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Summary
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The Cancer Genome Atlas |
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Ovarian Cancer (TCGA-OV) data collection is part of a larger effort |
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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 |
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the Genomic Data Commons (GDC) Data Portal while the radiological data is stored on The Cancer Imaging Archive (TCIA). |
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Matched TCGA patient identifiers
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allow researchers to explore the TCGA/TCIA databases for correlations between tissue genotype
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, radiological phenotype
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Note: Per TCGA Guidelines, formal permission requests are still required for publications using TCGA-OV data. More info about TCGA Publication Policies can be found on the Data Usage Policies and Restrictions page.
CIP TCGA Radiology Initiative
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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
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Acknowledgements
How to Retrieve the Images from TCIA
Imaging Data
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You can view and download these images on TCIA by clicking Image Removed and selecting the TCGA-OV collection. |
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Collection Statistics
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Updated 2014/08/15
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Modalities
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computed tomography (CT)
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Number of Patients
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111
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Number of Studies
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147
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Number of Series
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534
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 Holback, MD 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 Mutch, MD, Ira C, MD & 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
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Number of Images
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If you are unsure how to download this collection, please view Searching by Collection or refer to TCIA's User's Guide for more detailed instructions on using the site.
Related Data
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Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:
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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 Mutch, MD, Ira C, MD & Judith Gall, MD Ob/Gyn.
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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.
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