The Cancer Imaging Archive

A091105-Tumor-Annotations | Annotations for Sorafenib Tosylate in Treating Patients With Desmoid Tumors or Aggressive Fibromatosis

DOI: 10.7937/T8RN-J447 | Data Citation Required | 14 Views | Analysis Result

Summary

This dataset contains image annotations derived from the NCI Clinical Trial “Sorafenib Tosylate in Treating Patients With Desmoid Tumors or Aggressive Fibromatosis (A091105)”.  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, 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. 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. If the primary lesion was <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 coronal plane.
3. MRIs were annotated using the T1-weighted axial post contrast sequence, fat saturated if available. Occasionally, if the tumor was significantly better delineated on a STIR or T2 fat-sat sequence, it wase annotated on that sequence instead of the post contrast sequence.
4. CTs were annotated using the axial post contrast series. If not available, the non contrast series was annotated.
5. Lesions were labeled separately.
6. The volume of each annotated lesion was calculated and reported in cubic centimeters [cc] in the Annotation Metadata CSV.
7. Seed points were automatically generated, but reviewed by a radiologist.
8. A “negative” annotation was created for any exam without findings.

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 RTSTRUCT file.
2. SNOMED-CT “Anatomic Region Sequence” and “Segmented Property Category Code Sequence” and codes were inserted for all segmented structures.
3. “Tracking ID” and “Tracking UID” tags will be inserted for each segmented structure to enable longitudinal lesion tracking.
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. (262502001, SCT, “Post-chemotherapy”)

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 2023/11/13

Collections Used In This Analysis Result

Additional Resources For This Dataset

• NCTN/NCORP Data Archive provides the Clinical Data files related to these subjects, and is also where you go to request access to the entire dataset
• Jupyter notebook demonstrating how to use the NBIA Data Retriever Command-Line Interface application and REST API (with authentication) to access these data
• Instructions for Visualizing these data in 3D Slicer

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: