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The aim of this study is to investigate if image noise can be used to estimate the relative system sensitivity under different imaging conditions. Image noise was determined in a uniform cylindrical phantom, a Jaszczak phantom with fillable lesions (0.5-20 ml), with varying lesion to background ratios, ranging from 3-1 to 10-1, and an anthropomorphic torso phantom. In the torso phantom, fillable spheres were added to simulate lesions (5-1 lesion to background ratio). The phantoms were all scanned on a 2-D BGO system and an LSO 3-D system. Image noise was estimated using the bootstrap method. For each data set, 250 sinogram replicates were generated, which were reconstructed using FBP and OSEM (2i8s). The images were filtered to a final image resolution of 7 mm. From the reconstructed image sets, mean and SD images were generated. The relative sensitivities based on scatter corrected count rates from a 20 cm uniform cylinder is 5.4:1 (3D-LSO:2D-BGO). Based on the scan time resulting in equivalent noise levels in the uniform cylinder images, the relative system sensitivity reduced to approximately 4.1:1. A further reduction was seen when comparing the %SD in the spheres in the Jaszczak and the torso phantoms, at 3.1:1 and 2.6:1 at sphere to background ratio of 10-1, and 5:1, respectively. These results indicate that image noise may be a better measure to estimate relative system performance since it includes all factors contributing to the final image quality.