A Novel Approach for Position Verification and Dose Calculation through Local MVCT Reconstruction

Traditional positioning verification using cone-beam computed tomography (CBCT) may incur errors due to potential misalignments between the isocenter of CBCT and the treatment beams in radiotherapy. This study introduces an innovative method for verifying patient positioning in radiotherapy. Initially, the transmission images from an electronic portal imaging device (EPID) are acquired from 10 distinct angles. Utilizing the ART-TV algorithm, a sparse reconstruction of local megavoltage computed tomography (MVCT) is performed. Subsequently, this MVCT is aligned with the planning CT via a three-dimensional mutual information registration technique, pinpointing any patient-positioning discrepancies and facilitating corrective adjustments to the treatment setup. Notably, this approach employs the same radiation source as used in treatment to obtain three-dimensional images, thereby circumventing errors stemming from misalignment between the isocenter of CBCT and the accelerator. The registration process requires only 10 EPID images, and the dose absorbed during this process is included in the total dose calculation. The results show that our method's reconstructed MVCT images fulfill the requirements for registration, and the registration algorithm accurately detects positioning errors, thus allowing for adjustments in the patient's treatment position and precise calculation of the absorbed dose.

Deep learning-based tools to distinguish plan-specific from generic deviations in EPID-based in vivo dosimetry

BACKGROUND

Dose distributions calculated with electronic portal imaging device (EPID)-based in vivo dosimetry (EIVD) differ from planned dose distributions due to generic and plan-specific deviations. Generic deviations are characteristic to a class of plans. Examples include limitations in EIVD dose reconstruction, inaccuracies in treatment planning system (TPS) calculations and systematic machine deviations. Plan-specific deviations have an unpredictable character. Examples include discrepancies between the patient model used for dose calculation and the patient position or anatomy during delivery, random machine deviations, and data transfer, human or software errors. During the inspection work performed with traditional γ-evaluation statistical methods: (i) generic deviations raise alerts that need to be inspected but that rarely lead to action as their root cause is usually understood and (ii) the detection of relevant plan-specific deviations may be hindered by the presence of generic deviations.

PURPOSE

To investigate whether deep learning-based tools can help in identifying γ-alerts raised by generic deviations and in improving the detectability of plan-specific deviations.

METHODS

A 3D U-Net was trained as an autoencoder to reconstruct underlying patterns of generic deviations in γ-distributions. The network was trained for four treatment disease sites differently affected by generic deviations: volumetric modulated arc therapy (VMAT) lung (no known deviations), VMAT prostate (TPS inaccuracies), VMAT head-and-neck (EIVD limitations) and intensity modulated radiation therapy (IMRT) breast (large EIVD limitations). The network was trained with virtual non-transit γ-distributions: 60 train/10 validation for the VMAT sites and 30 train/10 validation for IMRT breast. It was hypothesized that in vivo γ-distributions obtained in the presence of plan-specific deviations would differ from those seen during training. For each disease site, the sensitivity of γ-analysis and the network to detect (synthetically introduced) patient-related deviations was compared by receiver operator characteristic analysis. The investigated deviations were patient positioning errors, weight gain or loss, and tumor volume changes. The clinical relevance was illustrated qualitatively with 793 in vivo clinical cases (141 lung, 136 head-and-neck, 209 prostate and 307 breast).

RESULTS

Error detectability of patient-related deviations was better with the network than with γ-analysis. The average area under the curve values over all sites were 0.86 ± 0.12(1SD) and 0.69 ± 0.25(1SD), respectively. Regarding in vivo clinical results, the percentage of cases differently classified by γ-analysis and the network was 1%, 19%, 18% and 64% for lung, head-and-neck, prostate, and breast, respectively. In head-and-neck and breast cases, 45 γ-only alerts were examined, of which 43 were attributed to EPID dose reconstruction limitations. For prostate, all 15 investigated γ-only alerts were due to known TPS inaccuracies. All 59 investigated network alerts were explained by either patient-related deviations or EPID acquisition incidents. Some patient-related deviations detected by the network were not detected by γ-analysis.

CONCLUSIONS

Deep learning-based tools trained to reconstruct underlying patterns of generic deviations in γ-distributions can be used to (i) automatically identify false positives within the set of γ-alerts and (ii) improve the detection of plan-specific deviations, hence minimizing the likelihood of false negatives. The presented method provides clear additional value to the γ-alert management process for large scale EIVD systems.

Effect of metal implants and metal artifacts on back-projected two-dimensional entrance fluence determined by EPID dosimetry

PURPOSE

To evaluate the errors caused by metal implants and metal artifacts in the two-dimensional entrance fluences reconstructed using the back-projection algorithm based on electronic portal imaging device (EPID) images.

METHODS

The EPID in the Varian VitalBeam accelerator was used to acquire portal dose images (PDIs), and then commercial EPID dosimetry software was employed to reconstruct the two-dimensional entrance fluences based on computed tomography (CT) images of the head phantoms containing interchangeable metal-free/titanium/aluminum round bars. The metal-induced errors in the two-dimensional entrance fluences were evaluated by comparing the γ results and the pixel value errors in the metal-affected regions. We obtained metal-artifact-free CT images by replacing the voxel values of non-metal inserts with those of metal inserts in metal-free CT images to evaluate the metal-artifact-induced errors.

RESULTS

The γ passing rates (versus PDIs obtained without a phantom in the beam field (PDIair ), 2%/2 mm) for the back-projected two-dimensional entrance fluences of phantoms containing titanium or aluminum (BPTi /BPAl ) were reduced from 92.4% to 90.5% and 90.6%, respectively, relative to the metal-free phantom (BPmetal-free ). Titanium causes more severe metal artifacts in CT images than aluminum, and its removal resulted in a 0.0022 CU (median) reduction in the pixel value of BPTi artifact-free relative to BPTi in the metal-affected region. Moreover, the mean absolute error (MAE) and root mean square error (RMSE) decreased from 0.0050 CU and 0.0063 CU to 0.0034 CU and 0.0040 CU, respectively (vs. BPmetal-free ).

CONCLUSION

Metal implants increase the errors in back-projected two-dimensional entrance fluences, and metals with higher electron densities cause more errors. For high-electron-density metal implants that produce severe metal artifacts (e.g., titanium), removing metal artifacts from the CT images can improve the accuracy of the two-dimensional entrance fluences reconstructed by back-projection algorithms.

Towards real-time EPID-based 3D in vivo dosimetry for IMRT with Deep Neural Networks: A feasibility study

We investigate the potential of the Deep Dose Estimate (DDE) neural network to predict 3D dose distributions inside patients with Monte Carlo (MC) accuracy, based on transmitted EPID signals and patient CTs. The network was trained using as input patient CTs and first-order dose approximations (FOD). Accurate dose distributions (ADD) simulated with MC were given as training targets. 83 pelvic CTs were used to simulate ADDs and respective EPID signals for subfields of prostate IMRT plans (gantry at 0∘). FODs were produced as backprojections from the EPID signals. 581 ADD-FOD sets were produced and divided into training and test sets. An additional dataset simulated with gantry at 90∘ (lateral set) was used for evaluating the performance of the DDE at different beam directions. The quality of the FODs and DDE-predicted dose distributions (DDEP) with respect to ADDs, from the test and lateral sets, was evaluated with gamma analysis (3%,2 mm). The passing rates between FODs and ADDs were as low as 46%, while for DDEPs the passing rates were above 97% for the test set. Meaningful improvements were also observed for the lateral set. The high passing rates for DDEPs indicate that the DDE is able to convert FODs into ADDs. Moreover, the trained DDE predicts the dose inside a patient CT within 0.6 s/subfield (GPU), in contrast to 14 h needed for MC (CPU-cluster). 3D in vivo dose distributions due to clinical patient irradiation can be obtained within seconds, with MC-like accuracy, potentially paving the way towards real-time EPID-based in vivo dosimetry.

A structure-based gamma evaluation method for identifying clinically relevant dose differences in organs at risk

Gamma evaluation is currently the most widely used dose comparison method for patient specific quality assurance (PSQA). However, existing methods for normalising the dose difference, using either the dose at the global maximum dose point or at each local point, can respectively lead to under- and over-sensitivity to dose differences in organ-at-risk structures. This may be of concern for plan evaluation from clinical perspectives. This study has explored and proposed a new method called structural gamma, which takes structural dose tolerances into consideration while performing gamma analysis for PSQA. As a demonstration of the structural gamma method, a total of 78 retrospective plans on four treatment sites were re-calculated on an in-house Monte Carlo system and compared with doses calculated from the treatment planning system. Structural gamma evaluations were performed using both QUANTEC dose tolerances and radiation oncologist specified dose tolerances, then compared with conventional global and local gamma evaluations. Results demonstrated that structural gamma evaluation is especially sensitive to errors in structures with restrictive dose constraints. The structural gamma map provides both geometric and dosimetric information on PSQA results, allowing straightforward clinical interpretation. The proposed structure-based gamma method accounts for dose tolerances for specific anatomical structures. This method can provide a clinically useful method to assess and communicate PSQA results, offering radiation oncologists a more intuitive way of examining agreement in surrounding critical normal structures.

A recurrent neural network for rapid detection of delivery errors during real-time portal dosimetry

Background and purpose

Real-time portal dosimetry compares measured images with predicted images to detect delivery errors as the radiotherapy treatment proceeds. This work aimed to investigate the performance of a recurrent neural network for processing image metrics so as to detect delivery errors as early as possible in the treatment.

Materials and methods

Volumetric modulated arc therapy (VMAT) plans of six prostate patients were used to generate sequences of predicted portal images. Errors were introduced into the treatment plans and the modified plans were delivered to a water-equivalent phantom. Four different metrics were used to detect errors. These metrics were applied to a threshold-based method to detect the errors as soon as possible during the delivery, and also to a recurrent neural network consisting of four layers. A leave-two-out approach was used to set thresholds and train the neural network then test the resulting systems.

Results

When using a combination of metrics in conjunction with optimal thresholds, the median segment index at which the errors were detected was 107 out of 180. When using the neural network, the median segment index for error detection was 66 out of 180, with no false positives. The neural network reduced the rate of false negative results from 0.36 to 0.24.

Conclusions

The recurrent neural network allowed the detection of errors around 30% earlier than when using conventional threshold techniques. By appropriate training of the network, false positive alerts could be prevented, thereby avoiding unnecessary disruption to the patient workflow.

Evaluation of kV-CBCT based 3D dose calculation accuracy and its validation using delivery fluence derived dose metrics in Head and Neck Cancer

PURPOSE

The purpose of this study is to evaluate the dosimetric impact of Hounsfield unit (HU) variations in kilovoltage cone-beam computed tomography (kV-CBCT) based 3D dose calculation accuracy in the treatment planning system and its validation using measured treatment delivery dose (MTDD) derived dose metrics for Volumetric Modulated Arc Therapy (VMAT) and Intensity Modulated Radiotherapy (IMRT) plans in Head and Neck (HN) Cancer.

METHODS

CBCT dose calculation accuracy was evaluated for 8 VMAT plans on inhomogeneous phantom and 40 VMAT and IMRT plans of HN Cancer patients and validated using ArcCHECK diode array MTDD derived 3D dose metric on CT and CBCT.

RESULTS

The mean percentage dose difference between CBCT and CT in TPS (ΔD(CBCT-CT)_TPS) and 3DVH (ΔD(CBCT-CT)_3DVH) were compared for the corresponding evaluation dose metrics (D_98%, D_95%, D_50%, D_2%, D_max, D_1cc, D_0.03cc, D_mean) of all PTVs and OARs in phantom and patients. ΔD(CBCT-CT)_TPS and ΔD(CBCT-CT)_3DVH for all evaluation dose points of all PTVs and OARs were less than 2.55% in phantom and 2.4% in HN patients. The Pearson correlation coefficient (r) between ΔD(CBCT-CT)_TPS and ΔD(CBCT-CT)_3DVH for all dose points in all PTVs and OARs showed a strong to moderate correlation in phantom and patients with p < 0.001.

CONCLUSIONS

This study evaluated and validated the potential feasibility of kV-CBCT for treatment plan 3D dose reconstruction in clinical decision making for Adaptive radiotherapy on CT in Head and Neck cancer.

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.

Development of an Electronic Portal Imaging Device Dosimetry Method

Support arm backscatter and off-axis effects of an electronic portal imaging device (EPID) are challenging for radiotherapy quality assurance. Aiming at the issue, we proposed a simple yet effective method with correction matrices to rectify backscatter and off-axis responses for EPID images. First, we measured the square fields with ionization chamber array (ICA) and EPID simultaneously. Second, we calculated the dose-to-pixel value ratio and used it as the correction matrix of the corresponding field. Third, the correction value of the large field was replaced with that of the same point in the small field to generate a correction matrix suitable for different EPID images. Finally, we rectified the EPID image with the correction matrix, and then the processed EPID images were converted into the absolute dose. The calculated dose was compared with the measured dose via ICA. The gamma pass rates of 3%/3 mm and 2%/2 mm (5% threshold) were 99.6% ± 0.94% and 95.48% ± 1.03%, and the average gamma values were 0.28 ± 0.04 and 0.42 ± 0.05, respectively. Experimental results verified our method accurately corrected EPID images and converted pixel values into absolute dose values such that EPID was an efficient radiotherapy dosimetry tool.

Verification of the delivered patient radiation dose for non-coplanar beam therapy

PURPOSE

There is an increased interest in using non-coplanar beams for radiotherapy, including SBRT and SRS. This approach can significantly reduce doses to organs-at-risk, however, it requires stringent quality assurance, especially when a dynamic treatment couch is used. In this work, new functionality that allows using non-coplanar beam arrangements in addition to conventional coplanar beams was added and validated to the previously developed in vivo dose verification system.

METHODS

The existing program code was modified to manage the additional treatment couch parameters: angle and positions. Ten non-coplanar test plans that use a static couch were created in the treatment planning system. Also, two plans that use a dynamic treatment couch were created and delivered using Varian Developer mode, since the treatment planning system does not support a dynamic couch. All non-coplanar test trajectories were delivered on a simple geometric phantom, using an Edge linear accelerator (Varian Medical Systems) with the megavoltage imager deployed and acquiring megavoltage transmission images that were used to calculate the delivered 3D dose distributions in the phantom with the updated dose calculation algorithm. The reconstructed dose distributions were compared using the 3D chi-comparison test with 2%/2mm tolerances to the corresponding reference dose distributions obtained from the treatment planning system.

RESULTS

The chi-comparison test resulted in at least a 97.0% pass rate over the entire 3D volume for all tested trajectories. For static gantry, static couch non-coplanar fields, and non-coplanar arcs using dynamic couch the pass rates observed were at least 98%, while for the static couch, non-transverse coplanar arc fields, pass rates were at least 97%.

CONCLUSIONS

A model-based 3D dose calculation algorithm has been extended and validated for a variety of non-coplanar beam trajectories of different complexities. This system can potentially be applied for quality assurance of treatment delivery systems that use complex, non-coplanar beam arrangements.

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.

Optimisation of a composite difference metric for prompt error detection in real-time portal dosimetry of simulated volumetric modulated arc therapy

OBJECTIVES

In real-time portal dosimetry, thresholds are set for several measures of difference between predicted and measured images, and signals larger than those thresholds signify an error. The aim of this work is to investigate the use of an additional composite difference metric (CDM) for earlier detection of errors.

METHODS

Portal images were predicted for the volumetric modulated arc therapy plans of six prostate patients. Errors in monitor units, aperture opening, aperture position and path length were deliberately introduced into all 180 segments of the treatment plans, and these plans were delivered to a water-equivalent phantom. Four different metrics, consisting of central axis signal, mean image value and two image difference measures, were used to identify errors, and a CDM was added, consisting of a weighted power sum of the individual metrics. To optimise the weights of the CDM and to evaluate the resulting timeliness of error detection, a leave-pair-out strategy was used. For each combination of four patients, the weights of the CDM were determined by an exhaustive search, and the result was evaluated on the remaining two patients.

RESULTS

The median segment index at which the errors were identified was 87 (range 40-130) when using all of the individual metrics separately. Using a CDM as well as multiple separate metrics reduced this to 73 (35-95). The median weighting factors of the four metrics constituting the composite were (0.15, 0.10, 0.15, 0.00). Due to selection of suitable threshold levels, there was only one false positive result in the six patients.

CONCLUSION

This study shows that, in conjunction with appropriate error thresholds, use of a CDM is able to identify increased image differences around 20% earlier than the separate measures.

ADVANCES IN KNOWLEDGE

This study shows the value of combining difference metrics to allow earlier detection of errors during real-time portal dosimetry for volumetric modulated arc therapy treatment.

Dosimetric performance of continuous EPID imaging in stereotactic treatment conditions

PURPOSE

This study aims at investigating the dosimetric characteristics of a Varian aS1000 EPID, focusing on its continuous acquisition mode under the challenging conditions that can be met in stereotactic radiotherapy verification.

METHODS

An aS1000 EPID installed on a Varian TrueBeamSTx was irradiated with 6 and 10 MV unflattened and flattened photon beams. In order to avoid detector saturation, the source-to-detector distance (SDD) was set to 150 or 180 cm depending on the dose rate. EPID image sets were acquired in continuous mode (CM) and also in the commonly used integrated mode (IM) for comparison, to evaluate dose linearity (including dose rate dependence), repeatability, reproducibility, stability, ghosting effect and field size dependence.

RESULTS

CM response linearity was found to be within 0.8% of IM and independent of dose rate. Response repeatability was slightly better for IM and FF beams, being in all cases within 0.9%. Reproducibility was within 0.6% for both modes and all beam qualities. Response stability between continuous frames varied within 1% for dynamic and static irradiations and for all the beam qualities, showing its independence from these parameters. Ghosting effect was not significant, being comparable to signal variations between continuous frames (±1%). Field size dependence in both modes agreed within 1%.

CONCLUSIONS

The dosimetric response of the aS1000 EPID in CM with FFF beams and high dose rates is comparable to that in IM and for flattened beams provided that the appropriate SDD is used. aS1000 EPID in continuous acquisition mode is therefore suitable for stereotactic applications.

A tri-hybrid method to estimate the patient-generated scattered photon fluence components to the EPID image plane

In vivo dosimetry methods can verify the prescription dose is delivered to the patient during treatment. Unfortunately, in exit dosimetry, the megavoltage image is contaminated with patient-generated scattered photons. However, estimation and removal of the effect of this fluence improves accuracy of in vivo dosimetry methods. This work develops a 'tri-hybrid' algorithm combining analytical, Monte Carlo (MC) and pencil-beam scatter kernel methods to provide accurate estimates of the total patient-generated scattered photon fluence entering the MV imager. For the multiply-scattered photon fluence, a modified MC simulation method was applied, using only a few histories. From each second- and higher-order interaction site in the simulation, energy fluence entering all pixels of the imager was calculated using analytical methods. For photon fluence generated by electron interactions in the patient (i.e. bremsstrahlung and positron annihilation), a convolution/superposition approach was employed using pencil-beam scatter fluence kernels as a function of patient thickness and air gap distance, superposed on the incident fluence distribution. The total patient-scattered photon fluence entering the imager was compared with a corresponding full MC simulation (EGSnrc) for several test cases. These included three geometric phantoms (water, half-water/half-lung, computed tomography thorax) using monoenergetic (1.5, 5.5 and 12.5 MeV) and polyenergetic (6 and 18 MV) photon beams, 10 × 10 cm² field, source-to-surface distance 100 cm, source-to-imager distance 150 cm and 40 × 40 cm² imager. The proposed tri-hybrid method is demonstrated to agree well with full MC simulation, with the average fluence differences and standard deviations found to be within 0.5% and 1%, respectively, for test cases examined here. The method, as implemented here with a single CPU (non-parallelized), takes ∼80 s, which is considerably shorter compared to full MC simulation (∼30 h). This is a promising method for fast yet accurate calculation of patient-scattered fluence at the imaging plane for in vivo dosimetry applications.

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.

In vivo dosimetry in external beam photon radiotherapy: Requirements and future directions for research, development, and clinical practice

External beam radiotherapy with photon beams is a highly accurate treatment modality, but requires extensive quality assurance programs to confirm that radiation therapy will be or was administered appropriately. In vivo dosimetry (IVD) is an essential element of modern radiation therapy because it provides the ability to catch treatment delivery errors, assist in treatment adaptation, and record the actual dose delivered to the patient. However, for various reasons, its clinical implementation has been slow and limited. The purpose of this report is to stimulate the wider use of IVD for external beam radiotherapy, and in particular of systems using electronic portal imaging devices (EPIDs). After documenting the current IVD methods, this report provides detailed software, hardware and system requirements for in vivo EPID dosimetry systems in order to help in bridging the current vendor-user gap. The report also outlines directions for further development and research. In vivo EPID dosimetry vendors, in collaboration with users across multiple institutions, are requested to improve the understanding and reduce the uncertainties of the system and to help in the determination of optimal action limits for error detection. Finally, the report recommends that automation of all aspects of IVD is needed to help facilitate clinical adoption, including automation of image acquisition, analysis, result interpretation, and reporting/documentation. With the guidance of this report, it is hoped that widespread clinical use of IVD will be significantly accelerated.

Estimating dose delivery accuracy in stereotactic body radiation therapy: A review of in-vivo measurement methods

Stereotactic body radiation therapy (SBRT) has been recognized as a standard treatment option for many anatomical sites. Sophisticated radiation therapy techniques have been developed for carrying out these treatments and new quality assurance (QA) programs are therefore required to guarantee high geometrical and dosimetric accuracy. This paper focuses on recent advances on in-vivo measurements methods (IVM) for SBRT treatment. More specifically, all of the online QA methods for estimating the effective dose delivered to patients were compared. Determining the optimal IVM for performing SBRT treatments would reduce the risk of errors that could jeopardize treatment outcome. A total of 89 papers were included. The papers were subdivided into the following topics: point dosimeters (PD), transmission detectors (TD), log file analysis (LFA), electronic portal imaging device dosimetry (EPID), dose accumulation methods (DAM). The detectability capability of the main IVM detectors/devices were evaluated. All of the systems have some limitations: PD has no spatial data, EPID has limited sensitivity towards set-up errors and intra-fraction motion in some anatomical sites, TD is insensitive towards patient related errors, LFA is not an independent measure, DAMs are not always based on measures. In order to minimize errors in SBRT dose delivery, we recommend using synergic combinations of two or more of the systems described in our review: on-line tumor position and patient information should be combined with MLC position and linac output detection accuracy. In this way the effects of SBRT dose delivery errors will be reduced.

Technical note: development and validation of a Monte Carlo tool for analysis of patient-generated photon scatter

Scattered radiation unavoidably generated in the patient will negatively impact both kilovoltage (KV) and megavoltage (MV) imaging applications. Recently, 'hybrid' methods (i.e. combining analytical and Monte Carlo (MC) techniques) are being investigated as a solution to accurately yet quickly calculate the scattered contribution for both KV and MV images. We have developed a customized MC simulation user code for investigating the individual components of patient-scattered photon fluence, which serves as a valuable tool in this area of research. The MC tool is based on the EGSnrc/DOSXYZnrc user code. The IAUSFL flag options associated with subroutine AUSGAB, combined with LATCH tracking, are used to classify the various interactions of particles with the media. Photons are grouped into six different categories: primary, 1st Compton scatter, 1st Rayleigh scatter, multiple scatter, bremsstrahlung, and positron annihilation. We take advantage of the geometric boundary check in DOSXYZnrc, to write exiting photon particle information to a phase-space file. The tool is validated using homogeneous and heterogeneous phantom configurations with monoenergetic and polyenergetic beams under parallel and divergent beam geometry, comparing MC-simulated exit primary fluence and singly-scattered fluence to corresponding analytical calculations. This MC tool has been validated to separately score the primary and scatter fluence components of the KV and MV imaging applications in the field of radiation therapy. The results are acceptable for the various configurations and beam energies tested here. Overall, the mean percentage differences are less than 0.2% and standard deviations less than 1.6%. This will be a critical test instrument for research in photon scatter applications and particularly for the development of hybrid methods, and is freely available from the authors for research purposes.⁵.

3D dosimetric verification of unity MR-linac treatments by portal dosimetry

PURPOSE AND BACKGROUND

3D dosimetric verification of online adaptive workflows is essential as their complexity is unprecedented in radiation oncology. The aim of this work is to demonstrate the feasibility of back-projection portal dosimetry for 3D dosimetric verification of Unity MR-linac treatments.

MATERIAL AND METHODS

An earlier presented 2D back-projection algorithm for the Unity MR-linac geometry was extended for 3D dose reconstruction and comparison against planned dose distributions. 'In-air' as well as in-vivo portal EPID images can be used as input. The method was validated using data from treatments of 5 patients (2 rectal, 2 prostate cancer and one oligo metastasis). 3D pre-treatment verification of the reference plan using 'in-air' EPID images was performed and compared against measured (with the Octavius 4D system) and planned (in the planning CT) dose distributions. In-vivo EPID dose distributions were compared to the TPS for the first three adaptations of all treatments. For all comparisons, dose difference values at the reference point and γ-parameters were reported.

RESULTS

The comparison against the OCTAVIUS 4D system (3%, 2 mm, local) showed y-mean = 0.52 ± 0.10 and y-passrate = 91.9%, 95% CI [85.4, 98.4], and ΔD_RP = -0.1 ± 1.1%. Pre-treatment verification against TPS data (3%, 2 mm, global) showed y-mean = 0.52 ± 0.04, y-passrate = 93.5%, 95% CI [92.4, 94.6] and ΔD_RP = -0.9 ± 1.5%. The averaged y-results for the in-vivo 3D verification were y-mean = 0.52 ± 0.05, y-passrate = 92.5%, 95% CI [90.2, 94.8] and ΔD_RP = 0.8 ± 2.1%.

CONCLUSION

3D dosimetric verification of Unity MR-linac treatments using portal dosimetry is feasible, pre-treatment as well as in-vivo.

The effect of the choice of patient model on the performance of in vivo 3D EPID dosimetry to detect variations in patient position and anatomy

PURPOSE

In vivo EPID dosimetry is meant to trigger on relevant differences between delivered and planned dose distributions and should therefore be sensitive to changes in patient position and patient anatomy. Three-dimensional (3D) EPID back-projection algorithms can use either the planning computed tomography (CT) or the daily patient anatomy as patient model for dose reconstruction. The purpose of this study is to quantify the effect of the choice of patient model on the performance of in vivo 3D EPID dosimetry to detect patient-related variations.

METHODS

Variations in patient position and patient anatomy were simulated by transforming the reference planning CT images (pCT) into synthetic daily CT images (dCT) representing a variation of a given magnitude in patient position or in patient anatomy. For each variation, synthetic in vivo EPID data were also generated to simulate the reconstruction of in vivo EPID dose distributions. Both the planning CT images and the synthetic daily CT images could be used as patient model in the reconstructions yielding e D pCT and e D dCT EPID reconstructed dose distributions respectively. The accuracy of e D pCT and e D dCT reconstructions was evaluated against absolute dose measurements made in different phantom setups, and against dose distributions calculated by the treatment planning system (TPS). The comparison was performed by γ-analysis (3% local dose/2 mm). The difference in sensitivity between e D pCT and e D dCT reconstructions to detect variations in patient position and in patient anatomy was investigated using receiver operating characteristic analysis and the number of triggered alerts for 100 volumetric modulated arc therapy plans and 12 variations.

RESULTS

e D dCT showed good agreement with both absolute point dose measurements (<0.5%) and TPS data (γ-mean = 0.52 ± 0.11). The agreement degraded with e D pCT , with the magnitude of the deviation varying with each specific case. e D dCT readily detected combined 3 mm translation setup errors in all directions (AUC = 1.0) and combined 3° rotation setup errors around all axes (AUC = 0.86) whereas e D pCT showed good detectability only for 12 mm translations (AUC = 0.85) and 9° rotations (AUC = 0.80). Conversely, e D pCT manifested a higher sensitivity to patient anatomical changes resulting in AUC values of 0.92/0.95 for a 6 mm patient contour expansion/contraction compared to 0.70/0.64 with e D dCT . Using |ΔPTV_D50 | > 3% as clinical tolerance level, the percentage of alerts for 6 mm changes in patient contour were 85%/27% with e D pCT / e D dCT .

CONCLUSIONS

With planning CT images as patient model, EPID dose reconstructions underestimate the dosimetric effects caused by errors in patient positioning and overestimate the dosimetric effects caused by changes in patient anatomy. The use of the daily patient position and anatomy as patient model for in vivo 3D EPID transit dosimetry improves the ability of the system to detect uncorrected errors in patient position and it reduces the likelihood of false positives due to patient anatomical changes.

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.

Electronic Portal Imaging Device-Based Three-Dimensional Volumetric Dosimetry for Intensity-modulated Radiotherapy Pretreatment Quality Assurance

Aim:

This study aimed at evaluating the efficacy of treatment planning system (TPS)-based heterogeneity correction for two- and three-dimensional (2D and 3D) electronic portal imaging device (EPID)-based pretreatment dose verification. An experiment was conducted on the EPID back-projection technique and intensity-modulated radiotherapy (IMRT).

Materials and Methods:

Treatment plans were delivered in EPID without a patient to obtain the fluence pattern (F_EPID). A heterogeneity correction plane (F_het) for an open beam of 30 cm × 30 cm was extracted from the TPS. The heterogeneity-corrected measured fluence is developed by matrix element multiplication (F_Resultant = F_EPID × F_het). Further planes were summed to develop a 3D dose distribution and exported to the TPS. Dose verifications for 2D and 3D were carried out with the corresponding TPS values using 2D gamma analysis (ɣ) and dose volume histogram (DVH) comparison, respectively. Totally, 33 patients (17 head–neck and 16 thorax cases) were evaluated in this study.

Results:

The head–neck and thorax plans show a 3-mm-distance to agreement (DTA) 3% DD gamma passing of 96.3% ± 2.0% and 95.4% ± 1.8% points, respectively, between F_TPS and F_Resultant. The comparison of the uncorrected measured fluence (F_EPID) with F_TPS reveals a gamma passing of 82.2% ± 7.3% and 80.4% ± 8.6% for head–neck and thorax cases, respectively. A total of 87 out of the 102 head–neck and thorax beams exhibit a planner gamma passing of 97.6% ± 2.1%. In the 3D-DVH comparison of thorax and head–neck cases, D5% for planning target volume were −0.5% ± 2.2% and −2.1% ± 3.5%, respectively; D95% varies as 1.0% ± 2.7% and 1.4% ± 1.1% between TPS calculated and heterogeneity-corrected-EPID-based dose reconstruction.

Conclusion:

The novel TPS-based heterogeneity correction can improve the 2D and 3D EPID-based back projection technique. Structures with large heterogeneities can also be handled using the proposed technique.

Two-dimensional EPID dosimetry for an MR-linac: Proof of concept

PURPOSE

At our institute, in vivo patient dose distributions are reconstructed for all treatments delivered using conventional linacs from electronic portal imaging device (EPID) transit images acquired during treatment using a simple back-projection model. Currently, the clinical implementation of MRI-guided radiotherapy systems, which aims for online and real-time adaptation of the treatment plan, is progressing. In our department, the MR-linac (Unity, Elekta AB, Stockholm, Sweden) is now in clinical use. The aim of this work is to demonstrate the feasibility of two-dimensional (2D) EPID dosimetric verification for the magnetic resonance (MR)-linac by comparing back-projected EPID doses to ionization chamber (IC) array dose distributions.

MATERIALS AND METHODS

Our conventional back-projection algorithm was adapted for the MR-linac. The most important changes involve modeling of the attenuation by and scatter from the cryostat. The commissioning process involved the acquisition of square field EPID measurements using various phantom setups (varying SSD, phantom thickness, and field size). Commissioning models were created for gantry 0°, 90°, and 180° and verified by comparing EPID-reconstructed 2D dose distributions to measurements made with the OCTAVIUS 1500 IC array (PTW, Freiburg, Germany) for two prostate and one rectum IMRT plans (25 beams total). The average of the γ parameters (y-mean and y-pass rate) and the dose difference at a reference point were reported. Due to their construction, the attenuation of couch, bridge, and cryostat shows a much stronger dependence on gantry angle in the MR-linac compared to conventional linacs. We present a method to correct for these effects. This method is validated by dose reconstruction of the 25 intensity-modulated radiation therapy beams recorded at a certain gantry angle using the model of another gantry angle, combined with the correction method.

RESULTS

For dose verification performed at a gantry angle identical to the commissioned model, the average y-mean and y-pass rate values (3% global dose, 2 mm, 10% isodose) were 0.37 ± 0.07 and 98.1, 95% CI [98.1 ± 2.4], respectively. The average dose difference at the reference point was -0.5% ± 1.8%. Verification at gantry angles different from the commissioned model (i.e., using the gantry angle dependent correction) reported 0.39 ± 0.08 and 97.6, 95% CI [96.9, 98.3] average y-mean and y-pass rate values. The average dose difference at the reference point was -0.1% ± 1.8%.

CONCLUSION

The EPID dosimetry back-projection model was successfully adapted for the MR-linac at gantry 0°, 90°, and 180°, accounting for the presence of the MRI housing between phantom (or patient) and the EPID. A method to account for the gantry angle dependence was also tested reporting similar results.

Investigating the effectiveness of monitoring relevant variations during IMRT and VMAT treatments by EPID-based 3D in vivo verification performed using planning CTs

Purpose

The goal of this study was to investigate the effectiveness of monitoring relevant variations during treatments for electronic portal imaging device (EPID)-based 3D in vivo verification performed using planning CTs.

Methods

Experiments on two simple phantoms (uniform and nonuniform phantoms) and a thoracic phantom were analyzed in this study, and six relevant variations including the machine output, planning target volume (PTV) deformation, multileaf collimator (MLC) and Phantom shift (set-up errors), and gantry and couch angle shifts were evaluated. 3D gamma and dose-volume histogram (DVH) methods were used to evaluate the detection sensitivity of the EPID-based 3D in vivo dosimetry and the dose accuracy of the EPID reconstruction, respectively, as affected by the variations, and the results were validated by determining the consistency with TPS simulated results.

Results

The results of the simple phantoms showed that the gamma failure rates and DVH trend of EPID reconstructions were consistent with the results of TPS simulations for machine output and MLC shifts and inconsistent for phantom shift, gantry/couch angle shift and PTV deformation variations. The results of the thoracic phantom showed that CBCT-guided EPID reconstruction sensitively detected 3-mm Phantom shift in thoracic phantom and its gamma failure rates and DVH trend were consistent with the results of TPS simulations.

Conclusion

The variations, such as machine output and MLC shift, that are phantom unrelated and cause changes in the beam of the linear accelerator can be sensitively detected by EPID-based 3D in vivo dosimetry and do not affect the accuracy of the EPID reconstruction dose. Planning CT will limit the detection sensitivity and the accuracy of the reconstruction dose of the EPID-based 3D in vivo dosimetry for phantom-related variations (such as Phantom shift and gantry/couch angle shift). EPID reconstruction combined with IGRT technology is a more effective method to monitor phantom shift variations.

Transit and non-transit 3D EPID dosimetry versus detector arrays for patient specific QA

PURPOSE

Despite their availability and simplicity of use, Electronic Portal Imaging Devices (EPIDs) have not yet replaced detector arrays for patient specific QA in 3D. The purpose of this study is to perform a large scale dosimetric evaluation of transit and non-transit EPID dosimetry against absolute dose measurements in 3D.

METHODS

After evaluating basic dosimetric characteristics of the EPID and two detector arrays (Octavius 1500 and Octavius 1000SRS ), 3D dose distributions for 68 VMAT arcs, and 10 IMRT plans were reconstructed within the same phantom geometry using transit EPID dosimetry, non-transit EPID dosimetry, and the Octavius 4D system. The reconstructed 3D dose distributions were directly compared by γ-analysis (2L2 = 2% local/2 mm and 3G2 = 3% global/2 mm, 50% isodose) and by the percentage difference in median dose to the high dose volume (%∆HDVD 50 ).

RESULTS

Regarding dose rate dependency, dose linearity, and field size dependence, the agreement between EPID dosimetry and the two detector arrays was found to be within 1.0%. In the 2L2 γ-comparison with Octavius 4D dose distributions, the average γ-pass rate value was 92.2 ± 5.2%(1SD) and 94.1 ± 4.3%(1SD) for transit and non-transit EPID dosimetry, respectively. 3G2 γ-pass rate values were higher than 95% in 150/156 cases. %∆HDVD 50 values were within 2% in 134/156 cases and within 3% in 155/156 cases. With regard to the clinical classification of alerts, 97.5% of the treatments were equally classified by EPID dosimetry and Octavius 4D.

CONCLUSION

Transit and non-transit EPID dosimetry are equivalent in dosimetric terms to conventional detector arrays for patient specific QA. Non-transit 3D EPID dosimetry can be readily used for pre-treatment patient specific QA of IMRT and VMAT, eliminating the need of phantom positioning.

An evaluation of techniques for dose calculation on cone beam computed tomography

OBJECTIVE:

To assess the accuracy and efficiency of four different techniques, thus determining the optimum method for recalculating dose on cone beam CT (CBCT) images acquired during radiotherapy treatments.

METHODS:

Four established techniques were investigated and their accuracy assessed via dose calculations: (1) applying a standard planning CT (pCT) calibration curve, (2) applying a CBCT site-specific calibration curve, (3) performing a density override and (4) using deformable registration. Each technique was applied to 15 patients receiving volumetric modulated arc therapy to one of three treatment sites, head and neck, lung and prostate. Differences between pCT and CBCT recalculations were determined with dose volume histogram metrics and 2.0%/0.1 mm gamma analysis using the pCT dose distribution as a reference.

RESULTS:

Dose volume histogram analysis indicated that all techniques yielded differences from expected results between 0.0 and 2.3% for both target volumes and organs at risk. With volumetric gamma analysis, the dose recalculation on deformed images yielded the highest pass-rates. The median pass-rate ranges at 50% threshold were 99.6-99.9%, 94.6-96.0%, and 94.8.0-96.0% for prostate, head and neck and lung patients, respectively.

CONCLUSION:

Deformable registration, HU override and site-specific calibration curves were all identified as dosimetrically accurate and efficient methods for dose calculation on CBCT images.

ADVANCES IN KNOWLEDGE:

With the increasing adoption of CBCT, this study provides clinical radiotherapy departments with invaluable information regarding the comparison of dose reconstruction methods, enabling a more accurate representation of a patient's treatment. It can also integrate studies in which CBCT is used in image-guided radiation therapy and for adaptive radiotherapy planning processes.

Comparison of forward- and back-projection in vivo EPID dosimetry for VMAT treatment of the prostate

In the forward-projection method of portal dosimetry for volumetric modulated arc therapy (VMAT), the integrated signal at the electronic portal imaging device (EPID) is predicted at the time of treatment planning, against which the measured integrated image is compared. In the back-projection method, the measured signal at each gantry angle is back-projected through the patient CT scan to give a measure of total dose to the patient. This study aims to investigate the practical agreement between the two types of EPID dosimetry for prostate radiotherapy. The AutoBeam treatment planning system produced VMAT plans together with corresponding predicted portal images, and a total of 46 sets of gantry-resolved portal images were acquired in 13 patients using an iViewGT portal imager. For the forward-projection method, each acquisition of gantry-resolved images was combined into a single integrated image and compared with the predicted image. For the back-projection method, iViewDose was used to calculate the dose distribution in the patient for comparison with the planned dose. A gamma index for 3% and 3 mm was used for both methods. The results were investigated by delivering the same plans to a phantom and repeating some of the deliveries with deliberately introduced errors. The strongest agreement between forward- and back-projection methods is seen in the isocentric intensity/dose difference, with moderate agreement in the mean gamma. The strongest correlation is observed within a given patient, with less correlation between patients, the latter representing the accuracy of prediction of the two methods. The error study shows that each of the two methods has its own distinct sensitivity to errors, but that overall the response is similar. The forward- and back-projection EPID dosimetry methods show moderate agreement in this series of prostate VMAT patients, indicating that both methods can contribute to the verification of dose delivered to the patient.

Normalize the response of EPID in pursuit of linear accelerator dosimetry standardization

Normalize the response of electronic portal imaging device (EPID) is the first step toward an EPID‐based standardization of Linear Accelerator (linac) dosimetry quality assurance. In this study, we described an approach to generate two‐dimensional (2D) pixel sensitivity maps (PSM) for EPIDs response normalization utilizing an alternative beam and dark‐field (ABDF) image acquisition technique and large overlapping field irradiations. The automated image acquisition was performed by XML‐controlled machine operation and the PSM was generated based on a recursive calculation algorithm for Varian linacs equipped with aS1000 and aS1200 imager panels. Cross‐comparisons of normalized beam profiles and 1.5%/1.5 mm 1D Gamma analysis was adopted to quantify the improvement of beam profile matching before and after PSM corrections. PSMs were derived for both photon (6, 10, 15 MV) and electron (6, 20 MeV) beams via proposed method. The PSM‐corrected images reproduced a horn‐shaped profile for photon beams and a relative uniform profiles for electrons. For dosimetrically matched linacs equipped with aS1000 panels, PSM‐corrected images showed increased 1D‐Gamma passing rates for all energies, with an average 10.5% improvement for crossline and 37% for inline beam profiles. Similar improvements in the phantom study were observed with a maximum improvement of 32% for 15 MV and 22% for 20 MeV. The PSM value showed no significant change for all energies over a 3‐month period. In conclusion, the proposed approach correct EPID response for both aS1000 and aS1200 panels. This strategy enables the possibility to standardize linac dosimetry QA and to benchmark linac performance utilizing EPID as the common detector.

Preliminary study of clinical application on IMRT three-dimensional dose verification-based EPID system

The three-dimensional dose (3D) distribution of intensity-modulated radiation therapy (IMRT) was verified based on electronic portal imaging devices (EPIDs), and the results were analyzed. Thirty IMRT plans of different lesions were selected for 3D EPID-based dose verification. The gamma passing rates of the 3D dose verification-based EPID system (Edose, Version 3.01, Raydose, Guangdong, China) and Delta4 measurements were then compared with treatment planning system (TPS) calculations using global gamma criteria of 5%/3 mm, 3%/3 mm, and 2%/2 mm. Furthermore, the dose-volume histograms (DVHs) for planning target volumes (PTVs) as well as organs at risk (OARs) were analyzed using Edose. For dose verification of the 30 treatment plans, the average gamma passing rates of Edose reconstructions under the gamma criteria of 5%/3 mm, 3%/3 mm, and 2%/2 mm were (98.58 ± 0.93)%, (95.67 ± 1.97)%, and (83.13 ± 4.53)%, respectively, whereas the Delta4 measurement results were (99.14% ± 1.16)%, (95.81% ± 2.88)%, and (84.74% ± 7.00)%, respectively. The dose differences between Edose reconstructions and TPS calculations were within 3% for D95% , D98% , and Dmean in each PTV, with the exception that the D98% of the PTV-clinical target volume (CTV) in esophageal carcinoma cases was (3.21 ± 2.33)%. However, the larger dose deviations in OARs (such as lens, parotid gland, optic nerve, and spinal cord) can be determined based on DVHs. The difference was particularly obvious for OARs with small volumes; for example, the maximum dose deviation for the lens reached (-6.12 ± 5.28)%. A comparison of the results obtained with Edose and Delta4 indicated that the Edose system could be applied for 3D pretreatment dose verification of IMRT. This system could also be utilized to evaluate the gamma passing rate of each treatment plan. Furthermore, the detailed dose distributions of PTVs and OARs could be indicated based on DVHs, providing additional reliable data for quality assurance in a clinic setting.

In vivo Portal Imaging Dosimetry Identifies Delivery Errors in Rectal Cancer Radiotherapy on the Belly Board Device

Purpose:

We recently developed a novel, open-source in vivo dosimetry that uses the electronic portal imaging device to detect dose delivery discrepancies. We applied our method on patients with rectal cancer treated on a belly board device.

Methods:

In vivo dosimetry was performed on 10 patients with rectal cancer treated prone on the belly board with a 4-field box arrangement. Portal images were acquired approximately once per week from each treatment beam. Our dosimetry method used these images along with the planning CT to reconstruct patient planar dose at isocenter depth.

Results:

Our algorithm proved sensitive to dose discrepancies and detected discordances in 7 patients. The majority of these were due to soft tissue differences between planning and treatment, present despite matching to bony anatomy. As a result of this work, quality assurance procedures have been implemented for our immobilization devices.

Conclusion:

In vivo dosimetry is a powerful quality assurance tool that can detect delivery discrepancies, including changes in patient setup and position. The added information on actual dose delivery may be used to evaluate equipment and process quality and to guide for adaptive radiotherapy.

A Simple Method for 2-D In Vivo Dosimetry by Portal Imaging

PURPOSE

To improve patient safety and treatment quality, verification of dose delivery in radiotherapy is desirable. We present a simple, easy-to-implement, open-source method for in vivo planar dosimetry of conformal radiotherapy by electronic portal imaging device (EPID).

METHODS

Correlation ratios, which relate dose in the mid-depth of slab phantoms to transit EPID signal, were determined for multiple phantom thicknesses and field sizes. Off-axis dose is corrected for by means of model-based convolution. We tested efficacy of dose reconstruction through measurements with off-reference values of attenuator thickness, field size, and monitor units. We quantified the dose calculation error in the presence of thickness changes to simulate anatomical or setup variations. An example of dose calculation on patient data is provided.

RESULTS

With varying phantom thickness, field size, and monitor units, dose reconstruction was almost always within 3% of planned dose. In the presence of thickness changes from planning CT, the dose discrepancy is exaggerated by up to approximately 1.5% for 1 cm changes upstream of the isocenter plane and 4% for 1 cm changes downstream.

CONCLUSION

Our novel electronic portal imaging device in vivo dosimetry allows clinically accurate 2-dimensional reconstruction of dose inside a phantom/patient at isocenter depth. Due to its simplicity, commissioning can be performed in a few hours per energy and may be modified to the user's needs. It may provide useful dose delivery information to detect harmful errors, guide adaptive radiotherapy, and assure quality of treatment.

Online 3D EPID-based dose verification: Proof of concept

PURPOSE

Delivery errors during radiotherapy may lead to medical harm and reduced life expectancy for patients. Such serious incidents can be avoided by performing dose verification online, i.e., while the patient is being irradiated, creating the possibility of halting the linac in case of a large overdosage or underdosage. The offline EPID-based 3D in vivo dosimetry system clinically employed at our institute is in principle suited for online treatment verification, provided the system is able to complete 3D dose reconstruction and verification within 420 ms, the present acquisition time of a single EPID frame. It is the aim of this study to show that our EPID-based dosimetry system can be made fast enough to achieve online 3D in vivo dose verification.

METHODS

The current dose verification system was sped up in two ways. First, a new software package was developed to perform all computations that are not dependent on portal image acquisition separately, thus removing the need for doing these calculations in real time. Second, the 3D dose reconstruction algorithm was sped up via a new, multithreaded implementation. Dose verification was implemented by comparing planned with reconstructed 3D dose distributions delivered to two regions in a patient: the target volume and the nontarget volume receiving at least 10 cGy. In both volumes, the mean dose is compared, while in the nontarget volume, the near-maximum dose (D2) is compared as well. The real-time dosimetry system was tested by irradiating an anthropomorphic phantom with three VMAT plans: a 6 MV head-and-neck treatment plan, a 10 MV rectum treatment plan, and a 10 MV prostate treatment plan. In all plans, two types of serious delivery errors were introduced. The functionality of automatically halting the linac was also implemented and tested.

RESULTS

The precomputation time per treatment was ∼180 s/treatment arc, depending on gantry angle resolution. The complete processing of a single portal frame, including dose verification, took 266 ± 11 ms on a dual octocore Intel Xeon E5-2630 CPU running at 2.40 GHz. The introduced delivery errors were detected after 5-10 s irradiation time.

CONCLUSIONS

A prototype online 3D dose verification tool using portal imaging has been developed and successfully tested for two different kinds of gross delivery errors. Thus, online 3D dose verification has been technologically achieved.

Clinical Implementation of a Model-Based In Vivo Dose Verification System for Stereotactic Body Radiation Therapy-Volumetric Modulated Arc Therapy Treatments Using the Electronic Portal Imaging Device

PURPOSE

To report findings from an in vivo dosimetry program implemented for all stereotactic body radiation therapy patients over a 31-month period and discuss the value and challenges of utilizing in vivo electronic portal imaging device (EPID) dosimetry clinically.

METHODS AND MATERIALS

From December 2013 to July 2016, 117 stereotactic body radiation therapy-volumetric modulated arc therapy patients (100 lung, 15 spine, and 2 liver) underwent 602 EPID-based in vivo dose verification events. A developed model-based dose reconstruction algorithm calculates the 3-dimensional dose distribution to the patient by back-projecting the primary fluence measured by the EPID during treatment. The EPID frame-averaging was optimized in June 2015. For each treatment, a 3%/3-mm γ comparison between our EPID-derived dose and the Eclipse AcurosXB-predicted dose to the planning target volume (PTV) and the ≥20% isodose volume were performed. Alert levels were defined as γ pass rates <85% (lung and liver) and <80% (spine). Investigations were carried out for all fractions exceeding the alert level and were classified as follows: EPID-related, algorithmic, patient setup, anatomic change, or unknown/unidentified errors.

RESULTS

The percentages of fractions exceeding the alert levels were 22.6% for lung before frame-average optimization and 8.0% for lung, 20.0% for spine, and 10.0% for liver after frame-average optimization. Overall, mean (± standard deviation) planning target volume γ pass rates were 90.7% ± 9.2%, 87.0% ± 9.3%, and 91.2% ± 3.4% for the lung, spine, and liver patients, respectively.

CONCLUSIONS

Results from the clinical implementation of our model-based in vivo dose verification method using on-treatment EPID images is reported. The method is demonstrated to be valuable for routine clinical use for verifying delivered dose as well as for detecting errors.

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.

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.