Direct kinetic parameter estimation from dynamic ECT sinogram using dimension-reduced time-activity basis

Presents an algorithm of reduced computational cost which is able to estimate kinetic model parameters directly from dynamic ECT sinograms. The algorithm exploits the extreme degree of parameter redundancy inherent in linear combinations of the exponential functions which represent the modes of first order compartmental systems. The singular value decomposition is employed to find a small set of orthogonal functions, the linear combinations of which are able to accurately represent all modes within the physiologically anticipated range in a given study. The reduced-dimension basis is formed as the convolution of this orthogonal set with a measured input function. The Moore-Penrose pseudoinverse is used to find coefficients of this basis. Algorithm performance is evaluated at realistic count rates using MCAT phantom and clinical ⁹⁹Tc-teboroxime myocardial study data. Recovered tissue responses compare favorably with those obtained using more computationally intensive methods