Summary
Matched TCGA patient identifiers allow researchers to explore the TCGA/TCIA databases for correlations between tissue genotype, radiological phenotype and patient outcomes. Tissues for TCGA were collected from many sites all over the world in order to reach their accrual targets, usually around 500 specimens per cancer type. For this reason the image data sets are also extremely heterogeneous in terms of scanner modalities, manufacturers and acquisition protocols. In most cases the images were acquired as part of routine care and not as part of a controlled research study or clinical trial.
CIP TCGA Radiology Initiative
Imaging Source Site (ISS) Groups are being populated and governed by participants from institutions that have provided imaging data to the archive for a given cancer type. Modeled after TCGA analysis groups, ISS groups are given the opportunity to publish a marker paper for a given cancer type per the guidelines in the table above. This opportunity will generate increased participation in building these multi-institutional data sets as they become an open community resource. Learn more about the CIP TCGA Radiology Initiative.
Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:
- Mayo Clinic, Rochester, MN - Special thanks to Bradley J. Erickson, M.D., Ph.D. from the Department of Radiology, Mayo Medical School.
- University of North Carolina, Chapel Hill, NC - Special thanks to J. Keith Smith, M.D., Ph.D. and Shanah Kirk from the Department of Radiology, University of North Carolina School of Medicine.
- Alberta Health Services, - Special thanks to Oliver Bathe, M.D., FRCS(C) from the Department of Oncology, and Melissa Kearns, MRT(R) CTIC.
- Lahey Hospital & Medical Center, Burlington, MA - Special thanks to John Lemmerman, RT and Kimberly Reiger-Christ, PhD, Cancer Research, Sophia Gordon Cancer Center.
Data Access
Data Type | Download all or Query/Filter | License |
---|---|---|
Images (DICOM, 52.5GB) | (Download requires the NBIA Data Retriever) |
Click the Versions tab for more info about data releases.
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)
- Genomic Data Commons (GDC) (Genomic, Digitized Histopathology & Clinical Data)
Third Party Analyses of this Dataset
TCIA encourages the community to publish your analyses of our datasets. Below is a list of such third party analyses published using this Collection:
Detailed Description
Image Statistics | |
---|---|
Modalities | CT, MR, PT |
Number of Participants | 97 |
Number of Studies | 237 |
Number of Series | 1,688 |
Number of Images | 125,397 |
Images Size (GB) | 52.5 |
GDC Data Portal - Clinical and Genomic Data
The GDC Data Portal has extensive clinical and genomic data, which can be matched to the patient identifiers on the images here in TCIA. Below is a snapshot of clinical data extracted on 1/5/2016.
Explanations of the clinical data can be found on the Biospecimen Core Resource Clinical Data Forms linked below:
A Note about TCIA and TCGA Subject Identifiers and Dates
Subject Identifiers: a subject with radiology images stored in TCIA is identified with a Patient ID that is identical to the Patient ID of the same subject with demographic, clinical, pathological, and/or genomic data stored in TCGA. For each TCGA case, the baseline TCGA imaging studies found on TCIA are pre-surgical.
Dates: TCIA and TCGA handle dates differently, and there are no immediate plans to reconcile:
- TCIA Dates: dates (be they birth dates, imaging study dates, etc.) in the Digital Imaging and Communications in Medicine (DICOM) headers of TCIA radiology images have been offset by a random number of days. The offset is a number of days between 3 and 10 years prior to the real date that is consistent for each TCIA image-submitting site and collection, but that varies among sites and among collections from the same site. Thus, the number of days between a subject’s longitudinal imaging studies are accurately preserved when more than one study has been archived while still meeting HIPAA requirements.
- TCGA Dates: the patient demographic and clinical event dates are all the number of days from the index date, which is the actual date of pathologic diagnosis. So all the dates in the data are relative negative or positive integers, except for the “days_to_pathologic_diagnosis” value, which is 0 – the index date. The years of birth and diagnosis are maintained in the distributed clinical data file. The NCI retains a copy of the data with complete dates, but those data are not made available.With regard to other TCGA dates, if a date comes from a HIPAA “covered entity’s” medical record, it is turned into the relative day count from the index date. Dates like the date TCGA received the specimen or when the TCGA case report form was filled out are not such covered dates, and they will appear as real dates (month, day, and year).
Citations & Data Usage Policy
Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution should include references to the following citations:
Data Citation
Erickson, B. J., Kirk, S., Lee, Y., Bathe, O., Kearns, M., Gerdes, C., Rieger-Christ, K., & Lemmerman, J. (2016). The Cancer Genome Atlas Liver Hepatocellular Carcinoma Collection (TCGA-LIHC) (Version 5) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2016.IMMQW8UQ
Acknowledgement
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
Other Publications Using This Data
TCIA maintains a list of publications which leverage our data.
- QIU, Jia-jun et al. "Texture Classification Study of Mr Images for Hepatocellular Carcinoma." 电子科技大学学报, vol. 48, no. 4, 2019, pp. 619-626, doi:10.3969/j.issn.1001-0548.2019.04.021.
- Renukadevi, Thangavel and Saminathan Karunakaran. "Optimizing Deep Belief Network Parameters Using Grasshopper Algorithm for Liver Disease Classification." International Journal of Imaging Systems and Technology, 2019, doi:10.1002/ima.22375.
- West, Derek L et al. "Ct-Based Radiomic Analysis of Hepatocellular Carcinoma Patients to Predict Key Genomic Information." Journal of Clinical Oncology, vol. 35, no. 15, 2017, doi:10.1200/JCO.2017.35.15_suppl.e15623
If you have a manuscript you'd like to add please contact the TCIA Helpdesk.
Version 5 (Current): 2020/05/29
Data Type | Download all or Query/Filter |
---|---|
Images (DICOM, 52.5GB) | (Download requires the NBIA Data Retriever) |
Tissue Slide Images (web) | |
Clinical Data (TXT) | |
Biomedical Data (TXT) | |
Genomics (web) |
Updated clinical data link with latest spreadsheets from GDC. Added new biomedical spreadsheets from GDC.
Version 4: Updated 2017/01/30
Data Type | Download all or Query/Filter |
---|---|
Images (DICOM, 52.5GB) | (Download requires the NBIA Data Retriever) |
Clinical Data (TXT) | |
Genomics (web) |
Data for 4 new subjects added.
Version 3: Updated 2016/06/21
Data Type | Download all or Query/Filter |
---|---|
Images (DICOM, 51.0GB) | (Download requires the NBIA Data Retriever) |
Clinical Data (TXT) | |
Genomics (web) |
New Image Data added to TCGA-LIHC collection.
Version 2: Updated 2016/01/05
Data Type | Download all or Query/Filter |
---|---|
Images (DICOM, 42.6GB) | (Download requires the NBIA Data Retriever) |
Clinical Data (TXT) | |
Genomics (web) |
Extracted latest release of clinical data (TXT) from the GDC Data Portal.
Version 1: Updated 2014/05/05
Data Type | Download all or Query/Filter |
---|---|
Images (DICOM, 42.6GB) | (Download requires the NBIA Data Retriever) |
Clinical Data (TXT) | |
Genomics (web) |