3D Printed Biomimetic Rabbit Airway Simulation Model for Nasotracheal Intubation Training

Rabbit inhalation anesthesia by endotracheal intubation involves a higher risk among small animals owing to several anatomical and physiological features, which is pathognomonic to this species of lagomorphs. Rabbit-specific airway devices have been designed to prevent misguided intubation attempts. However, it is believed that expert anesthetic training could be a boon in limiting the aftermaths of this procedure. Our research is aimed to develop a novel biomimetic 3D printed rabbit airway model with representative biomechanical material behavior and radiodensity. Imaging data were collected for two sacrificed rabbit heads using micro-computed tomography (μCT) and micro-magnetic resonance imaging for the first head and cone beam computed tomography (CBCT) for the second head. Imaging-based life-size musculoskeletal airway models were printed using polyjet technology with a combination of hard and soft materials in replicates of three. The models were evaluated quantitatively for dimensional accuracy and radiodensity and qualitatively using digital microscopy and endoscopy for technical, tactic, and visual realism. The results displayed that simulation models printed with polyjet technology have an overall surface representation of 93% for μCT-based images and 97% for CBCT-based images within a range of 0.0–2.5 mm, with μCT showing a more detailed reproduction of the nasotracheal anatomy. Dimensional discrepancies can be caused due to inadequate support material removal and due to the limited reconstruction of microstructures from the imaging on the 3D printed model. The model showed a significant difference in radiodensities in hard and soft tissue regions. Endoscopic evaluation provided good visual and tactile feedback, comparable to the real animal. Overall, the model, being a practical low-cost simulator, comprehensively accelerates the learning curve of veterinary nasotracheal intubation and paves the way for 3D simulation-based image-guided interventional procedures.