Direct least squares estimation of spatiotemporal distributions from dynamic cardiac SPECT projections

Artifacts can result when reconstructing a dynamic image sequence from inconsistent, as well as insufficient and truncated, cone beam SPECT projection data acquired by a slowly rotating gantry. The artifacts can lead to biases in kinetic model parameters estimated from time-activity curves generated by overlaying volumes of interest on the images. However, the biases in time-activity curve estimates and subsequent kinetic parameter estimates can be reduced significantly by first modeling the spatial and temporal distribution of the radiopharmaceutical throughout the projected field of view, and then estimating the time-activity curves directly from the projections. This approach is potentially useful for clinical SPECT studies involving slowly rotating gantries, particularly those using a single-detector system or body contouring orbits with a multi-detector system. We have implemented computationally efficient methods for fully 4-D direct estimation of spatiotemporal distributions from dynamic cone beam SPECT projection data. Temporal splines were used to model the time-activity curves for the blood pool and tissue volumes in a simulated cardiac data acquisition. Least squares estimates of time-activity curves were obtained quickly and accurately using a workstation. From these curves, kinetic parameters were estimated accurately for noiseless data and with some bias for noisy data