Determination of a Multi-dimensional Parametric Model to Predict the Optimum PET SUV Threshold Values in Lung Tumor Volume Delineation

Abstract

Using FDG-PET in addition to CT to define the tumor volume has been shown to reduce the inter-observer variability and to effectively discriminate malignant from normal tissue. However, the PET SUV-threshold values used to define the internal tumor volume (ITV) has a large variation. To complicate the situation, PET images, taken over multiple respiratory cycles are prone to respiratory motion effects. We therefore developed a functional form to predict how SUV-threshold is influenced by tumor motion amplitude, tumor volume, and maximum PET SUV.