We present a novel technique for accurate whole body attenuation correction (AC) in the presence of metallic endoprosthesis, on integrated non-time-of-flight (non-TOF) PET/MR imaging scanners. The proposed implant PET-based attenuation map completion (IPAC) method performs a joint reconstruction of radioactivity and attenuation from the emission data to determine the position, shape and linear attenuation coefficient (LAC) of metallic implants. Methods: The initial estimate of the attenuation map is obtained using the MR Dixon-method currently available on the Siemens Biograph mMR scanner. The attenuation coefficients in the area of the MR image subjected to metal susceptibility artifacts are then reconstructed from the PET emission data using the IPAC algorithm. The method was tested on eleven subjects presenting thirteen different metallic implants, who underwent computed tomography (CT) and PET/MR scans. Relative mean LACs and Dice Similarity Coefficients (DSCs) were calculated in order to determine the accuracy of the reconstructed attenuation values and the shape of the metal implant, respectively. The reconstructed PET images were compared to those obtained using the reference CT-based approach and the Dixon-based method. Absolute relative-change (aRC) images were generated in each case and voxel-based analyses were performed. Results: The error in implant LAC estimation, using the proposed IPAC algorithm, was 15.7±7.8%, which was significantly smaller than the Dixon- (100%) and CT- (39%) derived values. A mean DSC of 73±9% was obtained when comparing the IPAC- to the CT-derived implant shape. The voxel-based analysis of the reconstructed PET images revealed quantification errors (aRC) of 13.2±22.1% for the IPAC- with respect to CT-corrected images. The Dixon-based method performed substantially worse with a mean aRC of 23.1±38.4%. Conclusion: We have presented a non-TOF emission-based approach for estimating the attenuation map in the presence of metallic implants, to be used for whole body AC in integrated PET/MR scanners. The GPU implementation of the algorithm will be included in the open-source reconstruction toolbox Occiput.io.
- Journal Article