SA1 - Pilot Study: Fabricating an Anatomically Accurate Head and Neck Airway Model Using 3D Printing

Abstract: While the application of three-dimensional (3D) printing is used in numerous fields of medicine and surgery, current studies on its use in anesthesia remain simplistic and scarce (Chao et al). Difficult airway management is the leading cause of death in anesthesia (Green et al), despite the psychomotor skills required to manage an airway being learnable through simulation training. Most airway models fail to accurately replicate the biomechanics, anatomy, and haptics of the human airway, and high-fidelity patient anesthesia simulators can cost more than $50,000 (Green et al). 3D printing is a versatile technology capable of producing complex structures from various materials in a cost-effective manner. This study investigates whether 3D printing can be utilized to create an airway model that is comparable to a cadaveric airway model in terms of anatomy, haptics, and biomechanics.

A .STL file of a 3D airway model, derived from a real human computed tomography scan without identifiers or abnormal anatomy, was segmented and optimized using Materialise Mimics Innovation Suite. Key anatomical features were identified and physically created using 3D printing (hard tissues via Formlabs 3B printer, silicone molds via Ultimaker S5 printer). Silicone material was selected based on haptic and biomechanical feedback as determined by the investigators. Fabricated airway models underwent rigorous physical examination by the research team until an adequate model was developed with respect to anatomy, haptics (material features/tactile feel), and biomechanics. This model was then used in a comparative airway assessment lab, where both the 3D-printed model and a fresh-frozen cadaver were intubated by anesthesiology and oral surgery residents using a video laryngoscope. Participants completed pre-intubation and post-intubation surveys with 10-point Likert scale questions for comparative qualitative assessment of the instrumented airways.

All Likert scale ratings were analyzed using the Mann-Whitney U nonparametric statistical test to identify differences between participant ratings of the 3D-printed and cadaveric airway models regarding anatomy, haptics, and biomechanical properties (see Table 2). Data analysis was performed using SAS® v9.4 (North Carolina State University, Raleigh, NC).

Fifteen anesthesiology and oral surgery residents participated in the comparative airway assessment lab. Of these, twelve (80%) had previous experience with airway simulators, while three (20%) did not. The cadaveric model demonstrated statistically significant greater anatomic and biomechanical similarities to a live patient compared to the 3D-printed airway in both post-intubation surveys 1 (PS-1) and 2 (PS-2) (median Likert score of 10 vs 5 in PS-1 for anatomic similarities, P = .001; 10 vs 7 in PS-2, P = .005; median Likert score of 10 vs 7 in PS-1 for biomechanical similarities, P = .016; 10 vs 7.5 in PS-2, P = .016). However, the cadaveric model did not show statistically significant greater haptic similarities to a live patient compared to the 3D-printed airway in PS-2 (median Likert score of 10 vs 9, P = .125). PS-2 concluded with an open-ended question for additional comments, which, though not statistically analyzed, included multiple responses noting that the 3D-printed airway tongue felt more realistic than that of the cadaveric model.

While the 3D-printed airway was not proven to be comparable to a fresh-frozen cadaver regarding anatomic and biomechanical similarities to a live patient, our results suggest that it achieved comparable haptics. Further refinement of the model is needed to enhance its potential as an effective anesthesia airway training simulator in the future.

References:
1. Chao, I., Young, J., Coles-Black, J., Chuen, J., Weinberg, L. and Rachbuch, C. (2017), The application of three-dimensional printing technology in anaesthesia: a systematic review. Anaesthesia, 72: 641-650. https://doi.org/10.1111/anae.13812

2. Green, M., Tariq, R., Green, P. "Improving Patient Safety through Simulation Training in Anesthesiology: Where Are We?", Anesthesiology Research and Practice, vol. 2016, Article ID 4237523, 12 pages, 2016. https://doi.org/10.1155/2016/4237523
Table 2