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Computational and Mathematical Methods in Medicine
Volume 2015 (2015), Article ID 415923, 11 pages
http://dx.doi.org/10.1155/2015/415923
Review Article

PET-Specific Parameters and Radiotracers in Theoretical Tumour Modelling

1School of Chemistry & Physics, University of Adelaide, Adelaide, SA 5000, Australia
2Department of Medical Physics, Royal Adelaide Hospital, Adelaide, SA 5000, Australia
3Faculty of Science, University of Oradea, 410087 Oradea, Romania

Received 17 July 2014; Accepted 15 September 2014

Academic Editor: Iuliana Toma-Dasu

Copyright © 2015 Matthew Jennings 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

The innovation of computational techniques serves as an important step toward optimized, patient-specific management of cancer. In particular, in silico simulation of tumour growth and treatment response may eventually yield accurate information on disease progression, enhance the quality of cancer treatment, and explain why certain therapies are effective where others are not. In silico modelling is demonstrated to considerably benefit from information obtainable with PET and PET/CT. In particular, models have successfully integrated tumour glucose metabolism, cell proliferation, and cell oxygenation from multiple tracers in order to simulate tumour behaviour. With the development of novel radiotracers to image additional tumour phenomena, such as pH and gene expression, the value of PET and PET/CT data for use in tumour models will continue to grow. In this work, the use of PET and PET/CT information in in silico tumour models is reviewed. The various parameters that can be obtained using PET and PET/CT are detailed, as well as the radiotracers that may be used for this purpose, their utility, and limitations. The biophysical measures used to quantify PET and PET/CT data are also described. Finally, a list of in silico models that incorporate PET and/or PET/CT data is provided and reviewed.