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Erschienen in: Abdominal Radiology 4/2012

01.08.2012

Tissue perfusion in pathologies of the pancreas: assessment using 128-slice computed tomography

verfasst von: L. Delrue, P. Blanckaert, D. Mertens, S. Van Meerbeeck, W. Ceelen, P. Duyck

Erschienen in: Abdominal Radiology | Ausgabe 4/2012

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Abstract

Purpose

Perfusion CT can provide information regarding blood perfusion and permeability in (tumor) tissues in a non-invasive manner. In this study, values of CT perfusion parameters in several pancreas pathologies were determined and compared to a control population.

Materials and methods

Dynamic 128-slice perfusion CT was performed in patients admitted to the radiology department between June 2010 and March 2011. Included pathologies were pancreatic adenocarcinoma, acute and chronic pancreatitis, neuroendocrine tumors, and (pseudo)cystic lesions. Parametric mappings of blood flow, blood volume, and permeability surface area product were generated.

Results

Blood flow and blood volume were significantly lower in acute and chronic pancreatitis compared to the control group. In the center of adenocarcinoma tumors, low blood flow and blood volume was observed, gradually increasing toward the tumor rim; perfusion values in pancreatic parenchyma adjacent to the tumor were not significantly different from the control population. In neuroendocrine tumors, significantly increased perfusion values were observed.

Conclusion

Compared to the control population, significant decreases in perfusion values were observed in all pancreatic pathologies under study, except in neuroendocrine tumors. Perfusion CT values can be used as an additional parameter to differentiate pancreatic pathologies.
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Metadaten
Titel
Tissue perfusion in pathologies of the pancreas: assessment using 128-slice computed tomography
verfasst von
L. Delrue
P. Blanckaert
D. Mertens
S. Van Meerbeeck
W. Ceelen
P. Duyck
Publikationsdatum
01.08.2012
Verlag
Springer-Verlag
Erschienen in
Abdominal Radiology / Ausgabe 4/2012
Print ISSN: 2366-004X
Elektronische ISSN: 2366-0058
DOI
https://doi.org/10.1007/s00261-011-9783-0

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