Parametric imaging and statistical mapping of brain tumor in Ga-68 EDTA dynamic PET studies

摘要: To improve the reliability and sensitivity of quantitative analysis in study evaluation brain tumor using Ga-68 EDTA dynamic PET, a linear parametric imaging algorithm was developed this for estimation both distribution volume (DV) blood barrier permeability. F statistics used separating from normal tissue. A two-compartmental model to describe tracer kinetics. The operational equations: C/sub pet/=((K/sub 1/+k/sub 2/)V/sub p/)/spl int/C/sub p/ds-k/sub 2//spl pet/ds+V/sub p/C/sub p/ /spl pet/=(DV+V/sub p/ds-(1/k/sub 2/)C/sub pet/+(V/sub p//k/sub p/, were estimate K/sub 1/ (permeability) DV(=K/sub 1//k/sub 2/), respectively. reliable robust regression with spatial constraint generate DV images. Pixel-wise 2 k-2 degree freedom calculated as: F=(((k-2)k/(2(k/sup 2/-1)))D/sup 2/ D/sup 2/=(x-/spl mu/)'S/sup -1/(x-/spl mu/), where sample is two dimensional space {(K/sub 1/, DV)} reference regions tissue pixels, size k number pixels within ROIs, mu/ S are, respectively, mean vector (K/sub DV) covariance matrix. By setting critical values at 0.2, 0.05, 0.001, statistical significance level images generated, its pixel can be, 0 if 0.92) found between estimated by fitting ROI time activity curve ones method generating DV, F, high computation efficiency easy be implemented. current provided tool integrate multi-dimensional physiological information. region integration multi-physiological may specificity detection treatment.