B-0120 Determining the vulnerable plaque: correlation between 18F-FDG PET and dynamic contrast-enhanced MRI in atherosclerotic plaques of symptomatic patients

M.T.B. Truijman, R.M. Kwee, R.H.M. van Hoof, R.J. van Oostenbrugge, W.H. Mess, J.E. Wildberger, W.H. Backes, J.A. Bucerius, M.E. Kooi | Thursday, March 7, 10:30 – 12:00 / Room N/O

Purpose: Identifying vulnerable atherosclerotic plaques in symptomatic patients with moderate (30-69%) carotid artery stenosis can contribute to clinical decision making. Hallmarks of plaque vulnerability are inflammation and increased neovascularisation. Inflammation can be assessed with ¹⁸F-FDG PET, while neovascularisation can be quantified with dynamic contrast-enhanced (DCE) MRI. We aimed to investigate the correlation between inflammation as assessed by¹⁸F-FDG PET and neovascularisation as assessed by DCE-MRI.
Methods and Materials: Fifty-eight patients with transient ischaemic attack (TIA) or minor stroke in the carotid territory and ipsilateral carotid plaque causing a moderate stenosis were included. All patients underwent 1.5 T multi-sequence MR imaging. Quantification of neovascularisation was done using a custom-made Matlab program which calculates K^trans. A 3D PET-CT scan was performed on all patients one hour after injection of 2.75 MBq/kg body weight ¹⁸F-FDG. Dedicated fusion software was used to calculate mean blood-normalised ¹⁸F-FDG standard uptake values (SUV) of the plaque.
Results: Of the 58 patients, 9 were excluded due to poor image quality of the DCE-MRI. In total, we analysed 49 patients. The mean K^trans and mean normalised SUV were 0.110 (±0.027) and 1.446 (±0.255), respectively. We found a weak but significant positive correlation between the mean normalised SUV and the meanK^trans (Spearman’s r=0.302, p=0.035).
Conclusion: There is a weak but significant positive correlation between K^trans, which is a marker for neovascularisation and SUV, which is a marker for inflammation. Future studies are warranted to investigate whether DCE-MRI and/or 18F-FDG PET can be used to predict cerebrovascular events.

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