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Development and Evaluation of a Mixed Reality Model for Training the Retrosigmoid Approach.
- Source :
-
World Neurosurgery . Sep2024, Vol. 189, pe459-e466. 8p. - Publication Year :
- 2024
-
Abstract
- The use of simulation has the potential to accelerate the learning curves and increase the efficiency of surgeons. However, there is currently a scarcity in models dedicated to skull base surgical approaches. Thus, the objective of this study was to develop a cost-effective mixed reality system consisting of an ultrarealistic physical model and augmented reality and evaluate its use in training surgeons on the retrosigmoid approach. The virtual models were developed from images of patients with vestibular schwannoma. The tumor was mirrored to allow bilateral approaches and the model has drawers for repositioning structures, allowing reuse of the material and cost reduction. Pre and posttest assessments were applied to 10 residents and young neurosurgeons, divided into control and test groups. Only the control group was exposed to the model. The difference in scores obtained by participants before and after exposure to the models was considered for analysis and participants in the control group answered self-satisfaction questionnaires. The mean differences were 4.80 in the control group (95% credibility intervals = 1.08–9.79) and 5.43 in the test group (95% credibility intervals = 1.67–8.20). The average score of the self-satisfaction questionnaires was 24.0 (23–25). The ultrarealistic model efficiently allowed retromastoid access to the cerebellopontine angle. A tendency toward greater gains in performance in the group exposed to the model was verified. Scores from the self-satisfaction questionnaires demonstrated that participants considered the model relevant for neurosurgical training and increased confidence among surgeons. [ABSTRACT FROM AUTHOR]
- Subjects :
- *MIXED reality
*LEARNING curve
*CEREBELLOPONTILE angle
*SKULL base
*ACOUSTIC neuroma
Subjects
Details
- Language :
- English
- ISSN :
- 18788750
- Volume :
- 189
- Database :
- Academic Search Index
- Journal :
- World Neurosurgery
- Publication Type :
- Academic Journal
- Accession number :
- 179500277
- Full Text :
- https://doi.org/10.1016/j.wneu.2024.06.085