Monte Carlo modelling of a compact CZT-based gamma camera with application to 177Lu imaging

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Abstract

Background: Semiconductor gamma-camera systems based on cadmium zinc telluride (CZT) detectors present new challenges due to an energy-response that includes effects of low-energy tailing. In particular, such energy tails produce effects that need to be considered when imaging radionuclides with multiple emissions such as 177Lu. Monte Carlo simulation can be used to investigate the behaviour of such systems and optimise their use, provided that the detector model closely reflects the real physical detector. The aim of this work is to develop a CZT model applicable for simulation of CZT-based gamma cameras. Methods: The equations describing the charge transport and signal induction are considered in three dimensions and are solved numerically, and the CZT model is then realised by coupling the detector-response to the photon-transport handled by the SIMIND Monte Carlo program. The CZT model is tuned to reproduce experimentally measured energy spectra of a hand-held gamma camera system for multiple radionuclides (99 mTc , 123I and 177Lu ) and parallel-hole collimators (MEGP, LEHR) as well as an uncollimated system. Results: Overall, the model results agree well with measurements across the range of experimental conditions. The applicability of the model is demonstrated by separating energy spectra into components to investigate the interference of high-energy photons on lower energy-windows, where pronounced effects of low-energy tailing for 177Lu are observed. Conclusions: The developed model provides understanding of the specifics of the camera response and is expected to be helpful for future optimisation of gamma camera applications.

Original languageEnglish
Article number35
JournalEJNMMI Physics
Volume9
Issue number1
DOIs
Publication statusPublished - 2022 Dec

Subject classification (UKÄ)

  • Radiology, Nuclear Medicine and Medical Imaging

Free keywords

  • CZT
  • Handheld gamma camera
  • Molecular imaging
  • Monte Carlo

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