A spectral analysis approach was used to estimate kinetic model parameters of the L-[1-(11)C]leucine positron emission tomography (PET) method and regional rates of cerebral protein synthesis (rCPS) in predefined regions of interest (ROIs). Unlike analyses based on the assumption that tissue ROIs are kinetically homogeneous, spectral analysis allows for heterogeneity within a region. To improve estimation performance, a new approach was developed-spectral analysis with iterative filter (SAIF). In simulation SAIF produced low bias, low variance estimates of the influx rate constant for leucine (K(1)), blood volume fraction (V(b)), fraction of unlabeled leucine in the tissue precursor pool for protein synthesis derived from arterial plasma (lambda), and rCPS. Simulation of normal count rate studies showed that SAIF applied to ROI time-activity curves (TACs) performed comparably to the basis function method (BFM) applied to voxel TACs when voxelwise estimates were averaged over all voxels in the ROI. At low count rates, however, SAIF performed better. In measured L-[1-(11)C]leucine PET data, there was good agreement between ROI-based SAIF estimates and average voxelwise BFM estimates of K(1), V(b), lambda, and rCPS. We conclude that SAIF sufficiently addresses the problem of tissue heterogeneity in ROI data and provides a valid tool for estimation of rCPS, even in low count rate studies.