Dynalog Files Research Articles

Clinical performance of FractionLab in patient-specific quality assurance for intensity-modulated radiotherapy: a retrospective study.

BackgroundThis study was aimed at comparing and analyzing the results of FractionLab (Varian/Mobius Medical System) with those of portal dosimetry that uses an electronic portal imaging device. Portal dosimetry is extensively used for patient-specific quality assurance (QA) in intensity-modulated radiotherapy (IMRT).MethodsThe study includes 29 patients who underwent IMRT on a Novalis-Tx linear accelerator (Varian Medical System and BrainLAB) between June 2019 and March 2021. We analyzed the multileaf collimator DynaLog files generated after portal dosimetry to evaluate the same condition using FractionLab. The results of the recently launched FractionLab at various gamma indices (0.1%/0.1 mm–1%/1 mm) are analyzed and compared with those of portal dosimetry (3%/3 mm).ResultsThe average gamma passing rates of portal dosimetry (3%/3 mm) and FractionLab are 98.1% (95.5%–100%) and 97.5% (92.3%–99.7%) at 0.6%/0.6 mm, respectively. The results of portal dosimetry (3%/3 mm) are statistically comparable with the QA results of FractionLab (0.6%/0.6 mm–0.9%/0.9 mm).ConclusionThis paper presents the clinical performance of FractionLab by the comparison of the QA results of FractionLab using portal dosimetry with various gamma indexes when performing patient-specific QA in IMRT treatment. Further, the appropriate gamma index when performing patient-specific QA with FractionLab is provided.

Estimation of Dynamic MLC Parameters Using Dynamic MLC Position Accuracy Analysis Software in Prostate IMRT

It is necessary to verify an intensity-modulated radiation therapy (IMRT) plan and to confirm dose error within the tolerance, in order to perform it securely and precisely. IMRT with dynamic multi-leaf collimator (DMLC) requires high DMLC position accuracy. The DMLC position accuracy analysis software DynaLog File Viewer (DFV; Varian Medical Systems, Palo Alto, CA, USA) is used to analyze position errors of DMLC for IMRT plans. We analyzed correlation between DMLC parameters and position error of DMLC obtained from DFV in prostate IMRT. A regression analysis of the position error and the DMLC parameters was performed. As a result, a strong correlation was found between MLC position error and each of the DMLC parameters: leaf speed, gap width, and segment monitor unit (MU). We found the factors for the DMLC position error in this study. DMLC position error could be estimated from leaf speed, gap width, and segment MU when we analyze IMRT cases in the further study.

Feasibility Study of the Fluence-to-Dose Network (FDNet) for Patient-Specific IMRT Quality Assurance

The aim of this study is to predict the delivered dose distribution [Ddelivered(x, y)] with the use of a fluence-to-dose network (FDNet) to conduct patient-specific intensity-modulated radiation therapy (IMRT) quality assurance (pQA). The architecture of the FDNet was based on a convolutional neural network. Forty-four IMRT clinical cases of planned dose distributions for pQA [Dplanned(x, y)] and dynamic multileaf collimator (MLC) log files (Dynalog files) were collected. Using the Dynalog files, the expected fluence stack [Fexpected(x, y, t)] and the actual fluence stack [Factual(x, y, t)] were created from the expected and the actual machine parameters, respectively. The actual fluence stack, which was reconstructed from the partial information of the Dynalog file, corresponded to the control points of the Digital Imaging and Communications in Medicine radiation treatment plan and was denoted as [Factual(x, y, tpartial)]. The entire dataset was split into 11 subsets for the k-fold averaging cross-validation (k = 11). Ten (out of the 11) folds were used to train 10 candidate optimal FDNet models, and an ultimate FDNet was determined by averaging the parameters of the optimal models. The pQA was performed using the test data of the remaining fold with the ultimate FDNet. The dose distributions predicted using Factual(x, y, t) [Dpredicted(Factual(x, y, t))] and Factual(x, y, tpartial) [Dpredicted(Factual(x, y, tpartial))] were acquired. To evaluate the predicted pQA results, we conducted dosimetry using EBT3 films and an ion-chamber array detector (MatriXX). These dose distributions were compared with the Dplanned(x, y) by using a gamma analysis. The average gamma passing rates were determined based on the 3%/3 mm gamma criterion and were, respectively, equal to 98.49%, 97.21%, 97.23%, and 98.03%, for the Dpredicted(Factual(x, y, t)), Dpredicted(Factual(x, y, tpartial)), EBT3 film, and MatriXX. According to this study, the feasibility of the dose prediction method using the FDNet with complete Dynalog information was verified for the pQA. The respective differences of the average gamma passing rates for the Dpredicted(Factual(x, y, t)), and Dpredicted(Factual(x, y, tpartial)) were equal, respectively, to 1.28% and 2.88% according to the 3%/3 mm and the 2%/2 mm gamma criteria.

Treatment verification using Varian\u2019s dynalog files in the Monte Carlo system PRIMO

BackgroundThe PRIMO system is a computer software that allows the Monte Carlo simulation of linear accelerators and the estimation of the subsequent absorbed dose distributions in phantoms and computed tomographies. The aim of this work is to validate the methods incorporated in PRIMO to evaluate the deviations introduced in the dose distributions by errors in the positioning of the leaves of the multileaf collimator recorded in the dynalog files during patient treatment.MethodsThe reconstruction of treatment plans from Varian’s dynalog files was implemented in the PRIMO system. Dose distributions were estimated for volumetric-modulated arc therapy clinical cases of prostate and head&neck using the PRIMO fast Monte Carlo engine DPM. Accuracy of the implemented reconstruction methods was evaluated by comparing dose distributions obtained from the simulations of the plans imported from the treatment planning system with those obtained from the simulations of the plans reconstructed from the expected leaves positions recorded in the dynalog files. The impact on the dose of errors in the positions of the leaves was evaluated by comparing dose distributions estimated for plans reconstructed from expected leaves positions with dose distributions estimated from actual leaves positions. Gamma pass rate (GPR), a hereby introduced quantity named percentage of agreement (PA) and the percentage of voxels with a given systematic difference (α/Δ) were the quantities used for the comparisons. Errors were introduced in leaves positions in order to study the sensitivity of these quantities.ResultsA good agreement of the dose distributions obtained from the plan imported from the TPS and from the plan reconstructed from expected leaves positions was obtained. Not a significantly better agreement was obtained for an imported plan with an increased number of control points such as to approximately match the number of records in the dynalogs. When introduced errors were predominantly in one direction, the methods employed in this work were sensitive to dynalogs with root-mean-square errors (RMS) ≥0.2 mm. Nevertheless, when errors were in both directions, only RMS >1.2 mm produced detectable deviations in the dose. The PA and the α/Δ showed more sensitive to errors in the leaves positions than the GPR.ConclusionsMethods to verify the accuracy of the radiotherapy treatment from the information recorded in the Varian’s dynalog files were implemented and verified in this work for the PRIMO system. Tolerance limits could be established based on the values of PA and α/Δ. GPR3,3 is not recommended as a solely evaluator of deviations introduced in the dose by errors captured in the dynalog files.

Plan-Class Specific Reference Quality Assurance for Volumetric Modulated Arc Therapy

Background: There have been much efforts to develop the proper and realistic machine Quality Assurance (QA) reflecting on real Volumetric Modulated Arc Therapy (VMAT) plan. In this work we propose and test a special VMAT plan of plan-class specific (pcsr) QA, as a machine QA so that it might be a good solution to supplement weak point of present machine QA to make it more realistic for VMAT treatment. Materials and Methods: We divided human body into 5 treatment sites: brain, head and neck, chest, abdomen, and pelvis. One plan for each treatment site was selected from real VMAT cases and contours were mapped into the computational human phantom where the same plan as real VMAT plan was created and called plan-class specific reference (pcsr) QA plan. We delivered this pcsr QA plan on a daily basis over the full research period and tracked how much MLC movement and dosimetric error occurred in regular delivery. Several real patients under treatments were also tracked to test the usefulness of pcsr QA through comparisons between them. We used dynalog file viewer (DFV) and Dynalog file to analyze position and speed of individual MLC leaf. The gamma pass rate from portal dosimetry for different gamma criteria was analyzed to evaluate analyze dosimetric accuracy. Results and Discussion: The maxRMS of MLC position error for all plans were all within the tolerance limit of < 0.35 cm and the positional variation of maxPEs for both pcsr and real plans were observed very stable over the research session. Daily variations of maxRMS of MLC speed error and gamma pass rate for real VMAT plans were observed very comparable to those in their pcsr plans in good acceptable fluctuation. Conclusion: We believe that the newly proposed pcsr QA would be useful and helpful to predict the mid-term quality of real VMAT treatment delivery.

144. Metric for assessment of mechanical reproducibility of leaves positions during VMAT treatment

Purpose To assess mechanical reproducibility of Multi Leaf Collimator (MLC) leaves positions during VMAT delivery and to formulate a suitable metric for daily quality assurance (QA) measurements. Methods A plan consisting of 2 dynamic arcs (CW and CCW) has been delivered on a Varian linac for 12 months (444 total arcs) as daily QA to assess MLC Long Term Reproducibility (LTR) and 10 times consecutively (20 total arcs) for Short Term Reproducibility (STR). Dynalog files were generated from the linac and analyzed in MatLAB environment. The distribution of the positioning errors of MLC weighted for leaves aperture was calculated for every delivery. An Index Error (IE) was calculated as the percentiles of these distributions that minimize the CV among the sampled data (Fig. 1): average values ( X m ) and standard deviations (SD) were calculated in order to define the thresholds for 95% of statistic confidence of the sample (TH = X m + 2SD). IE is calculated with daily frequency and the percentage of events out of TH is evaluated including a window data of 1 month. The Attention Level (AL) is reached when the number of the events (Fig. 2) out of threshold is the 5% of the sample. The events out of the statistic confidence are related to mechanical mismatch of MLC during delivery. Results The minimization CV value is obtained for the 49th percentile of MLC weighted positioning error distribution. The trends of average, SD and CV for the LTR and STR (Table) samples are similar this means the absence of perturbative boundary conditions. During monitoring of MLC performance the method highlighted the beginning of the malfunction (blue-line in Fig. 2) and the subsequent return into the limits following the maintenance service. Conclusions The IE calculated as 49th percentile of MLC positioning error distributions can be used to define an AL for MLC performance monitoring for VMAT delivery and daily QA. The proposed metric provides a strong method for monitoring mechanical errors during VMAT plans. Furthermore, a mechanical equivalence between linacs could be assessed to ensure a safe machine switching when service is occurring.

134. DynaLog file-based Procedure for a daily monitoring of IMRT dose delivery

PurposeThanks to the intensity modulated radiation therapy (IMRT) it is possible to achieve highly conformal dose distribution with an important shield to the adjacent organs at risk. Nevertheless, the complex nature of such treatments requires a comprehensive Quality Assurance (QA). The last decade witnessed a proliferation of QA method based on machine log files (DynaLogs Files) since their several advantages [1,2]. In this study we propose a DynaLog file-based method to ensure a daily monitoring of the correct dose delivery. MethodsThe delivery of one prostate IMRT treatment has been daily monitored thanks to the DynaLogs Files. These files are generated for each field delivery and record many useful information [1,2]. Herein the DynaLogs information about planned and actual cumulative dose fraction is taken into account. The prostate IMRT plan consists of 5 fixed field arrangements using a dynamic delivery technique (sliding window). It was calculated using the Varian Eclipse TPS (version 13.6; Varian, Palo Alto) with the analytical anisotropic algorithm (AAA) and it was delivered on a Varian Clinac2100CD. Target dose prescription is 80 Gy in 40 fractions. ResultsThe deviation between planned and actual dose fraction was calculated, for each field, as a function of both fraction numbers and delivery time. The mean and maximum dose deviations were 0.1 and 0.3 Monitor Units, respectively. ConclusionsUsually the IMRT QA is performed before the treatment beginning and it is assumed that no further variations will occur. The proposed method allows to daily assess the correct dose delivery thanks to DynaLogs Files in a no time-consuming way.

Daily Based Quality Assurance of Volumetric Modulated Arc Therapy for the Full Session of Treatment

Volumetric modulated arc therapy (VMAT) with highly complex advanced delivering technique, is widely practiced in radiation therapy and requires a quality assurance for treatment plan at least once a treatment session. In this study we collected six VMAT patients with different treatment sites. The VMAT plans and their quality assurance (QA) plans were performed on a daily basis before treatment for their full period of treatment. We tried to evaluate the accuracy of their delivering through analyses of first mechanical error of multileaf collimator (MLC) movement and second dosimetric error of beam delivery. We used a MATLAB program and portal dosimetry to estimate a maximum root mean square (RMS) error from dynalog files for mechanical analysis and a gamma index from portal dosimetry for dosimetric analysis, respectively. We introduced newly in this study a representative VMAT QA to be used to perform a routine VMAT QA. The daily variation of maximum error RMSs for all treatment sites were all below maximum 0.3503 ± 0.0002 mm for treatment plans and QA plans and they all showed the gamma pass rate of more than 98%. Mean of inter difference between treatment and QA plans stayed below 0.04 mm, showing that QA deliveries agree well with treatment deliveries. The Linac used kept a good performance within the tolerances in American Association of Physicists in Medicine (AAPM) TG142 guideline for the period of research. We suggest that the representative VMAT QA can be a good surrogate for real VMAT plan and “whole time” plan QA for a patient selected randomly at least once a year be performed to confirm the long-term stability of Linac performance.

Quality Assurance of Volumetric Modulated Arc Therapy Using the Dynalog Files

Quality Assurance of Volumetric Modulated Arc Therapy Using the Dynalog Files

Configuration of the PRIMO software to simulate intensity modulated radiation therapy through dynalog file

Introduction Varian DynaLog files contain information on the Multi Leaf Collimator (MLC) actual configuration, and gantry and collimator angles during Intensity Modulated Radiation Therapy (IMRT). The Monte Carlo (MC) simulation of an actual IMRT procedure allows studying the dosimetric effect of possible mismatches between planned and actual delivery. The PRIMO software is a MC software targeted to External Radiotherapy environment. Nevertheless, IMRT is not part of the implemented options. Purpose To configure PRIMO to simulate an actual IMRT procedure by DynaLog files manipulation. Materials and methods A Varian 2300CD LINAC associated to a 120HD MLC was simulated. Static simulations were primarily performed to verify the LINAC and MLC models against experimental data. A dynamic irradiation with MLC modulation was split into a sequence of static segments. PRIMO was configured by introducing the DynaLog files information and the procedure was simulated on a solid water phantom. Gafchromic films were used to measure actual dose distribution and to compare it with the simulations through a 2D Gamma analysis. Results More than 95% of Gamma points Conclusion A workflow was developed to configure PRIMO to simulate IMRT through the direct introduction of DynaLog files. These results represent an initial study towards a clinically useful implementation of IMRT simulation using PRIMO. Disclosure The authors have no relevant financial or nonfinancial relationships to disclose.

Practical use of dynalogs analysis in seven linacs in IMRT and VMAT techniques over than 20 months

Introduction Dynalog files’s (DLGf) analysis can provide important information about deviations from planned and actual movement (positioning and velocity) of the MLC, during an IMRT or VMAT treatment delivery. Pre-treatment verification (QA) allows the comparison of the calculated and delivered dose distributions. In case of failure, the treatment plan must be reviewed and possible sources of fault must be tracked. Purpose The aim of this study is to substantiate a possible correlation between MLC behavior (through the analysis of the DLGf using FractionCheck software) and the failure of the QA procedure. Materials and methods Data from IMRT and VMAT DLGf acquired from May 2014 to February 2016 in 7 linacs was statistical analyzed as a complementary data source for the QA procedures. The analyzed results were expressed in “Warning” and “Fail” accordingly to the tolerances in TG142 report. Other parameters were also analyzed by the software: RMS, Beam-On, 95P, MaxRMS, MaxLag and Gamma-function distribution. Results were reviewed considering several factors: gantry angle, MLC maintenance, day time, pathology’s type, mechanical and dosimetric tests results and network upgrade. Results No correlation between Dynalog information and the results obtained from the QA measurements (VerySoft analysis) was verified. For an increase in the dose rate, the 95P’s, MaxRMS’s and RMS’s (for each leaf) parameters worsen. Conclusion Although the information obtained from DLGf can be very useful in some particular situations, it does not predict the outcome of IMRT or VMAT QA procedures. MLC’s performance does not depend on the treatment’s pathology, gantry angle, or day time due to possible linac’s overheating. Disclosure The authors have no relevant financial or non-financial relationships to disclose.

The step-and-shoot IMRT overshooting phenomenon: a novel method to mitigate patient overdosage.

The goal of this work is to evaluate the dosimetric impact of an overshooting phenomenon in step‐and‐shoot IMRT delivery, and to demonstrate a novel method to mitigate the issue. Five pelvis IMRT patients treated on Varian 2100C EX linacs with larger than +4.5% phantom ion chamber point‐dose difference relative to planned dose were investigated. For each patient plan, 5 fractions were delivered. DynaLog files were recorded and centi‐MU pulses from dose integrator board for every control point (CP) were counted using a commercial pulse counter. The counter recorded CP MU agrees with DynaLog records, both showing an ~0.6 MU overshoot of the first segment of every beam. The 3D patient dose was recalculated from the counter records and compared to the planned dose, showing that the overshoot resulted in on average 2.05% of PTV D95 error, and 2.49%, 2.61% and 2.45% of D1cc error for rectum, bladder, and bowel, respectively. The initial plans were then modified by inserting a specially designed MLC segment to the start of every beam. The modified plans were also delivered five times. The dose from the modified delivery was calculated using counter recorded CP MU. The corresponding Dx parameters were all within 0.31% from the original plan. IMRT QA results also show a 2.2% improvement in ion chamber point‐dose agreement. The results demonstrate that the proposed plan modification method effectively eliminates the overdosage from the overshooting phenomenon.PACS number(s): 87.55.Qr, 87.55.km

SU‐F‐T‐465: Two Years of Radiotherapy Treatments Analyzed Through MLC Log Files

Purpose:To present treatment statistics of a Varian Novalis Tx using more than 90,000 Varian Dynalog files collected over the past 2 years.Methods:Varian Dynalog files are recorded for every patient treated on our Varian Novalis Tx. The files are collected and analyzed daily to check interfraction agreement of treatment deliveries. This is accomplished by creating fluence maps from the data contained in the Dynalog files. From the Dynalog files we have also compiled statistics for treatment delivery times, MLC errors, gantry errors and collimator errors.Results:The mean treatment time for VMAT patients was 153 ± 86 seconds while the mean treatment time for step &amp; shoot was 256 ± 149 seconds. Patient's treatment times showed a variation of 0.4% over there treatment course for VMAT and 0.5% for step &amp; shoot. The average field sizes were 40 cm2 and 26 cm2 for VMAT and step &amp; shoot respectively. VMAT beams contained and average overall leaf travel of 34.17 meters and step &amp; shoot beams averaged less than half of that at 15.93 meters. When comparing planned and delivered fluence maps generated using the Dynalog files VMAT plans showed an average gamma passing percentage of 99.85 ± 0.47. Step &amp; shoot plans showed an average gamma passing percentage of 97.04 ± 0.04. 5.3% of beams contained an MLC error greater than 1 mm and 2.4% had an error greater than 2mm. The mean gantry speed for VMAT plans was 1.01 degrees/s with a maximum of 6.5 degrees/s.Conclusion:Varian Dynalog files are useful for monitoring machine performance treatment parameters. The Dynalog files have shown that the performance of the Novalis Tx is consistent over the course of a patients treatment with only slight variations in patient treatment times and a low rate of MLC errors.

SU‐F‐T‐266: Dynalogs Based Evaluation of Different Dose Rate IMRT Using DVH and Gamma Index

Purpose:This work investigates the impact of low and high dose rate on IMRT through Dynalogs by evaluating Gamma Index and Dose Volume Histogram.Methods:The Eclipse™ treatment planning software was used to generate plans on prostate and head and neck sites. A range of dose rates 300 MU/min and 600 MU/min were applied to each plan in order to investigate their effect on the beam ON time, efficiency and accuracy. Each plan had distinct monitor units per fraction, delivery time, mean dose rate and leaf speed. The DVH data was used in the assessment of the conformity and plan quality.The treatments were delivered on Varian™ Clinac 2100C accelerator equipped with 120 leaf millennium MLC. Dynalogs of each plan were analyzed by MATLAB™ program. Fluence measurements were performed using the Sun Nuclear™ 2D diode array and results were assessed, based on Gamma analysis of dose fluence maps, beam delivery statistics and Dynalogs data.Results:Minor differences found by adjusted R‐squared analysis of DVH's for all the plans with different dose rates. It has been also found that more and larger fields have greater time reduction at high dose rate and there was a sharp decrease in number of control points observed in dynalog files by switching dose rate from 300 MU/min to 600 MU/min. Gamma Analysis of all plans passes the confidence limit of ≥95% with greater number of passing points in 300 MU/min dose rate plans.Conclusion:The dynalog files are compatible tool for software based IMRT QA. It can work perfectly parallel to measurement based QA setup and stand‐by procedure for pre and post delivery of treatment plan.

SU‐F‐T‐463: Light‐Field Based Dynalog Verification

Purpose:To independently verify leaf positions in so‐called dynalog files for a Varian iX linac with a Millennium 120 MLC. This verification provides a measure of confidence that the files can be used directly as part of a more extensive intensity modulated radiation therapy / volumetric modulated arc therapy QA program.Methods:Initial testing used white paper placed at the collimator plane and a standard hand‐held digital camera to image the light and shadow of a static MLC field through the paper. Known markings on the paper allow for image calibration. Noise reduction was attempted with removal of ‘inherent noise’ from an open‐field light image through the paper, but the method was found to be inconsequential. This is likely because the environment could not be controlled to the precision required for the sort of reproducible characterization of the quantum noise needed in order to meaningfully characterize and account for it. A multi‐scale iterative edge detection algorithm was used for localizing the leaf ends. These were compared with the planned locations from the treatment console.Results:With a very basic setup, the image of the central bank A leaves 15–45, which are arguably the most important for beam modulation, differed from the planned location by [0.38±0.28] mm. Similarly, for bank B leaves 15–45 had a difference of [0.42±0.28] mmConclusion:It should be possible to determine leaf position accurately with not much more than a modern hand‐held camera and some software. This means we can have a periodic and independent verification of the dynalog file information. This is indicated by the precision already achieved using a basic setup and analysis methodology. Currently, work is being done to reduce imaging and setup errors, which will bring the leaf position error down further, and allow meaningful analysis over the full range of leaves.

SU‐F‐T‐295: MLCs Performance and Patient‐Specific IMRT QA Using Log File Analysis

Purpose:To analyze the performance of the multi‐leaf collimators (MLCs) from the log files recorded during the intensity modulated radiotherapy (IMRT) treatment and to construct the relative fluence maps and do the gamma analysis to compare the planned and executed MLCs movement.Methods:We developed a program to extract and analyze the data from dynamic log files (dynalog files) generated from sliding window IMRT delivery treatments. The program extracts the planned and executed (actual or delivered) MLCs movement, calculates and compares the relative planned and executed fluences. The fluence maps were used to perform the gamma analysis (with 3% dose difference and 3 mm distance to agreement) for 3 IMR patients. We compared our gamma analysis results with those obtained from portal dose image prediction (PDIP) algorithm performed using the EPID.Results:For 3 different IMRT patient treatments, the maximum difference between the planned and the executed MCLs positions was 1.2 mm. The gamma analysis results of the planned and delivered fluences were in good agreement with the gamma analysis from portal dosimetry. The maximum difference for number of pixels passing the gamma criteria (3%/3mm) was 0.19% with respect to portal dosimetry results.Conclusion:MLC log files can be used to verify the performance of the MLCs. Patientspecific IMRT QA based on MLC movement log files gives similar results to EPID dosimetry results. This promising method for patient‐specific IMRT QA is fast, does not require dose measurements in a phantom, can be done before the treatment and for every fraction, and significantly reduces the IMRT workload.The author would like to thank King Fahd University of petroleum and Minerals for the support.

SU‐F‐T‐302: Implementation of the RadCalc Image Analysis Tool for IMRT QA

Purpose:To assess RadCalc as a means for analyzing fluence maps of IMRT QA patient plans. Eclipse generated fluence maps were compared to RadCalc fluence maps generated from both Eclipse parameters and from dynalog trajectory files.Methods:Six IMRT plans consisting of fifty individual fields were compared both field‐by‐field and as composite plans. These plans were exported from Eclipse to RadCalc. Each plan was then delivered in QA mode on a Varian Clinac iX, while recording and saving the dynalog trajectory files. These files were then imported into RadCalc, providing three sources of generating fluence maps: Eclipse, RadCalc, and dynalog files. Using the image analysis tool in RadCalc, a gamma analysis was then performed as a point‐by‐point comparison for each IMRT field. The Eclipse fluence map was used as the baseline for each comparison.Results:Based on the manufacturer's recommendations, all fields were normalized to the maximum pixel value within each Eclipse field. All data was analyzed using a gamma index of 3mm/3% with passing criteria of 90%. For both dynalog analysis and RadCalc fluence analysis, 48/50 created fluence maps passed at greater than 90% when compared with the Eclipse baseline. In analyzing the composite of each of the six patients’ plans, all plans passed over 90%.Conclusion:Using the dynalog trajectory files in combination with RadCalc Version 6.3 image analysis is a promising metric for verifying IMRT QA passing rates. Notably, if a field failed, it did so for both dynalog and RadCalc compared to Eclipse. This suggests RadCalc can accurately simulate fluence maps, with similar results to dynalog comparisons. Limitations within the RadCalc software were discovered in the analytical process such as pixel resolution and the inability to set minimum threshold values. Comparisons could be extended to include dose map and distance to agreement analysis by expanding software capabilities.

SU‐F‐T‐228: Analysis of Multi‐Leaf Collimator Leaf Position Errors in Volumetric Modulated Arc Therapy for Nasopharyngeal Carcinoma

Purpose:The purpose of this study was evaluate the position error of multileaf collimator in volumetric modulated arc therapy of nasopharyngeal carcinoma via MLC logs from Varian machines and to provide a method for detecting the leaf position accuracy.Methods:Thirty one patients with nasopharyngeal carcinoma were randomly selected. Each patient was created with two 358° arcs. The MLC errors for all arcs, arc1 and arc2, left‐bank and right‐bank leafs of each arc were evaluated.Results:99.99% of the leaf position errors of all plans were within ± 2mm. The proportion of the leaf position errors within ± 1.5mm,± 1mm and ± 0.5mm were 99.90%, 98.98% and 94.17%,respectively. The leaf position errors range of ARC1 and ARC2 were −2.95 ∼ 2.99mm and −0.22 ∼ 0.23mm (t = 2.35, P = 0.00), The proportion of the leaf position errors within ± 1mm were 98.08% and 100% for ARC1 and ARC2. The leaf position errors range of Bank A and Bank B were −2.95 ∼ 2.68mm and −2.92 ∼ 2.99mm (t = 1.64, P = 0.31), The proportion of the leaf position errors within ± 1mm were 98.97% and 99.01%.Conclusion:During the VMAT treatment for NPC, it was found that the leaf positions were in control, the Dynalog files can be used as an effective way to analysis the leaf position errors.

Delivering RapidArc®: A comprehensive study on accuracy and long term stability

PurposeTo establish the reliability and accuracy of a UNIQUE Linac in delivering RapidArc treatments and assess its long term stability. Materials and methodsUNIQUE performance was monitored and analyzed for a period of nearly two years. 2280 Dynalog files, related to 179 clinical RapidArc treatments were collected. Different tumor sites and dose scheduling were included, covering the full range of our treatment plans. Statistical distributions of MLC motion error, gantry rotation error and MU delivery error were evaluated. The stochastic and systematic nature of each error was investigated together with their variation in time. ResultsAll the delivery errors are found to be small and more stringent tolerances than those proposed by TG142 are suggested. Unlike MLC positional errors, where a linear relationship with leaf speed holds, other Volumetric Modulated Arc Therapy (VMAT) parameters reveal a random nature and, consequently, a reduced clinical relevance. MLC errors are linearly related only to leaf speed no matter the shape of the MLC apertures. Gantry rotation and MU delivery are as accurate as major competing Linacs. UNIQUE was found to be reliable and accurate throughout the investigation period, regardless of the specific tumor sites and fractionation schemes. ConclusionsThe accuracy of RapidArc treatments delivered with UNIQUE has been established. The stochastic nature of delivery errors is proven. Long term statistics of the delivery parameter errors do not show significant variations, confirming the reliability of the VMAT delivery system.

SU‐F‐T‐308: Mobius FX Evaluation and Comparison Against a Commercial 4D Detector Array for VMAT Plan QA

Purpose:To evaluate the use of MobiusFX as a pre‐treatment verification IMRT QA tool and compare it with a commercial 4D detector array for VMAT plan QA.Methods:15 VMAT plan QA of different treatment sites were delivered and measured by traditional means with the 4D detector array ArcCheck (Sun Nuclear corporation) and at the same time measurement in linac treatment logs (Varian Dynalogs files) were analyzed from the same delivery with MobiusFX software (Mobius Medical Systems). VMAT plan QAs created in Eclipse treatment planning system (Varian) in a TrueBeam linac machine (Varian) were delivered and analyzed with the gamma analysis routine from SNPA software (Sun Nuclear corporation).Results:Comparable results in terms of the gamma analysis with 99.06% average gamma passing with 3%,3mm passing rate is observed in the comparison among MobiusFX, ArcCheck measurements, and the Treatment Planning System dose calculated. When going to a stricter criterion (1%,1mm) larger discrepancies are observed in different regions of the measurements with an average gamma of 66.24% between MobiusFX and ArcCheck.Conclusion:This work indicates the potential for using MobiusFX as a routine pre‐treatment patient specific IMRT method for quality assurance purposes and its advantages as a phantom‐less method which reduce the time for IMRT QA measurement. MobiusFX is capable of produce similar results of those by traditional methods used for patient specific pre‐treatment verification VMAT QA. Even the gamma results comparing to the TPS are similar the analysis of both methods show that the errors being identified by each method are found in different regions. Traditional methods like ArcCheck are sensitive to setup errors and dose difference errors coming from the linac output. On the other hand linac log files analysis record different errors in the VMAT QA associated with the MLCs and gantry motion that by traditional methods cannot be detected.