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International Journal of Molecular ImagingVolume 2011 2011, Article ID 356730, 6 pages

Research Article

Department of Biomedical Engineering, The University of Virginia, Charlottesville, VA 22908, USA

Department of Physics, The University of Virginia, Charlottesville, Virginia 22908, USA

Department of Radiology and Medical Imaging, The University of VA, Charlottesville, VA 22908, USA

Department of Pediatrics, The University of VA, Charlottesville, Virginia 22908, USA

Received 17 June 2011; Revised 14 September 2011; Accepted 17 September 2011

Academic Editor: Adriaan Anthonius Lammertsma

Copyright © 2011 Landon W. Locke et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Dynamic FDG-PET imaging was used to study inflammation in lungs of mice following administration of a virulent strain of Klebsiella K. pneumoniae. Net whole-lung FDG influx constant was determined in a compartment model using an image-derived blood input function. Methods. K. pneumoniae ~3 x 10

CFU was intratracheally administered to six mice with 6 other mice serving as controls. Dynamic FDG-PET and X-Ray CT scans were acquired 24 hr after K. pneumoniae administration. The experimental lung time activity curves were fitted to a 3-compartment FDG model to obtain . Following imaging, lungs were excised and immunohistochemistry analysis was done to assess the relative presence of neutrophils and macrophages. Results. Mean for control and K. pneumoniae infected mice were versus  min

, respectively, revealing a 2.24 fold significant increase in the rate of FDG uptake in the infected lung. Immunohistochemistry revealed that cellular lung infiltrate was almost exclusively neutrophils. Parametric maps by Patlak analysis revealed heterogeneous inflammatory foci within infected lungs. Conclusion. The kinetics of FDG uptake in the lungs of mice can be noninvasively quantified by PET with a 3-compartment model approach based on an image-derived input function.





Autor: Landon W. Locke, Mark B. Williams, Karen D. Fairchild, Min Zhong, Bijoy K. Kundu, and Stuart S. Berr

Fuente: https://www.hindawi.com/



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