Implementation of phantom-less IMRT delivery verification using Varian DynaLog files and R/V output

Agnew, Christina; King, R. B.; Hounsell, Alan R.; McGarry, Conor K.

doi:10.1088/0031-9155/57/21/6761

Cited by 48 publications

(48 citation statements)

References 20 publications

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“…Trajectory log files recorded during pretreatment QA (minimum three deliveries per patient) were analyzed using in‐house software written in MATLAB V.7.7.0 (MathWorks, Natick, MA) as previously described, with each control point considered as a beam segment (26) . Varian TrueBeam linacs record a single trajectory log file for each treatment arc.…”

Section: Methodsmentioning

confidence: 99%

“…Linac log file analysis has been proposed to improve efficiency of patient specific QA 13 , 22 , 23 , 26 and provide insight into machine parameters not possible with phantom‐based measurements 6 , 21 , 23 , 27 . Additionally, linac log file analysis could be used to assess actual/relative delivered dose reconstructed on the patient's anatomy using the patient's original CT image set 21 , 24 , 28 or the on‐treatment CBCT image set (25) .…”

Section: Introductionmentioning

confidence: 99%

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Correlation of phantom‐based and log file patient‐specific QA with complexity scores for VMAT

Agnew

Irvine

McGarry

2014

J Applied Clin Med Phys

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The motivation for this study was to reduce physics workload relating to patient‐specific quality assurance (QA). VMAT plan delivery accuracy was determined from analysis of pre‐ and on‐treatment trajectory log files and phantom‐based ionization chamber array measurements. The correlation in this combination of measurements for patient‐specific QA was investigated. The relationship between delivery errors and plan complexity was investigated as a potential method to further reduce patient‐specific QA workload. Thirty VMAT plans from three treatment sites — prostate only, prostate and pelvic node (PPN), and head and neck (H&N) — were retrospectively analyzed in this work. The 2D fluence delivery reconstructed from pretreatment and on‐treatment trajectory log files was compared with the planned fluence using gamma analysis. Pretreatment dose delivery verification was also carried out using gamma analysis of ionization chamber array measurements compared with calculated doses. Pearson correlations were used to explore any relationship between trajectory log file (pretreatment and on‐treatment) and ionization chamber array gamma results (pretreatment). Plan complexity was assessed using the MU/ arc and the modulation complexity score (MCS), with Pearson correlations used to examine any relationships between complexity metrics and plan delivery accuracy. Trajectory log files were also used to further explore the accuracy of MLC and gantry positions. Pretreatment 1%/1 mm gamma passing rates for trajectory log file analysis were 99.1% (98.7%–99.2%), 99.3% (99.1%–99.5%), and 98.4% (97.3%–98.8%) (median (IQR)) for prostate, PPN, and H&N, respectively, and were significantly correlated to on‐treatment trajectory log file gamma results (normalR=0.989,p<0.001). Pretreatment ionization chamber array (2%/2 mm) gamma results were also significantly correlated with on‐treatment trajectory log file gamma results (normalR=0.623,p<0.001). Furthermore, all gamma results displayed a significant correlation with MCS (normalR>0.57,p<0.001), but not with MU/arc. Average MLC position and gantry angle errors were 0.001±0.002.15emmm and 0.025°±0.008° over all treatment sites and were not found to affect delivery accuracy. However, variability in MLC speed was found to be directly related to MLC position accuracy. The accuracy of VMAT plan delivery assessed using pretreatment trajectory log file fluence delivery and ionization chamber array measurements were strongly correlated with on‐treatment trajectory log file fluence delivery. The strong correlation between trajectory log file and phantom‐based gamma results demonstrates potential to reduce our current patient‐specific QA. Additionally, insight into MLC and gantry position accuracy through trajectory log file analysis and the strong correlation between gamma analysis results and the MCS could also provide further methodologies to both optimize the VMAT planning and QA process.PACS number: 87.53.Bn, 87.55.Kh, 87.55.Qr

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Correlation of phantom‐based and log file patient‐specific QA with complexity scores for VMAT

Agnew

Irvine

McGarry

2014

J Applied Clin Med Phys

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“…The recent work of Agnew et al (17) demonstrates the successful implementation of DynaLog files to validate IMRT deliveries and how DynaLog files can diagnose delivery errors not possible with phantom based QA. Their analysis was performed on planned and actual fluence maps reconstructed from the MLC control file and delivered DynaLog files, respectively.…”

Section: Discussionmentioning

confidence: 99%

A Varian DynaLog file‐based procedure for patient dose‐volume histogram‐based IMRT QA

Calvo-Ortega

Teke

Moragues

et al. 2014

J Applied Clin Med Phys

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In the present study, we describe a method based on the analysis of the dynamic MLC log files (DynaLog) generated by the controller of a Varian linear accelerator in order to perform patient‐specific IMRT QA. The DynaLog files of a Varian Millennium MLC, recorded during an IMRT treatment, can be processed using a MATLAB‐based code in order to generate the actual fluence for each beam and so recalculate the actual patient dose distribution using the Eclipse treatment planning system. The accuracy of the DynaLog‐based dose reconstruction procedure was assessed by introducing ten intended errors to perturb the fluence of the beams of a reference plan such that ten subsequent erroneous plans were generated. In‐phantom measurements with an ionization chamber (ion chamber) and planar dose measurements using an EPID system were performed to investigate the correlation between the measured dose changes and the expected ones detected by the reconstructed plans for the ten intended erroneous cases. Moreover, the method was applied to 20 cases of clinical plans for different locations (prostate, lung, breast, and head and neck). A dose‐volume histogram (DVH) metric was used to evaluate the impact of the delivery errors in terms of dose to the patient. The ionometric measurements revealed a significant positive correlation false(normalR2=0.9993false) between the variations of the dose induced in the erroneous plans with respect to the reference plan and the corresponding changes indicated by the DynaLog‐based reconstructed plans. The EPID measurements showed that the accuracy of the DynaLog‐based method to reconstruct the beam fluence was comparable with the dosimetric resolution of the portal dosimetry used in this work false(3normal%/3 mmfalse). The DynaLog‐based reconstruction method described in this study is a suitable tool to perform a patient‐specific IMRT QA. This method allows us to perform patient‐specific IMRT QA by evaluating the result based on the DVH metric of the planning CT image (patient DVH‐based IMRT QA).PACS number: 87.55.Qr

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“…The Clinac DynaLog -ile contains both the planned cumulative MU versus gantry angle and the actual cumulative MU delivered versus the actual gantry angle. The MLC DynaLog -iles contain expected and actual leaf positions (22,23) . The mean standard deviations in MU and gantry angle and average root mean square (RMS) of the deviations of leaves were compared for the various gated deliveries of ten patients to know the performance of machine under different gated deliveries.…”

Section: Vmat Dynalog !Ilesmentioning

confidence: 99%

Performance evaluation of gated volumetric modulated arc therapy

Swamy

Radha

Garg

et al. 2016

IJRR

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Background: Aim of this study is to evaluate the accuracy of the gated volumetric modulated arc therapy (VMAT/RapidArc) using 2D planar dosimetry, DynaLog files and COMPASS 3D dosimetry system. Materials and Methods: Pre-treatment quality assurance of 10 gated VMAT plans was verified using 2D array and COMPASS 3D dosimetry system. Advantage of COMPASS over 2D planar is that it provides the clinical consequence of error in treatment delivery. Measurements were performed for non-gated and different phase ga.ng window level (80%, 50%, 30% & 20%) to know the impact of ga.ng in VMAT dose delivery. Results: In 2D planar dosimetry, gamma agreement index (GAI) for all measurements were more than 95%. DynaLog file analysis shows the average devia.ons between actual and expected posi.ons of monitor units, gantry and mul.-leaf collimator. The STDVs MU and gantry posi.on were less than 0.10 MU and 0.33° respec.vely. Root mean square (RMS) of the devia.ons of all leaves were less than 0.58 mm. The results from COMPASS show that 3D dose volume parameters for ten pa.ents measured for different phase ga.ng window level were within the tolerance level of ±5%. Average 3D gamma of PTV and OAR's for different window level was less than 0.6. Conclusion: The results from this study show that gated VMAT delivery provided dose distribu.ons equivalent to non-gated delivery to within clinically acceptable limits and COMPASS along with Matrix Evolu.on can be effec.vely used for pretreatment verifica.on of gated VMAT plans.

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Implementation of phantom-less IMRT delivery verification using Varian DynaLog files and R/V output

Cited by 48 publications

References 20 publications

Correlation of phantom‐based and log file patient‐specific QA with complexity scores for VMAT

Correlation of phantom‐based and log file patient‐specific QA with complexity scores for VMAT

A Varian DynaLog file‐based procedure for patient dose‐volume histogram‐based IMRT QA

Performance evaluation of gated volumetric modulated arc therapy

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