Assessing the effect of the critical view of safety criteria on simulated operative decision-making: a pilot study

Critical View of Safety in Laparoscopic Cholecystectomy: A Systematic Review of Current Evidence and Future Perspectives

BACKGROUND

The Critical View of Safety (CVS) has been increasingly recognised as the standard method for identification of the cystic structures, to prevent vasculobiliary injuries during laparoscopic cholecystectomy, however, its adoption has been anything but universal. A significant proportion of surgeons has a poor understanding of the three requirements. To bridge this gap between theory and practice, we aimed to summarise the available evidence on CVS, emphasising on current debates and future perspectives.

METHOD

We systematically reviewed the literature (1995-2021), to identify studies reporting on the CVS. Eligible articles were classified according to methodology and key idea. A quantitative analysis was performed to evaluate effectiveness of the CVS in preventing bile duct injury (BDI).

RESULTS

150 relevant articles were identified, focusing on six main points, (1) safety and effectiveness, (2) intraoperative documentation, (3) complementary imaging techniques, (4) bail-out alternatives, (5) adoption among surgeons, and (6) education and training. The quantitative analysis included 11 studies, with 10,938 cases. Overall, the CVS was achieved in 92.5%. Conversion rate was 4.8%. CVS-related BDI was 0.09% (0.05% technical errors and 0.04% misidentification errors).

CONCLUSION

Routine application of the CVS reduces BDI, but does not eliminate them altogether. Besides operative notes, the CVS should be documented by an imaging modality of sufficient quality. When the CVS cannot be safely established, the threshold for bail-out alternatives or complementary imaging should be low. Adoption by the surgical community worldwide shows great variability and focus should be placed on training through structured educational modules.

Are YouTube Videos a Reliable Training Method for Safe Laparoscopic Cholecystectomy? A Simulated Decision-Making Exercise to Assess the Critical View of Safety

Background  The present study assesses the educational value of laparoscopic cholecystectomy videos on YouTube regarding the correct application of the critical view of safety (CVS), and evaluates… surgical trainees' perceptions of the CVS criteria in a simulated, operative decision-making exercise.

Methods  YouTube was systematically searched for laparoscopic cholecystectomy videos, explicitly reporting a satisfactory CVS. The top 30 most popular videos, by number of views, were identified and scored on the 6-point scale by three experienced consultants. After watching a training module on CVS rationale and criteria, 10 trainees, blinded to the consultants' assessment, were instructed to view the videos, score each criterion and answer the binary question “Would you divide the cystic structures?” by “yes” or “no.”

Results  An inadequate CVS was found in 30% of the included videos. No statistical association was noted between number of views, likes, or dislikes with successful CVS rates. Inter-observer agreement between consultants and trainees ranged from minimal to moderate ( k  = 0.07–0.60). Discrepancy between trainees' CVS scores and their simulated decision to proceed to division of the cystic structures was found in 15% of assessments, with intra-observer agreement ranging from minimal to excellent ( k  = 0.27–1.0). For the CVS requirements, inter-observer agreement was minimal for the dissection of the cystic plate ( k  = 0.26) and triangle clearance ( k  = 0.39) and moderate for the identification of two and only two structures ( k  = 0.42).

Conclusion  The CVS is central to the culture of safety in laparoscopic cholecystectomy. Surgical videos are a useful training tool as simulated, operative decision-making exercises. However, public video platforms should be used judiciously, since their content is not peer-reviewed or quality-controlled.

Artificial Intelligence for Surgical Safety: Automatic Assessment of the Critical View of Safety in Laparoscopic Cholecystectomy Using Deep Learning

OBJECTIVE

To develop a deep learning model to automatically segment hepatocystic anatomy and assess the criteria defining the critical view of safety (CVS) in laparoscopic cholecystectomy (LC).

BACKGROUND

Poor implementation and subjective interpretation of CVS contributes to the stable rates of bile duct injuries in LC. As CVS is assessed visually, this task can be automated by using computer vision, an area of artificial intelligence aimed at interpreting images.

METHODS

Still images from LC videos were annotated with CVS criteria and hepatocystic anatomy segmentation. A deep neural network comprising a segmentation model to highlight hepatocystic anatomy and a classification model to predict CVS criteria achievement was trained and tested using 5-fold cross validation. Intersection over union, average precision, and balanced accuracy were computed to evaluate the model performance versus the annotated ground truth.

RESULTS

A total of 2854 images from 201 LC videos were annotated and 402 images were further segmented. Mean intersection over union for segmentation was 66.6%. The model assessed the achievement of CVS criteria with a mean average precision and balanced accuracy of 71.9% and 71.4%, respectively.

CONCLUSIONS

Deep learning algorithms can be trained to reliably segment hepatocystic anatomy and assess CVS criteria in still laparoscopic images. Surgical-technical partnerships should be encouraged to develop and evaluate deep learning models to improve surgical safety.