CT影像组学在肺癌诊治中应用的研究进展和问题探索

Research Advances and Obstacles of CT-based Radiomics in Diagnosis and Treatment of Lung Cancer

影像组学是一种基于多模态医学影像处理分析的技术,该技术能够基于高性能计算机及算法从目前普遍使用的计算机断层扫描(computed tomography, CT)、磁共振图像(magnetic resonance imaging, MRI)和正电子发射/断层图像(positron emission tomography/computed tomography, PET/CT)中自动提取海量数据进行分析,对疾病的早期诊断、良恶性肿瘤鉴别、疾病治疗全程管理,个体化精准治疗等需求提供更多有价值信息。近年来,许多研究表明基于CT的影像组学技术在肺癌的早期诊断、基因表型预测、疗效预测及预后评估均有良好的应用价值,且影像学检查具有无创、经济、可重复等优势。其对临床的指导价值已有所展露,在肺癌的个体化、精准化治疗和研究方面具有较大价值,但是,影像组学特征的重复性和一致性问题以及在肺部肿瘤图像提取中的特征筛选还需进一步研究。

Radiomics, a technology based on multimodal medical image processing and analysis, is able to extract automatically and analyze massive data from computed tomography(CT), magnetic resonance imaging(MRI), positron emission tomography/computed tomography(PET/CT) via high-performance computer algorithm in order to pursue early diagnosis of disease, benign and malignant tumor discrimination, dynamic evaluation of disease treatment, and individualized precision therapy. To date, many studies demonstrate that radiomics not only has great potential in early diagnosis of lung cancer and prediction of genotype, treatment efficacy, as well as prognosis but also is based on imaging methods that are noninvasive, inexpensive, and repeatable. It does demonstrate precious values in guiding the clinical diagnosis and treatment of lung cancer, especially in the personalized and precise treatments and researches of lung cancer. However, the consistency and reproducibility of radiomics and the selection of robust characteristics still warrant further researches.