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The Cancer Imaging Archive

CPTAC-UCEC-Tumor-Annotations | Annotations for The Clinical Proteomic Tumor Analysis Consortium Uterine Corpus Endometrial Carcinoma Collection

DOI: 10.7937/89M3-KQ43 | Data Citation Required | Analysis Result

Cancer Types Location Subjects Related Collections Size Supporting Data Updated
Corpus Endometrial Carcinoma Uterus 72 34.85MB Tumor segmentations, Seed points 2023/07/24


This dataset contains image annotations derived from “The Clinical Proteomic Tumor Analysis Consortium Uterine Corpus Endometrial Carcinoma Collection (CPTAC-UCEC)”.  This dataset was generated as part of a National Cancer Institute project to augment images from The Cancer Imaging Archive with annotations that will improve their value for cancer researchers and artificial intelligence experts.

Annotation Protocol

For each patient, all scans were reviewed to identify and annotate the clinically relevant time points and sequences/series. In a typical patient all available time points were annotated. The following annotation rules were followed:

  1. PERCIST criteria was followed for PET imaging. Specifically, the lesions estimated to have the most elevated SUVmax were annotated.
  2. RECIST 1.1 was otherwise generally followed for MR and CT imaging. A maximum of 5 lesions were annotated per patient scan (timepoint); no more than 2 per organ. The same 5 lesions were annotated at each time point. Lymph nodes were annotated if >1 cm in short axis. Other lesions were annotated if >1 cm. If the primary lesion measures < 1 cm, it was still annotated.
  3. Three-dimensional segmentations of lesions were created in the axial plane. If no axial plane was available, lesions were annotated in the available plane.
  4. MRIs were annotated using all available axial T1-weighted post contrast sequences.
  5. CTs were annotated using the axial post contrast series if available. If not available, the axial non-contrast series were annotated as accurately as possible.
  6. PET/CTs were annotated on the CT and attenuation corrected PET images, unless there was a diagnostic CT from the same time point, in which case the CT portion of the PET/CT was not annotated.
  7. Lesions were labeled separately.
  8. A “negative” annotation was created for any exam without findings.

At each time point:

  1. Volume calculations were performed for each segmented structure.  These calculations are provided in the Annotation Metadata CSV.
  2. A seed point (kernel) was created for each segmented structure. The seed points for each segmentation are provided in a separate DICOM RTSTRUCT file.
  3. SNOMED-CT “Anatomic Region Sequence” and “Segmented Property Category Code Sequence” and codes were inserted for all segmented structures.
  4. Imaging time point codes were inserted to help identify each annotation in the context of the clinical trial assessment protocol.
    1. “Clinical Trial Time Point ID” was used to encode time point type using one of the following strings as applicable: “pre-dose” or “post-chemotherapy”.
    2. Content Item in “Acquisition Context Sequence” was added containing “Time Point Type” using Concept Code Sequence (0040,A168) selected from:
      1. (255235001, SCT, “Pre-dose”)
      2. (719864002, SCT, “Post-cancer treatment monitoring”)

Important supplementary information and sample code

  1. A spreadsheet containing key details about the annotations is available in the Data Access section below.
  2. A Jupyter notebook demonstrating how to use the NBIA Data Retriever Command-Line Interface application and the REST API to access these data can be found in the Additional Resources section below.

Data Access

Version 1: Updated

Title Data Type Format Access Points Subjects Studies Series Images License
CPTAC-UCEC Annotations - Segmentations, Seed Points, and Negative Findings Assessments RTSTRUCT DICOM
Download requires NBIA Data Retriever
72 100 617 617 CC BY 4.0
CPTAC-UCEC Annotation Metadata CSV CC BY 4.0

Collections Used In This Analysis Result

Title Data Type Format Access Points Subjects Studies Series Images License
Original CPTAC-UCEC Images used to create Segmentations and Seed Points CT, MR, PT DICOM 72 91 216 29,795 CC BY 4.0
Original CPTAC-UCEC Images used to create Negative Assessment reports CT DICOM 9 9 9 1,687 CC BY 4.0

Collections Used In This Analysis Result

Related Collections

Additional Resources For This Dataset

Citations & Data Usage Policy

Data Citation Required: Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution must include the following citation, including the Digital Object Identifier:

Data Citation

Rozenfeld, M., & Jordan, P. (2023). Annotations for The Clinical Proteomic Tumor Analysis Consortium Uterine Corpus Endometrial Carcinoma Collection (CPTAC-UCEC-Tumor-Annotations) (Version 1) [Data set]. The Cancer Imaging Archive.

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.

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. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. In Journal of Digital Imaging (Vol. 26, Issue 6, pp. 1045–1057). Springer Science and Business Media LLC.