FUZZY CLUSTERING OF GRADIENT-ECHO FUNCTIONAL MRI IN THE HUMAN VISUAL-CORTEX - PART II - QUANTIFICATION

Fuzzy cluster analysis (FCA) is a new exploratory method for analyzing fMRI data. Using simulated functional MRI (fMRI) data, the performanc e of FCA, as implemented in the software package Evident, was tested a nd a quantitative comparison with correlation analysis is presented. F urthermore, the fMRI model fit allows separation and quantification of now and blood oxygen level dependent (BOLD) contributions in the huma n visual cortex. In gradient-recalled echo fMRI at 1.5 T (TR = 60 ms, TE = 42 ms, radiofrequency excitation flip angle [theta] = 10 degrees- 60 degrees) total signal enhancement in the human visual cortex, ie, n ow-enhanced BOLD plus inflow contributions, on average varies from 5% to 10% in or close to the visual cortex (average cerebral blood volume [CBV] = 4%) and from 10% to 20% in areas containing medium-sized vess els (ie, average CBV = 12% per voxel), respectively. Inflow enhancemen t, however, is restricted to intravascular space (= CBV) and increases with increasing radiofrequency (RF) flip angle, whereas BOLD contribu tions may be obtained from a region up to three times larger and, appl ying an unspoiled gradient-ache (GRE) sequence, also show a flip angle dependency with a minimum at approximately 30 degrees, This result su ggests that a localized hemodynamic response from the microvasculature at 1.5 T maybe extracted via fuzzy clustering, In summary, fuzzy clus tering of fMRI data, as realized in the Evident software, is a robust and efficient method to (a) separate functional brain activation from noise or other sources resulting in time-dependent signal changes as p roven by simulated fMRI data analysis and in vivo data hom the visual cortex, and (b) allows separation of different levels of activation ev en if the temporal pattern is indistinguishable. Combining fuzzy clust er separation of brain activation with appropriate model calculations allows quantification of now and (flow-enhanced) BOLD contributions in areas with different vascularization.