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Halcyon clinical performance evaluation: A log file-based study in comparison with a C-arm Linac
Physica Medica 71 (2020) 14–23
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Physica Medica journal homepage: www.elsevier.com/locate/ejmp
Original paper
Halcyon clinical performance evaluation: A log file-based study in comparison with a C-arm Linac
T
Ruoxi Wang, Yi Du, Kaining Yao, Zhuolun Liu, Hanlin Wang, Haizhen Yue, Yibao Zhang, ⁎ Hao Wu Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
ABSTRACT
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.
1. Introduction In modern-day radiotherapy, Volumetric Modulated Arc Therapy (VMAT) is a delivery technique leveraging the simultaneous modulation of gantry angle, MLC leaf position, and dose rate [1]. Compared with many-field Intensity Modulated Radiation Therapy (IMRT), VMAT could achieve similar dose comformity while greatly reducing delivery time [2,3]. The appearance of flattening filter free (FFF) beams indicates further reduction in delivery time. However, due to current speed limit on gantry rotation and MLC leaf movement, major improvement in delivery efficiency has not been observed with the use of FFF beams [4–6]. The Halcyon linear accelerator (Varian Medical Systems, Palo Alto, CA) is a fast-rotating, ring-shaped Treatment Delivery System (TDS) introduced in 2017 [7]. This linear accelerator (Linac) was conceived with an emphasize on tightly controlled performance in order to facilitate acceptance tests, commissioning, and daily Quality Assurance (QA) activities. To improve clinical throughput and patient comfort, the Halcyon TDS combined the use of FFF beams, fast gantry rotation, and high-speed MLC leaf movement. The great increase in gantry rotation speed was mainly attributed by the enclosed gantry design, providing ⁎
stabler support compared with C-arm Linacs. The numerous changes in the Linac design warrant performance verification by the medical physicists. As a result, several studies have addressed monitoring mechanical parameters in QA environment on the Halcyon TDS. For example, Lim et al. have experimentally characterized the mechanical parameters of the dual-layered MLC, including leaf positioning accuracy, leaf transmission, interleaf leakage, and leaf end/edge effect [8]. Regarding the clinical performance, the interest was focused on the plan quality and efficiency improvement [9,10]. In the meantime, De Roover et al. performed an end-to-end dosimetric verification on anthropomorphic phantoms, and confirmed results within clinical dosimetric tolerances [11]. The delivered dose distribution depends on the modulation accuracy of the mechanical components, e.g. MLC leaf positioning, gantry positioning, etc.. Modern-day TDS incorporates software services recording mechanical component status in form of log files during the beam delivery. The temporal resolution of the log files is in magnitude of tens of milliseconds. The log files can provide very detailed information on the evolving status even for each MLC leaf position [12]. TG-142 report recommended an annual statistic check on the MLC positioning errors based on log file analysis [13]. Since the log file is a
Corresponding author. E-mail address: [email protected] (H. Wu).
https://doi.org/10.1016/j.ejmp.2020.01.023 Received 24 October 2019; Received in revised form 27 December 2019; Accepted 26 January 2020 1120-1797/ © 2020 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
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representation of the treatment delivery process with high temporal resolution, one could essentially calculate the delivered dose distribution in the patient, based on the previously obtained patient geometry. Several studies have explored such approach to verify the delivery quality and confirmed positive impact of the patient specific QA [14,15] based on independent dose calculation. It is noted that the aforementioned studies of log file analysis on Varian Linacs were carried out on Clinac and TrueBeam (TB) platforms. The Halcyon TDS records log files corresponding to treatment deliveries as well, therefore a log file-based approach evaluating delivery quality on the Halcyon is also possible. This study aims to answer the following question: With the design changes on the Halcyon, how is its dosimetric and mechanical accuracy compared with a TB Linac? The comparison was performed based on log files recorded during clinical VMAT deliveries on two Linacs: a Halcyon and a TB. To the authors’ best knowledge, this is the first study evaluating delivery performance via log files on the Halcyon TDS. This study reports on statistics of both mechanical performance and dosimetric outcome of 480 VMAT delivery fractions on the Halcyon TDS. In comparison, 3951 VMAT log files from a TB system were analyzed for performance evaluation. The delivered dose distribution has been recalculated based on the log file of each delivered fraction and compared with the planned dose distribution. Although previous studies have reported undetected MLC positioning error by log files due to encoder malfunction [16,17], this study intends to reveal potential different error patterns in mechanical parameters between the Halcyon and the TB system, which would be less influenced by the rare malfunction events.
50 Hz. Although the log files from the Halcyon have not been explicitly announced to comply with the trajectory log specification, initial tests have shown that these log files followed the previous specification with minimal exceptions. The expected MLC leaf positions from the log files have been compared with expected leaf positions from the DICOM RT plans and the robustness and accuracy of parsed machine parameters were validated. 2.3. Statistical analysis A Python script was written to automate the data processing pipeline. First, the log file was parsed utilizing the pylinac package [19], where both expected and actual positions/status of the relevant parameters (MLC leaves, jaw positions, gantry angle, MU, etc.) were extracted from the parsed log files. The differences between expected and actual values at each sampling point were calculated and regarded as the measured errors. In order to obtain comparable descriptive metrics with regard to the previous studies [20,21], the mean and the root mean square (RMS) of the error, the skewness of the error mean distribution, and the 95th percentile of the error amplitude were chosen as the representative metrics for the error distributions for MLC and gantry angle. The RMS error of MLC was defined as the mean of RMS error for all the leaves within a log file, similar to the definition by Kerns et al. [21]. The skewness of the error mean distribution was computed as the Fisher-Pearson skewness coefficient [22], given by
g1 =
m3 m 23/2
(1)
where the mi is the biased i th central moment, defined as
2. Materials and methods
1 N
N
The data acquisition was performed on two Linacs: a Halcyon and a TB. Unlike traditional Linac designs, The Halcyon system features both fixed primary collimator and secondary collimator, equipped with a dual-layered and staggered MLC as the beam shaping device. Detailed features of the Halcyon can be found in previous literature [9]. The TDS versions of Halcyon and TB in this work were respectively 1.0 and 2.5. The Treatment Planning System (TPS) used were Eclipse of version 13.6 and 15.1 for the TB and the Halcyon respectively.
where the ej is the error mean in the jth log file and e¯ is the average of the error mean over all the log files. Our preliminary study showed that the leaf error distribution presented two distinguished peaks, corresponding to the moving leaves and the static leaves respectively. Because most static leaves correspond to closed leaf pairs, only moving leaf positions were included into the analysis. Since the motion accuracy during the beam-off period is not of interest in a clinical perspective, all recorded parameters were filtered by the beam-on flag, unless otherwise specified. Unlike the other parameters, the recorded MU corresponds to the accumulated value at the given control point. Therefore the MU error at the last beam-on moment was extracted as the integral MU error of the fraction. The first and second order derivatives of corresponding angle/position over predefined time window (20 ms ) were calculated using the three-pointcentered difference method [23], referring to the speed and acceleration. The calculated derivatives were then averaged over a moving window of 5 samples to reduce the noises. In the current work, Pandas and Matplotlib were then used for data aggregation, post-processing and visualization [24,25]. To investigate the influential parameters on the mechanical errors, correlation tests were performed between the mechanical parameters and their derivatives, using Pearson’s correlation test. Both integral data sets (about 3 × 108 entries for the Halcyon and 7 × 109 entries for the TB) are too large and efficiency-prohibitive for the correlation tests. As a result, 30 randomly sampled log files from both Linacs were selected for the correlation analysis, where the significance of the correlation was defined with p-value <0.01. The errors of the components (MLC, gantry, MU) were deemed as the parameters of interest (POI) in the correlation matrix. The parameters correlated strongly with the POIs were subsequently identified, and corresponding parameter-error pairs were retrieved from the integral data set for a joint distribution plot. In addition, each pair of the joint distributions of both Linacs were also compared to evaluate the differences between the two Linacs.
2.2. Log files For the Halcyon, all treatment-related log files for a cohort of twenty patients under the institutional review board-approved clinical study (approval number: 2017QX013) was retrieved from the TDS for a retrospective study, where sixteen patients were treated with VMAT technique during February to May in 2018. The number of IMRT treatment fractions was too limited (n = 20 ) to perform statistical analysis. After filtering out the IMRT deliveries, the Halcyon data set was reduced to 480 log files, corresponding to 18 plans. At the same time, 3951 log files of VMAT delivery in 2018 were retrieved from a TB system for comparison analysis, corresponding to 291 patients and 320 plans. The treated fraction per plan was relatively low on the TB, due to the fact that the TB machine treated a large amount of plans single fractioned from beam-matched machines. Treated plan statistics summaries on two machines were listed in Table 1. The plan complexity was evaluated using the MU per arc (MU/arc), and the Edge Metric (EM), defined as the ratio of the perimeter over the area of the field [18]. Since the introduction of the TB system, the output log files, named as trajectory log files, are in binary format, encoded according to the manufacturer’s log file format specification. The log file records the mechanical component positions (gantry, collimator, MLC, etc.), as well as the accumulated Monitor Units (MU), at a sampling frequency of 15
(ej
e¯)i
2.1. Equipments
mi =
j =1
(2)
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Table 1 Summary of VMAT plan statistics on both Halcyon and TB; the noted uncertainty refers to one standard deviation (k = 1) Abbreviations: H&N: Head and Neck; EM: Edge Metric; Plan #: Number of plans. Halcyon Sites H&N Thorax Abdomen Pelvis Brain Limb Total
TB
Plan #
EM (mm 1 )
MU/arc (MU )
Plan #
EM (mm 1)
MU/arc (MU )
2 10 2 4 0 0 18
0.11 ± 0.01 0.09 ± 0.01 0.10 ± 0.02 0.07 ± 0.01 N/A N/A 0.09 ± 0.02
217.2 ± 10.2 222.6 ± 45.9 231.7 ± 9.7 222.6 ± 45.9 N/A N/A 237.1 ± 56.1
132 89 17 69 11 2 320
0.10 ± 0.03 0.11 ± 0.03 0.10 ± 0.03 0.09 ± 0.03 0.10 ± 0.03 0.09 ± 0.03 0.10 ± 0.1
354.6 ± 62.4 303.6 ± 91.0 283.8 ± 128.5 346.1 ± 102.4 417.3 ± 128.3 195.1 ± 52.0 246.97 ± 67.3
In order to compare the gravity effect on the leaf positioning error, the instant leaf errors were binned into a 2D distribution as a function of collimator and gantry angle. Since the collimator angle distribution was discrete and concentrated around the 0° , 90° , and 270°, the data set was dichotomized into two categories: 1. from 157.5° to 202.5° , i.e. almost parallel to the gravity direction; 2. from 67.5° to 112.5° and from 247.5° to 292.5°, i.e. almost perpendicular to the gravity direction. The average leaf error belonging to either bank (noted as bank error) was plotted as a function of the gantry angle. Our preliminary study has shown that no significant difference was observed between the error distributions of the distal and proximal MLC layers on the Halcyon1. Therefore the bank error for the Halcyon was reported as the weighted sum of the two MLC layers.
expected parameters from the log file and the DICOM RT plan, due to: 1. existence of inherent difference between the two; 2. numerical errors introduced by interpolation and down-sampling, as is noted in the supporting materials. The differences in D10%, D50%, D95% , D99% , and Dmax of the PTV between two plans (expected/actual) were used to evaluate the delivery performance, where the dose-volume parameters (DVP) of the expected plans were regarded as the reference. The reported differences in the DVPs were normalized by the prescription dose of each plan. All dose calculations and DVH analysis were performed on a test box with 15.0 Eclipse TPS using Analytical Anisotropic Algorithm (AAA, version 15017), with a calculation grid of 2.5 mm. 3. Results
2.4. Log file-based dose verification
3.1. Log file statistics and analysis
To compare the dosimetric accuracies on two Linacs, the dose distributions based on the log files were calculated with the TPS dose calculation engine. Due to limitation on computing resources, a thorough dose recalculation on all the log files was not possible. As a result, a sampling dose calculation was performed on the most deviated log files in terms of mechanical parameters, using a simple heuristic function, defined as N
Hi = j=1
mij
m¯ j
Table 2 presents aggregate error statistics for both Halcyon and TB systems. The leaf error statistics are comparable between the two Linacs, yet the observed differences in all three metrics (mean leaf error, leaf error mean RMS, and 95th percentile of the leaf error) are statistically significant ( p < 0.001). Such significance may be explained by the presence of large sized data. The differences on the statistical metrics of the gantry angle error for two Linacs are also statistically significant ( p < 0.001). The studied gantry angle metrics on the TB are all larger than those on the Halcyon, where the largest difference is 0.087° for the 95th error percentile. The statistics on MU error between the Halcyon and the TB are similar as well. It is noted that the recorded MU errors reflect the accumulated MU difference during the delivery process, thus impact less of the actual delivery performance compared to the errors on gantry and MLC leaves. Fig. 2 (a) and (b) present the correlation matrices of selected mechanical parameters of the Halcyon and the TB respectively. It is noted that the gantry speed is negatively correlated (rp,Halcyon = 0.42 , rp,TB = 0.72 ) with the gantry acceleration on both Linacs. These correlations are related to the motion patterns of the Linacs. The gantry speed for the VMAT plans was set at the nominal maximum value per Linac, in order to reduce treatment time and maintain delivery accuracy, as is pointed out by Nicolini et al. [27]. This motion pattern would generate a large amount of data at the high speed/low acceleration region and much less data in the low speed/high acceleration region, forming a negative correlation between the gantry speed and the gantry acceleration. The MLC leaf error is observed to be positively correlated with the MLC leaf speed (rp,Halcyon = 0.47, rp,TB = 0.89) on both Linacs. Positive correlation between the gantry error and the gantry acceleration (rp,Halcyon = 0.17, rp,TB = 0.49) is observed. For both Linacs, the MU error does not exhibit any strong correlation with the investigated parameters. The most strongly correlated parameter pairs with respective errors (i.e. MLC leaf error/MLC leaf speed and gantry error/ gantry acceleration) were plotted in joint distribution to investigate major error sources. Since one of the main features on the Halcyon is
2
mj
(3)
where the mij refers to the metrics of the i th log file, including the error mean and the RMS for MLC, gantry angle, and MU. The m¯ j and the mj refer to the mean and the standard deviation of the jth metric over all the log files of either Linac. Fig. 1 illustrates the H distribution over the data sets for both Linacs. The H refers to the negative log probability of a multi-variate normal distribution, therefore log files with the higher H values deviate further from the mean of the distribution. 23 and 100 log files from the Halcyon and the TB data set were chosen for dose recalculation respectively, as is shown in Fig. 1. The actual mechanical parameters from the log files were first interpolated as a function of the control points and then written into a modified DICOM RT plan file, where pydicom was used to parse and modify DICOM RT plan files [26]. For each delivered fraction, both expected and actual parameters extracted from the log files were used to reconstruct two DICOM RT plans, corresponding to the actual plan and the expected plan. The dose distributions of these two DICOM RT plans were compared in form of dose-volume histogram (DVH) to evaluate the dosimetric impact of the parameter difference between the delivered plan and the expected plan, instead of comparing directly with the original DICOM RT plan. The rationale behind this is to avoid difference between 1
Details are described in the supporting materials. 16
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Fig. 1. The H distribution for (a) Halcyon and (b) TB; shadowed bins refer to selected log files for dose recalculation; the figure b is plotted in log scale to show the tail distribution. Table 2 Error statistics categorized according to mechanical components over all the log files of corresponding Linac. Abbreviations: g1: The skewness of the sample mean distribution; RMS: average root mean square; 95th : mean 95th percentile of the absolute samples. Halcyon component error leaf (mm) gantry (deg) MU (MU)
TB
mean
g1
RMS
95th
mean
g1
RMS
95th
−0.002 −0.002 0.016
1.48 0.06 −0.13
0.028 0.015 0.015
0.078 0.026 0.06
0.001 −0.001 0.018
−0.07 −1.09 0.79
0.031 0.065 0.013
0.064 0.113 0.05
Fig. 2. Correlation matrix of selected mechanical parameters based on 30 randomly selected log files for (a) Halcyon and (b) TB.
the increase of the gantry rotation speed, the correlation between the gantry error and the gantry speed was further studied as well. The joint distribution of the leaf error and the leaf speed is shown in Fig. 3 (a) and (c) for the Halcyon and the TB respectively. It is noted that the resulting distribution map is normalized and plotted in log scale due to the extremely imbalanced distribution. The Halcyon leaf error exhibits a wider spread compared with the TB leaf error
distribution, where the most significant difference lies in the high leaf speed/low leaf error region of the joint distribution map. In the high leaf speed area, The lower bounds of leaf errors distribution are 0 mm/s for Halcyon, while the lower bounds of leaf errors remain non-zero for the TB. To reveal the leaf error differences between two Linacs, three pronounced peaks are selected from marginal leaf speed distributions, and corresponding conditional error distributions are presented in 17
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Fig. 3. 2D joint distribution on leaf error (egantry ) and leaf speed (v leaf ) for: (a) Halcyon; (c) TB; and conditional distribution of leaf error on selected leaf speeds for: (b) Halcyon; (d) TB, where the given leaf speed was marked in (a)/(c) with corresponding color. e¯ notes the average leaf errors in the conditional distributions.
Fig. 3 (b) and (d). The leaf speeds of the selected peaks are 14.6 mm/s, 29.8 mm/s, 50.0 mm/s for the Halcyon, and 6.9 mm/s, 16.3 mm/s, 22.4 mm/s for the TB. Comparing the conditional distributions in three separate pairs, it can be noted that the errors on the Halcyon tend to have a wider spread, but the average errors are of the same magnitude for the two Linacs. Fig. 4 (a) and (c) illustrate the joint distribution of instant gantry error and gantry acceleration for Halcyon and TB respectively. The gantry acceleration distribution in Fig. 4 (c) is presented in lower resolution compared with Fig. 4 (a) due to limited gantry angle reading resolution on the TB system. The modal gantry errors are 0.012° and 0.044° for the Halcyon and the TB respectively. The joint distribution for the Halcyon does not exhibit any clear pattern, due to lack of
statistics. However, the joint distribution of gantry error and acceleration for the TB presents clear positive correlation, where the conditional distributions shown in 4 (b) and (d) demonstrates different error components given different acceleration values. Fig. 5 shows the joint distribution of gantry rotation speed and gantry error. Different to previous distributions, data at beam-off moments were included. In both distributions, major peaks can be observed located at gantry = 12.0°/s, 6.0°/s for the Halcyon and the TB respectively, agreeing with the planned gantry speeds. For the Halcyon, 73% of total data points are within the gantry speed range 11.5°/s 12.5°/s , and for the TB, 58% of total data points are gantry 6.5°/s . Another diswithin the gantry speed range 5.5°/s gantry tinctive peak located at gantry = 24.0°/s can be observed in the 18
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Fig. 4. 2D joint distribution on gantry error (egantry ) and gantry acceleration (agantry ) for: (a) Halcyon; (c) TB, and conditional distribution of leaf error on selected gantry acceleration for: (b) Halcyon; (d) TB, where the given gantry acceleration was marked in (a)/(c) with corresponding color; e¯ notes the average gantry angle errors in the conditional distributions.
marginal distribution of gantry speed for the Halcyon, which corresponds to the maximum gantry speed at beam-off moments. The average gantry error at gantry = 24.0°/s is effectively larger than the gantry error at planned maximum speed gantry = 12.0°/s . Fig. 5 (b) and (d) illustrates the conditional distributions of the gantry angle errors given representative gantry speeds. The distributions with gantry,H = 12.0° /s and gantry,TB = 6.0° /s on both Linacs exhibit Gaussian-like forms, where the average gantry angle error on the TB (e¯gantry,TB = 0.04° ) is effectively larger than that on the Halcyon (e¯gantry,H = 0.01°). Fig. 6 (a) and (b) shows the bank error distribution as a function of the gantry angle bins on two Linacs. The leaf error curves of both banks
exhibit opposing sinusoidal patterns for both Linacs when the collimator is parallel to the gravity direction (i.e. collimator angle close to 180° ), introducing a systematic field shift towards the gravity direction. It is noted that this systematic field shift for the Halcyon is significantly greater compared with that for TB, when the gantry angle is around 180° . This minimum and maximum systematic shifts for the Halcyon are −0.03 mm and 0.04 mm respectively, and for TB, the corresponding values are −0.01 mm and 0.01 mm. The difference in the noise level between the curves is evidently due to data set size difference on the two Linacs. When the collimator is perpendicular to the gravity direction (i.e. collimator angle close to 270° or 90° ), the leaf error exhibits no significant variation with regard to the gantry angle. 19
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Fig. 5. 2D joint distribution on gantry error and gantry speed for: (a) Halcyon; (c) TB, and conditional distribution of the leaf error on selected leaf speeds for: (b) Halcyon; (d) TB. Data registered at beam-off states are also plotted in blue dashed line; the relative histograms of gantry speed/error at beam-on state are normalized to the total population (including data at beam-off states) and shown in respective marginal distributions; e¯ notes the average gantry angle errors in the conditional distributions.
3.2. Log file based-dose verification
and D99% is more susceptible to such perturbations than D10%.
Table 3 demonstrates the average difference and standard deviation in the selected DVPs for both Linacs. The most significant mean differences among the DVPs were D99% , which were both within 0.5% for both Linacs. Overall the average difference of DVPs of the TB were slightly higher than those of the Halcyon. One can notice an increasing tendency of the mean and standard deviation of the DVP errors as the volume percentage in the DVP increases. This observation agrees with the intuition, since the variation of the mechanical parameters can be regarded perturbations of the fluence (direction-wise and field wise),
4. Discussion In this study, both Linacs have shown strong correlation between the MLC leaf error and the MLC leaf speed, as is noted in previous study [28]. The parameter pairs were plotted in the joint distributions per control cycle in this study, instead of averaging over each log file, in order to reveal the complete distribution of parameters. Such presentation is not directly comparable with previous studies. However, the calculated mean leaf RMS error and mean 95th percentile error on 20
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Fig. 6. Average leaf error of bank a/b as a function of the gantry angle for (a) Halcyon; (b) TB, where the leaf error were binned into two groups based on the collimator angle.
rotation speed and positive correlation with the gantry acceleration on both Linacs, as is shown in Fig. 4 and Fig. 5. It can be noted that large amounts of data points concentrated within the low acceleration/ planned speed region, and varying acceleration or speed happens only when: 1. the delivery starts or ends; 2. when the dose rate achieved maximum planned value, i.e., additional gantry speed modulation is required. One could notice that the average gantry accelerations were 2.47°/s2 and 2.31°/s2 for TB and Halcyon respectively in Fig. 4. The gantry acceleration on the TB might be overestimated due to the limited gantry angle reading resolution. The observed gantry angle reading resolution on the TB is 0.003° and can introduce numerical error as large as 7.5°/s2 for acceleration since the derivative operation is prone to magnify the noise. In Fig. 5, data points at the beam-off moments were included to highlight the gantry speed distribution on the Halcyon. One can note that the gantry error on the Halcyon within the speed interval 12°/s < gantry < 24°/s showed a stronger correlation to the gantry speed compared with the lower speed interval gantry < 12°/s . On the tested Halcyon system (Version 1.0), maximum allowed gantry speed for delivery is 12.0°/s . Such limit on gantry rotation speed could be a compromise of leaf speed limit, dose rate limit, or achievable mechanical accuracy of related components. Nevertheless, the average gantry speed at beam-on moments was 10.96°/s and 5.19°/s for the Halcyon and the TB, indicating a twofold improvement in delivery efficiency. The gantry maintains a rotation speed of 24°/s for MV-CBCT image acquisition and rotation at beam-off moments, where additional clinical throughput can be expected. Michiels et al. recently reported a comparison in delivery efficiency between the Halcyon and the TB system for Head and Neck cases, where a twofold reduction of the integral treatment process time (including volumetric image acquisition and plan delivery) was found [9]. The current study employed a comparison of the DVPs to investigate the dosimetric difference introduced by mechanical deviation between the two Linacs. The simple heuristic function used to sort out the “outlier” log files employed two metrics of different parts: the mean and the RMS, representing the systematic and random error components. However, this heuristic function is by no means optimal, since the intrinsic model imposed some strong constraints on the metrics in Eq. 3: (1) the distribution of should be at least Gaussian-like; (2) the potential covariance between the metrics are ignored. One interesting finding is that the first 100 log files ranked by the H value form a very long tailed distribution of plan frequency: 53 delivered log files in the TB data set corresponds to only 3 plans (2 H&N cases and 1 thorax case). Similar
Table 3 Relative DVP difference of the PTV between expected and actual mechanical parameters from both Linacs; the noted error interval represents one standard deviation. Parameters
D10% D50% D95% D99% Dmax
Halcyon
0.003 0.001 0.023 0.05 0.003
± ± ± ± ±
0.16% 0.14% 0.11% 0.11% 0.21%
TB
0.05 0.05 0.12 0.20 0.19
± ± ± ± ±
0.11% 0.17% 0.56% 1.11% 0.32%
the TB Linac are respectively 0.031 mm and 0.064 mm from Table 2, comparable with results obtained by Olasolo et al. and Kerns et al. [20,21]. The positioning accuracy of MLC leaf on Halcyon is controlled at a similar level of that on TB, while the average leaf speed on Halcyon doubles. The joint distribution of MLC leaf error and leaf speed of Halcyon have shown different patterns compared with that of TB, which could explain the weaker correlation on the Halcyon than that of the TB shown in Fig. 2. An excess of the nominal leaf speed limit has been observed in Fig. 2(a) and (c) on both Linacs. About 0.01% of data samples from TB exceeded 25 mm/s. About 0.03% of data samples from Halcyon exceeded 50 mm/s, which are the nominal maximum leaf speeds in TPS. Such difference should be attributed mainly by noise and binning error. TG-142 report recommended using 95th percentile and maximum error RMS, defined as the RMS of maximum error per leaf during a delivery as key parameter to evaluate MLC leaf performance, where the recommended acceptance threshold for both metrics were set at 3.5 mm [13]. Based on the obtained results in Table 2, such criteria turned out to be too loose for the Halcyon and the TB Linacs, where more appropriate criteria should be established. The gantry speed and acceleration have been found to be weakly correlated with the MLC leaf error for both Linacs. This can be explained by the positive correlation between gantry speed and MLC leaf speed, as faster gantry rotation would need faster leaf travels to achieve required modulation level [21]. The gravity effect on the MLC leaf error has been shown to be systematic when the MLC leaves are along the gravity direction. This systematic error introduced by gravity on Halcyon was more significant compared with the TB. For VMAT technique, the systematic errors caused by the gravity may introduce less dosimetric impact due to the potential compensation, therefore further study with IMRT technique on the Halcyon would be of interest. The gantry error exhibited a negative correlation with the gantry 21
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case is observed in the Halcyon data set: 1 H&N plan contributed 13 log files in the first 25 ranked by the H value. This finding suggests that the mechanical errors might be very tightly related to the complexities of the plans. A higher mean and standard deviations of the DVPs on the TB can be observed compared with those on the Halcyon. This comparison is not completely fair, given the differences in the data set size, the daily workload and the served age of the two Linacs. Nevertheless, the overall dosimetric deviations for the PTV are relatively low in a clinical perspective. Several previous studies have notably investigated the dosimetric errors related to manually introduced systematic MLC or gantry angle errors [29–31]. For example, Oliver et al. found that an average change of 0.28%/mm and 2.54%/mm for the D95% of the PTV for random and systematic MLC errors respectively [32]. Unlike the previous studies, the investigated dosimetric difference in the current study incorporates mechanical errors recorded during clinical treatment, including both random and systematic errors. However, the DVP differences on the organs at risks (OAR) were not investigated because the data set includes various treatment sites and various OARs were present with little statistical significance. In addition, Hernandez et al. pointed out that the dosimetric influence of mechanical errors are also dependent on the size of the ROI as well [33]. Additional site-specific studies should be conducted to address these limits in the current work. The actual MLC positions in the log files may be inaccurate in some circumstances, as is proven by the cross-check against electronic portal image tests [16,17]. Therefore the routine QA process based on independent QA tools can be an opportunity for the log file “calibrations”. On the other hand, the mechanical data from the log files during the routine QA process provide a source for further analysis. For example, the aggregate mechanical data from the log files during daily QA process (or clinical treatment) can be sorted into time series, where statistical methods can be employed to analyze these data, so that potential system dysfunction and anomaly can be predicted [34,35]. These projects fall into the domain of anomaly detection, which finds extensive applications in industrial system control, insurance and cyber-security. A thorough discussion of anomaly detection on the QA in radiotherapy is obviously beyond the scope of this article. Nevertheless, establishing statistical process control would be a great starting point, since the performance of most mechanical components degrades in a gradual manner [36]. The statistical analysis can effectively indicate such degradation, and preventive alerts can be signaled based on established statistical model.
Acknowledgments This work was jointly supported by the Capital Funds for Health Improvement and Research (2018-4-1027), Ministry of Education Science and Technology Development Center (2018A01019), Beijing Municipal Administration of Hospitals Incubating Program (PX2019042), National Key R&D Program of China (2019YFF01014405) and Beijing Municipal Natural Science Foundation (1202009). The authors thank Dr. James Kerns for his help and explanation on the log file parsing module in the pylinac package. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, athttps://doi.org/10.1016/j.ejmp.2020.01.023. References [1] Otto Karl. Volumetric modulated arc therapy: IMRT in a single gantry arc. Med Phys 2008;35(1):310–7. [2] Clemente Stefania, BinBin Wu, Sanguineti Giuseppe, Fusco Vincenzo, Ricchetti Francesco, Wong John, McNutt Todd. Smartarc-based volumetric modulated arc therapy for oropharyngeal cancer: a dosimetric comparison with both intensitymodulated radiation therapy and helical tomotherapy. Int J Rad Oncol Biol Phys 2011;80(4):1248–55. [3] Stieler Florian, Wolff Dirk, Schmid Heike, Welzel Grit, Wenz Frederik, Lohr Frank. A comparison of several modulated radiotherapy techniques for head and neck cancer and dosimetric validation of VMAT. Radiother Oncol 2011;101(3):388–93. [4] Budgell Geoff, Brown Kirstie, Cashmore Jason, Duane Simon, Frame John, Hardy Mark, Paynter David, Thomas Russell. IPEM topical report 1: guidance on implementing flattening filter free (FFF) radiotherapy. Phys Med Biol 2016;61(23):8360. [5] Gasic D, Ohlhues L, Brodin NP, Fog LS, Pommer T, Bangsgaard JP, Munck af Rosenschöld P. Oc- 0389: Comparison between conventional and FFF beams for IMAT radiation therapy of various treatment sites. Radiother Oncol 2014;111:S151–2. [6] Lechner Wolfgang, Kragl Gabriele, Georg Dietmar. Evaluation of treatment plan quality of IMRT and VMAT with and without flattening filter using Pareto optimal fronts. Radiother Oncol 2013;109(3):437–41. [7] Netherton Tucker, Li Yuting, Nitsch Paige, Shaitelman Simona, Balter Peter, Gao Song, Klopp Ann, Muruganandham Manickam, Court Laurence. Interplay effect on a 6-mv flattening-filter-free linear accelerator with high dose rate and fast multi-leaf collimator motion treating breast and lung phantoms. Med Phys 2018;45(6):2369–76. [8] Lim Tze Yee, Dragojević Irena, Hoffman David, Everardo Flores-Martinez, Kim GweYa. Characterization of the Halcyon multileaf collimator system. J Appl Clinical Med Phys 2019;20(4):106–14. [9] Michiels Steven, Poels Kenneth, Crijns Wouter, Delombaerde Laurence, De Roover Robin, Vanstraelen Bianca, Haustermans Karin, Nuyts Sandra, Depuydt Tom. Volumetric modulated arc therapy of head-and-neck cancer on a fast-rotating O-ring linac: Plan quality and delivery time comparison with a C-arm linac. Radiother Oncol 2018;128(3):479–84. [10] Taoran Li, Ryan Scheuermann, Alexander Lin, Boon-Keng Kevin Teo, Wei Zou, Samuel Swisher-McClure, Michelle Alonso-Basanta, John N Lukens, Alireza Fotouhi Ghiam, Chris Kennedy, et al. Impact of multi-leaf collimator parameters on head and neck plan quality and delivery: A comparison between Halcyon and Truebeam treatment delivery systems. Cureus, 10(11), 2018. [11] De Roover Robin, Crijns Wouter, Poels Kenneth, Michiels Steven, Nulens An, Vanstraelen Bianca, Petillion Saskia, De Brabandere Marisol, Haustermans Karin, Depuydt Tom. Validation and IMRT/VMAT delivery quality of a preconfigured fastrotating O-ring linac system. Med Phys 2019;46(1):328–39. [12] Sun Baozhou, Rangaraj Dharanipathy, Palaniswaamy Geethpriya, Yaddanapudi Sridhar, Wooten Omar, Yang Deshan, Mutic Sasa, Santanam Lakshmi. Initial experience with TrueBeam trajectory log files for radiation therapy delivery verification. Practical Radiation Oncol 2013;3(4):e199–208. [13] Klein Eric E, Hanley Joseph, Bayouth John, Yin Fang Fang, Simon William, Dresser Sean, Serago Christopher, Aguirre Francisco, Ma Lijun, Arjomandy Bijan, Liu Chihray, Sandin Carlos, Holmes Todd. Task group 142 report: Quality assurance of medical accelerators. Med Phys 2009;36(9):4197–212. [14] Teke Tony, Bergman Alanah M, Kwa William, Gill Bradford, Duzenli Cheryl, Antoniu Popescu I. Monte Carlo based, patient-specific RapidArc QA using Linac log files. Med Phys 2010;37(1):116–23. [15] Sun Baozhou, Rangaraj Dharanipathy, Boddu Sunita, Goddu Murty, Yang Deshan, Palaniswaamy Geethpriya, Yaddanapudi Sridhar, Wooten Omar, Mutic Sasa. Evaluation of the efficiency and effectiveness of independent dose calculation followed by machine log file analysis against conventional measurement based IMRT QA. J Appl Clin Med Phys 2012;13(5):140–54. [16] Agnew A, Agnew CE, Grattan MWD, Hounsell AR, McGarry CK. Monitoring daily MLC positional errors using trajectory log files and EPID measurements for IMRT and VMAT deliveries. Phys Med Biol 2014;59(9):N49.
5. Conclusion This work compared the delivery accuracy in VMAT treatments by log file analysis on the TB and the Halcyon TDS. The delivery accuracy was compared in both mechanical and dosimetric aspects. The newly designed dual-layered MLC on the Halcyon was shown to achieve similar accuracy with the Millennium 120 MLC on the TB, with a higher average leaf travel speed. The most significant improvement of the Halcyon lies in the gantry positioning accuracy, where the 95th percentiles of gantry error were 0.026° and 0.113° for Halcyon and TB respectively. In addition, the log file analysis on Halcyon gantry angle revealed different mean error level between beam-on and beam-off states. The dosimetric analysis showed that the existing error on both Linacs can induce DVP variations of the PTV of the order of 0.1%, with a maximum standard deviation of 1.1%. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 22
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R. Wang, et al. [17] Neal Brian, Ahmed Mahmoud, Kathuria Kunal, Watkins Tyler, Wijesooriya Krishni, Siebers Jeffrey. A clinically observed discrepancy between image-based and logbased MLC positions. Med Phys 2016;43(6Part1):2933–5. [18] Younge Kelly C, Roberts Don, Janes Lindsay A, Anderson Carlos, Moran Jean M, Matuszak Martha M. Predicting deliverability of volumetric-modulated arc therapy (vmat) plans using aperture complexity analysis. J Appl Clin Med Phys 2016;17(4):124–31. [19] Pylinac.https://pylinac.readthedocs.io/en/stable/. Accessed: 2019-09-01. [20] Olasolo-Alonso José, Vázquez-Galiñanes Alejandro, Santiago Pellejero-Pellejero, José Fernando Pérez-Azorín. Evaluation of MLC performance in VMAT and dynamic IMRT by log file analysis. Physica Medica 2017;33:87–94. [21] Kerns James R, Childress Nathan, Kry Stephen F. A multi-institution evaluation of MLC log files and performance in IMRT delivery. Radiation Oncol 2014;9(1):176. [22] Kokoska Stephen, Zwillinger Daniel. CRC standard probability and statistics tables and formulae. CRC Press; 2000. [23] Stoer Josef, Bulirsch Roland. Introduction to numerical analysis vol. 12. Springer Science & Business Media; 2013. [24] McKinney Wes. Pandas: a foundational Python library for data analysis and statistics. Python High Perform Sci Comput 2011;14. [25] Hunter John D. Matplotlib A 2D graphics environment. Comput Sci Eng 2007;9(3):90. [26] Mason Darcy. SU-E-T-33: pydicom: an open source DICOM library. Med Phys 2011;38(6Part10). 3493–3493. [27] Nicolini Giorgia, Clivio Alessandro, Cozzi Luca, Fogliata Antonella, Vanetti Eugenio. On the impact of dose rate variation upon RapidArc implementation of volumetric modulated arc therapy. Med Phys 2011;38(1):264–71. [28] Clifton Ling C, Zhang Pengpeng, Archambault Yves, Bocanek Jiri, Tang Grace, LoSasso Thomas. Commissioning and quality assurance of RapidArc radiotherapy
delivery system. Int J Radiation Oncol Biol Phys 2008;72(2):575–81. [29] Kim Jung-in, Park So-Yeon, Kim Hak Jae, Kim Jin Ho, Ye Sung-Joon, Park Jong Min. The sensitivity of gamma-index method to the positioning errors of high-definition MLC in patient-specific VMAT QA for SBRT. Radiation Oncol 2014;9(1):167. [30] Betzel Gregory T, Yi Byong Yong, Niu Ying, Yu Cedric X. Is RapidArc more susceptible to delivery uncertainties than dynamic IMRT? Med Phys 2012;39(10):5882–90. [31] Katsuta Yoshiyuki, Kadoya Noriyuki, Fujita Yukio, Shimizu Eiji, Matsunaga Kenichi, Matsushita Haruo, Majima Kazuhiro, Jingu Keiichi. Quantification of residual dose estimation error on log file-based patient dose calculation. Physica Medica 2016;32(5):701–5. [32] Oliver Mike, Gagne Isabelle, Bush Karl, Zavgorodni Sergei, Ansbacher Will, Beckham Wayne. Clinical significance of multi-leaf collimator positional errors for volumetric modulated arc therapy. Radiotherapy Oncol 2010;97(3):554–60. [33] Hernandez V, Abella R, Calvo JF, Jurado-Bruggemann D, Sancho I, Carrasco P. Determination of the optimal tolerance for MLC positioning in sliding window and VMAT techniques. Med Phys 2015;42(4):1911–6. [34] Able Charles M, Baydush Alan H, Nguyen Callistus, Gersh Jacob, Ndlovu Alois, Rebo Igor, Booth Jeremy, Perez Mario, Sintay Benjamin, Munley Michael T. A model for preemptive maintenance of medical linear accelerators-predictive maintenance. Radiation Oncol 2016;11(1):36. [35] Binbin Wu, Zhang Pengpeng, Tsirakis Bill, Kanchaveli David, LoSasso Thomas. Utilizing historical mlc performance data from trajectory logs and service reports to establish a proactive maintenance model for minimizing treatment disruptions. Med Phys 2019;46(2):475–83. [36] Pawlicki Todd, Whitaker Matthew, Boyer Arthur L. Statistical process control for radiotherapy quality assurance. Med Phys 2005;32(9):2777–86.
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Physica Medica journal homepage: www.elsevier.com/locate/ejmp
Original paper
Halcyon clinical performance evaluation: A log file-based study in comparison with a C-arm Linac
T
Ruoxi Wang, Yi Du, Kaining Yao, Zhuolun Liu, Hanlin Wang, Haizhen Yue, Yibao Zhang, ⁎ Hao Wu Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
ABSTRACT
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.
1. Introduction In modern-day radiotherapy, Volumetric Modulated Arc Therapy (VMAT) is a delivery technique leveraging the simultaneous modulation of gantry angle, MLC leaf position, and dose rate [1]. Compared with many-field Intensity Modulated Radiation Therapy (IMRT), VMAT could achieve similar dose comformity while greatly reducing delivery time [2,3]. The appearance of flattening filter free (FFF) beams indicates further reduction in delivery time. However, due to current speed limit on gantry rotation and MLC leaf movement, major improvement in delivery efficiency has not been observed with the use of FFF beams [4–6]. The Halcyon linear accelerator (Varian Medical Systems, Palo Alto, CA) is a fast-rotating, ring-shaped Treatment Delivery System (TDS) introduced in 2017 [7]. This linear accelerator (Linac) was conceived with an emphasize on tightly controlled performance in order to facilitate acceptance tests, commissioning, and daily Quality Assurance (QA) activities. To improve clinical throughput and patient comfort, the Halcyon TDS combined the use of FFF beams, fast gantry rotation, and high-speed MLC leaf movement. The great increase in gantry rotation speed was mainly attributed by the enclosed gantry design, providing ⁎
stabler support compared with C-arm Linacs. The numerous changes in the Linac design warrant performance verification by the medical physicists. As a result, several studies have addressed monitoring mechanical parameters in QA environment on the Halcyon TDS. For example, Lim et al. have experimentally characterized the mechanical parameters of the dual-layered MLC, including leaf positioning accuracy, leaf transmission, interleaf leakage, and leaf end/edge effect [8]. Regarding the clinical performance, the interest was focused on the plan quality and efficiency improvement [9,10]. In the meantime, De Roover et al. performed an end-to-end dosimetric verification on anthropomorphic phantoms, and confirmed results within clinical dosimetric tolerances [11]. The delivered dose distribution depends on the modulation accuracy of the mechanical components, e.g. MLC leaf positioning, gantry positioning, etc.. Modern-day TDS incorporates software services recording mechanical component status in form of log files during the beam delivery. The temporal resolution of the log files is in magnitude of tens of milliseconds. The log files can provide very detailed information on the evolving status even for each MLC leaf position [12]. TG-142 report recommended an annual statistic check on the MLC positioning errors based on log file analysis [13]. Since the log file is a
Corresponding author. E-mail address: [email protected] (H. Wu).
https://doi.org/10.1016/j.ejmp.2020.01.023 Received 24 October 2019; Received in revised form 27 December 2019; Accepted 26 January 2020 1120-1797/ © 2020 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
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representation of the treatment delivery process with high temporal resolution, one could essentially calculate the delivered dose distribution in the patient, based on the previously obtained patient geometry. Several studies have explored such approach to verify the delivery quality and confirmed positive impact of the patient specific QA [14,15] based on independent dose calculation. It is noted that the aforementioned studies of log file analysis on Varian Linacs were carried out on Clinac and TrueBeam (TB) platforms. The Halcyon TDS records log files corresponding to treatment deliveries as well, therefore a log file-based approach evaluating delivery quality on the Halcyon is also possible. This study aims to answer the following question: With the design changes on the Halcyon, how is its dosimetric and mechanical accuracy compared with a TB Linac? The comparison was performed based on log files recorded during clinical VMAT deliveries on two Linacs: a Halcyon and a TB. To the authors’ best knowledge, this is the first study evaluating delivery performance via log files on the Halcyon TDS. This study reports on statistics of both mechanical performance and dosimetric outcome of 480 VMAT delivery fractions on the Halcyon TDS. In comparison, 3951 VMAT log files from a TB system were analyzed for performance evaluation. The delivered dose distribution has been recalculated based on the log file of each delivered fraction and compared with the planned dose distribution. Although previous studies have reported undetected MLC positioning error by log files due to encoder malfunction [16,17], this study intends to reveal potential different error patterns in mechanical parameters between the Halcyon and the TB system, which would be less influenced by the rare malfunction events.
50 Hz. Although the log files from the Halcyon have not been explicitly announced to comply with the trajectory log specification, initial tests have shown that these log files followed the previous specification with minimal exceptions. The expected MLC leaf positions from the log files have been compared with expected leaf positions from the DICOM RT plans and the robustness and accuracy of parsed machine parameters were validated. 2.3. Statistical analysis A Python script was written to automate the data processing pipeline. First, the log file was parsed utilizing the pylinac package [19], where both expected and actual positions/status of the relevant parameters (MLC leaves, jaw positions, gantry angle, MU, etc.) were extracted from the parsed log files. The differences between expected and actual values at each sampling point were calculated and regarded as the measured errors. In order to obtain comparable descriptive metrics with regard to the previous studies [20,21], the mean and the root mean square (RMS) of the error, the skewness of the error mean distribution, and the 95th percentile of the error amplitude were chosen as the representative metrics for the error distributions for MLC and gantry angle. The RMS error of MLC was defined as the mean of RMS error for all the leaves within a log file, similar to the definition by Kerns et al. [21]. The skewness of the error mean distribution was computed as the Fisher-Pearson skewness coefficient [22], given by
g1 =
m3 m 23/2
(1)
where the mi is the biased i th central moment, defined as
2. Materials and methods
1 N
N
The data acquisition was performed on two Linacs: a Halcyon and a TB. Unlike traditional Linac designs, The Halcyon system features both fixed primary collimator and secondary collimator, equipped with a dual-layered and staggered MLC as the beam shaping device. Detailed features of the Halcyon can be found in previous literature [9]. The TDS versions of Halcyon and TB in this work were respectively 1.0 and 2.5. The Treatment Planning System (TPS) used were Eclipse of version 13.6 and 15.1 for the TB and the Halcyon respectively.
where the ej is the error mean in the jth log file and e¯ is the average of the error mean over all the log files. Our preliminary study showed that the leaf error distribution presented two distinguished peaks, corresponding to the moving leaves and the static leaves respectively. Because most static leaves correspond to closed leaf pairs, only moving leaf positions were included into the analysis. Since the motion accuracy during the beam-off period is not of interest in a clinical perspective, all recorded parameters were filtered by the beam-on flag, unless otherwise specified. Unlike the other parameters, the recorded MU corresponds to the accumulated value at the given control point. Therefore the MU error at the last beam-on moment was extracted as the integral MU error of the fraction. The first and second order derivatives of corresponding angle/position over predefined time window (20 ms ) were calculated using the three-pointcentered difference method [23], referring to the speed and acceleration. The calculated derivatives were then averaged over a moving window of 5 samples to reduce the noises. In the current work, Pandas and Matplotlib were then used for data aggregation, post-processing and visualization [24,25]. To investigate the influential parameters on the mechanical errors, correlation tests were performed between the mechanical parameters and their derivatives, using Pearson’s correlation test. Both integral data sets (about 3 × 108 entries for the Halcyon and 7 × 109 entries for the TB) are too large and efficiency-prohibitive for the correlation tests. As a result, 30 randomly sampled log files from both Linacs were selected for the correlation analysis, where the significance of the correlation was defined with p-value <0.01. The errors of the components (MLC, gantry, MU) were deemed as the parameters of interest (POI) in the correlation matrix. The parameters correlated strongly with the POIs were subsequently identified, and corresponding parameter-error pairs were retrieved from the integral data set for a joint distribution plot. In addition, each pair of the joint distributions of both Linacs were also compared to evaluate the differences between the two Linacs.
2.2. Log files For the Halcyon, all treatment-related log files for a cohort of twenty patients under the institutional review board-approved clinical study (approval number: 2017QX013) was retrieved from the TDS for a retrospective study, where sixteen patients were treated with VMAT technique during February to May in 2018. The number of IMRT treatment fractions was too limited (n = 20 ) to perform statistical analysis. After filtering out the IMRT deliveries, the Halcyon data set was reduced to 480 log files, corresponding to 18 plans. At the same time, 3951 log files of VMAT delivery in 2018 were retrieved from a TB system for comparison analysis, corresponding to 291 patients and 320 plans. The treated fraction per plan was relatively low on the TB, due to the fact that the TB machine treated a large amount of plans single fractioned from beam-matched machines. Treated plan statistics summaries on two machines were listed in Table 1. The plan complexity was evaluated using the MU per arc (MU/arc), and the Edge Metric (EM), defined as the ratio of the perimeter over the area of the field [18]. Since the introduction of the TB system, the output log files, named as trajectory log files, are in binary format, encoded according to the manufacturer’s log file format specification. The log file records the mechanical component positions (gantry, collimator, MLC, etc.), as well as the accumulated Monitor Units (MU), at a sampling frequency of 15
(ej
e¯)i
2.1. Equipments
mi =
j =1
(2)
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Table 1 Summary of VMAT plan statistics on both Halcyon and TB; the noted uncertainty refers to one standard deviation (k = 1) Abbreviations: H&N: Head and Neck; EM: Edge Metric; Plan #: Number of plans. Halcyon Sites H&N Thorax Abdomen Pelvis Brain Limb Total
TB
Plan #
EM (mm 1 )
MU/arc (MU )
Plan #
EM (mm 1)
MU/arc (MU )
2 10 2 4 0 0 18
0.11 ± 0.01 0.09 ± 0.01 0.10 ± 0.02 0.07 ± 0.01 N/A N/A 0.09 ± 0.02
217.2 ± 10.2 222.6 ± 45.9 231.7 ± 9.7 222.6 ± 45.9 N/A N/A 237.1 ± 56.1
132 89 17 69 11 2 320
0.10 ± 0.03 0.11 ± 0.03 0.10 ± 0.03 0.09 ± 0.03 0.10 ± 0.03 0.09 ± 0.03 0.10 ± 0.1
354.6 ± 62.4 303.6 ± 91.0 283.8 ± 128.5 346.1 ± 102.4 417.3 ± 128.3 195.1 ± 52.0 246.97 ± 67.3
In order to compare the gravity effect on the leaf positioning error, the instant leaf errors were binned into a 2D distribution as a function of collimator and gantry angle. Since the collimator angle distribution was discrete and concentrated around the 0° , 90° , and 270°, the data set was dichotomized into two categories: 1. from 157.5° to 202.5° , i.e. almost parallel to the gravity direction; 2. from 67.5° to 112.5° and from 247.5° to 292.5°, i.e. almost perpendicular to the gravity direction. The average leaf error belonging to either bank (noted as bank error) was plotted as a function of the gantry angle. Our preliminary study has shown that no significant difference was observed between the error distributions of the distal and proximal MLC layers on the Halcyon1. Therefore the bank error for the Halcyon was reported as the weighted sum of the two MLC layers.
expected parameters from the log file and the DICOM RT plan, due to: 1. existence of inherent difference between the two; 2. numerical errors introduced by interpolation and down-sampling, as is noted in the supporting materials. The differences in D10%, D50%, D95% , D99% , and Dmax of the PTV between two plans (expected/actual) were used to evaluate the delivery performance, where the dose-volume parameters (DVP) of the expected plans were regarded as the reference. The reported differences in the DVPs were normalized by the prescription dose of each plan. All dose calculations and DVH analysis were performed on a test box with 15.0 Eclipse TPS using Analytical Anisotropic Algorithm (AAA, version 15017), with a calculation grid of 2.5 mm. 3. Results
2.4. Log file-based dose verification
3.1. Log file statistics and analysis
To compare the dosimetric accuracies on two Linacs, the dose distributions based on the log files were calculated with the TPS dose calculation engine. Due to limitation on computing resources, a thorough dose recalculation on all the log files was not possible. As a result, a sampling dose calculation was performed on the most deviated log files in terms of mechanical parameters, using a simple heuristic function, defined as N
Hi = j=1
mij
m¯ j
Table 2 presents aggregate error statistics for both Halcyon and TB systems. The leaf error statistics are comparable between the two Linacs, yet the observed differences in all three metrics (mean leaf error, leaf error mean RMS, and 95th percentile of the leaf error) are statistically significant ( p < 0.001). Such significance may be explained by the presence of large sized data. The differences on the statistical metrics of the gantry angle error for two Linacs are also statistically significant ( p < 0.001). The studied gantry angle metrics on the TB are all larger than those on the Halcyon, where the largest difference is 0.087° for the 95th error percentile. The statistics on MU error between the Halcyon and the TB are similar as well. It is noted that the recorded MU errors reflect the accumulated MU difference during the delivery process, thus impact less of the actual delivery performance compared to the errors on gantry and MLC leaves. Fig. 2 (a) and (b) present the correlation matrices of selected mechanical parameters of the Halcyon and the TB respectively. It is noted that the gantry speed is negatively correlated (rp,Halcyon = 0.42 , rp,TB = 0.72 ) with the gantry acceleration on both Linacs. These correlations are related to the motion patterns of the Linacs. The gantry speed for the VMAT plans was set at the nominal maximum value per Linac, in order to reduce treatment time and maintain delivery accuracy, as is pointed out by Nicolini et al. [27]. This motion pattern would generate a large amount of data at the high speed/low acceleration region and much less data in the low speed/high acceleration region, forming a negative correlation between the gantry speed and the gantry acceleration. The MLC leaf error is observed to be positively correlated with the MLC leaf speed (rp,Halcyon = 0.47, rp,TB = 0.89) on both Linacs. Positive correlation between the gantry error and the gantry acceleration (rp,Halcyon = 0.17, rp,TB = 0.49) is observed. For both Linacs, the MU error does not exhibit any strong correlation with the investigated parameters. The most strongly correlated parameter pairs with respective errors (i.e. MLC leaf error/MLC leaf speed and gantry error/ gantry acceleration) were plotted in joint distribution to investigate major error sources. Since one of the main features on the Halcyon is
2
mj
(3)
where the mij refers to the metrics of the i th log file, including the error mean and the RMS for MLC, gantry angle, and MU. The m¯ j and the mj refer to the mean and the standard deviation of the jth metric over all the log files of either Linac. Fig. 1 illustrates the H distribution over the data sets for both Linacs. The H refers to the negative log probability of a multi-variate normal distribution, therefore log files with the higher H values deviate further from the mean of the distribution. 23 and 100 log files from the Halcyon and the TB data set were chosen for dose recalculation respectively, as is shown in Fig. 1. The actual mechanical parameters from the log files were first interpolated as a function of the control points and then written into a modified DICOM RT plan file, where pydicom was used to parse and modify DICOM RT plan files [26]. For each delivered fraction, both expected and actual parameters extracted from the log files were used to reconstruct two DICOM RT plans, corresponding to the actual plan and the expected plan. The dose distributions of these two DICOM RT plans were compared in form of dose-volume histogram (DVH) to evaluate the dosimetric impact of the parameter difference between the delivered plan and the expected plan, instead of comparing directly with the original DICOM RT plan. The rationale behind this is to avoid difference between 1
Details are described in the supporting materials. 16
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Fig. 1. The H distribution for (a) Halcyon and (b) TB; shadowed bins refer to selected log files for dose recalculation; the figure b is plotted in log scale to show the tail distribution. Table 2 Error statistics categorized according to mechanical components over all the log files of corresponding Linac. Abbreviations: g1: The skewness of the sample mean distribution; RMS: average root mean square; 95th : mean 95th percentile of the absolute samples. Halcyon component error leaf (mm) gantry (deg) MU (MU)
TB
mean
g1
RMS
95th
mean
g1
RMS
95th
−0.002 −0.002 0.016
1.48 0.06 −0.13
0.028 0.015 0.015
0.078 0.026 0.06
0.001 −0.001 0.018
−0.07 −1.09 0.79
0.031 0.065 0.013
0.064 0.113 0.05
Fig. 2. Correlation matrix of selected mechanical parameters based on 30 randomly selected log files for (a) Halcyon and (b) TB.
the increase of the gantry rotation speed, the correlation between the gantry error and the gantry speed was further studied as well. The joint distribution of the leaf error and the leaf speed is shown in Fig. 3 (a) and (c) for the Halcyon and the TB respectively. It is noted that the resulting distribution map is normalized and plotted in log scale due to the extremely imbalanced distribution. The Halcyon leaf error exhibits a wider spread compared with the TB leaf error
distribution, where the most significant difference lies in the high leaf speed/low leaf error region of the joint distribution map. In the high leaf speed area, The lower bounds of leaf errors distribution are 0 mm/s for Halcyon, while the lower bounds of leaf errors remain non-zero for the TB. To reveal the leaf error differences between two Linacs, three pronounced peaks are selected from marginal leaf speed distributions, and corresponding conditional error distributions are presented in 17
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Fig. 3. 2D joint distribution on leaf error (egantry ) and leaf speed (v leaf ) for: (a) Halcyon; (c) TB; and conditional distribution of leaf error on selected leaf speeds for: (b) Halcyon; (d) TB, where the given leaf speed was marked in (a)/(c) with corresponding color. e¯ notes the average leaf errors in the conditional distributions.
Fig. 3 (b) and (d). The leaf speeds of the selected peaks are 14.6 mm/s, 29.8 mm/s, 50.0 mm/s for the Halcyon, and 6.9 mm/s, 16.3 mm/s, 22.4 mm/s for the TB. Comparing the conditional distributions in three separate pairs, it can be noted that the errors on the Halcyon tend to have a wider spread, but the average errors are of the same magnitude for the two Linacs. Fig. 4 (a) and (c) illustrate the joint distribution of instant gantry error and gantry acceleration for Halcyon and TB respectively. The gantry acceleration distribution in Fig. 4 (c) is presented in lower resolution compared with Fig. 4 (a) due to limited gantry angle reading resolution on the TB system. The modal gantry errors are 0.012° and 0.044° for the Halcyon and the TB respectively. The joint distribution for the Halcyon does not exhibit any clear pattern, due to lack of
statistics. However, the joint distribution of gantry error and acceleration for the TB presents clear positive correlation, where the conditional distributions shown in 4 (b) and (d) demonstrates different error components given different acceleration values. Fig. 5 shows the joint distribution of gantry rotation speed and gantry error. Different to previous distributions, data at beam-off moments were included. In both distributions, major peaks can be observed located at gantry = 12.0°/s, 6.0°/s for the Halcyon and the TB respectively, agreeing with the planned gantry speeds. For the Halcyon, 73% of total data points are within the gantry speed range 11.5°/s 12.5°/s , and for the TB, 58% of total data points are gantry 6.5°/s . Another diswithin the gantry speed range 5.5°/s gantry tinctive peak located at gantry = 24.0°/s can be observed in the 18
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Fig. 4. 2D joint distribution on gantry error (egantry ) and gantry acceleration (agantry ) for: (a) Halcyon; (c) TB, and conditional distribution of leaf error on selected gantry acceleration for: (b) Halcyon; (d) TB, where the given gantry acceleration was marked in (a)/(c) with corresponding color; e¯ notes the average gantry angle errors in the conditional distributions.
marginal distribution of gantry speed for the Halcyon, which corresponds to the maximum gantry speed at beam-off moments. The average gantry error at gantry = 24.0°/s is effectively larger than the gantry error at planned maximum speed gantry = 12.0°/s . Fig. 5 (b) and (d) illustrates the conditional distributions of the gantry angle errors given representative gantry speeds. The distributions with gantry,H = 12.0° /s and gantry,TB = 6.0° /s on both Linacs exhibit Gaussian-like forms, where the average gantry angle error on the TB (e¯gantry,TB = 0.04° ) is effectively larger than that on the Halcyon (e¯gantry,H = 0.01°). Fig. 6 (a) and (b) shows the bank error distribution as a function of the gantry angle bins on two Linacs. The leaf error curves of both banks
exhibit opposing sinusoidal patterns for both Linacs when the collimator is parallel to the gravity direction (i.e. collimator angle close to 180° ), introducing a systematic field shift towards the gravity direction. It is noted that this systematic field shift for the Halcyon is significantly greater compared with that for TB, when the gantry angle is around 180° . This minimum and maximum systematic shifts for the Halcyon are −0.03 mm and 0.04 mm respectively, and for TB, the corresponding values are −0.01 mm and 0.01 mm. The difference in the noise level between the curves is evidently due to data set size difference on the two Linacs. When the collimator is perpendicular to the gravity direction (i.e. collimator angle close to 270° or 90° ), the leaf error exhibits no significant variation with regard to the gantry angle. 19
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Fig. 5. 2D joint distribution on gantry error and gantry speed for: (a) Halcyon; (c) TB, and conditional distribution of the leaf error on selected leaf speeds for: (b) Halcyon; (d) TB. Data registered at beam-off states are also plotted in blue dashed line; the relative histograms of gantry speed/error at beam-on state are normalized to the total population (including data at beam-off states) and shown in respective marginal distributions; e¯ notes the average gantry angle errors in the conditional distributions.
3.2. Log file based-dose verification
and D99% is more susceptible to such perturbations than D10%.
Table 3 demonstrates the average difference and standard deviation in the selected DVPs for both Linacs. The most significant mean differences among the DVPs were D99% , which were both within 0.5% for both Linacs. Overall the average difference of DVPs of the TB were slightly higher than those of the Halcyon. One can notice an increasing tendency of the mean and standard deviation of the DVP errors as the volume percentage in the DVP increases. This observation agrees with the intuition, since the variation of the mechanical parameters can be regarded perturbations of the fluence (direction-wise and field wise),
4. Discussion In this study, both Linacs have shown strong correlation between the MLC leaf error and the MLC leaf speed, as is noted in previous study [28]. The parameter pairs were plotted in the joint distributions per control cycle in this study, instead of averaging over each log file, in order to reveal the complete distribution of parameters. Such presentation is not directly comparable with previous studies. However, the calculated mean leaf RMS error and mean 95th percentile error on 20
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Fig. 6. Average leaf error of bank a/b as a function of the gantry angle for (a) Halcyon; (b) TB, where the leaf error were binned into two groups based on the collimator angle.
rotation speed and positive correlation with the gantry acceleration on both Linacs, as is shown in Fig. 4 and Fig. 5. It can be noted that large amounts of data points concentrated within the low acceleration/ planned speed region, and varying acceleration or speed happens only when: 1. the delivery starts or ends; 2. when the dose rate achieved maximum planned value, i.e., additional gantry speed modulation is required. One could notice that the average gantry accelerations were 2.47°/s2 and 2.31°/s2 for TB and Halcyon respectively in Fig. 4. The gantry acceleration on the TB might be overestimated due to the limited gantry angle reading resolution. The observed gantry angle reading resolution on the TB is 0.003° and can introduce numerical error as large as 7.5°/s2 for acceleration since the derivative operation is prone to magnify the noise. In Fig. 5, data points at the beam-off moments were included to highlight the gantry speed distribution on the Halcyon. One can note that the gantry error on the Halcyon within the speed interval 12°/s < gantry < 24°/s showed a stronger correlation to the gantry speed compared with the lower speed interval gantry < 12°/s . On the tested Halcyon system (Version 1.0), maximum allowed gantry speed for delivery is 12.0°/s . Such limit on gantry rotation speed could be a compromise of leaf speed limit, dose rate limit, or achievable mechanical accuracy of related components. Nevertheless, the average gantry speed at beam-on moments was 10.96°/s and 5.19°/s for the Halcyon and the TB, indicating a twofold improvement in delivery efficiency. The gantry maintains a rotation speed of 24°/s for MV-CBCT image acquisition and rotation at beam-off moments, where additional clinical throughput can be expected. Michiels et al. recently reported a comparison in delivery efficiency between the Halcyon and the TB system for Head and Neck cases, where a twofold reduction of the integral treatment process time (including volumetric image acquisition and plan delivery) was found [9]. The current study employed a comparison of the DVPs to investigate the dosimetric difference introduced by mechanical deviation between the two Linacs. The simple heuristic function used to sort out the “outlier” log files employed two metrics of different parts: the mean and the RMS, representing the systematic and random error components. However, this heuristic function is by no means optimal, since the intrinsic model imposed some strong constraints on the metrics in Eq. 3: (1) the distribution of should be at least Gaussian-like; (2) the potential covariance between the metrics are ignored. One interesting finding is that the first 100 log files ranked by the H value form a very long tailed distribution of plan frequency: 53 delivered log files in the TB data set corresponds to only 3 plans (2 H&N cases and 1 thorax case). Similar
Table 3 Relative DVP difference of the PTV between expected and actual mechanical parameters from both Linacs; the noted error interval represents one standard deviation. Parameters
D10% D50% D95% D99% Dmax
Halcyon
0.003 0.001 0.023 0.05 0.003
± ± ± ± ±
0.16% 0.14% 0.11% 0.11% 0.21%
TB
0.05 0.05 0.12 0.20 0.19
± ± ± ± ±
0.11% 0.17% 0.56% 1.11% 0.32%
the TB Linac are respectively 0.031 mm and 0.064 mm from Table 2, comparable with results obtained by Olasolo et al. and Kerns et al. [20,21]. The positioning accuracy of MLC leaf on Halcyon is controlled at a similar level of that on TB, while the average leaf speed on Halcyon doubles. The joint distribution of MLC leaf error and leaf speed of Halcyon have shown different patterns compared with that of TB, which could explain the weaker correlation on the Halcyon than that of the TB shown in Fig. 2. An excess of the nominal leaf speed limit has been observed in Fig. 2(a) and (c) on both Linacs. About 0.01% of data samples from TB exceeded 25 mm/s. About 0.03% of data samples from Halcyon exceeded 50 mm/s, which are the nominal maximum leaf speeds in TPS. Such difference should be attributed mainly by noise and binning error. TG-142 report recommended using 95th percentile and maximum error RMS, defined as the RMS of maximum error per leaf during a delivery as key parameter to evaluate MLC leaf performance, where the recommended acceptance threshold for both metrics were set at 3.5 mm [13]. Based on the obtained results in Table 2, such criteria turned out to be too loose for the Halcyon and the TB Linacs, where more appropriate criteria should be established. The gantry speed and acceleration have been found to be weakly correlated with the MLC leaf error for both Linacs. This can be explained by the positive correlation between gantry speed and MLC leaf speed, as faster gantry rotation would need faster leaf travels to achieve required modulation level [21]. The gravity effect on the MLC leaf error has been shown to be systematic when the MLC leaves are along the gravity direction. This systematic error introduced by gravity on Halcyon was more significant compared with the TB. For VMAT technique, the systematic errors caused by the gravity may introduce less dosimetric impact due to the potential compensation, therefore further study with IMRT technique on the Halcyon would be of interest. The gantry error exhibited a negative correlation with the gantry 21
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case is observed in the Halcyon data set: 1 H&N plan contributed 13 log files in the first 25 ranked by the H value. This finding suggests that the mechanical errors might be very tightly related to the complexities of the plans. A higher mean and standard deviations of the DVPs on the TB can be observed compared with those on the Halcyon. This comparison is not completely fair, given the differences in the data set size, the daily workload and the served age of the two Linacs. Nevertheless, the overall dosimetric deviations for the PTV are relatively low in a clinical perspective. Several previous studies have notably investigated the dosimetric errors related to manually introduced systematic MLC or gantry angle errors [29–31]. For example, Oliver et al. found that an average change of 0.28%/mm and 2.54%/mm for the D95% of the PTV for random and systematic MLC errors respectively [32]. Unlike the previous studies, the investigated dosimetric difference in the current study incorporates mechanical errors recorded during clinical treatment, including both random and systematic errors. However, the DVP differences on the organs at risks (OAR) were not investigated because the data set includes various treatment sites and various OARs were present with little statistical significance. In addition, Hernandez et al. pointed out that the dosimetric influence of mechanical errors are also dependent on the size of the ROI as well [33]. Additional site-specific studies should be conducted to address these limits in the current work. The actual MLC positions in the log files may be inaccurate in some circumstances, as is proven by the cross-check against electronic portal image tests [16,17]. Therefore the routine QA process based on independent QA tools can be an opportunity for the log file “calibrations”. On the other hand, the mechanical data from the log files during the routine QA process provide a source for further analysis. For example, the aggregate mechanical data from the log files during daily QA process (or clinical treatment) can be sorted into time series, where statistical methods can be employed to analyze these data, so that potential system dysfunction and anomaly can be predicted [34,35]. These projects fall into the domain of anomaly detection, which finds extensive applications in industrial system control, insurance and cyber-security. A thorough discussion of anomaly detection on the QA in radiotherapy is obviously beyond the scope of this article. Nevertheless, establishing statistical process control would be a great starting point, since the performance of most mechanical components degrades in a gradual manner [36]. The statistical analysis can effectively indicate such degradation, and preventive alerts can be signaled based on established statistical model.
Acknowledgments This work was jointly supported by the Capital Funds for Health Improvement and Research (2018-4-1027), Ministry of Education Science and Technology Development Center (2018A01019), Beijing Municipal Administration of Hospitals Incubating Program (PX2019042), National Key R&D Program of China (2019YFF01014405) and Beijing Municipal Natural Science Foundation (1202009). The authors thank Dr. James Kerns for his help and explanation on the log file parsing module in the pylinac package. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, athttps://doi.org/10.1016/j.ejmp.2020.01.023. References [1] Otto Karl. Volumetric modulated arc therapy: IMRT in a single gantry arc. Med Phys 2008;35(1):310–7. [2] Clemente Stefania, BinBin Wu, Sanguineti Giuseppe, Fusco Vincenzo, Ricchetti Francesco, Wong John, McNutt Todd. Smartarc-based volumetric modulated arc therapy for oropharyngeal cancer: a dosimetric comparison with both intensitymodulated radiation therapy and helical tomotherapy. Int J Rad Oncol Biol Phys 2011;80(4):1248–55. [3] Stieler Florian, Wolff Dirk, Schmid Heike, Welzel Grit, Wenz Frederik, Lohr Frank. A comparison of several modulated radiotherapy techniques for head and neck cancer and dosimetric validation of VMAT. Radiother Oncol 2011;101(3):388–93. [4] Budgell Geoff, Brown Kirstie, Cashmore Jason, Duane Simon, Frame John, Hardy Mark, Paynter David, Thomas Russell. IPEM topical report 1: guidance on implementing flattening filter free (FFF) radiotherapy. Phys Med Biol 2016;61(23):8360. [5] Gasic D, Ohlhues L, Brodin NP, Fog LS, Pommer T, Bangsgaard JP, Munck af Rosenschöld P. Oc- 0389: Comparison between conventional and FFF beams for IMAT radiation therapy of various treatment sites. Radiother Oncol 2014;111:S151–2. [6] Lechner Wolfgang, Kragl Gabriele, Georg Dietmar. Evaluation of treatment plan quality of IMRT and VMAT with and without flattening filter using Pareto optimal fronts. Radiother Oncol 2013;109(3):437–41. [7] Netherton Tucker, Li Yuting, Nitsch Paige, Shaitelman Simona, Balter Peter, Gao Song, Klopp Ann, Muruganandham Manickam, Court Laurence. Interplay effect on a 6-mv flattening-filter-free linear accelerator with high dose rate and fast multi-leaf collimator motion treating breast and lung phantoms. Med Phys 2018;45(6):2369–76. [8] Lim Tze Yee, Dragojević Irena, Hoffman David, Everardo Flores-Martinez, Kim GweYa. Characterization of the Halcyon multileaf collimator system. J Appl Clinical Med Phys 2019;20(4):106–14. [9] Michiels Steven, Poels Kenneth, Crijns Wouter, Delombaerde Laurence, De Roover Robin, Vanstraelen Bianca, Haustermans Karin, Nuyts Sandra, Depuydt Tom. Volumetric modulated arc therapy of head-and-neck cancer on a fast-rotating O-ring linac: Plan quality and delivery time comparison with a C-arm linac. Radiother Oncol 2018;128(3):479–84. [10] Taoran Li, Ryan Scheuermann, Alexander Lin, Boon-Keng Kevin Teo, Wei Zou, Samuel Swisher-McClure, Michelle Alonso-Basanta, John N Lukens, Alireza Fotouhi Ghiam, Chris Kennedy, et al. Impact of multi-leaf collimator parameters on head and neck plan quality and delivery: A comparison between Halcyon and Truebeam treatment delivery systems. Cureus, 10(11), 2018. [11] De Roover Robin, Crijns Wouter, Poels Kenneth, Michiels Steven, Nulens An, Vanstraelen Bianca, Petillion Saskia, De Brabandere Marisol, Haustermans Karin, Depuydt Tom. Validation and IMRT/VMAT delivery quality of a preconfigured fastrotating O-ring linac system. Med Phys 2019;46(1):328–39. [12] Sun Baozhou, Rangaraj Dharanipathy, Palaniswaamy Geethpriya, Yaddanapudi Sridhar, Wooten Omar, Yang Deshan, Mutic Sasa, Santanam Lakshmi. Initial experience with TrueBeam trajectory log files for radiation therapy delivery verification. Practical Radiation Oncol 2013;3(4):e199–208. [13] Klein Eric E, Hanley Joseph, Bayouth John, Yin Fang Fang, Simon William, Dresser Sean, Serago Christopher, Aguirre Francisco, Ma Lijun, Arjomandy Bijan, Liu Chihray, Sandin Carlos, Holmes Todd. Task group 142 report: Quality assurance of medical accelerators. Med Phys 2009;36(9):4197–212. [14] Teke Tony, Bergman Alanah M, Kwa William, Gill Bradford, Duzenli Cheryl, Antoniu Popescu I. Monte Carlo based, patient-specific RapidArc QA using Linac log files. Med Phys 2010;37(1):116–23. [15] Sun Baozhou, Rangaraj Dharanipathy, Boddu Sunita, Goddu Murty, Yang Deshan, Palaniswaamy Geethpriya, Yaddanapudi Sridhar, Wooten Omar, Mutic Sasa. Evaluation of the efficiency and effectiveness of independent dose calculation followed by machine log file analysis against conventional measurement based IMRT QA. J Appl Clin Med Phys 2012;13(5):140–54. [16] Agnew A, Agnew CE, Grattan MWD, Hounsell AR, McGarry CK. Monitoring daily MLC positional errors using trajectory log files and EPID measurements for IMRT and VMAT deliveries. Phys Med Biol 2014;59(9):N49.
5. Conclusion This work compared the delivery accuracy in VMAT treatments by log file analysis on the TB and the Halcyon TDS. The delivery accuracy was compared in both mechanical and dosimetric aspects. The newly designed dual-layered MLC on the Halcyon was shown to achieve similar accuracy with the Millennium 120 MLC on the TB, with a higher average leaf travel speed. The most significant improvement of the Halcyon lies in the gantry positioning accuracy, where the 95th percentiles of gantry error were 0.026° and 0.113° for Halcyon and TB respectively. In addition, the log file analysis on Halcyon gantry angle revealed different mean error level between beam-on and beam-off states. The dosimetric analysis showed that the existing error on both Linacs can induce DVP variations of the PTV of the order of 0.1%, with a maximum standard deviation of 1.1%. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 22
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