Elhalawani; Hesham, (et al). (2018). Radiomics outcome prediction in Oropharyngeal cancer. The Cancer Imaging Archive. http://dx.doi.org/ (coming soon)

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. 

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.

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    1. HNSCC data (first batch hyperlink),  ## series
    2. HNSCC data (second batch hyperlink) ## series
    3. Clinical data