Abstract

Cellular inflammation is an integral part of the healing process following acute myocardial infarction and has been under intense investigation for both therapeutic and prognostic approaches. Monocytes and macrophages are metabolically highly active and show increased uptake rates of glucose and its analog, 18F-FDG. Yet, the specific allocation of the radioactivity to the inflammatory cells via positron emission tomography (PET) imaging requires the suppression of glucose metabolism in viable myocardium. In mice, the most important model organism in basic research, this can be achieved by the application of ketamine/xylazine (KX) for anesthesia instead of isoflurane. Yet, while the consensus exists that glucose metabolism is effectively suppressed, a strategy for reproducible image analysis is grossly lacking and causes uncertainty concerning data interpretation. We introduce a simple strategy for systematic image analysis, which is a prerequisite to evaluate therapies targeting myocardial inflammation. Mice underwent permanent occlusion of the left anterior descending artery (LAD), inducing an acute myocardial infarction (MI). Five days after MI induction, 10MBq 18F-FDG was injected intravenously and a static PET/CT scan under ketamine/xylazine anesthesia was performed. For image reconstruction, we used an algorithm based on three-dimensional ordered subsets expectation maximization (3D-OSEM) followed by three-dimensional ordinary Poisson maximum a priori (MAP) reconstruction. Using this approach, high focal tracer uptake was typically located in the border zone of the infarct by visual inspection. To precisely demarcate the border zone for reproducible volume of interest (VOI) positioning, our protocol relies on positioning VOIs around the whole left ventricle, the inferobasal wall and the anterolateral wall guided by anatomical landmarks. This strategy enables comparable data in mouse studies, which is an important prerequisite for using a PET-based assessment of myocardial inflammation as a prognostic tool in therapeutic applications.

Highlights

  • According to the World Health Organization, coronary artery disease (CAD) is the world’s biggest killer, accounting for almost 10 million deaths per year worldwide

  • Cellular inflammation is an integral part of the healing process after myocardial infarction and an attractive target for both therapeutic and diagnostic approaches

  • A protocol for the imaging of cellular inflammation in mice based on 18F-FDG positron emission tomography (PET) has been evaluated by us and others [5,9,10,11]

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Summary

Introduction

According to the World Health Organization, coronary artery disease (CAD) is the world’s biggest killer, accounting for almost 10 million deaths per year worldwide. The use of this approach for the assessment and quantification of cellular inflammation in the context of therapy monitoring is currently hampered by the lack of strategies for image analysis In this protocol we describe an approach for measuring of the focal tracer uptake based on positioning volumes of interest (VOI) around the whole left ventricle, the inferobasal and the anterolateral wall. This strategy will help researchers to generate comparable data when using 18F-FDG PET for imaging cellular inflammation and its modulation post-acute myocardial infarction. Sci. 2020, 21, x FOR PEER REVIEW au1r(ien8ssgFeoeid-sfoFlVVTtFaaaFa0Vg“TTunhDnnsii.nrhriOOhah0gnrsgeeoeieemel5maGIumeItsuuusai“ntrt“rewtcrpeazshohehheeueaieosle)flenntaesdeen)m.pe4tdasef4ttaiaTe”aa.iitr±cz.fppzrlnaserhntoweteVeaRRsccoekSheddlpdrtsrlsiileODee”yeentrtoi“iwpph1btfhdeI.wefeVwitrraaesieopnn×ewettveitOrni-dnhitotsiscsanvenizh1aieeeItorbnitmaeabsg0ndensterfldtnliioe6tedlutrsispaliauiaanfllifeosBnwemolcotlatunfrufgseiliqstwsitlvaaevaecratuihw/ve”enhtnatlmelma,reissenyaeoeeanVkaeeeniaeisrsnsLndnexnxnaOeyntaete(etarfnafhdAcnaes(cdeIaimVmKocsmae(r±drr)lAttonolctiepOeXphhcainSitbtffln”)kluzenlaDe)IeateeetteeilidiaVnssrsnihapc/n.stdznxaettsOpsaekofosoeseyldusa-meaafdwsdfIlviwptertalnivhkaratmtcetizwuiahfhaeeemnliettceiulsonfoeheendtilergtliatiesnddeineonah/laatmvsiico.xibgnesnnncntnekwbVyaa/disooaattoxnlgeasnalhoynflelytatarelycyllhierate.(ulul/zamFasaseaFexmflseriiiDwrizysidtnscsensgaaigiualGecnainesllansasoudltolsle,etrtczsaelem.uerbrer/uit(lcaaxvnaenapmBhTypwltttyniltaeteeeoe)a5rholatdFtaeggdbac)5e-(kessDs.syytyzldBtreedeecftTieGw)nnuosneauauuomfhtstoleylls5nns.fehudeee.(esiydddtccgnopedVdhoaaVbteergltrasaecfarerreaa:stOfaydlleltekvLroyyuhrmsnilrVeIidoiireeeawsnnMaaemisfob(sudgrgaftwapfltartIynmeeuesourtvttieofhrhhendw±mreirsc(eeendpeerpMnye)Syne.uliLttrppteDpndoetI*ecrVrrf:scgtals.itooraiiac-aerpVno(o(ttrtlcrrntgpeooadnre

Discussion
Limitations
Animal Model
PET Imaging
PET Image Analysis
Findings
Statistics
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