Child pages
  • The Clinical Proteomic Tumor Analysis Consortium Uterine Corpus Endometrial Carcinoma Collection (CPTAC-UCEC)

Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

Summary


 

Excerpt

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

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.

, and is being made available on a release schedule that is coordinated with the CPTAC program releases of proteomic and genomic data.  A summary of CPTAC 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 and , 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).


Localtab Group



Localtab
activetrue
titleData Access

Data Access

Choosing the Download option will provide you with a file to launch the TCIA Download Manager to download the entire collection. If you want to browse or filter the data to select only specific scans/studies please use the Search By Collection option.

Data TypeDownload all or Query/Filter
Images (DICOM,
6
58.
04
5 GB)
 Image Removed

Image Added

(Download requires the NBIA Data Retriever)     

Tissue Slide Images (
web
SVS, 154 GB)

Clinical Data API (

CSV

JSON - more info)

Coming soon

Proteomics (web)

Coming soon

Genomics (web)

 

Discovery Study 
Coming soon


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:




Localtab
titleDetailed Description

Detailed Description



Radiology Image Statistics

 
Pathology Image Statistics

Modalities

CT, MR, PT, CR, DX, SR

Pathology

Number of

Patients

Participants

74

7
250

Number of Studies

105

10
N/A

Number of Series

83

1,658

N/A

Number of Images

153,204

11805
888
Images Size (GB)
6
58.
04
5154


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.




Localtab
titleCitations & Data Usage Policy

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

Users of this data must abide by the Creative Commons Attribution 3.0 Unported License under which it has been published. CPTAC proteomic and genomic data use must also 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  Questions may be directed to help@cancerimagingarchive.net. Please be sure to acknowledge both this data set and TCIA in publications by including Attribution should include references to the following citations in your work:



Info
titleData 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




Info
titleAcknowledgement

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).”




Info
titleTCIA 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. (paper). DOI: 10.1007/s10278-013-9622-7


Other Publications Using This Data

TCIA maintains a list of publications which that leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk.




Localtab
titleVersions

Version 8 (Current): Updated 2020/03/31


Data TypeDownload all or Query/Filter
Images (DICOM, 58.5 GB)
Tissue Slide Images (SVS, 154 GB)

Clinical Data API (JSON - more info

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


Added 14 radiology subjects

Version 7 : Updated 2019/09/30


Data TypeDownload all or Query/Filter
Images (DICOM, 46.9 GB)
Tissue Slide Images (SVS, 154 GB)

Clinical Data API (JSON - more info

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)
Clinical Data (web)
Proteomics (web)


Added Subjects

Version 5 : Updated 2019/1

(Current)

/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)
Tissue Slide Images (web)
Clinical Data (CSV)(Coming Soon)
Proteomics (web)


Added new subjects.

Version 3: Updated 2018/

01

06/

10

30


Data TypeDownload all or Query/Filter
Images (DICOM,
4
 25.
38
5 GB)

Image Modified  

(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)

Image Added  

(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)

Image Added

(Requires the NBIA Data Retriever . )

Tissue Slide Images (web)
Genomics
Clinical Data (CSV)

(Coming Soon)

Proteomics (web)