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QIN-LUNG-CT

QIN LUNG CT | QIN LUNG CT

DOI: 10.7937/K9/TCIA.2015.NPGZYZBZ | Data Citation Required | Image Collection

Location Species Subjects Data Types Cancer Types Size Status Updated
Lung Human 47 CT Non-small Cell Lung Cancer 2.08GB Public, Complete 2017/07/31

Summary

The Computed tomography (CT) Image data was obtained on patients diagnosed with Non-Small Cell Lung Cancer (NSCLC) with mixed stage & histology from the H. Lee Moffitt Cancer Center and Research Institute. Scans were obtained from patients who underwent surgical resection and had corresponding pre-surgery diagnostic CTs. The scans were de-identified following HIPAA guidelines to protect patient privacy. The data was shared with the QIN collaborators for research purpose complying with collaborative data sharing policy of the H. Lee Moffitt Total Cancer Care (TCC) .

About the NCI QIN

The mission of the QIN is to improve the role of quantitative imaging for clinical decision making in oncology by developing and validating data acquisition, analysis methods, and tools to tailor treatment for individual patients and predict or monitor the response to drug or radiation therapy. More information is available on the Quantitative Imaging Network Collections page. Interested investigators can apply to the QIN at: Quantitative Imaging for Evaluation of Responses to Cancer Therapies (U01) PAR-11-150.

Data Access

Version 2: Updated 2017/07/31

Added DICOM for 37 new subjects

Title Data Type Format Access Points Subjects Studies Series Images License
Images CT DICOM
Download requires NBIA Data Retriever
 47 47 47 3,954 CC BY 3.0

Additional Resources for this Dataset

The NCI Cancer Research Data Commons (CRDC) provides access to additional data and a cloud-based data science infrastructure that connects data sets with analytics tools to allow users to share, integrate, analyze, and visualize cancer research data.

Citations & Data Usage Policy

Data Citation Required: Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution must include the following citation, including the Digital Object Identifier:

Data Citation

Goldgof, D., Hall, L., Hawkins, S., Schabath, M., Stringfield, O., Garcia, A., Balagurunathan, Y., Kim, J., Eschrich, S., Berglund, A., Gatenby, R., & Gillies, R. (2015). Data From QIN LUNG CT (version 2) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2015.NPGZYZBZ

Data Citation
Kalpathy-Cramer J, Napel S, Goldgof D, Zhao B. (2015) QIN multi-site collection of Lung CT data with Nodule Segmentations.  https://doi.org/10.7937/K9/TCIA.2015.1BUVFJR7

Other Publications Using this Data

TCIA maintains a list of publications which leverage our data.  If you have a publication you’d like to add, please contact TCIA’s Helpdesk.

TCIA Citation

Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., Moore, S., Phillips, S., Maffitt, D., Pringle, M., Tarbox, L., & Prior, F. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. In Journal of Digital Imaging (Vol. 26, Issue 6, pp. 1045–1057). Springer Science and Business Media LLC. https://doi.org/10.1007/s10278-013-9622-7

Analysis Results Using this Collection

Previous Versions

Version 1: Updated 2014/12/17

Title Data Type Format Access Points Studies Series Images License
Images DICOM
Analysis Results Using This Collection