Background Compared to conventional laparoscopy, robot assisted surgery is expected to have most potential in difficult areas and demanding technical skills like minimally invasive suturing. This study was performed to identify the differences in the learning curves of laparoscopic versus robot assisted suturing. Method Novice participants performed three suturing tasks on the EoSim laparoscopic augmented reality simulator or the RobotiX robot assisted virtual reality simulator. Each participant performed an intracorporeal suturing task, a tilted plane needle transfer task and an anastomosis needle transfer task. To complete the learning curve, all tasks were repeated up to twenty repetitions or until a time plateau was reached. Clinically relevant and comparable parameters regarding time, movements and safety were recorded. Intracorporeal suturing time and cumulative sum analysis was used to compare the learning curves and phases. Results Seventeen participants completed the learning curve laparoscopically and 30 robot assisted. Median first knot suturing time was 611 s (s) for laparoscopic versus 251 s for robot assisted (p < 0.001), and this was 324 s versus 165 (sixth knot, p < 0.001) and 257 s and 149 s (eleventh knot, p < 0.001) respectively on base of the found learning phases. The percentage of 'adequate surgical knots' was higher in the laparoscopic than in the robot assisted group. First knot: 71% versus 60%, sixth knot: 100% versus 83%, and eleventh knot: 100% versus 73%. When assessing the 'instrument out of view' parameter, the robot assisted group scored a median of 0% after repetition four. In the laparoscopic group, the instrument out of view increased from 3.1 to 3.9% (left) and from 3.0 to 4.1% (right) between the first and eleventh knot (p > 0.05). Conclusion The learning curve of minimally invasive suturing shows a shorter task time curve using robotic assistance compared to the laparoscopic curve. However, laparoscopic outcomes show good end results with rapid outcome improvement.

BackgroundThe purpose of this study was to validate the eoSim, an affordable and mobile inanimate laparoscopic simulator with instrument tracking capabilities, regarding face, content and construct validity on complex suturing tasks.MethodsParticipants recruited for this study were novices (no laparoscopic experience), target group for this training (surgical/gynaecologic/urologic residents, > 10 basic and < 20 advanced laparoscopic procedures) and experts (> 20 advanced laparoscopic procedures). Each participant performed the intracorporeal suturing exercise (Task 1), an upside down needle transfer (Task 2, developed for this study) and an anastomosis needle transfer (Task 3). Following, the participants completed a questionnaire regarding their demographics and opinion on the eoSim in terms of realism, didactic value and usability. Measured outcome parameters were time, distance, percentage of instrument tip off-screen, working area, speed, acceleration and smoothness.ResultsIn total, 104 participants completed the study, of which 60 novices, 31 residents and 13 experts. Face and content validity results showed a mean positive opinion on realism (3.9 Task 1, 3.6 Task 2 and 3.7 Task 3), didactic value (4.0, 3.4 and 3.7, respectively) and usability (4.2. 3.7 and 4.0, respectively). There were no significant differences in these outcomes between the specified expertise groups. Construct validity results showed significant differences between experts, target group or novices for Task 1 in terms of time (means 339, 607 and 1224 s, respectively, p < 0.001) and distance (means 8.1, 15.6 and 21.7 m, respectively, p < 0.001). Task 2 showed significant differences between groups regarding time (p < 0.001), distance (p 0.003), off-screen (p < 0.001) and working area (p < 0.001). Task 3 showed significant differences between groups, after subanalyses, on total number of stitches (p < 0.001), time per stitch (p < 0.001) and distance per stitch (p < 0.001).ConclusionsThe results of this study indicate that the eoSim is a potential meaningful and valuable simulator in the training of suturing tasks.

Background Laparoscopic suturing can be technically challenging and requires extensive training to achieve competency. To date no specific and objective assessment method for laparoscopic suturing and knot tying is available that can guide training and monitor performance in these complex surgical skills. In this study we aimed to develop a laparoscopic suturing competency assessment tool (LS-CAT) and assess its inter-observer reliability. Methods We developed a bespoke CAT tool for laparoscopic suturing through a structured, mixed methodology approach, overseen by a steering committee with experience in developing surgical assessment tools. A wide Delphi consultation with over twelve experts in laparoscopic surgery guided the development stages of the tool. Following, subjects with different levels of laparoscopic expertise were included to evaluate this tool, using a simulated laparoscopic suturing task which involved placing of two surgical knots. A research assistant video recorded and anonymised each performance. Two blinded expert surgeons assessed the anonymised videos using the developed LS-CAT. The LS-CAT scores of the two experts were compared to assess the inter-observer reliability. Lastly, we compared the subjects' LS-CAT performance scores at the beginning and end of their learning curve. Results This study evaluated a novel LS-CAT performance tool, comprising of four tasks. Thirty-six complete videos were analysed and evaluated with the LS-CAT, of which the scores demonstrated excellent inter-observer reliability. Cohen's Kappa analysis revealed good to excellent levels of agreement for almost all tasks of both instrument handling and tissue handling (0.87; 0.77; 0.75; 0.86; 0.85, all with p < 0.001). Subjects performed significantly better at the end of their learning curve compared to their first attempt for all LS-CAT items (all with p < 0.001). Conclusions We developed the LS-CAT, which is a laparoscopic suturing grading matrix, with excellent inter-rater reliability and to discriminate between experience levels. This LS-CAT has a potential for wider use to objectively assess laparoscopic suturing skills.

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