Comparison of 3D Scatter Correction Methods for a Long Axial Field of View PET Scanner

Single scatter simulation (SSS) is the most commonly used approach to mitigate the effects of scattered photons in PET imaging. However, the introduction of long axial field of view (LAFOV) scanners has required this method to be revisited or alternative methods to be adopted. In this work we compared a version of SSS with tail fitting (SSS-TF) devised for LAFOV, an alternative version of SSS with a statistical method to scale the scatter sinogram (SSS-MLSS), and a simplified fast GPU-based Monte-Carlo method (MC-GPU). These methods were evaluated using the MC toolkit GATE, simulating geometrical and realistic patient-based voxelized phantoms, employing the scatter simulated by GATE as reference. Furthermore, the three scatter correction methods were compared on scanned phantoms and patients. Regarding image artefacts, results showed that SSS-TF and SSS-MLSS performed similarly in general, but SSS-MLSS outperformed SSS-TF in challenging scenarios. MC-GPU consistently outperformed SSS-TF and SSS-MLSS regarding image artefacts, but at slightly longer computation times. Quantitatively, all methods showed relative differences <=5% compared to the reference, except for those regions with artefacts, but none of them showed consistently overall superior performance among them. Experimental measurements confirmed that SSS-MLSS outperforms SSS-TF in challenging cases, showing similar performance compared to MC-GPU.