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Summary


This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium Uterine Corpus Endometrial Carcinoma (CPTAC-UCEC) cohort. 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 Phase 3 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 Phase 3 collects data from ten cancer types.  In TCIA, imaging from each cancer type will be contained in its own TCIA Collection, with the collection name "CPTAC-cancertype". CPTAC Phase 3 Imaging data is made available on TCIA each quarter as it is collected.  A summary of CPTAC Phase 3 imaging efforts can be found on the CPTAC Imaging Proteomics page. 

Radiology imaging is collected from standard of care imaging performed on patients immediately before the pathological diagnosis, and from follow-up scans where available.  For this reason the radiology image data sets are heterogeneous in terms of scanner modalities, manufacturers and acquisition protocols. Pathology imaging is collected as part of the CPTAC qualification workflow.  

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.

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.
  • Boston Medical Center, Boston, MA - Special thanks to Chris D. Andry M.Phil, PhD from the Department of Pathology and Laboratory Medicine, Margaret Lavoye, Artem Kaliaev, Wilson Chavez, Stephan Anderson, Jorge Soto, and Mitchell Horn from the Department of Radiology, Elizabeth Duffy, MA and Cheryl Spencer, MA of the Biobank.
  • International Institute for Molecular Oncology, Poznań, Poland - Special thanks to Maciej Wiznerowicz MD, PhD and Jan Lubiński MD PhDRafal Matkowski, MD, PhD, Marcin Jędryka MD, PhD, and Andrzej Czekański MD PhD, from Lower Silesia Cancer Center in Wrocław, Poland.
  • St. Joseph's Hospital and Medical Center, Phoenix, AZ - Special thanks to Jennifer Eschbacher, MD from the Department of Neuropathology, Catherine Seiler, PhDRosy Singh and Beth Hermes from the Biobank Core Facility, and Victor Sisneros, RT(R)(CT), CPSA.
  • BioPartners, CA - Special thanks to Alexander Gasparian, PhD. from the Department of Drug Discovery and Biomedical Sciences, University of South Carolina College of Pharmacy, Kakhaber Zaalishvili, MD Medical Advisor and Staff Pathologist at BioPartners, LLC, Milla Gorodnia, President of BioPartners, Inc., Victoria Christensen, Global Business Development/Project Coordination Manager, Oksana Havryliuk, MD. Chief of Research department of radiodiagnostics of NCI (Ukraine), Marianna Gredil’, Director of BioPartners, LLC, and Anna Legenka Chief of the Data Department at BioPartners, LLC
  • University of Pittsburgh/UPMC, Pittsburgh, PA - Special thanks to Scott Beasley (MD, FACR) and Rose Jarosz in the Department of Radiology; Rajiv Dhir (MBBS, MBA) and Tony Green (HT (ASCP), AS) in the Department of Pathology (PBC).


Data Access

Click the Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever. Click the Search button to open our Data Portal, where you can browse the data collection and/or download a subset of its contents.

Data TypeDownload all or Query/Filter
Images (DICOM, 46.9 GB)

Tissue Slide Images (SVS, 154 GB)

download pathology slide images

Clinical Data API (JSON - more info

download pathology slide images

Discovery Study Proteomics/Clinical Data (external)
Genomics/Clinical Data (external) 

Click the Versions tab for more info about data releases.

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

CT, MR, PT, CR, DX, SR

Pathology

Number of Patients

60

250

Number of Studies

84

N/A

Number of Series

1,257

N/A

Number of Images

121,109

888
Images Size (GB)46.9154

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 (i.e. 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 

CPTAC imaging data is considered CPTAC metadata and as such it is freely available to the public according to the TCIA Data Usage Policy. Note that CPTAC proteomic and genomic data use must comply with the CPTAC Data Use Agreement.

These collections are freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License. Questions may be directed to help@cancerimagingarchive.net. Please be sure to acknowledge both this data set and TCIA in publications by including the following citations in your work:

Data Citation

National Cancer Institute Clinical Proteomic Tumor Analysis Consortium (CPTAC). (2018). Radiology Data from the Clinical Proteomic Tumor Analysis Consortium Uterine Corpus Endometrial Carcinoma [CPTAC-UCEC] Collection [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/k9/tcia.2018.3r3juisw

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 that leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk.

Version 7 (Current): Updated 2019/09/30

Data TypeDownload all or Query/Filter
Images (DICOM, 46.9 GB)

Tissue Slide Images (SVS, 154 GB)

download pathology slide images

Clinical Data API (JSON - more info

download pathology slide images

Clinical Data (web)
Proteomics (web)

Added new subjects

Version 6 : Updated 2019/06/30

Data TypeDownload all or Query/Filter
Images (DICOM, 31.9 GB)

Tissue Slide Images (SVS, 151.6 GB)

download pathology slide images

Clinical Data (web)
Proteomics (web)

Added Subjects

Version 5 : Updated 2019/1/23

Data TypeDownload all or Query/Filter
Images (DICOM, 26.1 GB)

Tissue Slide Images (web)

Clinical Data (web)
Proteomics (web)

Added links to clinical and proteomic data from CPTAC Discovery Study (first 100 patients)

Version 4: Updated 2018/10/29

Data TypeDownload all or Query/Filter
Images (DICOM, 26.1 GB)

(Requires the NBIA Data Retriever.)

Tissue Slide Images (web)

Clinical Data (CSV)(Coming Soon)
Proteomics (web)

Added new subjects.

Version 3: Updated 2018/06/30

Data TypeDownload all or Query/Filter
Images (DICOM, 25.5 GB)

 

(Requires the NBIA Data Retriever.)

Tissue Slide Images (web)

Clinical Data (CSV)(Coming Soon)
Proteomics (web)

Added new subjects.

Version 2: Updated 2018/04/26

Data TypeDownload all or Query/Filter
Images (DICOM, 24.6 GB)

 

(Requires the NBIA Data Retriever.)

Tissue Slide Images (web)

Clinical Data (CSV)(Coming Soon)
Proteomics (web)

Added new subjects.

Version 1: Updated 2018/01/10

Data TypeDownload all or Query/Filter
Images (DICOM, 4.38 GB)

(Requires the NBIA Data Retriever.)

Tissue Slide Images (web)

Clinical Data (CSV)

(Coming Soon)

Proteomics (web)


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