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胸腺瘤CT影像组学研究进展

Research Progress in CT Radiomics of Thymomas
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摘要 胸腺瘤近年来在我国的发病率呈逐渐上升的趋势,术前早期准确判断胸腺瘤的危险分类可以影响治疗计划并改善临床预后,以及预测术后复发风险。传统的影像学诊断是利用形态学基础及诊断医生的临床经验进行诊断,难以准确区分肿瘤风险分类,已经不能达到生物个体的精准影像医学的标准。影像组学则是对医学影像图像进行高通量特征空间数据信息提取,着眼于临床问题构建预测模型,从而可以无创地量化肿瘤异质性,旨在根据患者个体及其肿瘤的特征量身定制治疗方案。本文就CT影像组学在胸腺瘤中的应用研究进展进行综述。 In recent years,the incidence rate of thymoma in China has been increasing gradually.Early preoperative accurate judgment of the risk classification of thymoma can affect the treatment plan and improve the clinical prognosis,as well as predict the risk of postoperative recurrence.The traditional imaging diagnosis is based on the morphological basis and the clinical experience of the diagnostician,and it is difficult to accurately distinguish tumor risk classification and cannot meet the standards of precision imaging medicine for biological individuals.Radiomics is the extraction of high-throughput characteristic spatial data information from medical images,and the construction of prediction models focusing on clinical problems,so as to noninvasively quantify tumor heterogeneity,aiming to tailor treatment plans according to the characteristics of individual patients and their tumors.This paper reviewed the research and application of radiomics in thymomas.
作者 杜梦颖 杨峰 DU Mengying;YANG Feng(Department of Radiology,Xiangyang No.1 People’s Hospital Affiliated to Hubei University of Medicine,Xiangyang Hubei 441011,China)
出处 《中国医疗设备》 2024年第4期159-163,共5页 China Medical Devices
基金 2023年襄阳市第一人民医院科技创新项目(XYY2023SD18)。
关键词 胸腺瘤 影像组学 机器学习 体层摄影术 X线计算机 thymoma radiomics machine learning tomography X-ray computed
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