Aims: There is a strong evidence to suggest that 3D imaging improves the laparoscopic task performance when compared against 2D. However, to date, no study has explained why that might be. We identified six generic visual components during laparoscopic imaging and aimed to study each component in both 2D and 3D environments for comparison.
Methods: Twenty-four consented laparoscopic novices performed specific isolated tasks in a laparoscopic Endo Trainer in 2D and 3D separately. The six endpoints were the accuracy in detecting changes in the laparoscopic images in the following components: distance, area, angle, curvature, volume and spatial coordinates. All the components except the spatial coordinates were assessed by creation, measurement and comparison. Each component was analysed between 2D and 3D groups and within each group at different values. Tests of spatial coordinates were video-recorded and analysed for error number and error types by human reliability analysis technique. Errors types included past-pointing, not reaching the object and touching the wrong object. The results were statistically analysed with independent T test.
Results: There was no statistically significant difference between 2D and 3D accuracy in the angle, area, distance and curvature. 3D performed more accurately in comparing volumes (p = 0.05). In spatial coordinates, there were a statistically significant higher number of errors in 2D as compared to 3D (p < 0.001). Past-pointing and touching the wrong objects were significantly higher in 2D (p < 0.05).
Conclusion: Between all the visual components, detecting change in volume and the spatial coordinates showed significant improvement in 3D environment when compared to 2D.
- Imaging, Three-Dimensional
- Random Allocation
- Spatial Processing
- Task Performance and Analysis
- Video Recording
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Randomised cross-over trial assessing the impact of angle, area, distance, curvature, volume, spatial coordinates, and effect of eye exercises in surgical task performance: 2D vs 3D laparoscopic visionAuthor: Ramakrishnan, G., 2021
Supervisor: Alijani, A. (Supervisor) & Kay, V. (Supervisor)
Student thesis: Master's Thesis › Master of ScienceFile