PURPOSE: The aim of this retrospective study was to assess the performance of fluorine-18 fluorodeoxyglucose positron emission tomography-computed tomography ([(18)F]-FDG PET-CT) for diagnosing large-vessel vasculitis (LVV) for a subset of patients at increased risk of rheumatic/immune diseases, taking into account concurrent immunosuppressive therapy. MATERIALS AND METHODS: The study comprised 64 rheumatological referrals with suspected LVV; half of the patients were on immunosuppressive therapy at the time of examination. The final diagnosis of LVV was established in 31 patients. To evaluate vascular uptake, the nuclear medicine physician employed both a semiquantitative method based on standardised uptake value (SUV) determination and a qualitative method based on a visual score from 0 to 3 on the maximum intensity projection (MIP) reformats. Finally, a joint assessment was carried out between the nuclear medicine physician and the reporting radiologist, in which PET metabolic data were re-evaluated taking into account clinical data and baseline CT scans. McNemar's test was used to compare four types of analysis: semiquantitative (cutoff ≥ 2.4), qualitative with standard cutoff (grade ≥ 2), qualitative with reduced cutoff (grade ≥ 1) and joint. RESULTS: Semiquantitative analysis (sensitivity 74.19%, specificity 78.78%, accuracy 76.56%) and qualitative analysis with standard cutoff (sensitivity 64.51%, specificity 84.84%, accuracy 75.00%) showed no statistical difference for the diagnosis of LVV, whereas qualitative analysis with lower cutoff (sensitivity 93.54%, specificity 75.75%, accuracy 84.37%) proved to be better than the other two. Joint analysis (sensitivity 93.54%, specificity 93.93%, accuracy 93.75%) introduced some corrective elements not present in the qualitative analysis with cutoff ≥ 1 and therefore increased specificity significantly. CONCLUSIONS: Interpretation of PET-CT should be individualised for each patient by taking into account clinical-radiological and metabolic data. To this end, cooperation between the nuclear medicine specialist and the radiologist is essential.
PURPOSE: The aim of this retrospective study was to assess the performance of fluorine-18 fluorodeoxyglucose positron emission tomography-computed tomography ([(18)F]-FDG PET-CT) for diagnosing large-vessel vasculitis (LVV) for a subset of patients at increased risk of rheumatic/immune diseases, taking into account concurrent immunosuppressive therapy. MATERIALS AND METHODS: The study comprised 64 rheumatological referrals with suspected LVV; half of the patients were on immunosuppressive therapy at the time of examination. The final diagnosis of LVV was established in 31 patients. To evaluate vascular uptake, the nuclear medicine physician employed both a semiquantitative method based on standardised uptake value (SUV) determination and a qualitative method based on a visual score from 0 to 3 on the maximum intensity projection (MIP) reformats. Finally, a joint assessment was carried out between the nuclear medicine physician and the reporting radiologist, in which PET metabolic data were re-evaluated taking into account clinical data and baseline CT scans. McNemar's test was used to compare four types of analysis: semiquantitative (cutoff ≥ 2.4), qualitative with standard cutoff (grade ≥ 2), qualitative with reduced cutoff (grade ≥ 1) and joint. RESULTS: Semiquantitative analysis (sensitivity 74.19%, specificity 78.78%, accuracy 76.56%) and qualitative analysis with standard cutoff (sensitivity 64.51%, specificity 84.84%, accuracy 75.00%) showed no statistical difference for the diagnosis of LVV, whereas qualitative analysis with lower cutoff (sensitivity 93.54%, specificity 75.75%, accuracy 84.37%) proved to be better than the other two. Joint analysis (sensitivity 93.54%, specificity 93.93%, accuracy 93.75%) introduced some corrective elements not present in the qualitative analysis with cutoff ≥ 1 and therefore increased specificity significantly. CONCLUSIONS: Interpretation of PET-CT should be individualised for each patient by taking into account clinical-radiological and metabolic data. To this end, cooperation between the nuclear medicine specialist and the radiologist is essential.
Authors: J Meller; F Strutz; U Siefker; A Scheel; C O Sahlmann; K Lehmann; M Conrad; R Vosshenrich Journal: Eur J Nucl Med Mol Imaging Date: 2003-04-04 Impact factor: 9.236
Authors: Martin A Walter; Ralph A Melzer; Christian Schindler; Jan Müller-Brand; Alan Tyndall; Egbert U Nitzsche Journal: Eur J Nucl Med Mol Imaging Date: 2005-03-04 Impact factor: 9.236
Authors: H Kuehl; H Eggebrecht; T Boes; G Antoch; S Rosenbaum; S Ladd; A Bockisch; J Barkhausen; R Erbel Journal: Heart Date: 2007-12-10 Impact factor: 5.994
Authors: L Dellavedova; M Carletto; P Faggioli; A Sciascera; A Del Sole; A Mazzone; L S Maffioli Journal: Eur J Nucl Med Mol Imaging Date: 2015-08-08 Impact factor: 9.236