| Literature DB >> 30054776 |
Allan Javaux1, David Bouget2, Caspar Gruijthuijsen3, Danail Stoyanov4, Tom Vercauteren4,5, Sebastien Ourselin4, Jan Deprest4,5, Kathleen Denis3, Emmanuel Vander Poorten3.
Abstract
PURPOSE: Smaller incisions and reduced surgical trauma made minimally invasive surgery (MIS) grow in popularity even though long training is required to master the instrument manipulation constraints. While numerous training systems have been developed in the past, very few of them tackled fetal surgery and more specifically the treatment of twin-twin transfusion syndrome (TTTS). To address this lack of training resources, this paper presents a novel mixed-reality surgical trainer equipped with comprehensive sensing for TTTS procedures. The proposed trainer combines the benefits of box trainer technology and virtual reality systems. Face and content validation studies are presented and a use-case highlights the benefits of having embedded sensors.Entities:
Keywords: Content validation; Face validation; Fetal minimally invasive surgery; Mixed-reality trainer
Mesh:
Year: 2018 PMID: 30054776 PMCID: PMC6223750 DOI: 10.1007/s11548-018-1822-7
Source DB: PubMed Journal: Int J Comput Assist Radiol Surg ISSN: 1861-6410 Impact factor: 2.924
Fig. 1Two fetuses are represented in a womb. A flexible cannula is inserted through the maternal abdomen allowing surgeons to access the placenta with a fetoscope equipped with a scope and laser to coagulate specific targets (courtesy of UZ Leuven)
Fig. 2The setup of the advanced mixed-reality surgical trainer: (A) straight and curved fetoscopes, (B) cannula, (C) body wall phantom, (D) force sensor, (E) virtual scope view
Fig. 3A straight fetoscope is employed for the posterior placenta (left). A curved one is used for the anterior placenta (right)
Fig. 4Illustration of the two different tasks with the effect of lasering on the placenta
Results of face validity
| Face validity | Total | Novices | Intermediates | Experts |
| |||
|---|---|---|---|---|---|---|---|---|
| Median | Median | SD | Median | SD | Median | SD | ||
| Overall realism of trainer | 3.50 | 3.50 | 1.00 | 3.50 | 0.50 | 3.50 | 0.50 | 1.000 |
| Body wall phantom | 3.00 | 3.50 | 1.00 | 3.50 | 0.50 | 3.00 | 0.00 | 0.497 |
| Equipment | 4.00 | 3.50 | 1.00 | 3.50 | 0.50 | 4.00 | 0.00 | 0.497 |
| Environment VR rendering | ||||||||
| Placenta model | 3.00 | 4.00 | 0.25 | 3.00 | 0.00 | 3.00 | 0.00 | 0.123 |
| Posterior configuration | 3.50 | 4.00 | 0.25 | 3.00 | 0.00 | 3.50 | 0.50 | 0.269 |
| Anterior configuration | 3.50 | 4.00 | 0.25 | 3.00 | 0.00 | 3.00 | 1.00 | 0.343 |
| Coagulation model | 3.00 | 3.00 | 0.25 | 3.50 | 0.50 | 3.50 | 0.50 | 0.249 |
| Procedural tasks | ||||||||
| Selective lasering | 4.00 | 3.50 | 1.00 | 4.00 | 0.00 | 3.50 | 0.50 | 0.497 |
| Line lasering | 4.00 | 3.00 | 0.50 | 4.00 | 0.00 | 4.00 | 0.00 | 0.135 |
| Scope VR rendering | ||||||||
| Scope view | 3.00 | 4.00 | 0.25 | 3.00 | 0.00 | 3.00 | 0.00 | 0.123 |
| Image quality | 3.00 | 3.00 | 0.25 | 3.50 | 0.50 | 2.50 | 1.50 | 0.553 |
| Light propagation | 4.00 | 3.00 | 2.00 | 4.00 | 0.00 | 3.50 | 0.50 | 0.472 |
| Depth perception | 3.50 | 3.50 | 1.50 | 3.50 | 0.50 | 3.00 | 1.00 | 0.936 |
| Workspace of instruments | 3.50 | 3.00 | 0.25 | 4.00 | 0.00 | 3.50 | 0.50 | 0.269 |
Kruskal–Wallis test with significance
Fig. 5Realism versus required improvements according to fetal MIS surgeons
Results of content validity
| Content validity | Total | Novices | Intermediates | Experts |
| |||
|---|---|---|---|---|---|---|---|---|
| Median | Median | IQR | Median | IQR | Median | IQR | ||
| Training capacities | ||||||||
| Scope handling | 5.00 | 5.00 | 0.25 | 4.50 | 0.50 | 4.00 | 1.00 | 0.664 |
| Lasering | 5.00 | 5.00 | 0.00 | 5.00 | 0.00 | 4.50 | 0.50 | 0.223 |
| Self-confidence | 5.00 | 5.00 | 0.00 | 5.00 | 0.00 | 4.50 | 0.50 | 0.223 |
| Usefulness of task | ||||||||
| Task I: basic skills | 5.00 | 5.00 | 0.25 | 5.00 | 0.00 | 4.50 | 0.50 | 0.558 |
| Task II: procedural skills | 5.00 | 5.00 | 0.25 | 5.00 | 0.00 | 4.50 | 0.50 | 0.558 |
Kruskal–Wallis test with significance
Fig. 6The different signals of motion, force and pedal state data are shown for selective lasering in a posterior and anterior configuration. For each plot, the signal is highlighted in green when the pedal is activated
Results of the motion and force-based analysis of the use-case study
| Metrics |
| Posterior | Anterior | ||
|---|---|---|---|---|---|
| Mean | SD | Mean | SD | ||
| Planar force maximum | 3.71 | 1.48 | 6.99 | 2.01 | |
| Planar force integral | 412 | 125 | 813 | 153 | |
| Vertical force integral | 462 | 387 | 786 | 375 | |
| Depth perception | 1.09 | 0.55 | 1.41 | 0.50 | |
| Vertical force maximum | 0.218 | 1.06 | 0.70 | 1.57 | 0.93 |
| Velocity maximum | 0.383 | 0.91 | 0.71 | 1.06 | 0.60 |
| Acceleration maximum | 0.641 | 4.20 | 3.77 | 4.42 | 3.04 |
| Tool path length | 0.742 | 2.28 | 1.04 | 2.47 | 0.90 |
| Acceleration mean | 0.742 | 0.030 | 0.010 | 0.032 | 0.005 |
| Velocity mean | 0.844 | 0.0081 | 0.0025 | 0.0084 | 0.0016 |
| Time | 1.000 | 269.62 | 111.53 | 269.38 | 71.30 |
Kruskal–Wallis test with significance bold values