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CPTAC-PDA-TUMOR-ANNOTATIONS

The Cancer Imaging Archive

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

DOI: 10.7937/BW9V-BX61 | Data Citation Required | 39 Views | 3 Citations | Analysis Result

Cancer Types Location Subjects Related Collections Size Supporting Data Updated
Ductal Adenocarcinoma Pancreas 103 14.6MB Tumor segmentations, Seed points 2023/07/24

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. Scans were initially annotated by an international team of radiologists holding MBBS degrees or higher, which were then reviewed by US-based board-certified radiologists to ensure accuracy. 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

Version 1: Updated 2023/07/24

Title Data Type Format Access Points Subjects Studies Series Images License
CPTAC-PDA Annotations - Segmentations, Seed Points, and Negative Findings Assessments RTSTRUCT DICOM
Download requires NBIA Data Retriever
103 119 534 534 CC BY 4.0
CPTAC-PDA Annotation Metadata Classification, Measurement CSV CC BY 4.0

Collections Used In This Analysis Result

Title Data Type Format Access Points Subjects Studies Series Images License
Original CPTAC-PDA Images used to create Segmentations and Seed Points CT, MR DICOM 99 106 170 34,622 CC BY 4.0
Original CPTAC-PDA Images used to create Negative Assessment reports CT, MR DICOM 16 18 18 2,905 CC BY 4.0

Collections Used In This Analysis Result

Related Collections
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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 Pancreatic Ductal Adenocarcinoma Collection (CPTAC-PDA-Tumor-Annotations) (Version 1) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/BW9V-BX61

Related Publications

Publications by the Dataset Authors

The authors recommended the following as the best source of additional information about this dataset:

No other publications were recommended by dataset authors.

Research Community Publications

TCIA maintains a list of publications that leveraged this dataset. If you have a manuscript you’d like to add please contact TCIA’s Helpdesk.

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.