Use of a Monte-Carlo based probability matrix for 3D iterative reconstruction of MADPET-II data

The small animal PET scanner MADPET-II, currently under development, is characterized by a small diameter (71 mm), two radial layers of detectors and by small LSO crystal elements read out individually by avalanche photodiodes. To exploit this configuration, aimed at achieving high resolution and high sensitivity, we intend to reconstruct a FOV almost as large as the opening of the device. However, parallax errors may hinder this task. To overcome this problem, our objective was to implement fully 3D reconstruction techniques (MLEM and OSEM) based on an accurate description of the system response. The mean feature of our method is the calculation of the probability system matrix by means of Monte-Carlo simulations. This approach requires the sorting of the simulated data into the matrix, a computation-expensive procedure hindered by the huge size of the matrix. To overcome this problem, we have employed a database management system (DB2), which has proved to be a practical solution. In this work we also studied the effect of applying the underlying symmetries within the matrix to reduce statistical noise affecting the matrix elements and to save disk space. The results showed that this procedure increases the SNR and contrast. The transaxial resolution calculated from a phantom consisting of 7 point sources degraded slowly towards the edges of the FOV: for a source at r = 0 the FWHM was 1.0 mm, while for a source at r = 30 mm, the FWHM was 2.0 mm. The use of the symmetries allowed us to reduce the resolution degradation (FWHM = 1.4 mm for r = 30 mm). Despite the gaps between modules and between detectors, rotation of the scanner was not needed. For the 3D case, an important issue is to improve the accuracy and the statistical quality of the matrix. This is the objective of our future work.