Non-invasive estimation of hepatic blood perfusion from H2 15O PET images using tissue-derived arterial and portal input functions

The liver is perfused through the portal vein and the hepatic artery. When its perfusion is assessed using positron emission tomography (PET) and (15)O-labeled water (H(2) (15)O), calculations require a dual blood input function (DIF), i.e., arterial and portal blood activity curves. The former can...

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Bibliographic Details
Published in:European journal of nuclear medicine and molecular imaging 2008-10, Vol.35 (10), p.1899-1911
Main Authors: Kudomi, N, Slimani, L, Järvisalo, M J, Kiss, J, Lautamäki, R, Naum, G A, Savunen, T, Knuuti, J, Iida, H, Nuutila, P, Iozzo, P
Format: Article
Language:English
Subjects:
Algorithms
Animals
Blood Flow Velocity - physiology
Hepatic Artery - physiology
Image Interpretation, Computer-Assisted - methods
Liver
Liver - blood supply
Liver - physiology
Nuclear medicine
Oxygen Radioisotopes
Positron-Emission Tomography - methods
Reproducibility of Results
Sensitivity and Specificity
Swine
Tomography
Veins & arteries
Water
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Summary:The liver is perfused through the portal vein and the hepatic artery. When its perfusion is assessed using positron emission tomography (PET) and (15)O-labeled water (H(2) (15)O), calculations require a dual blood input function (DIF), i.e., arterial and portal blood activity curves. The former can be generally obtained invasively, but blood withdrawal from the portal vein is not feasible in humans. The aim of the present study was to develop a new technique to estimate quantitative liver perfusion from H(2) (15)O PET images with a completely non-invasive approach. We studied normal pigs (n=14) in which arterial and portal blood tracer concentrations and Doppler ultrasonography flow rates were determined invasively to serve as reference measurements. Our technique consisted of using model DIF to create tissue model function and the latter method to simultaneously fit multiple liver time-activity curves from images. The parameters obtained reproduced the DIF. Simulation studies were performed to examine the magnitude of potential biases in the flow values and to optimize the extraction of multiple tissue curves from the image. The simulation showed that the error associated with assumed parameters was
ISSN:1619-7070
1619-7089
DOI:10.1007/s00259-008-0796-z