NSCLC Radiogenomics | NSCLC Radiogenomics
DOI: 10.7937/K9/TCIA.2017.7hs46erv | Data Citation Required | 2.4k Views | 73 Citations | Image Collection
| Location | Species | Subjects | Data Types | Cancer Types | Size | Status | Updated | |
|---|---|---|---|---|---|---|---|---|
| Chest | Human | 211 | SEG, CT, PT, Demographic, Exposure, Follow-Up, Treatment, Molecular Test, Radiomic Feature, Classification | Non-small Cell Lung Cancer | Clinical, Image Analyses, Genomics | Public, Complete | 2021/06/01 |
Summary
Medical image biomarkers of cancer promise improvements in patient care through advances in precision medicine. Compared to genomic biomarkers, image biomarkers provide the advantages of being a non-invasive procedure, and characterizing a heterogeneous tumor in its entirety, as opposed to limited tissue available for biopsy. We developed a unique radiogenomic dataset from a Non-Small Cell Lung Cancer (NSCLC) cohort of 211 subjects. The dataset comprises Computed Tomography (CT), Positron Emission Tomography (PET)/CT images, semantic annotations of the tumors as observed on the medical images using a controlled vocabulary, segmentation maps of tumors in the CT scans, and quantitative values obtained from the PET/CT scans. Imaging data are also paired with gene mutation, RNA sequencing data from samples of surgically excised tumor tissue, and clinical data, including survival outcomes. This dataset was created to facilitate the discovery of the underlying relationship between genomic and medical image features, as well as the development and evaluation of prognostic medical image biomarkers. Further details regarding this data-set may be found in Bakr, et. al, Sci Data. 2018 Oct 16;5:180202. doi: 10.1038/sdata.2018.202, https://www.ncbi.nlm.nih.gov/pubmed/30325352. For scientific and other inquiries about this dataset, please contact TCIA's Helpdesk.
Data Access
Version 4: Updated 2021/06/01
- Added missing image studies for the following cases: R01-009 (CT), R01-100 (PET/CT), and R01-111 (PET/CT).
- SUV conversion factor DICOM tag (7053,1000) was added for the following Philips PET images: R01-074, R01-077, R01-079, R01-089, R01-98 and R01-137.
| Title | Data Type | Format | Access Points | Subjects | License | |||
|---|---|---|---|---|---|---|---|---|
| Images and Segmentations | SEG, CT, PT | DICOM | Download requires NBIA Data Retriever |
211 | 395 | 1,351 | 286,754 | CC BY 3.0 |
| AIM Annotations | Radiomic Feature, Classification | XML and ZIP | CC BY 3.0 | |||||
| Clinical Data | Demographic, Exposure, Follow-Up, Treatment, Molecular Test | CSV | 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.
- Imaging Data Commons (IDC) (Imaging Data)
- IDC Zenodo community dataset: Image segmentations produced by BAMF under the AIMI Annotations initiative
The following external resources have been made available by the data submitters. These are not hosted or supported by TCIA, but may be useful to researchers utilizing this collection.
- RNA sequence data (Note: 130 subject subset)
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 |
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Bakr, S., Gevaert, O., Echegaray, S., Ayers, K., Zhou, M., Shafiq, M., Zheng, H., Zhang, W., Leung, A., Kadoch, M., Shrager, J., Quon, A., Rubin, D., Plevritis, S., & Napel, S. (2017). Data for NSCLC Radiogenomics (Version 4) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2017.7hs46erv |
Detailed Description
This collection was originally submitted to TCIA as a 26 subject pilot data set. You can learn more about that subset of the collection in the following Analysis Results publication:
Data Citation
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
Related Publications
Publications by the Dataset Authors
The authors recommended the following as the best source of additional information about this dataset:
Publication Citation |
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Bakr, S., Gevaert, O., Echegaray, S., Ayers, K., Zhou, M., Shafiq, M., Zheng, H., Benson, J. A., Zhang, W., Leung, A., Kadoch, M., Hoang, C. D., Shrager, J., Quon, A., Rubin, D. L., Plevritis, S. K., & Napel, S. (2018). A radiogenomic dataset of non-small cell lung cancer. Scientific data, 5, 180202. https://doi.org/10.1038/sdata.2018.202 |
Publication Citation |
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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 |
The Collection authors recommend these readings to give context to this dataset
Research Community Publications
TCIA maintains a list of publications that leveraged this dataset. If you have a manuscript you’d like to add please contact TCIA’s Helpdesk.
Previous Versions
Version 3: Updated 2020/11/10
- A new version of RO1-023 was created to correct a cranial-caudal flip of the segmentation of the CT volume (483 images) and associated Segmentation object. The UIDs of the other scans were updated to preserve Study level consistency but were otherwise unmodified. The referenced UIDs within the AIM object for RO1-023 were updated and renamed to RO1-023v1.
- RO1-038 was updated to remove a coronal slice at the start of the of the CT volume. This created difficulty for some software to determine slice spacing.
| Title | Data Type | Format | Access Points | License | ||||
|---|---|---|---|---|---|---|---|---|
| Images | DICOM | Download requires NBIA Data Retriever |
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| AIM Annotations | XML and ZIP | |||||||
| Clinical Data | CSV |
Version 2: Updated 2017/02/28
| Title | Data Type | Format | Access Points | License | ||||
|---|---|---|---|---|---|---|---|---|
| Images | DICOM | Download requires NBIA Data Retriever |
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| AIM Annotations | XML and ZIP | |||||||
| Clinical Data | CSV |
Version 1: Updated 2015/12/22
This collection was originally submitted to TCIA as a 26 subject pilot data set. You can learn more about that subset of the collection in the following Analysis Results publication: