Learning curve for the surgical time of laparoscopic cholecystectomy performed by surgical trainees using the three-port method: how many cases are needed for stabilization?

Comparative Analysis of Learning Curves in Robotic Versus Laparoscopic Cholecystectomy: A Systematic Review

Robotic surgery has undergone much development and increased use over the years; it has offered many benefits for the operating surgeon compared to the more restrictive nature of conventional laparoscopic surgery (CLS) which is the current standard of care. However, to the best of our knowledge, no studies have attempted to draw a comparison between the two in terms of the cases required for the learning curve to be achieved. The systematic review was performed at Barts Cancer Institute. A search of Cochrane, PubMed and Embase was made on 15 March 2024. Screening and risk of bias were done by two reviewers. Screening was done via the eligibility criteria by two reviewers. Data collection was done using Excel (Microsoft® Corp., Redmond, USA) and information was double-checked by another reviewer and transferred into a tabulated format. Seventeen studies were included, with the learning curve reported in 14 studies. The cases required to achieve the learning curve for multiport robotic cholecystectomy (MRC) ranged from 16 to 134 and for single-site robotic cholecystectomy (SSRC), it ranged from 10 to over 102 cases. Conventional laparoscopic cholecystectomy (CLC) was from 7 to 200. The improvement in operating times was measured in very different ways and was reported in 10 of the 17 studies. The studies that were available had a high level of heterogeneity making it difficult for comparisons to be made between studies. Several studies included only one surgeon resulting in the sample size of surgeons being too small and vulnerable to bias. As robotic surgery is still relatively novel, higher-quality studies have to be made in order for more conclusive conclusions to be made on the benefits of the learning curve of MRC and SSRC.

Safety of laparoscopic cholecystectomy performed by trainee surgeons with different cholangiographic techniques (SCOTCH): a prospective non-randomized trial on the impact of fluorescent cholangiography during laparoscopic cholecystectomy performed by trainees

AIMS

The identification of the anatomical components of the Calot's Triangle during laparoscopic cholecystectomy (LC) might be challenging and its difficulty may increase when a surgical trainee (ST) is in charge, ultimately allegedly affecting also the incidence of common bile duct injuries (CBDIs). There are various methods to help reach the critical view of safety (CVS): intraoperative cholangiogram (IOC), critical view of safety in white light (CVS-WL) and near-infrared fluorescent cholangiography (NIRF-C). The primary objective was to compare the use of these techniques to obtain the CVS during elective LC performed by ST.

METHODS

This was a multicentre prospective observational study (Clinicalstrials.gov Registration number: NCT04863482). The impact of three different visualization techniques (IOC, CVS-WL, NIRF-C) on LC was analyzed. Operative time and time to achieve the CVS were considered. All the participating surgeons were also required to fill in three questionnaires at the end of the operation focusing on anatomical identification of the general task and their satisfaction.

RESULTS

Twenty-nine centers participated for a total of 338 patients: 260 CVS-WL, 10 IOC and 68 NIRF-C groups. The groups did not differ in the baseline characteristics. CVS was considered achieved in all the included case. Rates were statistically higher in the NIR-C group for common hepatic and common bile duct visualization (p = 0.046; p < 0.005, respectively). There were no statistically significant differences in operative time (p = 0.089) nor in the time to achieve the CVS (p = 0.626). Three biliary duct injuries were reported: 2 in the CVS-WL and 1 in the NIR-C. Surgical workload scores were statistically lower in every domain in the NIR-C group. Subjective satisfaction was higher in the NIR-C group. There were no other statistically significant differences.

CONCLUSIONS

These data showed that using NIRF-C did not prolong operative time but positively influenced the surgeon's satisfaction of the performance of LC.

Automatic surgical phase recognition-based skill assessment in laparoscopic distal gastrectomy using multicenter videos

BACKGROUND

Gastric surgery involves numerous surgical phases; however, its steps can be clearly defined. Deep learning-based surgical phase recognition can promote stylization of gastric surgery with applications in automatic surgical skill assessment. This study aimed to develop a deep learning-based surgical phase-recognition model using multicenter videos of laparoscopic distal gastrectomy, and examine the feasibility of automatic surgical skill assessment using the developed model.

METHODS

Surgical videos from 20 hospitals were used. Laparoscopic distal gastrectomy was defined and annotated into nine phases and a deep learning-based image classification model was developed for phase recognition. We examined whether the developed model's output, including the number of frames in each phase and the adequacy of the surgical field development during the phase of supra-pancreatic lymphadenectomy, correlated with the manually assigned skill assessment score.

RESULTS

The overall accuracy of phase recognition was 88.8%. Regarding surgical skill assessment based on the number of frames during the phases of lymphadenectomy of the left greater curvature and reconstruction, the number of frames in the high-score group were significantly less than those in the low-score group (829 vs. 1,152, P < 0.01; 1,208 vs. 1,586, P = 0.01, respectively). The output score of the adequacy of the surgical field development, which is the developed model's output, was significantly higher in the high-score group than that in the low-score group (0.975 vs. 0.970, P = 0.04).

CONCLUSION

The developed model had high accuracy in phase-recognition tasks and has the potential for application in automatic surgical skill assessment systems.

Learning curve of laparoscopic cholecystectomy: a risk-adjusted cumulative summation (RA-CUSUM) analysis of six general surgery residents

BACKGROUND

Laparoscopic cholecystectomy (LapC) is one of the most frequently performed surgical procedures worldwide. Reaching technical competency in performing LapC is considered one essential task for young surgeons. Investigating the learning curve for LapC (LC-LapC) may provide important information regarding the learning process and guide the training pathway of residents, improving educational outcomes. The present study aimed to investigate LC-LapC among general surgery residents (GSRs).

METHODS

Operative surgical reports of consecutive patients undergoing LapC performed by GSRs attending the General Surgery Residency Program at the University of Milan were analysed. Data on patient- and surgery-related variables were obtained from the ICD-9-CM diagnosis codes and gathered. A multidimensional assessment of the LC was performed through Cumulative Sum (CUSUM) and Risk-Adjusted (RA)-CUSUM analysis.

RESULTS

340 patients operated by 6 GSRs were collected. The CUSUM and RA-CUSUM graphs based on surgical failures allowed to distinguish two defined phases for all GSRs: an initial phase ending at the peak, so-called learning phase, followed by a phase in which there was a significant decrease in failure incidence, so-called proficiency phase. The learning phase was completed for all GSRs at most within 25 procedures, but the trend of the curves and the number of procedures needed to achieve technical competency varied among operators ranging between 7 and 25.

CONCLUSIONS

The present study suggested that at most 25 procedures might be sufficient to acquire technical competency in LapC. The variability in the number of procedures needed to complete the LC, ranging between 7 and 25, could be due to the heterogeneous scenarios in which LapC was performed, and deserves to be investigated through a prospective study involving a larger number of GSRs and institutions.