title: 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 weighted nonlinear least square (WNLLS) values and the lowest percentage of mean relative difference (1±1%). All methods showed comparable variability in the relative differences. H-BFM provided the best correlation with WNLLS (y=1.034x-0.013; R(2)=0.973). Despite a slight bias, the other three methods also showed good agreement and high correlation (R(2)>0.96). H-BFM yielded the most reliable voxelwise quantification of [(11)C](R)-rolipram as well as the complete description of the tracer kinetic. The Logan plot represents a valid alternative if only VT estimation is required. Its marginally higher bias was outweighed by a low computational time, ease of implementation, and robustness.
authors.affiliation: Department of Information Engineering, University of Padova, Padova, Italy.
authors.forename: Gaia
authors.initials: G
authors.lastname: Rizzo
authors.forename: Mattia
authors.initials: M
authors.lastname: Veronese
authors.forename: Paolo
authors.initials: P
authors.lastname: Zanotti-Fregonara
authors.forename: Alessandra
authors.initials: A
authors.lastname: Bertoldo
mesh_terms: D001921:Brain / Q000000981:diagnostic imaging* / Q000378:metabolism; D001931:Brain Mapping / Q000295:instrumentation / Q000379:methods* / Q000706:statistics & numerical data; D002250:Carbon Radioisotopes; D003198:Computer Simulation; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D016018:Least-Squares Analysis; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D049268:Positron-Emission Tomography / Q000295:instrumentation / Q000379:methods* / Q000706:statistics & numerical data; D020889:Rolipram / Q000493:pharmacokinetics
chemical_list: D002250:Carbon Radioisotopes; D020889:Rolipram