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

Mascagni, Pietro; Fiorillo, Claudio; Urade, Takeshi; Emre, Taha; Yu, Tong; Wakabayashi, Taiga; Felli, Emanuele; Perretta, Silvana; Swanström, Lee L.; Mutter, Didier; Marescaux, Jacques; Pessaux, Patrick; Costamagna, Guido; Padoy, Nicolas; Dallemagne, Bernard

doi:10.1007/s00464-019-07149-3

Cited by 43 publications

(42 citation statements)

References 20 publications

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“…The number of studies reporting this evidence suggests two possibilities: the iconographic documentation does not correspond to the real intraoperative perception or surgeons who supposed to know CVS in truth fails understanding its application. This would reinforce the concept that programmes and task forces for a safe cholecystectomy help to increase the number of surgeons able to act safely and that the use of additional techniques, such as comparison with iconographic findings, can help the operator to have perception of his work and document what has been done [16,68,[71][72][73].…”

Section: Discussionmentioning

confidence: 70%

The critical view of safety during laparoscopic cholecystectomy: Strasberg Yes or No? An Italian Multicentre study

et al. 2020

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Background Laparoscopic cholecystectomy is considered the gold standard for the treatment of gallbladder lithiasis; nevertheless, the incidence of bile duct injuries (BDI) is still high (0.3-0.8%) compared to open cholecystectomy (0.2%). In 1995, Strasberg introduced the "Critical View of Safety" (CVS) to reduce the risk of BDI. Despite its widespread use, the scientific evidence supporting this technique to prevent BDI is controversial. Methods Between March 2017 and March 2019, the data of patients submitted to laparoscopic cholecystectomy in 30 Italian surgical departments were collected on a national database. A survey was submitted to all members of Italian Digestive Pathology Society to obtain data on the preoperative workup, the surgical and postoperative management of patients and to judge, at the end of the procedure, if the isolation of the elements was performed according to the CVS. In the case of a declared critical view, iconographic documentation was obtained, finally reviewed by an external auditor. Results Data from 604 patients were analysed. The study population was divided into two groups according to the evidence (Group A; n = 11) or absence (Group B; N = 593) of BDI and perioperative bleeding. The non-use of CVS was found in 54.6% of procedures in the Group A, and 25.8% in the Group B, and evaluating the operator-related variables the execution of CVS was associated with a significantly lower incidence of BDI and intraoperative bleeding. Conclusions The CVS confirmed to be the safest technique to recognize the elements of the Calot triangle and, if correctly performed, it significantly impacted on preventing intraoperative complications. Additional educational programs on the correct application of CVS in clinical practice would be desirable to avoid extreme conditions that may require additional procedures. Keywords Cholecystectomy • Critical view of safety • Laparoscopy • Bile duct injuries • Intraoperative bleeding • Laparoscopic training Laparoscopic cholecystectomy (LC) is currently and worldwide considered the gold standard for the treatment of gallbladder lithiasis. Since its introduction, in the early 1990s, this procedure has gained a remarkable consensus until becoming a routine surgical procedure. LC is characterized by a reduction in postoperative pain, hospital stay, and recovery times to normal daily activities, which translates into reduced costs for the national healthcare systems (NHS) [1]. However, this procedure comes with an increased incidence of bile duct injuries (BDI), compared to open cholecystectomy (OC): 0.3% and 0.8% vs 0.2% [2-7]. LC-related BDIs include minor injuries up to complex hilar injuries, as classified by Strasberg et al., in which the and Other Interventional Techniques

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Section: Discussionmentioning

confidence: 70%

The critical view of safety during laparoscopic cholecystectomy: Strasberg Yes or No? An Italian Multicentre study

et al. 2020

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“…Furthermore, while it is true that models like DeepCVS or GoNoGoNet produce consistent output for any given input, they rely on human annotation to learn so their value is strictly dependent on the quality and reliability of annotations. To improve the quality of annotation, these should be performed by multiple trained reviewers using validated protocols 59 . This is likely to reduce human subjectivity and bias, especially compared to operators self‐assessing during potentially stressful procedures.…”

Section: Limitations and Future Directionsmentioning

confidence: 99%

Surgical data science and artificial intelligence for surgical education

Ward

Mascagni

Madani

et al. 2021

Journal of Surgical Oncology

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Surgical data science (SDS) aims to improve the quality of interventional healthcare and its value through the capture, organization, analysis, and modeling of procedural data. As data capture has increased and artificial intelligence (AI) has advanced, SDS can help to unlock augmented and automated coaching, feedback, assessment, and decision support in surgery. We review major concepts in SDS and AI as applied to surgical education and surgical oncology.

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“…In robotic prostatectomy, subtle pulsation of vessels can be detected and magnified to an extent that is perceivable by a surgeon [35]. In laparoscopic cholecystectomy, automated video retrieval can help in assessing whether a critical view of safety was achieved [36], with potential risk reduction and a safer removal of the gallbladder. Additionally, the detection and classification of anatomy enables Visc Med 2020;36:456-462 DOI: 10.1159/000511934 the automatic generation of standardized procedure reports for quality control assessment and clinical training [37].…”

Section: Anatomy Detectionmentioning

confidence: 99%

Computer Vision in the Surgical Operating Room

et al. 2020

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Background: Multiple types of surgical cameras are used in modern surgical practice and provide a rich visual signal that is used by surgeons to visualize the clinical site and make clinical decisions. This signal can also be used by artificial intelligence (AI) methods to provide support in identifying instruments, structures, or activities both in real-time during procedures and postoperatively for analytics and understanding of surgical processes. Summary: In this paper, we provide a succinct perspective on the use of AI and especially computer vision to power solutions for the surgical operating room (OR). The synergy between data availability and technical advances in computational power and AI methodology has led to rapid developments in the field and promising advances. Key Messages: With the increasing availability of surgical video sources and the convergence of technologiesaround video storage, processing, and understanding, we believe clinical solutions and products leveraging vision are going to become an important component of modern surgical capabilities. However, both technical and clinical challenges remain to be overcome to efficiently make use of vision-based approaches into the clinic.

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

Cited by 43 publications

References 20 publications

The critical view of safety during laparoscopic cholecystectomy: Strasberg Yes or No? An Italian Multicentre study

The critical view of safety during laparoscopic cholecystectomy: Strasberg Yes or No? An Italian Multicentre study

Surgical data science and artificial intelligence for surgical education

Computer Vision in the Surgical Operating Room

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