title: Spectral Analysis of Dynamic PET Studies: A Review of 20 Years of Method Developments and Applications.
abstract: In Positron Emission Tomography (PET), spectral analysis (SA) allows the quantification of dynamic data by relating the radioactivity measured by the scanner in time to the underlying physiological processes of the system under investigation. Among the different approaches for the quantification of PET data, SA is based on the linear solution of the Laplace transform inversion whereas the measured arterial and tissue time-activity curves of a radiotracer are used to calculate the input response function of the tissue. In the recent years SA has been used with a large number of PET tracers in brain and nonbrain applications, demonstrating that it is a very flexible and robust method for PET data analysis. Differently from the most common PET quantification approaches that adopt standard nonlinear estimation of compartmental models or some linear simplifications, SA can be applied without defining any specific model configuration and has demonstrated very good sensitivity to the underlying kinetics. This characteristic makes it useful as an investigative tool especially for the analysis of novel PET tracers. The purpose of this work is to offer an overview of SA, to discuss advantages and limitations of the methodology, and to inform about its applications in the PET field.
authors.affiliation: Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
authors.forename: Mattia
authors.identifier: 0000-0003-3562-0683
authors.initials: M
authors.lastname: Veronese
authors.affiliation: Department of Information Engineering, University of Padova, Padova, Italy.
authors.forename: Gaia
authors.initials: G
authors.lastname: Rizzo
authors.affiliation: Department of Information Engineering, University of Padova, Padova, Italy.
authors.forename: Alessandra
authors.initials: A
authors.lastname: Bertoldo
authors.affiliation: Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
authors.forename: Federico E
authors.initials: FE
authors.lastname: Turkheimer
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain / Q000000981:diagnostic imaging*; D003196:Computer Graphics; D019788:Fluorodeoxyglucose F18; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007700:Kinetics; D016014:Linear Models; D049268:Positron-Emission Tomography / Q000639:trends*; D013053:Spectrophotometry / Q000639:trends*
chemical_list: D019788:Fluorodeoxyglucose F18