Validation of a real-time biliopancreatic endoscopic ultrasonography analytical device in China: a prospective, single-centre, randomised, controlled trial

• Published in: The Lancet. Digital health 2023-11, Vol.5 (11), p.e812-e820
• Main Authors: Wu, Hui Ling, MD, Yao, Li Wen, PhD, Shi, Hui Ying, MD, Wu, Lian Lian, MD, Li, Xun, MD, Zhang, Chen Xia, MA, Chen, Bo Ru, MA, Zhang, Jun, MD, Tan, Wei, MD, Cui, Ning, MD, Zhou, Wei, MD, Zhang, Ji Xiang, MD, Xiao, Bing, MD, Gong, Rong Rong, MA, Ding, Zhen, Prof, Yu, Hong Gang, Prof
• Format: Article
• Language: English
• Subjects: Informatics; Internal Medicine; Public Health
• ISSN: 2589-7500; 2589-7500
• DOI: 10.1016/S2589-7500(23)00160-7

SummaryBackgroundEndoscopic ultrasonography (EUS) is a key procedure for the diagnosis of biliopancreatic diseases. However, the performance among EUS endoscopists varies greatly and leads to blind spots during the operation, which can impair the health outcomes of patients. We previously developed an artificial intelligence (AI) device that accurately identified EUS standard stations and significantly reduced the difficulty of ultrasonography image interpretation. In this study, we updated the device (named EUS-IREAD) and validated its performance in improving the quality of EUS procedures. MethodsIn this single-centre, randomised, controlled trial, we updated EUS-IREAD so it consisted of five learning models to identify eight EUS stations and 24 anatomical structures. The trial was done at the Renmin Hospital of Wuhan University (Wuhan, China) and included patients aged 18 years or older with suspected biliopancreatic (pancreas and biliopancreatic duct) lesions due to clinical symptoms, radiological findings, or laboratory findings, and with a high risk of pancreatic cancer. Patients were randomly assigned (1:1) by a dedicated research assistant using a computer-generated random number series (with a block size of four) to undergo the EUS procedure with or without the assistance of EUS-IREAD. Endoscopists in the EUS-IREAD-assisted group were required to observe all standard stations and anatomical structures according to the prompts by the AI device. Data collectors, the independent data anaylsis team, and patients were masked to group allocation. The primary outcome was the missed scanning rate of standard stations between the two groups, which was assessed in patients who underwent EUS procedure in accordance with the assigned intervention (per protocol). This trial is registered with ClinicalTrials.gov, NCT05457101. FindingsBetween July 9, 2022, and Feb 28, 2023, 290 patients (mean age 55·93 years [SD 14·06], 152 [52%] male, and 138 [48%] female) were randomly assigned and analysed, including 144 in the EUS-IREAD-assisted group and 146 in the control group. The EUS-IREAD-assisted group had a lower missed scanning rate of stations than the control group (4·5% [SD 0·8] vs 14·3% [1·0], –9·8% [95% CI –12·2 to –7·5]; odds ratio 3·6 [95% Cl 2·6 to 4·9]; p