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Description
This study describes a subset of the HNSCC collection on TCIA.
There is an unmet need for integrating quantitative imaging biomarkers into current risk stratification tools and to explore the correlation between radiomics features –alone or in combination with clinical prognosticators- and tumor outcome. Clinical meta-data and matched baseline contrast-enhanced computed tomography (CECT) scans were used to build a cohort of 495 oropharyngeal cancer (OPC) patients treated between 2005 and 2012. Expert radiation oncologists manually segmented primary and nodal disease gross volumes (GTVp & GTVn). Structures were named per the American Association of Physicists in Medicine (AAPM) TG-263 recommendations, then retrieved in RT-STRUCT format. Matched patient, disease, treatment and outcomes data were obtained. Radiomics analysis was performed using an open-source institutionally-developed software that runs on Matlab platform.
A related dataset is here: Data from Head and Neck Cancer CT Atlas. DOI: 10.7937/K9/TCIA.2017.umz8dv6sand the combined collection is listed here: HNSCC
Acknowledgements:
This research was supported by the Andrew Sabin Family Foundation; Dr. Fuller is a Sabin Family Foundation Fellow. Drs. Mohamed and Fuller receive funding support from the National Institutes of Health (NIH)/National Institute for Dental and Craniofacial Research (NIDCR) (R01DE025248) and the National Institutes of Health (NIH)/National Cancer Institute (NCI) (1R01CA214825-01).
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| title | Data Access |
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| Data AccessClick the Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever | Data Type | Download all or Query/Filter | License |
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| Images - 814 series (DICOM, 51.6 GB) |  Image Removed | | Tcia button generator |
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| url | https://wiki.cancerimagingarchive.net/download/attachments/33948240/manifest-1585330520084.tcia?api=v2 |
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(Download requires NBIA Data Retriever) | | | Clinical Data (CSV, | 79kB)Image Removed86 kB) |
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| url | https://wiki.cancerimagingarchive.net/download/attachments/33948240/Radiomics_Outcome_Prediction_in_OPC_ASRM_corrected.csv?api=v2 |
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Please contact help@cancerimagingarchive.net with any questions regarding usage. Collections Used in this Third Party Analysis |
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| title | Detailed Description |
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| Detailed Description| Image Statistics | Radiology |
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Modalities | CT, RTSTRUCT | Number of Patients | 412 | Number of Studies | 412 | Number of Series | 814 | Number of Images | 104,558 | | Images Size (GB) | 51.6 |
Methods Diagnostic contrast-enhanced computed tomography (CECT) Digital Imaging and Communications in Medicine (DICOM) files prior to any active intervention were collected for 495 OPC patients treated at our institution between 2005 and 2012. Expert radiation oncologists manually segmented primary and nodal disease gross volumes (GTVp & GTVn). Structures were named per the American Association of Physicists in Medicine (AAPM) TG-263 recommendations, then retrieved in RT-STRUCT format. Matched patient, disease, treatment and outcomes data were obtained. Radiomics analysis was performed using an open-source institutionally-developed software that runs on Matlab platform. Links to these can be found in the related publication. Note from the investigators: Some PET scans will include two PET AC files—one includes the head & neck portion of the exam, the other includes eyes-to-thighs. There is no file naming convention to distinguish between the two, so delineation may require the use of a DICOM viewer. |
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| title | Citations & Data Usage Policy |
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| Citations & Data Usage Policy These collections are freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License. Questions may be directed to help@cancerimagingarchive.net. Please be sure to acknowledge both this data set and TCIA in publications by including the following citations in your work:| Tcia limited license policy |
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| Info |
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| Elhalawani H, White AL, Zafereo J, Wong AJ, Berends JE, AboHashem S, Williams B, Aymard JM, Kanwar A, Perni S, Mulder S, Rock CD, Grossberg A, Mohamed A, Gunn GB, Frank SJ, Rosenthal DI, Garden AS, Fuller CD; M.D. Anderson Cancer Center Head and Neck Quantitative Imaging Working Group (2018). Radiomics outcome prediction in Oropharyngeal cancer [Dataset]. The Cancer Imaging Archive. httpDOI: //dx.doi.org/ 10.7937/TCIA.2020.2vx6-fy46 |
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| title | Publication Citation |
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| Elhalawani, H., Mohamed, A., White, A. et al. Matched computed tomography segmentation and demographic data for oropharyngeal cancer radiomics challenges. Sci Data 4, 170077 (2017). DOI: 10.1038/sdata.2017.77 (coming soon) |
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| Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. (paper) |
In addition to the dataset citation above, please be sure to cite the following if you utilize these data in your research: | Info |
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| title | Publication Citation |
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| Elhalawani, H., Mohamed, A., White, A. et al. Matched computed tomography segmentation and demographic data for oropharyngeal cancer radiomics challenges. Sci Data 4, 170077 (2017). DOI: 10.1038/sdata.2017.771007/s10278-013-9622-7 |
Other Publications Using This DataTCIA maintains a list of publications that leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk. |
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| Version 1 (Current): 2020/02/282 (Current): Updated 2022/08/02 | Data Type | Download all or Query/Filter |
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| Images - 814 series (DICOM, 51.6 GB) |
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| url | https://wiki.cancerimagingarchive.net/download/attachments/33948240/manifest-1585330520084.tcia?api=v2 |
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(Download requires NBIA Data Retriever) | | Clinical Data (CSV, 86 kB) |
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| url | https://wiki.cancerimagingarchive.net/download/attachments/33948240/Radiomics_Outcome_Prediction_in_OPC_ASRM_corrected.csv?api=v2 |
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Corrected version of the clinical data CSV attached, because the investigators noticed an error in some of the durations of the endpoints including the overall survival, local and regional control, and freedom from distant metastasis. The original excel sheet had errors because the formulas to calculate the duration for patients with events were not applied so we fixed this error and now all the durations are correct. Version 1: Updated 2020/03/31| Data Type | Download all or Query/Filter |
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| Images - 814 series (DICOM, 51.6 GB) |
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(Download requires NBIA Data Retriever) | | Clinical Data (CSV, 79 kB) |
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