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CPTAC-CCRCC-Tumor-Annotations | Annotations for The Clinical Proteomic Tumor Analysis Consortium Clear Cell Renal Cell Carcinoma Collection

DOI: 10.7937/SKQ4-QX48 | Data Citation Required | Analysis Result

Cancer Types Location Subjects Related Collections Size Supporting Data Updated
Clear Cell Carcinoma Kidney 60 28.68MB Tumor segmentations, Seed points 2023/07/24


This dataset contains image annotations derived from “The Clinical Proteomic Tumor Analysis Consortium Clear Cell Renal Cell Carcinoma Collection (CPTAC-CCRCC)”.  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. RECIST 1.1 was 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.
  2. Three-dimensional segmentations of lesions were created in the axial plane. If no axial plane was available, lesions were annotated in the available plane.
  3. MRIs were annotated using all axial T1-weighted post contrast sequences.
  4. CTs were annotated using all axial post contrast series.
  5. Lesions were labeled separately.
  6. Seed points were automatically generated, but reviewed by a radiologist.
  7. 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. “Tracking ID” and “Tracking UID” tags were inserted for each segmented structure to enable longitudinal lesion tracking.
  5. 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 2023/07/24

Title Data Type Format Access Points Subjects Studies Series Images License
CPTAC-CCRCC Annotations - Segmentations, Seed Points, and Negative Findings Assessments RTSTRUCT DICOM
Download requires NBIA Data Retriever
60 73 636 636 CC BY 4.0
CPTAC-CCRCC 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-CCRCC Images used to create Segmentations and Seed Points CT, MR DICOM 59 68 153 38,908 CC BY 4.0
Original CPTAC-CCRCC Images used to create Negative Assessment reports CT, MR DICOM 5 6 6 1,194 CC BY 4.0

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 Clear Cell Renal Cell Carcinoma Collection (CPTAC-CCRCC-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.

Collections Used In This Analysis Result

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