Image-Derived Input Function for Human Brain Using High Resolution PET Imaging with [11C](R)-rolipram and [11C]PBR28

Paolo Zanotti-Fregonara,Ronald Boellaard,Elise Luong,Sami S Zoghbi,Robert B Innis,Jeih-San Liow,Victor W Pike,Elodie Dusch,Claude Comtat,Masahiro Fujita,Juri Gelovani

doi:10.1371/journal.pone.0017056

Paolo Zanotti-Fregonara, Ronald Boellaard + Show 9 more

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https://doi.org/10.1371/journal.pone.0017056

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Abstract

BackgroundThe aim of this study was to test seven previously published image-input methods in state-of-the-art high resolution PET brain images. Images were obtained with a High Resolution Research Tomograph plus a resolution-recovery reconstruction algorithm using two different radioligands with different radiometabolite fractions. Three of the methods required arterial blood samples to scale the image-input, and four were blood-free methods.MethodsAll seven methods were tested on twelve scans with [11C](R)-rolipram, which has a low radiometabolite fraction, and on nineteen scans with [11C]PBR28 (high radiometabolite fraction). Logan V T values for both blood and image inputs were calculated using the metabolite-corrected input functions. The agreement of image-derived Logan V T values with the reference blood-derived Logan V T values was quantified using a scoring system. Using the image input methods that gave the most accurate results with Logan analysis, we also performed kinetic modelling with a two-tissue compartment model.ResultsFor both radioligands the highest scores were obtained with two blood-based methods, while the blood-free methods generally performed poorly. All methods gave higher scores with [11C](R)-rolipram, which has a lower metabolite fraction. Compartment modeling gave less reliable results, especially for the estimation of individual rate constants.ConclusionOur study shows that: 1) Image input methods that are validated for a specific tracer and a specific machine may not perform equally well in a different setting; 2) despite the use of high resolution PET images, blood samples are still necessary to obtain a reliable image input function; 3) the accuracy of image input may also vary between radioligands depending on the magnitude of the radiometabolite fraction: the higher the metabolite fraction of a given tracer (e.g., [11C]PBR28), the more difficult it is to obtain a reliable image-derived input function; and 4) in association with image inputs, graphical analyses should be preferred over compartmental modelling.

Highlights

Using radioligands that bind to specific receptors and enzymes, positron emission tomography (PET) can quantify the in vivo density of such targets in brain
High resolution images can be obtained using a tomograph with a higher intrinsic resolution, like the HRRT (High Resolution Research Tomograph; resolution = 2.5 mm), or using reconstruction-based resolution recovery algorithms, which are implemented on many standard resolution PET machines
Blood analyses The shape of the whole-blood curves was very similar for the two tracers (Figure 2AB), with a concentration peak at,90 seconds and a rapid decline thereafter; the relative concentration of parent and metabolites differed (Figure 2C). [11C](R)-rolipram remained the predominant portion of blood radioactivity throughout the scan

Summary

Introduction

Using radioligands that bind to specific receptors and enzymes, positron emission tomography (PET) can quantify the in vivo density of such targets in brain. As an alternative to arterial sampling, many methods have been proposed to calculate the input function from serial images of the internal carotid artery – i.e., an image-derived input function [2,3,4,5,6,7,8] Such methods have been validated for PET cameras with a standard resolution (typically. mm). Some of these methods require at least one blood sample in order to scale the image-input, while others are completely blood-free, and more attractive. High resolution images can be obtained using a tomograph with a higher intrinsic resolution, like the HRRT (High Resolution Research Tomograph; resolution = 2.5 mm), or using reconstruction-based resolution recovery algorithms, which are implemented on many standard resolution PET machines. Three of the methods required arterial blood samples to scale the image-input, and four were blood-free methods

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