A comparison of a Monte Carlo-based detection probability matrix with analytical probability matrix for small animal PET scanners
Positron Emission Tomography (PET) offers the possibility to quantitatively measure the radiotracer distribution in tissues. In order to obtain images of these tissues, the detection probability matrix (DPM) must be accurately determined. Usually, DPM is analytically calculated. However, this approach does not take into account the whole probabilistic interactions of the photons. On the other hand, Monte Carlo simulations (MC) are more accurate to calculate the DPM as they selectively consider diverse photon interactions. In this work, MC DPM (MCDPM) and analytically calculated DPM (ACDPM) were compared in terms of image quality. The results showed that the images obtained from the MCDPM were qualitatively better resolved and provided a significant improvement of the signal-to-noise ratio (SNR). The MCDPM yielded to an increase of up to 40% in SNR and up to 25% in contrast in comparison with ACDPM. On the other hands, MCDPM enhanced the counts distribution by more than 12% with respect to ACDPM.
detection probability matrix positron emission tomography monte carlo simulations image reconstruction small animal imaging