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Many modern molecular imaging techniques, based on radiopharmaceuticals, can take advantage of sophisticated devices but are still based on the scintillation detector mechanism proposed by Anger. These devices can perform with millimeter spatial resolution and high detection efficiency, but the final performance is strongly affected by the algorithm used for the scintillation position detection. In this work, a detailed comparison of the effect on the imaging performances of three new position detection algorithms, in terms of spatial resolution, detection linearity and useful Field of View is performed on a prototype gamma detector. The detector, built by the authors, is based on a continuous LaBr3:Ce scintillation crystal coupled to an Hamamatsu MA-PMT H8500 and a single anode readout electronics. The experimental data are obtained scanning the detector surface with a Tc99m collimated source (0.4 mm ϕ) at 1.5 mm step. The overall imaging performances of the device are also tested by mean of a bar phantom. We conclude that the Anger-like algorithms give a 50% uFoV with a 1.30 mm ±0.05 mm spatial resolution while the proposed algorithms give a 80% uFoV and 1.10 mm ±0.06 mm spatial resolution.

In this work, we developed a model able to predict in a few seconds the response of a gamma camera based on continuous scintillator in terms of linearity and spatial resolution in the whole field of view (FoV). This model will be useful during the design phase of a SPECT or PET detector in order to predict and optimize gamma camera performance by varying the parameter values of its components (scintillator, light guides, and photodetector). Starting from a model of the scintillation light distribution on the photodetector sensitive surface, a theoretical analysis based on the estimation theory is carried out in order to find the analytical expressions of bias and FWHM related to four interaction position estimation methods: the classical Center of Gravity method (Anger Logic), an enhanced Center of Gravity method, a Mean Square Error fitting method, and the Maximum Likelihood Estimation method. Afterwards, spatial resolution as well as depth of interaction (DOI) distribution effects are evaluated by processing biases and FWHMs at different DOIs. The comparison between the model and GEANT4 Monte Carlo simulations of four different detection systems has been carried out. Our model prediction errors of spatial resolution, in terms of percentage RMSDs with respect to the simulated spatial resolution, are lower than 13.2% in the whole FoV for three estimation methods. The computational time to calculate spatial resolutions with the model in the whole FoV is five order of magnitudes faster than an equivalent standard Monte Carlo simulation. © 2016 IEEE

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