A novel ex vivo trainer for robotic vesicourethral anastomosis.
Prostatectomy
Robotic surgery
Simulation
Surgical education
Surgical skills training
Journal
Journal of robotic surgery
ISSN: 1863-2491
Titre abrégé: J Robot Surg
Pays: England
ID NLM: 101300401
Informations de publication
Date de publication:
Feb 2020
Feb 2020
Historique:
received:
28
11
2018
accepted:
18
01
2019
pubmed:
29
1
2019
medline:
20
8
2020
entrez:
29
1
2019
Statut:
ppublish
Résumé
Robotic surgical skill development is central to training in urology as well as other surgical disciplines. Vesicourethral anastomosis (VUA) in robotic prostatectomy is a challenging task for novices due to delicate tissue and difficult suturing angles. Commercially available, realistic training models are limited. Here, we describe the development and validation of a 3D-printed model of the VUA for ex vivo training using the da Vinci Surgical System. Models of the bladder and urethra were created using 3D-printing technology based on estimations of average in vivo anatomy. 10 surgical residents without prior robotics training were enrolled in the study: 5 residents received structured virtual reality (VR) training on the da Vinci Skills Simulator ("trained"), while the other 5 did not ("untrained"). 4 faculty robotic surgeons trained in robotic urologic oncology ("experts") were also enrolled. Mean (range) completion percentage was 20% (10-30%), 54% (40-70%), and 96% (85-100%) by the untrained, trained, and expert groups, respectively. Anastomosis integrity was rated as excellent (as opposed to moderate or poor) in 40%, 60%, and 100% of untrained, trained, and expert groups, respectively. Face validity (realism) was rated as 8 of 10 on average by the expert surgeons, each of whom rated the model as a superior training tool to digital VR trainers. Content validity (usefulness) was rated as 10 of 10 by all participants. This is the first reported 3D-printed ex vivo trainer for VUA in robotic prostatectomy validated for use in robotic simulation. The addition of 3D-printed ex vivo training to existing digital simulation technologies may augment and improve robotic surgical education in the future.
Identifiants
pubmed: 30689167
doi: 10.1007/s11701-019-00926-1
pii: 10.1007/s11701-019-00926-1
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
21-27Subventions
Organisme : Intuitive Surgical
ID : Intuitive Surgical Standalone Simulator Program
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