Endoscopy 2023; 55(01): 4-11
DOI: 10.1055/a-1850-6717
Original article

An artificial intelligence difficulty scoring system for stone removal during ERCP: a prospective validation

Li Huang*
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
3   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
,
Youming Xu*
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
3   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
,
Jie Chen
4   Department of Gastroenterology, Changhai Hospital, Naval Medical University, Shanghai, China
,
Feng Liu
5   Digestive Endoscopy Center, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
,
Deqing Wu
5   Digestive Endoscopy Center, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
,
Wei Zhou
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
3   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
,
Lianlian Wu
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
3   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
,
Tingting Pang
4   Department of Gastroenterology, Changhai Hospital, Naval Medical University, Shanghai, China
,
Xu Huang
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
3   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
,
Kuo Zhang
6   Wuhan ENDOANGEL Medical Technology Company, Wuhan, China
,
1   Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
2   Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
3   Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
› Author Affiliations
Trial Registration: ClinicalTrials.gov Registration number (trial ID): NCT04719117 Type of study: Prospective observation Trial


Abstract

Background A computer-assisted (CAD) system was developed to assess, score, and classify the technical difficulty of common bile duct (CBD) stone removal during endoscopic retrograde cholangiopancreatography (ERCP). The efficacy of the CAD system was subsequently assessed through a multicenter, prospective, observational study.

Method All patients who met the inclusion criteria were included. Based on cholangiogram images, the CAD system analyzed the level of difficulty of stone removal and classified it into “difficult” and “easy” groups. Subsequently, differences in clinical endpoints, including attempts at stone extraction, stone extraction time, total operation time, and stone clearance rates were compared between the two groups.

Results 173 patients with CBD stones from three hospitals were included in the study. The group classified as difficult by CAD had more extraction attempts (7.20 vs. 4.20, P < 0.001), more frequent machine lithotripsy (30.4 % vs. 7.1 %, P < 0.001), longer stone extraction time (16.59 vs. 7.69 minutes, P < 0.001), lower single-session stone clearance rate (73.9 % vs. 94.5 %, P < 0.001), and lower total stone clearance rate (89.1 % vs. 97.6 %, P = 0.019) compared with the group classified as easy by CAD.

Conclusion The CAD system effectively assessed and classified the degree of technical difficulty in endoscopic stone extraction during ERCP. In addition, it automatically provided a quantitative evaluation of CBD and stones, which in turn could help endoscopists to apply suitable procedures and interventional methods to minimize the possible risks associated with endoscopic stone removal.

* These authors contributed equally.


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Publication History

Received: 25 November 2021

Accepted after revision: 12 May 2022

Accepted Manuscript online:
12 May 2022

Article published online:
12 July 2022

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