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An investigation into the effect of input function shape and image acquisition interval on estimates of washin for
S G Ross1, A Welch, G T Gullberg
1University of Utah, Salt Lake City 84132, USA.
Abstract:
Dynamic cardiac SPECT and PET can be used to measure myocardial perfusion by estimating the kinetic rate constant describing the washing of radioactive-labelled tracers from the blood to the extravascular myocardial tissue. Because of differences in photon statistics and data acquisition techniques, protocols which produce optimal estimates of the washin for dynamic cardiac PET may give suboptimal estimates if applied in dynamic cardiac SPECT. Two important factors in the estimation of washin are the shape of the tracer input function and the image acquisition interval. This study uses computer simulations to investigate the effect of varying the tracer infusion length and image acquisition interval on the bias and variance of estimates of washin obtained with dynamic cardiac SPECT and 99mTc-labelled teboroxime. Bias in parameter estimates can be introduced by aliasing, integration of the time-varying radioactivity by the detector, and detector motion. This bias can be reduced by decreasing the acquisition interval and using a longer-duration input function. However, this results in poor photon statistics, which generate large variance, and can also introduce bias in the estimates of the washin. Our studies indicate that better estimates of the washin are obtained by using an acquisition interval that is of sufficient duration to obtain adequate photon statistics even if this is at the expense of temporal resolution. The increase in bias caused by using a 10 or 20 s acquisition interval instead of a 5 s acquisition interval is minimal when compared with the reduction in variance. Variance in estimates is also reduced by using a sharp input function, resulting in higher peak counts during washin. It is also shown that the variance of estimates of the washin increases generally when faster kinetics are observed. This variance can, however, be reduced by using longer acquisition intervals.