Abstract

BackgroundGraphical methods of radiotracer kinetic modeling in PET are ideal for parametric imaging and data quality assurance but can suffer from noise bias. This study compared the Logan and Multilinear Analysis-1 (MA1) graphical models to the standard one-tissue-compartment (1TC) model, including correction for partial-volume effects, in dynamic PET-CT studies of myocardial sympathetic innervation in the left ventricle (LV) using [11C]HED.MethodsTest and retest [11C]HED PET imaging (47 ± 22 days apart) was performed in 18 subjects with heart failure symptoms. Myocardial tissue volume of distribution (VT) was estimated using Logan and MA1 graphical methods and compared to the 1TC standard model values using intraclass correlation (ICC) and Bland-Altman analysis of the non-parametric reproducibility coefficient (NPC).ResultsA modeling start-time of t* = 5 min gave the best fit for both Logan and MA1 (R2 = 0.95) methods. Logan slightly underestimated VT relative to 1TC (p = 0.002), whereas MA1 did not (p = 0.96). Both the MA1 and Logan models exhibited good-to-excellent agreement with the 1TC (MA1-1TC ICC = 0.96; Logan-1TC ICC = 0.93) with no significant differences in NPC between the two comparisons (p = 0.92). All methods exhibited good-to-excellent test-retest repeatability with no significant differences in NPC (p = 0.57).ConclusionsLogan and MA1 models exhibited similar agreement and variability compared to the 1TC for modeling of [11C]HED kinetics. Using t* = 5 min and partial-volume correction produced accurate estimates of VT as an index of myocardial sympathetic innervation.

Highlights

  • Graphical methods of radiotracer kinetic modeling in positron emission tomography (PET) are ideal for parametric imaging and data quality assurance but can suffer from noise bias

  • Two graphical methods reported in the literature for kinetic modeling of reversible-binding tracers are the Logan [4] and Multilinear Analysis-1 (MA1) models [5], which are both computationally simpler than non-graphical methods [6], while being able to provide visual representations of kinetic parameters

  • The Logan method has been established as the standard graphical model to estimate volume of distribution (VT) in a wide range of PET applications in the brain and heart, while MA1 was proposed as an alternative numerical formulation to estimate VT with lower noise bias compared to Logan estimates [5]

Read more

Summary

Introduction

Graphical methods of radiotracer kinetic modeling in PET are ideal for parametric imaging and data quality assurance but can suffer from noise bias. This study compared the Logan and Multilinear Analysis-1 (MA1) graphical models to the standard one-tissue-compartment (1TC) model, including correction for partial-volume effects, in dynamic PET-CT studies of myocardial sympathetic innervation in the left ventricle (LV) using [11C]HED. Developed as a positron emission tomography (PET) imaging agent to target the cardiac sympathetic nervous system, carbon-11-labeled meta-hydroxyephedrine ([11C]HED) is a norepinephrine analog that is taken up by nerve terminal varicosities in the myocardium, and used to assess sympathetic nerve function [1]. The goal of this study was to determine a method of partial-volume correction applicable to graphical kinetic modeling and to compare the Logan and MA1 models to the standard 1TC kinetic model for accurate quantification of myocardial sympathetic innervation using dynamic [11C]HED PET-CT studies

Objectives
Methods
Results
Conclusion

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.