西安交通大学学报（医学版）2026，Vol.47Issue(3)：447-454,8.DOI:10.7652/jdyxb202603007
人工智能联合多模态成像构建肝内胆管癌淋巴结转移精准外科诊疗新体系
Artificial intelligence combined with multimodal imaging in establishing a new precision surgical diagnosis and treatment system for lymph node metastasis in intrahepatic cholangiocarcinoma
摘要
Abstract
Intrahepatic cholangiocarcinoma(ICC),as a primary liver malignancy,has a lower incidence than hepatocellular carcinoma(HCC).However,its prognosis is extremely poor,with a recurrence rate of over 60%within five years after radical resection.Lymph node metastasis(LNM)is a key factor leading to recurrence and low survival rates.Currently,there are significant controversies regarding the clinical application of intraoperative lymphadenectomy(LND)for ICC.Routine LND may increase surgical risks and affect the efficacy of immunotherapy.The implementation of selective LND urgently requires accurate preoperative prediction of LNM and intraoperative lymph node visualization techniques.Nevertheless,traditional imaging methods(such as CT and MRI)have insufficient sensitivity and specificity for LNM(sensitivity:45%-50%,specificity:86.4%-88%),making it difficult to meet the needs of precise diagnosis and treatment.This paper focuses on constructing a research framework to solve this problem by integrating artificial intelligence and novel imaging technologies.In preoperative diagnosis,through radiomics,habitat analysis,and deep-learning models(such as CNN and Transformer),tumor heterogeneity features and lymph node metastasis risk markers are extracted from multimodal images to build a high-precision LNM prediction system.Through the full-process technical integration of"preoperative AI prediction-intraoperative precise visualization",the"selective LND"strategy is proposed.This strategy aims to provide a basis for precise lymph node dissection in patients at high risk of LNM while avoiding excessive surgical damage to low-risk patients,ultimately optimizing the individualized treatment decision-making for ICC.This paper further explores the application potential of multidisciplinary cross-cutting technologies(imaging medicine,artificial intelligence,and molecular probe design)in breaking through the bottleneck of LNM diagnosis,providing theoretical support and technical approaches for improving the precision of ICC surgical treatment and patient prognosis.关键词
肝内胆管癌/淋巴结转移/影像组学/深度学习/近红外二区成像/选择性淋巴结清扫Key words
intrahepatic cholangiocarcinoma/lymph node metastasis/radiomics/deep learning/near-infrared II imaging/selective lymphadenectomy分类
医药卫生引用本文复制引用
王傅民,任耀星,韩大为,陆镜明,吕毅,张谞丰..人工智能联合多模态成像构建肝内胆管癌淋巴结转移精准外科诊疗新体系[J].西安交通大学学报（医学版）,2026,47(3):447-454,8.基金项目
国家自然科学基金国际(地区)合作与交流项目(No.W2511094)Supported by International(Regional)Cooperation and Exchange Project of the National Natural Science Foundation of China(No.W2511094) （地区）
