An iterative image-based inter-frame motion compensation method for dynamic brain PET imaging

Author(s):  
Tao Sun ◽  
Yaping Wu ◽  
Yan Bai ◽  
Zhenguo Wang ◽  
Chushu Shen ◽  
...  

Abstract As a non-invasive imaging tool, Positron Emission Tomography (PET) plays an important role in brain science and disease research. Dynamic acquisition is one way of brain PET imaging. Its wide application in clinical research has often been hindered by practical challenges, such as patient involuntary movement, which could degrade both image quality and the accuracy of the quantification. This is even more obvious in scans of patients with neurodegeneration or mental disorders. Conventional motion compensation methods were either based on images or raw measured data, were shown to be able to reduce the effect of motion on the image quality. As for a dynamic PET scan, motion compensation can be challenging as tracer kinetics and relatively high noise can be present in dynamic frames. In this work, we propose an image-based inter-frame motion compensation approach specifically designed for dynamic brain PET imaging. Our method has an iterative implementation that only requires reconstructed images, based on which the inter-frame subject movement can be estimated and compensated. The method utilized tracer-specific kinetic modelling and can deal with simple and complex movement patterns. The synthesized phantom study showed that the proposed method can compensate for the simulated motion in scans with 18F-FDG, 18F-Fallypride and 18F-AV45. Fifteen dynamic 18F-FDG patient scans with motion artifacts were also processed. The quality of the recovered image was superior to the one of the non-corrected images and the corrected images with other image-based methods. The proposed method enables retrospective image quality control for dynamic brain PET imaging, hence facilitates the applications of dynamic PET in clinics and research.

2016 ◽  
Vol 61 (19) ◽  
pp. 7074-7091 ◽  
Author(s):  
Matthew G Spangler-Bickell ◽  
Lin Zhou ◽  
Andre Z Kyme ◽  
Bart De Laat ◽  
Roger R Fulton ◽  
...  

2004 ◽  
Vol 1265 ◽  
pp. 255-261 ◽  
Author(s):  
Hiroshi Toyama ◽  
Masanori Ichise ◽  
Jeih-San Liow ◽  
Kendra J Modell ◽  
Douglass C Vines ◽  
...  

2019 ◽  
Vol 23 (6) ◽  
pp. 2576-2582 ◽  
Author(s):  
Elisa Roccia ◽  
Arthur Mikhno ◽  
R. Todd Ogden ◽  
J. John Mann ◽  
Andrew F. Laine ◽  
...  

2020 ◽  
Vol 41 (12) ◽  
pp. 1265-1274
Author(s):  
Otto M. Henriksen ◽  
Søren Holm ◽  
Lisbeth Marner ◽  
Ian Law

NeuroImage ◽  
2014 ◽  
Vol 91 ◽  
pp. 129-137 ◽  
Author(s):  
Chuan Huang ◽  
Jerome L. Ackerman ◽  
Yoann Petibon ◽  
Marc D. Normandin ◽  
Thomas J. Brady ◽  
...  

2005 ◽  
Vol 90 (3) ◽  
pp. 1752-1759 ◽  
Author(s):  
Alessandra Bertoldo ◽  
Julie Price ◽  
Chet Mathis ◽  
Scott Mason ◽  
Daniel Holt ◽  
...  

Insulin-stimulated glucose transport in skeletal muscle is regarded as a key determinant of insulin sensitivity, yet isolation of this step for quantification in human studies is a methodological challenge. One notable approach is physiological modeling of dynamic positron emission tomography (PET) imaging using 2-[18-fluoro]2-deoxyglucose ([18F]FDG); however, this has a potential limitation in that deoxyglucose undergoes phosphorylation subsequent to transport, complicating separate estimations of these steps. In the current study we explored the use of dynamic PET imaging of [11C]3-O-methylglucose ([11C]3-OMG), a glucose analog that is limited to bidirectional glucose transport. Seventeen lean healthy volunteers with normal insulin sensitivity participated; eight had imaging during basal conditions, and nine had imaging during euglycemic insulin infusion at 30 mU/min·m2. Dynamic PET imaging of calf muscles was conducted for 90 min after the injection of [11C]3-OMG. Spectral analysis of tissue activity indicated that a model configuration of two reversible compartments gave the strongest statistical fit to the kinetic pattern. Accordingly, and consistent with the structure of a model previously used for [18F]FDG, a two-compartment model was applied. Consistent with prior [18F]FDG findings, insulin was found to have minimal effect on the rate constant for movement of [11C]3-OMG from plasma to tissue interstitium. However, during insulin infusion, a robust and highly significant increase was observed in the kinetics of inward glucose transport; this and the estimated tissue distribution volume for [11C]3-OMG increased 6-fold compared with basal conditions. We conclude that dynamic PET imaging of [11C]3-OMG offers a novel quantitative approach that is both chemically specific and tissue specific for in vivo assessment of glucose transport in human skeletal muscle.


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