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Proceedings Paper

Feasibility of quantitative lung perfusion by 4D CT imaging by a new dynamic-scanning protocol in an animal model
Author(s): Yang Wang; Jonathan G. Goldin; Fereidoun G. Abtin; Matt Brown; Mike McNitt-Gray
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Paper Abstract

The purpose of this study is to test a new dynamic Perfusion-CT imaging protocol in an animal model and investigate the feasibility of quantifying perfusion of lung parenchyma to perform functional analysis from 4D CT image data. A novel perfusion-CT protocol was designed with 25 scanning time points: the first at baseline and 24 scans after a bolus injection of contrast material. Post-contrast CT scanning images were acquired with a high sampling rate before the first blood recirculation and then a relatively low sampling rate until 10 minutes after administrating contrast agent. Lower radiation techniques were used to keep the radiation dose to an acceptable level. 2 Yorkshire swine with pulmonary emboli underwent this perfusion- CT protocol at suspended end inspiration. The software tools were designed to measure the quantitative perfusion parameters (perfusion, permeability, relative blood volume, blood flow, wash-in & wash-out enhancement) of voxel or interesting area of lung. The perfusion values were calculated for further lung functional analysis and presented visually as contrast enhancement maps for the volume being examined. The results show increased CT temporal sampling rate provides the feasibility of quantifying lung function and evaluating the pulmonary emboli. Differences between areas with known perfusion defects and those without perfusion defects were observed. In conclusion, the techniques to calculate the lung perfusion on animal model have potential application in human lung functional analysis such as evaluation of functional effects of pulmonary embolism. With further study, these techniques might be applicable in human lung parenchyma characterization and possibly for lung nodule characterization.

Paper Details

Date Published: 12 March 2008
PDF: 8 pages
Proc. SPIE 6916, Medical Imaging 2008: Physiology, Function, and Structure from Medical Images, 69161H (12 March 2008); doi: 10.1117/12.772720
Show Author Affiliations
Yang Wang, David Geffen School of Medicine at Univ. of California, Los Angeles (United States)
Jonathan G. Goldin, David Geffen School of Medicine at Univ. of California, Los Angeles (United States)
Fereidoun G. Abtin, David Geffen School of Medicine at Univ. of California, Los Angeles (United States)
Matt Brown, David Geffen School of Medicine at Univ. of California, Los Angeles (United States)
Mike McNitt-Gray, David Geffen School of Medicine at Univ. of California, Los Angeles (United States)


Published in SPIE Proceedings Vol. 6916:
Medical Imaging 2008: Physiology, Function, and Structure from Medical Images
Xiaoping P. Hu; Anne V. Clough, Editor(s)

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