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RADCURE

The Cancer Imaging Archive

RADCURE | Computed Tomography Images from Large Head and Neck Cohort

DOI: 10.7937/J47W-NM11 | Data Citation Required | 1k Views | 4 Citations | Image Collection

Location Species Subjects Data Types Cancer Types Size Supporting Data Status Updated
Head-Neck Human 3,346 CT, RTSTRUCT, Other, Demographic, Diagnosis, Exposure, Follow-Up, Treatment Oropharyngeal 390.25GB Clinical Limited, Complete 2024/03/27

Summary

The RADCURE dataset was collected clinically for radiation therapy treatment planning and retrospectively reconstructed for quantitative imaging research.  

Inclusion: The dataset used for this study consists of 3,346 head and neck cancer CT image volumes collected from 2005-2017 treated with definitive RT at the University Health Network (UHN) in Toronto, Canada

Acquisition and Validation Methods: RADCURE contains computed tomography (CT) images with corresponding normal and non-normal tissue contours. CT scans were collected using systems from three different manufacturers. Standard clinical imaging protocols were followed, and contours were generated and reviewed at weekly quality assurance rounds. RADCURE imaging and structure set data was extracted from our institution’s radiation treatment planning and oncology systems using an in-house data mining and processing system. Furthermore, images are linked to clinical data for each patient and include demographic, clinical and treatment information based on the 7th edition TNM staging system. The median patient age is 63, with the final dataset including 80% males. Oropharyngeal cancer makes up 50% of the population with larynx, nasopharynx, and hypopharynx cancer, comprising 25, 12, and 5% respectively. Median follow-up was 5 years with 60% of the patients alive at last follow-up.   

Data Format and Usage Notes: During extraction of images and contours from our institution’s radiation treatment planning and oncology systems, the data was converted to DICOM and RTSTRUCT formats, respectively. To improve the usability of the RTSTRUCT files, individual contour names were standardized for primary tumor volumes and 19 organs-at-risk. Demographic, clinical, and treatment information is provided as a comma-separated values (csv) file. This dataset is a superset of the Radiomic Biomarkers in Oropharyngeal Carcinoma (OPC-Radiomics) dataset and fully encapsulates all previous data; this dataset replaces the OPC-Radiomics dataset. The RTSTRUCTs from OPC-Radiomics have been standardized to adhere to the TG263 nomenclature. Age of 90 years or greater is considered PHI and set to 90 years to minimize impact to privacy. Both radiological and clinical metadata were offset by an undisclosed number of days for anonymization and should be noted for downstream analysis. The TG263-standardized RTSTRUCTs include only the GTVp (primary gross tumor volume) contours. Patients without corresponding GTVp contours will not have RTSTRUCTs.

Potential Applications: The availability of imaging, clinical, demographic and treatment data in RADCURE makes it a viable option for a variety of quantitative image analysis research initiatives. This includes the application of machine learning or artificial intelligence methods to expedite routine clinical practices, discover new non-invasive biomarkers, or develop prognostic models.  

Data Access

Some data in this collection contains images that could potentially be used to reconstruct a human face. To safeguard the privacy of participants, users must sign and submit a TCIA Restricted License Agreement to help@cancerimagingarchive.net before accessing the data.

Version 3: Updated 2024/03/27

Added 3,337 RTSTRUCTs for phase 2 release: This full release of RADCURE contains all clinically available contours (primary gross tumor volume (GTVp), nodal gross tumor volume (GTVn), and 19 OARs), as mentioned in Welch et al., 2024, https://doi.org/10.1002/mp.16972.

Title Data Type Format Access Points Subjects Studies Series Images License
Images and Radiation Therapy Structures, full dataset CT, RTSTRUCT DICOM
Download requires NBIA Data Retriever
3,346 3,346 9,677 618,821 TCIA Restricted
Images and Radiation Therapy Structures, updated OPC-Radiomics subset CT, RTSTRUCT DICOM
Download requires NBIA Data Retriever
606 606 1,142 108,735 TCIA Restricted
Clinical data Demographic, Diagnosis, Exposure, Follow-Up, Treatment, Other XLSX 3,346 CC BY 4.0
Patient ID Mapping-RADCURE patient id to OPC-RADIOMICS patient id Other CSV 606 CC BY 4.0
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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

Welch, M. L., Kim, S., Hope, A., Huang, S. H., Lu, Z., Marsilla, J., Kazmierski, M., Rey-McIntyre, K., Patel, T., O’Sullivan, B., Waldron, J., Kwan, J., Su, J., Soltan Ghoraie, L., Chan, H. B., Yip, K., Giuliani, M., Princess Margaret Head And Neck Site Group, Bratman, S., Haibe-Kains, B., Tadic, T. (2023). Computed Tomography Images from Large Head and Neck Cohort (RADCURE) (Version 3) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/J47W-NM11

Acknowledgements

We would like to acknowledge the individuals and institutions that have provided data for this collection:

  • University Health Network (UHN), Toronto, Ontario, Canada - Special thanks to  Scott Bratman, PhD, Department of Radiation Oncology and Medical Biophysics, University of Toronto. 

Related Publications

Publications by the Dataset Authors

The authors recommended the following as the best source of additional information about this dataset:

Publication Citation

Welch, M. L., Kim, S., Hope, A. J., Huang, S. H., Lu, Z., Marsilla, J., Kazmierski, M., Rey‐McIntyre, K., Patel, T., O’Sullivan, B., Waldron, J., Bratman, S., Haibe‐Kains, B., & Tadic, T. (2024). RADCURE: An open‐source head and neck cancer CT dataset for clinical radiation therapy insights. In Medical Physics. Wiley. https://doi.org/10.1002/mp.16972

The Collection authors recommend these readings to give context to this dataset

Kazmierski, M., Welch, M., Kim, S., McIntosh, C., Rey-McIntyre, K., Huang, S. H., Patel, T., Tadic, T., Milosevic, M., Liu, F.-F., Ryczkowski, A., Kazmierska, J., Ye, Z., Plana, D., Aerts, H. J. W. L., Kann, B. H., Bratman, S. V., Hope, A. J., & Haibe-Kains, B. (2023). Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics. In Cancer Research Communications (Vol. 3, Issue 6, pp. 1140–1151). American Association for Cancer Research (AACR). https://doi.org/10.1158/2767-9764.crc-22-0152

Publication Citation

Welch, M. L., Kim, S., Hope, A. J., Huang, S. H., Lu, Z., Marsilla, J., Kazmierski, M., Rey‐McIntyre, K., Patel, T., O’Sullivan, B., Waldron, J., Bratman, S., Haibe‐Kains, B., & Tadic, T. (2024). RADCURE: An open‐source head and neck cancer CT dataset for clinical radiation therapy insights. In Medical Physics. Wiley. https://doi.org/10.1002/mp.16972

Research Community Publications

TCIA maintains a list of publications that leveraged this dataset. If you have a manuscript you’d like to add please contact TCIA’s Helpdesk.

TCIA maintains a list of publications that leveraged this dataset. If you have a manuscript you’d like to add please contact TCIA’s Helpdesk.

Additional Publications Related to this Work

The Collection authors recommend these readings to give context to this dataset

Kazmierski, M., Welch, M., Kim, S., McIntosh, C., Rey-McIntyre, K., Huang, S. H., Patel, T., Tadic, T., Milosevic, M., Liu, F.-F., Ryczkowski, A., Kazmierska, J., Ye, Z., Plana, D., Aerts, H. J. W. L., Kann, B. H., Bratman, S. V., Hope, A. J., & Haibe-Kains, B. (2023). Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics. In Cancer Research Communications (Vol. 3, Issue 6, pp. 1140–1151). American Association for Cancer Research (AACR). https://doi.org/10.1158/2767-9764.crc-22-0152

Other Publications Using this Data

TCIA maintains a list of publications that leveraged this dataset. If you have a manuscript you’d like to add please contact TCIA’s Helpdesk.

Previous Versions

Version 2: Updated 2023/11/30

Clinical data changes:

  1. RT_Tech column removed due to ambiguity.
  2. Added Contrast Enhanced column, indicates which patients received contrast.

Title Data Type Format Access Points Subjects Studies Series Images License
Images and Radiation Therapy Structures, full dataset RTSTRUCT, CT DICOM
Download requires NBIA Data Retriever
3,346 3,346 6,340 615,484 TCIA Restricted
Images and Radiation Therapy Structures, updated OPC-Radiomics subset RTSTRUCT, CT DICOM
Download requires NBIA Data Retriever
606 606 1,142 108,735 TCIA Restricted
Clinical Data XLSX 3,346 0 CC BY 4.0
Patient ID Mapping-RADCURE patient id to OPC-RADIOMICS patient id Other CSV CC BY 4.0

Version 1: Updated 2023/06/14

Title Data Type Format Access Points Subjects Studies Series Images License
Images and Radiation Therapy Structures, full dataset CT, RTSTRUCT DICOM
Download requires NBIA Data Retriever
3,346 3,346 9,693 618,837 TCIA Restricted
Images and Radiation Therapy Structures, updated OPC-Radiomics CT, RTSTRUCT DICOM
Download requires NBIA Data Retriever
606 606 1,142 108,735 TCIA Restricted
Clinical data XLSX CC BY 4.0
Patient ID Mapping-RADCURE patient id to OPC-RADIOMICS patient id CSV CC BY 4.0