Takato Inomata1, Shoichi Watanuki2, Hayato Odagiri3, Takeyuki Nambu4, Nicolas A Karakatsanis5, Hiroshi Ito4,6, Hiroshi Watabe7, Manabu Tashiro2, Miho Shidahara8,9. 1. Division of Medical Physics, Tohoku University Graduate School of Medicine, Sendai, Japan. 2. Division of Cyclotron Nuclear Medicine, Cyclotron and Radioisotope Center, Tohoku University, Sendai, Japan. 3. Department of Diagnostic Radiology, Tohoku University Hospital, Sendai, Japan. 4. Advanced Clinical Research Center, Fukushima Medical University, Fukushima, Japan. 5. Division of Radiopharmaceutical Sciences, Department of Radiology, Weill Cornell Medical College, Cornell University, Ithaca, USA. 6. Department of Radiology and Nuclear Medicine, Fukushima Medical University, Fukushima, Japan. 7. Division of Radiation Protection and Safety Control, Cyclotron and Radioisotope Center, Tohoku University, Sendai, Japan. 8. Division of Cyclotron Nuclear Medicine, Cyclotron and Radioisotope Center, Tohoku University, Sendai, Japan. miho.shidahara@qse.tohoku.ac.jp. 9. Division of Applied Quantum Medical Engineering, Department of Quantum Science and Energy Engineering, Graduate School of Engineering, Tohoku University, Sendai, Japan. miho.shidahara@qse.tohoku.ac.jp.
Abstract
PURPOSES: Subject's motion during brain PET scan degrades spatial resolution and quantification of PET images. To suppress these effects, rigid-body motion correction systems have been installed in commercial PET scanners. In this study, we systematically compare the accuracy of motion correction among 3 commercial PET scanners using a reproducible experimental acquisition protocol. METHODS: A cylindrical phantom with two 22Na point sources was placed on a customized base to enable two types of motion, 5° yaw and 15° pitch rotations. Repetitive PET scans (5 min × 5 times) were performed at rest and under 2 motion conditions using 3 clinical PET scanners: the Eminence STARGATE G/L PET/CT (STARGATE) (Shimadzu Corp.), the SET-3000 B/X PET (SET-3000) (Shimadzu Corp.), and the Biograph mMR PET/MR (mMR) (Siemens Healthcare) systems. For STARGATE and SET-3000, the Polaris Vicra (Northern Digital Inc.) optical tracking system was used for frame-by-frame motion correction. For Biograph mMR, sequential MR images were simultaneously acquired with PET and used for LOR-based motion correction. All PET images were reconstructed by FBP algorithm with 1 × 1 mm pixel size. To evaluate the accuracy of motion correction, FWHMs and spherical ROI values were analyzed. RESULTS: The percent differences (%diff) in averaged FWHMs of point sources at 4 cm off-center between motion-corrected and static images were 0.77 ± 0.16 (STARGATE), 2.4 ± 0.34 (SET-3000), and 11 ± 1.0% (mMR) for a 5° yaw and 2.3 ± 0.37 (STARGATE) and 1.1 ± 0.60 (SET-3000) for a 15° pitch respectively. The averaged %diff between ROI values of motion-corrected images and static images were less than 2.0% for all conditions. CONCLUSIONS: In this study, we proposed a reproducible experimental framework to allow the systematic validation and comparison of multiple motion tracking and correction methodologies among different PET/CT and PET/MR commercial systems. Our proposed validation platform may be useful for future studies evaluating state-of-the-art motion correction strategies in clinical PET imaging.
PURPOSES: Subject's motion during brain PET scan degrades spatial resolution and quantification of PET images. To suppress these effects, rigid-body motion correction systems have been installed in commercial PET scanners. In this study, we systematically compare the accuracy of motion correction among 3 commercial PET scanners using a reproducible experimental acquisition protocol. METHODS: A cylindrical phantom with two 22Na point sources was placed on a customized base to enable two types of motion, 5° yaw and 15° pitch rotations. Repetitive PET scans (5 min × 5 times) were performed at rest and under 2 motion conditions using 3 clinical PET scanners: the Eminence STARGATE G/L PET/CT (STARGATE) (Shimadzu Corp.), the SET-3000 B/X PET (SET-3000) (Shimadzu Corp.), and the Biograph mMR PET/MR (mMR) (Siemens Healthcare) systems. For STARGATE and SET-3000, the Polaris Vicra (Northern Digital Inc.) optical tracking system was used for frame-by-frame motion correction. For Biograph mMR, sequential MR images were simultaneously acquired with PET and used for LOR-based motion correction. All PET images were reconstructed by FBP algorithm with 1 × 1 mm pixel size. To evaluate the accuracy of motion correction, FWHMs and spherical ROI values were analyzed. RESULTS: The percent differences (%diff) in averaged FWHMs of point sources at 4 cm off-center between motion-corrected and static images were 0.77 ± 0.16 (STARGATE), 2.4 ± 0.34 (SET-3000), and 11 ± 1.0% (mMR) for a 5° yaw and 2.3 ± 0.37 (STARGATE) and 1.1 ± 0.60 (SET-3000) for a 15° pitch respectively. The averaged %diff between ROI values of motion-corrected images and static images were less than 2.0% for all conditions. CONCLUSIONS: In this study, we proposed a reproducible experimental framework to allow the systematic validation and comparison of multiple motion tracking and correction methodologies among different PET/CT and PET/MR commercial systems. Our proposed validation platform may be useful for future studies evaluating state-of-the-art motion correction strategies in clinical PET imaging.
Authors: Eric Einspänner; Thies H Jochimsen; Osama Sabri; Bernhard Sattler; Johanna Harries; Andreas Melzer; Michael Unger; Richard Brown; Kris Thielemans Journal: EJNMMI Phys Date: 2022-03-03