Computational Modeling in Quantitative Cancer Imaging

摘要

In recent years there have been dramatic increases in the range and quality of information available from non-invasive imaging methods so that a number of potentially valuable metrics are now available to quantitatively assess tumor status. Several of these have been used in both pre-clinical studies of animal models and clinical trials involving patients. However, the optimal methods by which these emerging imaging metrics are integrated and applied have yet to be developed. Here we provide an example of the kind of data available from quantitative imaging of cancer, and then propose an approach for how these data can be combined in order to offer a more comprehensive description of tumor growth and treatment response.