Summary
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The Cancer Genome Atlas Glioblastoma Multiforme (TCGA-GBM) 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) |
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. Clinical, genetic, and pathological data resides in the Genomic Data Commons (GDC) Data Portal while the radiological data is stored on The Cancer Imaging |
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Archive ( |
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Clinical, genetic, and pathology data reside in the TCGA data portal while the radiological data is stored on The Cancer Imaging Archive (TCIA). The data utilizes the same TCGA patient identifiers in both repositories, allowing researchers to explore the correlations between tissue genotype and radiological phenotype. This Collection within TCIA is related to the GBM disease type within TCGA.
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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 Glioma Phenotype Research Group.
Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:
- Henry Ford Hospital, Detroit, MI - Special thanks to Lisa Scarpace and Tom Mikkelsen, MD from the Department of Neurosurgery, Hermelin Brain Tumor Center.
- University of California, San Francisco, CA - Special thanks to Soonmee Cha, MD from the Department of Neurological Surgery, Brain Tumor Research Center.
- MD Anderson Cancer Center, Houston, TX - Special thanks to Sujaya Rao and Sangeeta Tekchandani from the Office of Translational/Clinical Research.
- Emory University, Atlanta, GA - Special thanks to David Gutman, MD, Ph.D. and Joel Saltz, MD, Ph.D. from the Center for Comprehensive Informatics.
- Thomas Jefferson University, Philadelpha, PA - Special thanks to Nancy Pedano and Adam E. Flanders, MD from the Department of Radiology, Jefferson Medical College.
- CWRU School of Medicine, Cleveland, OH - Special thanks to Jill Barnholtz-Sloan, Ph.D. and Quinn Ostrom, MA, MPH from Case Comprehensive Cancer Center.
- Duke University School of Medicine, Durham, NC - Special thanks to Daniel Barboriak, MD and Laura J Pierce.
- Fondazione IRCCS Instituto Neuroligico C. Besta, Milan, Italy - Special thanks to Domenico Aquino and Alessandro Perin MD.
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Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:
- Henry Ford Hospital, Detroit, MI - Special thanks to Lisa Scarpace and Tom Mikkelsen, MD from the Department of Neurosurgery, Hermelin Brain Tumor Center.
- University of California, San Francisco, CA - Special thanks to Soonmee Cha, MD from the Department of Neurological Surgery, Brain Tumor Research Center.
- MD Anderson Cancer Center, Houston, TX - Special thanks to Sujaya Rao and Sangeeta Tekchandani from the Office of Translational/Clinical Research.
- Emory University, Atlanta, GA - Special thanks to David Gutman, MD, PhD and Joel Saltz, MD, PhD from the Center for Comprehensive Informatics.
- Mayo Clinic, Rochester, MN - Special thanks to Bradley J. Erickson, MD, PhD from the Department of Radiology, Mayo Medical School.
- Thomas Jefferson University, Philadelpha, PA - Special thanks to Nancy Pedano and Adam E. Flanders, MD from the Department of Radiology, Jefferson Medical College.
- CWRU School of Medicine, Cleveland, OH - Special thanks to Jill Barnholtz-Sloan, PhD and Quinn Ostrom, MA, MPH from Case Comprehensive Cancer Center.
- Duke University School of Medicine, Durham, NC - Special thanks to Daniel Barboriak, MD and Laura J Pierce.
CIP TCGA Radiology Initiative
The Cancer Imaging Program is supporting multiple projects within the academic community to encourage cross disciplinary research which utilizes the data provided in these resources. Much more can be learned about this effort on the TCGA Glioma Phenotype Research Group page.
Data Access
Imaging Data
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You can view and download these images on The Cancer Imaging Archive by logging in to TCIA and selecting the TCGA-GBM collection. A full listing of the available imaging studies/series for each patient can be found in this spreadsheet: TCGA-GBM_series_descriptions.csv |
Collection Statistics | (updated 12/2/2013) |
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Modalities | MR |
Number of Patients | 240 |
Number of Studies | 550 |
Number of Series | 5,234 |
Number of Images | 458,951 |
If you are unsure how to download this Collection please view our quick guide on Searching by Collection or refer to our The Cancer Imaging Archive User's Guide for more detailed instructions on using the site.
Metadata
The TCGA data portal has extensive clinical and genomic data which can be matched to the patient identifiers of the images here in TCIA. Here are just a sample of some of the clinical data types available:
bcr_patient_barcode,additional_chemo_therapy,additional_drug_therapy,additional_hormone_therapy,additional_immuno_therapy,additional_pharmaceutical_therapy,additional_radiation_therapy,age_at_initial_pathologic_diagnosis,
anatomic_organ_subdivision,chemo_therapy,days_to_birth,days_to_death,days_to_initial_pathologic_diagnosis,days_to_last_followup,days_to_tumor_progression,days_to_tumor_recurrence,drugs,gender,histological_type,hormonal_therapy,
immuno_therapy,informed_consent_verified,initial_pathologic_diagnosis_method,person_neoplasm_cancer_status,pretreatment_history,prior_glioma,radiation_therapy,radiations,targeted_molecular_therapy,tumor_tissue_site,vital_status,
year_of_initial_pathologic_diagnosis
Verbose explanations of the clinical data can be found on the Biospecimen Core Resource Clinical Data Forms linked below:
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