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Summary

This dataset contains image annotations derived from the NCI Clinical Trial "Rituximab and Combination Chemotherapy in Treating Patients With Diffuse Large B-Cell Non-Hodgkin's Lymphoma (CALGB50303)”.  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 all available time points were annotated.

In a typical patient the following annotation rules were followed:

a.    PERCIST criteria was followed. Specifically, the lesions estimated to have the most elevated SUVmax were annotated. 
b.    Lesions were annotated in the axial plane. If no axial plane were available, lesions were annotated in the coronal plane. 
c.    Lesions were annotated on the attenuation corrected PET series as well as the diagnostic contrast-enhanced CT. If no diagnostic contrast-enhanced CT was available for that timepoint, then the non-contrast CT portion of the PET/CT was annotated. 
d.    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 were followed. Specifically, lymph nodes were annotated if > 1.5 cm in short axis. Other lesions were annotated if > 1 cm.  
e.    Lesions were labeled separately.
f.    Seed points were automatically generated and reviewed by a radiologist.

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

Data TypeDownload all or Query/FilterLicense

CALGB50303 Annotations - Segmentations, Seed Points, and Negative Findings Assessments (DICOM, 0.1 GB)


   

(Download requires NBIA Data Retriever)

CALGB50303 Annotation Metadata (CSV)

Click the Versions tab for more info about data releases.

Additional Resources for this Dataset

Collections Used in this Third Party Analysis

Below is a list of the Collections used in these analyses:

Source Data TypeDownloadLicense
Original CALGB50303 Images used to create Segmentations and Seed Points (DICOM, 78.7 GB)

 

(Download requires NBIA Data Retriever)

Original CALGB50303 Images used to create Negative Assessment reports (DICOM, 12.0 GB)

 

(Download requires NBIA Data Retriever)


Detailed Description

Image Statistics

Radiology Image Statistics

Modalities

RTSTRUCT

Number of Patients

155

Number of Studies

519

Number of Series

3077

Number of Images

3077

Images Size (GB)0.1



Citations & Data Usage Policy

Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution should include references to the following citations:

Data Citation

Rozenfeld, M., & Jordan, P. (2023). Annotations for Rituximab and Combination Chemotherapy in Treating Patients With Diffuse Large B-Cell Non-Hodgkin's Lymphoma (CALGB50303-Tumor-Annotations) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/9JER-G980

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

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.

Version 1 (Current): Updated 2023/03/30

Data TypeDownload all or Query/FilterLicense

CALGB50303 Annotations - Segmentations, Seed Points, and Negative Findings Assessments (DICOM, 0.1 GB)


    (Download requires the NBIA Data Retriever)

CALGB50303 Annotation Metadata (CSV)
Original CALGB50303 Images used to create Segmentations and Seed Points (DICOM, 78.7 GB)

 

(Download requires the NBIA Data Retriever)

Original CALGB50303 Images used to create Negative Assessment reports (DICOM, 12.0 GB)

 

(Download requires the NBIA Data Retriever)



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