Monte Carlo simulation and experimental validation of SPECT systems via energy spectrum decomposition and image...

Accurate modelling and performance evaluation of gamma-ray scintillation detectors are required in single photon emission computed tomography (SPECT) systems to ensure reliable nuclear medicine diagnostics. Monte Carlo simulation is therefore a powerful computational technique used to accurately model the gamma-ray scintillation detectors and photon transport in medical imaging systems. Therefore, the objective of this study is to validate the SIMIND Monte Carlo simulation code using a self-developed peak-detection algorithm for clinical SPECT gamma cameras (Siemens E.Cam and GE Infinia), with a focus on energy-spectrum decomposition and image-profile analysis.

This study presents a dual-system evaluation of clinical SPECT gamma cameras-the Siemens E.Cam and GE Infinia systems using the SIMIND Monte Carlo simulation code. We assessed collimator and detector-specific SPECT performance metrics, including energy resolution, sensitivity, image evaluation, spatial resolutions, and spectral fidelity for a ^99mTc point source and spatial resolution with Co-57 flood source. A custom algorithm was then developed to automatically decompose energy spectra and identify key spectral components, including the photopeak, Compton edge, iodine escape, and lead X-ray peaks. Quantitative methods, such as 2D and 3D image profile analysis and FWHM comparisons, were integrated to validate the simulation against experimental data.

Energy resolution differences ≤ 4% and sensitivity variations < 1.2% were observed between simulated and experimental measurements. Spatial resolution analysis revealed a range of 3.5-4.8 mm for Siemens E.Cam (bar and pie phantoms) and ~ 1 cm for GE Infinia, highlighting system-specific imaging capabilities. A custom algorithm successfully identified key spectral components, including photopeaks, Compton edges, and lead X-ray peaks, with deviations < 3%. Image profile analysis revealed FWHM values of 4-4.5 pixels for both systems.

This work shows that SIMIND accurately reproduces the fundamental photon interaction characteristics including energy spectra, energy resolution, and sensitivity for both Siemens E.Cam and GE Infinia SPECT systems. However, for image-profile evaluation, good agreement was obtained for Siemens E.Cam, whereas the GE Infinia results revealed a system-specific discrepancy associated with the actual clinical condition of the installed camera. Nevertheless, when used appropriately, SIMIND provides a robust framework for optimizing quantitative SPECT protocols and guiding system design improvements, particularly for well-calibrated systems.