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All the images are diagnostic contrast enhanced CT scans. The images were retrospectively acquired, to ensure sufficient patient follow-up. Slice thickness is variable : between 3 and 6 mm. All images were done at diagnosis and prior to surgery. The objective of the study was to extract prognostic image features that will describe lung adenocarcinomas and will associate with overall survival. More information is available in the related publication (see Citation tab below).
We would like to acknowledge the individual and institution that have provided data for this collection:
- Moffitt Cancer Center (Tampa Florida) - Special thanks to Olya Stringfield, PhD from the Department of Cancer Imaging and Metabolism.
Choosing the Download option will provide you with a file to launch the TCIA Download Manager to download the entire collection. If you want to browse or filter the data to select only specific scans/studies please use the Search By Collection option.
|Data Type||Download all or Query/Filter|
|Images (DICOM, 2.5GB)|
|Representative Tumor Slices (XLS)|
|Clinical Data (DOC)|
Click the Versions tab for more info about data releases.
Number of Patients
Number of Studies
Number of Series
Number of Images
|Images Size (GB)||2.5|
TCIA DICOM Subject ID, SOP Instance UID, Instance Number, and Image Position (Patient) X-Y-Z are noted in Representative-Tumor-Slices.xlsx
The accompanying data are survival data (status: dead or alive, survival time in months) and pathological stage (TNM).
Citations & Data Usage Policy
This collection is freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License. See TCIA's Data Usage Policies and Restrictions for additional details. Questions may be directed to email@example.com.
Please be sure to include the following citations in your work if you use this data set:
Olya Grove, Anders E. Berglund, Matthew B. Schabath, Hugo J.W.L. Aerts, Andre Dekker, Hua Wang, Emmanuel Rios Velazquez, Philippe Lambin, Yuhua Gu, Yoganand Balagurunathan, Edward Eikman, Robert A. Gatenby, Steven Eschrich, Robert J. Gillies; (2015): Data from: Quantitative computed tomographic descriptors associate tumor shape complexity and intratumor heterogeneity with prognosis in lung adenocarcinoma; The Cancer Imaging Archive. http://dx.doi.org/10.7937/K9/TCIA.2015.A6V7JIWX
Quantitative computed tomographic descriptors associate tumor shape complexity and intratumor heterogeneity with prognosis in lung adenocarcinoma. Grove O, Berglund AE, Schabath MB, Aerts HJ, Dekker A, Wang H, Velazquez ER, Lambin P, Gu Y, Balagurunathan Y, Eikman E, Gatenby RA, Eschrich S, Gillies RJ. PLoS One. 2015 Mar 4;10(3):e0118261. http://dx.doi.org/10.1371/journal.pone.0118261. eCollection 2015.
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)
Other Publications Using This Data
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