Model-based analysis of fiber-optic extended-wavelength diffuse reflectance spectroscopy for nerve detection

Abstract

Optical spectroscopy is a real-time technique that holds promise as a potential surgical guidance tool. Fiber-optic diffuse reflectance spectroscopy (DRS) is a technique capable of intraoperative tissue differentiation. The common DRS focuses on estimating chromophore concentrations in the visible (VIS) wavelength range (400-1000 nm), where spectroscopic features of the blood, pigments, and tissue densities are present between 400 and 700 nm. Recently, extended-wavelength DRS (EWDRS), which extends the spectral window from the VIS through the short wave-infrared region (SWIR) up to 1800 nm, has emerged as a promising approach for identifying nerves and nerve bundles due to the SWIR including robust tissue absorption features associated with nerve-tissue related chromophores, including lipids, water and collagen proteins. One potential application of EWDRS is guiding minimally invasive surgical techniques, such as laparoscopy, where inadvertent injury to pelvic autonomic nerves (PANs) is a primary complication that can result in over 70% of patients suffering long-term side effects, including urinary incontinence and sexual dysfunction. There is a need for objective laparoscopic surgical guidance to precisely identify PANs from other tissues, and an improved basis for EWDRS development could assist clinical translation. Prior development of Fiber-optic DRS for tissue classification in the VIS greatly benefited from the application of modeling techniques for simulation of optical measurements, analysis, and fiber-probe design. Model-based analysis can inform fundamental understanding of measured signals in different measurement scenarios, such as the varying tissue morphologies possible in laparoscopic procedures, and guide application-specific fiber-probe design through comparison of unique illumination/collection geometries; however, the demonstration of these approaches in EWDRS is not widely reported. This dissertation focuses on the advancement of platforms for model-driven analysis of EWDRS for nerve identification. In order to advance the current state of EWDRS, a model-based characterization platform for analysis of a custom-developed fiber-optic EWDRS system was developed in Aim 1, which demonstrated agreement between data collected from optical phantoms, ex vivo microsurgical model, and Monte Carlo (MC) computational simulations of EWDRS measurements. In Aim 2, the model-based platform was used to perform a detailed analysis of two similar EWDRS fiber-optic probes, which indicated subtle differences in the depth-dependent measurement performance. Finally, in Aim 3, the custom EWDRS was prepared for adapting laparoscopic use to demonstrate laparoscopic measurement feasibility, including evaluation of placement variance and customized EWDRS package for short-distance transportation. The successful completion of this dissertation will enable improved analyses of EWDRS devices for a variety of future intraoperative applications.