Spectral Reflectance as a Unique Tissue Identifier in Healthy Humans and Inhalation Injury Subjects

Tracheal intubation is the preferred method of airway management, a common emergency trauma medicine problem. Currently, methods for confirming tracheal tube placement are lacking, and we propose a novel technology, spectral reflectance, which may be incorporated into the tracheal tube for verification of placement. Previous work demonstrated a unique spectral profile in the trachea, which allowed differentiation from esophageal tissue in ex vivo swine, in vivo swine, and human cadavers. The goal of this study is to determine if spectral reflectance can differentiate between trachea and other airway tissues in living humans and whether the unique tracheal spectral profile persists in the presence of an inhalation injury. Reflectance spectra were captured using a custom fiber-optic probe from the buccal mucosa, posterior oropharynx, and trachea of healthy humans intubated for third molar extraction and from the trachea of patients admitted to a burn intensive care unit with and without inhalation injury. Using ratio comparisons, we found that the tracheal spectral profile was significantly different from buccal mucosa or posterior oropharynx, but the area under the curve values are not high enough to be used clinically. In addition, inhalation injury did not significantly alter the spectral reflectance of the trachea. Further studies are needed to determine the utility of this technology in a clinical setting and to develop an algorithm for tissue differentiation.

Automated summary

Tracheal intubation is the preferred method for airway management in emergency trauma medicine. This study proposes a novel technology, spectral reflectance, for verifying tracheal tube placement. The research demonstrates that trachea has a unique spectral profile that differentiates it from other airway tissues. Furthermore, inhalation injury does not affect the spectral reflectance of the trachea. However, more studies are needed to determine the clinical utility of this technology and develop a tissue differentiation algorithm.