List mode-driven cardiac and respiratory gating in PET
Florian Büther1, Mohammad Dawood, Lars Stegger
1Department of Nuclear Medicine, University of Münster, Münster, Germany. butherf@uni-muenster.de
Summary
This study shows that analyzing PET list mode data can effectively capture cardiac and respiratory motion, reducing image artifacts. This method offers a viable alternative to traditional gating techniques like ECG and video monitoring.
Area of Science:
- Medical Imaging
- Nuclear Medicine
- Cardiovascular Imaging
Background:
- Motion artifacts in Positron Emission Tomography (PET) imaging, particularly from cardiac and respiratory movements, degrade image quality and can lead to misinterpretations.
- Traditional gating methods, such as electrocardiography (ECG) for cardiac gating and video monitoring for respiratory gating, are used to mitigate these motion effects.
Purpose of the Study:
- To evaluate and compare different cardiac and respiratory gating methods for PET imaging.
- To assess the efficacy of methods based on inherent list mode data versus external signals (ECG, video).
Main Methods:
- Three gating methods were evaluated in 29 coronary artery disease patients undergoing list mode PET scans: ECG/video-based gating, a sensitivity-based list mode method, and a center-of-mass based list mode method.
- Gating accuracy was assessed using measures like left ventricular wall displacement and ejection fraction.
Main Results:
- All evaluated methods successfully reduced motion-induced blurring in PET images.
- The center-of-mass list mode method showed significantly greater left ventricular wall displacements compared to the sensitivity method.
- List mode-based cardiac gating using the center-of-mass method correlated well (r=0.95) with ECG-based gating for ejection fraction in patients with high (18)F-FDG uptake.
Conclusions:
- Analyzing PET list mode data frame-by-frame is a valid approach for obtaining gating signals.
- This internal list mode analysis provides an effective alternative to external gating signals like ECG and video tracking for reducing motion artifacts in PET scans.


