Evaluation of factor analysis accuracy for myocardial perfusion in PET studies

Factor Analysis of Medical Image Sequences (FAMIS) estimates kinetics (factors) and corresponding spatial regions (factor images) from dynamic studies, taking into account statistical noise and spillover effects. Factor images obtained from ¹⁵O-water clinical cardiac PET studies are less noisy than conventional subtraction images, and factors match physiologic kinetics. Here, the authors studied FAMIS accuracy and precision depending on the application context. FAMIS was evaluated through kinetics parameters quantification. Numerical simulations and phantom experiments were carried out using a typical left ventricular pattern. This object was simulated in 2D with 3 noise levels and 2 kinds of kinetics: mono-exponentials which correspond to natural tracer decay, and tissue perfusion kinetics obtained with a realistic vascular input function. Mono-exponentials association was adapted to phantom experiments while perfusion kinetics represented clinical cardiac studies. In both phantom experiments and simulations, the inner chamber was filled with ¹⁵ O-water and the myocardial space with Carbon-11. The different noise levels which were studied corresponded to ideal, normal and low quality scans. Using the factors estimated by FAMIS, decay constants and an index of flow (k1) were estimated by fitting or modelling. Relative bias to the true value and standard deviation were then estimated, and spatial correlation between factor images and original spatial pattern was computed. Factor images spatial correlation was very good, despite of large overlapping pattern. Oxygen-15 decay constant was assessed from factor with a small relative bias, for all noise levels and trixel sizes. However, Carbon-11 extraction was very sensitive to both noise and spillover in phantom and simulations. A reasonable bias was only achieved by including a spillover term which accounted for an overcorrection. On the contrary, factors associated to perfusion were well extracted and k1 parameter was recovered with a low relative bias (r.b.<6%), except for the higher noise level. It was already shown that FAMIS performances depend on the overlap of the spatial structures. This study demonstrates that factor analysis without a priori information performances depend on kinetics shape. Moreover, in the context of cardiac ¹⁵O-water perfusion studies, FAMIS should provide accurate quantification