This subset of NSCLC Radiogenomics contains images from patients with non-small cell lung cancer (NSCLC) imaged prior to surgical excision with both thin-section computed tomography (CT) and whole body positron emissions tomography (PET)/CT scans acquired under Institutional Review Board approval from Stanford University and the Veterans Administration Palo Alto Health Care System. The first installment of 26 cases (see shared list "NSCLC Radiogenomics: Initial Stanford Study of 26 Cases") corresponds to microarray data acquired from the excised samples, which is available on the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus , where Digital Imaging and Communications in Medicine (DICOM) patient names are identical to microarray sample names. For scientific inquiries relating to the data-set, please contact Drs. Sandy Napel ( firstname.lastname@example.org ) or Sylvia K. Plevritis ( email@example.com ).
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The original 26 cases referenced in this manuscript have been renamed. A list of the mapping between GSM-XXX Patient IDs and R01-XXX Patient IDs can be found here .
Citations & Data Usage PolicyUsers of this data must abide by the Creative Commons Attribution 3.0 Unported License under which it has been published. Attribution should include references to the following citations:
Napel, Sandy, & Plevritis, Sylvia K. (2014). NSCLC Radiogenomics: Initial Stanford Study of 26 Cases. The Cancer Imaging Archive. http://doi.org/10.7937/K9/TCIA.2014.X7ONY6B1
Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. (paper)
In addition to the dataset citation above, please be sure to cite the following if you utilize these data in your research:
Gevaert, O., Xu, J., Hoang, C. D., Leung, A. N., Xu, Y., Quon, A., … Plevritis, S. K. (2012, August). Non–Small Cell Lung Cancer: Identifying Prognostic Imaging Biomarkers by Leveraging Public Gene Expression Microarray Data—Methods and Preliminary Results. Radiology. Radiological Society of North America (RSNA). http://doi.org/10.1148/radiol.12111607