CPTAC-PDA-Tumor-Annotations | Annotations for The Clinical Proteomic Tumor Analysis Consortium Pancreatic Ductal Adenocarcinoma Collection

DOI: 10.7937/BW9V-BX61 | Page Accessibility: Public | Analysis Result

Summary

This dataset contains image annotations derived from “The Clinical Proteomic Tumor Analysis Consortium Pancreatic Ductal Adenocarcinoma Collection (CPTAC-PDA)”.  This dataset was generated as part of a National Cancer Institute project to augment images from The Cancer Imaging Archive with tumor 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 coronal plane.
4. MRIs were annotated using axial T1-weighted post contrast sequences that best demonstrated the tumor.
5. CTs were annotated using all axial post contrast series. If not available, the axial non-contrast series were annotated.
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. Seed points were automatically generated, but reviewed by a radiologist.
9. 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

Click the Versions tab for more info about data releases.

Additional Resources for this Dataset

• The NCI Cancer Research Data Commons (CRDC) provides access to proteomic, genomic and clinical data related to these subjects. 
  • Imaging Data Commons (IDC) (Imaging Data)
  • Proteomic Data Commons (PDC) (Proteomic & Clinical Data)
  • Genomic Data Commons (GDC) (Genomic & Clinical Data)
• Jupyter notebook demonstrating how to use the NBIA Data Retriever Command-Line Interface application and REST API to access these data
• Instructions for Visualizing these data in 3D Slicer

Detailed Description

Citations & Data Usage Policy

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.

Collections Used In This Analysis Result