2D dose reconstruction of IMRT patient-specific QA based on log file

Mubarok, Sayid; Wahyu, Wibowo Edy; Supriyanto, Pawiro Ardjo

doi:10.1016/j.radphyschem.2019.108473

Cited by 4 publications

(10 citation statements)

References 14 publications

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“…1 st plan is before MLC error applied and 2 nd plan for after MLC error applied. That results in difference in DVH values figure (5) shows two DVH one before MLC modifications and second after MLC modification this result is in line with Woon et al, 2018 [2].…”

Section: Effect Of Mlc Error On Dvh Result: -supporting

confidence: 85%

“…As shown in the figure (5), the coverage of PTV is increased after MLC modification error which is applied from logfile analysis. On the other hand, the dose of OAR is also increased; this noted effect may lead to increasing the dose constrains of OAR, and at a same time, may lead to late dose effect.…”

Section: Effect Of Mlc Error On Dvh Result: -mentioning

confidence: 99%

“…Tow plans were created for each case; one is the original plan before MLC modification and the other plan done after MLC modification. Figure (7) and Table (5) shows the result of TCP for target tumor. The result shows increasing in the TCP result after modification compared with TCP before modification.…”

Section: Tcp and Ntcp Calculations Results: -mentioning

confidence: 99%

“…MLC movement accuracy depends on several factors such as motors of MLC, gravity and gantry direction, leaf speed, and dose rate [1,4]. In the modern clinical series of linear accelerators, there is an option to record the mechanism of dose delivery from the LINAC in a logfile, this logfile has also been proposed to save the information of gantry rotation, delivered monitor unite, collimator rotation, MLCs position and actual speeds during delivery and planned in treatment planning system (TPS) [5]. To improve the efficiency of patient-specific quality assurance and provide insight into machine parameters not possible with phantom based measurements, logfile analysis has also been proposed [5,6,7,8].…”

Section: Radiobiological Assessment Of the Mlc Positioning Error And Itsmentioning

confidence: 99%

See 3 more Smart Citations

Radiobiological Assessment of the MLC Positioning error and its relation to the delivery of dose rate using logfile analysis

Yousif

Gawad

Metwally

et al. 2022

Egypt. J. Biophys. Biomed. Engng.

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Section: Effect Of Mlc Error On Dvh Result: -supporting

confidence: 85%

Section: Effect Of Mlc Error On Dvh Result: -mentioning

confidence: 99%

Section: Tcp and Ntcp Calculations Results: -mentioning

confidence: 99%

Section: Radiobiological Assessment Of the Mlc Positioning Error And Itsmentioning

confidence: 99%

See 2 more Smart Citations

Radiobiological Assessment of the MLC Positioning error and its relation to the delivery of dose rate using logfile analysis

Yousif

Gawad

Metwally

et al. 2022

Egypt. J. Biophys. Biomed. Engng.

View full text Add to dashboard Cite

“…Due to their convenience and high temporal resolution, the use of machine log files as input data for linac and patient‐specific QA has been heavily investigated 19–55 . Log file–based patient‐specific QA usually involves the recalculation of the treatment plan with control points modified based upon log file data used as a representation of the “actual” delivery to be compared to the planned delivery 23–28,32,34–36,41–43,45–47,50–52,55 . A number of authors have cautioned about the nonindependence of log files from the systems under investigation and potential insensitivity of log files to MLC mis‐calibration or to faults in the MLC drive train and hence have suggested a need for separate MLC QA to assure log file accuracy 20,22,23,32,37,38,43,45,50 .…”

Section: Introductionmentioning

confidence: 99%

Insensitivity of machine log files to MLC leaf backlash and effect of MLC backlash on clinical dynamic MLC motion: An experimental investigation

Barnes

Pomare

Doebrich

et al. 2022

J Applied Clin Med Phys

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Multi-leaf -collimator (MLC) leaf position accuracy is important for accurate dynamic radiotherapy treatment plan delivery. Machine log files have become widely utilized for quality assurance (QA) of such dynamic treatments. The primary aim is to test the sensitivity of machine log files in comparison to electronic portal imaging device (EPID)-based measurements to MLC position errors caused by leaf backlash. The secondary aim is to investigate the effect of MLC leaf backlash on MLC leaf motion during clinical dynamic plan delivery. Methods: The sensitivity of machine log files and two EPID-based measurements were assessed via a controlled experiment, whereby the length of the "T" section of a series of 12 MLC leaf T-nuts in a Varian Millennium MLC for a Trilogy C-series type linac was reduced by sandpapering the top of the "T" to introduce backlash. The built-in machine MLC leaf backlash test as well as measurements for two EPID-based dynamic MLC positional tests along with log files were recorded pre-and post-T-nut modification. All methods were investigated for sensitivity to the T-nut change by assessing the effect on measured MLC leaf positions. A reduced version of the experiment was repeated on a TrueBeam type linac with Millennium MLC. Results: No significant differences before and after T-nut modification were detected in any of the log file data. Both EPID methods demonstrated sensitivity to the introduced change at approximately the expected magnitude with a strong dependence observed with gantry angle. EPID-based data showed MLC positional error in agreement with the micrometer measured T-nut length change to 0.07 ± 0.05 mm (1 SD) using the departmental routine QA test. Backlash results were consistent between linac types. Conclusion: Machine log files appear insensitive to MLC position errors caused by MLC leaf backlash introduced via the T-nut. The effect of backlash on clinical MLC motions is heavily gantry angle dependent.

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The Comparison of 2d Dose Patient-Specific Quality Assurance Between Monte Carlo-Convolution and Modified Clarkson Integration Algorithm

Azzi,

Pawiro,

Mart

2023

SPEKTRA

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A sophisticated machine of radiotherapy treatment process follows the complexity of the quality assurance (QA) measurement. Non-measurement QA becomes one of the solutions to reduce the medical physicists’ workload. However, this method has not been clinically established. This study compared two non-measurement methods of patient-specific quality assurance (PSQA) to find the feasible algorithm for the adaptive radiotherapy process. Monte Carlo-based (MC) PSQA used a phase space file of the medical linear accelerator (Linac) to obtain the photon energy fluence and forward projected to the isoplane. In contrast, Modified Clarkson Integration-based (MCI) used a non-uniform fluence map in the isoplane. For the modulated intensity, we used a pair of the dynamic log files of the multileaf-collimator (MLC) and then employed them in the algorithms. The dose distributions of MC and MCI methods were compared to the treatment planning system (TPS) using gamma index analysis. We found that the gamma pass rates (GPR) for MC-TPS and MCI-TPS were 99.54% and 99.57%, respectively. Further, the dose distribution in the off-axis region for the MCI method showed lesser accuracy due to the higher secondary dose contribution. The linac log file information can be used and calculated into a 2D dose distribution using both MC and MCI methods, providing high-accuracy results.

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2D dose reconstruction of IMRT patient-specific QA based on log file

Cited by 4 publications

References 14 publications

Radiobiological Assessment of the MLC Positioning error and its relation to the delivery of dose rate using logfile analysis

Radiobiological Assessment of the MLC Positioning error and its relation to the delivery of dose rate using logfile analysis

Insensitivity of machine log files to MLC leaf backlash and effect of MLC backlash on clinical dynamic MLC motion: An experimental investigation

The Comparison of 2d Dose Patient-Specific Quality Assurance Between Monte Carlo-Convolution and Modified Clarkson Integration Algorithm

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