OBJECTIVE Radiogenomics investigates radiographic imaging phenotypes associated with gene expression patterns. This study aims to explore relationships between CT imaging radiomics features and gene expression data in non-small cell lung cancer (NSCLC). METHODS Eighty-nine NSCLC patients are included in the study. Radiomics features are extracted and selected to quantify the phenotype of tumors on CT-scans. Co-expressed genes are also clustered and the first principal component of the cluster is represented, which is defined as a metagene. Then, statistical analysis was performed to assess association of CT radiomics features with metagenes. In addition, predictive models are built and metagene enrichment are conducted to further evaluate performance of NSCLC radiogenomics statistically and biologically. RESULTS There are 187 significant pairwise correlations between a CT radiomics feature and a metagene of NSCLC, where eighteen metagenes are annotated with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms. Metagenes are predicted in terms of radiomics features with an accuracy of 41.89% -89.93%. CONCLUSIONS This study reveals the associations between CT imaging radiomics features and NSCLC co-expressed gene sets. The findings suggest that CT radiomics features can reflect important biological information of NSCLC patients, which may have a significant clinical impact as CT is routinely used in clinical practice, assisting in improving medical decision-support at low cost.

中文翻译：

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非小细胞肺癌中基于CT的放射学特征与基因表达数据之间的相关性。

目的放射基因组学研究与基因表达模式相关的放射成像表型。本研究旨在探讨非小细胞肺癌（NSCLC）中CT成像放射学特征与基因表达数据之间的关系。方法本研究包括89例NSCLC患者。提取并选择Radiomics特征以量化CT扫描上肿瘤的表型。共表达的基因也被聚类并且代表该聚类的第一个主要成分，其被定义为元基因。然后，进行统计分析以评估CT放射学特征与元基因的关联。此外，建立了预测模型并进行了基因表达富集，以进一步从统计学和生物学角度评估NSCLC放射基因组学的性能。结果CT放射学特征与NSCLC的一个基因之间存在187个显着的成对相关性，其中18个基因用基因本体论（GO）和《京都基因与基因组百科全书》（KEGG）标注。根据放射组学特征预测元基因，其准确性为41.89％-89.93％。结论这项研究揭示了CT成像放射学特征与NSCLC共表达基因集之间的关联。研究结果表明，CT放射学特征可以反映NSCLC患者的重要生物学信息，这可能对临床产生重大影响，因为CT通常用于临床实践中，有助于以低成本改善医疗决策支持。其中18个元基因用基因本体论（GO）和《京都基因与基因组百科全书》（KEGG）进行注释。根据放射组学特征预测元基因，其准确性为41.89％-89.93％。结论这项研究揭示了CT成像放射学特征与NSCLC共表达基因集之间的关联。研究结果表明，CT放射学特征可以反映NSCLC患者的重要生物学信息，这可能对临床产生重大影响，因为CT通常用于临床实践中，有助于以低成本改善医疗决策支持。其中18个元基因用基因本体论（GO）和《京都基因与基因组百科全书》（KEGG）进行注释。根据放射组学特征预测元基因，其准确性为41.89％-89.93％。结论这项研究揭示了CT成像放射学特征与NSCLC共表达基因集之间的关联。研究结果表明，CT放射学特征可以反映NSCLC患者的重要生物学信息，这可能对临床产生重大影响，因为CT通常用于临床实践中，有助于以低成本改善医疗决策支持。