Systematic review on the use of artificial intelligence to identify anatomical structures during laparoscopic cholecystectomy: a tool towards the future.

Abstract

Purpose: Bile duct injury (BDI) during laparoscopic cholecystectomy (LC) is a dreaded complication. Artificial intelligence (AI) has recently been introduced in surgery. This systematic review aims to investigate whether AI can guide surgeons in identifying anatomical structures to facilitate safer dissection during LC.

Methods: Following PROSPERO registration CRD-42023478754, a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-compliant systematic search of MEDLINE (via PubMed), EMBASE, and Web of Science databases was conducted.

Results: Out of 2304 articles identified, twenty-five were included in the analysis. The mean average precision for biliary structures detection reported in the included studies reaches 98%. The mean intersection over union ranges from 0.5 to 0.7, and the mean Dice/F1 spatial correlation index was greater than 0.7/1. AI system provided a change in the annotations in 27% of the cases, and 70% of these shifts were considered safer changes. The contribution to preventing BDI was reported at 3.65/4.

Conclusions: Although studies on the use of AI during LC are few and very heterogeneous, AI has the potential to identify anatomical structures, thereby guiding surgeons towards safer LC procedures.