影像组学在非小细胞肺癌精准治疗中的应用进展

影像组学（radiomics）是通过对CT、MRI、PET等医学影像感兴趣区域提取数百个定量影像特征，对这些特征进行筛选、分析，用于描述肿瘤生物学特征和异质性等信息的一种高通量定量分析方法。它在非小细胞肺癌（NSCLC）的精准治疗中具有较大潜在应用价值，可用于肺结节良、恶性淋巴结转移、肿瘤基因表型等生物学特性判定，以及肿瘤对治疗的反应性、预后及放射性肺损伤的预测，为个体化治疗提供客观依据。Radiomics具有无创、在体、动态、定量、高通量、性价比高和易借助互联网发展的特点，有望在今后的肺癌精准治疗中发挥更大作用。目前需建立标准的研究流程，用多中心研究验证其可靠性和临床应用价值。

Progress on application of radiomics in precise treatment of non-small cell lung cancer

Radiomics utilizes the high-throughput extraction of large amounts of quantitative features from radiographic images, giving a comprehensive quantification of tumor phenotype. Thus it can provide complementary and interchangeable information for clinical usage, such as differentiating malignant nodules from benign ones, predicting response to treatment, identifying lymph node metastasis, improving individualized treatment selection and monitoring. The advantages of radiomics give it great potential in precise treatment. But much work needs to be done before it could be used in practice. It is imperative that a standard research procedure is needed to verify its reliability and clinical value via multi-central prospective clinical trials.