AHOD0831-Tumor-Annotations | Annotations for Combination Chemotherapy and Radiation Therapy in Treating Young Patients With Newly Diagnosed Hodgkin Lymphoma

DOI: 10.7937/4QAD-4280 | Data Citation Required | Analysis Result

Summary

This dataset contains image annotations derived from the NCI Clinical Trial “Combination Chemotherapy and Radiation Therapy in Treating Young Patients With Newly Diagnosed Hodgkin Lymphoma (AHOD0831)”.  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/series. In a typical patient all available time points were annotated:

In a typical patient the following annotation rules were followed:

1. PERCIST criteria was followed. Specifically, the lesions estimated to have the most elevated SUVmax were annotated.
2. Lesions were annotated in the axial plane. If no axial plane was available, lesions were annotated in the coronal plane.
3. Lesions were annotated on the attenuation corrected PET series as well as the diagnostic contrast enhanced CT. If no diagnostic contrast enhanced CT is available for that timepoint, then the non contrast CT portion of the PET/CT was annotated.
4. A maximum of 5 lesions were annotated per patient scan (timepoint); no more than 2 per organ. For the purposes of this project, the lymph nodes constitute 1 organ, while other lymphatic structures such as the spleen, salivary glands, and Waldeyer’s ring structures constitute separate organs.  The same 5 lesions were annotated at each time point.  RECIST 1.1 principles will be followed. Specifically, lymph nodes were annotated if > 1.5 cm in short axis. Other lesions were annotated if > 1 cm.
5. Lesions were labeled separately.
6. Seed points were automatically generated but reviewed by a radiologist.
7. 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. “Tracking ID” and “Tracking UID” tags were 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 (with authentication) to access these data can be found in the Additional Resources section below.

Data Access

Version 1: Updated 2023/02/10

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: