The worst mistake in endotracheal intubation is not recognizing esophageal intubation, because the result might be severe hypoxia leading to anoxic brain damage or death. Capnography and stethoscope auscultation offer ETT position confirmation by demonstrating indirect characteristics of respiration baring significant false positive and false negatives.5,20–24 In this research we studied the ability of a computerized algorithm to successfully differentiate an intraluminar image of an esophagus from that of the trachea/carina as a new tool to verify proper ETT position. It was our hypothesis that image analysis is accurate because it uses direct airway property (i.e., visual anatomy).
In our study only 1 esophageal video image (of 560) was mistakenly recognized as airway; this made for a false positive rate of 0.001. Similarly, 24 images (of 1040) of trachea/carina were recognized as esophagus, yielding a 0.041 false negative rate. Of interest is the fact that the algorithm identified carina as esophagus in 2 instances, and trachea was recognized 22 times as esophagus. This 10-fold difference can be attributed to the anatomic similarity of trachea and esophagus, namely, having 1 lumen.
Currently, carbon dioxide (CO2) in exhaled air (capnography) serves as the confirmation method of choice for proper ETT positioning. This is, however, not failsafe because the air in the stomach may contain CO2.6 Keller et al. found that there is a significant potential for false-positive colorimetric capnometric results even in the presence of small amounts of carbonated beverages.25 In a different clinical scenario, that of cardiac arrest, Kramer-Johansen et al. compared the values of end-tidal (ETCO2) measured from an ETT located in the trachea and in the esophagus. The ETCO2 values obtained were 11.3 mm Hg and 3.8 mm Hg, respectively. These low values are the result of low cardiac output and cannot be distinguished clinically, nor were they statistically different.26 A meta-analysis study demonstrated capnography sensitivity and specificity to be 93% and 97%, respectively.5 In our study the algorithm differentiated esophagus from airway images (carina and trachea together) with 98% sensitivity and 99% specificity. It should be noted that the results of the meta-analysis were derived from emergency intubation trials, understandably difficult clinical scenarios, yet it gives an objective value that puts our results in perspective.
There are other methods to confirm ETT proper position, but they are even less accurate than is capnography: auscultation uses the sound of airflow. One assumes that if the stethoscope diaphragm is positioned over the chest, the sound of airflow will originate from the airways. However, airflow sound from the stomach can be transmitted to the chest, yielding a false-negative finding.4,27 Other methods have been suggested over the years to verify ETT location; none of them was widely adopted.26,28–31 For example, Kelly et al. studied in canines the reliability of water condensation seen on the inner walls of an ETT upon ventilation. They found that condensation was seen in all tubes located in the trachea; however, it was also seen in 83% of tubes placed in the esophagus.32
The aforementioned ETT placement confirmation methods (fogging, auscultation, capnography, etc.) suffer significant false positives and negatives because they rely upon interpretation of secondary physical products of ventilation. Bronchoscopy through the ETT is more sensitive because it uses the primary characteristic of ETT position, visualization of anatomical image of tracheal rings. Theoretically, we could have confirmed each ETT position using a bronchoscope. However, bronchoscopes are large, fragile, and expensive. Economically speaking, we cannot equip every remote anesthesia location, disaster field hospital, military forward surgical team, and advance life support ambulance with a bronchoscope. Our proposed system mimics the bronchoscope by acquiring a direct video image, with subsequent analysis and interpretation.
The system described herein, as we see it in the future, should not be cumbersome: a video camera is mounted on the tip of an intubating stylet and connected to a small processor (personal digital assistant size). The stylet will be used inside an elastic condom (like vaginal ultrasound) and is therefore for multiple uses. While introducing the ETT, video images are acquired and transferred to the processor while the algorithm analyzes the ETT's location. Upon identification of an esophageal image, an audio alarm sounds, alerting the operator to an esophageal intubation location, allowing the operator to maintain visualization of the anatomy at all times. A different and unique sound is chimed once a carinal image replaces a tracheal image, suggesting proper ETT positioning. The video camera lens possesses a focal distance, and therefore the distance from the carina at which the image will change is about 2 cm. For noisy environments (such as in a helicopter), light signals might replace audio signals.
The video camera will be a part of an intubating stylet and will allow ETT shape manipulation. It allows repeated confirmations of ETT location without stopping chest compressions as requested by the 2010 American Heart Association cardiopulmonary resuscitation algorithm.1 It enables quick verification after and during patient transport. If needed, the system can be modified for continuous ETT position monitoring by connecting the processor to ETView® (Misgav, Israel). This product is a US Food and Drug Administration–approved ETT that has a video camera embedded at its end. If the medical team finds it appropriate, the ETT can be replaced for continuous monitoring.
The end product will not contain a monitor, although some anesthesiologists presented with the concept stated that they would rather trust their eyesight. There are 3 reasons for the lack of a monitor: first, avoiding the need to disconnect the user's continuous visualization of the upper airway; second, eliminating the need for bronchoscopy operator training, because it is not meant to be a mini-bronchoscope; and finally, cost of the end product. Another concern of many was the use of a “black box” in the clinical setting, i.e., a monitor without a known method of operation. The algorithm used here is part of a family of “image pattern analysis systems” also commonly known as “biometric recognition systems.” This technology is widely used by security agencies to identify potential terrorists, identifying people at border controls as well as limiting access to restricted areas where it was proved to carry 99.9% accuracy.12 We therefore believe that it is a safe method.
We “taught” the algorithm to differentiate tracheal from carinal image (in addition to esophageal intubation exclusion). In 971 (of 1016) airway images the algorithms correctly differentiated trachea from carinal image, i.e., 96% accuracy (0.96 sensitivity, 0.95 specificity). The system will identify correct intratracheal positioning by finding the first transition from 1 lumen (trachea) to 2 lumens (carina). This potential ability to prevent endobronchial intubation is an additional merit of the system, not present in any commercial monitor. Intratracheal positioning is a secondary benefit, not the main purpose of the system.
This study suffers a few limitations mandating further investigation. The study design was aimed at simulating resuscitation, a clinical scenario with a high rate of intubation failures, done in austere locations and under tremendous stress.8,9 In fact 10% of ETT misplacements were in cardiac arrest scenarios.5 The use of fresh bovine specimens was therefore chosen as a model for unperfused biological tissue, mandating repeating the study in a human model. Substantial additional research is needed involving the performance of the algorithm under inferior visual conditions (e.g., pulmonary edema, pulmonary bleeding, copious bronchial secretions). This comparison will be a challenge because of the difficulty performing such a prospective study. It will, however, be very interesting because it is these clinical scenarios in which capnography might fail secondary to sampling line obstruction and auscultation is limited because alveoli are filled with fluid. Our statistical evaluation tool (leave-one-case-out method) is a common acceptable method to evaluate performance of supervised systems. However, it is known to suffer from a tendency to have optimistic results on laboratory studies. A larger clinical study is therefore desirable.
In summary, a potential novel tube position verification system incorporating visual pattern recognition algorithms was assessed. High accuracy of the analysis algorithm was shown using nonperfused biological tissue, justifying further research.
Name: Micha Y. Shamir, MD.
Contribution: This author helped design the study, analyze the data, and write the manuscript. The author approved the last manuscript.
Conflicts of Interest: This author has no conflict of interest to report.
Name: Dror Lederman, PhD, EMT-P.
Conflicts of Interest: Dr. Lederman is the inventor of the system presented in this paper and founder and owner of Tube-Eye Medical Ltd., which aims to commercialize the invention.
Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript. The author approved the last manuscript.
Name: Dietrich Gravenstein, MD.
Contribution: This author helped analyze the data and write the manuscript. The author approved the last manuscript.
Conflicts of Interest: This author has no conflict of interest to report.
This manuscript was handled by: Dwayne R. Westenskow, PhD.
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