Estimation of dynamic time activity curves from dynamic cardiac SPECT imaging

Whole-heart coronary flow reserve (CFR) may be useful as an early predictor of cardiovascular disease or heart failure. Here we propose a simple method to extract the time-activity curve, an essential component needed for estimating the CFR, for a small number of compartments in the body, such as normal myocardium, blood pool, and ischemic myocardial regions, from SPECT data acquired with conventional cameras using slow rotation. We evaluated the method using a realistic simulation of (99m)Tc-teboroxime imaging. Uptake of (99m)Tc-teboroxime based on data from the literature were modeled. Data were simulated using the anatomically-realistic 3D NCAT phantom and an analytic projection code that realistically models attenuation, scatter, and the collimator-detector response. The proposed method was then applied to estimate time activity curves (TACs) for a set of 3D volumes of interest (VOIs) directly from the projections. We evaluated the accuracy and precision of estimated TACs and studied the effects of the presence of perfusion defects that were and were not modeled in the estimation procedure.The method produced good estimates of the myocardial and blood-pool TACS organ VOIs, with average weighted absolute biases of less than 5% for the myocardium and 10% for the blood pool when the true organ boundaries were known and the activity distributions in the organs were uniform. In the presence of unknown perfusion defects, the myocardial TAC was still estimated well (average weighted absolute bias <10%) when the total reduction in myocardial uptake (product of defect extent and severity) was ≤ 5%. This indicates that the method was robust to modest model mismatch such as the presence of moderate perfusion defects and uptake nonuniformities. With larger defects where the defect VOI was included in the estimation procedure, the estimated normal myocardial and defect TACs were accurate (average weighted absolute bias ≈ 5% for a defect with 25% extent and 100% severity).