Voxelwise quantification of [(11)C](R)-rolipram PET data: a comparison between model-based and data-driven methods.

ABSTRACT: This study compared model-based and data-driven methods to assess the best methodology for generating precise and accurate parametric maps of the parameters of interest in [(11)C](R)-rolipram brain positron-emission tomography studies. Parametric images were generated using (1) a two-tissue compartmental model (2TCM) solved with the hierarchical basis function method (H-BFM) linear estimator; (2) data-driven spectral-based methods: standard spectral analysis (std SA) and rank-shaping SA (RS); and (3) the Logan graphical plot. Nonphysiologic VT estimates were eliminated and the remaining ones were compared with the reference values, i.e., those obtained with a voxelwise 2TCM solved with a nonlinear estimator. With regard to voxelwise VT estimates, H-BFM showed the best agreement with weight

SUBMITTER: Rizzo G 

PROVIDER: S-EPMC3705428 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature