文献类型：期刊文献

中文题名：人工智能联合影像技术在转移性颈部淋巴结检测中的应用进展

英文题名：Advancements in the integration of artificial intelligence and imaging technology for the detection of metastatic cervical lymph nodes

作者：陈莉军[1,2];王冰[3];王琳[4]

第一作者：陈莉军

机构：[1]甘肃中医药大学第一临床医学院,兰州730000;[2]甘肃省人民医院放射科,兰州730050;[3]白银市第一人民医院骨科,白银730900;[4]甘肃中医药大学附属医院放射科,兰州730000

第一机构：甘肃中医药大学临床医学院

年份：2025

卷号：16

期号：11

起止页码：209

中文期刊名：磁共振成像

外文期刊名：Chinese Journal of Magnetic Resonance Imaging

收录：;北大核心:【北大核心2023】；

基金：甘肃省科技计划项目(编号:25JRRD002);甘肃省人民医院院内项目(编号:20GSSY3-9)。

语种：中文

中文关键词：头颈部肿瘤;淋巴结转移;人工智能;深度学习;影像技术;磁共振成像

外文关键词：head and neck neoplasms;lymph node metastasis;artificial intelligence;deep learning;imaging technology;magnetic resonance imaging

摘要：转移性颈部淋巴结(metastatic cervical lymph nodes,MCLN)在众多头颈部肿瘤的诊断分期和临床决策制订中至关重要。传统的CT、MRI、PET-CT等影像学检查虽普遍应用于临床中,但在精准区分MCLN的敏感性和特异性较差。人工智能(artificial intelligence,AI)近两年迅速发展,尤其是深度学习(deep learning,DL)在医学影像分析方面取得了突破性成就。本文对不同模态影像技术联合AI(CT增强配以自动分割、MRI高软组织对比结合自动分割、PET-CT代谢图像融合AI模型、超声结合DL的实时自动辅助诊断等)在头颈部MCLN的最新研究进行概括性综述,阐述了AI在MCLN诊断和疗效和预后评估中的应用,总结目前研究中存在的不足及技术困境,并提出未来的发展方向。本综述旨在为未来研究协同、模型优化及临床应用提供参考。
Metastatic cervical lymph nodes(MCLN)are crucial in the diagnosis,staging,and clinical decision-making processes for various head and neck tumors.Despite the widespread use of conventional imaging modalities such as computed tomography(CT),magnetic resonance imaging(MRI),and positron emission tomography-computed tomography(PET-CT)in clinical practice,their sensitivity and specificity in accurately identifying all instances of MCLN remain suboptimal.In recent years,artificial intelligence(AI),and deep learning(DL)in particular,have made significant advancements in the field of medical image analysis.This review provides a comprehensive review of the latest research on the combined use of different modal imaging techniques and AI(CT enhancement combined with automatic segmentation,MRI high soft tissue contrast combined with automatic segmentation,PET-CT metabolic image fusion AI model,ultrasound combined with DL for real-time automatic auxiliary diagnosis,etc.)in head and neck MCLN.It elaborates on the application of AI in the diagnosis,therapeutic effect and prognosis assessment of MCLN,summarizes the existing shortcomings and technical challenges in current research,and proposes future development directions.This review aims to provide a reference for future research collaboration,model optimization and clinical application.