2018
DOI: 10.1002/mp.12926
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Evaluation of machine log files/MC‐based treatment planning and delivery QA as compared to ArcCHECK QA

Abstract: Reconstructing every log file sample with no increase in computational cost, MC-based LF QA is faster and more accurate than CS-based LF QA. Offering similar dosimetric accuracy compared to AC measurement, MC-based log files can be used for treatment planning QA.

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Cited by 10 publications
(12 citation statements)
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References 35 publications
(73 reference statements)
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“…Stanhope et al [13] found a behavior of the dose ratio rather similar to the one shown in Figs. 6a and 6b though the ranges are smaller than ours.…”
Section: Dependence On the Pulse Repetition Ratesupporting
confidence: 62%
See 1 more Smart Citation
“…Stanhope et al [13] found a behavior of the dose ratio rather similar to the one shown in Figs. 6a and 6b though the ranges are smaller than ours.…”
Section: Dependence On the Pulse Repetition Ratesupporting
confidence: 62%
“…Other works have dealt with the physical characterization of the device [3,[9][10][11][12][13]. However, much of the tests carried out in these studies have considered only one of the diodes that are part of the device or, at most, a reduced number of them.…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, the conventional method ignores patient-specific anatomical variations. In comparison, a logfiles-based QA system, such as Mobi-us3D (Varian Medical System) and ArcCHECK (Sun Nuclear), will enable automation, tracking of heterogeneous anatomical dose, and allow for root-cause analysis [21].…”
Section: Discussionmentioning
confidence: 99%
“…Log file analysis is a very time‐saving tool for patient QA in clinical routine. Because of these advantages, there is a growing interest in using log files with an independent Monte Carlo (MC) algorithm 18 . Haga et al investigated log file analysis for a single simple prostate plan and demonstrated that Elekta 4‐Hz log files have satisfying results for QA 19 .…”
Section: Introductionmentioning
confidence: 99%