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基于磁共振成像的影像组学在肺癌中的研究进展 被引量:1

Research progress of MRI based radiomics in lung cancer
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摘要 计算机断层扫描(computed tomography,CT)、正电子发射断层扫描和磁共振成像(magnetic resonance imaging,MRI)等技术在肺癌诊断、分期、治疗、术后监测和反应评估等方面具有重要意义,提供了肺癌表型的解剖和功能信息,但仍有大量的遗传和预后信息未被揭示。影像组学可深度挖掘高维数据,反映病变的分子表达和基因表达等深层生物学信息,有助于肺癌预后评估和疗效评估等精准预测。过去,肺癌影像组学常基于CT图像展开研究。随着肺部MRI技术的不断进步,其软组织分辨率得到显著提高,因此MRI也开始被广泛应用于肺癌影像组学研究。本文将从MRI肺癌影像组学的模型构建以及影像组学在肺癌鉴别、分型、病理分级、基因表达等方面进行介绍,并阐述当前肺部MRI影像组学的局限性与展望,以期为肺癌临床精准诊疗提供新的方法,促进影像组学研究的临床应用。 Technologies such as computed tomography(CT),positron emission tomography,and magnetic resonance imaging(MRI)play an important role in the diagnosis,staging,treatment,postoperative monitoring,and response evaluation of lung cancer,providing anatomical and functional information about the phenotype of lung cancer.However,a large amount of genetic and prognostic information remains undiscovered.Radiomics can deeply mine high-dimensional data,reflecting deep biological information such as molecular and gene expression of lesions,which can help in the accurate prediction of lung cancer prognosis and treatment efficacy.In the past,lung cancer radiomics studies were mainly based on CT images.With the continuous improvement of lung MRI technology and its significant increase in soft tissue resolution,magnetic resonance imaging has also been widely used in lung cancer radiomics research.This article will introduce the model construction of MRI lung cancer radiomics and the application of radiomics in lung cancer differentiation,classification,pathological grading,gene expression,etc.,and discuss the current limitations and prospects of lung MRI radiomics,in order to provide new methods for the precise diagnosis and treatment of lung cancer and promote the clinical application of radiomics research.
作者 江叶海 蒲豆豆 于楠 JIANG Yehai;PU Doudou;YU Nan(School of Medical Technology,Shaanxi University of Chinese Medicine,Xianyang 712046,China;Department of Medical Imaging,Affiliated Hospital of Shaanxi University of Chinese Medicine,Xianyang 712000,China)
出处 《磁共振成像》 CAS CSCD 北大核心 2023年第7期166-170,共5页 Chinese Journal of Magnetic Resonance Imaging
基金 陕西省重点研发计划项目(编号:2021ZDLSF04-10) 陕西省自然科学基础研究计划(编号:2022JM-453) 国家级大学生创新创业训练计划(编号:202210716013)。
关键词 磁共振成像 影像组学 肺癌 肺结节 特征提取 基因表型 病理分级 magnetic resonance imaging radiomics lung cancer pulmonary nodules feature extraction gene phenotype pathological grade
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