Abstract

Gating of positron emission tomography images has been shown to reduce the motion effects, especially when imaging small targets, such as coronary plaques. However, the selection of optimal number of gates for gating remains a challenge. Selecting too high number of gates results in a loss of signal-to-noise ratio, while too low number of gates does remove only part of the motion. Here, we introduce a respiratory-cardiac motion model to determine the optimal number of respiratory and cardiac gates. We evaluate the model using a realistic heart phantom and data from 12 cardiac patients (47–77 years, 64.5 on average). To demonstrate the benefits of our model, we compared it with an existing respiratory model. Based on our study, the optimal number of gates was determined to be five respiratory and four cardiac gates in the phantom and patient studies. In the phantom study, the diameter of the most active hot spot was reduced by 24% in the dual gated images compared to non-gated images. In the patient study, the thickness of myocardium wall was reduced on average by 21%. In conclusion, the motion model can be used for estimating the optimal number of respiratory and cardiac gates for dual gating.

Details

Title
Estimation of optimal number of gates in dual gated 18F-FDG cardiac PET
Author
Klén, R 1 ; Teuho, J 1 ; Noponen, T 2 ; Thielemans, K 3 ; Hoppela, E 1 ; Lehtonen, E 4 ; Sipila, H T 1 ; Teräs, M 5 ; Knuuti, J 1 

 University of Turku, Turku PET Centre, Turku University Hospital, Turku, Finland (GRID:grid.1374.1) (ISNI:0000 0001 2097 1371) 
 Turku University Hospital, Division of Medical Imaging, Department of Medical Physics, Turku, Finland (GRID:grid.410552.7) (ISNI:0000 0004 0628 215X); Turku University Hospital, Department of Clinical Physiology and Nuclear Medicine, Turku, Finland (GRID:grid.410552.7) (ISNI:0000 0004 0628 215X) 
 University College London, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201); Hammersmith Imanet Ltd, London, UK (GRID:grid.83440.3b) 
 University of Turku, Department of Future Technologies, Turku, Finland (GRID:grid.1374.1) (ISNI:0000 0001 2097 1371) 
 Turku University Hospital, Division of Medical Imaging, Department of Medical Physics, Turku, Finland (GRID:grid.410552.7) (ISNI:0000 0004 0628 215X); University of Turku, Institute of Biomedicine, Turku, Finland (GRID:grid.1374.1) (ISNI:0000 0001 2097 1371) 
Publication year
2020
Publication date
2020
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2471556409
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.