- Created by Tracy Nolan, last modified by Kirk Smith on May 20, 2022
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Summary
This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium Glioblastoma Multiforme (CPTAC-GBM) cohort. The GBM confirmatory cohort was supplemented with retrospective samples from CHOP (Children’s hospital of Philadelphia)-Upenn. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics. Radiology and pathology images from CPTAC patients are being collected and made publicly available by The Cancer Imaging Archive to enable researchers to investigate cancer phenotypes which may correlate to corresponding proteomic, genomic and clinical data.
CPTAC Imaging Special Interest Group
You can join the CPTAC Imaging Special Interest Group to be notified of webinars & data releases, collaborate on common data wrangling tasks and seek out partners to explore research hypotheses! Artifacts from previous webinars such as slide decks and video recordings can be found on the CPTAC SIG Webinars page.
On May 13, 2020 Liang-Bo Wang and Runyu Hong presented the consortium's proteogenomic analyses of the CPTAC Glioblastoma (GBM) cohort. This deep dive into the GBM genomic and proteomic datasets will help researchers better understand how these can be correlated with features derived from the imaging data. (Download the slides)
Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:
Beaumont Health System, Royal Oak, MI - Special thanks to George D. Wilson, PhD from the Department of Radiation Oncology Research, Barbara Pruetz of the Biobank, Debra Kapczynski, MHSA, CIIP, RT(R)(CT) and Rachel Deyer from the Department of Diagnostic Radiology.
International Institute for Molecular Oncology, Poznań, Poland - Special thanks to Maciej Wiznerowicz MD, PhD and Jan Lubiński MD PhD, Tomasz Czernicki MD, PhD and Andrzej Marchel MD, PhD from Central Clinical Hospital in Warsaw, Pawel Jarmużek MD, PhD, Jakub Stawicki MD and Piotr Makarewicz MD from Karol Marcinkowski Regional Clinical Hospital in Zielona Góra; and Wojciech Szopa MD, PhD and Wojciech Kaspera MD, PhD from Regional Clinical Hospital Sosnowiec in Poland
- St. Joseph's Hospital and Medical Center, Phoenix, AZ - Special thanks to Jennifer Eschbacher, MD from the Department of Neuropathology, Catherine Seiler, PhD, Rosy Singh and Beth Hermes from the Biobank Core Facility, and Victor Sisneros, RT(R)(CT), CPSA.
- Cureline, Inc. team and clinical network, Brisbane, CA - Special thanks to Olga Potapova, Ph.D., Vladislav Golubkov, Ph.D., Victoria Fulidou, M.D., Alexander Sviridov, Dmitry Belyaev, M.D., Oxana Paklina, M.D., Dr.Sc., Galiya Setdikova, M.D., Ph.D., Denis Golbin, M.D., Ph.D.
Data Access
Data Type | Download all or Query/Filter |
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Images (DICOM, 39.8 GB) | (Download requires the NBIA Data Retriever) |
Tissue Slide Images (SVS, 87 GB) | |
Discovery Study (see Detailed Description tab for more info) |
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Click the Versions tab for more info about data releases.
Additional Resources for this Dataset
- Access these data in the cloud via the NIH Imaging Data Commons (IDC)
- Obtain data from the CPTAC Discovery Study (see Detailed Description tab for more info)
- Proteomic Data Commons (Proteomic & Clinical Data)
- Genomic Data Commons (Genomic & Clinical Data)
- Radiology
- Pathology
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
Radiology Image Statistics | Pathology Image Statistics | |
---|---|---|
Modalities | CR, CT, MR, SC | Pathology |
Number of Participants | 66 | 189 |
Number of Studies | 164 | N/A |
Number of Series | 1,771 | N/A |
Number of Images | 156,493 | 510 |
Images Size (GB) | 39.8 | 112 |
Accessing the Proteomic & Genomic Clinical Data
To access/download the clinical data on the Proteomic Data Commons (PDC) and Genomic Data Commons (GDC), once you have identified the data of your interest, move to the 'Clinical' tab on the browse page. Select the checkbox to select a specific row, all rows on the page or all pages and click the export clinical manifest button in CSV or TSV format on the GDC, or TSV or JSON format on the PDC.
A Note about TCIA and CPTAC Subject Identifiers and Dates
Subject Identifiers:
A subject with radiology and pathology images stored in TCIA is identified with a de-identified project Patient ID that is identical to the Patient ID of the same subject with clinical, proteomic, and/or genomic data stored in other CPTAC databases and web sites.
Dates:
The radiology imaging data is in DICOM format. To provide temporal context information aligned with events in the clinical data set for each patient, TCIA has inserted information in DICOM tag (0012,0050) Clinical Trial Time Point ID. This DICOM tag contains the number of days from the date the patient was initially diagnosed pathologically with the disease to the date of the scan. E.g. a scan acquired 3 days before the diagnosis would contain the value -3. A follow up scan acquired 90 days after diagnosis would contain the value 90.
The DICOM date tags (be they birth dates, imaging study dates, etc.) are modified per TCIA's standard process which offsets them 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.
Citations & Data Usage Policy
Radiology data from this collection has been published under a TCIA Limited Access License. Users must download and submit a signed copy of this license to help@cancerimagingarchive.net before accessing the data. CPTAC proteomic and genomic data use must also comply with the CPTAC Data Use Agreement. Questions may be directed to help@cancerimagingarchive.net. Attribution should include references to the following citations:
Users of the tissue slide image data from this collection must abide by the TCIA Data Usage Policy and the Creative Commons Attribution 4.0 International License under which it has been published. Attribution should include references to the following citations:
Data Citation
National Cancer Institute Clinical Proteomic Tumor Analysis Consortium (CPTAC). (2018). Radiology Data from the Clinical Proteomic Tumor Analysis Consortium Glioblastoma Multiforme [CPTAC-GBM] collection [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/k9/tcia.2018.3rje41q1
Acknowledgement
The CPTAC program requests that publications using data from this program include the following statement: “Data used in this publication were generated by the National Cancer Institute Clinical Proteomic Tumor Analysis Consortium (CPTAC).”
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. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. DOI: 10.1007/s10278-013-9622-7
Other Publications Using This Data
TCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk.
Version 13 (Current): 2020/09/03
Data Type | Download all or Query/Filter |
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Images (DICOM, 39.8 GB) | (Requires NBIA Data Retriever .) |
Tissue Slide Images (SVS, 112 GB) | |
Clinical Data API (JSON - more info) | |
Proteomics (web) |
Changed to new Aspera download link for histopathology slides.
Version 12: Updated 2020/02/31
Data Type | Download all or Query/Filter |
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Images (DICOM, 39.8 GB) | (Requires NBIA Data Retriever .) |
Tissue Slide Images (SVS, 112 GB) | |
Clinical Data API (JSON - more info) | |
Proteomics (web) |
Corrected 1 radiology subject cancer type, and added 3 radiology subjects.
Version 11: Updated 2020/02/14
Data Type | Download all or Query/Filter |
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Images (DICOM, 39.4 GB) | (Requires NBIA Data Retriever .) |
Tissue Slide Images (SVS, 112 GB) | |
Clinical Data (CSV) | Coming Soon |
Proteomics (web) |
Added 8 new pathology subjects & 37 new pathology slides
Version 10: Updated 2019/12/16
Data Type | Download all or Query/Filter |
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Images (DICOM, 39.4 GB) | (Requires NBIA Data Retriever .) |
Tissue Slide Images (SVS, 87 GB) | |
Clinical Data (CSV) | Coming Soon |
Proteomics (web) |
Added 5 new radiology and 2 pathology subjects
Version 9 : Updated 2019/10/30
Data Type | Download all or Query/Filter |
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Images (DICOM, 38.7 GB) | (Requires NBIA Data Retriever .) |
Tissue Slide Images (SVS, 87 GB) | |
Clinical Data (CSV) | Coming Soon |
Proteomics (web) |
Added new subjects
Version 8: Updated 2019/09/30
Data Type | Download all or Query/Filter |
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Images (DICOM, 38.7 GB) | (Requires NBIA Data Retriever .) |
Tissue Slide Images (SVS, 79 GB) | |
Clinical Data (CSV) | Coming Soon |
Proteomics (web) |
Added new subjects
Version 7 : Updated 2019/06/30
Data Type | Download all or Query/Filter |
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Images (DICOM, 36.1 GB) | (Requires NBIA Data Retriever .) |
Tissue Slide Images (SVS, 52.3 GB) | |
Clinical Data (CSV) | Coming Soon |
Proteomics (web) |
Added new subjects
Version 6 : Updated 2019/03/31
Data Type | Download all or Query/Filter |
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Images (DICOM, 21.2 GB) | (Requires NBIA Data Retriever .) |
Tissue Slide Images (web) | |
Clinical Data (CSV) | Coming Soon |
Proteomics (web) |
Added new subjects
Version 5: Updated 2018/12/31
Data Type | Download all or Query/Filter |
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Images (DICOM, 20.8 GB) | (Requires NBIA Data Retriever .) |
Tissue Slide Images (web) | |
Proteomics (web) |
Added new subjects.
Version 4: Updated 2018/10/24
Data Type | Download all or Query/Filter |
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Images (DICOM, 19.2 GB) | (Requires NBIA Data Retriever .) |
Tissue Slide Images (web) | |
Proteomics (web) |
Added new subjects.
Version 3: Updated 2018/06/30
Data Type | Download all or Query/Filter |
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Images (DICOM, 12.9 GB) | (Requires NBIA Data Retriever.) |
Tissue Slide Images (web) | |
Proteomics (web) |
Added new subjects.
Version 2: Updated 2018/04/26
Data Type | Download all or Query/Filter |
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Images (DICOM, 12.4 GB) | (Requires NBIA Data Retriever) |
Tissue Slide Images (web) | |
Proteomics (web) |
Added new subjects.
Version 1: Updated 2018/01/10
Data Type | Download all or Query/Filter |
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Images (DICOM, 10.42 GB) | (Requires NBIA Data Retriever) |
Tissue Slide Images (web) | |
Proteomics (web) |
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