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Alhazmi, Abdulaziz; Gianoli, Chiara; Neppl, Sebastian; Martins, Juliana; Veloza, Stella; Podesta, Mark; Verhaegen, Frank; Reiner, Michael; Belka, Claus; Parodi, Katia (2018): A novel approach to EPID-based 3D volumetric dosimetry for IMRT and VMAT QA. In: Physics in Medicine and Biology, Vol. 63, No. 11, 115002
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Abstract

Intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) are relatively complex treatment delivery techniques and require quality assurance (QA) procedures. Pre-treatment dosimetric verification represents a fundamental QA procedure in daily clinical routine in radiation therapy. The purpose of this study is to develop an EPID-based approach to reconstruct a 3D dose distribution as imparted to a virtual cylindrical water phantom to be used for plan-specific pre-treatment dosimetric verification for IMRT and VMAT plans. For each depth, the planar 2D dose distributions acquired in air were back-projected and convolved by depth-specific scatter and attenuation kernels. The kernels were obtained by making use of scatter and attenuation models to iteratively estimate the parameters from a set of reference measurements. The derived parameters served as a look-up table for reconstruction of arbitrary measurements. The summation of the reconstructed 3D dose distributions resulted in the integrated 3D dose distribution of the treatment delivery. The accuracy of the proposed approach was validated in clinical IMRT and VMAT plans by means of gamma evaluation, comparing the reconstructed 3D dose distributions with Octavius measurement. The comparison was carried out using (3% , 3 mm) criteria scoring 99% and 96% passing rates for IMRT and VMAT, respectively. An accuracy comparable to the one of the commercial device for 3D volumetric dosimetry was demonstrated. In addition, five IMRT and five VMAT were validated against the 3D dose calculation performed by the TPS in a water phantom using the same passing rate criteria. The median passing rates within the ten treatment plans was 97.3%, whereas the lowest was 95%. Besides, the reconstructed 3D distribution is obtained without predictions relying on forward dose calculation and without external phantom or dosimetric devices. Thus, the approach provides a fully automated, fast and easy QA procedure for plan-specific pretreatment dosimetric verification.