Formalizing video documentation of the Critical View of Safety in laparoscopic cholecystectomy: a step towards artificial intelligence assistance to improve surgical safety



In laparoscopic cholecystectomy (LC), achievement of the Critical View of Safety (CVS) is commonly advocated to prevent bile duct injuries (BDI). However, BDI rates remain stable, probably due to inconsistent application or a poor understanding of CVS as well as unreliable reporting. Objective video reporting could serve for quality auditing and help generate consistent datasets for deep learning models aimed at intraoperative assistance. In this study, we develop and test a method to report CVS using videos.


LC videos performed at our institution were retrieved and the video segments starting 60 s prior to the division of cystic structures were edited. Two independent reviewers assessed CVS using an adaptation of the doublet view 6-point scale and a novel binary method in which each criterion is considered either achieved or not. Feasibility to assess CVS in the edited video clips and inter-rater agreements were evaluated.


CVS was attempted in 78 out of the 100 LC videos retrieved. CVS was assessable in 100% of the 60-s video clips. After mediation, CVS was achieved in 32/78(41.03%). Kappa scores of inter-rater agreements using the doublet view versus the binary assessment were as follows: 0.54 versus 0.75 for CVS achievement, 0.45 versus 0.62 for the dissection of the hepatocystic triangle, 0.36 versus 0.77 for the exposure of the lower part of the cystic plate, and 0.48 versus 0.79 for the 2 structures connected to the gallbladder.


The present study is the first to formalize a reproducible method for objective video reporting of CVS in LC. Minute-long video clips provide information on CVS and binary assessment yields a higher inter-rater agreement than previously used methods. These results offer an easy-to-implement strategy for objective video reporting of CVS, which could be used for quality auditing, scientific communication, and development of deep learning models for intraoperative guidance.

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The authors would like to thank the whole surgical department for their continuous collaboration and Philippe De Rooy for the precious discussions. In addition, the authors are thankful to Lionel Grienenberger for video editing, to Camille Goustiaux for audio narration and proofreading, and to Christopher Burel and Guy Temporal for their professional medical English proofreading.


The present research was supported by an EAES Research Grant and an IHU Feasibility Grant.

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Correspondence to Pietro Mascagni.

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Pietro Mascagni, Claudio Fiorillo, Takeshi Urade, Taha Emre, Tong Yu, Taiga Wakabayashi, Emanuele Felli, Silvana Perretta, Lee Swanstrom, Didier Mutter, Jacques Marescaux, Patrick Pessaux, Guido Costamagna, Nicolas Padoy, and Bernard Dallemagne have no conflicts of interest or financial ties to disclose.

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Mascagni, P., Fiorillo, C., Urade, T. et al. Formalizing video documentation of the Critical View of Safety in laparoscopic cholecystectomy: a step towards artificial intelligence assistance to improve surgical safety. Surg Endosc 34, 2709–2714 (2020).

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  • Laparoscopic cholecystectomy
  • Bile duct injury
  • Critical View of Safety
  • Objective video reporting
  • Surgical safety
  • Surgical data science