Ingo Einspieler1,2, Victor Mergen3, Heiko Wendorff4, Bernhard Haller5, Matthias Eiber3, Markus Schwaiger3,6, Stephan G Nekolla3,6, Mona Mustafa3. 1. Department of Nuclear Medicine, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany. ingo.einspieler@ukr.de. 2. Department of Radiology, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany. ingo.einspieler@ukr.de. 3. Department of Nuclear Medicine, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany. 4. Vascular Surgery, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany. 5. Medical Statistics and Epidemiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany. 6. Deutsches Zentrum für Herz-Kreislauf-Forschung e.V. Partner site Munich Heart Alliance, Munich, Germany.
Abstract
PURPOSE: The aim of this study was the evaluation of quantitative and qualitative parameters for the diagnosis of aortic graft infection (AGI) using [18F]-FDG PET/CT. METHODS: PET/CT was performed in 50 patients with clinically suspected AGI. 12 oncological patients with aortic repair but without suspicion of AGI were included in the analysis to serve as control cohort. The [18F]-FDG uptake pattern around the graft was assessed using (a) a five-point visual grading scale (VGS), (b) SUVmax and (c) different graft-to-background ratios (GBRs). The diagnostic performance of VGS, SUVmax and GBRs was assessed and compared by ROC analysis. RESULTS: 28 infected and 34 uninfected grafts were identified by standard of reference. SUVmax and VGS were the most powerful predictors for the diagnosis of AGI according to the area under the curve (AUC 0.988 and 0.983, respectively) without a significant difference compared to GBRs. SUVmax and VGS showed congruent and accurate findings in 54 patients (i.e. either both positive or negative), yielding sensitivity and specificity (100%) in this subgroup of patients. CONCLUSION: Quantitative analysis by SUVmax and qualitative analysis by VGS are highly effective in the diagnosis of AGI and should be tested as an outcome measure in prospective trials.
PURPOSE: The aim of this study was the evaluation of quantitative and qualitative parameters for the diagnosis of aortic graft infection (AGI) using [18F]-FDG PET/CT. METHODS: PET/CT was performed in 50 patients with clinically suspected AGI. 12 oncological patients with aortic repair but without suspicion of AGI were included in the analysis to serve as control cohort. The [18F]-FDG uptake pattern around the graft was assessed using (a) a five-point visual grading scale (VGS), (b) SUVmax and (c) different graft-to-background ratios (GBRs). The diagnostic performance of VGS, SUVmax and GBRs was assessed and compared by ROC analysis. RESULTS: 28 infected and 34 uninfected grafts were identified by standard of reference. SUVmax and VGS were the most powerful predictors for the diagnosis of AGI according to the area under the curve (AUC 0.988 and 0.983, respectively) without a significant difference compared to GBRs. SUVmax and VGS showed congruent and accurate findings in 54 patients (i.e. either both positive or negative), yielding sensitivity and specificity (100%) in this subgroup of patients. CONCLUSION: Quantitative analysis by SUVmax and qualitative analysis by VGS are highly effective in the diagnosis of AGI and should be tested as an outcome measure in prospective trials.
Authors: Walter R Wilson; Thomas C Bower; Mark A Creager; Sepideh Amin-Hanjani; Patrick T O'Gara; Peter B Lockhart; Rabih O Darouiche; Basel Ramlawi; Colin P Derdeyn; Ann F Bolger; Matthew E Levison; Kathryn A Taubert; Robert S Baltimore; Larry M Baddour Journal: Circulation Date: 2016-10-13 Impact factor: 29.690
Authors: Chiara Lauri; Alberto Signore; Andor W J M Glaudemans; Giorgio Treglia; Olivier Gheysens; Riemer H J A Slart; Roberto Iezzi; Niek H J Prakken; Eike Sebastian Debus; Susanne Honig; Anne Lejay; Nabil Chakfé Journal: Eur J Nucl Med Mol Imaging Date: 2022-04-04 Impact factor: 10.057