Researchers: Elizabeth Le, James Rudd, Fulvio Zaccagna, Yuan Huang, Balaji Ganesan (TexRAD – Centre Industry Partner)

Using pooled, well-characterised CT datasets from subjects with vascular disease, we are investigating whether quantifying calcium density and quantity can predict symptomatic state, beyond conventional vascular risk factors.

We will also consider the value of image heterogeneity analysis of atherosclerotic plaque texture in risk prediction. Using TexRAD, a proprietary software that enables textural analysis to be applied to medical images, we will derive quantitative descriptors from the images that are not normally visible to the naked eye. TexRAD allows heterogeneity parameters measured at different spatial scales to be compared and presented as ‘texture ratios’ or ‘texture spectra’ enabling quantitative assessment of imaging biomarkers.

We will further consider semantic features such as the spatial characteristics and biological composition of plaque using co-registered FDG and DOTATATE PET datasets.