肝細胞癌の層別化のためのRadiomics特徴量と遺伝子発現の関係分析

抄録

For hepatocellular carcinoma, complicated stratifications and treatment methods have being studied. However,the 5-year survival rate of hepatocellular carcinoma in stage I is 60.4%, which is lower than that for breast cancer or lung cancer. The purpose of this study is to investigate whether radiomic feature and gene expression are useful for stratifying the prognosis of hepatocellular carcinoma. From a public database TCGA-LIHC（The Cancer Genome Atlas Liver Hepatocellular Carcinoma）, contrast-enhanced CT images and gene expression levels of 19 cases, including 11 cases were death 2 years later, were selected for this study. 5 radiomic features and 5 genes were selected by Lasso, and hepatocellular carcinomas were stratified using principal coordinate analysis and clustering. In addition, we analyzed the relationship between radiomic feature and gene expression using canonical correlation analysis. Experimental results showed that gene expression was more useful for stratifying hepatocellular carcinomas than radiomic feature. However, since the canonical correlation analysis can be applied to search for radiomic features that are complementary to gene data, we believe that the proposed method is an important technique in considering the division of roles between image and gene examinations in the future.