Presentation + Paper
6 March 2020 Image-guided fluorescence tomography in tissue phantom models of oral cancer
Author Affiliations +
Abstract
Current intraoperative methods to assess tumor invasion depth in mucosal oral cancer provide limited real-time information. The advent of targeted fluorescence contrast agents for head and neck cancer is a promising innovation, but surgical imaging systems typically provide only two-dimensional views. Here, we investigate the use of an image-guided fluorescence tomography (igFT) system to estimate the depth of tumor invasion in tissue-simulating oral cancer phantoms. Implementation of non-contact diffuse optical tomography using finite-element software (NIRFAST) is enabled with geometric data from intraoperative cone-beam CT (CBCT) imaging and surgical navigation. The tissue phantoms used gelatin for the background (5% for fat, 10% for muscle) and 2% agar for palpable, tumor-like inclusions. Standard agents were used for absorption (hemoglobin), scattering (Intralipid), fluorescence (indocyanine green), and CT contrast (iohexol). The agar inclusions were formed using 3D printed molds, and positioned at the surface of the gelatin background to mimic mucosal tumor invasion (an “iceberg” model). Simulations and phantom experiments characterize fluorescence tomography performance across a range of tumor invasion depths. To aid surgical visualization, the fluorescence volume is converted to a colored surface indicating tumor depth, and overlaid on the navigated endoscopic video. Clinical studies are necessary to assess in vivo performance and intraoperative workflow.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael J. Daly, Jacqueline Fleisig, Harley Chan, Marco Ferrari, Catriona Douglas, Brian C. Wilson, David A. Jaffray, and Jonathan C. Irish "Image-guided fluorescence tomography in tissue phantom models of oral cancer", Proc. SPIE 11222, Molecular-Guided Surgery: Molecules, Devices, and Applications VI, 112220E (6 March 2020); https://doi.org/10.1117/12.2547348
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KEYWORDS
Tumors

Fluorescence tomography

Tissues

Luminescence

3D modeling

Natural surfaces

Cancer

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