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The National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (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.

Pathology imaging is collected as part of the CPTAC qualification workflow.  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. 

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". This collection addresses CPTAC participants with pancreatic ductal adenocarcinoma (PDA).  CPTAC Phase 3 Imaging data is made available on TCIA each quarter as it is collected.


We would like to acknowledge the individuals and institutions that have provided data for this collection:

  • <coming soon>
  • 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 PhDTomasz 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, PhDRosy Singh and Beth Hermes from the Biobank Core Facility, and Victor Sisneros, RT(R)(CT), CPSA.
  • University of Calgary, Alberta, Canada - Special thanks to Oliver Bathe, MD, FRCS(C) from the Departments of Surgery/Oncology, Marina Salluzzi, PhD and Nicole Blenkin from the Department of Radiology, Calgary Image Processing and Analysis Centre (CIPAC), and Jennifer Koziak from the Department of Surgery.

Localtab Group

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, 4.38 GB)


Tissue Slide Images (web)

Clinical Data (CSV)

Coming soon

Proteomics (web)

Coming soon

Genomics (web)

Coming soon

Click the Versions tab for more info about data releases.

titleDetailed Description

Detailed Description

Image Statistics




Number of Patients


Number of Studies


Number of Series


Number of Images


Images Size (GB)4.38

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.


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.

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 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 Please be sure to acknowledge both this data set and TCIA in publications by including the following citations in your work:

titleData Citation

(Coming Soon)


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).”

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)

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 1 (Current): Updated 2018/01/10

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


Tissue Slide Images (web)

Clinical Data (CSV)

(Coming Soon)

Proteomics (web)

Genomics (web)