ESTRO 2022 - Abstract Book

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Abstract book

ESTRO 2022

Fig. 1: a) MC-calculated ratios of the average absorbed dose to the detector cavity and water as a function of radial distance; b) Values normalized at 2 cm distance.

Fig. 2: MC-calculated ratios of the average absorbed dose to ZnSe detector and absorbed dose to water as a function of radial distance. All values were normalized to the ratio at 2 cm distance. Conclusion Experimental determination of absorbed-dose energy dependence of high- Z detectors should be performed under patient- like scattering conditions instead of adhering to TG-43 formalism. Additionally, it must be accounted for that the dependence is a function of radial distance and polar angle. While in these aspects inorganic scintillators are disadvantageous compared to the organic ones, we show that MC methods can aid and complement their characterization under clinically relevant conditions. Thus, allowing to introduce new detectors into the field that may benefit 192 Ir BT in vivo dosimetry.

OC-0116 Online treatment verification during brachytherapy using an inorganic scintillator – a phantom study

J. Johansen 1,2 , E.B. Jørgensen 1,2 , P. Georgi 1,2 , K. Tanderup 1,2

1 Aarhus University Hospital, Department of Oncology, Aarhus, Denmark; 2 Aarhus University, Department of Clinical Medicine, Aarhus, Denmark Purpose or Objective Currently, in vivo dosimetry (IVD) treatment verification is mainly based on evaluation of accumulated absorbed dose. The purpose of this study is to demonstrate online brachytherapy treatment verification based on real-time IVD and source tracking. Materials and Methods A brachytherapy treatment was simulated in a water phantom while real-time IVD was performed (phantom size: 25x30x30 cm 3 , water temperature: 37.5±1 o C). A ZnSe:O-based scintillation detector [1] with an in-house developed treatment verification software was used for IVD, and the procedure resembled a clinical routine. Prior to irradiation, a calibration of the scintillator was performed in a plastic phantom. For the simulated treatment, six needles were used for irradiation and the dosimeter was placed in a dedicated needle (distances to the other needles, 1, 1, 2, 2, 3 and 4 cm). A treatment plan (exported from Oncentra Prostate) was loaded into the treatment verification software to generate the expected dose rates, fig. 1. The treatment plan consisted of 5-12 dwell positions in each needle with dwell times in the range of 0.7-2 s. During irradiation, the software recorded and converted the signal into dose rate including a correction of the energy- dependency based on the signal height. A graphical user interface provided a direct comparison of the measured and

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