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Elhalawani; Hesham, (et al). (2018). Radiomics outcome prediction in Oropharyngeal cancer. The Cancer Imaging Archive. http://dx.doi.org/ (coming soon)
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Description
There is an unmet need for integrating quantitative imaging biomarkers into current risk stratification tools. To explore the correlation between radiomics features –alone or in combintaion with clinical prognosticators- and tumor outcome, we retrieved clinical meta-data and matched baseline contrast-enhanced computed tomography (CECT) scans from a single institution, institutional review board (IRB)-approved cohort of 495 oropharyngeal cancer (OPC) patients. We opted to publicly share this large curated data set and subsequent radiomics analytical outcome via The Cancer Imaging Archive (TCIA) to serve as a resource for optimized standardization in the radiomics field.
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active | true |
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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 |
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HNSCC batch 1 Images - ## series (DICOM, X.X GB) | Coming Soon | HNSCC batch 2 Images - ## series (DICOM, X.X GB) | Coming Soon | Clinical Data (???, X.X GB) | Coming Soon |
Please contact help@cancerimagingarchive.net with any questions regarding usage. |
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title | Detailed Description |
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| Detailed DescriptionMethods 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. |
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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: |
| Publication Citation |
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- Image Data: Save/open a link below to initiate our TCIA download manager to begin your download:
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| Elhalawani; Hesham, (et al). (2018). Radiomics outcome prediction in Oropharyngeal cancer. The Cancer Imaging Archive. http://dx.doi.org/ (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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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): 2018/02/09Data Type | Download all or Query/Filter |
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HNSCC batch 1 Images - ## series (DICOM, X.X GB) | Coming Soon | HNSCC batch 2 Images - ## series (DICOM, X.X GB) | Coming Soon | Clinical Data (???, X.X GB) | Coming Soon |
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