Evaluation and Optimization of Compensation Methods for Myocardial SPECT using a Set of Realistic Phantoms that Include Patient Variability

The goal of this study was to evaluate and optimize different compensation methods used during reconstruction process with respect to defect detection in myocardial SPECT images. Various combinations of attenuation, detector response and scatter compensation were used in this study. A major difference between this and previous studies was that the level of realism was significantly increased by inclusion of variability in heart and organ uptakes in the heart size and orientation, and in the defect size and contrast. In this study we used a population of 24 3D NCAT phantoms (half male, half female) recently developed with models for organ uptake and organ size based on clinical data. Almost noise-free projection data of the torso, heart, liver, lungs, and other organs were simulated for each phantom using the SIMSET MC simulation code. They were then combined to form 72 sets of projections for each phantom using randomly sampled activity ratios from a clinically realistic distribution. Poisson noise was then added. We applied the Channelized Hotelling Observer (CHO) and Receiver Operating Characteristic (ROC) analysis to optimize iteration number for OSEM and cutoff frequency of a 3-D post-reconstruction Butterworth filter. We found that the Area Under Curves (AUC) values were reduced compared to a previous study that included significantly less phantom variability, even though the defect contrast was higher and noise level was lower. The resulting AUC values were similar to those obtained using patient data. We found, in agreement with the previous study, that including compensation for more effects resulted in improved defect detectabilty. However, the optimal filter cutoff was increased compared to the previous study. These studies demonstrate the importance of including realistic levels of phantom variability in evaluation of myocardial perfusion studies.