Implementing RapidArc into clinical routine: A comprehensive program from machine QA to TPS validation and patient QA

Volumetric‐modulated arc therapy (VMAT) treatment delivery requires three key dynamic components; gantry rotation, dose rate modulation, and multi‐leaf collimator motion, which are all simultaneously varied during the delivery. Misalignment of the gantry angle can potentially affect clinical outcome due to the steep dose gradients and complex MLC shapes involved. It is essential to develop independent gantry angle quality assurance (QA) appropriate to VMAT that can be performed simultaneously with other key VMAT QA testing. In this work, a simple and inexpensive fully independent gantry angle measurement methodology was developed that allows quantitation of the gantry angle accuracy as a function of time. This method is based on the analysis of video footage of a “Double dot” pattern attached to the front cover of the linear accelerator that consists of red and green circles printed on A4 paper sheet. A standard mobile phone is placed on the couch to record the video footage during gantry rotation. The video file is subsequently analyzed and used to determine the gantry angle from each video frame using the relative position of the two dots. There were two types of validation tests performed including the static mode with manual gantry angle rotation and dynamic mode with three complex test plans. The accuracy was 0.26° ± 0.04° and 0.46° ± 0.31° (mean ± 1 SD) for the static and dynamic modes, respectively. This method is user friendly, cost effective, easy to setup, has high temporal resolution, and can be combined with existing time‐resolved method for QA of MLC and dose rate to form a comprehensive set of procedures for time‐resolved QA of VMAT delivery system.

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A novel and independent method for time‐resolved gantry angle quality assurance for VMAT

Fuangrod

Greer

Zwan

et al. 2017

“…These three dynamic components (i.e., MLC, gantry angle, and dose rate) must remain synchronized throughout the treatment in order to deliver the intended dose to the planning target volume (PTV) and organs at risk (OAR). Due to this high level of complexity, there is a need for comprehensive and informative quality assurance (QA) techniques 4 , 5 …”

Section: Introductionmentioning

confidence: 99%

“…In this test, the leaves move in a single direction, a uniform leaf speed is used, and the leaf positions are not determined quantitatively. A set of different tests were proposed by van Esch et al; (5) however, these are very time‐consuming, involve film dosimetry, and have not gained widespread use. More recently, the Netherlands Commission on Radiation Dosimetry has proposed a more comprehensive quality assurance program for VMAT (13) .…”

Section: Introductionmentioning

confidence: 99%

An EPID‐based system for gantry‐resolved MLC quality assurance for VMAT

Zwan

Barnes

Fuangord

et al. 2016

Multileaf collimator (MLC) positions should be precisely and independently measured as a function of gantry angle as part of a comprehensive quality assurance (QA) program for volumetric‐modulated arc therapy (VMAT). It is also ideal that such a QA program has the ability to relate MLC positional accuracy to patient‐specific dosimetry in order to determine the clinical significance of any detected MLC errors. In this work we propose a method to verify individual MLC trajectories during VMAT deliveries for use as a routine linear accelerator QA tool. We also extend this method to reconstruct the 3D patient dose in the treatment planning system based on the measured MLC trajectories and the original DICOM plan file. The method relies on extracting MLC positions from EPID images acquired at 8.41 fps during clinical VMAT deliveries. A gantry angle is automatically tagged to each image in order to obtain the MLC trajectories as a function of gantry angle. This analysis was performed for six clinical VMAT plans acquired at monthly intervals for three months. The measured trajectories for each delivery were compared to the MLC positions from the DICOM plan file. The maximum mean error detected was 0.07 mm and a maximum root‐mean‐square error was 0.8 mm for any leaf of any delivery. The sensitivity of this system was characterized by introducing random and systematic MLC errors into the test plans. It was demonstrated that the system is capable of detecting random and systematic errors on the range of 1–2 mm and single leaf calibration errors of 0.5 mm. The methodology developed in the work has potential to be used for efficient routine linear accelerator MLC QA and pretreatment patient‐specific QA and has the ability to relate measured MLC positional errors to 3D dosimetric errors within a patient volume.PACS number(s): 87.55.Qr

A method to reconstruct and apply 3D primary fluence for treatment delivery verification

Shi

Mazur

et al. 2016

MotivationIn this study, a method is reported to perform IMRT and VMAT treatment delivery verification using 3D volumetric primary beam fluences reconstructed directly from planned beam parameters and treatment delivery records. The goals of this paper are to demonstrate that 1) 3D beam fluences can be reconstructed efficiently, 2) quality assurance (QA) based on the reconstructed 3D fluences is capable of detecting additional treatment delivery errors, particularly for VMAT plans, beyond those identifiable by other existing treatment delivery verification methods, and 3) QA results based on 3D fluence calculation (3DFC) are correlated with QA results based on physical phantom measurements and radiation dose recalculations.MethodsUsing beam parameters extracted from DICOM plan files and treatment delivery log files, 3D volumetric primary fluences are reconstructed by forward‐projecting the beam apertures, defined by the MLC leaf positions and modulated by beam MU values, at all gantry angles using first‐order ray tracing. Treatment delivery verifications are performed by comparing 3D fluences reconstructed using beam parameters in delivery log files against those reconstructed from treatment plans. Passing rates are then determined using both voxel intensity differences and a 3D gamma analysis. QA sensitivity to various sources of errors is defined as the observed differences in passing rates. Correlations between passing rates obtained from QA derived from both 3D fluence calculations and physical measurements are investigated prospectively using 20 clinical treatment plans with artificially introduced machine delivery errors.ResultsStudies with artificially introduced errors show that common treatment delivery problems including gantry angle errors, MU errors, jaw position errors, collimator rotation errors, and MLC leaf position errors were detectable at less than normal machine tolerances. The reported 3DFC QA method has greater sensitivity than measurement‐based QA methods. Statistical analysis‐based Spearman's correlations shows that the 3DFC QA passing rates are significantly correlated with passing rates of physical phantom measurement‐based QA methods.ConclusionAmong measurement‐less treatment delivery verification methods, the reported 3DFC method is less demanding than those based on full dose re‐calculations, and more comprehensive than those that solely checks beam parameters in treatment log files. With QA passing rates correlating to measurement‐based passing rates, the 3DFC QA results could be useful for complementing the physical phantom measurements, or verifying treatment deliveries when physical measurements are not available. For the past 4+ years, the reported method has been implemented at authors’ institution 1) as a complementary metric to physical phantom measurements for pretreatment, patient‐specific QA of IMRT and VMAT plans, and 2) as an important part of the log file‐based automated verification of daily patient treatment deliveries. It has been demonstrated to be useful in catching both treatment plan data transfer errors and treatment delivery problems.