摘要
宫颈癌(cervical cancer,CC)是我国女性癌症中第五大常见癌症,且发病有年轻化的趋势,严重威胁女性的生命健康。不同分期及风险者治疗方案不尽相同,随着保育手术普及,对术前精准分期和风险评估提出了更高的要求。MRI是CC诊断、分期和疗效评估的重要方法。但MRI常规序列对CC的诊断及评估受限于主观经验,且缺乏客观定量,准确性欠佳。MRI功能成像及定量成像等新技术,能提供血流动力学改变、组织微观结构的变化、肿瘤乏氧环境以及细胞增殖和蛋白代谢等多维度的精准定量信息,用于CC术前精准诊断和风险评估,为全面了解肿瘤的病理生理、代谢等提供可视化依据。借助人工智能技术挖掘影像大数据,有助于解决临床难题。本文将针对CC分期、疗效及是否复发评估等临床难题,综述MRI功能成像及定量成像在CC诊疗中的应用进展,以推动其临床应用,提升诊疗水平。
Cervical cancer(CC)is the fifth most common cancer among women in our country,and the incidence is tending to be younger,which seriously threatens the life and health of women.The treatment plans for different stages and risks are not the same,and with the popularization of fertility preserving surgical treatment,higher requirements are placed on accurate preoperative staging and risk assessment.Magnetic resonance imaging(MRI)is an important method for the diagnosis,staging and efficacy evaluation of CC.However,the diagnosis and evaluation of CC by conventional MRI sequences are limited by subjective experience and lack of objective quantification,resulting in poor accuracy.New technologies,such as MRI functional imaging and quantitative imaging,can provide accurate quantitative information in multiple dimensions,including hemodynamic changes,varies in tissue microstructure,tumor hypoxia environment,cell proliferation and protein metabolism,which can be used for accurate preoperative diagnosis and risk assessment of CC and provide a visual basis for the comprehensive understanding of the pathophysiology and metabolism of tumors.Mining big imaging data by artificial intelligence can help solve clinical problems.This article will review the application progress of MRI functional imaging and quantitative imaging in the diagnosis and treatment of CC,aiming at clinical problems such as the staging,efficacy and recurrence assessment of CC,so as to promote its clinical application and improve the level of diagnosis and treatment.
作者
张钦和
刘爱连
ZHANG Qinhe;LIU Ailian(Department of Radiology,The First Affiliated Hospital of Dalian Medcial University,Dalian 116011,China)
出处
《磁共振成像》
CAS
CSCD
北大核心
2024年第8期1-11,24,共12页
Chinese Journal of Magnetic Resonance Imaging
基金
大连医科大学附属第一医院院内基金项目(编号:2021HZ015)。
关键词
宫颈癌
磁共振成像
病理特征
分子病理
疗效
预后
影像组学
人工智能
深度学习
精准医疗
cervical cancer
magnetic resonance imaging
pathological features
molecular pathology
efficacy
prognosis
radiomics
artificial intelligence
deep learning
precision medicine
