Assessing tumor physiology by dynamic contrast-enhanced near-infrared spectroscopy

Kyle Verdecchia; Jonathan Elliott; Mamadou Diop; Lisa Hoffman; Ting-Yim Lee; Keith St. Lawrence

doi:10.1117/12.2004774

25 March 2013 Assessing tumor physiology by dynamic contrast-enhanced near-infrared spectroscopy

Kyle Verdecchia, Jonathan Elliott, Mamadou Diop, Lisa Hoffman, Ting-Yim Lee, Keith St. Lawrence

Proceedings Volume 8578, Optical Tomography and Spectroscopy of Tissue X; 857823 (2013) https://doi.org/10.1117/12.2004774
Event: SPIE BiOS, 2013, San Francisco, California, United States

Abstract

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 (IRD_cxb). The DCE curves were analyzed using a kinetic model capable of extracting estimates of tumor blood flow (F), capillary transit time (t_c) 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 t_c 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 IRD_cxb, 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.

Citation Download Citation

Kyle Verdecchia, Jonathan Elliott, Mamadou Diop, Lisa Hoffman, Ting-Yim Lee, and Keith St. Lawrence "Assessing tumor physiology by dynamic contrast-enhanced near-infrared spectroscopy", Proc. SPIE 8578, Optical Tomography and Spectroscopy of Tissue X, 857823 (25 March 2013); https://doi.org/10.1117/12.2004774

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KEYWORDS

Tumors

Data modeling

Near infrared spectroscopy

Blood

Picosecond phenomena

Tissues

Data acquisition

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