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肿瘤异质性与影像组学模型

已有 81 次阅读2020-10-27 17:21 |个人分类:临床预测模型学习|系统分类:医学科学

Tumor's stage is the rule in the management of lung cancer, however even in patient with the same stage a different clinical behavior can been seen

In addition to the anatomic extend of the lesion other factors related to the patient, tumor histology or “habitat” determine prognosis

肿瘤分期是肺癌治疗的原则,但即使在同一阶段的病人中也可以看到不同的临床表现

除了病变的解剖范围与病人有关外,肿瘤的组织学或“生境”决定预后

Microenvironment and neoplastic cells interaction leads to adaptive genetic/phenotypic mutations in neoplastic tissue, determining tumor heterogeneity

微环境和肿瘤细胞相互作用导致肿瘤组织中适应性基因/表型突变,决定肿瘤的异质性

Generally more heterogeneous tumors tend to be more aggressive and to be associated with poorer outcomes

一般来说,异质性更强的肿瘤往往更具侵袭性,且预后较差

Multifactorial predictive models are mandatory to obtain the so-called “PERSONALIZED MEDICINE”

多因素预测模型是必须的,才能获得所谓的“个性化治疗”

Medical image is partly determined by tumor phenotype and genotype,imaging features and heterogeneity could provide information about tumor structure

医学图像部分取决于肿瘤的表型和基因型,影像学特征和异质性可以提供肿瘤结构的信息

Radiomics refers to the extraction of quantitative image features from standard-of-care medical imaging, their analysis and modelling in relation to

prediction targets such as clinical and genomic endpoints

影像组学是指从标准医疗影像中提取定量图像特征,并对其进行分析和建模,以预测目标,如临床和基因组终点

Imaging data can be analyzed with others “omics” or clinical information

multidisciplinary clinical-decision support systems can be obtained

影像数据可以用其他“组学”或临床分析信息.多学科可以获得临床决策支持系统


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