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.

Extending in aqua portal dosimetry with dose inhomogeneity conversion maps for accurate patient dose reconstruction in external beam radiotherapy.

Background and purpose: In aqua dosimetry with electronic portal imaging devices (EPIDs) allows for dosimetric treatment verification in external beam radiotherapy by comparing EPID-reconstructed dose distributions (EPID_IA) with dose distributions calculated with the treatment planning system in water-equivalent geometries. The main drawback of the method is the inability to estimate the dose delivered to the patient. In this study, an extension to the method is presented to allow for patient dose reconstruction in the presence of inhomogeneities. Materials and methods: EPID_IA dose distributions were converted into patient dose distributions (EPID_IA_MC) by applying a 3D dose inhomogeneity conversion, defined as the ratio between patient and water-filled patient dose distributions computed using Monte Carlo calculations. EPID_IA_MC was evaluated against dose distributions calculated with a collapsed cone convolution superposition (CCCS) algorithm and with a GPU-based Monte Carlo dose calculation platform (GPUMCD) using non-transit EPID measurements of 25 plans. In vivo EPID measurements of 20 plans were also analyzed. Results: In the evaluation of EPID_IA_MC, the average γ-mean values (2% local/2mm, 50% isodose volume) were 0.70 ± 0.14 (1SD) and 0.66 ± 0.10 (1SD) against CCCS and GPUMCD, respectively. Percentage differences in median dose to the planning target volume were within 3.9% and 2.7%, respectively. The number of in vivo dosimetric alerts with EPID_IA_MC was comparable to EPID_IA. Conclusions: EPID_IA_MC accommodates accurate patient dose reconstruction for treatment disease sites with significant tissue inhomogeneities within a simple EPID-based direct dose back-projection algorithm, and helps to improve the clinical interpretation of both pre-treatment and in vivo dosimetry results.

Automatic dosimetric verification of online adapted plans on the Unity MR-Linac using 3D EPID dosimetry.

BACKGROUND AND PURPOSE: The Unity MR-Linac is equipped with an EPID, the images from which contain information about the dose delivered to the patient. The purpose of this study was to introduce a framework for the automatic dosimetric verification of online adapted plans using 3D EPID dosimetry and to present the obtained dosimetric results. MATERIALS AND METHODS: The framework was active during the delivery of 1207 online adapted plans corresponding to 127 clinical IMRT treatments (74 prostate, 19 rectum, 19 liver and 15 lymph node oligometastases). EPID reconstructed dose distributions in the patient geometry were calculated automatically and then compared to the dose distributions calculated online by the treatment planning system (TPS). The comparison was performed by γ-analysis (3% global/2mm/10% threshold) and by the difference in median dose to the high-dose volume (ΔHDVD50). 85% for γ-pass rate and 5% for ΔHDVD50 were used as tolerance limit values. RESULTS: 93% of the online plans were verified automatically by the framework. Missing EPID data was the reason for automation failure. 91% of the verified plans were within tolerance. CONCLUSION: Automatic dosimetric verification of online adapted plans on the Unity MR-Linac is feasible using in vivo 3D EPID dosimetry. Almost all online adapted plans were approved automatically by the framework. This newly developed framework is a major step forward towards the clinical implementation of a permanent safety net for the entire online adaptive workflow.

Characterization of Gas Electron Multiplier-based detector for external beam radiation therapy dosimetry.

PURPOSE: Electronic portal imaging devices (EPIDs) are commonly installed on modern linear accelerators (LINACs) and are convenient for imaging and, potentially, dosimetry. However, owing to their construction with metal and scintillating layers of high atomic number, they exhibit nonwater-equivalent response and oversensitivity to low-energy photons. Therefore, EPIDs are not ideal for dosimetry purposes. Additionally, nonlinearities due to the combined use of scintillators and photodiodes have been reported. Here, an EPID which employs a variable gain Gas Electron Multiplier (GEM) and direct detection of electrons is introduced. To investigate its dosimetric performance, measurements characterizing the novel EPID are performed and compared with measurements from ionization chambers and conventional EPIDs. METHODS: Linearity, dose rate dependence, field size dependence, off-axis response, and transmission response were measured for all available energy settings (6, 10, 6 MV Flattening Filter Free (FFF) and 10 MVFFF) using three different detector gain settings. Additionally, an evaluation of the ghosting and image lag of the panel was completed. Reference ionization chamber measurements were performed for the off-axis and transmission response and existing data for conventional EPIDs and ionization chambers from equivalent measurements were used for comparison of the field size dependence. Elsewhere, values from the linac monitoring chambers were used. RESULTS: In the range from 10 to 1000 Monitor Units (MU), the detector was linear within 1% for all combinations of gain settings and energies. The dose rate dependence was also within 1% for all energies and for two out of three gain settings. Regarding field size dependency, the ratio of ionization chamber and panel values was 0.94 and 0.98 for the conventional EPID and GEMini respectively, at 20 × 20 cm2 and 10 MV. For 6 MV, 6 MVFFF, and 10MVFFF these ratios were 0.97, 0.98, and 0.99 for the GEMini, and 0.95, 0.97, and 0.97 for the conventional EPID. Similar performance between the GEMini and conventional EPID is observed for field sizes smaller than 10 × 10 cm2 . The transmission response was within 5% for all energies for thicknesses up to 30 cm, compared to 10-20% for a conventional EPID. The off-axis response for shifts up to 16 cm was within 1% and 3% for 6 MV and 10 MV, with and without phantom. The rise and fall of the signal from the detector correspond well to monitor chamber measurements indicating little ghosting and image lag, regardless of gain setting. CONCLUSION: The GEM EPID exhibits dose rate dependence and linearity within 1%, and negligible ghosting and image lag. In this regard, it performs particularly well using 50 and 250 V of gain, and either could be chosen. For higher sensitivity, 250 V is the recommended base gain setting, although other applications may warrant different gains. For most tests performed in this study, the GEM EPID demonstrates a more water-equivalent response than conventional EPIDs making GEMs a viable technology for dosimetry in radiation therapy.

Portal dosimetry of small unflattened beams.

We developed and validated a dedicated small field back-projection portal dosimetry model for pretreatment andin vivoverification of stereotactic plans entailing small unflattened photon beams. For this purpose an aSi-EPID was commissioned as a small field dosimeter. Small field output factors for 6 MV FFF beams were measured using the PTW microDiamond detector and the Agility 160-leaf MLC from Elekta. The back-projection algorithm developed in our department was modified to better model the small field physics. The feasibility of small field portal dosimetry was validated via absolute point dose differences w.r.t. small static beams, and 5 hypofractionated stereotactic VMAT clinical plans measured with the OCTAVIUS 1000 SRS array dosimeter and computed with the treatment planning system Pinnacle v16.2. Dose reconstructions using the currently clinically applied back-projection model were also computed for comparison. We found that the latter yields underdosage of about -8% for square beams with cross section near 10 mm x 10 mm and about -6% for VMAT treatments with PTV volumes smaller than about 2cm3. With the methods described in this work such errors can be reduced to less than the ±3.0% recommendations for clinical use. Our results indicate that aSi-EPIDs can be used as accurate small field radiation dosimeters, offering advantages over point dose detectors, the correct positioning and orientation of which is challenging for routine clinical QA.

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 ΔDRP = -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 ΔDRP = -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 ΔDRP = 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.

A Deep Learning-based correction to EPID dosimetry for attenuation and scatter in the Unity MR-Linac system.

PURPOSE: EPID dosimetry in the Unity MR-Linac system allows for reconstruction of absolute dose distributions within the patient geometry. Dose reconstruction is accurate for the parts of the beam arriving at the EPID through the MRI central unattenuated region, free of gradient coils, resulting in a maximum field size of ~10 × 22 cm2 at isocentre. The purpose of this study is to develop a Deep Learning-based method to improve the accuracy of 2D EPID reconstructed dose distributions outside this central region, accounting for the effects of the extra attenuation and scatter. METHODS: A U-Net was trained to correct EPID dose images calculated at the isocenter inside a cylindrical phantom using the corresponding TPS dose images as ground truth for training. The model was evaluated using a 5-fold cross validation procedure. The clinical validity of the U-Net corrected dose images (the so-called DEEPID dose images) was assessed with in vivo verification data of 45 large rectum IMRT fields. The sensitivity of DEEPID to leaf bank position errors (±1.5 mm) and ±5% MU delivery errors was also tested. RESULTS: Compared to the TPS, in vivo 2D DEEPID dose images showed an average γ-pass rate of 90.2% (72.6%-99.4%) outside the central unattenuated region. Without DEEPID correction, this number was 44.5% (4.0%-78.4%). DEEPID correctly detected the introduced delivery errors. CONCLUSIONS: DEEPID allows for accurate dose reconstruction using the entire EPID image, thus enabling dosimetric verification for field sizes up to ~19 × 22 cm2 at isocentre. The method can be used to detect clinically relevant errors.

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.

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 |ΔPTVD50 | > 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.

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.

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.

Site-specific alert criteria to detect patient-related errors with 3D EPID transit dosimetry.

PURPOSE: To assess the sensitivity of various EPID dosimetry alert indicators to patient-related variations and to determine alert threshold values that ensure excellent error detectability. METHODS: Our virtual dose reconstruction method uses in air EPID measurements to calculate virtual 3D dose distributions within a CT data set. Patient errors are introduced by transforming the plan-CT into an error-CT data set. Virtual patient dose distributions reconstructed using the plan-CT and the error-CT data set are compared to the planned dose distributions by γ(3%/3 mm) and DVH analysis using seven indicators: ΔDISOC , γ-mean, near γ-max, γ-pass rate, ΔPTVD 2 , ΔPTVD 50, and ΔPTVD 98 . Translation and rotation patient setup errors and uniform contour changes are studied for 104 VMAT plans of 4 treatment sites. Lung expansions and contractions to simulate changes in lung density are considered for 26 IMRT lung plans. A ROC curve is generated for each combination of error and indicator. For each ROC curve, the AUC value and the optimal alert threshold value of the indicator are determined. RESULTS: AUC values for γ-indicators and ΔPTVD 2 are consistently higher than for ΔDISOC and ΔPTVD 98 . For VMAT plans, error detectability to patient position shifts is worse for pelvic treatments and best for head-and-neck and brain plans. Excellent detectability is observed for 5 mm translations in head-and-neck plans (AUC = 0.94) and for 4° rotations in brain plans (AUC = 0.89). All sites but prostate show good-to-excellent detectability (AUC > 0.8) for 10 mm translations and 8° rotations and excellent detectability (AUC > 0.9) for ±6 mm patient contour changes. For head-and-neck, excellent detectability is obtained with γ-mean and γ-pass rate threshold values of around 0.63 and 83%, respectively. For brain and rectum, these threshold values are 0.53 and 90%, respectively. In IMRT lung plans, expansions of 3 mm and contractions of 6 mm are detected (AUC > 0.8). CONCLUSIONS: By combining virtual dose reconstructions with synthetic patient data, we developed a framework to assess the sensitivity of our 3D EPID transit dosimetry method to patient-related variations. The detectability of each introduced error is specific to the treatment site and indicator used. Optimal alert criteria can be determined to ensure excellent detectability for each combination of error type and indicator. The alert threshold values and the magnitude of the error that can be detected are site-specific. In situations where the minimum error that can be detected is larger than the clinically desirable action level, EPID transit dosimetry must be used in combination with IGRT procedures to ensure correct patient positioning and early detection of anatomy variations.

Comparison of gamma- and DVH-based in vivo dosimetric plan evaluation for pelvic VMAT treatments.

BACKGROUND AND PURPOSE: To compare DVH-based quality assurance to a multi-parametric γ-based methodology for in vivo EPID dosimetry for VMAT to the pelvis. MATERIALS AND METHODS: For 47 rectum, 37 prostate, and 44 bladder VMAT treatments we reconstructed the 3D dose distributions of 387 fractions from in vivo EPID dosimetry. The difference between planned and measured dose was evaluated using γ analysis (3%/3mm) in the 50% isodose volume (IDV) and DVH differences (ΔD2, ΔD50 and ΔD98) of targets and organs at risk. The γ-indicators mean γ, γ pass rate and γ1% were compared to DVH-differences and their correlations were studied. DVH-based alerts on PTV and IDV were compared to γ-based alerts. RESULTS: Average PTV D50 and D98 dose differences were 0.0±2.2% (1SD) and -1.4±2.9% (1SD). Alert criteria of |ΔD50|<3.5-4.5% corresponded to an alert rate of about 10%. Strong correlations between mean γ and γ pass rate and difference in PTV ΔD50 were observed for all sites. DVH- and γ-based alerts agreed on >80% of the fractions for the majority of compared alert thresholds and methods. This agreement is >90% for the larger deviations. CONCLUSIONS: Strong correlations between some γ- and DVH indicators were found. Our comparison of multi-parametric alert strategies showed clinical equivalence for γ- and DVH-based methods.

Virtual patient 3D dose reconstruction using in air EPID measurements and a back-projection algorithm for IMRT and VMAT treatments.

PURPOSE: At our institute, a transit back-projection algorithm is used clinically to reconstruct in vivo patient and in phantom 3D dose distributions using EPID measurements behind a patient or a polystyrene slab phantom, respectively. In this study, an extension to this algorithm is presented whereby in air EPID measurements are used in combination with CT data to reconstruct 'virtual' 3D dose distributions. By combining virtual and in vivo patient verification data for the same treatment, patient-related errors can be separated from machine, planning and model errors. METHODS AND MATERIALS: The virtual back-projection algorithm is described and verified against the transit algorithm with measurements made behind a slab phantom, against dose measurements made with an ionization chamber and with the OCTAVIUS 4D system, as well as against TPS patient data. Virtual and in vivo patient dose verification results are also compared. RESULTS: Virtual dose reconstructions agree within 1% with ionization chamber measurements. The average γ-pass rate values (3% global dose/3mm) in the 3D dose comparison with the OCTAVIUS 4D system and the TPS patient data are 98.5±1.9%(1SD) and 97.1±2.9%(1SD), respectively. For virtual patient dose reconstructions, the differences with the TPS in median dose to the PTV remain within 4%. CONCLUSIONS: Virtual patient dose reconstruction makes pre-treatment verification based on deviations of DVH parameters feasible and eliminates the need for phantom positioning and re-planning. Virtual patient dose reconstructions have additional value in the inspection of in vivo deviations, particularly in situations where CBCT data is not available (or not conclusive).

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.

Overview of 3-year experience with large-scale electronic portal imaging device-based 3-dimensional transit dosimetry.

PURPOSE: To assess the usefulness of electronic portal imaging device (EPID)-based 3-dimensional (3D) transit dosimetry in a radiation therapy department by analyzing a large set of dose verification results. METHODS AND MATERIALS: In our institution, routine in vivo dose verification of all treatments is performed by means of 3D transit dosimetry using amorphous silicon EPIDs. The total 3D dose distribution is reconstructed using a back-projection algorithm and compared with the planned dose distribution using 3D gamma evaluation. Dose reconstruction and gamma evaluation software runs automatically in our clinic, and analysis results are (almost) immediately available. If a deviation exceeds our alert criteria, manual inspection is required. If necessary, additional phantom measurements are performed to separate patient-related errors from planning or delivery errors. Three-dimensional transit dosimetry results were analyzed per treatment site between 2012 and 2014 and the origin of the deviations was assessed. RESULTS: In total, 4689 of 15,076 plans (31%) exceeded the alert criteria between 2012 and 2014. These alerts were patient-related and attributable to limitations of our back-projection and dose calculation algorithm or to external sources. Clinically relevant deviations were detected for approximately 1 of 430 patient treatments. Most of these errors were because of anatomical changes or deviations from the routine clinical procedure and would not have been detected by pretreatment verification. Although cone beam computed tomography scans yielded information about anatomical changes, their effect on the dose delivery was assessed quantitatively by means of 3D in vivo dosimetry. CONCLUSIONS: EPID-based transit dosimetry is a fast and efficient dose verification technique. It provides more useful information and is less time-consuming than pretreatment verification measurements of intensity modulated radiation therapy and volumetric modulated arc therapy. Large-scale implementation of 3D transit dosimetry is therefore a powerful method to guarantee safe dose delivery during radiation therapy.

Portal dosimetry in wedged beams.

Portal dosimetry using electronic portal imaging devices (EPIDs) is often applied to verify high-energy photon beam treatments. Due to the change in photon energy spectrum, the resulting dose values are, however, not very accurate in the case of wedged beams if the pixel-to-dose conversion for the situation without wedge is used. A possible solution would be to consider a wedged beam as another photon beam quality requiring separate beam modeling of the dose calculation algorithm. The aim of this study was to investigate a more practical solution: to make aSi EPID-based dosimetry models also applicable for wedged beams without an extra commissioning effort of the parameters of the model. For this purpose two energy-dependent wedge multiplication factors have been introduced to be applied for portal images taken with and without a patient/phantom in the beam. These wedge multiplication factors were derived from EPID and ionization chamber measurements at the EPID level for wedged and nonwedged beams, both with and without a polystyrene slab phantom in the beam. This method was verified for an EPID dosimetry model used for wedged beams at three photon beam energies (6, 10, and 18 MV) by comparing dose values reconstructed in a phantom with data provided by a treatment planning system (TPS), as a function of field size, depth, and off-axis distance. Generally good agreement, within 2%, was observed for depths between dose maximum and 15 cm. Applying the new model to EPID dose measurements performed during ten breast cancer patient treatments with wedged 6 MV photon beams showed that the average isocenter underdosage of 5.3% was reduced to 0.4%. Gamma-evaluation (global 3%/3 mm) of these in vivo data showed an increase in percentage of points with γ ≤ 1 from 60.2% to 87.4%, while γmean reduced from 1.01 to 0.55. It can be concluded that, for wedged beams, the multiplication of EPID pixel values with an energy-dependent correction factor provides good agreement between dose values determined by an EPID and a TPS, indicating the usefulness of such a practical solution.

Clinical implementation and rapid commissioning of an EPID based in-vivo dosimetry system.

Using an Electronic Portal Imaging Device (EPID) to perform in-vivo dosimetry is one of the most effective and efficient methods of verifying the safe delivery of complex radiotherapy treatments. Previous work has detailed the development of an EPID based in-vivo dosimetry system that was subsequently used to replace pre-treatment dose verification of IMRT and VMAT plans. Here we show that this system can be readily implemented on a commercial megavoltage imaging platform without modification to EPID hardware and without impacting standard imaging procedures. The accuracy and practicality of the EPID in-vivo dosimetry system was confirmed through a comparison with traditional TLD in-vivo measurements performed on five prostate patients.The commissioning time required for the EPID in-vivo dosimetry system was initially prohibitive at approximately 10 h per linac. Here we present a method of calculating linac specific EPID dosimetry correction factors that allow a single energy specific commissioning model to be applied to EPID data from multiple linacs. Using this method reduced the required per linac commissioning time to approximately 30 min.The validity of this commissioning method has been tested by analysing in-vivo dosimetry results of 1220 patients acquired on seven linacs over a period of 5 years. The average deviation between EPID based isocentre dose and expected isocentre dose for these patients was (-0.7  ±  3.2)%.EPID based in-vivo dosimetry is now the primary in-vivo dosimetry tool used at our centre and has replaced nearly all pre-treatment dose verification of IMRT treatments.

In aqua vivo EPID dosimetry.

PURPOSE: At the Netherlands Cancer Institute--Antoni van Leeuwenhoek Hospital in vivo dosimetry using an electronic portal imaging device (EPID) has been implemented for almost all high-energy photon treatments of cancer with curative intent. Lung cancer treatments were initially excluded, because the original back-projection dose-reconstruction algorithm uses water-based scatter-correction kernels and therefore does not account for tissue inhomogeneities accurately. The aim of this study was to test a new method, in aqua vivo EPID dosimetry, for fast dose verification of lung cancer irradiations during actual patient treatment. METHODS: The key feature of our method is the dose reconstruction in the patient from EPID images, obtained during the actual treatment, whereby the images have been converted to a situation as if the patient consisted entirely of water; hence, the method is termed in aqua vivo. This is done by multiplying the measured in vivo EPID image with the ratio of two digitally reconstructed transmission images for the unit-density and inhomogeneous tissue situation. For dose verification, a comparison is made with the calculated dose distribution with the inhomogeneity correction switched off. IMRT treatment verification is performed for each beam in 2D using a 2D γ evaluation, while for the verification of volumetric-modulated arc therapy (VMAT) treatments in 3D a 3D γ evaluation is applied using the same parameters (3%, 3 mm). The method was tested using two inhomogeneous phantoms simulating a tumor in lung and measuring its sensitivity for patient positioning errors. Subsequently five IMRT and five VMAT clinical lung cancer treatments were investigated, using both the conventional back-projection algorithm and the in aqua vivo method. The verification results of the in aqua vivo method were statistically analyzed for 751 lung cancer patients treated with IMRT and 50 lung cancer patients treated with VMAT. RESULTS: The improvements by applying the in aqua vivo approach are considerable. The percentage of γ values ≤1 increased on average from 66.2% to 93.1% and from 43.6% to 97.5% for the IMRT and VMAT cases, respectively. The corresponding mean γ value decreased from 0.99 to 0.43 for the IMRT cases and from 1.71 to 0.40 for the VMAT cases, which is similar to the accepted clinical values for the verification of IMRT treatments of prostate, rectum, and head-and-neck cancers. The deviation between the reconstructed and planned dose at the isocenter diminished on average from 5.3% to 0.5% for the VMAT patients and was almost the same, within 1%, for the IMRT cases. The in aqua vivo verification results for IMRT and VMAT treatments of a large group of patients had a mean γ of approximately 0.5, a percentage of γ values ≤1 larger than 89%, and a difference of the isocenter dose value less than 1%. CONCLUSIONS: With the in aqua vivo approach for the verification of lung cancer treatments (IMRT and VMAT), we can achieve results with the same accuracy as obtained during in vivo EPID dosimetry of sites without large inhomogeneities.