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TCGA-LIHC

The Cancer Imaging Archive

TCGA-LIHC | The Cancer Genome Atlas Liver Hepatocellular Carcinoma Collection

DOI: 10.7937/K9/TCIA.2016.IMMQW8UQ | Data Citation Required | 1.9k Views | 39 Citations | Image Collection

Location Species Subjects Data Types Cancer Types Size Supporting Data Status Updated
Liver Human 97 CT, MR, PT Liver Hepatocellular Carcinoma 56.38GB Clinical, Genomics, Histopathology, Image Analyses Public, Complete 2020/05/29

Summary

The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) data collection is part of a larger effort to build a research community focused on connecting cancer phenotypes to genotypes by providing clinical images matched to subjects from The Cancer Genome Atlas (TCGA). Clinical, genetic, and pathological data resides in the Genomic Data Commons (GDC) Data Portal while the radiological data is stored on The Cancer Imaging Archive (TCIA). 

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.

Data Access

Version 5: Updated 2020/05/29

Updated clinical data link with latest spreadsheets from GDC. Added new biomedical spreadsheets from GDC.

Title Data Type Format Access Points Subjects Studies Series Images License
Images CT, MR, PT DICOM
Download requires NBIA Data Retriever
97 237 1,688 125,397 CC BY 3.0
Analysis Results Using This Collection
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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

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

Publications using data from this program are requested to include the following statement: “The results <published or shown> here are in whole or part based upon data generated by the TCGA Research Network: http://cancergenome.nih.gov/.”

Detailed Description

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).

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.

Related Publications

Publications by the Dataset Authors

The authors recommended the following as the best source of additional information about this dataset:

No other publications were recommended by dataset authors.

Research Community Publications

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

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.

Other Publications Using this Data

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

Previous Versions

Version 4: Updated 2017/01/30

Data for 4 new subjects added.

Title Data Type Format Access Points Subjects Studies Series Images License
Images DICOM
Download requires NBIA Data Retriever
Clinical Data TXT
Genomics WEB

Version 3: Updated 2016/06/21

New Image Data added to TCGA-LIHC collection.

Title Data Type Format Access Points Subjects Studies Series Images License
Images DICOM
Download requires NBIA Data Retriever
Clinical Data TXT
Genomics WEB

Version 2: Updated 2016/01/05

Extracted latest release of clinical data (TXT) from the GDC Data Portal.

Title Data Type Format Access Points Subjects Studies Series Images License
Images DICOM
Download requires NBIA Data Retriever
Clinical Data TXT
Genomics WEB

Version 1: Updated 2014/05/05

Title Data Type Format Access Points Subjects Studies Series Images License
Images DICOM
Download requires NBIA Data Retriever
Clinical Data TXT
Genomics WEB