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18F-FDG PET/MR-imaging in a Göttingen Minipig model of atherosclerosis: Correlations with histology and quantitative
Trine P Ludvigsen1, Sune F Pedersen2, Andreas Vegge1
1Global Drug Discovery, Novo Nordisk Park, Novo Nordisk A/S, DK-2760, Måløv, Denmark.
Background And Aims:
The advantage of combining molecular and morphological imaging, e.g. positron emission tomography and magnetic resonance imaging (PET/MRI), is reflected in the increased use of these modalities as surrogate end-points in clinical trials. This study aimed at evaluating plaque inflammation using 18F-fluorodeoxyglucose (18F-FDG)-PET/MRI, and gene expression in a minipig model of atherosclerosis.
Methods:
Göttingen Minipigs were fed for 60 weeks with fat/fructose/cholesterol-rich diet (FFC), chow (Control) or FFC-diet changed to chow midway (diet normalization group; DNO). In all groups, 18F-FDG-PET/MRI of the abdominal aorta was assessed midway and at study-end. The aorta was analyzed using histology and gene expression.
Results:
At study-end, FFC had significantly higher FDG-uptake compared to Control (target-to-background maximal uptake, TBRMax (95% confidence interval) CITBRMax: 0.092; 7.32) and DNO showed significantly decreased uptake compared to FFC (CITBRMax: -5.94;-0.07). No difference was observed between DNO and Control (CITBRMax: -2.71; 4.11). FFC displayed increased atherosclerosis and gene expression of inflammatory markers, including vascular cell adhesion molecule 1 (VCAM-1), cluster of differentiation 68 (CD68), matrix metalloproteinase 9 (MMP9), cathepsin K (CTSK) and secreted phosphoprotein 1 (SPP1) compared to Control and DNO (all, p < 0.05). FDG-uptake correlated with gene expression of inflammatory markers, including CD68, ρs = 0.58; MMP9, ρs = 0.46; SPP1, ρs = 0.44 and CTSK, ρs = 0.49; (p ≤ 0.01 for all).
Conclusions:
In a model of atherosclerosis, 18F-FDG-PET/MRI technology allows for detection of inflammation in atherosclerotic plaques, consistent with increased inflammatory gene expression. Our findings corroborate clinical data and are important in pre-clinical drug development targeting plaque inflammation.
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