Characterization of a Compton camera setup with monolithic LaBr3(Ce) absorber and segmented GAGG scatter detectors

Conference paper (2018)

Authors

Silvia Liprandi Ludwig Maximilians University
Sodai Takyu National Institute of Radiological Sciences (NIRS), National Institutes for Quantum and Radiological Science and Technology (QST), Chiba
Saad Aldawood Ludwig Maximilians University, Hamburg University of Technology
Tim Binder King Saud University
G. Dedes King Saud University
Kei Kamada Universität der Bundeswehr München
Rudolf Lutter King Saud University
M. Mayerhofer Cambridge Medical Robotics Ltd., Cambridge
D.R. Schaart RST/Medical Physics & Technology - AS , C and A Corporation
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Research Group
RST/Medical Physics & Technology (AS) (TU Delft)
Copyright: © 2018 Silvia Liprandi, Sodai Takyu, Saad Aldawood, Tim Binder, George Dedes, Kei Kamada, Rudolf Lutter, Michael Mayerhofer, D.R. Schaart, More Authors
DOI: https://doi.org/10.1109/NSSMIC.2017.8533134
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Published Date

2018

Language

English

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Faculty

Applied Sciences

Department

RST/Radiation, Science and Technology

Research Group

RST/Medical Physics & Technology

Abstract

The purpose of this study is to perform a first characterization and proof of principle investigation of a Compton camera setup composed by a scatterer component consisting of a pixelated GAGG crystal read out by a SiPM multi-pixel photon counter (MPPC) and an absorber component consisting of a monolithic LaBr3 (Ce) scintillator read out by a 256-fold multianode photomultiplier (PMT). The rationale of the study is to develop a Compton camera system as a future ion beam range verification device during particle therapy, via prompt gamma imaging. The properties to be investigated are the reconstruction efficiency and accuracy achievable with this system for detecting prompt-\gamma rays. The Compton camera system described has been tested with a laboratory radioactive Cesium137 source, in a certain geometrical configuration. The readout system is based on individual spectroscopy (NIM+VME) electronic modules, digitizing energy and time signals. The data have been analyzed to produce an input for the image reconstruction, performed using the MEGAlib toolkit software.

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