Performance of Ordered-Subset Reconstruction Algorithms Under Conditions of Extreme Attenuation and Truncation in Myocardial SPECT

We studied the bias and variance characteristics of the ordered-subset expectation maximization (OSEM) and rescaled block-iterative EM (RBIEM) iterative reconstruction algorithms in myocardial SPECT under extreme, but realistic, conditions. We used the 2-dimensional mathematic cardiac torso phantom to simulate 2 patient anatomies: a large male with a raised diaphragm and a female with large breast size, approximating extreme cases of attenuation conditions found in the clinic. For each anatomy, realistic 201Tl projection data were simulated for a 180 degrees acquisition arc. Three cases of truncation for a 90 degrees-configured dual detector system were simulated: no truncation, moderate truncation, and extreme truncation. For each case, an ensemble of 250 noise simulations was generated, and each noisy dataset was reconstructed with the OSEM and RBIEM algorithms. The reconstructions modeled only the effects of nonuniform attenuation and used a range of subset configurations. Over the ensemble, we computed means and variances of activity in 8 regions of interest (ROIs) in the heart as a function of iteration. Under conditions of no truncation and moderate truncation, the results from OSEM and RBIEM were very close to those from maximum-likelihood EM (MLEM); in all cases, the difference in ROI means was