Comparison of Different Algorithms for Minimizing Macro Vessel Signal in Cerebral Perfusion Imaging

Gernot Reishofer¹, Karl Koschutnig², Christian Enzinger³, Stefan Ropele³, Franz Ebner²

Parameter values obtained by DSC-MRI are often overestimated compared to PET and SPECT, which is due to the high sensitivity of DSC-MRI to large vessel. Two methods for minimizing macro vessel signal are compared in this work. First, the ICA method which is based on the separation of independent flow patterns using independent component analysis and second, the ELV method which is based on clustering of parameters derived from the dynamic contrast-enhanced first-pass curve. Our results indicate that the ICA method has some advantages over the ELV method and should be preferred for minimizing macro vessel signal in DSC-MRI data.