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      Non-invasive kinetic modelling approaches for quantitative analysis of brain PET studies

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          Abstract

          Pharmacokinetic modelling with arterial sampling is the gold standard for analysing dynamic PET data of the brain. However, the invasive character of arterial sampling prevents its widespread clinical application. Several methods have been developed to avoid arterial sampling, in particular reference region methods. Unfortunately, for some tracers or diseases, no suitable reference region can be defined. For these cases, other potentially non-invasive approaches have been proposed: (1) a population based input function (PBIF), (2) an image derived input function (IDIF), or (3) simultaneous estimation of the input function (SIME). This systematic review aims to assess the correspondence of these non-invasive methods with the gold standard. Studies comparing non-invasive pharmacokinetic modelling methods with the current gold standard methods using an input function derived from arterial blood samples were retrieved from PubMed/MEDLINE (until December 2021). Correlation measurements were extracted from the studies. The search yielded 30 studies that correlated outcome parameters (V T, DVR, or BP ND for reversible tracers; K i or CMR glu for irreversible tracers) from a potentially non-invasive method with those obtained from modelling using an arterial input function. Some studies provided similar results for PBIF, IDIF, and SIME-based methods as for modelling with an arterial input function ( R 2 = 0.59–1.00, R 2 = 0.71–1.00, R 2 = 0.56–0.96, respectively), if the non-invasive input curve was calibrated with arterial blood samples. Even when the non-invasive input curve was calibrated with venous blood samples or when no calibration was applied, moderate to good correlations were reported, especially for the IDIF and SIME ( R 2 = 0.71–1.00 and R 2 = 0.36–0.96, respectively). Overall, this systematic review illustrates that non-invasive methods to generate an input function are still in their infancy. Yet, IDIF and SIME performed well, not only with arterial blood calibration, but also with venous or no blood calibration, especially for some tracers without plasma metabolites, which would potentially make these methods better suited for clinical application. However, these methods should still be properly validated for each individual tracer and application before implementation.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s00259-022-06057-4.

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          Graphical analysis of reversible radioligand binding from time-activity measurements applied to [N-11C-methyl]-(-)-cocaine PET studies in human subjects.

          A graphical method of analysis applicable to ligands that bind reversibly to receptors or enzymes requiring the simultaneous measurement of plasma and tissue radioactivities for multiple times after the injection of a radiolabeled tracer is presented. It is shown that there is a time t after which a plot of integral of t0ROI(t')dt'/ROI(t) versus integral of t0Cp(t')dt'/ROI(t) (where ROI and Cp are functions of time describing the variation of tissue radioactivity and plasma radioactivity, respectively) is linear with a slope that corresponds to the steady-state space of the ligand plus the plasma volume,.Vp. For a two-compartment model, the slope is given by lambda + Vp, where lambda is the partition coefficient and the intercept is -1/[kappa 2(1 + Vp/lambda)]. For a three-compartment model, the slope is lambda(1 + Bmax/Kd) + Vp and the intercept is -[1 + Bmax/Kd)/k2 + [koff(1 + Kd/Bmax)]-1) [1 + Vp/lambda(1 + Bmax/Kd)]-1 (where Bmax represents the concentration of ligand binding sites and Kd the equilibrium dissociation constant of the ligand-binding site complex, koff (k4) the ligand-binding site dissociation constant, and k2 is the transfer constant from tissue to plasma). This graphical method provides the ratio Bmax/Kd from the slope for comparison with in vitro measures of the same parameter. It also provides an easy, rapid method for comparison of the reproducibility of repeated measures in a single subject, for longitudinal or drug intervention protocols, or for comparing experimental results between subjects. Although the linearity of this plot holds when ROI/Cp is constant, it can be shown that, for many systems, linearity is effectively reached some time before this. This analysis has been applied to data from [N-methyl-11C]-(-)-cocaine ([11C]cocaine) studies in normal human volunteers and the results are compared to the standard nonlinear least-squares analysis. The calculated value of Bmax/Kd for the high-affinity binding site for cocaine is 0.62 +/- 0.20, in agreement with literature values.
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            First Human Imaging Studies with the EXPLORER Total-Body PET Scanner*

            Within the EXPLORER Consortium, the construction of the world's first total-body PET/CT scanner has recently been completed. The 194-cm axial field of view of the EXPLORER PET/CT scanner is sufficient to cover, for the first time, the entire human adult body in a single acquisition in more than 99% of the population and allows total-body pharmacokinetic studies with frame durations as short as 1 s. The large increase in sensitivity arising from total-body coverage as well as increased solid angle for detection at any point within the body allows whole-body 18F-FDG PET studies to be acquired with unprecedented count density, improving the signal-to-noise ratio of the resulting images. Alternatively, the sensitivity gain can be used to acquire diagnostic PET images with very small amounts of activity in the field of view (25 MBq, 0.7 mCi or less), with very short acquisition times (∼1 min or less) or at later time points after the tracer's administration. We report here on the first human imaging studies on the EXPLORER scanner using a range of different protocols that provide initial evidence in support of these claims. These case studies provide the foundation for future carefully controlled trials to quantitatively evaluate the improvements possible through total-body PET imaging.
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              Partial-volume effect in PET tumor imaging.

              PET has the invaluable advantage of being intrinsically quantitative, enabling accurate measurements of tracer concentrations in vivo. In PET tumor imaging, indices characterizing tumor uptake, such as standardized uptake values, are becoming increasingly important, especially in the context of monitoring the response to therapy. However, when tracer uptake in small tumors is measured, large biases can be introduced by the partial-volume effect (PVE). The purposes of this article are to explain what PVE is and to describe its consequences in PET tumor imaging. The parameters on which PVE depends are reviewed. Actions that can be taken to reduce the errors attributable to PVE are described. Various PVE correction schemes are presented, and their applicability to PET tumor imaging is discussed.
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                Author and article information

                Contributors
                e.f.j.de.vries@umcg.nl
                Journal
                Eur J Nucl Med Mol Imaging
                Eur J Nucl Med Mol Imaging
                European Journal of Nuclear Medicine and Molecular Imaging
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                1619-7070
                1619-7089
                18 January 2023
                18 January 2023
                2023
                : 50
                : 6
                : 1636-1650
                Affiliations
                [1 ]GRID grid.4494.d, ISNI 0000 0000 9558 4598, Department of Nuclear Medicine and Molecular Imaging, , University of Groningen, University Medical Center Groningen, ; Hanzeplein 1, 9713GZ Groningen, The Netherlands
                [2 ]GRID grid.4494.d, ISNI 0000 0000 9558 4598, Department of Radiology, , University of Groningen, University Medical Center Groningen, ; Hanzeplein 1, Groningen, The Netherlands
                [3 ]GRID grid.4494.d, ISNI 0000 0000 9558 4598, Department of Neurology, , University of Groningen, University Medical Center Groningen, ; Hanzeplein 1, Groningen, The Netherlands
                Author information
                http://orcid.org/0000-0002-6915-1590
                Article
                6057
                10.1007/s00259-022-06057-4
                10119247
                36651951
                54cbecf9-316a-471e-b65d-d28c0fe37252
                © The Author(s) 2023

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 11 August 2022
                : 21 November 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100003000, Stichting MS Research;
                Award ID: PTO-95105010
                Award Recipient :
                Funded by: the Nederlandse organisatie voor gezondheidsonderzoek en zorginnovatie (ZonMW)
                Award ID: PTO-95105010
                Award Recipient :
                Categories
                Review Article
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2023

                Radiology & Imaging
                positron emission tomography,arterial input function,image derived input function,population-based input function,simultaneous estimation of the input function

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