Comprehensive Computed Tomography Radiomics Analysis of Lung Adenocarcinoma for Prognostication

Background In this era of personalized medicine, there is an expanded demand for advanced imaging biomarkers that reflect the biology of the whole tumor. Therefore, we investigated a large number of computed tomography‐derived radiomics features along with demographics and pathology‐related variables in patients with lung adenocarcinoma, correlating them with overall survival. Materials and Methods Three hundred thirty‐nine patients who underwent operation for lung adenocarcinoma were included. Analysis was performed using 161 radiomics features, demographic, and pathologic variables and correlated each with patient survival. Prognostic performance for survival was compared among three models: (a) using only clinicopathological data; (b) using only selected radiomics features; and (c) using both clinicopathological data and selected radiomics features. Results At multivariate analysis, age, pN, tumor size, type of operation, histologic grade, maximum value of the outer 1/3 of the tumor, and size zone variance were statistically significant variables. In particular, maximum value of outer 1/3 of the tumor reflected tumor microenvironment, and size zone variance represented intratumor heterogeneity. Integration of 31 selected radiomics features with clinicopathological variables led to better discrimination performance. Conclusion Radiomics approach in lung adenocarcinoma enables utilization of the full potential of medical imaging and has potential to improve prognosis assessment in clinical oncology. Implications for Practice Two radiomics features were prognostic for lung cancer survival at multivariate analysis: (a) maximum value of the outer one third of the tumor reflects the tumor microenvironment and (b) size zone variance represents the intratumor heterogeneity. Therefore, a radiomics approach in lung adenocarcinoma enables utilization of the full potential of medical imaging and could play a larger role in clinical oncology. This article reports a comprehensive analysis of a large number of chest computed tomographyderived radiomics features, along with demographic characteristics and pathology‐related variables in patients with lung adenocarcinoma, and correlates them with overall survival to capture the clinical potential of the radiomics approach in the field of oncology. 摘要 背景.在这个个性化医学时代,对能够反映整体肿瘤生物学的先进影像学生物标记物的需求不断扩大。因此,我们研究了肺腺癌患者的大量源于计算机断层扫描的影像组学特征,以及与人口统计学和病理学相关的变量,并将其与总生存期联系起来。 材料与方法.共纳入339例肺腺癌手术患者。使用161个影像组学特征、人口统计学和病理变量进行分析,并将每一项指标与患者生存情况