Abstract 4211: <i>In vivo</i> fluorescence kinetic imaging for improved contrast and studies of temporal and quantitative biodistribution (2010)

Abstract In vivo fluorescence imaging has added an easy and economical modality to the rapidly growing field of molecular imaging. It offers the possibility to perform experiments analogous to bioluminescence imaging through fluorescent proteins, but at longer and more efficient wavelengths. A further distinction is the translational and research aspects enabling the imaging of fluorophore-labelled biologics (e.g., antibodies, peptides, siRNA) and activatable reagents. One unique aspect limiting the sensitivity of in vivo fluorescence methodologies is the confounding effect of tissue autofluorescence, which can be addressed through the proper use of spectral imaging [1,2]. However, like other molecular imaging modalities, reagent-based in vivo fluorescence imaging also has to contend with sensitivity and contrast problems due to non-specific signals and long wash-out times, both limiting the detection of specifically bound reagent and preventing accurate determination of uptake rates. To address this issue, we have developed a kinetic imaging modality, Dynamic Contrast Enhancement, or DyCETM, that combines rapid imaging (up to 15 frames/sec monochrome or 10 sec/frame multispectrally) with an advanced data processing methodology. When combined, these allow determination of (1) the rates of change of the intensity of the fluorophore in each pixel of the image and (2) the rate of uptake and wash-out in the animal. By utilizing the uptake and wash-out rate information, a much higher contrast image of the accumulating fluorophore can be obtained in a much shorter period of time (minutes and hours vs. days). In addition, body compartment data can provide information on the temporal distributions of a fluorescent agent during the experiment and can act as inputs for rate-of-change or body compartment models. This broadly applicable temporal-biodistribution methodology can be used, for example, to differentiate between the rate of liver uptake vs. the rate of tumor uptake and quantitate each signal relative to general body and/or bladder distribution. This information can then be combined with multispectral imaging and used to quantitate the biodistribution of multiple fluorophores simultaneously, each without interference from autofluorescence. When combined with models of peripheral, tumor, blood and wash-out (bladder) distributions, this kinetic imaging data can be transformed into a physiologically based pharmacokinetic model of agent distribution that provides an estimate of the pK values between the various compartments. Potentially such a method can also be used to establish optimal drug treatment schedules aiding drug discovery and development. [1] Levenson, Mansfield, Cytometry A. 2006 Aug; 69(8):748-58. [2] Tam et al., Mol Imaging. 2007 Oct-Dec;6(4):269-76. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4211.