Efficient estimation of dynamic cardiac SPECT kinetic parameters using weighted least squares estimates of dynamic reconstructions

Efficient estimates of dynamic cardiac SPECT kinetic parameters are determined using weighted least squares fitting that incorporates the variance and covariance of weighted least squares estimates of dynamic reconstructions. Sequential tomographic projections are reconstructed into a sequence of 64×64 transaxial images for one transaxial slice using for each reconstruction in the time sequence a separate singular value decomposition to calculate the weighted reconstruction estimate. Attenuation factors are included in the projection equations and are calculated from a transmission reconstruction. Time-activity-curves for a sum of activity in a blood region inside the left ventricle and a sum in a cardiac tissue region, for the variance of the two estimates of the sum, and for the covariance between the two ROI estimates are generated from the attenuation corrected transaxial reconstructions. A two-compartment model is fit to the blood and tissue activity curves to give weighted least squares estimates of blood volume fraction, wash-in and wash-out rate constants specifying teboroxime kinetics for the left ventricular myocardium. For the data obtained in a dynamic cardiac SPECT study, weighted least squares reconstructions do not necessarily give more efficient estimates of the tissue kinetic parameters