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BioMed Research International
Volume 2015, Article ID 120749, 6 pages
http://dx.doi.org/10.1155/2015/120749
Research Article

CT Perfusion Characteristics Identify Metastatic Sites in Liver

1Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
2Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA

Received 4 April 2015; Revised 29 May 2015; Accepted 7 June 2015

Academic Editor: Franco M. Buonaguro

Copyright © 2015 Yuan Wang 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

Tissue perfusion plays a critical role in oncology because growth and migration of cancerous cells require proliferation of new blood vessels through the process of tumor angiogenesis. Computed tomography (CT) perfusion is an emerging functional imaging modality that measures tissue perfusion through dynamic CT scanning following intravenous administration of contrast medium. This noninvasive technique provides a quantitative basis for assessing tumor angiogenesis. CT perfusion has been utilized on a variety of organs including lung, prostate, liver, and brain, with promising results in cancer diagnosis, disease prognostication, prediction, and treatment monitoring. In this paper, we focus on assessing the extent to which CT perfusion characteristics can be used to discriminate liver metastases from neuroendocrine tumors from normal liver tissues. The neuroendocrine liver metastases were analyzed by distributed parameter modeling to yield tissue blood flow (BF), blood volume (BV), mean transit time (MTT), permeability (PS), and hepatic arterial fraction (HAF), for tumor and normal liver. The result reveals the potential of CT perfusion as a tool for constructing biomarkers from features of the hepatic vasculature for guiding cancer detection, prognostication, and treatment selection.