Summary
This dataset contains image annotations derived from the NCI Clinical Trial "ACRIN-HNSCC-FDG-PET/CT (ACRIN 6685)”. 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. In a typical patient all available time points were annotated. The following annotation rules were followed:
- PERCIST criteria was followed for PET imaging. Specifically, the lesions estimated to have the most elevated SUVmax were annotated.
- 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.
- Three-dimensional segmentations of lesions were created in the axial plane. If no axial plane was available, lesions were annotated in the coronal plane.
- MRIs were annotated using the T1-weighted axial post contrast sequence.
- Some lesions may cross multiple exams (ie. an MRI of the head and an MRI of the neck). The images portions on each exam were then annotated. If, however, the complete lesion was visualized on either a neck or head exam, then the other exam was not annotated to avoid redundancy.
- Lesions were labeled separately.
- The volume of each annotated lesion was calculated and reported in cubic centimeters [cc] in a dataset metadata report.
- A “negative” annotation was created for any exam without findings.
At each time point:
Volume calculations were performed for each segmented structure. These calculations are provided in the Annotation Metadata CSV.- A seed point (kernel) was created for each segmented structure. The seed points for each segmentation are provided in a separate DICOM RTSTRUCT file.
- SNOMED-CT “Anatomic Region Sequence” and “Segmented Property Category Code Sequence” and codes were inserted for all segmented structures.
- “Tracking ID” and “Tracking UID” tags were inserted for each segmented structure to enable longitudinal lesion tracking.
- Imaging time point codes were inserted to help identify each annotation in the context of the clinical trial assessment protocol.
- “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”.
- Content Item in “Acquisition Context Sequence” was added containing "Time Point Type" using Concept Code Sequence (0040,A168) selected from:
- (255235001, SCT, “Pre-dose”)
- (719864002, SCT, "Post-cancer treatment monitoring")
Important supplementary information and sample code
- A spreadsheet containing key details about the annotations is available in the Data Access section below.
- 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.
Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:
Hospital/Institution Name city, state, country - Special thanks to First Last Names, degree PhD, MD, etc from the Department of xxxxxx, Additional Names from same location.
- Continue with any names from additional submitting sites if collection consists of more that one.
Data Access
Data Type | Download all or Query/Filter | License |
---|---|---|
Images, Segmentations, and Radiation Therapy Structures/Doses/Plans (DICOM, XX.X GB) << latter two items only if DICOM SEG/RTSTRUCT/RTDOSE/PLAN exist >> | (Download requires NBIA Data Retriever) | |
Clinical data (CSV) |
Click the Versions tab for more info about data releases.
Additional Resources for this 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
Third Party Analyses of this Dataset
TCIA encourages the community to publish your analyses of our datasets. Below is a list of such third party analyses published using this Collection:
- <add links to TCIA Analysis Result DOIs here>
Detailed Description
Image Statistics | Radiology Image Statistics | Pathology Image Statistics |
---|---|---|
Modalities | ||
Number of Patients | ||
Number of Studies | ||
Number of Series | ||
Number of Images | ||
Images Size (GB) |
<< Add any additional information that didn't fit or belong in the Summary section. >>
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
DOI goes here. Create using Datacite with information from Collection Approval form
Publication Citation
We ask on the proposal form if they have ONE traditional publication they'd like users to cite.
Acknowledgement
Required acknowledgements only (ex:The CPTAC program requests that publications using data from this program...). If they just want to thank someone, that goes in the Acknowledgement section underneath the Summary.
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 yyyy/mm/dd
Data Type | Download all or Query/Filter | License |
---|---|---|
Images, Segmentations, and Radiation Therapy Structures/Doses/Plans (DICOM, XX.X GB) << latter two items only if DICOM SEG/RTSTRUCT/RTDOSE/PLAN exist >> | (Download requires the NBIA Data Retriever) | |
Tissue Slide Images (SVS, XX.X GB) | ||
Clinical data (CSV) |
<< One or two sentences about what you changed since last version. No note required for version 1. >>