Abstract. During emergency medical situations, where the patient has an obstructed airway or necessitates respiratory support, endotracheal intubation (ETI) is the medical technique of placing a tube into the trachea in order to facilitate adequate ventilation of the lungs. Complications during ETI, such as repeated attempts, failed intubation, or accidental intubation of the esophagus, can lead to severe consequences or ultimately death. Consequently, a need exists for a feedback mechanism to aid providers in performing successful ETI. Our study examined the spectral reflectance properties of the tracheal and esophageal tissue to determine whether a unique spectral profile exists for either tissue for the purpose of detection. The study began by using a hyperspectral camera to image excised pig tissue samples exposed to white and UV light in order to capture the spectral reflectance properties with high fidelity. After identifying a unique spectral characteristic of the trachea that significantly differed from esophageal tissue, a follow-up investigation used a fiber optic probe to confirm the detectability and consistency of the different reflectance characteristics in a pig model. Our results characterize the unique and consistent spectral reflectance characteristic of tracheal tissue, thereby providing foundational support for exploiting spectral properties to detect the trachea during medical procedures. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Proper placement of the tracheal tube requires confirmation, and the predominant method in addition to clinical signs is the presence of end-tidal carbon dioxide. Such is the importance of confirmation that novel methods may also have a place. We previously demonstrated using ex-vivo swine tissue a unique spectral reflectance characteristic of tracheal tissue that differs from oesophageal tissue. We hypothesised that this characteristic would be present in living swine tissue and human cadavers. Reflectance spectra in the range 500-650 nm were captured using a customised fibreoptic probe, compact spectrometer and white light source from both the trachea and the oesophagus in anesthetised living swine and in human cadavers. A tracheal detection algorithm using ratio comparisons of reflectance was developed. The existence of the unique tracheal characteristic in both in-vivo swine and cadaver models was confirmed (p < 0.0001 for all comparisons between tracheal and oesophageal tissue at all target wavelengths in both species). Furthermore, our proposed tracheal detection algorithm exhibited a 100% positive predictive value in both models. This has potential utility for incorporation into airway management devices.

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Diagnostic test, level II.

Diagnostic study, level II.

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