Intensity-modulated radiation therapy dose verification using fluence and portal imaging device.

Iori Sumida,Mari Tsujii,Kazuhiko Ogawa,Osamu Suzuki,Indra J Das,Hisao Kizaki,Keiko Aboshi,Yuji Yamada,Hajime Yamaguchi,Fumiaki Isohashi,Yuji Seo

doi:10.1120/jacmp.v17i1.5899

Abstract

Patient‐specific quality assurance for intensity‐modulated radiation therapy (IMRT) dose verification is essential. The aim of this study is to provide a new method based on the relative error distribution by comparing the fluence map from the treatment planning system (TPS) and the incident fluence deconvolved from the electronic portal imaging device (EPID) images. This method is validated for 10 head and neck IMRT cases. The fluence map of each beam was exported from the TPS and EPID images of the treatment beams were acquired. Measured EPID images were deconvolved to the incident fluence with proper corrections. The relative error distribution between the TPS fluence map and the incident fluence from the EPID was created. This was also created for a 2D diode array detector. The absolute point dose was measured with an ionization chamber, and the dose distribution was measured by a radiochromic film. In three cases, MLC leaf positions were intentionally changed to create the dose error as much as 5% against the planned dose and our fluence‐based method was tested using gamma index. Absolute errors between the predicted dose of 2D diode detector and of our method and measurements were 1.26%±0.65% and 0.78%±0.81% respectively. The gamma passing rate (3% global / 3 mm) of the TPS was higher than that of the 2D diode detector (p<0.02), and lower than that of the EPID (p<0.04). The gamma passing rate (2% global / 2 mm) of the TPS was higher than that of the 2D diode detector, while the gamma passing rate of the TPS was lower than that of EPID (p<0.02). For three modified plans, the predicted dose errors against the measured dose were 1.10%, 2.14%, and −0.87%. The predicted dose distributions from the EPID were well matched to the measurements. Our fluence‐based method provides very accurate dosimetry for IMRT patients. The method is simple and can be adapted to any clinic for complex cases.PACS numbers: 87.55.D‐, 87.55.km, 87.55.Qr, 87.57.uq

Highlights

260 Sumida et al.: Fluence-based verification method for intensity-modulated radiation therapy (IMRT) quality assurance (QA) imaging devices (EPIDs), computed tomography (CT) on-rail, infrared markers, and ultrasound systems have been used before or during irradiation
Kruse[22] reported insensitivity between the per-beam QA gamma passing rate and dosimetric accuracy in 3D. These studies suggest the importance of evaluating dose verification in 3D over a clinically relevant anatomic field and of predicting dose distributions on the basis of QA results,(23,24) or measurement-guided dose reconstruction (MGDR).(25) The measured data are usually derived from 2D or 3D detector arrays and include electronic portal imaging device (EPID) dosimetry.[26]. A few studies have used measured fluence data[27,28] and required dose calculation engines, such as pencil beam convolution algorithms, to reconstruct the 3D dose distributions
The relative error distribution between the fluence map calculated by the treatment planning system (TPS) and the measured fluence map deconvolved from an EPID image was used to predict doses on the basis of perbeam QA results

Summary

Introduction

260 Sumida et al.: Fluence-based verification method for IMRT QA imaging devices (EPIDs), computed tomography (CT) on-rail, infrared markers, and ultrasound systems have been used before or during irradiation. Kruse[22] reported insensitivity between the per-beam QA gamma passing rate and dosimetric accuracy in 3D These studies suggest the importance of evaluating dose verification in 3D over a clinically relevant anatomic field and of predicting dose distributions on the basis of QA results,(23,24) or measurement-guided dose reconstruction (MGDR).(25) The measured data are usually derived from 2D or 3D detector arrays and include EPID dosimetry.[26] A few studies have used measured fluence data[27,28] and required dose calculation engines, such as pencil beam convolution algorithms, to reconstruct the 3D dose distributions

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Methods

Discussion

Conclusion