Clinical trials with novel fluorescence contrast agents for head and neck cancer are driving new applications for fluorescence-guided surgery. Two-dimensional fluorescence imaging systems, however, provide limited in vivo assessment capabilities to determine tumor invasion depth below the mucosal surface. Here, we investigate the use of spatial frequency domain imaging (SFDI) methods for sub-surface fluorescence in tissue-simulating oral cancer phantoms. A two-step profile-correction approach for SFDI is under development to account for the complex surface topography of the oral cavity. First, for structured-illumination estimation of the surface profile, we are evaluating gray code and phase shift profilometry methods in agar-based oral cavity phantoms to maximize resolution and minimize sensitivity to surface discontinuities. Second, for profile-correction of the diffuse reflectance, global lighting effects within the oral cavity – analogous to an integrating sphere – are modeled using a multi-bounce numerical model. Subsurface fluorescence imaging is enabled based on the variations in optical sampling depth that result from changes in spatial frequency. An analytical depth recovery approach is based on a numerical diffusion theory model for semi-infinite fluorescence slabs of variable thickness. Depth estimation is evaluated in an agar-based phantom with fluorescence inclusions of thicknesses 1-5.5 mm originating from the top surface (“iceberg model”). Future clinical studies are necessary to assess in vivo performance and intraoperative workflow.
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.