Assessment of the setup dependence of detector response functions for mega-voltage linear accelerators

Evaluation and Comparison of Dosimetric Characteristics of Semiflex®3D and Microdiamond in Relative Dosimetry under 6 and 15 MV Photon Beams in Small Fields

BACKGROUND

In modern radiotherapy techniques, the frequently small and non-uniformed fields can increase treatment efficiency due to their highly conformal dose distribution. Particular features including lack of Lateral Charge Particle Equilibrium (LCPE) lead to detectors with high resolution since any error in obtained dosimetric data could cause patient mistreatments.

OBJECTIVE

This study aims to evaluate and compare two small detectors (Semiflex^®3D and microdiamond) dosimetric characteristics in small field relative dosimetry.

MATERIAL AND METHODS

In this experimental study, the dosimetric properties of Semiflex^®3D and microdiamond were assessed under 6 and 15 MV photon beams. The linearity and stability of the detector's response and dose rate were measured. Square-field sizes ranging from 0.6×0.6 - 5×5 cm² were used for obtaining percentage depth dose curves (PDDs) and in-plane profiles. The angular and temperature dependence of both detectors' responses were also studied.

RESULTS

The detector response shows good stability, no deviation from linearity, and low dose rate dependence (≤1.6%). PDDs and in-plan profiles of both detectors are in good agreement and no significant difference was observed except for the high dose gradient regions (P-value≤0.017). Both detectors demonstrated low angular dependence (<0.3%) with temperature dependence lower than 1% for both detectors.

CONCLUSION

The results indicate both investigated detectors were well performed in small field relative dosimetry and for measuring penumbra, it is better to use microdiamond detector.

The effect of geometry dependent Chamber Spatial Response Function in small field profile measurements

The effect of Chamber-Spatial Response Function (CSRF) on beam profile measurements has been studied for Standard Ionization Chamber-Radiation Field Analyzer setup. The Chamber-Spatial Response Function is assumed to be Gaussian and parameterized through the projected geometry of the chamber along the measurement axis. CSRF widths was measured by constructing chamber diameter-FWHM correlation for a set of ionization chambers. The results were analyzed through Geant4 simulations. The geometrical parameters for the chamber, used in Geant4 simulation, have been derived from the CT scan images of the chamber. An excellent agreement between measurement and simulation is obtained. Various factors effecting the CSRF, such as chamber width and Compton current are analyzed. The analysis shows that the Compton current has significant role in broadening the CSRF. Further, it is also observed that a spherical chamber geometry provides better and compact CSRF.

Artificial intelligence based deconvolving on megavoltage photon beam profiles for radiotherapy applications

Objective. The aim of this work is an AI based approach to reduce the volume effect of ionization chambers used to measure high energy photon beams in radiotherapy. In particular for profile measurements, the air-filled volume leads to an inaccurate measurement of the penumbra. Approach. The AI-based approach presented in this study was trained with synthetic data intended to cover a wide range of realistic linear accelerator data. The synthetic data was created by randomly generating profiles and convolving them with the lateral response function of a Semiflex 3D ionization chamber. The neuronal network was implemented using the open source tensorflow.keras machine learning framework and a U-Net architecture. The approach was validated on three accelerator types (Varian TrueBeam, Elekta VersaHD, Siemens Artiste) at FF and FFF energies between 6 MV and 18 MV at three measurement depths. For each validation, a Semiflex 3D measurement was compared against a microDiamond measurement, and the AI processed Semiflex 3D measurement was compared against the microDiamond measurement. Main results. The AI approach was validated with dataset containing 306 profiles measured with Semiflex 3D ionization chamber and microDiamond. In 90% of the cases, the AI processed Semiflex 3D dataset agrees with the microDiamond dataset within 0.5 mm/2% gamma criterion. 77% of the AI processed Semiflex 3D measurements show a penumbra difference to the microDiamond of less than 0.5 mm, 99% of less than 1 mm. Significance. This AI approach is the first in the field of dosimetry which uses synthetic training data. Thus, the approach is able to cover a wide range of accelerators and the whole specified field size range of the ionization chamber. The application of the AI approach offers an quality improvement and time saving for measurements in the water phantom, in particular for large field sizes.

The dose response of PTW microDiamond and microSilicon in transverse magnetic field under small field conditions

The aim of the present work is to investigate the behavior of two diode-type detectors (PTW microDiamond 60019 and PTW microSilicon 60023) in transverse magnetic field under small field conditions. A formalism based on TRS 483 has been proposed serving as the framework for the application of these high-resolution detectors under these conditions. Measurements were performed at the National Metrology Institute of Germany (PTB, Braunschweig) using a research clinical linear accelerator facility. Quadratic fields corresponding to equivalent square field sizesSbetween 0.63 and 4.27 cm at the depth of measurement were used. The magnetic field strength was varied up to 1.4 T. Experimental results have been complemented with Monte Carlo simulations up to 1.5 T. Detailed simulations were performed to quantify the small field perturbation effects and the influence of detector components on the dose response. The does response of both detectors decreases by up to 10% at 1.5 T in the largest field size investigated. InS = 0.63 cm, this reduction at 1.5 T is only about half of that observed in field sizesS > 2 cm for both detectors. The results of the Monte Carlo simulations show agreement better than 1% for all investigated conditions. Due to normalization at the machine specific reference field, the resulting small field output correction factors for both detectors in magnetic fieldkQclin,QmsrBare smaller than those in the magnetic field-free case, where correction up to 6.2% at 1.5 T is required for the microSilicon in the smallest field size investigated. The volume-averaging effect of both detectors was shown to be nearly independent of the magnetic field. The influence of the enhanced-density components within the detectors has been identified as the major contributors to their behaviors in magnetic field. Nevertheless, the effect becomes weaker with decreasing field size that may be partially attributed to the deficiency of low energy secondary electrons originated from distant locations in small fields.

Evaluation of a neural network‐based photon beam profile deconvolution method

Purpose

The authors have previously shown the feasibility of using an artificial neural network (ANN) to eliminate the volume average effect (VAE) of scanning ionization chambers (ICs). The purpose of this work was to evaluate the method when applied to beams of different energies (6 and 10 MV) and modalities [flattened (FF) vs unflattened (FFF)], measured with ICs of various sizes.

Methods

The three‐layer ANN extracted data from transverse photon beam profiles using a sliding window, and output deconvolved value corresponding to the location at the center of the window. Beam profiles of seven fields ranging from 2 × 2 to 10 × 10 cm² at four depths (1.5, 5, 10 and 20 cm) were measured with three ICs (CC04, CC13, and FC65‐P) and an EDGE diode detector for 6 MV FF and FFF. Similar data for the 10 MV FF beam was also collected with CC13 and EDGE. The EDGE‐measured profiles were used as reference data to train and test the ANNs. Separate ANNs were trained by using the data of each beam energy and modality. Combined ANNs were also trained by combining data of different beam energies and/or modalities. The ANN's performance was quantified and compared by evaluating the penumbra width difference (PWD) between the deconvolved and reference profiles.

Results

Excellent agreement between the deconvolved and reference profiles was achieved with both separate and combined ANNs for all studied ICs, beam energies, beam modalities, and geometries. After deconvolution, the average PWD decreased from 1–3 mm to under 0.15 mm with separate ANNs and to under 0.20 mm with combined ANN.

Conclusions

The ANN‐based deconvolution method can be effectively applied to beams of different energies and modalities measured with ICs of various sizes. Separate ANNs yielded marginally better results than combined ANNs. An IC‐specific, combined ANN can provide clinically acceptable results as long as the training data includes data of each beam energy and modality.

Application of high field magnetic resonance microimaging in polymer gel dosimetry

Purpose

The purpose of this work was to examine the suitability of VIPAR^nd polymer gel–9.4 T magnetic resonance microimaging system for high spatial resolution dose distribution measurements.

Methods

The VIPAR^nd samples (3 cm in outside diameter and 12 cm in height) were exposed to ionizing radiation by using a linear accelerator (Varian TrueBeam, USA; 6 MV x‐ray beam). In the calibration stage, nine gel dosimeter vials were irradiated in a water phantom homogenously to the doses from 1.5 to 30 Gy in order to obtain R2‒dose relation. In the verification stage, two gel dosimeter vials were irradiated in the half beam penumbra area of 10 × 10 cm radiation field using the amount of monitor units appropriate to deliver 20 Gy at the field center. The gels were imaged on a vertical 9.4 T magnetic resonance (MR) microimaging scanner using single slice and multislice (9 slices) multiecho (90 × 7 ms) sequences at the spatial resolutions of 0.2–0.4 × 0.2–0.4 × 3 mm³ and 0.2–0.4 × 0.2–0.4 × 1 mm³ respectively. The gels were subjected to microimaging during the period of two weeks after irradiation. The reference data consisted of the dose profiles measured using the diode dosimetry, radiochromic film, ionization chamber, and the water phantom system.

Results

The VIPAR^nd‒9.4 T MR microimaging system was characterized by the dose sensitivity of 0.067 ± 0.002 Gy⁻¹ s⁻¹ at day 3 after irradiation. The dose resolution at 10 Gy (at P = 95%) was equal to 0.42 Gy at day 3 after irradiation using a single slice sequence (0.2 × 0.2 × 3 mm³) and 2.0 Gy at day 4 after irradiation using a multislice sequence (0.2 × 0.2 × 1 mm³) for one signal acquisition (measurement time: 15 min). These values were improved by ~1.4‐fold when using four signal acquisitions in the single slice sequence, and by ~2.78‐fold for 12 signal acquisitions in the multislice sequence. Furthermore, decreasing the in‐plane resolution from 0.2 × 0.2 mm² to 0.4 × 0.4 mm² resulted in a dose resolution of 0.3 Gy and 1 Gy at 10 Gy (at P = 95%) for one signal acquisition in the single slice and multislice sequences respectively (measurement time: 7.5 min).

As reveals from the gamma index analysis the dose distributions measured at days 3–4 postirradiation using both VIPAR^nd verification phantoms agree with the data obtained using a silicon diode, assuming 1 mm/5% criterion. A good interphantom reproducibility of the polymer gel dosimetry was proved by monitoring of two phantoms up to 10 days after irradiation. However, the agreement between the dose distributions measured using the diode and polymer gel started to get worse from day 5 after irradiation.

Conclusion

The VIPAR^nd–9.4T MR microimaging system allows to obtain dose resolution of 0.42 Gy at 10 Gy (at P = 95%) for a spatial resolution of 0.2 × 0.2 × 3 mm³ (acquisition time: 15 min). Further studies are required to improve a temporal stability of the gel‐derived dose distribution.

Feasibility of two-dimensional dose distribution deconvolution using convolution neural networks

PURPOSE

The purpose of this study was to investigate the feasibility of two-dimensional (2D) dose distribution deconvolution using convolutional neural networks (CNNs) instead of an analytical approach for an in-house scintillation detector that has a detector-interface artifact in the penumbra region.

METHODS

Datasets of 2D dose distributions were acquired from a medical linear accelerator of Novalis Tx. The datasets comprise two different sizes of square radiation fields and 13 clinical intensity-modulated radiation treatment (IMRT) plans. These datasets were divided into two datasets (training and test) to train and validate the developed network, called PenumbraNet, which is a shallow linear CNN. The PenumbraNet was trained to transform the measured dose distribution [M(x, y)] to calculated distribution [D(x, y)] by the treatment planning system. After training of the PenumbraNet was completed, the performance was evaluated using test data, which were 10 × 10 cm² open field and ten clinical IMRT cases. The corrected dose distribution [C(x, y)] was evaluated against D(x, y) with 2%/2 mm and 3%/3 mm criteria of the gamma index for each field. The M(x, y) and deconvolved dose distribution with the analytically obtained kernel using Wiener filtering [A(x, y)] were also evaluated for comparison. In addition, we compared the performance of the shallow depth of linear PenumbraNet with that of nonlinear PenumbraNet and a deep nonlinear PenumbraNet within the same training epoch.

RESULTS

The mean gamma passing rates were 84.77% and 95.81% with 3%/3 mm gamma criteria for A(x, y) and C(x, y) of the PenumbraNet, respectively. The mean gamma pass rates of nonlinear PenumbraNet and the deep depth of nonlinear PenumbraNet were 96.62%, 93.42% with 3%/3 mm gamma criteria, respectively.

CONCLUSIONS

We demonstrated the feasibility of the PenumbraNets for 2D dose distribution deconvolution. The nonlinear PenumbraNet which has the best performance improved the gamma passing rate by 11.85% from the M(x, y) at 3%/3 mm gamma criteria.

The effect of SSD, Field size, Energy and Detector type for Relative Output Factor measurement in small photon beams as compared with Monte Carlo simulation

Introduction: Small fields photon dosimetry is associated with many problems. Using the right detector for measurement plays a fundamental role. This study investigated the measurement of relative output for small photon fields with different detectors. It was investigated for three-photon beam energies at SSDs of 90, 95, 100 and 110 cm. As a benchmark, the Monte Carlo simulation was done to calculate the relative output of these small photon beams for the dose in water.

Materials and Methods: 6, 10 and 15 MV beams were delivered from a Synergy LINAC equipped with an Agility 160 multileaf collimator (MLC). A CC01 ion chamber, EFD-3G diode, PTW60019 microdiamond, EBT2 radiochromic film, and EDR2 radiographic film were used to measure the relative output of the linac. Measurements were taken in water for the CC01 ion chamber, EFD-3G diode, and the PTW60019. Films were measured in water equivalent RW3 phantom slabs. Measurements were made for 1 × 1, 2 × 2, 3 × 3, 4 × 4, 5 × 5 and a reference field of 10 × 10 cm2. Field sizes were defined at 100cm SSD. Relative output factors were also compared with Monte Carlo (MC) simulation of the LINAC and a water phantom model. The influence of voxel size was also investigated for relative output measurement. Results and Discussion: The relative output factor (ROF) increased with energy for all fields large enough to have lateral electronic equilibrium (LEE). This relation broke down as the field sizes decreased due to the onset of lateral electronic disequilibrium (LED). The high-density detector, PTW60019 gave the highest ROF for the different energies, with the less dense CC01 giving the lowest ROFs.

Conclusion: These are results compared to MC simulation, higher density detectors give higher ROF values. Relative to water, the ROF measured with the air-chamber remained virtually unchanged. The ROFs, as measured in this study showed little variation due to increased SSDs. The effect of voxel size for the Monte Carlo calculations in water does not lead to significant ROF variation over the small fields studied.

Feasibility of photon beam profile deconvolution using a neural network

PURPOSE

Ionization chambers are the detectors of choice for photon beam profile scanning. However, they introduce significant volume averaging effect (VAE) that can artificially broaden the penumbra width by 2-3 mm. The purpose of this study was to examine the feasibility of photon beam profile deconvolution (the elimination of VAE from ionization chamber-measured beam profiles) using a three-layer feedforward neural network.

METHODS

Transverse beam profiles of photon fields between 2 × 2 and 10 × 10 cm² were collected with both a CC13 ionization chamber and an EDGE diode detector on an Elekta Versa HD accelerator. These profiles were divided into three datasets (training, validation and test) to train and test a three-layer feedforward neural network. A sliding window was used to extract input data from the CC13-measured profiles. The neural network produced the deconvolved value at the center of the sliding window. The full deconvolved profile was obtained after the sliding window was moved over the measured profile from end to end. The EDGE-measured beam profiles were used as reference for the training, validation, and test. The number of input neurons, which equals the sliding window width, and the number of hidden neurons were optimized with a parametric sweeping method. A total of 135 neural networks were fully trained with the Levenberg-Marquardt backpropagation algorithm. The one with the best overall performance on the training and validation dataset was selected to test its generalization ability on the test dataset. The agreement between the neural network-deconvolved profiles and the EDGE-measured profiles was evaluated with two metrics: mean squared error (MSE) and penumbra width difference (PWD).

RESULTS

Based on the two-dimensional MSE plots, the optimal combination of sliding window width of 15 and 5 hidden neurons was selected for the final neural network. Excellent agreement was achieved between the neural network-deconvolved profiles and the reference profiles in all three datasets. After deconvolution, the mean PWD reduced from 2.43 ± 0.26, 2.44 ± 0.36, and 2.46 ± 0.29 mm to 0.15 ± 0.15, 0.04 ± 0.03, and 0.14 ± 0.09 mm for the training, validation, and test dataset, respectively.

CONCLUSIONS

We demonstrated the feasibility of photon beam profile deconvolution with a feedforward neural network in this work. The beam profiles deconvolved with a three-layer neural network had excellent agreement with diode-measured profiles.

Experimental determination of the lateral dose response functions of detectors to be applied in the measurement of narrow photon-beam dose profiles

This study aims at the experimental determination of the detector-specific 1D lateral dose response function K(x) and of its associated rotational symmetric counterpart K(r) for a set of high-resolution detectors presently used in narrow-beam photon dosimetry. A combination of slit-beam, radiochromic film, and deconvolution techniques served to accomplish this task for four detectors with diameters of their sensitive volumes ranging from 1 to 2.2 mm. The particular aim of the experiment was to examine the existence of significant negative portions of some of these response functions predicted by a recent Monte-Carlo-simulation (Looe et al 2015 Phys. Med. Biol. 60 6585-607). In a 6 MV photon slit beam formed by the Siemens Artiste collimation system and a 0.5 mm wide slit between 10 cm thick lead blocks serving as the tertiary collimator, the true cross-beam dose profile D(x) at 3 cm depth in a large water phantom was measured with radiochromic film EBT3, and the detector-affected cross-beam signal profiles M(x) were recorded with a silicon diode, a synthetic diamond detector, a miniaturized scintillation detector, and a small ionization chamber. For each detector, the deconvolution of the convolution integral M(x)  =  K(x)  ∗  D(x) served to obtain its specific 1D lateral dose response function K(x), and K(r) was calculated from it. Fourier transformations and back transformations were performed using function approximations by weighted sums of Gaussian functions and their analytical transformation. The 1D lateral dose response functions K(x) of the four types of detectors and their associated rotational symmetric counterparts K(r) were obtained. Significant negative curve portions of K(x) and K(r) were observed in the case of the silicon diode and the diamond detector, confirming the Monte-Carlo-based prediction (Looe et al 2015 Phys. Med. Biol. 60 6585-607). They are typical for the perturbation of the secondary electron field by a detector with enhanced electron density compared with the surrounding water. In the cases of the scintillation detector and the small ionization chamber, the negative curve portions of K(x) practically vanish. It is planned to use the measured functions K(x) and K(r) to deconvolve clinical narrow-beam signal profiles and to correct the output factor values obtained with various high-resolution detectors.

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.

Assessment of a three-dimensional (3D) water scanning system for beam commissioning and measurements on a helical tomotherapy unit

Beam scanning data collected on the tomotherapy linear accelerator using the TomoScanner water scanning system is primarily used to verify the golden beam profiles included in all Helical TomoTherapy treatment planning systems (TOMO TPSs). The user is not allowed to modify the beam profiles/parameters for beam modeling within the TOMO TPSs. The authors report the first feasibility study using the Blue Phantom Helix (BPH) as an alternative to the TomoScanner (TS) system. This work establishes a benchmark dataset using BPH for target commissioning and quality assurance (QA), and quantifies systematic uncertainties between TS and BPH. Reproducibility of scanning with BPH was tested by three experienced physicists taking five sets of measurements over a six‐month period. BPH provides several enhancements over TS, including a 3D scanning arm, which is able to acquire necessary beam‐data with one tank setup, a universal chamber mount, and the OmniPro software, which allows online data collection and analysis. Discrepancies between BPH and TS were estimated by acquiring datasets with each tank. In addition, data measured with BPH and TS was compared to the golden TOMO TPS beam data. The total systematic uncertainty, defined as the combination of scanning system and beam modeling uncertainties, was determined through numerical analysis and tabulated. OmniPro was used for all analysis to eliminate uncertainty due to different data processing algorithms. The setup reproducibility of BPH remained within 0.5 mm/0.5%. Comparing BPH, TS, and Golden TPS for PDDs beyond maximum depth, the total systematic uncertainties were within 1.4 mm/2.1%. Between BPH and TPS golden data, maximum differences in the field width and penumbra of in‐plane profiles were within 0.8 and 1.1 mm, respectively. Furthermore, in cross‐plane profiles, the field width differences increased at depth greater than 10 cm up to 2.5 mm, and maximum penumbra uncertainties were 5.6 mm and 4.6 mm from TS scanning system and TPS modeling, respectively. Use of BPH reduced measurement time by 1–2 hrs per session. The BPH has been assessed as an efficient, reproducible, and accurate scanning system capable of providing a reliable benchmark beam data. With this data, a physicist can utilize the BPH in a clinical setting with an understanding of the scan discrepancy that may be encountered while validating the TPS or during routine machine QA. Without the flexibility of modifying the TPS and without a golden beam dataset from the vendor or a TPS model generated from data collected with the BPH, this represents the best solution for current clinical use of the BPH.

PACS number: 87.56.Fc

Depth dependence of the single chamber response function of the I'mRT MatriXX array in a 6 MV photon beam

One of the factors which influence the spatial resolution of a 2D detector array is the size of the single detector, another the transport of the secondary electrons from the walls into the measuring volume. In this study, the single ion chamber dose response function of an I'mRT MatriXX array was determined by comparison between slit beam dose profiles measured with the array and with EBT2 radiochromic film in a solid water-equivalent phantom at a shallow depth of 0.5cm and at a depth of 5cm beyond the depth dose maximum for a 6 MV photon beam. The dose response functions were obtained using two methods, the best fit method and the deconvolution method. At the shallow depth, a Lorentz function and at 5cm depth a Gaussian function, both with the same FWHM of 7.4mm within limits of uncertainty, were identified as the best suited dose response functions of the 4.5mm diameter single array chamber. These dose response functions were then tested on various dose profiles whose true shape had been determined with EBT2 film and with the IC03 ionization chamber. By convolving these with the Lorentz kernel (at shallow depth) and the Gaussian kernel (at 5cm depth) the signal profiles measured with the I'mRT MatriXX array were closely approximated. Thus, the convolution of TPS-calculated dose profiles with these dose response functions can minimize the differences between calculation and measurement which occur due to the limited spatial resolution of the I'mRT MatriXX detector.

Super-resolution non-parametric deconvolution in modelling the radial response function of a parallel plate ionization chamber

The signal of the dosimetric detector is generally dependent on the shape and size of the sensitive volume of the detector. In order to optimize the performance of the detector and reliability of the output signal the effect of the detector size should be corrected or, at least, taken into account. The response of the detector can be modelled using the convolution theorem that connects the system input (actual dose), output (measured result) and the effect of the detector (response function) by a linear convolution operator. We have developed the super-resolution and non-parametric deconvolution method for determination of the cylinder symmetric ionization chamber radial response function. We have demonstrated that the presented deconvolution method is able to determine the radial response for the Roos parallel plate ionization chamber with a better than 0.5 mm correspondence with the physical measures of the chamber. In addition, the performance of the method was proved by the excellent agreement between the output factors of the stereotactic conical collimators (4-20 mm diameter) measured by the Roos chamber, where the detector size is larger than the measured field, and the reference detector (diode). The presented deconvolution method has a potential in providing reference data for more accurate physical models of the ionization chamber as well as for improving and enhancing the performance of the detectors in specific dosimetric problems.

Multisource modeling of flattening filter free (FFF) beam and the optimization of model parameters

PURPOSE

With the introduction of flattening filter free (FFF) linear accelerators to radiation oncology, new analytical source models for a FFF beam applicable to current treatment planning systems is needed. In this work, a multisource model for the FFF beam and the optimization of involved model parameters were designed.

METHODS

The model is based on a previous three source model proposed by Yang et al. ["A three-source model for the calculation of head scatter factors," Med. Phys. 29, 2024-2033 (2002)]. An off axis ratio (OAR) of photon fluence was introduced to the primary source term to generate cone shaped profiles. The parameters of the source model were determined from measured head scatter factors using a line search optimization technique. The OAR of the photon fluence was determined from a measured dose profile of a 40 x 40 cm2 field size with the same optimization technique, but a new method to acquire gradient terms for OARs was developed to enhance the speed of the optimization process. The improved model was validated with measured dose profiles from 3 x 3 to 40 x 40 cm2 field sizes at 6 and 10 MV from a TrueBeam STx linear accelerator. Furthermore, planar dose distributions for clinically used radiation fields were also calculated and compared to measurements using a 2D array detector using the gamma index method.

RESULTS

All dose values for the calculated profiles agreed with the measured dose profiles within 0.5% at 6 and 10 MV beams, except for some low dose regions for larger field sizes. A slight overestimation was seen in the lower penumbra region near the field edge for the large field sizes by 1%-4%. The planar dose calculations showed comparable passing rates (> 98%) when the criterion of the gamma index method was selected to be 3%/3 mm.

CONCLUSIONS

The developed source model showed good agreements between measured and calculated dose distributions. The model is easily applicable to any other linear accelerator using FFF beams as the required data include only the measured PDD, dose profiles, and output factors for various field sizes, which are easily acquired during conventional beam commissioning process.