Efficacy of real-time artificial intelligence-aid endoscopic ultrasonography diagnostic system in discriminating gastrointestinal stromal tumors and leiomyomas: a multicenter diagnostic study

Zhixia Dong; Xiangyun Zhao; Hangbin Zheng; HanYao Zheng; Dafan Chen; Jia Cao; Zili Xiao; Yunwei Sun; Qian Zhuang; Shan Wu; Jie Xia; Min Ning; Binjie Qin; Hui Zhou; Jinsong Bao; Xinjian Wan

doi:10.1016/j.eclinm.2024.102656

Efficacy of real-time artificial intelligence-aid endoscopic ultrasonography diagnostic system in discriminating gastrointestinal stromal tumors and leiomyomas: a multicenter diagnostic study

EClinicalMedicine. 2024 May 24:73:102656. doi: 10.1016/j.eclinm.2024.102656. eCollection 2024 Jul.

Authors

Zhixia Dong¹, Xiangyun Zhao¹, Hangbin Zheng², HanYao Zheng², Dafan Chen¹, Jia Cao³, Zili Xiao⁴, Yunwei Sun⁵, Qian Zhuang¹, Shan Wu¹, Jie Xia¹, Min Ning¹, Binjie Qin⁶, Hui Zhou⁷, Jinsong Bao², Xinjian Wan¹

Affiliations

¹ Digestive Endoscopic Center, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
² College of Mechanical Engineering, Dong Hua University, Shanghai, China.
³ Endoscopy Center, Department of Gastroenterology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
⁴ Digestive Endoscopic Department, Huadong Hospital Affiliated to Fudan University, Shanghai, China.
⁵ Department of Gastroenterology, Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
⁶ School of Biomedical Engineering, Shanghai Jiao Tong University, China.
⁷ Department of Gastroenterology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Abstract

Background: Gastrointestinal stromal tumors (GISTs) represent the most prevalent type of subepithelial lesions (SELs) with malignant potential. Current imaging tools struggle to differentiate GISTs from leiomyomas. This study aimed to create and assess a real-time artificial intelligence (AI) system using endoscopic ultrasonography (EUS) images to differentiate between GISTs and leiomyomas.

Methods: The AI system underwent development and evaluation using EUS images from 5 endoscopic centers in China between January 2020 and August 2023. EUS images of 1101 participants with SELs were retrospectively collected for AI system development. A cohort of 241 participants with SELs was recruited for external AI system evaluation. Another cohort of 59 participants with SELs was prospectively enrolled to assess the real-time clinical application of the AI system. The AI system's performance was compared to that of endoscopists. This study is registered with Chictr.org.cn, Number ChiCT2000035787.

Findings: The AI system displayed an area under the curve (AUC) of 0.948 (95% CI: 0.921-0.969) for discriminating GISTs and leiomyomas. The AI system's accuracy (ACC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) reached 91.7% (95% CI 87.5%-94.6%), 90.3% (95% CI 83.4%-94.5%), 93.0% (95% CI 87.2%-96.3%), 91.9% (95% CI 85.3%-95.7%), and 91.5% (95% CI 85.5%-95.2%), respectively. Moreover, the AI system exhibited excellent performance in diagnosing ≤20 mm SELs (ACC 93.5%, 95% CI 0.900-0.969). In a prospective real-time clinical application trial, the AI system achieved an AUC of 0.865 (95% CI 0.764-0.966) and 0.864 (95% CI 0.762-0.966) for GISTs and leiomyomas diagnosis, respectively, markedly surpassing endoscopists [AUC 0.698 (95% CI 0.562-0.834) for GISTs and AUC 0.695 (95% CI 0.546-0.825) for leiomyomas].

Interpretation: We successfully developed a real-time AI-assisted EUS diagnostic system. The incorporation of the real-time AI system during EUS examinations can assist endoscopists in rapidly and accurately differentiating various types of SELs in clinical practice, facilitating improved diagnostic and therapeutic decision-making.

Funding: Science and Technology Commission Foundation of Shanghai Municipality, Science and Technology Commission Foundation of the Xuhui District, the Interdisciplinary Program of Shanghai Jiao Tong University and the Research Funds of Shanghai Sixth people's Hospital.

Keywords: Artificial intelligence; Endoscopic ultrasound; Gastrointestinal stromal tumors; Gastrointestinal subepithelial lesions; Leiomyomas.