Clinical comparison of the positron emission tracking (PeTrack) algorithm with the real‐time position management system for respiratory gating in cardiac positron emission tomography

Purpose A data‐driven motion tracking system was developed for respiratory gating in positron emission tomography (PET)/computed tomography (CT) studies. The positron emission tracking system (PeTrack) estimates the position of a low‐activity fiducial marker placed on the patient during imaging. The aim of this study was to compare the performance of PeTrack against that of the real‐time position management (RPM) system as applied to respiratory gating in cardiac PET/CT studies. Methods The list‐mode data of 35 patients that were referred for 82 Rb myocardial perfusion studies were retrospectively processed with PeTrack to generate respiratory motion signals and triggers. Fifty acquisitions from the initial cohort, conducted under physiologic rest and stress, were considered for analysis. Respiratory‐gated reconstructions were performed using reconstruction software provided by the vendor. The respiratory signals and triggers of the gating systems were compared using quantitative measurements of the respiratory signal correlation, median, and interquartiles range (IQR) of observed respiratory rates and the relative frequencies of respiratory cycle outliers. Quantitative measurements of left‐ventricular wall thicknesses and motion due to respiration were also compared. Real‐time position management signals were also retrospectively processed using the trigger detection method of PeTrack for a third comparator (“RPMretro”) that allowed direct comparison of the motion tracking quality independently of differences in the trigger detection methods. The comparison of PeTrack to the original RPM data represent a practical comparison of the two systems, whereas that of PeTrack and RPMretro represents an equal comparison of the two. Nongated images were also reconstructed to provide reference left‐ventricular wall thicknesses. LV wall thickness and motion measurements were repeated for a subset of cases with motion ≥7 mm as image artifacts were expected to be more severe in these cases. Results A significant correlation ( P  < 0.05) was observed between the RPM and PeTrack respiratory signals in 45/50 acquisitions; the mean correlation coefficient was 0.43. Similar results were found between PeTrack and RPMretro. No significant difference was observed between the RPM and PeTrack with respect to median respiratory rates and the percentage of respiratory cycles outliers. Respiratory rate variability (IQR) was significantly higher with PeTrack vs RPM ( P  = 0.002) and RPMretro ( P  = 0.04). Both PeTrack and RPM had a significant increase in the percentage of respiratory rate outliers compared to RPMretro ( P  < 0.001 and P  = 0.001, respectively). All methods indicated significant differences in LV thickness compared to nongated images ( P  < 0.02). LV thickness was significantly larger for PeTrack compared to RPMretro in the highest motion subset ( P  = 0.009). Images gated with RPMretro showed significant increases in motion compared to both PeTrack ( P  < 0.001) and prospective RPM ( P  = 0.002). In the subset of highest motion cases, the difference between RPM and RPMretro was no longer present. Conclusions The data‐driven PeTrack algorithm performed similarly to the well‐established RPM system for respiratory gating of 82 Rb cardiac perfusion PET/CT studies. Real‐time position management performance improved after retrospective processing and led to enhanced performance compared to both PeTrack and prospective RPM. With further development PeTrack has the potential to reduce the need for ancillary hardware systems to monitor respiratory motion.