A Comprehensive Training Model for Simulation of Intracranial Aneurysm Surgery Using a Human Placenta and a Cadaveric Head.


Journal

Operative neurosurgery (Hagerstown, Md.)
ISSN: 2332-4260
Titre abrégé: Oper Neurosurg (Hagerstown)
Pays: United States
ID NLM: 101635417

Informations de publication

Date de publication:
05 Jul 2024
Historique:
received: 14 12 2023
accepted: 11 03 2024
medline: 5 7 2024
pubmed: 5 7 2024
entrez: 5 7 2024
Statut: aheadofprint

Résumé

Aneurysmal surgery is technically complex, and surgeon experience is an important factor in therapeutic success, but training young vascular neurosurgeons has become a complex paradigm. Despite new technologies and simulation models, cadaveric studies still offer an incomparable training tool with perfect anatomic accuracy, especially in neurosurgery. The use of human placenta for learning and improving microsurgical skills has been previously described. In this article, we present a comprehensive simulation model with both realistic craniotomy exposure and vascular handling consisting of a previously prepared and perfused human placenta encased in a human cadaveric specimen. Humans' placentas from the maternity and cadaveric heads from the body donation program of the anatomy laboratory were used. Placentas were prepared according to the established protocol, and aneurysms were created by catheterization of a placental artery. Ten participants, including senior residents or young attendees, completed an evaluation questionnaire after completing the simulation of conventional unruptured middle artery aneurysm clipping surgery from opening to closure. The skin incision, muscle dissection, and craniotomy were assessed as very similar to reality. Brain tissue emulation and dissection of the lateral fissure were judged to be less realistic. Vascular management was evaluated as similar to reality as closure. Participants uniformly agreed that this method could be implemented as a standard part of their training. This model could provide a good model for unruptured aneurysm clipping training.

Sections du résumé

BACKGROUND AND OBJECTIVES OBJECTIVE
Aneurysmal surgery is technically complex, and surgeon experience is an important factor in therapeutic success, but training young vascular neurosurgeons has become a complex paradigm. Despite new technologies and simulation models, cadaveric studies still offer an incomparable training tool with perfect anatomic accuracy, especially in neurosurgery. The use of human placenta for learning and improving microsurgical skills has been previously described. In this article, we present a comprehensive simulation model with both realistic craniotomy exposure and vascular handling consisting of a previously prepared and perfused human placenta encased in a human cadaveric specimen.
METHODS METHODS
Humans' placentas from the maternity and cadaveric heads from the body donation program of the anatomy laboratory were used. Placentas were prepared according to the established protocol, and aneurysms were created by catheterization of a placental artery. Ten participants, including senior residents or young attendees, completed an evaluation questionnaire after completing the simulation of conventional unruptured middle artery aneurysm clipping surgery from opening to closure.
RESULTS RESULTS
The skin incision, muscle dissection, and craniotomy were assessed as very similar to reality. Brain tissue emulation and dissection of the lateral fissure were judged to be less realistic. Vascular management was evaluated as similar to reality as closure. Participants uniformly agreed that this method could be implemented as a standard part of their training.
CONCLUSION CONCLUSIONS
This model could provide a good model for unruptured aneurysm clipping training.

Identifiants

pubmed: 38967445
doi: 10.1227/ons.0000000000001190
pii: 01787389-990000000-01243
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © Congress of Neurological Surgeons 2024. All rights reserved.

Références

Hulsbergen AFC, Mirzaei L, van der Boog ATJ, et al. Long-term durability of open surgical versus endovascular repair of intracranial aneurysms: a systematic review and meta-analysis. World Neurosurg. 2019;132:e820-e833.
Hsu CE, Lin TK, Lee MH, et al. The impact of surgical experience on major intraoperative aneurysm rupture and their consequences on outcome: a multivariate analysis of 538 microsurgical clipping cases. PLoS One. 2016;11(3):e0151805.
Steinert Y, Mann K, Anderson B, et al. A systematic review of faculty development initiatives designed to enhance teaching effectiveness: a 10-year update: BEME Guide No. 40. Med Teach. 2016;38(8):769-786.
Davids J, Manivannan S, Darzi A, Giannarou S, Ashrafian H, Marcus HJ. Simulation for skills training in neurosurgery: a systematic review, meta-analysis, and analysis of progressive scholarly acceptance. Neurosurg Rev. 2021;44(4):1853-1867.
Hu M, Wattchow D, de Fontgalland D. From ancient to avant-garde: a review of traditional and modern multimodal approaches to surgical anatomy education. ANZ J Surg. 2018;88(3):146-151.
Hino A. Training in microvascular surgery using a chicken wing artery. Neurosurgery. 2003;52(6):1495-1498; discussion 1497-1498.
Olabe J, Olabe J, Roda J. Microsurgical cerebral aneurysm training porcine model. Neurol India. 2011;59(1):78-81.
Regelsberger J, Eicker S, Siasios I, et al. In vivo porcine training model for cranial neurosurgery. Neurosurg Rev. 2015;38(1):157-163; discussion 163.
Kimura T, Morita A, Nishimura K, et al. Simulation of and training for cerebral aneurysm clipping with 3-dimensional models. Neurosurgery. 2009;65(4):719-726; discussion 725-726.
Vakharia VN, Vakharia NN, Hill CS. Review of 3-dimensional printing on cranial neurosurgery simulation training. World Neurosurg. 2016;88:188-198.
Wang JL, Yuan ZG, Qian GL, Bao WQ, Jin GL. 3D printing of intracranial aneurysm based on intracranial digital subtraction angiography and its clinical application. Medicine (Baltimore). 2018;97(24):e11103.
Joseph FJ, Weber S, Raabe A, Bervini D. Neurosurgical simulator for training aneurysm microsurgery-a user suitability study involving neurosurgeons and residents. Acta Neurochir (Wien). 2020;162(10):2313-2321.
Delorme S, Laroche D, DiRaddo R, Del Maestro RF. NeuroTouch: a physics-based virtual simulator for cranial microneurosurgery training. Neurosurgery. 2012;71(1 Suppl Operative):32-42.
Choudhury N, Gélinas-Phaneuf N, Delorme S, Del Maestro R. Fundamentals of neurosurgery: virtual reality tasks for training and evaluation of technical skills. World Neurosurg. 2013;80:e9-e19.
Alaraj A, Luciano CJ, Bailey DP, et al. Virtual reality cerebral aneurysm clipping simulation with real-time haptic feedback. Neurosurgery. 2015;11 Suppl 2(0 2):52-58.
Gmeiner M, Dirnberger J, Fenz W, et al. Virtual cerebral aneurysm clipping with real-time haptic force feedback in neurosurgical education. World Neurosurg. 2018;112:e313-e323.
Perin A, Galbiati TF, Gambatesa E, et al. Filling the gap between the OR and virtual simulation: a European study on a basic neurosurgical procedure. Acta Neurochir (Wien). 2018;160(11):2087-2097.
Bairamian D, Liu S, Eftekhar B. Virtual reality angiogram vs 3-dimensional printed angiogram as an educational tool-a comparative study. Neurosurgery. 2019;85(2):e343-e349.
Kim SC, Fisher JG, Delman KA, Hinman JM, Srinivasan JK. Cadaver-based simulation increases resident confidence, initial exposure to fundamental techniques, and may augment operative autonomy. J Surg Educ. 2016;73(6):e33-e41.
Gnanakumar S, Kostusiak M, Budohoski KP, et al. Effectiveness of cadaveric simulation in neurosurgical training: a review of the literature. World Neurosurg. 2018;118:88-96.
Kshettry VR, Mullin JP, Schlenk R, Recinos PF, Benzel EC. The role of laboratory dissection training in neurosurgical residency: results of a national survey. World Neurosurg. 2014;82:554-559.
Aboud E, Al-Mefty O, Yaşargil MG. New laboratory model for neurosurgical training that simulates live surgery. J Neurosurg. 2002;97(6):1367-1372.
Goldstein M. Use of fresh human placenta for microsurgical training. J Microsurg. 1979;1(1):70-71.
Romero FR, Fernandes ST, Chaddad-Neto F, Ramos JG, de Campos JM, de Oliveira E. Microsurgical techniques using human placenta. Arq Neuropsiquiatr. 2008;66(4):876-878.
Belykh E, Miller EJ, Lei T, et al. Face, content, and construct validity of an aneurysm clipping model using human placenta. World Neurosurg. 2017;105:952-960.e2.
Oliveira MM, Ferrarez CE, Lovato R, et al. Quality assurance during brain aneurysm microsurgery-operative error teaching. World Neurosurg. 2019;130:e112-e116.
Gallardo FC, Bustamante JL, Martin C, et al. Novel simulation model with pulsatile flow system for microvascular training, research, and improving patient surgical outcomes. World Neurosurg. 2020;143:11-16.
Oliveira Magaldi M, Nicolato A, Godinho JV, et al. Human placenta aneurysm model for training neurosurgeons in vascular microsurgery. Neurosurgery. 2014;10(Suppl 4):592-600; discussion 600-601.
Aboud E, Aboud G, Al-Mefty O, et al. “Live cadavers” for training in the management of intraoperative aneurysmal rupture. J Neurosurg. 2015;123(5):1339-1346.
de Oliveira MMR, Ferrarez CE, Ramos TM, et al. Learning brain aneurysm microsurgical skills in a human placenta model: predictive validity. J Neurosurg. 2018;128(3):846-852.
Chueh JY, Wakhloo AK, Gounis MJ. Neurovascular modeling: small-batch manufacturing of silicone vascular replicas. AJNR Am J Neuroradiol. 2009;30(6):1159-1164.
Mashiko T, Otani K, Kawano R, et al. Development of three-dimensional hollow elastic model for cerebral aneurysm clipping simulation enabling rapid and low cost prototyping. World Neurosurg. 2015;83:351-361.
Ryan JR, Almefty KK, Nakaji P, Frakes DH. Cerebral aneurysm clipping surgery simulation using patient-specific 3d printing and silicone casting. World Neurosurg. 2016;88:175-181.
Chugh AJ, Pace JR, Singer J, et al. Use of a surgical rehearsal platform and improvement in aneurysm clipping measures: results of a prospective, randomized trial. J Neurosurg. 2017;126(3):838-844.
Lechanoine F, Smirnov M, Armani-Franceschi G, et al. Stereoscopic images from computed tomography angiograms. World Neurosurg. 2019;128:259-267.

Auteurs

Emmanuel De Schlichting (E)

Service de Neurochirurgie, Centre Hospitalier Universitaire de Grenoble-Alpes, Grenoble, France.

Julien Francisco Zaldivar-Jolissaint (JF)

Service de Neurochirurgie, Centre Hospitalier Universitaire de Grenoble-Alpes, Grenoble, France.

Nicolas Molter (N)

Université de Grenoble Alpes, Grenoble, France.

Marion Chenevas-Paule (M)

Université de Grenoble Alpes, Grenoble, France.

Ayah Hamadmad (A)

Université de Grenoble Alpes, Grenoble, France.

Luc Giroux (L)

Université de Grenoble Alpes, Grenoble, France.

Arnaud Lazard (A)

Service de Neurochirurgie, Centre Hospitalier Universitaire de Grenoble-Alpes, Grenoble, France.
Université de Grenoble Alpes, Grenoble, France.
Laboratoire d'Anatomie Des Alpes Françaises (LADAF), Université de Grenoble Alpes, Grenoble, France.

Didier Riethmuller (D)

Université de Grenoble Alpes, Grenoble, France.
Service de Gynécologie et Obstétrique, Centre Hospitalier Universitaire de Grenoble-Alpes, Grenoble, France.

Philippe Chaffanjon (P)

Université de Grenoble Alpes, Grenoble, France.
Laboratoire d'Anatomie Des Alpes Françaises (LADAF), Université de Grenoble Alpes, Grenoble, France.
Service de Chirurgie Thoracique, Centre Hospitalier Universitaire de Grenoble-Alpes, Grenoble, France.

Guillaume Coll (G)

Service de Neurochirurgie, Centre hospitalier universitaire Gabriel Montpied, Clermont Ferrand, France.

François Lechanoine (F)

Neurosurgery Unit, Maria Cecilia Hospital, Cotignola, Italy.

Classifications MeSH