Multi-bed elastic motion correction for whole body MR-PET

Single bed motion correction algorithms are increasingly being used to model and compensate for the respiratory motion in clinical PET images. In this work we develop a multi-bed elastic motion correction algorithm and workflow for the MR-PET (Siemens biograph mMR) scanner. For validation of the proposed multi-bed motion algorithm we performed multi-bed NCAT phantom simulations as well as physical multi-bed rod phantom studies using the clinical scanner. The NCAT and rod phantoms were used as the motion vectors are exactly know and any bias in the final reconstructed image can be easily identified. Finally four patient scans were performed using a two bed protocol. A self-gated radial VIBE MRI sequence was used to generate the gated MR images. The motion vectors were calculated from the gated MR images using demons algorithm. In the mMR system the clinical PET data can be acquired simultaneously along with the MR diagnostic scans of the patient. The list-mode PET data for each bed is divided into pre-determined frames based on the amplitude of the respiratory waveform. The mu-maps corresponding to each frame was generated and used to reconstruct each PET frame separately. A post reconstruction motion correction algorithm was used to compensate for the motion in the different frame of the multi-bed acquisition. Each frame of the multi-bed reconstructed images was warped to the whole body reference image taking into account the acquisition time of each frame as well as the possibility of miss-match in the motion vectors between the beds. The phantom as well as patient studies were motion compensated to the reference image and found to give a faithful whole body reconstruction.