The nature of mathematical modeling
The nature of mathematical modeling
EVAM: an eigenvector-based algorithm for multichannel blinddeconvolution of input colored signals
IEEE Transactions on Signal Processing
IEEE Transactions on Information Technology in Biomedicine
Simultaneous estimation of physiological parameters and the input function - in vivo PET data
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
Dynamic PET, in contrast to static PET, can identify temporal variations in the radiotracer concentration. Mathematical modeling of the tissue of interest in dynamic PET can be simplified using compartment models as a linear system where the time activity curve of a specific tissue is the convolution of the tracer concentration in the plasma and the impulse response of the tissue containing kinetic parameters. Since the arterial sampling of blood to acquire the value of tracer concentration is invasive, blind methods to estimate both blood input function and kinetic parameters have recently drawn attention. Several methods have been developed, but the effect of accuracy of the estimated blood function on the estimation of the kinetic parameters is not studied. In this paper, we present a method to compute the error in the kinetic parameter estimates caused by the error in the blood input function. Computer simulations show that analytical expressions we derive are sufficiently close to results obtained fromnumerical methods. Our findings are important to observe the effect of the blood function on kinetic parameter estimation, but also useful to evaluate various blind methods and observe the dependence of kinetic parameter estimates to certain parts of the blood function.