Skip to main content

AREN0534-TUMOR-ANNOTATIONS

AREN0534-Tumor-Annotations | Annotations for Combination Chemotherapy and Surgery in Treating Young Patients With Wilms Tumor

DOI: 10.7937/N930-BM78 | Data Citation Required | Analysis Result

Cancer Types Location Subjects Related Collections Size Supporting Data Updated
Wilms Tumor Kidney 239 131.59MB Tumor segmentations, Seed points 2023/02/08

Summary

This dataset contains image annotations derived from the NCI Clinical Trial “Combination Chemotherapy and Surgery in Treating Young Patients With Wilms Tumor (AREN0534)”.  This dataset was generated as part of an NCI project to augment TCIA datasets with annotations that will improve their value for cancer researchers and AI developers.

Annotation Protocol

For each patient, every DICOM Study and DICOM Series was reviewed to identify and annotate the clinically relevant time points and sequences. In a typical patient the following time points were annotated:

  1. Pre-surgical CT chest and CT/MRI abdomen
  2. CT chest and/or CT/MRI abdomen at 6 weeks
  3. Possible CT/MRI abdomen at 12 weeks.
  4. Any negative imaging included past 12 weeks was annotated as negative. If any included imaging past 12 weeks is positive for tumor, the last positive exam was annotated.

In a typical patient the following annotation rules were followed:

  1. The primary renal tumor(s) were annotated on post-contrast axial series. Normal renal parenchyma were excluded.
  2. 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.  RECIST 1.1 principles were followed for lesion annotation, however, if <5 lesions measuring >1 cm were present, then smaller lesions were annotated, again up to 2 lesions per organ or 5 lesions per patient scan. Bone lesions were included if other lesions were not present.
  3. Lesions were labeled separately.
  4. Seed points were automatically generated but reviewed by a radiologist.
  5. To ensure a high standard of accuracy and data quality, each annotation was reviewed by a secondary reader.

At each time point:

  1. A seed point (kernel) was created for each segmented structure. The seed points for each segmentation are provided in a separate DICOM RTSS file.
  2. SNOMED-CT “Anatomic Region Sequence” and “Segmented Property Category Code Sequence” and codes were inserted for all segmented structures.
  3. 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”, “post-chemotherapy”, or “post-operative”.
    2. Content Item in “Acquisition Context Sequence” will be added containing “Time Point Type” using Concept Code Sequence (0040,A168) selected from:
      1. (255235001, SCT, “Pre-dose”)
      2. (262502001, SCT, “Post-chemotherapy”)
      3. (262061000, SCT, “Post-operative”)

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 (with authentication) to access these data can be found in the Additional Resources section below.

Data Access

Version 1: Updated 2023/02/08

Title Data Type Format Access Points Subjects Studies Series Images License
AREN0534 Annotations -- Segmentations, Seed Points, and Negative Findings Assessments RTSTRUCT DICOM
Download requires NBIA Data Retriever
239 1,102 3,785 3,785
AREN0534 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 AREN0534 Images used to create Segmentations and Seed Points CT, MR DICOM 236 804 846 114,629
Original AREN0534 Images used to create Negative Assessment reports CT, MR DICOM 210 456 493 56,708

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 Combination Chemotherapy and Surgery in Treating Young Patients With Wilms Tumor (AREN0534-Tumor-Annotations) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/N930-BM78

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. https://doi.org/10.1007/s10278-013-9622-7

Collections Used In This Analysis Result

Related Collections