Radiogenomics is a recent promising field in cancer research focusing on associating genomic data with radiographic imaging phenotypes. This study is initiated to establish the mapping between quantitative characteristics of CT images and gene expression data, based on publically available dataset that includes 26 non-small cell lung cancer (NSCLC) patients. On one hand, a set of 66 features are extracted to quantify the phenotype of tumors after segmentation. On the other hand, co-expressed genes are clustered and are biologically annotated that are represented by metagenes, namely the first principal component of clusters. Finally, statistical analysis is performed to assess relationship between CT imaging features and metagenes. Furthermore, a predictive model is built to evaluate NSCLC radiogenomics performance. Experiment show that there are 126 significant and reliable pairwise correlations which suggest that CTbased features are minable and can reflect important biological information of NSCLC patients.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.