CT影像组学在鉴别诊断良恶性肺结节中的应用进展

Progress of Application of CT Imaging Omics in Differential Diagnosis of Benign and Malignant Pulmonary Nodules

肺癌是全球死亡率最高的恶性肿瘤,严重危害人类健康。肺癌的早期检测是通过鉴别肺结节实现的。为了提高早期肺结节良恶性诊断的准确性与高效性,人们创造了基于大数据与医学影像学的医工结合产物—影像组学。影像组学作为新兴技术,应用各种算法,从CT、PET或MRI等医学影像图像中提取高通量的影像学特征并进行分析,构建预测模型。分析了影像组学的基本流程,综述了影像组学在良恶性肺结节鉴别、淋巴结转移状态预测等方面的发展。研究表明,影像组学在准确度、灵敏度、特异度、临床效益等方面均表现出很高的水平,说明其在良恶性肺结节鉴别中具有很大的应用潜力,发展前景广阔,未来可广泛应用于临床影像诊断中。

Lung cancer is the malignant tumor with the highest mortality rate in the world,which seriously endangers human health.Early detection of lung cancer is achieved by pulmonary nodules.To improve the accuracy and efficiency of early pulmonary nodule screening,a combined imaging technology is created.As an emerging development technology,imaging omics refers to the application of various algorithms to extract and analyze high-throughput imaging features from medical imaging images,such as CT,PET or MRI,etc.The study analyzes the basic process of imaging omics,and summarizes the development of the differentiation of benign and malignant pulmonary nodules,lymph node metastasis prediction related research,etc.It is found that imaging omicshave shown high level in accuracy,sensitivity,specificity and clinical benefit,etc.,indicating great application potential in differential diagnosis of benign and malignant pulmonary nodules,and wide prospect.It can be widely applied in clinical diagnostic imaging.