基于人工智能平台直肠癌新辅助治疗效果评估系统外科临床应用专家共识(2022版)  

Expert consensus on the surgical clinical application of rectal cancer neoadjuvant therapy effect evaluation system based on artificial intelligence platform(2022 edition)

作　　者：中华医学会外科学分会结直肠外科学组 北京航空航天大学虚拟现实技术与系统国家重点实验室 张忠涛[2] 郝爱民[3] 卢云[4] 李帅[5] 高源[4] Colorectal Surgery Group of the Surgery Branch in the Chinese Medical Association;Beihang University State Key Laboratory of Virtual Reality Technology and Systems;Zhang Zhongtao;Hao Aimin(不详;Depertment of General Surgery,Bejing Friendship Hospital,Capital Medical University,National Clinical Research Center of Digestive Disease,Beijing 100050,China;Beihang University State Key Laboratory of Virtual Reality Technology and Systems,Bejing 100191,China)

机构地区：[1]不详 [2]首都医科大学附属北京友谊医院普外科国家消化系统疾病临床医学研究中心,北京100050 [3]北京航空航天大学虚拟现实技术与系统国家重点实验室,北京100191 [4]青岛大学附属医院 [5]北京航空航天大学

出　　处：《中华外科杂志》2022年第8期732-735,共4页Chinese Journal of Surgery

摘　　要：新辅助治疗是进展期直肠癌治疗体系的重要组成部分, 目前评价新辅助治疗效果的主要手段是MRI。为了缓解我国影像科医师相对缺乏的现状, 中华医学会外科学分会结直肠外科学组联合北京航空航天大学虚拟现实技术与系统国家重点实验室, 参考目前利用人工智能自动识别系统协助直肠癌新辅助治疗效果评估的相关研究, 提出基于人工智能平台的直肠癌新辅助治疗效果评估系统的外科临床应用专家共识, 以期引导该技术的规范应用, 提高影像学阅片的效率和准确性。Neoadjuvant therapy plays an important role in the treatment system of advanced rectal cancer.At present,the main method to evaluate the effect of neoadjuvant therapy is MRI.In order to alleviate the relative lack of radiologist,Colorectal Surgery Group of the Surgery Branch in the Chinese Medical Association,along with Beihang University State Key Laboratory of Virtual Reality Technology and Systems,refer to the current research on the use of artificial intelligence automatic identification system to assist the evaluation of neoadjuvant therapy effect for rectal cancer,the expert consensus on surgical clinical application of the effect evaluation system of neoadjuvant therapy for rectal cancer based on artificial intelligence platform was proposed,in order to guide the standard application of this technology and improve the efficiency and accuracy of image reading.

关 键 词：直肠肿瘤 人工智能 新辅助治疗 深度学习 

分 类 号：R735.37[医药卫生—肿瘤]