Development and initial evaluation of a novel simulation model for comprehensive brain tumor surgery training.


Journal

Acta neurochirurgica
ISSN: 0942-0940
Titre abrégé: Acta Neurochir (Wien)
Pays: Austria
ID NLM: 0151000

Informations de publication

Date de publication:
08 2020
Historique:
received: 21 01 2020
accepted: 16 04 2020
pubmed: 10 5 2020
medline: 6 1 2021
entrez: 10 5 2020
Statut: ppublish

Résumé

Increasing technico-manual complexity of procedures and time constraints necessitates effective neurosurgical training. For this purpose, both screen- and model-based simulations are under investigation. Approaches including 3D printed brains, gelatin composite models, and virtual environments have already been published. However, quality of brain surgery simulation is limited due to discrepancies in visual and haptic experience. Similarly, virtual training scenarios are still lacking sufficient real-world resemblance. In this study, we introduce a novel simulator for realistic neurosurgical training that combines real brain tissue with 3D printing and augmented reality. Based on a human CT scan, a skull base and skullcap were 3D printed and equipped with an artificial dura mater. The cerebral hemispheres of a calf's brain were placed in the convexity of the skullcap and tumor masses composed of aspic, water, and fluorescein were injected in the brain. The skullcap and skull base were placed on each other, glued together, and filled up with an aspic water solution for brain fixation. Then, four surgical scenarios were performed in the operating room as follows: (1) simple tumor resection, (2) complex tumor resection, (3) navigated biopsy via burr hole trepanation, and (4) retrosigmoidal craniotomy. Neuronavigation, augmented reality, fluorescence, and ocular-as well as screen-based (exoscopic)-surgery were available for the simulator training. A total of 29 participants performed at least one training scenario of the simulator and completed a 5-item Likert-like questionnaire as well as qualitative interviews. The questionnaire assessed the realism of the tumor model, skull, and brain tissue as well as the capability for training purposes. Visual and sensory realism of the skull and brain tissue were rated,"very good," while the sensory and visual realism of the tumor model were rated "good." Both overall satisfaction with the model and eligibility of the microscope and neurosurgical instruments for training purposes were rated with "very good." However, small size of the calf's brain, its limited shelf life, and the inability to simulate bleedings due to the lack of perfusion were significant drawbacks. The combination of 3D printing and real brain tissue provided surgical scenarios with very good real-life resemblance. This novel neurosurgical model features a versatile setup for surgical skill training and allows for efficient training of technological support like image and fluorescence guidance, exoscopic surgery, and robotic technology.

Sections du résumé

BACKGROUND
Increasing technico-manual complexity of procedures and time constraints necessitates effective neurosurgical training. For this purpose, both screen- and model-based simulations are under investigation. Approaches including 3D printed brains, gelatin composite models, and virtual environments have already been published. However, quality of brain surgery simulation is limited due to discrepancies in visual and haptic experience. Similarly, virtual training scenarios are still lacking sufficient real-world resemblance. In this study, we introduce a novel simulator for realistic neurosurgical training that combines real brain tissue with 3D printing and augmented reality.
METHODS
Based on a human CT scan, a skull base and skullcap were 3D printed and equipped with an artificial dura mater. The cerebral hemispheres of a calf's brain were placed in the convexity of the skullcap and tumor masses composed of aspic, water, and fluorescein were injected in the brain. The skullcap and skull base were placed on each other, glued together, and filled up with an aspic water solution for brain fixation. Then, four surgical scenarios were performed in the operating room as follows: (1) simple tumor resection, (2) complex tumor resection, (3) navigated biopsy via burr hole trepanation, and (4) retrosigmoidal craniotomy. Neuronavigation, augmented reality, fluorescence, and ocular-as well as screen-based (exoscopic)-surgery were available for the simulator training. A total of 29 participants performed at least one training scenario of the simulator and completed a 5-item Likert-like questionnaire as well as qualitative interviews. The questionnaire assessed the realism of the tumor model, skull, and brain tissue as well as the capability for training purposes.
RESULTS
Visual and sensory realism of the skull and brain tissue were rated,"very good," while the sensory and visual realism of the tumor model were rated "good." Both overall satisfaction with the model and eligibility of the microscope and neurosurgical instruments for training purposes were rated with "very good." However, small size of the calf's brain, its limited shelf life, and the inability to simulate bleedings due to the lack of perfusion were significant drawbacks.
CONCLUSION
The combination of 3D printing and real brain tissue provided surgical scenarios with very good real-life resemblance. This novel neurosurgical model features a versatile setup for surgical skill training and allows for efficient training of technological support like image and fluorescence guidance, exoscopic surgery, and robotic technology.

Identifiants

pubmed: 32385637
doi: 10.1007/s00701-020-04359-w
pii: 10.1007/s00701-020-04359-w
pmc: PMC7360639
doi:

Types de publication

Evaluation Study Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1957-1965

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Auteurs

Anne Sophie Grosch (AS)

Department of Neurosurgery, Charité, Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.

Timo Schröder (T)

Berliner Simulations & Trainingszentrum (BeST), Berlin Simulation Centre, Charité, Universitätsmedizin Berlin, Berlin, Germany.

Torsten Schröder (T)

Berliner Simulations & Trainingszentrum (BeST), Berlin Simulation Centre, Charité, Universitätsmedizin Berlin, Berlin, Germany.

Julia Onken (J)

Department of Neurosurgery, Charité, Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.

Thomas Picht (T)

Department of Neurosurgery, Charité, Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany. thomas.picht@charite.de.
Berliner Simulations & Trainingszentrum (BeST), Berlin Simulation Centre, Charité, Universitätsmedizin Berlin, Berlin, Germany. thomas.picht@charite.de.
Cluster of Excellence, Matters of Activity, Image Space Material, Humboldt University, Berlin, Germany. thomas.picht@charite.de.

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