Evaluation of a novel elastic respiratory motion correction algorithm on quantification and image quality in abdominothoracic PET/CT

Our aim was to evaluate in phantom and patient studies a recently developed elastic motion deblurring (EMDB) technique that makes use of all the acquired PET data and compare its performance with other conventional techniques such as phase-based gating (PBG) and HDChest (HDC), both of which use fractions of the acquired data. Comparisons were made with respect to static whole-body (SWB) images with no motion correction. Methods: A phantom simulating respiratory motion of the thorax with lung lesions (5 spheres with internal diameters of 10–28 mm) was scanned with 0, 1, 2, and 3 cm of motion. Four reconstructions were performed: SWB, PBG, HDC, and EMDB. For PBG, the average (PBG _ave ) and maximum bin (PBG _max ) were used. To compare the reconstructions, the ratios of SUV _max , SUV _peak , and contrast-to-noise ratio (CNR) were calculated with respect to SWB. Additionally, 46 patients with lung or liver tumors less than 3 cm in diameter were studied. Measurements of SUV _max , SUV _peak , and CNR were made for 46 lung and 19 liver lesions. To evaluate image noise, the SUV SD was measured in healthy lung and liver tissue and in the phantom background. Finally, the subjective image quality of patient examinations was scored on a 5-point scale by 4 radiologists. Results: In the phantom, EMDB increased SUV _max and SUV _peak over SWB but to a lesser extent than the other reconstruction methodologies. The ratio of CNR with respect to SWB for EMDB, however, was higher than all other reconstructions (0.68 with EMDB . 0.54 with HDC . 0.41 with PBG _max . 0.31 with PBG _ave ). Similar results were seen in patient studies. SUV _max and SUV _peak were higher by, respectively, 19.3% and 11.1% with EMDB, 21.6% and 13.9% with HDC, 22.8% and 12.8% with PBG _ave , and 45.6% and 26.8% with PBG _max , compared with SWB. Lung and liver noise increased with EMDB by, respectively, 3% and 15%, with HDC by 35% and 56%, with PBG _ave by 100% and 170%, and with PBG _max by 146% and 219%. CNR increased in lung and liver tumors only with EMDB (18% and 13%, respectively) and decreased with HDC (−14% and −23%), PBG _ave (−39% and −63%), and PBG _max (−18% and −46%). The average radiologist scores of image quality were 4.0 ± 0.8 with SWB, 3.7 ± 1.0 with EMDB, 3.1 ± 1.0 with HDC, and 1.5 ± 0.7 with PBG. Conclusion: The EMDB algorithm had the least increase in image noise, improved lesion CNR, and had the highest overall image quality score.