Assessing tumor physiology by dynamic contrast-enhanced near-infrared spectroscopy
Author(s) -
Kyle Verdecchia,
Jonathan T. Elliott,
Mamadou Diop,
Lisa Hoffman,
TingYim Lee,
Keith St. Lawrence
Publication year - 2013
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.2004774
Subject(s) - indocyanine green , chemistry , dynamic contrast , contrast (vision) , blood flow , biomedical engineering , biophysics , pathology , computer science , biology , medicine , radiology , artificial intelligence , magnetic resonance imaging
The purpose of this study was to develop a dynamic contrast-enhanced (DCE) near-infrared spectroscopy (NIRS) technique to characterize tumor physiology. Dynamic data were acquired using two contrast agents of different molecular weights, indocyanine green (ICG) and IRDye 800CW carboxylate (IRDcxb). The DCE curves were analyzed using a kinetic model capable of extracting estimates of tumor blood flow (F), capillary transit time (tc) and the amount of dye that leaked into the extravascular space (EVS) – characterized by the extraction fraction (E). Data were acquired from five nude rats with tumor xenografts (>10mm) implanted in the neck. Four DCE-NIR datasets (two from each contrast agent) were acquired for each rat. The dye concentration curve in arterial blood, which is required to quantify the model parameters, was measured non-invasively by dye densitometry. A modification to the kinetic model to characterize tc as a distribution of possible values, rather than finite, improved the fit of acquired tumor concentration curves, resulting in more reliable estimates. This modified kinetic model identified a difference between the extracted fraction of IRDcxb, 15 ± 6 %, and ICG, 1.6 ± 0.6 %, in the tumor, which can be explained by the difference in molecular weight: 67 kDa for ICG since it binds to albumin and 1.17 kDa for IRD. This study demonstrates the ability of DCENIRS to quantify tumor physiology. The next step is to adapt this approach with a dual-receptor approach.
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