Abstract
The optimization of a whole-body PET system remains a challenging task, as the imaging performance is influenced by a complex interaction of different design parameters. However, it is not always clear which parameters have the largest impact on image quality and are most eligible for optimization. To determine this, we need to be able to assess their influence on image quality. We performed Monte-Carlo simulations of a whole-body PET scanner to predict the influence on image quality of three detector parameters: the TOF resolution, the transverse pixel size and depth-of-interaction (DOI)-correction. The inner diameter of the PET scanner was 65 cm, small enough to allow physical integration into a simultaneous PET-MR system. Point sources were used to evaluate the influence of transverse pixel size and DOI-correction on spatial resolution as function of radial distance. To evaluate the influence on contrast recovery and pixel noise a cylindrical phantom of 35 cm diameter was used, representing a large patient. The phantom contained multiple hot lesions with 5 mm diameter. These lesions were placed at radial distances of 50, 100 and 150 mm from the center of the field-of-view, to be able to study the effects at different radial positions. The non-prewhitening (NPW) observer was used for objective analysis of the detectability of the hot lesions in the cylindrical phantom. Based on this analysis the NPW-SNR was used to quantify the relative improvements in image quality due to changes of the variable detector parameters. The image quality of a whole-body PET scanner can be improved significantly by reducing the transverse pixel size from 4 to 2.6 mm and improving the TOF resolution from 600 to 400 ps and further from 400 to 200 ps. Compared to pixel size, the TOF resolution has the larger potential to increase image quality for the simulated phantom. The introduction of two layer DOI-correction only leads to a modest improvement for the spheres at radial distance of 150 mm from the center of the transaxial FOV.
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