Skip to main content

TCGA-OV

TCGA-OV | The Cancer Genome Atlas Ovarian Cancer Collection

DOI: 10.7937/K9/TCIA.2016.NDO1MDFQ | Data Citation Required | Image Collection

Location Species Subjects Data Types Cancer Types Size Supporting Data Status Updated
Ovary Human 143 CT, MR Ovarian Serous Cystadenocarcinoma 28.3GB Clinical, Genomics, Image Analyses, Pathology Public, Complete 2020/05/29

Summary

The Cancer Genome Atlas Ovarian Cancer (TCGA-OV) 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 TCGA Ovarian Phenotype Research Group.

Data Access

Version 4: Updated 2020/05/29

Note: When DICOM data are downloaded with the NBIA Data Retriever, the app uses “Series Description” values to construct descriptive directory names. In some series for this Collection, characters that are not allowed in directory names are present. So the workaround is to select the “Classic Directory Name” option, which is located above “Select Directory For Downloaded Files.”

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, OT DICOM
Download requires NBIA Data Retriever
143 322 844 53,662 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

Holback, C., Jarosz, R., Prior, F., Mutch, D. G., Bhosale, P., Garcia, K., Lee, Y., Kirk, S., Sadow, C. A., Levine, S., Sala, E., Elnajjar, P., Morgan, T., & Erickson, B. J. (2016). The Cancer Genome Atlas Ovarian Cancer Collection (TCGA-OV) (Version 4) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2016.NDO1MDFQ

Detailed Description

Note:

When DICOM data are downloaded with the NBIA Data Retriever, the app uses “Series Description” values to construct descriptive directory names. In some series for this Collection, characters that are not allowed in directory names are present. So the workaround is to select the “Classic Directory Name” option, which is located above “Select Directory For Downloaded Files.”

GDC Data Portal – Clinical and Genomic Data

Shared List:  Ovarian Cases with Early Post-Operative Scans

This shared list is tor researchers wanting to evaluate the completeness  of OV tumor surgical de-bulking, this group of cases has sequential CT scans that have both pre-op (baseline) and early post-op (less than ~ 2 months).

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:

  • University of Pittsburgh/UPMC, Pittsburgh, PA - Special thanks to Chandra HolbackMD and Rose Jarosz.
  • Washington University School of Medicine, St. Louis, MO - Special thanks to Fred Prior, Ph.D. from the Electronic Radiology Lab, Mallinckrodt Institute and David G MutchMDIra CMD & Judith Gall, MD Ob/Gyn.  

  • MD Anderson Cancer Center, Houston TX - Special thanks to Priya Bhosale, MD and Kimberly Garcia.
  • University of North Carolina, Chapel Hill, NC - Special thanks to Yueh Lee, MD, PhD and Shanah Kirk.
  • Brigham & Women's Hospital, Boston, MA - Special thanks to Cheryl A. Sadow, MD and Seth Levine.

  • Memorial Sloan-Kettering Cancer Center, New York, NY - Special thanks to Evis Sala, MD, PhD and Pierre Elnajjar.

  • University of California, San Francisco, CA - Special thanks to Tara Morgan, MD
  • Mayo Clinic, Rochester, MN - Special thanks to Brad Erickson, MD, PhD. Ca

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

Acknowledgement

“The results <published or shown> here are in whole or part based upon data generated by the TCGA Research Network: http://cancergenome.nih.gov/.”

Previous Versions

Version 3: Updated 2020/04/03

On 2020-04-03 DICOM tags associated with TCGA-30-1891 were updated with a corrected version of the file.

Title Data Type Format Access Points Studies Series Images License

Version 2: Updated 2016/01/05

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

Title Data Type Format Access Points Studies Series Images License
Images DICOM
Clinical Data TXT
Genomics WEB

Version 1: Updated 2014/11/05

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