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N Fuin, O A Catalano, M Scipioni, L P W Canjels, D Izquierdo, S Pedemonte, and C Catana, Concurrent Respiratory Motion Correction of Abdominal PET and DCE-MRI using a Compressed Sensing Approach J Nucl Med, 2018

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Purpose: We present an approach for concurrent reconstruction of respiratory motion compensated abdominal DCE-MRI and PET data in an integrated PET/MR scanner. The MR and PET reconstructions share the same motion vector fields (MVFs) derived from radial MR data; the approach is robust to changes in respiratory pattern and do not increase the total acquisition time.

Methods: PET and DCE-MRI data of 12 oncological patients were simultaneously acquired for 6 minutes on an integrated PET/MR system after administration of 18 F-FDG and gadoterate meglumine. Golden-angle radial MR data were continuously acquired simultaneously with PET data and sorted into multiple motion phases based on a respiratory signal derived directly from the radial MR data. The resulting multidimensional dataset was reconstructed using a compressed sensing approach that exploits sparsity among respiratory phases. MVFs obtained using the full 6-minute (MC_6-min) and only the last 1 minute (MC_1-min) of data were incorporated into the PET reconstruction to obtain motion-corrected PET images and in an MR iterative reconstruction algorithm to produce a series of motion-corrected DCE-MRI images (moco_GRASP). The motion-correction methods (MC_6-min and MC_1-min) were evaluated by qualitative analysis of the MR images and quantitative analysis of maximum and mean standardized uptake values (SUVmax, SUVmean), contrast, signal-to-noise ratio (SNR) and lesion volume in the PET images.

Results: Motion corrected MC_6-min PET images demonstrated 30%, 23%, 34% and 18% increases in average SUVmax, SUVmean, contrast and SNR, and an average 40% reduction in lesion volume with respect to the non-motion-corrected PET images. The changes in these figures of merit were smaller but still substantial for the MC_1-min protocol: 19%, 10%, 15% and 9% increases in average SUVmax , SUVmean, contrast and SNR; and a 28% reduction in lesion volume. Moco_GRASP images were deemed of acceptable or better diagnostic image quality with respect to conventional breath hold cartesian VIBE acquisitions.

Conclusion: We presented a method that allows the simultaneous acquisition of respiratory motion-corrected diagnostic quality DCE-MRI and quantitatively accurate PET data in an integrated PET/MR scanner with negligible prolongation in acquisition time compared to routine PET/DCE-MRI protocols.