Literature DB >> 29117409

Development of a Perfusion-Based Cadaveric Simulation Model Integrated into Neurosurgical Training: Feasibility Based On Reconstitution of Vascular and Cerebrospinal Fluid Systems.

Gabriel Zada1, Joshua Bakhsheshian1, Martin Pham1, Mike Minneti2, Eisha Christian1, Jesse Winer1, Aaron Robison3, Bozena Wrobel4, Jonathan Russin1, William J Mack1, Steven Giannotta1.   

Abstract

BACKGROUND: Novel methodologies providing realistic simulation of the neurosurgical operating room environment are currently needed, particularly for highly subspecialized operations with steep learning curves, high-risk profiles, and demands for advanced psychomotor skills.
OBJECTIVE: To describe the development of a curriculum for using perfusion-based cadaveric simulation models in a "Mock Operating Room" for neurosurgical procedures.
METHODS: At the USC Keck School of Medicine Fresh Tissue Dissection Laboratory between 2012 and 2016, 43 cadaveric specimens underwent cannulation of the femoral or carotid artery and artificial perfusion of the arterial system, and/or cannulation of the intradural cervical spine for intrathecal reconstitution of the cerebrospinal fluid (CSF) system. Models were used to train neurosurgical residents in various procedures. Self-assessment of pre- and postprocedure trainee confidence (Likert) scores was compared for each module.
RESULTS: The following novel procedural training methodologies were successfully established: management of an injury to the carotid artery during an endoscopic endonasal approach (n = 12), endoscopic endonasal CSF leak repair (n = 6) with fluorescein perfusion, carotid endarterectomy (n = 4), extracranial-to-intracranial bypass (n = 2), insertion of ventriculostomy catheter (n = 7), spinal laminectomy with durotomy repair (n = 9), and intraventricular neuro-endoscopy with septum pellucidotomy and third ventriculostomy (n = 12). In all instances, trainees reported improvement in their postprocedural confidence scores, with mean pre- and postprocedural Likert scores being 2.85 ± 1.09 and 4.14 ± 0.93 (P < .05).
CONCLUSION: Augmentation of fresh cadaveric specimens via reconstitution of vascular and CSF pathways is a feasible methodology for complimenting surgical training in numerous neurosurgical procedures, and may hold implications in the future of neurosurgical resident education.
Copyright © 2017 by the Congress of Neurological Surgeons

Entities:  

Keywords:  Cadaver; Education; Simulation; Skills lab; Surgical skills; Surgical training

Mesh:

Year:  2018        PMID: 29117409     DOI: 10.1093/ons/opx074

Source DB:  PubMed          Journal:  Oper Neurosurg (Hagerstown)        ISSN: 2332-4252            Impact factor:   2.703


  4 in total

1.  Innovative real CSF leak simulation model for rhinology training: human cadaveric design.

Authors:  Abdulaziz A AlQahtani; Abeer A Albathi; Othman M Alhammad; Abdulkarim S Alrabie
Journal:  Eur Arch Otorhinolaryngol       Date:  2018-02-12       Impact factor: 2.503

2.  Expert surgeons and deep learning models can predict the outcome of surgical hemorrhage from 1 min of video.

Authors:  Dhiraj J Pangal; Guillaume Kugener; Yichao Zhu; Aditya Sinha; Vyom Unadkat; David J Cote; Ben Strickland; Martin Rutkowski; Andrew Hung; Animashree Anandkumar; X Y Han; Vardan Papyan; Bozena Wrobel; Gabriel Zada; Daniel A Donoho
Journal:  Sci Rep       Date:  2022-05-17       Impact factor: 4.996

3.  3D-printed cranial models simulating operative field depth for microvascular training in neurosurgery.

Authors:  Vadim Byvaltsev; Roman Polkin; Dmitry Bereznyak; Morgan B Giers; Phillip A Hernandez; Valery Shepelev; Marat Aliyev
Journal:  Surg Neurol Int       Date:  2021-05-10

4.  Utility of the Simulated Outcomes Following Carotid Artery Laceration Video Data Set for Machine Learning Applications.

Authors:  Guillaume Kugener; Dhiraj J Pangal; Tyler Cardinal; Casey Collet; Elizabeth Lechtholz-Zey; Sasha Lasky; Shivani Sundaram; Nicholas Markarian; Yichao Zhu; Arman Roshannai; Aditya Sinha; X Y Han; Vardan Papyan; Andrew Hung; Animashree Anandkumar; Bozena Wrobel; Gabriel Zada; Daniel A Donoho
Journal:  JAMA Netw Open       Date:  2022-03-01
  4 in total

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