Quantification of tissue distribution and therapeutic response using paired agent imaging in a chicken chorioallantoic membrane xenograft assay (Conference Presentation)

Kimberley S. Samkoe; Lei G. Wang; Jesse R. Korber; Summer L. Gibbs; Kenneth M. Tichauer

doi:10.1117/12.2547100

20 April 2020 Quantification of tissue distribution and therapeutic response using paired agent imaging in a chicken chorioallantoic membrane xenograft assay (Conference Presentation)

Kimberley S. Samkoe, Lei G. Wang, Jesse R. Korber, Summer L. Gibbs, Kenneth M. Tichauer

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Proceedings Volume 11219, Visualizing and Quantifying Drug Distribution in Tissue IV; 112190E (2020) https://doi.org/10.1117/12.2547100
Event: SPIE BiOS, 2020, San Francisco, California, United States

Abstract

Intracellular Paired-Agent Imaging (iPAI) quantifies intracellular drug targets using fluorescently-labeled small molecule imaging agents. iPAI has the potential to predict therapeutic response for individual patients but requires a patient derived xenograft (PDX) model that accurately mimics in vivo tumor heterogeneity yet is easily accessible for intravenous drug administration and rapid image collection. The chicken embryo chorioallantoic membrane (CAM) provides an intermediate, cost-effective model that provides vascularized, in vivo tumors in a matter of days (typically ~72 h) from implantation. Here, we investigate the implantation of thin (< 1 mm) cross-sectional slices (1-2 cm) of freshly excised tumor tissues from mouse xenografts. Multispectral iPAI will be performed to quantify the distribution and heterogeneity of drug targets within the tumor cross-section.

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Kimberley S. Samkoe, Lei G. Wang, Jesse R. Korber, Summer L. Gibbs, and Kenneth M. Tichauer "Quantification of tissue distribution and therapeutic response using paired agent imaging in a chicken chorioallantoic membrane xenograft assay (Conference Presentation)", Proc. SPIE 11219, Visualizing and Quantifying Drug Distribution in Tissue IV, 112190E (20 April 2020); https://doi.org/10.1117/12.2547100

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KEYWORDS

Tumors

Tissues

3D modeling

Content addressable memory

In vivo imaging

Molecules

Statistical modeling

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