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A statistical study of the factors influencing the extent of respiratory motion blur in PET imaging.

Authors :
Xu Q
Xie K
Yuan K
Yu L
Wang W
Ye D
Source :
Computers in biology and medicine [Comput Biol Med] 2012 Jan; Vol. 42 (1), pp. 8-18. Date of Electronic Publication: 2011 Nov 10.
Publication Year :
2012

Abstract

Respiratory motion results in significant motion blur in thoracic and abdomen PET imaging. The extent of respiratory motion blur is mainly correlated with breathing amplitude, tumor size and location. In this paper we introduce a statistical study to quantitatively show the factors influencing the extent of respiratory motion blur in thoracic PET images. The study is centered on two regression models, one is linked with motion blur induced loss of mean intensity(LMI), tumor motion magnitude and tumor size, and another is to investigate the influence of tumor location, patient gender and patient height on tumor motion magnitude. We use the blur identification and image restoration technique to estimate the tumor motion and compute the LMI. The regression model was validated by simulation and phantom data before extended to 39 cases of clinical lung tumor PET images corrupted with blurring artifact. Results show that the motion magnitude of lung tumor during breathing is 10.9±3.7mm in transaxial plane, and it is significantly greater in lower lung lobes than in upper lobes. The LMI is 7.1±2.4% in the region of interest (ROI) above 40% of the image's maximum intensity. The least-square estimate of regression equations demonstrates that LMI is proportional to tumor motion magnitude and is inversely proportional to tumor size; the two factors play the same role in determining the extent of respiratory motion blur in thoraco-abdominal PET imaging. The location of tumor was shown as the major factor determining its motion magnitude, while the influencing of patient gender and height on tumor motion was not shown significant.<br /> (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1879-0534
Volume :
42
Issue :
1
Database :
MEDLINE
Journal :
Computers in biology and medicine
Publication Type :
Academic Journal
Accession number :
22078500
Full Text :
https://doi.org/10.1016/j.compbiomed.2011.10.002