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Computational and Mathematical Methods in Medicine
Volume 2013 (2013), Article ID 793142, 10 pages
http://dx.doi.org/10.1155/2013/793142
Research Article

Estimate of FDG Excretion by means of Compartmental Analysis and Ant Colony Optimization of Nuclear Medicine Data

1Dipartimento di Matematica, Università di Genova, Via Dodecaneso 35, 16146 Genova, Italy
2CNR—SPIN, Via Dodecaneso 33, 16146 Genova, Italy
3Dipartimento di Ingegneria Navale, Elettrica, Elettronica e delle Telecomunicazioni, Università di Genova, Via Opera Pia 11, 16145 Genova, Italy
4IRCCS San Martino IST, Largo Rosanna Benzi 10, 16132 Genova, Italy
5Dipartimento di Scienze della Salute, Università di Genova, Largo Rosanna Benzi 10, 16132 Genova, Italy

Received 30 May 2013; Revised 7 August 2013; Accepted 14 August 2013

Academic Editor: William Crum

Copyright © 2013 Sara Garbarino 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

[18F]fluoro-2-deoxy-D-glucose (FDG) is one of the most utilized tracers for positron emission tomography (PET) applications in oncology. FDG-PET relies on higher glycolytic activity in tumors compared to normal structures as the basis of image contrast. As a glucose analog, FDG is transported into malignant cells which typically exhibit an increased radioactivity. However, different from glucose, FDG is not reabsorbed by the renal system and is excreted to the bladder. The present paper describes a novel computational method for the quantitative assessment of this excretion process. The method is based on a compartmental analysis of FDG-PET data in which the excretion process is explicitly accounted for by the bladder compartment and on the application of an ant colony optimization (ACO) algorithm for the determination of the tracer coefficients describing the FDG transport effectiveness. The validation of this approach is performed by means of both synthetic data and real measurements acquired by a PET device for small animals (micro-PET). Possible oncological applications of the results are discussed in the final section.