Training Performance Assessment for Intracranial Aneurysm Clipping Surgery Using a Patient-Specific Mixed-Reality Simulator: A Learning Curve Study.

Cuba, Miguel; Vanluchene, Hanne; Murek, Michael; Goldberg, Johannes; Müller, Mandy D; Montalbetti, Matteo; Janosovits, Katharina; Rhomberg, Thomas; Zhang, David; Raabe, Andreas; Joseph, Fredrick J; Bervini, David (2024). Training Performance Assessment for Intracranial Aneurysm Clipping Surgery Using a Patient-Specific Mixed-Reality Simulator: A Learning Curve Study. (In Press). Operative neurosurgery, 26(6), pp. 727-736. Oxford University Press 10.1227/ons.0000000000001041

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BACKGROUND AND OBJECTIVES

The value of simulation-based training in medicine and surgery has been widely demonstrated. This study investigates the introduction and use of a new mixed-reality neurosurgical simulator in aneurysm clipping surgery, focusing on the learning curve and performance improvement.

METHODS

Five true-scale craniotomy head models replicating patient-specific neuroanatomy, along with a mixed-reality simulator, a neurosurgical microscope, and a set of microsurgical instruments and clips, were used in the operation theater to simulate aneurysm microsurgery. Six neurosurgical residents participated in five video-recorded simulation sessions over 4 months. Complementary learning modalities were implemented between sessions. Thereafter, three blinded analysts reported on residents' use of the microscope, quality of manipulation, aneurysm occlusion, clipping techniques, and aneurysm rupture. Data were also captured regarding training time and clipping attempts.

RESULTS

Over the course of training, clipping time and number of clipping attempts decreased significantly (P = .018, P = .032) and the microscopic skills improved (P = .027). Quality of manipulation and aneurysm occlusion scoring improved initially although the trend was interrupted because the spacing between sessions increased. Significant differences in clipping time and attempts were observed between the most and least challenging patient models (P = .005, P = .0125). The least challenging models presented higher rates of occlusion based on indocyanine green angiography evaluation from the simulator.

CONCLUSION

The intracranial aneurysm clipping learning curve can be improved by implementing a new mixed-reality simulator in dedicated training programs. The simulator and the models enable comprehensive training under the guidance of a mentor.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurosurgery
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Image Guided Therapy

UniBE Contributor:

Cuba Gato, Miguel Angel, Vanluchene, Hanne Eline R., Murek, Michael Konrad, Goldberg, Johannes, Müller, Mandy, Montalbetti, Matteo Luigi, Janosovits, Katharina Elisabeth, Rhomberg, Thomas, Zhang, David Yuzhe, Raabe, Andreas, Joseph, Fredrick Johnson, Bervini, David

Subjects:

600 Technology > 610 Medicine & health
500 Science > 570 Life sciences; biology

ISSN:

2332-4260

Publisher:

Oxford University Press

Language:

English

Submitter:

Pubmed Import

Date Deposited:

23 Jan 2024 08:25

Last Modified:

13 May 2024 00:13

Publisher DOI:

10.1227/ons.0000000000001041

PubMed ID:

38251883

BORIS DOI:

10.48350/191993

URI:

https://boris.unibe.ch/id/eprint/191993

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