Reduction of systematic dosimetric uncertainties in volumetric modulated arc therapy triggered by patient-specific quality assurance.

BACKGROUND AND PURPOSE: Dosimetric patient-Specific Quality Assurance (PSQA) data contain in addition to cases with alerts, many cases without alerts. The aim of this study was to present a procedure to investigate long-term trend analysis of the complete set of PSQA data for the presence of site-specific deviations to reduce underlying systematic dose uncertainties. MATERIALS AND METHODS: The procedure started by analysing a large set of prostate Volumetric Modulated Arc Therapy (VMAT) PSQA data obtained by comparing 3D electronic portal image device (EPID)_based in vivo dosimetry measurements with dose values predicted by the Treatment Planning System (TPS). If systematic deviations were present, several actions were required. These included confirmation of these deviations with an independent dose verification system for which a 2D detector array in a phantom was used, and analysing calculated with measured PSQA data, or delivery machine characteristics. Further analysis revealed that the under-dosage correlated with plan complexity and coincided with changes in clinically applied planning techniques. RESULTS: Prostate VMAT PSQA data showed an under-dosage gradual increasing to about 2% in 3 years, which was confirmed by the measurements with the 2D detector array in a phantom. The implementation of new beam fits in the TPS led to a reduction of the observed deviations. CONCLUSION: Long-term analysis of site-specific PSQA data is a useful method to monitor incremental changes in a radiotherapy department due to various changes in the treatment planning and delivery of prostate VMAT, and may lead to a reduction of systematic dose uncertainties in complex treatments.

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.

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.

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.

Impact of daily anatomical changes on EPID-based in vivo dosimetry of VMAT treatments of head-and-neck cancer.

BACKGROUND AND PURPOSE: Target dose verification for VMAT treatments of head-and-neck (H&N) cancer using 3D in vivo EPID dosimetry is expected to be affected by daily anatomical changes. By including these anatomical changes through cone-beam CT (CBCT) information, the magnitude of this effect is investigated. MATERIALS AND METHODS: For 20 VMAT-treated H&N cancer patients, all plan-CTs (pCTs), 633 CBCTs and 1266 EPID movies were used to compare four dose distributions per fraction: treatment planning system (TPS) calculated dose and EPID reconstructed in vivo dose, both determined using the pCT and using the CBCT. D2, D50 and D98 of the planning target volume (PTV) were determined per dose distribution. RESULTS: When including daily anatomical information, D2, D50 and D98 of the PTV change on average by 0.0±0.4% according to TPS calculations; the standard deviation of the difference between EPID and TPS target dose changes from 2.5% (pCT) to 2.1% (CBCT). Small time trends are seen for both TPS and EPID dose distributions when using the pCT, which disappear when including CBCT information. CONCLUSIONS: Daily anatomical changes hardly influence the target dose distribution for H&N VMAT treatments according to TPS recalculations. Including CBCT information in EPID dose reconstructions slightly improves the agreement with TPS calculations.

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.

In vivo portal dosimetry for head-and-neck VMAT and lung IMRT: linking γ-analysis with differences in dose-volume histograms of the PTV.

PURPOSE: To relate the results of γ-analysis and dose-volume histogram (DVH) analysis of the PTV for detecting dose deviations with in vivo dosimetry for two treatment sites. METHODS AND MATERIALS: In vivo 3D dose distributions were reconstructed for 722 fractions of 200 head-and-neck (H&N) VMAT treatments and 183 fractions of 61 lung IMRT plans. The reconstructed and planned dose distributions in the PTV were compared using (a) the γ-distribution and (b) the differences in D2, D50 and D98 between the two dose distributions. Using pre-defined tolerance levels, all fractions were classified as deviating or not deviating by both methods. The mutual agreement, the sensitivity and the specificity of the two methods were compared. RESULTS: For lung IMRT, the classification of the fractions was nearly identical for γ- and DVH-analyses of the PTV (94% agreement) and the sensitivity and specificity were comparable for both methods. Less agreement (80%) was found for H&N VMAT, while γ-analysis was both less sensitive and less specific. CONCLUSIONS: DVH- and γ-analyses perform nearly equal in finding dose deviations in the PTV for lung IMRT treatments; for H&N VMAT treatments, DVH-analysis is preferable. As a result of this study, a smooth transition to using DVH-analysis clinically for detecting in vivo dose deviations in the PTV is within reach.