Intrinsic detector sensitivity analysis as a tool to characterize ArcCHECK and EPID sensitivity to variations in delivery for lung SBRT VMAT plans

Abstract

Purpose To investigate intrinsic sensitivity of an electronic portal imaging device (EPID) and the ArcCHECK detector and to use this in assessing their performance in detecting delivery variations for lung SBRT VMAT. The effect of detector spatial resolution and dose matrix interpolation on the gamma pass rate was also considered. Materials and methods Fifteen patients’ lung SBRT VMAT plans were used. Delivery variations (errors) were introduced by modifying collimator angles, multi‐leaf collimator (MLC) field sizes and MLC field shifts by ±5, ±2, and ±1 degrees or mm (investigating 103 plans in total). EPID and ArcCHECK measured signals with introduced variations were compared to measured signals without variations (baseline), using OmniPro‐I'mRT software and gamma criteria of 3%/3 mm, 2%/2 mm, 2%/1 mm, and 1%/1 mm, to test each system's basic performance. The measurement sampling resolution for each was also changed to 1 mm and results compared to those with the default detector system resolution. Results Intrinsic detector sensitivity analysis, that is, comparing measurement to baseline measurement, rather than measurement to plan, demonstrated the intrinsic constraints of each detector and indicated the limiting performance that users might expect. Changes in the gamma pass rates for ArcCHECK, for a given introduced error, were affected only by dose difference (DD %) criteria. However, the EPID showed only slight changes when changing DD%, but greater effects when changing distance‐to‐agreement criteria. This is pertinent for lung SBRT where the minimum dose to the target will drop dramatically with geometric errors. Detector resolution and dose matrix interpolation have an impact on the gamma results for these SBRT plans and can lead to false positives or negatives in error detection if not understood. Conclusion The intrinsic sensitivity approach may help in the selection of more meaningful gamma criteria and the choice of optimal QA device for site‐specific dose verification.

Evaluation of the ability of three commercially available dosimeters to detect systematic delivery errors in Step-and-Shoot IMRT plans

“…This was attributed to the head and neck plans having larger fields with higher modulation and irregular field shapes. The differences between detectors may be attributed to factors such as the inherent variations between the detectors in terms of resolution, detector density, geometry (2D/3D) as well as potential differences in how gamma is calculated in the software [45].…”

“…The aim of this work was to investigate any variations in the ability of three dosimetry systems (ArcCHECK (3D), EPID (2D) and MatriXX Evolution (2D)) to detect systematic delivery errors in step-and-shoot IMRT. This work is part of a larger investigation by the local research group of the impact of uncertainties on advanced radiotherapy treatment techniques [18,[37][38][39][40][41][42][43][44][45].…”

Evaluating Mobius3D Dose Calculation Accuracy for Small-Field Flattening- Filter-Free Photon Beams

“…To overcome these limitations, various pretreatment QA methods have been proposed using innovative devices and algorithms. [9][10][11][12][13][14][15][16][17][18][19] Among these, dose-volume histogram (DVH)-based patient-specific QA has emerged in recent years. The DVH-based method enables the calculation of dose distributions in the patient domain, where tissue inhomogeneity is considered.…”

Comprehensive clinical evaluation of TomoEQA for patient-specific pre-treatment quality assurance in helical tomotherapy

“…Delta4 (Scandi-Dos, Madison, WI, USA; biplanar diode array) and Arc-CHECK (SNC, Melbourne, FL, USA; cylindrical diode array) are more innovative devices that are capable of semi-3D dosimetry, and the dose distribution information can be preserved regardless of the beam incidence angle. However, the measurement errors of such devices tend to be underestimated because data post-processing procedures, including interpolation and setup error correction, are required [4][5][6][7][8]. To compensate for the limitations of these existing QA methods, TomoEQA, a log-based patient-specific pre-treatment QA method dedicated to HT, was proposed in our previous work [9].…”