A clinically observed discrepancy between image‐based and log‐based MLC positions

Neal, Brian; Ahmed, Mahmoud; Kathuria, Kunal; Watkins, Tyler; Wijesooriya, K.; Siebers, Jeffrey V.

doi:10.1118/1.4949002

Cited by 52 publications

(74 citation statements)

References 10 publications

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“…Initially, we started our investigations using the extended logging information of the linac for synchronization of the sub‐arcs, as described by Mans et al However, mainly due to the logging frequency and the lag of the system, synchronization based on this information resulted in less accurate results for sub‐arc dose delivery QA (data not presented). Similar problems with the accuracy of logging information have also been reported for Varian linacs . After applying our synchronization, we observed that the gantry angles were generally within 2° agreement with the ones recorded in the log files.…”

Section: Discussionsupporting

confidence: 81%

A novel method for sub‐arc VMAT dose delivery verification based on portal dosimetry with an EPID

2017

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Section: Discussionsupporting

confidence: 81%

A novel method for sub‐arc VMAT dose delivery verification based on portal dosimetry with an EPID

2017

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“…This study used the absolute difference between positions (c) and (d) for MLC performance quantitation. However, Neal et al 12 reported observed discrepancies between positions (b) and (d). We have not observed such discrepancies and cannot comment on this issue.…”

Section: Introductionmentioning

confidence: 97%

Utilizing historical MLC performance data from trajectory logs and service reports to establish a proactive maintenance model for minimizing treatment disruptions

Zhang

Kanchaveli

et al. 2019

Medical Physics

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Purpose This study proposes a proactive maintenance model utilizing historical Multileaf collimator (MLC) performance data to predict potential MLC dysfunctions, promote preemptive maintenance and thereby reduce treatment disruptions. Methods MLC failures were assumed to correlate with MLC performance quantitation from trajectory logs. A cohort of data from service reports and trajectory logs was used to establish a model for predicting MLC dysfunctions. Specifically, the service reports logged by our in‐house engineers recorded failure status, including service date, service reason and actions taken, while trajectory logs recorded the ordered/actual leaf positions in 20‐ms intervals. Leaf performance from trajectory logs was quantified, where an event was defined as detecting a leaf's position deviation ≥a mm. Three a values, 0.05, 0.1, and 0.5 mm, were used as candidates to determine the appropriate threshold for deviation event quantitation. Logged MLC failures from service reports were retrieved and classified into two categories based on the patterns of their deviation events calculated from trajectory logs: (a) failures with continuous deviations: deviation events lasted several days before failure, and (b) failures with a burst of deviations: deviation events only lasted 1 or 2 days and then MLC failed suddenly. The proposed proactive model focused on the failures with continuous deviations since abnormal trends in their deviation events lasted couple of days, allowing preventive maintenance. The model was predefined with three parameters (x, y, z): if a leaf scored ≥x deviation events per day in any y days within up to a z‐day window, the leaf was marked as a “potential failure.” The distributions of the deviation events as functions of time (days or weeks) and leaves using the found a‐value were then associated with logged failures to find model parameters. In a retrospective demonstration, a total of 28 logged failures with continuous deviations and 66 397 trajectory logs from two TBs' 3‐yr records were used to determine the model parameters (x, y, z). The established model was then applied to a third TB for validation. Results Deviation event threshold, a, was determined to be 0.1 mm, and the resulting model parameters were (x = 20, y = 6, z = 10). When validating the third TB's 3‐yr record with 12 logged continuous deviation failures, the model predicted 16 failures: seven were confirmed from the records with a hit rate of 58.3%, while nine were not; further investigation of each unconfirmed failure convinced that some could be actual failures, but somehow not recorded. Conclusion The model offers an addition to preemptive maintenance for reducing treatment disruptions.

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“…However, the EPID resolution of the Vero4DRT was 0.18 mm/pixel at the isocenter plane and this gave sufficient sensitivity to detect positional errors with submillimeter sizes. Furthermore, several researchers reported that Varian Dynalog files were not sufficient to detect MLC leaf position errors 17, 35. Zwan et al.…”

Section: Discussionmentioning

confidence: 99%

Quality assurance of geometric accuracy based on an electronic portal imaging device and log data analysis for Dynamic WaveArc irradiation

Hirashima

Miyabe

Nakamura

et al. 2018

J Applied Clin Med Phys

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The purpose of this study was to develop a simple verification method for the routine quality assurance (QA) of Dynamic WaveArc (DWA) irradiation using electronic portal imaging device (EPID) images and log data analysis. First, an automatic calibration method utilizing the outermost multileaf collimator (MLC) slits was developed to correct the misalignment between the center of the EPID and the beam axis. Moreover, to verify the detection accuracy of the MLC position according to the EPID images, various positions of the MLC with intentional errors in the range 0.1–1 mm were assessed. Second, to validate the geometric accuracy during DWA irradiation, tests were designed in consideration of three indices. Test 1 evaluated the accuracy of the MLC position. Test 2 assessed dose output consistency with variable dose rate (160–400 MU/min), gantry speed (2.2–6°/s), and ring speed (0.5–2.7°/s). Test 3 validated dose output consistency with variable values of the above parameters plus MLC speed (1.6–4.2 cm/s). All tests were delivered to the EPID and compared with those obtained using a stationary radiation beam with a 0° gantry angle. Irradiation log data were recorded simultaneously. The 0.1‐mm intentional error on the MLC position could be detected by the EPID, which is smaller than the EPID pixel size. In Test 1, the MLC slit widths agreed within 0.20 mm of their exposed values. The averaged root‐mean‐square error (RMSE) of the dose outputs was less than 0.8% in Test 2 and Test 3. Using log data analysis in Test 3, the RMSE between the planned and recorded data was 0.1 mm, 0.12°, and 0.07° for the MLC position, gantry angle, and ring angle, respectively. The proposed method is useful for routine QA of the accuracy of DWA.

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A clinically observed discrepancy between image‐based and log‐based MLC positions

Cited by 52 publications

References 10 publications

A novel method for sub‐arc VMAT dose delivery verification based on portal dosimetry with an EPID

A novel method for sub‐arc VMAT dose delivery verification based on portal dosimetry with an EPID

Utilizing historical MLC performance data from trajectory logs and service reports to establish a proactive maintenance model for minimizing treatment disruptions

Quality assurance of geometric accuracy based on an electronic portal imaging device and log data analysis for Dynamic WaveArc irradiation

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