Method of detecting tissue contact for fiber-optic probes to automate data acquisition without hardware modification

Fully automated fiber-based optical spectroscopy system for use in a clinical setting

While there are a plethora of in vivo fiber-optic spectroscopic techniques that have demonstrated the ability to detect a number of diseases in research trials with highly trained personnel familiar with the operation of experimental optical technologies, very few techniques show the same level of success in large multicenter trials. To meet the stringent requirements for a viable optical spectroscopy system to be used in a clinical setting, we developed components including an automated calibration tool, optical contact sensor for signal acquisition, and a methodology for real-time in vivo probe calibration correction. The end result is a state-of-the-art medical device that can be realistically used by a physician with spectroscopic fiber-optic probes. We show how the features of this system allow it to have excellent stability measuring two scattering phantoms in a clinical setting by clinical staff with ∼0.5  %   standard deviation over 25 unique measurements on different days. In addition, we show the systems' ability to overcome many technical obstacles that spectroscopy applications often face such as speckle noise and user variability. While this system has been designed and optimized for our specific application, the system and design concepts are applicable to most in vivo fiber-optic-based spectroscopic techniques.

Hemoglobin parameters from diffuse reflectance data

Tissue vasculature is altered when cancer develops. Consequently, noninvasive methods of monitoring blood vessel size, density, and oxygenation would be valuable. Simple spectroscopy employing fiber optic probes to measure backscattering can potentially determine hemoglobin parameters. However, heterogeneity of blood distribution, the dependence of the tissue-volume-sampled on scattering and absorption, and the potential compression of tissue all hinder the accurate determination of hemoglobin parameters. We address each of these issues. A simple derivation of a correction factor for the absorption coefficient, μa, is presented. This correction factor depends not only on the vessel size, as others have shown, but also on the density of blood vessels. Monte Carlo simulations were used to determine the dependence of an effective pathlength of light through tissue which is parameterized as a ninth-order polynomial function of μa. The hemoglobin bands of backscattering spectra of cervical tissue are fit using these expressions to obtain effective blood vessel size and density, tissue hemoglobin concentration, and oxygenation. Hemoglobin concentration and vessel density were found to depend on the pressure applied during in vivo acquisition of the spectra. It is also shown that determined vessel size depends on the blood hemoglobin concentration used.