Surface-enhanced Raman scattering (SERS) nanoparticles (NPs) are increasingly being engineered for a variety of disease-detection and treatment applications. For example, we have previously developed a fiber-optic Raman-encoded molecular imaging (REMI) system for spectral imaging of biomarker-targeted SERS NPs topically applied on tissue surfaces to identify residual tumors at surgical margins. Although accurate tumor detection was achieved, the commercial SERS NPs used in our previous studies lacked the signal strength to enable high-speed imaging with high pixel counts (large fields of view and/or high spatial resolution), which limits their use for certain time-constrained clinical applications. As a solution, we explored the use of surface-enhanced resonant Raman scattering (SERRS) NPs to enhance imaging speeds. The SERRS NPs were synthesized de novo, and then conjugated to HER2 antibodies to achieve high binding affinity, as validated by flow cytometry. Under identical tissue-staining and imaging conditions, the targeted SERRS NPs enabled reliable identification of HER2-overexpressed tumor xenografts with 50-fold-enhanced imaging speed compared with our standard targeted SERS NPs. This enables our REMI system to image tissue surfaces at a rate of 150 cm2 per minute at a spatial resolution of 0.5 mm.
Intraoperative tumor/surgical margin assessment is required to achieve higher tumor resection rate in breast-conserving surgery. Though current histology provides incomparable accuracy in margin assessment, thin tissue sectioning and the limited field of view of microscopy makes histology too time-consuming for intraoperative applications. If thick tissue, wide-field imaging can provide an acceptable assessment of tumor cells at the surface of resected tissues, an intraoperative protocol can be developed to guide the surgery and provide immediate feedback for surgeons. Topical staining of margins with cancer-targeted molecular imaging agents has the potential to provide the sensitivity needed to see microscopic cancer on a wide-field image; however, diffusion and nonspecific retention of imaging agents in thick tissue can significantly diminish tumor contrast with conventional methods. Here, we present a mathematical model to accurately simulate nonspecific retention, binding, and diffusion of imaging agents in thick tissue topical staining to guide and optimize future thick tissue staining and imaging protocol. In order to verify the accuracy and applicability of the model, diffusion profiles of cancer targeted and untargeted (control) nanoparticles at different staining times in A431 tumor xenografts were acquired for model comparison and tuning. The initial findings suggest the existence of nonspecific retention in the tissue, especially at the tissue surface. The simulator can be used to compare the effect of nonspecific retention, receptor binding and diffusion under various conditions (tissue type, imaging agent) and provides optimal staining and imaging protocols for targeted and control imaging agent.
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