Our goal is to construct a publicly available computational radiomics system for the objective and automated extraction of quantitative imaging features that we believe will yield biomarkers of greater prognostic value compared with routinely extracted descriptors of tumor size. We will create a generalized, open, portable, and extensible radiomics platform that is widely applicable across cancer types and imaging modalities and describe how we will use lung and head and neck cancers as models to validate our developments. To achieve our goals we will identify and implement a large array of quantitative imaging features, develop a flexible radiomics platform usable by both image analysis experts (such as engineering scientists) and imaging non-experts (such as bioinformatics scientists or physicians) alike, and validate these developments by integrating radiomics, genomics, and clinical data to evaluate prognostic performance and examine associations. We will take advantage of The Cancer Imaging Archive (TCIA) with imaging data, and The Cancer Genome Atlas (TCGA), with corresponding genomic and clinical data. Throughout the project all software, tools, and other resources will be made freely available to ensure community building. The aims of the project are1: Development of radiomic feature technology for the quantitative assessment of the tumor phenotype (Features). 2: Development of a software infrastructure with distribution of tools to support radiomics research (Platform). 3: Validate Developments by integrating Radiomics, Genomics, and clinical data and evaluate its prognostic performance and examine associations (Validation).
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