Simulation of Cerebrospinal Fluid Leak Repair Using a 3-Dimensional Printed Model

Muhamed A. Masalha, Kyle K. VanKoevering, Omar S. Latif, Allison R. Powell, Ashley Zhang, Keren H. Hod, Daniel M. Prevedello, Ricardo L. Carrau

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Acquiring proficiency for the repair of a cerebrospinal fluid (CSF) leak is challenging in great part due to its relative rarity, which offers a finite number of training opportunities. Objective: The purpose of this study was to evaluates the use of a 3-dimensional (3D) printed, anatomically accurate model to simulate CSF leak closure. Methods: Volunteer participants completed two simulation sessions. Questionnaires to assess their professional qualifications and a standardized 5-point Likert scale to estimate the level of confidence, were completed before and after each session. Participants were also queried on the overall educational utility of the simulation. Results: Thirteen otolaryngologists and 11 neurosurgeons, met the inclusion criteria. A successful repair of the CSF leak was achieved by 20/24 (83.33%), and 24/24 (100%) during the first and second simulation sessions respectively (average time 04:04 ± 1.39 and 02:10 ± 01:11). Time-to-close-the-CSF-leak during the second session was significantly shorter than the first (p < 0.001). Confidence scores increased across the training sessions (3.3 ± 1.0, before the simulation, 3.7 ± 0.6 after the first simulation, and 4.2 ± 0.4 after the second simulation; p < 0.001). All participants reported an increase in confidence and believed that the model represented a valuable training tool. Conclusions: Despite significant differences with varying clinical scenarios, 3D printed models for cerebrospinal leak repair offer a feasible simulation for the training of residents and novice surgeons outside the constrictions of a clinical environment.

Original languageEnglish
Pages (from-to)802-808
Number of pages7
JournalAmerican Journal of Rhinology and Allergy
Volume35
Issue number6
DOIs
StatePublished - Nov 2021

Keywords

  • 3-D model
  • cerebrospinal fluid
  • rhinorrhea
  • simulation training
  • skull base surgery
  • transnasal approach

All Science Journal Classification (ASJC) codes

  • Immunology and Allergy
  • Otorhinolaryngology

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