List Mode-Driven Cardiac and Respiratory Gating in PET

Gating methods acquiring biosignals (such as electrocardiography [ECG] and respiration) during PET enable one to reduce motion effects that potentially lead to image blurring and artifacts. This study evaluated different cardiac and respiratory gating methods: one based on ECG signals for cardiac gating and video signals for respiratory gating; 2 others based on measured inherent list mode events. Methods: Twenty-nine patients with coronary artery disease underwent a 20-min ECG-gated single-bed list mode PET scan of the heart. Of these, 17 were monitored by a video camera registering a marker on the patient's abdomen, thus capturing the respiratory motion for PET gating (video method). Additionally, respiratory and cardiac gating information was deduced without auxiliary measurements by dividing the list mode stream in 50-ms frames and then either determining the number of coincidences (sensitivity method) or computing the axial center of mass and SD of the measured counting rates in the same frames (center-of-mass method). The gated datasets (respiratory and cardiac gating) were reconstructed without attenuation correction. Measured wall thicknesses, maximum displacement of the left ventricular wall, and ejection fraction served as measures of the exactness of gating. Results: All methods successfully captured respiratory motion and significantly decreased motion-induced blurring in the gated images. The center-of-mass method resulted in significantly larger left ventricular wall displacements than did the sensitivity method (P < 0.02); other differences were nonsignificant. List mode-based cardiac gating was found to work well for patients with high F-18-FDG uptake when the center-of-mass method was used, leading to an ejection fraction correlation coefficient of r = 0.95 as compared with ECG-based gating. However, the sensitivity method did not always result in valid cardiac gating information, even in patients with high 18F-FDG uptake. Conclusion: Our study demonstrated that valid gating signals during PET scans cannot be obtained only by tracking the external motion or applying an ECG but also by simply analyzing the PET list mode stream on a frame-by-frame basis.