Table of Contents
International Journal of Molecular Imaging
Volume 2011, Article ID 185083, 12 pages
http://dx.doi.org/10.1155/2011/185083
Research Article

Patient-Specific Method of Generating Parametric Maps of Patlak without Blood Sampling or Metabolite Correction: A Feasibility Study

1UCSF Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143-0628, USA
2Division of Nuclear Medicine, Radiological Associates of Sacramento, Sacramento, CA 95815, USA
3UCSF Department of Radiation Oncology, University of California, San Francisco, CA 94115-1708, USA
4UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA 94143-0875, USA
5UC Berkeley & UCSF Graduate Program in Bioengineering, Berkeley and San Francisco, CA 94158-2330, USA

Received 1 May 2011; Accepted 23 June 2011

Academic Editor: Oliver C. Y. Wong

Copyright © 2011 George A. Sayre 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

Currently, kinetic analyses using dynamic positron emission tomography (PET) experience very limited use despite their potential for improving quantitative accuracy in several clinical and research applications. For targeted volume applications, such as radiation treatment planning, treatment monitoring, and cerebral metabolic studies, the key to implementation of these methods is the determination of an arterial input function, which can include time-consuming analysis of blood samples for metabolite correction. Targeted kinetic applications would become practical for the clinic if blood sampling and metabolite correction could be avoided. To this end, we developed a novel method (Patlak-) of generating parametric maps that is identical to Patlak (within a global scalar multiple) but does not require the determination of the arterial input function or metabolite correction. In this initial study, we show that Patlak- (a) mimics Patlak images in terms of visual assessment and target-to-background (TB) ratios of regions of elevated uptake, (b) has higher visual contrast and (generally) better image quality than SUV, and (c) may have an important role in improving radiotherapy planning, therapy monitoring, and neurometabolism studies.