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A Simple Model for In-Vivo Exit Dose Verification Based On EPID in Intensity Modulated Radiotherapy

z wu*, j wang , Y Chen , W Hu , fudan university shanghai cancer center, Shanghai, shanghai


(Sunday, 7/29/2018) 3:00 PM - 6:00 PM

Room: Exhibit Hall

Purpose: The aim of this study was to present a model-based EPID dosimetry method as a means of gross treatment delivery errors detection(i.e. setup errors, wrong patient), and to investigate the performance of the EPID dosimetry system for error detection during IMRT treatments.

Methods: EPID can be used to acquire a two-dimensional exit dose distribution during treatment delivery, and the EPID was positioned at a 150cm source detector distance(SDD). We utilized equivalent thickness water which was positioned at a 120cm SDD represent the metal-plate of EPID, to determine the predicted portal dose image (PDI) in a clinical treatment planning system (TPS). The PDIs was converted to the fluences at SDD of 150cm using the inverse square law. The in-vivo verification of the dose delivery through a comparison of measured EPID images to predicted EPID images. The 2D dose evaluation was conducted using 3%/3 gamma-index criteria. Systematic setup errors were introduced by manually moving the treatment couch by 0.5cm, 0.8cm, 1cm, 1.2cm, 1.5cm in each translational direction to assess the sensitivity of setup errors using the gamma analysis. Apply different patients (10 head and neck patients) CT data for predicted EPID data to simulate wrong patient being treated.

Results: The measured dose–response with homogeneous phantom in the square fields agreed with TPS dose calculations to within 2%. Gamma evaluation showed at least 92% in integrated doses with rando phantom in the clinical fields acquired by the compared with TPS-calculated portal dose images. The gamma algorithm was insensitive to setup error. For error simulation, the system utilized the Gamma evaluation could detect wrong patient immediately.

Conclusion: Our novel approach to in-vivo dose delivery verification has been demonstrated utilizing a water equivalent EPID. The model proposed provides an accurate method to detect those gross treatment delivery errors.


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