人工智能在胸外科规范化培训教学中肺结节分析与肺段切除规划的应用效果研究  

Application of artificial intelligence in pulmonary nodule analysis and lung segment resection planning for standardized training in thoracic surgery

作　　者：高超 周小昀[1] 郭超[1] 刘洪生[1] 李单青 梁乃新[1] GAO Chao;ZHOU Xiaoyun;GUO Chao;LIU Hongsheng;LI Shanqing;LIANG Naixin(Department of Thoracic Surgery,Peking Union Medical College Hospital,Chinese Academy of Medical Sciences,Beijing,100730,P.R.China)

机构地区：[1]中国医学科学院北京协和医院胸外科,北京100730

出　　处：《中国胸心血管外科临床杂志》2025年第4期469-472,共4页Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

摘　　要：目的探讨人工智能(artificial intelligence,AI)在胸外科住院医师规范化培训中的应用,特别是通过AI辅助肺结节识别和肺段解剖教学,提升医师的临床技能和解剖理解。方法本研究选取2023年9月—2024年9月在北京协和医院进行胸外科规范化培训的住院医师,采用随机数字表法将其随机分为试验组和对照组。试验组使用AI辅助的三维重建技术进行肺结节识别,而对照组仅使用常规胸部CT图像。在进行基础教学和自主练习后,评估两组对相同患者CT图像的肺结节识别能力,最后通过问卷调查收集反馈。结果本研究共纳入72名住院医师,其中男30人(41.7%)、女42人(58.3%),平均年龄为(24.0±3.0)岁。试验组在肺结节的总体诊断准确性(91.9%vs.73.3%)和肺段标识(100.0%vs.83.7%)方面均显著优于对照组,且阅片时间显著缩短[(118.5±10.5)s vs.(332.1±20.2)s,P<0.01]。问卷结果显示,94.4%的住院医师对AI技术持积极态度,91.7%认为其能够提高诊断的准确性。结论AI辅助教学显著提升了胸外科住院医师的阅片能力和临床思维,为规范化培训改革提供了新的方向。Objective To explore the application of artificial intelligence(AI)in the standardized training of thoracic surgery residents,specifically in enhancing clinical skills and anatomical understanding through AI-assisted lung nodule identification and lung segment anatomy teaching.Methods Thoracic surgery residents undergoing standardized training at Peking Union Medical College Hospital from September 2023 to September 2024 were selected.They were randomly assigned to a trial group and a control group using a random number table.The trial group used AI-assisted three-dimensional reconstruction technology for lung nodule identification,while the control group used conventional chest CT images.After basic teaching and self-practice,the ability to identify lung nodules on the same patient CT images was evaluated,and feedback was collected through questionnaires.Results A total of 72 residents participated in the study,including 30(41.7%)males and 42(58.3%)females,with an average age of(24.0±3.0)years.The trial group showed significantly better overall diagnostic accuracy for lung nodules(91.9%vs.73.3%)and lung segment identification(100.0%vs.83.70%)compared to the control group,and the reading time was significantly shorter[(118.5±10.5)s vs.(332.1±20.2)s,P<0.01].Questionnaire results indicated that 94.4%of the residents had a positive attitude toward AI technology,and 91.7%believed that it improved diagnostic accuracy.Conclusion AI-assisted teaching significantly improves thoracic surgery residents’ability to read images and clinical thinking,providing a new direction for the reform of standardized training.

关 键 词：人工智能 胸外科 肺结节 肺段解剖 教学 

分 类 号：R655[医药卫生—外科学]