A novel spectral imaging system for use during pancreatic cancer surgery

Abstract

Pancreatic cancer is the fourth leading cause of cancer death in the United States. Most pancreatic cancer patients will die within the first year of diagnosis, and just 6% will survive five years. Currently, surgery is the only treatment that offers a chance of cure for pancreatic cancer patients. Accurately identifying the tumors margins in real time is a significant difficulty during pancreatic cancer surgery and contributes to the low 5-year survival rate. We are developing a hyperspectral imaging system based on compressive sampling for real-time tumor margin detection to facilitate more effective removal of diseased tissue and result in better patient outcomes. Recent research has shown that optical spectroscopy can be used to distinguish between healthy and diseased tissue and will likely become an important minimally invasive diagnostic tool for a range of diseases. Reflectance spectroscopy provides information about tissue morphology, while laser-induced autofluorescence spectra give accurate information about the content and molecular structure of the emitting tissue. We are developing a spectral imaging system that targets emission from collagen and NAD(P)H as diagnostics for differentiating healthy and diseased pancreatic tissue. In this study, we demonstrate the ability of our camera system to acquire hyperspectral images and its potential application for imaging autofluorescent emission from pancreatic tissue.