Autor: |
Imfeld, Stephan, Rottenburger, Christof, Schegk, Elke, Aschwanden, Markus, Juengling, Freimut, Staub, Daniel, Recher, Mike, Kyburz, Diego, Berger, Christoph T, Daikeler, Thomas |
Předmět: |
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Zdroj: |
European Heart Journal - Cardiovascular Imaging; Aug2018, Vol. 19 Issue 8, p933-940, 8p |
Abstrakt: |
Aims The usefulness of [18F] fluorodeoxyglucose-positron emission tomography/computed tomography ([18F]FDG-PET/CT) for diagnosing giant cell arteritis (GCA) has been previously reported. Yet, the interpretation of PET scans is not clear-cut. The present study aimed at determining the best method to analyse PET/CT in a large, real-life cohort of patients presenting with suspicion of GCA. Methods and results One hundred and three patients with clinical suspicion of GCA undergoing PET/CT between 2006 and 2012 were included. Clinical data were retrieved from patients’ charts. PET/CT was categorized by visual scoring of the uptake and by the artery/liver standardized uptake values (SUV) ratios. Diagnosis of GCA was confirmed in 68 patients and excluded in 35 patients, which served as the controls. GCA patients were older (median age 75 vs. 68 years), and presented more often with ischaemic symptoms. The best discrimination between GCA patients and controls was achieved for PET/CT findings within the supra-aortic arteries (sensitivity 0.71, specificity 0.91 for a SUV/LE cut-off value of 1.0). Specificity of PET/CT for the aorta and the iliofemoral arteries was lower (<0.34). Visual scoring correlated poorly to SUV measurements (Kendall Tau-b 0.13–0.55) and had a lower diagnostic accuracy (sensitivity 0.77, specificity 0.75). Prednisone treatment for ≥10 days significantly reduced PET/CT sensitivity (P = 0.009). Conclusion SUV based analysis of PET/CT enhances diagnostic accuracy with best discrimination in the supra-aortic region, particularly in steroid naïve patients. For discrimination based on the aorta and the iliofemoral region, higher cut-off values have to be applied, resulting in lower sensitivities for diagnosing GCA. [ABSTRACT FROM AUTHOR] |
Databáze: |
Complementary Index |
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