Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

This data applies a radiomic approach to computed tomography data of 1,019 patients with lung or head-and-neck cancer which are described in Nature Communications (<a href="http://doi.org/10.1038/ncomms5006">http://doi.org/10.1038/ncomms5006</a>).  The various arms of the study are represented in TCIA as distinct Collections including <a href="https://www.cancerimagingarchive.net/collection/nsclc-radiomics">NSCLC-Radiomics</a> (Lung1), <a href="https://cancerimagingarchive.net/collection/nsclc-radiomics-genomics/" target="_blank" rel="noopener">NSCLC-Radiomics-Genomics</a> (Lung3), <a href="https://www.cancerimagingarchive.net/collection/head-neck-radiomics-hn1/">Head-Neck-Radiomics-HN1</a> (H&N1), <a href="https://cancerimagingarchive.net/collection/nsclc-radiomics-interobserver1/" target="_blank" rel="noopener">NSCLC-Radiomics-Interobserver1</a> (Multiple delineation), and <a href="https://cancerimagingarchive.net/analysis-result/rider-lungct-seg/" target="_blank" rel="noopener">RIDER-LungCT-Seg</a> (RIDER test/retest).Radiomics refers to the comprehensive quantification of tumour phenotypes by applying a large number of quantitative image features. In present analysis 440 features quantifying tumour image intensity, shape and texture, were extracted. We found that a large number of radiomic features have prognostic power in independent data sets, many of which were not identified as significant before. Radiogenomics analysis revealed that a prognostic radiomic signature, capturing intra-tumour heterogeneity, was associated with underlying gene-expression patterns. These data suggest that radiomics identifies a general prognostic phenotype existing in both lung and head-and-neck cancer. This may have a clinical impact as imaging is routinely used in clinical practice, providing an unprecedented opportunity to improve decision-support in cancer treatment at low cost.

本数据集采用放射组学方法，对1,019例肺癌或头颈癌患者的计算机断层扫描数据进行了分析，相关研究发表在《自然通讯》杂志（http://doi.org/10.1038/ncomms5006）。研究中的不同分支在TCIA中表现为独立的集合，包括<a href=