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[18F]FDG PET/CT in Large Vessel Vasculitis: The Impact of Expertise and Confounders on Image Analysis

Articolo
Data di Pubblicazione:
2022
Citazione:
[18F]FDG PET/CT in Large Vessel Vasculitis: The Impact of Expertise and Confounders on Image Analysis / Antunovic, Lidija; Artesani, Alessia; Coniglio, Michael; Oyen, Wim J. G.; Ciccarelli, Michele; Selmi, Carlo; Chiti, Arturo; Sollini, Martina. - In: DIAGNOSTICS. - ISSN 2075-4418. - 12:11(2022). [10.3390/diagnostics12112717]
Abstract:
Background: Diagnosis of vasculitis is challenging. To avoid invasive approaches, clinical guidelines recommend the use of diagnostic imaging. This study aimed at evaluating the diagnostic accuracy of [18F]-fluorodeoxyglucose ([18F]FDG) position emission tomography/computed tomography (PET/CT) in large vessel vasculitis (LVV) and how this is affected by inter-operator variability. Methods: A total of 279 patients who performed [18F]-FDG PET/CT for suspicion of LVV were retrospectively analyzed. We tested the qualitative and semi-quantitative analysis and parameters influencing image quality and interpretation. Exams were evaluated by two readers with different experience and their performance was compared. Results: LVV diagnosis was confirmed in 81 patients. [18F]-FDG PET/CT accuracy was 73% and 67% for the expert reader and less experienced reader, respectively. The expert reader overall performed better than the less experienced one, with higher accuracy in patients with normal BMI (77.3 vs. 63.8%), normal level of glycemia (73.3 vs. 65%), younger age (76.6 vs. 68.2%), and when no therapy was in course at time of imaging (76.7 vs. 66.7%). The diagnostic performance of both readers did not improve using semi-quantitative parameters. Conclusions: We confirmed the appropriateness of the recommended criteria for image acquisition and interpretation, underlining the importance of experience in image interpretation for the optimal diagnostic performance of [18F]FDG PET/CT in vasculitis.
Tipologia CRIS:
1.1 Articolo in rivista
Elenco autori:
Antunovic, Lidija; Artesani, Alessia; Coniglio, Michael; Oyen, Wim J. G.; Ciccarelli, Michele; Selmi, Carlo; Chiti, Arturo; Sollini, Martina
Autori di Ateneo:
CHITI ARTURO
SOLLINI MARTINA
Link alla scheda completa:
https://iris.unisr.it/handle/20.500.11768/140702
Link al Full Text:
https://iris.unisr.it//retrieve/handle/20.500.11768/140702/114188/diagnostics-12-02717.pdf
Pubblicato in:
DIAGNOSTICS
Journal
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URL

https://www.mdpi.com/2075-4418/12/11/2717
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