Brain MRI Coil Attenuation Map Processing for the GE SIGNA PET/MR: Impact on PET Image Quantification and Uniformity

Attenuation correction of brain MRI coils used on PET/MR systems can be prone to error emanating from artifacts in CT-based coil attenuation maps. In this study editing was applied to brain-coil CT images to reduce the impact of metal-induced artifacts on attenuation correction for the GE SIGNA PET/MR. Methods for global and material-specific transformation of coil CT images to linear attenuation coefficient (LAC) maps were evaluated. In addition, CT-based attenuation maps were generated for the coil mirrors and four levels of smoothing were applied to the attenuation maps. A uniform phantom experiment was performed to assess absolute quantification, and both axial and transaxial image uniformity. For the three coils tested, the edited CT attenuation maps improved absolute quantification (mean absolute error 1.2% vs. 7.2% in the central axial 15 cm) and axial uniformity by up to 60% (33% on average) compared to the vendor-supplied attenuation maps, although transaxial uniformity deteriorated by up to 38% (16% on average). No single CT-to-LAC conversion method was found to be optimal across coils and performance metrics. Overall, material-specific CT-to-LAC conversion performed best for image quantification (0.6% vs. 1.5%), whereas global transformation narrowly ranked best for uniformity (1.69% vs. 1.71%). The inclusion of the mirror marginally improved axial uniformity in the majority of cases, but also slightly degraded transaxial uniformity. The impact of changing smoothing was minor, with the system default setting of 10 mm FWHM Gaussian producing the best results overall.