Monitoring daily MLC positional errors using trajectory log files and EPID measurements for IMRT and VMAT deliveries

ONLINE ADAPTIVE FIVE-FRACTION ABLATIVE RADIOTHERAPY FOR PROSTATE CANCER USING A CONVENTIONAL LINEAR ACCELERATOR

AIM

To assess the dosimetric results of an online adaptive stereotactic body radiotherapy (SBRT) program to treat patients with prostate cancer using a conventional linear accelerator.

METHODS AND MATERIALS

Prostate SBRT with five fractions is performed at the XXXX using an online adaptive method previously described (XXXX). A CBCT based adaptive "plan-of-the-day" (POD) is generated for each treatment fraction, which consists of a single volumetric modulated arc therapy. A dosimetric evaluation of the PODs was performed for the first twenty patients and included analysis of the target (prostate), organs-at-risks (OARs), and patient-specific quality assurance (PSQA). Each of the PODs was also compared with the corresponding conventional image-guided radiotherapy (IGRT) method. Finally, the adaptive treatment timing is analyzed for the one hundred PODs in this study RESULTS: The online adaptive treatment method ensured optimal target coverage in all treatment fractions for all patients. However, the simulated IGRT plans did not result in adequate prostate coverage (V40 Gy ≥ 95%) in 70% of fractions. Small average differences between PODs and IGRT plans were found in the OARs. The dose sparing in the rectum and bladder provided by some simulated IGRT plans, was associated with a compromised prostate coverage. The PSQA resulted in an excellent agreement between the online-calculated plans and the independent dose checks performed for all one hundred PODs. The average duration of the plan adaptation was 20.1 ± 6.1 minutes and the average overall session time including adaptation and treatment delivery was 26.4 ± 33.2 minutes.

CONCLUSIONS

This study demonstrates The online adaptive program using a conventional linac to treat prostate cancer described in this study is clinically feasible and in adherence with the acceptance criteria set by the PACE B.

TRIAL

Evaluation of an improved picket fence style test for routine MLC positional QA

PURPOSE

The aim was to develop and evaluate an EPID-based MLC positional test that addresses known weaknesses of the picket fence test and has sufficient accuracy so that the AAPM MPPG 8.b. MLC position action limit of ± 0.5 mm can be implemented.

METHODS

Weaknesses and inaccuracies in the picket fence test were identified and a new test plan and analysis algorithm named stakitt was developed. Stakitt was evaluated for repeatability and for sensitivity on the Varian TrueBeam linac with both Millennium MLC and HDMLC and on a Varian Clinac with Millennium MLC. Sensitivity was tested via deliberate introduction of errors into the test plan of magnitude: ± 0.1, ± 0.5, ± 1.0 and ± 1.5 mm. Measured sensitivity was compared to published sensitivity of the picket fence test. Additionally, a use case was presented based on results from a TrueBeam linac to highlight the effect of MLC backlash on MLC positions at non-zero gantry angles.

RESULTS

Repeatability was observed to within 0.04 mm (3 SD) with the TrueBeams being more repeatable than the Clinac. The deliberately introduced errors were accurately measured to within 0.28 mm and were comparable to the traditional picket fence. Reduced accuracy was recorded for the HDMLC small leaves, which was attributed to an apparent variation in measured leaf width across the range of travel, which impacted the measurement of the leaf tip position. The clinical use case demonstrated variability in MLC leaf positions between gantry 90° and gantry 270° that were of the magnitude of the MLC backlash.

CONCLUSION

The stakitt test addresses the weaknesses of the picket fence test and has accuracy appropriate for implementation of a ± 0.5 mm action limit. However, such an action limit may not be currently practical at non-zero gantry angles due to the impact of MLC leaf backlash.

Development of a new VMAT QA framework for Mobius3D using control-point specific EPID images

Purpose

This study presents novel quality assurance (QA) approach for volumetric modulated arc therapy (VMAT) that leverages frame-by-frame electronic portal imaging device (EPID) images integrated into Mobius3D for accurate three-dimensional dose calculations.

Methods

Sequential EPID images for VMAT plans were acquired every 0.4-second by iView system and processed through iterative deconvolution to mitigate blurring from photon scattering. Deconvolved images were binarized to define multi-leaf collimator (MLC) positions. Pre-acquired box fluences determined optimal threshold for binarization and adjusted for detector shift depending on gantry and collimator angles. Sequential EPID images were re-scaled using pixel scaling factor (PSF) and converted to monitor unit (MU) proportional values. Generated EPID-based log file, including control-point specific MLC and monitor units (MU) information, were analyzed in Mobius3D for Gamma passing rate (GPR) of VMAT plans from 18 patients. Plan complexity indices were calculated and correlated with GPR.

Results

Clinically appropriate threshold was defined to be 20000 that can extract accurate MLC data from the deconvolved binarized EPID images. Positional deviations due to gantry and collimator rotations were observed to be up to 4.5 pixels. Recalibrated EPID pixel values showed linearity with MU regardless of changes in dose rate. Consequently, average GPR for 18 patients evaluated using Mobius3D reached 95.2% ± 3.7%%, based on 3% dose difference and 3mm distance-to-agreement criterion. It was found that two plan complexity indices showed statistically significant correlation with GPR.

Conclusion

This study successfully implemented novel measurement-based VMAT QA framework based on control-point specific EPID, based upon accurate MLC and MU data at each frame.

Is it still necessary to perform measured based pre-treatment patient-specific QA for SRS HyperArc treatments?

PURPOSE

The Mobius3D system was validated as a modern secondary check dosimetry system. In particular, our objective has been to assess the suitability of the M3D as pre-treatment patient-specific Quality Assurance (QA) tool for Stereotactic Radiosurgery (SRS) HyperArc (HA) treatments. We aimed to determine whether Mobius3D could safely replace the measurements-based patient-specific QA for this type of treatment.

METHODS

30 SRS HA treatment plans for brain were selected. The dose distributions, calculated by Mobius and our routinely used algorithm (AcurosXB v.15.6), were compared using gamma analysis index and DVH parameters based on the patient's CT dataset. All 30 plans were then delivered across the ionization chamber in a homogeneous phantom and the measured dose was compared with both M3D and TPS calculated one. The plans were delivered and verified in terms of PSQA using the electronic portal imaging device (EPID) with Portal Dosimetry (PD) and myQA SRS (IBA Dosimetry) detector. Plans that achieved a global gamma passing rate (GPR) ≥ 97% based on 2%/2 mm criteria, with both Mobius3D and the conventional methods were evaluated acceptable. Finally, we assessed the capability of the M3D system to detect errors related to the position of the Multi-Leaf Collimator (MLC) in comparison to the analyzed measurement-based systems.

RESULTS

No relevant differences were observed in the comparison between the dose calculated on the CT-dataset by M3D and the TPS. Observed discrepancies are imputable to different used algorithms, but no discrepancies related to goodness of plans have been found. Average differences between calculated (M3D and TPS) vs measured dose with ionization chamber were 2.5% (from 0.41% to 3.2%) and 1.81% (from 0.66% to 2.65%), for M3D and TPS, respectively. All plans passed with a gamma passing rate > 97% using conventional PSQA methods with a gamma criterion of 2% dose difference and 2 mm distance-to-agreement. The average gamma passing rate for the M3D system was determined to be 99.4% (from 97.3% to 100%). Results from this study also demonstrated Mobius has better error detectability than conventional measurement-based systems.

CONCLUSION

Our study shows Mobius3D could be a suitable alternative to conventional measured based QA methods for SRS HyperArc treatments.

A feasibility study to predict 3D dose delivery accuracy for IMRT using DenseNet with log files

OBJECTIVE

This study aims to explore the feasibility of DenseNet in the establishment of a three-dimensional (3D) gamma prediction model of IMRT based on the actual parameters recorded in the log files during delivery.

METHODS

A total of 55 IMRT plans (including 367 fields) were randomly selected. The gamma analysis was performed using gamma criteria of 3% /3 mm (Dose Difference/Distance to Agreement), 3% /2 mm, 2% /3 mm, and 2% /2 mm with a 10% dose threshold. In addition, the log files that recorded the gantry angle, monitor units (MU), multi-leaf collimator (MLC), and jaws position during delivery were collected. These log files were then converted to MU-weighted fluence maps as the input of DenseNet, gamma passing rates (GPRs) under four different gamma criteria as the output, and mean square errors (MSEs) as the loss function of this model.

RESULTS

Under different gamma criteria, the accuracy of a 3D GPR prediction model decreased with the implementation of stricter gamma criteria. In the test set, the mean absolute error (MAE) of the prediction model under the gamma criteria of 3% /3 mm, 2% /3 mm, 3% /2 mm, and 2% /2 mm was 1.41, 1.44, 3.29, and 3.54, respectively; the root mean square error (RMSE) was 1.91, 1.85, 4.27, and 4.40, respectively; the Sr was 0.487, 0.554, 0.573, and 0.506, respectively. There was a correlation between predicted and measured GPRs (P < 0.01). Additionally, there was no significant difference in the accuracy between the validation set and the test set. The accuracy in the high GPR group was high, and the MAE in the high GPR group was smaller than that in the low GPR group under four different gamma criteria.

CONCLUSIONS

In this study, a 3D GPR prediction model of patient-specific QA using DenseNet was established based on log files. As an auxiliary tool for 3D dose verification in IMRT, this model is expected to improve the accuracy and efficiency of dose validation.

Feasibility study of a scintillation sheet-based detector for fluence monitoring during external photon beam radiotherapy

PURPOSE

This study evaluated the properties of a scintillation sheet-based dosimetry system for beam monitoring with high spatial resolution, including the effects of this system on the treatment beam. The dosimetric characteristics and feasibility of this system for clinical use were also evaluated.

METHODS

The effects of the dosimetry system on the beam were evaluated by measuring the percentage depth doses, dose profiles, and transmission factors. Fifteen treatment plans were created, and the influence of the dosimetry system on these clinical treatment plans was evaluated. The performance of the system was assessed by determining signal linearity, dose rate dependence, and reproducibility. The feasibility of the system for clinical use was evaluated by comparing intensity distributions with reference intensity distributions verified by quality assurance.

RESULTS

The spatial resolution of the dosimetry system was found to be 0.43 mm/pixel when projected to the isocenter plane. The dosimetry system attenuated the intensity of 6 MV beams by about 1.1%, without affecting the percentage depth doses and dose profiles. The response of the dosimetry system was linear, independent of the dose rate used in the clinic, and reproducible. Comparison of intensity distributions of evaluation treatment fields with reference intensity distributions showed that the 1%/1 mm average gamma passing rate was 99.6%.

CONCLUSIONS

The dosimetry system did not significantly alter the beam characteristics, indicating that the system could be implemented by using only a transmission factor. The dosimetry system is clinically suitable for monitoring treatment beam delivery with higher spatial resolution than other transmission detectors.

Application of error classification model using indices based on dose distribution for characteristics evaluation of multileaf collimator position errors

This study aims to evaluate the specific characteristics of various multileaf collimator (MLC) position errors that are correlated with the indices using dose distribution. The dose distribution was investigated using the gamma, structural similarity, and dosiomics indices. Cases from the American Association of Physicists in Medicine Task Group 119 were planned, and systematic and random MLC position errors were simulated. The indices were obtained from distribution maps and statistically significant indices were selected. The final model was determined when all values of the area under the curve, accuracy, precision, sensitivity, and specificity were higher than 0.8 (p < 0.05). The dose-volume histogram (DVH) relative percentage difference between the error-free and error datasets was examined to investigate clinical relations. Seven multivariate predictive models were finalized. The common significant dosiomics indices (GLCM Energy and GLRLM_LRHGE) can characterize the MLC position error. In addition, the finalized logistic regression model for MLC position error prediction showed excellent performance with AUC > 0.9. Furthermore, the results of the DVH were related to dosiomics analysis in that it reflects the characteristics of the MLC position error. It was also shown that dosiomics analysis could provide important information on localized dose-distribution differences in addition to DVH information.

Clinical implementation of a log file-based machine and patient QA system for IMRT and VMAT treatment plans

PURPOSE

To determine the error detection sensitivity of a commercial log file-based system (LINACWatch®, LW) for integration into clinical routine and to compare it with a measurement device (OCTAVIUS 4D, Oct4D) for IMRT and VMAT delivery QA.

MATERIALS AND METHODS

76 VMAT/IMRT plans (H&N, prostate, rectum and breast) preliminarily classified according to their Modulation Complexity Score (MCS) calculated by LW, were considered. Receiver Operating Characteristic (ROC) Curves were used to establish gamma criteria for LW. 12 plans (3 for each site) were intentionally modified in order to introduce delivery errors regarding MLC, jaws, collimator, gantry and MU (for a total set of 168 incorrect plans) and irradiated on Oct4D; the corresponding log files were analysed by LW. Each incorrect plan was compared to the error-free plan using γ-index analysis for MLC, jaws and MU errors investigation and Root-Mean-Square (RMS) values for gantry and collimator errors investigation.

RESULTS

MCS ranges values were: 0.10-0.20 for H&N, 0.21-0.40 for prostate and rectum, 0.41-1.00 for breast. From ROC curves, the Gamma Passing Rate (GPR) thresholds were: 87%, 92%, 99% for H&N, prostate and rectum, and breast, respectively. The 1.5%/1.5 mm/local criteria were adopted for the γ-analysis. LW sensitivity in detecting the introduced errors was higher when compared to Oct4D: 48.5% vs 30.4% respectively.

CONCLUSIONS

LW can be considered useful complement to phantom-based delivery QA of IMRT/VMAT plans. The MCS tool is effective in detecting over or under modulated plans prior to pre-treatment QA. However, rigorous and routinely machine QCs are recommended.

A method for patient-specific DVH verification using a high-sampling-rate log file in an Elekta linac

We have proposed a method for patient-specific dose-volume histogram (DVH) verification using a 40-ms high-sampling-rate log file (HLF) available in an Elekta linac. Ten prostate volumetric-modulated arc therapy plans were randomly selected, and systematic leaf position errors of ±0.2, ±0.4, or ±0.8 mm were added to the 10 plans, thereby producing a total of 70 plans. An RTP file was created by interpolating each leaf position in the HLF to obtain values at each control point, which is subsequently exported to a treatment planning system. The isocenter dose calculated by the HLF-based plan to a phantom (Delta4 Phantom+) was compared to that measured by the diode in the phantom in order to evaluate the accuracy of the HLF-based dose calculation. The D95 of the planning target volume (PTV) was also compared between the HLF-based plans and the original plans with the systematic leaf position errors, the latter being referred to as theory-based plans. Sensitivities of the DVH parameters in the target, the rectum, and the bladder were also calculated with the varied systematic leaf position errors. The relative differences in the isocenter doses between the HLF-based calculations and the measurements among the 70 plans were 0.21% ± 0.67% (SD). The maximum relative differences in PTV D95 between the HLF-based and the theory-based plans among the 70 cases were 0.11%. The patient-specific DVH verification method detected a change in the target DVH parameters of less than 1% when the systematic leaf position error was ±0.2 mm. It is therefore suggested that the proposed DVH verification method may simplify patient-specific dose quality assurance procedures without compromising accuracy and sensitivity.

Comparing log file to measurement-based patient-specific quality assurance

Recent technological advances have allowed the possibility of performing patient-specific quality assurance (QA) without time-intensive measurements. The objectives of this study are to: (1) compare how well the log file-based Mobius QA system agrees with measurement-based QA methods (ArcCHECK and portal dosimetry, PD) in passing and failing plans, and; (2) evaluate their error sensitivities. To these ends, ten phantom plans and 100 patient plans were measured with ArcCHECK and PD on VitalBeam, while log files were sent to Mobius for dose recalculation. Gamma evaluation was performed using criteria 3%/2 mm, per TG218 recommendations, and non-inferiority of the Mobius recalculation was determined with statistical testing. Ten random plans were edited to include systematic errors, then subjected to QA. Receiver operating characteristic curves were constructed to compare error sensitivities across the QA systems, and clinical significance of the errors was determined by recalculating dose to patients. We found no significant difference between Mobius, ArcCHECK, and PD in passing plans at the TG218 action limit. Mobius showed good sensitivity to collimator and gantry errors but not MLC bank shift errors, but could flag discrepancies in treatment delivery. Systematic errors were clinically significant only at large magnitudes; such unacceptable plans did not pass QA checks at the TG218 tolerance limit. Our results show that Mobius is not inferior to existing measurement-based QA systems, and can supplement existing QA practice by detecting real-time delivery discrepancies. However, it is still important to maintain rigorous routine machine QA to ensure reliability of machine log files.

Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images

Machine learning (ML) methods have been implemented in radiotherapy to aid virtual specific-plan verification protocols, predicting gamma passing rates (GPR) based on calculated modulation complexity metrics because of their direct relation to dose deliverability. Nevertheless, these metrics might not comprehensively represent the modulation complexity, and automatically extracted features from alternative predictors associated with modulation complexity are needed. For this reason, three convolutional neural networks (CNN) based models were trained to predict GPR values (regression and classification), using respectively three predictors: (1) the modulation maps (MM) from the multi-leaf collimator, (2) the relative monitor units per control point profile (MUcp), and (3) the composite dose image (CDI) used for portal dosimetry, from 1024 anonymized prostate plans. The models' performance was assessed for classification and regression by the area under the receiver operator characteristic curve (AUC_ROC) and Spearman's correlation coefficient (r). Finally, four hybrid models were designed using all possible combinations of the three predictors. The prediction performance for the CNN-models using single predictors (MM, MUcp, and CDI) were AUC_ROC = 0.84 ± 0.03, 0.77 ± 0.07, 0.75 ± 0.04, andr= 0.6, 0.5, 0.7. Contrastingly, the hybrid models (MM + MUcp, MM + CDI, MUcp+CDI, MM + MUcp+CDI) performance were AUC_ROC = 0.94 ± 0.03, 0.85 ± 0.06, 0.89 ± 0.06, 0.91 ± 0.03, andr= 0.7, 0.5, 0.6, 0.7. The MP, MUcp, and CDI are suitable predictors for dose deliverability models implementing ML methods. Additionally, hybrid models are susceptible to improving their prediction performance, including two or more input predictors.

MLC performance prognosis using a degradation model based on trajectory log data from a daily test

PURPOSE

This paper investigates the feasibility of implementing a predictive maintenance program for a multileaf collimator (MLC) based on data collected in trajectory logs (TLs) obtained by conducting a simple daily test, with the aim of minimizing unscheduled downtime.

METHODS

A dynamic field test was designed, and the TLs generated in the course of daily administration in a linear accelerator were collected to evaluate trajectory deviations of the MLC leaves as well as interlocks (COL 420219/20, COL 420207/08) reported by the machine. During this evaluation, we observed that the trajectory deviations of some leaves increased up to a threshold value beyond which certain interlocks began to appear in treatment fields in those leaves. An exponential degradation model was therefore developed to predict this drift and determine each leaf's remaining useful life (RUL). Once the applicability of the model was confirmed, we added a second accelerator equipped with an MLC with the same configuration to validate the model.

RESULTS

The model was able to predict certain COL 420219/20 interlocks resulting from primary readout/expected position discrepancies and to estimate each leaf's RUL. In total, 11 cases (8 interlocks + 3 potential interlocks avoided due to service interventions [27.3% of the total]) were detected over 7 days in advance, with no false positive results. Scheduling of service interventions several days prior to MLC failure would therefore be possible. When these types of interlocks were not predicted by the model, they were always generated by leaf motor failure. Consequently, intervention time could also be optimized by directly replacing the motor. During the study period, for these types of interlocks, our approach would have reduced downtime from 35.25 to 4.00 h (88.7%) and from 34.75 to 22.83 h (34.3%) for each accelerator, respectively. For COL 420207/08 interlocks, which are generated by primary/secondary readout discrepancies, no correlation with leaf trajectory deviation increases recorded in the TLs was found. Throughout the study period, these types of interlocks requiring service intervention, also mainly for motor replacement, represented a downtime of 9.50 h for the first accelerator (21.2% of total downtime) and by 4.33 h (11.1% of total downtime) for the second accelerator.

CONCLUSION

This study demonstrates that by applying a predictive MLC maintenance program based on information collected in TLs, it is possible to predict certain interlocks and therefore schedule preemptive interventions to avoid their occurrence. This could optimize health-care delivery performance and minimize the loss of treatment sessions.

An independent Monte Carlo-based IMRT QA tool for a 0.35 T MRI-guided linear accelerator

PURPOSE

To develop an independent log file-based intensity-modulated radiation therapy (IMRT) quality assurance (QA) tool for the 0.35 T magnetic resonance-linac (MR-linac) and investigate the ability of various IMRT plan complexity metrics to predict the QA results. Complexity metrics related to tissue heterogeneity were also introduced.

METHODS

The tool for particle simulation (TOPAS) Monte Carlo code was utilized with a previously validated linac head model. A cohort of 29 treatment plans was selected for IMRT QA using the developed QA tool and the vendor-supplied adaptive QA (AQA) tool. For 27 independent patient cases, various IMRT plan complexity metrics were calculated to assess the deliverability of these plans. A correlation between the gamma pass rates (GPRs) from the AQA results and calculated IMRT complexity metrics was determined using the Pearson correlation coefficients. Tissue heterogeneity complexity metrics were calculated based on the gradient of the Hounsfield units.

RESULTS

The median and interquartile range for the TOPAS GPRs (3%/3 mm criteria) were 97.24% and 3.75%, respectively, and were 99.54% and 0.36% for the AQA tool, respectively. The computational time for TOPAS ranged from 4 to 8 h to achieve a statistical uncertainty of <1.5%, whereas the AQA tool had an average calculation time of a few minutes. Of the 23 calculated IMRT plan complexity metrics, the AQA GPRs had correlations with 7 out of 23 of the calculated metrics. Strong correlations (|r| > 0.7) were found between the GPRs and the heterogeneity complexity metrics introduced in this work.

CONCLUSIONS

An independent MC and log file-based IMRT QA tool was successfully developed and can be clinically deployed for offline QA. The complexity metrics will supplement QA reports and provide information regarding plan complexity.

Isodoses-a set theory-based patient-specific QA measure to compare planned and delivered isodose distributions in photon radiotherapy

BACKGROUND

The gamma index and dose-volume histogram (DVH)-based patient-specific quality assurance (QA) measures commonly applied in radiotherapy planning are unable to simultaneously deliver detailed locations and magnitudes of discrepancy between isodoses of planned and delivered dose distributions. By exploiting statistical classification performance measures such as sensitivity or specificity, compliance between a planned and delivered isodose may be evaluated locally, both for organs-at-risk (OAR) and the planning target volume (PTV), at any specified isodose level. Thus, a patient-specific QA tool may be developed to supplement those presently available in clinical radiotherapy.

MATERIALS AND METHODS

A method was developed to locally establish and report dose delivery errors in three-dimensional (3D) isodoses of planned (reference) and delivered (evaluated) dose distributions simultaneously as a function the dose level and of spatial location. At any given isodose level, the total volume of delivered dose containing the reference and the evaluated isodoses is locally decomposed into four subregions: true positive-subregions within both reference and evaluated isodoses, true negative-outside of both of these isodoses, false positive-inside the evaluated isodose but not the reference isodose, and false negatives-inside the reference isodose but not the evaluated isodose. Such subregions may be established over the whole volume of delivered dose. This decomposition allows the construction of a confusion matrix and calculation of various indices to quantify the discrepancies between the selected planned and delivered isodose distributions, over the complete range of values of dose delivered. The 3D projection and visualization of the spatial distribution of these discrepancies facilitates the application of the developed method in clinical practice.

RESULTS

Several clinical photon radiotherapy plans were analyzed using the developed method. In some plans at certain isodose levels, dose delivery errors were found at anatomically significant locations. These errors were not otherwise highlighted-neither by gamma analysis nor by DVH-based QA measures. A specially developed 3D projection tool to visualize the spatial distribution of such errors against anatomical features of the patient aids in the proposed analysis of therapy plans.

CONCLUSIONS

The proposed method is able to spatially locate delivery errors at selected isodose levels and may supplement the presently applied gamma analysis and DVH-based QA measures in patient-specific radiotherapy planning.

Insensitivity of machine log files to MLC leaf backlash and effect of MLC backlash on clinical dynamic MLC motion: An experimental investigation

Purpose

Multi‐leaf‐collimator (MLC) leaf position accuracy is important for accurate dynamic radiotherapy treatment plan delivery. Machine log files have become widely utilized for quality assurance (QA) of such dynamic treatments. The primary aim is to test the sensitivity of machine log files in comparison to electronic portal imaging device (EPID)‐based measurements to MLC position errors caused by leaf backlash. The secondary aim is to investigate the effect of MLC leaf backlash on MLC leaf motion during clinical dynamic plan delivery.

Methods

The sensitivity of machine log files and two EPID‐based measurements were assessed via a controlled experiment, whereby the length of the “T” section of a series of 12 MLC leaf T‐nuts in a Varian Millennium MLC for a Trilogy C‐series type linac was reduced by sandpapering the top of the “T” to introduce backlash. The built‐in machine MLC leaf backlash test as well as measurements for two EPID‐based dynamic MLC positional tests along with log files were recorded pre‐ and post‐T‐nut modification. All methods were investigated for sensitivity to the T‐nut change by assessing the effect on measured MLC leaf positions. A reduced version of the experiment was repeated on a TrueBeam type linac with Millennium MLC.

Results

No significant differences before and after T‐nut modification were detected in any of the log file data. Both EPID methods demonstrated sensitivity to the introduced change at approximately the expected magnitude with a strong dependence observed with gantry angle. EPID‐based data showed MLC positional error in agreement with the micrometer measured T‐nut length change to 0.07 ± 0.05 mm (1 SD) using the departmental routine QA test. Backlash results were consistent between linac types.

Conclusion

Machine log files appear insensitive to MLC position errors caused by MLC leaf backlash introduced via the T‐nut. The effect of backlash on clinical MLC motions is heavily gantry angle dependent.

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.

Sensitivity of Three Patient-Specific Quality Assurance Systems to MLC Aperture Errors With Volumetric Modulated Arc Therapy

Purpose: To compare the sensitivity of ArcCHECK (AC), portal dosimetry (PD), and an in-house logfile-based system (LF) to multileaf collimators (MLC) aperture errors and the ability to identify these errors. Methods and Materials: For 12 retrospective original head and neck volumetric modulated arc therapy (VMAT) plans, MLC aperture errors of ± 0.4mm, ± 1.2mm, ± 2mm, and ± 3mm were introduced for each plan, resulting in 96 plans with errors. AC, PD, and LF were used for the gamma evaluation at 3%/3mm, 3%/2mm, and 2%/2mm criteria. Gradient analysis was used to evaluate the sensitivity to MLC aperture errors. The area under the curve (AUC) obtained from the receiver operating characteristic (ROC) curve was used to evaluate the ability to identify MLC aperture errors and dose errors, and the optimal cut-off value to identify the error was obtained. Results: The gamma pass rate (%GP) of LF had the smallest descent gradient as the MLC error increases in any case. The descent gradient of PD was larger than AC, except for the case at the 2%/2mm criteria. For the 3%/3mm criteria, the MLC aperture errors that can be perfectly identified by AC, PD, and LF were ± 3mm, ± 2mm, and ± 1.2mm, respectively, and the average percent dose error (%DEs) of dose metrics in targets that can be perfectly identified were 4% to 5%, 3% to 4%, and 2% to 3%, respectively. For the 3%/2mm criteria, the errors that AC, PD, and LF can perfectly identify were the same as the 3%/3mm criteria. For the 2%/2mm criteria, AC can perfectly identify the MLC error of ± 2mm and the %DE of 3% to 4%. PD and LF can identify the MLC error of ± 1.2mm and the %DE of 2% to 3%. Conclusion: Different patient-specific quality assurance (PSQA) systems have different sensitivity and recognition abilities to MLC aperture errors. Institutions should formulate their own customized %GP limits based on their PSQA process through ROC or other methods.

Report of AAPM Task Group 219 on independent calculation-based dose/MU verification for IMRT

Independent verification of the dose per monitor unit (MU) to deliver the prescribed dose to a patient has been a mainstay of radiation oncology quality assurance (QA). We discuss the role of secondary dose/MU calculation programs as part of a comprehensive QA program. This report provides guidelines on calculation-based dose/MU verification for intensity modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT) provided by various modalities. We provide a review of various algorithms for "independent/second check" of monitor unit calculations for IMRT/VMAT. The report makes recommendations on the clinical implementation of secondary dose/MU calculation programs; on commissioning and acceptance of various commercially available secondary dose/MU calculation programs; on benchmark QA and periodic QA; and on clinically reasonable action levels for agreement of secondary dose/MU calculation programs.

Evaluation of 4-Hz log files and secondary Monte Carlo dose calculation as patient-specific quality assurance for VMAT prostate plans

Purpose

In this study, 4‐Hz log files were evaluated with an independent secondary Monte Carlo dose calculation algorithm to reduce the workload for patient‐specific quality assurance (QA) in clinical routine.

Materials and Methods

A total of 30 randomly selected clinical prostate VMAT plans were included. The used treatment planning system (TPS) was Monaco (Elekta, Crawley), and the secondary dose calculation software was SciMoCa (Scientific‐RT, Munich). Monaco and SciMoCa work with a Monte Carlo algorithm. A plausibility check of Monaco and SciMoCa was performed using an ionization chamber in the BodyPhantom (BP). First, the original Monaco RT plans were verified with SciMoCa (pretreatment QA). Second, the corresponding 4‐Hz log files were converted into RT log file plans and sent to SciMoCa as on‐treatment QA. MLC shift errors were introduced for one prostate plan to determine the sensitivity of on‐treatment QA. For pretreatment and on‐treatment QA, a gamma analysis (2%/1mm/20%) was performed and dosimetric values of PTV and OARs were ascertained in SciMoCa.

Results

Plausibility check of TPS Monaco vs. BP measurement and SciMoCa vs. BP measurement showed valid accuracy for clinical VMAT QA. Using SciMoCa, there was no significant difference in PTV Dmean between RT plan and RT log file plan. Between pretreatment and on‐treatment QA, PTV metrics, femur right and left showed no significant dosimetric differences as opposed to OARs rectum and bladder. The overall gamma passing rate (GPR) ranged from 96.10% to 100% in pretreatment QA and from 93.50% to 99.80% in on‐treatment QA. MLC shift errors were identified for deviations larger than −0.50 mm and +0.75 mm using overall gamma criterion and PTV Dmean.

Conclusion

SciMoCa calculations of Monaco RT plans and RT log file plans are in excellent agreement to each other. Therefore, 4‐Hz log files and SciMoCa can replace labor‐intensive phantom‐based measurements as patient‐specific QA.

Validation of virtual water phantom software for pre-treatment verification of single-isocenter multiple-target stereotactic radiosurgery

The aim of this study was to benchmark the accuracy of the VIrtual Phantom Epid dose Reconstruction (VIPER) software for pre-treatment dosimetric verification of multiple-target stereotactic radiosurgery (SRS). VIPER is an EPID-based method to reconstruct a 3D dose distribution in a virtual phantom from in-air portal images. Validation of the VIPER dose calculation was assessed using several MLC-defined fields for a 6 MV photon beam. Central axis percent depth doses (PDDs) and output factors were measured with an ionization chamber in a water tank, while dose planes at a depth of 10 cm in a solid flat phantom were acquired with radiochromic films. The accuracy of VIPER for multiple-target SRS plan verification was benchmarked against Monte Carlo simulations. Eighteen multiple-target SRS plans designed with the Eclipse treatment planning system were mapped to a cylindrical water phantom. For each plan, the 3D dose distribution reconstructed by VIPER within the phantom was compared with the Monte Carlo simulation, using a 3D gamma analysis. Dose differences (VIPER vs. measurements) generally within 2% were found for the MLC-defined fields, while film dosimetry revealed gamma passing rates (GPRs) ≥95% for a 3%/1 mm criteria. For the 18 multiple-target SRS plans, average 3D GPRs greater than 93% and 98% for the 3%/2 mm and 5%/2 mm criteria, respectively. Our results validate the use of VIPER as a dosimetric verification tool for pre-treatment QA of single-isocenter multiple-target SRS plans. The method requires no setup time on the linac and results in an accurate 3D characterization of the delivered dose.

AAPM Task Group 198 Report: An implementation guide for TG 142 quality assurance of medical accelerators

The charges on this task group (TG) were as follows: (a) provide specific procedural guidelines for performing the tests recommended in TG 142; (b) provide estimate of the range of time, appropriate personnel, and qualifications necessary to complete the tests in TG 142; and (c) provide sample daily, weekly, monthly, or annual quality assurance (QA) forms. Many of the guidelines in this report are drawn from the literature and are included in the references. When literature was not available, specific test methods reflect the experiences of the TG members (e.g., a test method for door interlock is self-evident with no literature necessary). In other cases, the technology is so new that no literature for test methods was available. Given broad clinical adaptation of volumetric modulated arc therapy (VMAT), which is not a specific topic of TG 142, several tests and criteria specific to VMAT were added.

IMRT QA and gamma comparisons: The impact of detector geometry, spatial sampling, and delivery technique on gamma comparison sensitivity

PURPOSE

To separately quantify sensitivity differences in patient-specific quality assurance comparisons analyzed with the gamma comparison for different measurement geometries, spatial samplings, and delivery techniques [intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT)].

METHODS

Error-free calculations for 20 IMRT and 20 VMAT cases were compared to calculations with known induced errors of varying magnitudes, using gamma comparisons. Five error types (MU scaling, three different MLC errors, and collimator errors) were induced in plan calculations on three different detector geometries - ArcCHECK, MapCHECK, and Delta 4. To study detector geometry sensitivity effects alone, gamma comparisons were made with 1 mm error-free calculations compared to 1 mm error-induced calculations for each device. Effects of spatial sampling were studied by making the same gamma comparisons, but down-sampling the error-induced calculations to the real spatial sampling of each device. Additionally, 1 mm vs 1 mm comparisons between the IMRT and VMAT cases were compared to investigate sensitivity differences between IMRT and VMAT using IMRT and VMAT cohorts with similar ranges of plan complexity and average aperture size. For each case, induced error type, and device, five different gamma criteria were studied to ensure sensitivity differences between devices, spatial sampling scenarios, and delivery technique were not gamma criterion specific, resulting in over 36,000 gamma comparisons.

RESULTS

For IMRT cases, Delta4 and MapCHECK devices had similar error sensitivities for lagging leaf, bank shift, and MU errors, while the ArcCHECK had considerably lower sensitivity than the planar-type devices. For collimator errors and perturbational leaf errors the ArcCHECK had higher error sensitivity than planar-type devices. This behavior was independent of gamma parameters (percent dose difference, distance-to-agreement, and low dose threshold), though use of local normalization resulted in error sensitivites that were markedly similar between all three devices. Differences between detector geometries were less pronounced for VMAT deliveries. Error sensitivity for a given gamma criterion when comparing IMRT and VMAT deliveries on the same devices showed that VMAT plans were more sensitive to some specific error types and less sensitive to others, when compared to IMRT plans. For the ArcCHECK device, the sensitivity of IMRT and VMAT cases was quite similar, whereas this was not the case for the planar-type devices. When comparing error sensitivity between 1 mm vs 1 mm calculations and 1 mm vs the real spatial sampling for each device, results showed that increased spatial sampling did not systematically increase error sensitivity.

CONCLUSIONS

Noticeable differences in error sensitivity were observed for different detector geometries, but differences were dependent on induced error type, and a particular device geometry did not offer universal improvements in error sensitivity across studied error types. This study demonstrates that the sensitivity of the gamma comparison does not largely hinge on detector spatial sampling. VMAT deliveries were generally less sensitive to errors when compared to IMRT plans for the planar-type devices, while similar sensitivities were observed between delivery techniques for the ArcCHECK device. Results of this work suggest that a universal gamma criterion is inappropriate for IMRT QA and that the percent pixels passing is an insufficient metric for evaluating quality assurance checks in the clinic.

Reducing treatment machine downtime with a preventative MLC maintenance procedure

The persistent use of MLCs through VMAT and IMRT is causing additional wear and tear on these mechanical parts, leading to an increase in MLC interlocks, breakdowns and failures. This study investigates the effect of an MLC clean and service procedure on MLC performance and positional accuracy demonstrated through in-house service logbook reports, Varian MLC backlash test results, daily MLC position QC results and Varian TrueBeam trajectory log file data. A service and clean of each individual MLC leaf was carried out on 3 standard MLC and 2 high definition MLC (HDMLC) Varian TrueBeam linacs. In-house service logbook reports, Varian backlash test results, daily MLC picket fence QC results and beam hold data from patient delivery trajectory log files were analysed for up to 6 months pre and 2 years post the MLC service/clean to assess the impact on unplanned MLC maintenance work and MLC performance. The median (range) of hardware faults reduced from 12 (1-17) pre clean to 0 (0-1) and 4 (1-11) at 12 and 24 months respectively for all linacs with the exception of a HDMLC linac where faults increased from 4 pre-clean to 13 and 20 again at 12 and 24 months respectively. The reduction in faults in the alternative 4 linacs was consistent with the reduction in the number of MLCs reaching the 0.3 mm and the 0.4 mm backlash recommendations in the first 12 and 24 months following the service/clean. The increase in faults in the HDMLC linac was also consistent with the increase in MLCs reaching the 0.3 mm backlash recommendation in the first 12 and 24 months. The median (range) of MLCs reaching a daily picket fence QC position tolerance of 0.25 mm reduced from 14 (1-40) pre clean to 0 (0) at both 12 and 24 months post-clean. This demonstrates the improvement in MLC performance caused by the MLC service/clean but also reveals factors other than MLC position accuracy influence hardware faults. Additionally, the number of beam hold-offs determined from patient delivery trajectory log files were found to have no correlation with the MLC service/clean. The MLC service/clean improves MLC performance and MLC position accuracy, reducing reactive repair work for engineering and physics staff. The results were maintained for 1 year post the MLC service/clean, with a trend back towards pre-clean levels in the subsequent 12-24 months. This suggests this preventative maintenance work could be performed at a frequency of > 2 years. This period of reduced faults and improved performance is significant given the 10 year expected lifespan of a linac.

Effect of treatment planning system parameters on beam modulation complexity for treatment plans with single-layer multi-leaf collimator and dual-layer stacked multi-leaf collimator

OBJECTIVE

High levels of beam modulation complexity (MC) and monitor units (MU) can compromise the plan deliverability of intensity-modulated radiotherapy treatments. Our study evaluates the effect of three treatment planning system (TPS) parameters on MC and MU using different multi-leaf collimator (MLC) architectures.

METHODS

192 volumetric modulated arc therapy plans were calculated using one virtual prostate phantom considering three main settings: (1) three TPS-parameters (Convergence; Aperture Shape Controller, ASC; and Dose Calculation Resolution, DCR) selected from Eclipse v15.6, (2) four levels of dose-sparing priority for organs at risk (OAR), and (3) two treatment units with same nominal conformity resolution and different MLC architectures (Halcyon-v2 dual-layer MLC, DL-MLC & TrueBeam single-layer MLC, SL-MLC). We use seven complexity metrics to evaluate the MC, including two new metrics for DL-MLC, assessed by their correlation with γ passing rate (GPR) analysis.

RESULTS

DL-MLC plans demonstrated lower dose-sparing values than SL-MLC plans (p<0.05). TPS-parameters did not change significantly the complexity metrics for either MLC architectures. However, for SL-MLC, significant variations of MU, target volume dose-homogeneity, and dose spillage were associated with ASC and DCR (p<0.05). MU were found to be correlated (highly or moderately) with all complexity metrics (p<0.05) for both MLC plans. Additionally, our new complexity metrics presented a moderate correlation with GPR (r<0.65). An important correlation was demonstrated between MC (plan deliverability) and dose-sparing priority level for DL-MLC.

CONCLUSIONS

TPS-parameters selected do not change MC for DL-MLC architecture, but they might have a potential use to control the MU, PTV homogeneity or dose spillage for SL-MLC. Our new DL-MLC complexity metrics presented important information to be considered in future pre-treatment quality assurance programs. Finally, the prominent dependence between plan deliverability and priority applied to OAR dose sparing for DL-MLC needs to be analyzed and considered as an additional predictor of GPRs in further studies.

ADVANCES IN KNOWLEDGE

Dose-sparing priority might influence in modulation complexity of DL-MLC.

A novel quality assurance procedure for trajectory log validation using phantom-less real-time latency corrected EPID images

The use of trajectory log files for routine patient quality assurance is gaining acceptance. Such use requires the validation of the trajectory log itself. However, the accurate localization of a multileaf collimator (MLC) leaf while it is in motion remains a challenging task. We propose an efficient phantom‐less technique using the EPID to verify the dynamic MLC positions with high accuracy. Measurements were made on four Varian TrueBeams equipped with M120 MLCs. Two machines were equipped with the S1000 EPID; two were equipped with the S1200 EPID. All EPIDs were geometrically corrected prior to measurements. Dosimetry mode EPID measurements were captured by a frame grabber card directly linked to the linac. All leaf position measurements were corrected both temporally and geometrically. The readout latency of each panel, as a function of pixel row, was determined using a 40 × 1.0 cm² sliding window (SW) field moving at 2.5 cm/s orthogonal to the row readout direction. The latency of each panel type was determined by averaging the results of two panels of the same type. Geometric correction was achieved by computing leaf positions with respect to the projected isocenter position as a function of gantry angle. This was determined by averaging the central axis position of fields at two collimator positions of 90° and 270°. The radiological to physical leaf end position was determined by comparison of the measured gap with that determined using a feeler gauge. The radiological to physical leaf position difference was found to be 0.1 mm. With geometric and latency correction, the proposed method was found to be improve the ability to detect dynamic MLC positions from 1.0 to 0.2 mm for all leaves. Latency and panel residual geometric error correction improve EPID‐based MLC position measurement. These improvements provide for the first time a trajectory log QA procedure.

A tool for patient-specific prediction of delivery discrepancies in machine parameters using trajectory log files

PURPOSE

Multileaf collimator (MLC) delivery discrepancy between planned and actual (delivered) positions have detrimental effect on the accuracy of dose distributions for both IMRT and VMAT. In this study, we evaluated the consistency of MLC delivery discrepancies over the course of treatment and over time to verify that a predictive machine learning model would be applicable throughout the course of treatment. Next, the MLC and gantry positions recorded in prior trajectory log files were analyzed to build a machine learning algorithm to predict MLC positional discrepancies during delivery for a new treatment plan. An open source tool was developed and released to predict the MLC positional discrepancies at treatment delivery for any given plan.

METHODS

Trajectory log files of 142 IMRT plans and 125 VMAT plans from 9 Varian TrueBeam linear accelerators were collected and analyzed. The consistency of delivery discrepancy over patient-specific quality assurance (QA) and patient treatment deliveries was evaluated. Data were binned by treatment site and machine type to determine their relationship with MLC and gantry angle discrepancies. Motion-related parameters including MLC velocity, MLC acceleration, control point, dose rate, and gravity vector, gantry velocity and gantry acceleration, where applicable, were analyzed to evaluate correlations with MLC and gantry discrepancies. Several regression models, such as simple/multiple linear regression, decision tree, and ensemble method (boosted tree and bagged tree model) were used to develop a machine learning algorithm to predict MLC discrepancy based on MLC motion parameters.

RESULTS

MLC discrepancies at patient-specific QA differed from those at patient treatment deliveries by a small (mean = 0.0021 ± 0.0036 mm, P = 0.0089 for IMRT; mean = 0.0010 ± 0.0016 mm, P = 0.0003 for VMAT) but statistically significant amount, likely due to setting the gantry angle to zero for QA in IMRT. MLC motion parameters, MLC velocity and gravity vector, showed significant correlation (P < 0.001) with MLC discrepancy, especially MLC velocity, which had an approximately linear relationship (slope = -0.0027, P < 0.001, R²  = 0.79). Incorporating MLC motion parameters, the final generalized model trained by data from all linear accelerators can predict MLC discrepancy to a high degree of accuracy with high correlation (R²  = 0.86) between predicted and actual MLC discrepancies. The same prediction results were found across different treatment sites and linear accelerators.

CONCLUSION

We have developed a machine learning model using trajectory log files to predict the MLC discrepancies during delivery. This model has been a released as a research tool in which a DICOM-RT with predicted MLC positions can be generated using the original DICOM-RT file as input. This tool can be used to simulate radiotherapy treatment delivery and may be useful for studies evaluating plan robustness and dosimetric uncertainties from treatment delivery.

Toward real-time verification for MLC tracking treatments using time-resolved EPID imaging

PURPOSE

In multileaf collimator (MLC) tracking, the MLC positions from the original treatment plan are continuously modified to account for intrafraction tumor motion. As the treatment is adapted in real time, there is additional risk of delivery errors which cannot be detected using traditional pretreatment dose verification. The purpose of this work is to develop a system for real-time geometric verification of MLC tracking treatments using an electronic portal imaging device (EPID).

METHODS

MLC tracking was utilized during volumetric modulated arc therapy (VMAT). During these deliveries, treatment beam images were taken at 9.57 frames per second using an EPID and frame grabber computer. MLC positions were extracted from each image frame and used to assess delivery accuracy using three geometric measures: the location, size, and shape of the radiation field. The EPID-measured field location was compared to the tumor motion measured by implanted electromagnetic markers. The size and shape of the beam were compared to the size and shape from the original treatment plan, respectively. This technique was validated by simulating errors in phantom test deliveries and by comparison between EPID measurements and treatment log files. The method was applied offline to images acquired during the LIGHT Stereotactic Ablative Body Radiotherapy (SABR) clinical trial, where MLC tracking was performed for 17 lung cancer patients. The EPID-based verification results were subsequently compared to post-treatment dose reconstruction.

RESULTS

Simulated field location errors were detected during phantom validation tests with an uncertainty of 0.28 mm (parallel to MLC motion) and 0.38 mm (perpendicular), expressed as a root-mean-square error (RMS_Error ). For simulated field size errors, the RMS_Error was 0.47 cm² and field shape changes were detected for random errors with standard deviation ≥ 2.5 mm. For clinical lung SABR deliveries, field location errors of 1.6 mm (parallel MLC motion) and 4.9 mm (perpendicular) were measured (expressed as a full-width-half-maximum). The mean and standard deviation of the errors in field size and shape were 0.0 ± 0.3 cm² and 0.3 ± 0.1 (expressed as a translation-invariant normalized RMS). No correlation was observed between geometric errors during each treatment fraction and dosimetric errors in the reconstructed dose to the target volume for this cohort of patients.

CONCLUSION

A system for real-time delivery verification has been developed for MLC tracking using time-resolved EPID imaging. The technique has been tested offline in phantom-based deliveries and clinical patient deliveries and was used to independently verify the geometric accuracy of the MLC during MLC tracking radiotherapy.

Effect of Multileaf Collimator Leaf Position Error Determined by Picket Fence Test on Gamma Index Value in Patient-Specific Quality Assurance of Volumetric-Modulated Arc Therapy Plans

Aim The correlation between the MLC QA (IBA Dosimetry, Germany) results of the picket fence test created with intentional errors and the patient's quality assurance (QA) evaluation was investigated to assess the impact of multileaf collimator (MLC) positioning error on patient QA. Materials and methods The picket fence, including error-free and intentional MLC errors, defined in Bank In, Bank Out, and Bank Both were analyzed using MLC QA. The QA of 15 plans consisting of stereotactic radiosurgery (SRS), stereotactic body radiotherapy (SBRT), and conventionally fractionated volumetric-modulated arc therapy (VMAT) acquired with electronic portal imaging devices (EPID) was evaluated in the presence of error-free and MLC errors. The QA of plans were analyzed with 2%/2 mm and 3%/3 mm criteria. Results The passing rates of the picket fence test were 97%, 92%, 91%, and 87% for error-free and intentional errors. The criterion of 3%/3 mm wasn't able to detect an MLC error for either SRS/SBRT or conventionally fractionated VMAT. The criterion of 2%/2mm was more sensitive to detect MLC error for the conventionally fractionated VMAT than SRS/SBRT. While only two of SBRT plans had <90%, four of conventionally fractionated VMAT plans had a <90% passing rate. Conclusion We found that the systematic MLC positioning errors defined with picket fence have a smaller but measurable impact on SRS/SBRT than the VMAT plan for a conventionally fractionated and relatively complex plan such as head and neck and endometrium cases.

On the use of trajectory log files for machine & patient specific QA

Purpose:Trajectory log files are increasingly being utilized clinically for machine and patient specific QA. The process of converting the DICOM-RT plan to a deliverable trajectory by the linac control software introduces some uncertainty that is inherently incorporated into measurement-based patient specific QA but is not necessarily included for trajectory log file-based methods. Roughly half of prior studies have included this uncertainty in the analysis while the remaining studies have ignored it, and it has yet to be quantified in the literature.Methods:We collected DICOM-RT files from the treatment planning system and the trajectory log files from four TrueBeam linear accelerators for 25 IMRT and 10 VMAT plans. We quantified the DICOM-RT Conversion to Trajectory Residual (DCTR, difference between 'planned' MLC position from TPS DICOM-RT file and 'expected' MLC position (the deliverable MLC positions calculated by the linac control software) from trajectory log file) and compared it to the discrepancy between actual and expected machine parameters recorded in trajectory log files.Results:RMS of the DCTR was 0.0845 mm (range of RMS per field/arc: 0.0173-0.1825 mm) for 35 plans (114 fields/arcs) and was independent of treatment technique, with a maximum observed discrepancy at any control point of 0.7255 mm. DCTR was correlated with MLC velocity and was consistent over the course of treatment and over time, with a slight change in magnitude observed after a linac software upgrade. For comparison, the RMS of trajectory log file reported delivery error for moving MLCs was 0.0205 mm, thus DCTR is about four times the recorded delivery error in the trajectory log file.Conclusion:The uncertainty introduced from the conversion process by the linac control software from DICOM-RT plan to a deliverable trajectory is 3-4 times larger than the discrepancy between actual and expected machine parameters recorded in trajectory log files. This uncertainty should be incorporated into the analysis when using trajectory log file-based methods for analyzing MLC performance or patient-specific QA.

Error sensitivity of a log file analysis tool compared with a helical diode array dosimeter for VMAT delivery quality assurance

PURPOSE

Integrating log file analysis with LINACWatch® (LW) into clinical routine as part of the quality assurance (QA) process could be a time-saving strategy that does not compromise on quality. The purpose is to determine the error sensitivity of log file analysis using LINACWatch® compared with a measurement device (ArcCHECK®, AC) for VMAT delivery QA.

MATERIALS AND METHODS

Multi-leaf collimator (MLC) errors, collimator angle errors, MLC shift errors and dose errors were inserted to analyze error detection sensitivity. A total of 36 plans were manipulated with different magnitudes of errors. The gamma index protocols for AC were 3%/3 mm/Global and 2%/2 mm/Global, as well as 2%/2 mm/Global, and 1.5%/1.5 mm/Global for LW. Additionally, deviations of the collimator and monitor units between TPS and log file were calculated as RMS values. A 0.125 cm³ ionization chamber was used to independently examine the effect on dose.

RESULTS

The sensitivity for AC was 20.4% and 49.6% vs 63.0% and 86.5% for LW, depending on the analysis protocol. For MLC opening and closing errors, the detection rate was 19.0% and 47.7% for AC vs 50.5% and 75.5% for LW. For MLC shift errors, it was 29.6% and 66.7% for AC vs 66.7% and 83.3% for LW. AC could detect 25.0% and 44.4% of all collimator errors. Log file analysis detected all collimator errors using 1° detection level. 13.2% and 42.4% of all dose errors were detected by AC vs 59.0% and 92.4% for LW using gamma analysis. Using RMS value, all dose errors were detected by LW (1% detection level).

CONCLUSION

The results of this study clearly show that log file analysis is an excellent complement to phantom-based delivery QA of VMAT plans. We recommend a 1.5%/1.5 mm/Global criteria for log file-based gamma calculations. Log file analysis was implemented successfully in our clinical routine for VMAT delivery QA.

Patient-specific quality assurance using machine log files analysis for stereotactic body radiation therapy (SBRT)

An in‐house trajectory log analysis program (LOGQA) was developed to evaluate the delivery accuracy of volumetric‐modulated arc therapy (VMAT) for stereotactic body radiation therapy (SBRT). Methods have been established in LOGQA to provide analysis on dose indices, gantry angles, and multi‐leaf collimator (MLC) positions. Between March 2019 and May 2020, 120 VMAT SBRT plans of various treatment sites using flattening filter‐free (FFF) mode were evaluated using both LOGQA and phantom measurements. Gantry angles, dose indices, and MLC positions were extracted from log and compared with each plan. Integrated transient fluence map (ITFM) was reconstructed from log to examine the deviation of delivered fluence against the planned one. Average correlation coefficient of dose index versus gantry angle and ITFM for all patients were 1.0000, indicating that the delivered beam parameters were in good agreement with planned values. Maximum deviation of gantry angles and monitor units (MU) of all patients were less than 0.2 degree and 0.03 % respectively. Regarding MLC positions, maximum and root‐mean‐square (RMS) deviations from planned values were less than 0.6 mm and 0.3 mm respectively, indicating that MLC positions during delivery followed planned values in precise manner. Results of LOGQA were consistent with measurement, where all gamma‐index passing rates were larger than 95 %, with 2 %/2 mm criteria. Three types of intentional errors were introduced to patient plan for software validation. LOGQA was found to recognize the introduced errors of MLC positions, gantry angles, and dose indices with magnitudes of 1 mm, 1 degree, and 5 %, respectively, which were masked in phantom measurement. LOGQA was demonstrated to have the potential to reduce or even replace patient‐specific QA measurements for SBRT plan delivery provided that the frequency and amount of measurement‐based machine‐specific QA can be increased to ensure the log files record real values of machine parameters.

Cross verification of independent dose recalculation, log files based, and phantom measurement-based pretreatment quality assurance for volumetric modulated arc therapy

Independent treatment planning system (TPS) check with Mobius3D software, log files based quality assurance (QA) with MobiusFX, and phantom measurement‐based QA with ArcCHECK were performed and cross verified for head‐and‐neck (17 patients), chest (16 patients), and abdominal (19 patients) cancer patients who underwent volumetric modulated arc therapy (VMAT). Dosimetric differences and percentage gamma passing rates (%GPs) were evaluated and compared for this cross verification. For the dosimetric differences in planning target volume (PTV) coverage, there was no significant difference among TPS vs. Mobius3D, TPS vs. MobiusFX, and TPS vs. ArcCHECK. For the dosimetric differences in organs at risks (OARs), the number of metrics with an average dosimetric differences higher than ±3% for TPS vs Mobius3D, TPS vs MobiusFX, and TPS vs ArcCHECK were 1, 1, 7; 2, 1, 4; 1, 1, 5 for the patients with head‐and‐neck, abdomen, and chest cancer, respectively. The %GPs of global gamma indices for Mobius3D and MobiousFX were above 97%, while it ranged from 92% to 96% for ArcCHECK. The %GPs of individual volume‐based gamma indices were around 98% for Mobius3D and MobiousFX, except for γPTV for chest and abdominal cancer (88.9% to 92%); while it ranged from 86% to 99% for ArcCHECK. In conclusion, some differences in dosimetric metrics and gamma passing rates were observed with ArcCHECK measurement‐based QA in comparison with independent dosecheck and log files based QA. Care must be taken when considering replacing phantom measurement‐based IMRT/VMAT QA.

Error detection and classification in patient-specific IMRT QA with dual neural networks

PURPOSE

Despite being the standard metric in patient-specific quality assurance (QA) for intensity-modulated radiotherapy (IMRT), gamma analysis has two shortcomings: (a) it lacks sensitivity to small but clinically relevant errors (b) it does not provide efficient means to classify the error sources. The purpose of this work is to propose a dual neural network method to achieve simultaneous error detection and classification in patient-specific IMRT QA.

METHODS

For a pair of dose distributions, we extracted the dose difference histogram (DDH) for the low dose gradient region and two signed distance-to-agreement (sDTA) maps (one in x direction and one in y direction) for the high dose gradient region. An artificial neural network (ANN) and a convolutional neural network (CNN) were designed to analyze the DDH and the two sDTA maps, respectively. The ANN was trained to detect and classify six classes of dosimetric errors: incorrect multileaf collimator (MLC) transmission (±1%) and four types of monitor unit (MU) scaling errors (±1% and ±2%). The CNN was trained to detect and classify seven classes of spatial errors: incorrect effective source size, 1 mm MLC leaf bank overtravel or undertravel, 2 mm single MLC leaf overtravel or undertravel, and device misalignment errors (1 mm in x- or y direction). An in-house planar dose calculation software was used to simulate measurements with errors and noise introduced. Both networks were trained and validated with 13 IMRT plans (totaling 88 fields). A fivefold cross-validation technique was used to evaluate their accuracy.

RESULTS

Distinct features were found in the DDH and the sDTA maps. The ANN perfectly identified all four types of MU scaling errors and the specific accuracies for the classes of no error, MLC transmission increase, MLC transmission decrease were 98.9%, 96.6%, and 94.3%, respectively. For the CNN, the largest confusion occurred between the 1-mm-MLC bank overtravel class and the 1-mm-device alignment error in x-direction class, which brought the specific accuracies down to 90.9% and 92.0%, respectively. The specific accuracy for the 2-mm-single MLC leaf undertravel class was 93.2% as it misclassified 5.7% of the class as being error free (false negative). Otherwise, the specific accuracy was above 95%. The overall accuracies across the fivefold were 98.3 ± 0.7% and 95.6% ± 1.5% for the ANN and the CNN, respectively.

CONCLUSIONS

Both the DDH and the sDTA maps are suitable features for error classification in IMRT QA. The proposed dual neural network method achieved simultaneous error detection and classification with excellent accuracy. It could be used in complement with the gamma analysis to potentially shift the IMRT QA paradigm from passive pass/fail analysis to active error detection and root cause identification.

Halcyon clinical performance evaluation: A log file-based study in comparison with a C-arm Linac

PURPOSE

The aim of this study is to compare the dosimetric and mechanical accuracy of Volumetric Modulation Arc Therapy (VMAT) delivery on the Halcyon, a recent ring-shaped Treatment Delivery System (TDS) featuring fast rotating gantry, with a conventional C-arm Linac.

METHODS

The comparison was performed via log file analysis, where mechanical parameters of related components was extracted. 480 and 3951 VMAT log files of clinically delivered fractions from a Halcyon and a TrueBeam Linac were analyzed respectively. The relations between mechanical parameters and errors were extensively explored to further investigate the differences between the two Linacs. The mechanical parameter fluctuations were taken into account for dose recalculations, and the Dose Volume Parameters (DVP) on the PTV were evaluated to quantify such dosimetric variations.

RESULTS

The Multi-Leaf Collimator (MLC) leaf mean Root Mean Square (RMS) errors were 0.028 mm and 0.031 mm for Halcyon and TrueBeam respectively. Maximum systematic error on the MLC leaves introduced by the gravity effect were 0.04 mm and 0.01 mm for the Halcyon and TrueBeam respectively. Thanks to the O-ring design, the Halcyon achieved 0.035° in mean RMS error in gantry angle compared with the 0.065° of the TrueBeam. Overall mechanical errors introduced similar levels of dose-volume parameter variations (about 0.1%) on both Linacs.

CONCLUSION

The Halcyon TDS can achieve similar mechanical leaf positioning accuracy compared with the TrueBeam TDS with a doubled delivery speed. In terms of dosimetric accuracy, The DVP standard deviations on the studied TB are generally larger than that on the Halcyon.

Using a TRAPS upstream transmission detector to verify multileaf collimator positions during dynamic radiotherapy delivery

With the advancement of high-precision radiotherapy and the increasing use of higher intensity beams, the risk to the patient increases should the radiotherapy machine malfunction. Hence more accurate treatment verification is required. In this paper we provide a solution for real-time monitoring of X-ray beams from radiotherapy linear accelerators using monolithic active pixel sensors. We show that leaf errors can be detected with high precision in static fields and IMRT step and shoot, and accurate leaf tracking is possible in Volumetric Modulated Arc Therapy. The prototype MAPS detector meets the criteria of 1% attenuation acceptable for clinical use.

Two-dimensional solid-state array detectors: A technique for in vivo dose verification in a variable effective area

PURPOSE

We introduce a technique that employs a 2D detector in transmission mode (TM) to verify dose maps at a depth of dmax in Solid Water. TM measurements, when taken at a different surface-to-detector distance (SDD), allow for the area at dmax (in which the dose map is calculated) to be adjusted.

METHODS

We considered the detector prototype "MP512" (an array of 512 diode-sensitive volumes, 2 mm spatial resolution). Measurements in transmission mode were taken at SDDs in the range from 0.3 to 24 cm. Dose mode (DM) measurements were made at dmax in Solid Water. We considered radiation fields in the range from 2 × 2 cm2 to 10 × 10 cm2 , produced by 6 MV flattened photon beams; we derived a relationship between DM and TM measurements as a function of SDD and field size. The relationship was used to calculate, from TM measurements at 4 and 24 cm SDD, dose maps at dmax in fields of 1 × 1 cm2 and 4 × 4 cm2 , and in IMRT fields. Calculations were cross-checked (gamma analysis) with the treatment planning system and with measurements (MP512, films, ionization chamber).

RESULTS

In the square fields, calculations agreed with measurements to within ±2.36%. In the IMRT fields, using acceptance criteria of 3%/3 mm, 2%/2 mm, 1%/1 mm, calculations had respective gamma passing rates greater than 96.89%, 90.50%, 62.20% (for a 4 cm SSD); and greater than 97.22%, 93.80%, 59.00% (for a 24 cm SSD). Lower rates (1%/1 mm criterion) can be explained by submillimeter misalignments, dose averaging in calculations, noise artifacts in film dosimetry.

CONCLUSIONS

It is possible to perform TM measurements at the SSD which produces the best fit between the area at dmax in which the dose map is calculated and the size of the monitored target.

Complexity metrics for IMRT and VMAT plans: a review of current literature and applications

Modulated radiotherapy with multileaf collimators is widely used to improve target conformity and normal tissue sparing. This introduced an additional degree of complexity, studied by multiple teams through different properties. Three categories of complexity metrics were considered in this review: fluence, deliverability and accuracy metrics. The first part of this review is dedicated to the inventory of these complexity metrics. Different applications of these metrics emerged. Influencing the optimizer by integrating complexity metrics into the cost function has been little explored and requires more investigations. In modern treatment planning system, it remains confined to MUs or treatment time limitation. A large majority of studies calculated metrics only for analysis, without plan modification. The main application was to streamline the patient specific quality assurance workload, investigating the capability of complexity metrics to predict patient specific quality assurance results. Additionally complexity metrics were used to analyze behaviour of TPS optimizer, compare TPS, operators and plan properties, and perform multicentre audit. Their potential was also explored in the context of adaptive radiotherapy and automation planning. The second part of the review gives an overview of these studies based on the complexity metrics.

Evaluation of gantry angle during respiratory‐gated VMAT using triggered kilovoltage x‐ray image

Respiratory‐gated volumetric modulated arc therapy (gated VMAT) involves further complexities to the dose delivery process because the gantry rotation must repeatedly stop and restart according to the gating signals. In previous studies, the gantry rotation performances were evaluated by the difference between the plan and the machine log. However, several reports pointed out that log analysis does not sufficiently replicate the machine performance. In this report, a measurement‐based quality assurance of the relation between the gantry angle and gate‐on or gate‐off using triggered kilovoltage imaging and a cylinder phantom with 16 ball bearings is proposed. For the analysis, an in‐house program that estimates and corrects the phantom offset was developed. The gantry angle in static and gated arc delivery was compared between the machine log and the proposed method. The gantry was set every 5 deg through its full motion range in static delivery, and rotated at three speeds (2, 4 and 6 deg s^‐1) with different gating intervals (1.5 or 3.0 s) in gated arc delivery. The mean and standard deviation of the angular differences between the log and the proposed method was −0.05 deg ± 0.12 deg in static delivery. The mean of the angular difference was within ±0.10 deg and the largest difference was 0.41 deg in gated arc delivery. The log records the output of the encoder so that miscalibration and mechanical sagging will be disregarded. However, the proposed method will help the users to detect the mechanical issues due to the repeated gantry stops and restarts in gated VMAT.

Dosimetric accuracy of dynamic couch rotation during volumetric modulated arc therapy (DCR-VMAT) for primary brain tumours

Radiotherapy treatment plans using dynamic couch rotation during volumetric modulated arc therapy (DCR-VMAT) reduce the dose to organs at risk (OARs) compared to coplanar VMAT, while maintaining the dose to the planning target volume (PTV). This paper seeks to validate this finding with measurements. DCR-VMAT treatment plans were produced for five patients with primary brain tumours and delivered using a commercial linear accelerator (linac). Dosimetric accuracy was assessed using point dose and radiochromic film measurements. Linac-recorded mechanical errors were assessed by extracting deviations from log files for multi-leaf collimator (MLC), couch, and gantry positions every 20 ms. Dose distributions, reconstructed from every fifth log file sample, were calculated and used to determine deviations from the treatment plans. Median (range) treatment delivery times were 125 s (123-133 s) for DCR-VMAT, compared to 78 s (64-130 s) for coplanar VMAT. Absolute point doses were 0.8% (0.6%-1.7%) higher than prediction. For coronal and sagittal films, respectively, 99.2% (96.7%-100%) and 98.1% (92.9%-99.0%) of pixels above a 20% low dose threshold reported gamma  <1 for 3% and 3 mm criteria. Log file analysis showed similar gantry rotation root-mean-square error (RMSE) for VMAT and DCR-VMAT. Couch rotation RMSE for DCR-VMAT was 0.091° (0.086-0.102°). For delivered dose reconstructions, 100% of pixels above a 5% low dose threshold reported gamma  <1 for 2% and 2 mm criteria in all cases. DCR-VMAT, for the primary brain tumour cases studied, can be delivered accurately using a commercial linac.

EPID sensitivity to delivery errors for pre-treatment verification of lung SBRT VMAT plans

PURPOSE

To study the sensitivity of an Electronic Portal Imaging Device (EPID) in detecting delivery errors for VMAT lung stereotactic body radiotherapy (SBRT) using the Collapsed Arc method.

METHODS

Baseline VMAT plans and plans with errors intentionally introduced were generated for 15 lung SBRT patients. Three types of errors were introduced by modifying collimator angles and multi-leaf collimator (MLC) field sizes (MLCFS) and MLC shifts by ±5, ±2, and ±1° or millimeters. A total of 103 plans were measured with EPID on an Elekta Synergy Linear Accelerator (Agility MLC) and compared to both the original treatment planning system (TPS) Collapsed Arc dose matrix and the no-error plan baseline EPID measurements. Gamma analysis was performed using the OmniPro-I'mRT (IBA Dosimetry) software and gamma criteria of 1%/1 mm, 2%/1 mm, 2%/2 mm, and 3%/3.

RESULTS

When the error-introduced EPID measured dose matrices were compared to the TPS matrices, the majority of simulated errors were detected with gamma tolerance of 2%/1 mm and 1%/1 mm. When the error-introduced EPID measured dose matrices were compared to the baseline EPID measurements, all the MLCFS and MLC shift errors, and ±5°collimator errors were detected using 2%/1 mm and 1%/1 mm gamma criteria.

CONCLUSION

This work demonstrates the feasibility and effectiveness of the collapsed arc technique and EPID for pre-treatment verification of lung SBRT VMAT plans. The EPID was able to detect the majority of MLC and the larger collimator errors with sensitivity to errors depending on the gamma tolerances.

Trajectory log file sensitivity: A critical analysis using DVH and EPID

Aim

The aim of this study was to investigate the sensitivity of the trajectory log file based quality assurance to detect potential errors such as MLC positioning and gantry positioning by comparing it with EPID measurement using the most commonly used criteria of 3%/3 mm.

Materials and methods

An in-house program was used to modified plans using information from log files, which can then be used to recalculate a new dose distribution. The recalculated dose volume histograms (DVH) were compared with the originals to assess differences in target and critical organ dose. The dose according to the differences in DVH was also compared with dosimetry from an electronic portal imaging device.

Results

In all organs at risk (OARs) and planning target volumes (PTVs), there was a strong positive linear relationship between MLC positioning and dose error, in both IMRT and VMAT plans. However, gantry positioning errors exhibited little impact in VMAT delivery. For the ten clinical cases, no significant correlations were found between gamma passing rates under the criteria of 3%/3 mm for the composite dose and the mean dose error in DVH (r < 0.3, P > 0.05); however, a significant positive correlation was found between the gamma passing rate of 3%/3 mm (%) averaged over all fields and the mean dose error in the DVH of the VMAT plans (r = 0.59, P < 0.001).

Conclusions

This study has successfully shown the sensitivity of the trajectory log file to detect the impact of systematic MLC errors and random errors in dose delivery and analyzed the correlation of gamma passing rates with DVH.