Abstract
The ongoing revolution in genomics provides many new research opportunities for physicists. Two crucial research areas to advance clinical oncology include the intersections between imaging and genomics, as well as the use of genomic analyses to improve patient management in radiation oncology. Confusingly, the term ‘radiogenomics’ is used for both applications. In the field of radiology, ‘radiogenomics’ refers to the underlying genomic correlates of image features, for example the correlation of tumor biopsies mRNA microarray signatures with image features. In radiation oncology and radiobiology, the term ‘radiogenomics’ refers to the impact of a patient's genotype on the relative radiosensitivity or radioresistance of normal tissues. Tumor biopsy mRNA signatures, for radiosensitivity, hypoxia, or proliferation, have been studied to predict response and to potentially individualize treatments. Blood proteomics has been applied to normal tissue responses such as radiation pneumonitis. Imaging radiogenomics can further be thought of as ‘radiomics’ + genomics, where radiomics is the extraction of quantitative image features that can be incorporated into disease classification schemes or predictive models. We will also touch on the general application of systems modeling that is so important to advancement in modern biology and response modeling. This session will emphasis new opportunities, as well as challenges and obstacles to progress. ‘Omic’ sciences will greatly impact the study and clinical use of tumor control probability and normal tissue complication probability models; the biological interpretation of image features; and the clinical implications of imaging and cancer screening.
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