Huang Li, Liu Jun, Wu Lianlian, Xu Ming, Yao Liwen, Zhang Lihui, Shang Renduo, Zhang Mengjiao, Xiong Qiutang, Wang Dawei, Dong Zehua, Xu Youming, Li Jia, Zhu Yijie, Gong Dexin, Wu Huiling, Yu Honggang
Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China.
Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China.
Front Med (Lausanne). 2021 Dec 14;8:781256. doi: 10.3389/fmed.2021.781256. eCollection 2021.
To investigate the impact of the computer-assisted system on esophagogastroduodenoscopy (EGD) training for novice trainees in a prospective randomized controlled trial. We have constructed a computer-aided system (CAD) using retrospective images based on deep learning which could automatically monitor the 26 anatomical landmarks of the upper digestive tract and document standard photos. Six novice trainees were allocated and grouped into the CAD group and control group. Each of them took the training course, pre and post-test, and EGD examination scored by two experts. The CAD group was trained with the assistance of the CAD system and the control group without. Both groups achieved great improvements in EGD skills. The CAD group received a higher examination grading score in the EGD examination (72.83 ± 16.12 vs. 67.26 ± 15.64, = 0.039), especially in the mucosa observation (26.40 ± 6.13 vs. 24.11 ± 6.21, = 0.020) and quality of collected images (7.29 ± 1.09 vs. 6.70 ± 1.05). The CAD showed a lower blind spot rate (2.19 ± 2.28 vs. 3.92 ± 3.30, = 0.008) compared with the control group. The artificial intelligence assistant system displayed assistant capacity on standard EGD training, and assisted trainees in achieving a learning curve with high operation quality, which has great potential for application. This trial is registered at https:/clinicaltrials.gov/, number NCT04682821.
在一项前瞻性随机对照试验中，研究计算机辅助系统对新手学员食管胃十二指肠镜检查（EGD）培训的影响。我们基于深度学习，利用回顾性图像构建了一个计算机辅助系统（CAD），该系统可以自动监测上消化道的26个解剖标志并记录标准照片。将六名新手学员分配并分组到CAD组和对照组。他们每个人都参加了培训课程、进行了前后测试，并由两名专家对EGD检查进行评分。CAD组在CAD系统的协助下进行培训，对照组则没有。两组在EGD技能方面都取得了很大进步。CAD组在EGD检查中获得了更高的检查评分（72.83±16.12 vs. 67.26±15.64，P = 0.039），尤其是在黏膜观察方面（26.40±6.13 vs. 24.11±6.21，P = 0.020）和采集图像质量方面（7.29±1.09 vs. 6.70±1.05）。与对照组相比，CAD显示出更低的盲点率（2.19±2.28 vs. 3.92±3.30，P = 0.008）。人工智能辅助系统在标准EGD培训中显示出辅助能力，并帮助学员实现了具有高操作质量的学习曲线，具有很大的应用潜力。该试验已在https:/clinicaltrials.gov/注册，编号为NCT04682821。
