wellhofer, Bartlett, TN). The reoptimized beam model was validated by comparing the TPS-calculated profiles with diode-measured profiles. Its performance in intensity-modulated radiation therapy (IMRT) quality assurance (QA) for ten head-and-neck patients was compared with the CC13 beam model and a clinical beam model (manually optimized, clinically proven) using standard Gamma comparisons. The beam profiles calculated with the reoptimized beam model showed excellent agreement with diode measurement at all measured geometries. Performance of the reoptimized beam model was comparable with that of the clinical beam model in IMRT QA. The average passing rates using the reoptimized beam model increased substantially from 92.1% to 99.3% with 3%/3 mm and from 79.2% to 95.2% with 2%/2 mm when compared with the CC13 beam model. These results show the effectiveness of the proposed method. Less inter-user variability can be expected of the final beam model. It is also found that the method can be easily integrated into model-based TPS.