Mr. David Cooper Profile

David Cooper

at Univ of Washington

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Proceedings Article | 27 February 2019 Presentation + Paper

Custom bile duct phantom for first-in-human multiplexed NIR fluorescence peptide imaging

Yang Jiang, David Cooper, Matthew Carson, Eric Seibel

Proceedings Volume 10870, 108700M (2019) https://doi.org/10.1117/12.2509893

KEYWORDS: Near infrared, Endoscopes, 3D printing, Tissue optics, Cancer

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Multimodal endoscopy, with fluorescence labeled peptides specific for multiple biomarkers, is a promising technique to detect early-stage GI tract cancers in vivo. A reproducible bile duct phantom with near infrared (NIR) fluorescent targets is developed for practicing the clinical study protocol and quantitative evaluation of multimodal endoscope performance during biliary duct imaging. Furthermore, this phantom with strictures will be used for testing new fluorescence guided biopsy devices. Materials and Methods: A soft, flexible synthetic human bile duct was fabricated from a paintable silicone rubber. Due to the complex structure of biliary system (such as hepatic ducts, cystic duct, and common bile duct), the template mold for lumen was designed for 3D printing using Polyvinyl Acetate (PVA), which can be later dissolved in water. Cured gelatin patches with different concentrations of fluorescence dyes (Cy5 and IRDye800) were placed onto the mold. Then silicone rubber with pigments to simulate visual appearance was painted in layers. After the silicone curing, the phantom was placed in warm water (40 degreeC) to dissolve PVA. Two different multimodal scanning fiber endoscope systems, RGB reflectance + NIR fluorescence and 3 fluorescence (IRDye800, Cy5, and FITC) + grayscale reflectance, were used to test the phantom. Results: The bile duct phantom is flexible, stable, and repeatable to fabricate with strictures. Clinical study procedures of fluorescence labeling were evaluated quantitatively. The NIR fluorescence targets in the phantom were used to calibrate the imaging system, further develop image-based biomarker quantification.

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