| abstract |
Noninvasive imaging biomarkers to predict cancer treatment response based on early measurements, which would spare non-responding patients from unnecessary side effects and costs of ineffective treatment. Tissue characterization, classification and/or discrimination method is provided to capture different patterns of tissue perfusions. Two or three-dimensional dynamic contrast enhanced ultrasound (DCE US) data of a contrast bolus perfused tissue are acquired or available. Parametric perfusion maps of contrast bolus tissue perfusion parameters representing the DCE US data are generated. For each of the generated parametric perfusion maps statistical parameters are extracted. These statistical parameters, which are based on underlying perfusion characteristics, are first order statistical parameters, second order statistical parameters, or a combination thereof. The method then further classifies and/or discriminates the perfusion maps of the tissue using the extracted statistical parameters. |