Abstract
BACKGROUND: We aimed to investigate the clinical value of a 3D-T1 w turbo-spin-echo (TSE) sequence and [(18)]fluorodeoxyglucose positron emission tomography/computed tomography ([F-18]EDG-PET/CT) for the diagnosis of active large vessel vasculitis (LVV) and single-organ vasculitis (SOV) of the aorta. METHODS: Twenty-four patients with suspected vasculitis who underwent MRI and PET/CT were retrospectively evaluated. MRI was analyzed for concentric contrast enhancement and wall thickening, and flow artifact intensity (4-point-scales). PET/CT analysis comprised qualitative, quantitative and semiquantitative methods. Imaging findings were correlated with final diagnosis derived from the clinical follow-up data. RESULTS: Fifteen of 24 patients had a clinically confirmed active vasculitis, two had inactive vasculitis and 7 no vasculitis. [F-18]FDG-PET/CT and 3D-T1w TSE-MRI revealed both a high diagnostic accuracy of 88% and 831/o, respectively. In patients in whom both PET/CT and MRI showed concordant findings (19 patients), the accuracy increased to 95% with a high positive predictive value (92%) and negative predictive value (100%);thus. a correct diagnosis was obtained in 18 of 19 patients. Among the five patients with discordant findings PET/CT correctly identified the two patients without active vasculitis while rated false positive on MR'. Of the three remaining patients with active vasculitis, two were correctly identified by MRI and one by PET/CT. CONCLUSIONS: 3D-T1w TsE-mm and [F-18]FDG-PET/CT are both useful in the diagnosis of active vasculitis with high diagnostic accuracies. The diagnostic accuracy was even optimized by combining the two analysis methods. Therefore, there might be substantial potential for the application of whole-body hybrid PET/MRI in the evaluation of vasculitis in future studies.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
ISSN: | 1824-4785 |
Sprache: | Englisch |
Dokumenten ID: | 87345 |
Datum der Veröffentlichung auf Open Access LMU: | 25. Jan. 2022, 09:23 |
Letzte Änderungen: | 12. Mai 2022, 11:38 |