1. Proceedings
  2. I3M
  3. 2019
  4. IWISH
  5. 10.46354/i3m.2019.iwish.011

Model of a tracheobronchial tree for the training of bronchoscopy examinations

  • a Simone Bazurro  , 
  • b Raffaela Caddori  , 
  • c Clelia Capurro  , 
  • d Serena Ricci  , 
  • e Simone Marcutti  , 
  • f Francesca Vigo  , 
  • g Giorgio Carlini  , 
  • h Marco Chirico  , 
  • i Fabio Solari  , 
  • j Maura Casadio  , 
  • k Manuela Chessa 
  • a,Department of Scienze Chirurgiche e Diagnostiche Integrate, University of Genova, Italy
  • b,c,d,e,f,g,i,j,kDepartment of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genova, Italy
  • hSIMAV Centro di Servizi di ateneo di simulazione e formazione avanzata, University of Genova, Italy
Cite as
Bazurro S., Caddori R., Capurro C., Ricci S., Marcutti S., Vigo F., Carlini G., Chirico M., Solari F., Casadio M., Chessa M. (2019). Model of a tracheobronchial tree for the training of bronchoscopy examinations. Proceedings of the 8th International Workshop on Innovative Simulation for Healthcare (IWISH 2019), pp. 60-64. DOI: https://doi.org/10.46354/i3m.2019.iwish.011

Abstract

Simulation in medicine has been extensively used for the training of medical students, as well as for learning new procedures or studying complex situations, which need a deep understanding of the clinical case. Specifically, in anesthesia and intensive care, bronchoscopy is a procedure entailing some risks, such as perforation, bleeding or other emergency situations. Therefore, it is necessary to train residents with the use of alternative methods before practicing on patients. In this context, we combined a physical model of the tracheobronchial tree with a virtual reality-based system to create a low-cost simulator for bronchoscopy training. Specifically, we designed and implemented a system combining a physical and a virtual model of the tracheobronchial tree of a specific patient, starting from his/hers CT image. This system represents an innovative simulator combining visual and haptic feedbacks. Indeed, our prototype is intended to enhance clinicians’ skills in a riskless environment.

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