A feasibility study for in vivo treatment verification of IMRT using Monte Carlo dose calculation and deep learning-based modelling of EPID detector response

Background

This paper describes the development of a predicted electronic portal imaging device (EPID) transmission image (TI) using Monte Carlo (MC) and deep learning (DL). The measured and predicted TI were compared for two-dimensional in vivo radiotherapy treatment verification.

Methods

The plan CT was pre-processed and combined with solid water and then imported into PRIMO. The MC method was used to calculate the dose distribution of the combined CT. The U-net neural network-based deep learning model was trained to predict EPID TI based on the dose distribution of solid water calculated by PRIMO. The predicted TI was compared with the measured TI for two-dimensional in vivo treatment verification.

Results

The EPID TI of 1500 IMRT fields were acquired, among which 1200, 150, and 150 fields were used as the training set, the validation set, and the test set, respectively. A comparison of the predicted and measured TI was carried out using global gamma analyses of 3%/3 mm and 2%/2 mm (5% threshold) to validate the model's accuracy. The gamma pass rates were greater than 96.7% and 92.3%, and the mean gamma values were 0.21 and 0.32, respectively.

Conclusions

Our method facilitates the modelling process more easily and increases the calculation accuracy when using the MC algorithm to simulate the EPID response, and has potential to be used for in vivo treatment verification in the clinic.

A method for in vivo treatment verification of IMRT and VMAT based on electronic portal imaging device

Background

Intensity-modulated radiation therapy (IMRT) and volume-modulated arc therapy (VMAT) are rather complex treatment techniques and require patient-specific quality assurance procedures. Electronic portal imaging devices (EPID) are increasingly used in the verification of radiation therapy (RT). This work aims to develop a novel model to predict the EPID transmission image (TI) with fluence maps from the RT plan. The predicted TI is compared with the measured TI for in vivo treatment verification.

Methods

The fluence map was extracted from the RT plan and corrections of penumbra, response, global field output, attenuation, and scatter were applied before the TI was calculated. The parameters used in the model were calculated separately for central axis and off-axis points using a series of EPID measurement data. Our model was evaluated using a CIRS thorax phantom and 20 clinical plans (10 IMRT and 10 VMAT) optimized for head and neck, breast, and rectum treatments.

Results

Comparisons of the predicted and measured images were carried out using a global gamma analysis of 3%/2 mm (10% threshold) to validate the accuracy of the model. The gamma pass rates for IMRT and VMAT were greater than 97.2% and 94.5% at 3%/2 mm, respectively.

Conclusion

We have developed an accurate and straightforward EPID-based quality assurance model that can potentially be used for in vivo treatment verification of the IMRT and VMAT delivery.

Intrinsic detector sensitivity analysis as a tool to characterize ArcCHECK and EPID sensitivity to variations in delivery for lung SBRT VMAT plans

PURPOSE

To investigate intrinsic sensitivity of an electronic portal imaging device (EPID) and the ArcCHECK detector and to use this in assessing their performance in detecting delivery variations for lung SBRT VMAT. The effect of detector spatial resolution and dose matrix interpolation on the gamma pass rate was also considered.

MATERIALS AND METHODS

Fifteen patients' lung SBRT VMAT plans were used. Delivery variations (errors) were introduced by modifying collimator angles, multi-leaf collimator (MLC) field sizes and MLC field shifts by ±5, ±2, and ±1 degrees or mm (investigating 103 plans in total). EPID and ArcCHECK measured signals with introduced variations were compared to measured signals without variations (baseline), using OmniPro-I'mRT software and gamma criteria of 3%/3 mm, 2%/2 mm, 2%/1 mm, and 1%/1 mm, to test each system's basic performance. The measurement sampling resolution for each was also changed to 1 mm and results compared to those with the default detector system resolution.

RESULTS

Intrinsic detector sensitivity analysis, that is, comparing measurement to baseline measurement, rather than measurement to plan, demonstrated the intrinsic constraints of each detector and indicated the limiting performance that users might expect. Changes in the gamma pass rates for ArcCHECK, for a given introduced error, were affected only by dose difference (DD %) criteria. However, the EPID showed only slight changes when changing DD%, but greater effects when changing distance-to-agreement criteria. This is pertinent for lung SBRT where the minimum dose to the target will drop dramatically with geometric errors. Detector resolution and dose matrix interpolation have an impact on the gamma results for these SBRT plans and can lead to false positives or negatives in error detection if not understood.

CONCLUSION

The intrinsic sensitivity approach may help in the selection of more meaningful gamma criteria and the choice of optimal QA device for site-specific dose verification.

4D in vivo dose verification for real-time tumor tracking treatments using EPID dosimetry

The use of sophisticated techniques such as gating and tracking treatments requires additional quality assurance to mitigate increased patient risks. To address this need, we have developed and validated an in vivo method of dose delivery verification for real-time aperture tracking techniques, using an electronic portal imaging device (EPID)-based, on-treatment patient dose reconstruction and a dynamic anthropomorphic phantom. Using 4DCT scan of the phantom, ten individual treatment plans were created, 1 for each of the 10 separate phases of the respiratory cycle. The 10 MLC apertures were combined into a single dynamic intensity-modulated radiation therapy (IMRT) plan that tracked the tumor motion. The tumor motion and linac delivery were synchronized using an RPM system (Varian Medical Systems) in gating mode with a custom breathing trace. On-treatment EPID frames were captured using a data-acquisition computer with a dedicated frame-grabber. Our in-house EPID-based in vivo dose reconstruction model was modified to reconstruct the 4D accumulated dose distribution for a dynamic MLC (DMLC) tracking plan using the 10-phase 4DCT dataset. Dose estimation accuracy was assessed for the DMLC tracking plan and a single-phase (50% phase) static tumor plan, represented a static field test to verify baseline accuracy. The 3%/3 mm chi-comparison between the EPID-based dose reconstruction for the static tumor delivery and the TPS dose calculation for the static plan resulted in 100% pass rate for planning target volume (PTV) voxels while the mean percentage dose difference was 0.6%. Comparing the EPID-based dose reconstruction for the DMLC tracking to the TPS calculation for the static plan gave a 3%/3 mm chi pass rate of 99.3% for PTV voxels and a mean percentage dose difference of 1.1%. While further work is required to assess the accuracy of this approach in more clinically relevant situations, we have established clinical feasibility and baseline accuracy of using the transmission EPID-based, in vivo patient dose verification for MLC-tracking treatments.

Evaluating the sensitivity of Halcyon's automatic transit image acquisition for treatment error detection: A phantom study using static IMRT

PURPOSE

The Varian Halcyon™ electronic portal imaging detector is always in-line with the beam and automatically acquires transit images for every patient with full-field coverage. These images could be used for "every patient, every monitor unit" quality assurance (QA) and eventually adaptive radiotherapy. This study evaluated the imager's sensitivity to potential clinical errors and day-to-day variations from clinical exit images.

METHODS

Open and modulated fields were delivered for each potential error. To evaluate output changes, monitor units were scaled by 2%-10% and delivered to solid water slabs and a homogeneous CIRS phantom. To mimic weight changes, 0.5-5.0 cm of buildup was added to the solid water. To evaluate positioning changes, a homogeneous and heterogeneous CIRS phantom were shifted 2-10 cm and 0.2-1.5 cm, respectively. For each test, mean relative differences (MRDs) and standard deviations in the pixel-difference histograms (σ_RD ) between test and baseline images were calculated. Lateral shift magnitudes were calculated using cross-correlation and edge-detection filtration. To assess patient variations, MRD and σ_RD were calculated from six prostate patients' daily exit images and compared between fractions with and without gas present.

RESULTS

MRDs responded linearly to output and buildup changes with a standard deviation of 0.3%, implying a 1% output change and 0.2 cm changes in buildup could be detected with 2.5σ confidence. Shifting the homogenous phantom laterally resulted in detectable MRD and σ_RD changes, and the cross-correlation function calculated the shift to within 0.5 mm for the heterogeneous phantom. MRD and σ_RD values were significantly associated with the presence of gas for five of the six patients.

CONCLUSIONS

Rapid analyses of automatically acquired Halcyon™ exit images could detect mid-treatment changes with high sensitivity, though appropriate thresholds will need to be set. This study presents the first steps toward developing effortless image evaluation for all aspects of every patient's treatment.

A method for evaluating treatment quality using in vivo EPID dosimetry and statistical process control in radiation therapy

Purpose Due to increasing complexity, modern radiotherapy techniques require comprehensive quality assurance (QA) programmes, that to date generally focus on the pre-treatment stage. The purpose of this paper is to provide a method for an individual patient treatment QA evaluation and identification of a "quality gap" for continuous quality improvement. Design/methodology/approach A statistical process control (SPC) was applied to evaluate treatment delivery using in vivo electronic portal imaging device (EPID) dosimetry. A moving range control chart was constructed to monitor the individual patient treatment performance based on a control limit generated from initial data of 90 intensity-modulated radiotherapy (IMRT) and ten volumetric-modulated arc therapy (VMAT) patient deliveries. A process capability index was used to evaluate the continuing treatment quality based on three quality classes: treatment type-specific, treatment linac-specific, and body site-specific. Findings The determined control limits were 62.5 and 70.0 per cent of the χ pass-rate for IMRT and VMAT deliveries, respectively. In total, 14 patients were selected for a pilot study the results of which showed that about 1 per cent of all treatments contained errors relating to unexpected anatomical changes between treatment fractions. Both rectum and pelvis cancer treatments demonstrated process capability indices were less than 1, indicating the potential for quality improvement and hence may benefit from further assessment. Research limitations/implications The study relied on the application of in vivo EPID dosimetry for patients treated at the specific centre. Sampling patients for generating the control limits were limited to 100 patients. Whilst the quantitative results are specific to the clinical techniques and equipment used, the described method is generally applicable to IMRT and VMAT treatment QA. Whilst more work is required to determine the level of clinical significance, the authors have demonstrated the capability of the method for both treatment specific QA and continuing quality improvement. Practical implications The proposed method is a valuable tool for assessing the accuracy of treatment delivery whilst also improving treatment quality and patient safety. Originality/value Assessing in vivo EPID dosimetry with SPC can be used to improve the quality of radiation treatment for cancer patients.

A Swiss cheese error detection method for real-time EPID-based quality assurance and error prevention

PURPOSE

To develop a robust and efficient process that detects relevant dose errors (dose errors of ≥5%) in external beam radiation therapy and directly indicates the origin of the error. The process is illustrated in the context of electronic portal imaging device (EPID)-based angle-resolved volumetric-modulated arc therapy (VMAT) quality assurance (QA), particularly as would be implemented in a real-time monitoring program.

METHODS

A Swiss cheese error detection (SCED) method was created as a paradigm for a cine EPID-based during-treatment QA. For VMAT, the method compares a treatment plan-based reference set of EPID images with images acquired over each 2° gantry angle interval. The process utilizes a sequence of independent consecutively executed error detection tests: an aperture check that verifies in-field radiation delivery and ensures no out-of-field radiation; output normalization checks at two different stages; global image alignment check to examine if rotation, scaling, and translation are within tolerances; pixel intensity check containing the standard gamma evaluation (3%, 3 mm) and pixel intensity deviation checks including and excluding high dose gradient regions. Tolerances for each check were determined. To test the SCED method, 12 different types of errors were selected to modify the original plan. A series of angle-resolved predicted EPID images were artificially generated for each test case, resulting in a sequence of precalculated frames for each modified treatment plan. The SCED method was applied multiple times for each test case to assess the ability to detect introduced plan variations. To compare the performance of the SCED process with that of a standard gamma analysis, both error detection methods were applied to the generated test cases with realistic noise variations.

RESULTS

Averaged over ten test runs, 95.1% of all plan variations that resulted in relevant patient dose errors were detected within 2° and 100% within 14° (<4% of patient dose delivery). Including cases that led to slightly modified but clinically equivalent plans, 89.1% were detected by the SCED method within 2°. Based on the type of check that detected the error, determination of error sources was achieved. With noise ranging from no random noise to four times the established noise value, the averaged relevant dose error detection rate of the SCED method was between 94.0% and 95.8% and that of gamma between 82.8% and 89.8%.

CONCLUSIONS

An EPID-frame-based error detection process for VMAT deliveries was successfully designed and tested via simulations. The SCED method was inspected for robustness with realistic noise variations, demonstrating that it has the potential to detect a large majority of relevant dose errors. Compared to a typical (3%, 3 mm) gamma analysis, the SCED method produced a higher detection rate for all introduced dose errors, identified errors in an earlier stage, displayed a higher robustness to noise variations, and indicated the error source.

A model-based 3D patient-specific pre-treatment QA method for VMAT using the EPID

This study reports the development and validation of a model-based, 3D patient dose reconstruction method for pre-treatment quality assurance using EPID images. The method is also investigated for sensitivity to potential MLC delivery errors. Each cine-mode EPID image acquired during plan delivery was processed using a previously developed back-projection dose reconstruction model providing a 3D dose estimate on the CT simulation data. Validation was carried out using 24 SBRT-VMAT patient plans by comparing: (1) ion chamber point dose measurements in a solid water phantom, (2) the treatment planning system (TPS) predicted 3D dose to the EPID reconstructed 3D dose in a solid water phantom, and (3) the TPS predicted 3D dose to the EPID and our forward predicted reconstructed 3D dose in the patient (CT data). AAA and AcurosXB were used for TPS predictions. Dose distributions were compared using 3%/3 mm (95% tolerance) and 2%/2 mm (90% tolerance) γ-tests in the planning target volume (PTV) and 20% dose volumes. The average percentage point dose differences between the ion chamber and the EPID, AcurosXB, and AAA were 0.73  ±  1.25%, 0.38  ±  0.96% and 1.06  ±  1.34% respectively. For the patient (CT) dose comparisons, seven (3%/3 mm) and nine (2%/2 mm) plans failed the EPID versus AAA. All plans passed the EPID versus Acuros XB and the EPID versus forward model γ-comparisons. Four types of MLC sensitive errors (opening, shifting, stuck, and retracting), of varying magnitude (0.2, 0.5, 1.0, 2.0 mm), were introduced into six different SBRT-VMAT plans. γ-comparisons of the erroneous EPID dose and original predicted dose were carried out using the same criteria as above. For all plans, the sensitivity testing using a 3%/3 mm γ-test in the PTV successfully determined MLC errors on the order of 1.0 mm, except for the single leaf retraction-type error. A 2%/2 mm criteria produced similar results with two more additional detected errors.

EPID-based dosimetry to verify IMRT planar dose distribution for the aS1200 EPID and FFF beams

We proposed to perform a basic dosimetry commissioning on a new imager system, the Varian aS1200 electronic portal imaging device (EPID) and TrueBeam 2.0 linear accelerator for flattened (FF) and flattening filter‐free (FFF) beams, then to develop an image‐based quality assurance (QA) model for verification of the system delivery accuracy for intensity‐modulated radiation therapy (IMRT) treatments. For dosimetry testing, linearity of dose response with MU, imager lag, and effectiveness of backscatter shielding were investigated. Then, an image‐based model was developed to convert images to planar dose onto a virtual water phantom. The model parameters were identified using energy fluence of the Acuros treatment planning system (TPS) and, reference dose profiles and output factors measured at depths of 5, 10, 15, and 20 cm in water phantom for square fields. To validate the model, its calculated dose was compared to measured dose from MapCHECK 2 diode arrays for 36 IMRT fields at 10 cm depth delivered with 6X, 6XFFF, 10X, and 10XFFF energies. An in‐house gamma function was used to compare planar doses pixel‐by‐pixel. Finally, the method was applied to the same IMRT fields to verify their pretreatment delivery dose compared with Eclipse TPS dose. For the EPID commissioning, dose linearity was within 0.4% above 5 MU and ∼1% above 2 MU, measured lag was smaller than the previous EPIDs, and profile symmetry was improved. The model was validated with mean gamma pass rates (standard deviation) of 99.0% (0.4%), 99.5% (0.6%), 99.3% (0.4%), and 98.0% (0.8%) at 3%/3 mm for respectively 6X, 6XFFF, 10X, and 10XFFF beams. Using the same comparison criteria, the beam deliveries were verified with mean pass rates of 100% (0.0%), 99.6% (0.3%), 99.9% (0.1%), and 98.7% (1.4%). Improvements were observed in dosimetric response of the aS1200 imager compared to previous EPID models, and the model was successfully developed for the new system and delivery energies of 6 and 10 MV, FF, and FFF modes.

PACS number(s): 87.53.Oq, 87.53.Xd

Frame average optimization of cine-mode EPID images used for routine clinical in vivo patient dose verification of VMAT deliveries

PURPOSE

The in vivo 3D dose delivered to a patient during volumetric modulated arc therapy (VMAT) delivery can be calculated using electronic portal imaging device (EPID) images. These images must be acquired in cine-mode (i.e., "movie" mode) in order to capture the time-dependent delivery information. The angle subtended by each cine-mode EPID image during an arc can be changed via the frame averaging number selected within the image acquisition software. A large frame average number will decrease the EPID's angular resolution and will result in a decrease in the accuracy of the dose information contained within each image. Alternatively, less EPID images acquired per delivery will decrease the overall 3D patient dose calculation time, which is appealing for large-scale clinical implementation. Therefore, the purpose of this study was to determine the optimal frame average value per EPID image, defined as the highest frame averaging that can be used without an appreciable loss in 3D dose reconstruction accuracy for VMAT treatments.

METHODS

Six different VMAT plans and six different SBRT-VMAT plans were delivered to an anthropomorphic phantom. Delivery was carried out on a Varian 2300ix model linear accelerator (Linac) equipped with an aS1000 EPID running at a frame acquisition rate of 7.5 Hz. An additional PC was set up at the Linac console area, equipped with specialized frame-grabber hardware and software packages allowing continuous acquisition of all EPID frames during delivery. Frames were averaged into "frame-averaged" EPID images using matlab. Each frame-averaged data set was used to calculate the in vivo dose to the patient and then compared to the single EPID frame in vivo dose calculation (the single frame calculation represents the highest possible angular resolution per EPID image). A mean percentage dose difference of low dose (<20% prescription dose) and high dose regions (>80% prescription dose) was calculated for each frame averaged scenario for each plan. The authors defined their unacceptable loss of accuracy as no more than a ±1% mean dose difference in the high dose region. Optimal frame average numbers were then determined as a function of the Linac's average gantry speed and the dose per fraction.

RESULTS

The authors found that 9 and 11 frame averages were suitable for all VMAT and SBRT-VMAT treatments, respectively. This resulted in no more than a 1% loss to any of the dose region's mean percentage difference when compared to the single frame reconstruction. The optimized number was dependent on the treatment's dose per fraction and was determined to be as high as 14 for 12 Gy/fraction (fx), 15 for 8 Gy/fx, 11 for 6 Gy/fx, and 9 for 2 Gy/fx.

CONCLUSIONS

The authors have determined an optimal EPID frame averaging number for multiple VMAT-type treatments. These are given as a function of the dose per fraction and average gantry speed. These optimized values are now used in the authors' clinical, 3D, in vivo patient dosimetry program. This provides a reduction in calculation time while maintaining the authors' required level of accuracy in the dose reconstruction.

Investigation of a real-time EPID-based patient dose monitoring safety system using site-specific control limits

Purpose

The aim of this study is to investigate the performance and limitations of a real-time transit electronic portal imaging device (EPID) dosimetry system for error detection during dynamic intensity modulated radiation therapy (IMRT) treatment delivery. Sites studied are prostate, head and neck (HN), and rectal cancer treatments.

Methods

The system compares measured cumulative transit EPID image frames with predicted cumulative image frames in real-time during treatment using a χ comparison with 4 %, 4 mm criteria. The treatment site-specific thresholds (prostate, HN and rectum IMRT) were determined using initial data collected from 137 patients (274 measured treatment fractions) and a statistical process control methodology. These thresholds were then applied to data from 15 selected patients including 5 prostate, 5 HN, and 5 rectum IMRT treatments for system evaluation and classification of error sources.

Results

Clinical demonstration of real-time transit EPID dosimetry in IMRT was presented. For error simulation, the system could detect gross errors (i.e. wrong patient, wrong plan, wrong gantry angle) immediately after EPID stabilisation; 2 seconds after the start of treatment. The average rate of error detection was 7.0 % (prostate = 5.6 %, HN= 8.7 % and rectum = 6.7 %). The detected errors were classified as either clinical in origin (e.g. patient anatomical changes), or non-clinical in origin (e.g. detection system errors). Classified errors were 3.2 % clinical and 3.9 % non-clinical.

Conclusion

An EPID-based real-time error detection method for treatment verification during dynamic IMRT has been developed and tested for its performance and limitations. The system is able to detect gross errors in real-time, however improvement in system robustness is required to reduce the non-clinical sources of error detection.

Two-dimensional in vivo dose verification using portal imaging and correlation ratios

The electronic portal imaging device (EPID) has the potential to be used for in vivo dosimetry during radiation therapy as an additional dose delivery check. In this study we have extended a method developed by A. Piermattei and colleagues in 2006 that made use of EPID transit images (acquired during treatment) to calculate dose in the isocenter point. The extension allows calculation of two-dimensional dose maps of the entire radiation field at the depth of isocenter. We quantified the variability of the ratio of EPID signal to dose in the isocenter plane in Solid Water phantoms of various thicknesses and with various field sizes, and designed a field edge dose calculation correction. To validate the method, we designed three realistic conventional radiation therapy treatment plans on a thorax and head anthropomorphic phantom (whole brain, brain primary, lung tumor). Using CT data, EPID transit images, EPID signal-to-dose correlation, and our edge correction, we calculated dose in the isocenter plane and compared it with the treatment planning system's prediction. Gamma evaluation (3%, 3 mm) showed good agreement (Pγ<1 ≥ 96.5%) for all fields of the whole brain and brain primary plans. In the presence of lung, however, our algorithm overestimated dose by 7%-9%. This 2D EPID-based in vivo dosimetry method can be used for posttreatment dose verification, thereby improving the safety and quality of patient treatments. With future work, it may be extended to measure dose in real time and to prevent harmful delivery errors.

Transit dosimetry in dynamic IMRT with an a-Si EPID

Using an amorphous silicon (a-Si) EPID for transit dosimetry requires detailed characterization of its dosimetric response in a variety of conditions. In this study, a measurement-based model was developed to calibrate an a-Si EPID response to dose for transit dosimetry by comparison with a reference ionization chamber. The ionization chamber reference depth and the required additional buildup thickness for electronic portal imaging devices (EPID) transit dosimetry were determined. The combined effects of changes in radiation field size, phantom thickness, and the off-axis distance on EPID transit dosimetry were characterized. The effect of scattered radiation on out-of-field response was investigated for different field sizes and phantom thicknesses by evaluation of the differences in image profiles and in-water measured profiles. An algorithm was developed to automatically apply these corrections to EPID images based on the user-specified field size and phantom thickness. The average phantom thickness and an effective field size were used for IMRT fields, and images were acquired in cine mode in the presence of an anthropomorphic phantom. The effective field size was defined as the percentage of the jaw-defined field that was involved during the delivery. Nine head and neck dynamic IMRT fields were tested by comparison with a MatriXX two-dimensional array dosimeter using the Gamma (3%, 3 mm) evaluation. A depth of 1.5 cm was selected as the ionization chamber reference depth. An additional 2.2 mm of copper buildup was added to the EPID. Comparison of EPID and MatriXX dose images for the tested fields showed that using a 10% threshold, the average number of points with Gamma index <1 was 96.5%. The agreement in the out-of field area was shown by selection of a 2% threshold which on average resulted in 94.8% of points with a Gamma index <1. The suggested method is less complicated than previously reported techniques and can be used for all a-Si EPIDs regardless of the manufacturer.

Measurement and modeling of the effect of support arm backscatter on dosimetry with a varian EPID

PURPOSE

Amorphous silicon EPIDs have been used for planar dose verification in IMRT treatments for many years. The support arm used to attach some types of EPIDs to linear accelerators can introduce inaccuracies to dosimetry measurements due to the presence of metallic parts in their structures. It is demonstrated that this uncertainty may be as large as approximately 6% of maximum image signal for large fields. In this study, a method has been described to quantify, model and correct for the effect of backscattered radiation from the EPID support arm (E-Arm type, Varian Medical Systems).

METHODS

Measurements of a support arm backscatter kernel were made using several 1 x 1 cm2 6 MV pencil beam irradiations at a sample of positions over the sensitive area of the EPID in standard clinical setup and repeated with the EPID removed from the support arm but at the same positions. A curve-fit to the subtraction of EPID response obtained on and off the arm was used to define the backscatter kernel. The measured kernel was compared with a backscatter kernel obtained by Monte Carlo simulations with EGS/BEAM code. A backscatter dose prediction using the measured backscatter kernel was added to an existing EPID dose prediction model. The improvement in the agreement of the modified model predictions with EPID measurements for a number of open fields and IMRT beams were investigated by comparison to the original model results.

RESULTS

Considering all functions tested to find the best functional fit to the data points, a broad Gaussian curve proved to be the optimum fit to the backscatter data. The best fit through the Monte Carlo simulated backscatter kernel was also found to be a Gaussian curve. The maximum decrease in normalized root mean squared deviation of the measured and modeled EPID image profiles for open fields was 13.7% for a 15 x 15 cm2 field with no decrease observed for a 3 x 3 cm2 (the smallest) field as it was not affected by the arm backscatter. Gamma evaluation (2%, 2 mm criteria) showed the improvement in agreement between the model and measurement results when the backscatter was incorporated. The average increase in Gamma pass rate was 2% for head and neck and 1.3% for prostate IMRT fields investigated in this study.

CONCLUSIONS

The application of the backscatter kernel determined in this study improved the accuracy of dosimetry using a Varian EPID with E-arm for open fields of different sizes: Eight head and neck and seven prostate IMRT fields. Further improvement in the agreement between the model predictions and EPID measurements requires more sophisticated modeling of the backscatter.