Open AccessA transit portal dosimetry method for respiratory gating quality assurance with a dynamic 3D printed tumor phantom
Author(s) -
Tan Hong Qi,
Koh Calvin Wei Yang,
Tan Lloyd Kuan Rui,
Lew Kah Seng,
Chua Clifford Ghee Ann,
Ang Khong Wei,
Lee James Cheow Lei,
Park Sung Yong
Publication year - 2022
Publication title -
journal of applied clinical medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.83
H-Index - 48
ISSN - 1526-9914
DOI - 10.1002/acm2.13560
Subject(s) - imaging phantom , quality assurance , gating , dosimetry , breathing , computer science , detector , radiation treatment planning , ionization chamber , wilcoxon signed rank test , nuclear medicine , materials science , biomedical engineering , radiation therapy , medicine , physics , radiology , physiology , telecommunications , ion , external quality assessment , pathology , quantum mechanics , anatomy , ionization , mann–whitney u test
Backgrounds Respiratory gating is one of the motion management techniques that is used to deliver radiation dose to a tumor at a specific position under free breathing. However, due to the dynamic feedback process of this approach, regular equipment quality assurance (QA) and patient‐specific QA checks need to be performed. This work proposes a new QA methodology using electronic portal imaging detector (EPID) to determine the target localization accuracy of phase gating. Methods QA tools comprising 3D printed spherical tumor phantoms, programmable stages, and an EPID detector are characterized and assembled. Algorithms for predicting portal dose (PD) through moving phantoms are developed and verified using gamma analysis for two spherical tumor phantoms (2 cm and 4 cm), two different 6 MV volumetric modulated arc therapy plans, and two different gating windows (30%–70% and 40%–60%). Comparison between the two gating windows is then performed using the Wilcoxon signed‐rank test. An optimizer routine, which is used to determine the optimal window, based on maximal gamma passing rate (GPR), was applied to an actual breathing curve and breathing plan. This was done to ascertain if our method yielded a similar result with the actual gating window. Results High GPRs of more than 97% and 91% were observed when comparing the predicted PD with the measured PD in moving phantom at 2 mm/2% and 1 mm/1% levels, respectively. Analysis of gamma heatmaps shows an excellent agreement with the tumor phantom. The GPR of 40%–60% PD was significantly lower than that of the 30%–70% PD at the 1 mm/1% level ( p = 0.0064) . At the 2 mm/2% level, no significant differences were observed. The optimizer routine could accurately predict the center of the gating window to within a 10% range. Conclusion We have successfully performed and verified a new method for QA with the use of a moving phantom with EPID for phase gating with real‐time position management.