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Variability in quantitative analysis of atherosclerotic plaque inflammation using 18F-FDG PET/CT.

Variability in quantitative analysis of atherosclerotic plaque inflammation using 18F-FDG PET/CT.
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Lensen KDF, van Sijl AM, Voskuyl AE, van der Laken CJ, Heymans MW, Comans EFI, Nurmohamed MT, Smulders YM, Boellaard R,


Lensen KDF, van Sijl AM, Voskuyl AE, van der Laken CJ, Heymans MW, Comans EFI, Nurmohamed MT, Smulders YM, Boellaard R, (click to view)

Lensen KDF, van Sijl AM, Voskuyl AE, van der Laken CJ, Heymans MW, Comans EFI, Nurmohamed MT, Smulders YM, Boellaard R,

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PloS one 2017 08 1112(8) e0181847 doi 10.1371/journal.pone.0181847
Abstract
BACKGROUND
18F-FDG-PET(/CT) is increasingly used in studies aiming at quantifying atherosclerotic plaque inflammation. Considerable methodological variability exists. The effect of data acquisition and image analysis parameters on quantitative uptake measures, such as standardized uptake value (SUV) and target-to-background ratio (TBR) has not been investigated extensively.

OBJECTIVE
The goal of this study was to explore the effect of several data acquisition and image analysis parameters on quantification of vascular wall 18F-FDG uptake measures, in order to increase awareness of potential variability.

METHODS
Three whole-body emission scans and a low-dose CT scan were acquired 38, 60 and 90 minutes after injection of 18F-FDG in six rheumatoid arthritis patients with high cardiovascular risk profiles.Data acquisition (1 and 2) and image analysis (3, 4 and 5) parameters comprised:1. 18F-FDG uptake time, 2. SUV normalisation, 3. drawing regions/volumes of interest (ROI’s/VOI’s) according to: a. hot-spot (HS), b. whole-segment (WS) and c. most-diseased segment (MDS), 4. Background activity, 5. Image matrix/voxel size.Intraclass correlation coefficients (ICC’s) and Bland Altman plots were used to assess agreement between these techniques and between observers. A linear mixed model was used to determine the association between uptake time and continuous outcome variables.

RESULTS
1. Significantly higher TBRmax values were found at 90 minutes (1,57 95%CI 1,35-1,80) compared to 38 minutes (1,30 95%CI 1,21-1,39) (P = 0,024) 2. Normalising SUV for BW, LBM and BSA significantly influences average SUVmax (2,25 (±0,60) vs 1,67 (±0,37) vs 0,058 (±0,013)). 3. Intraclass correlation coefficients were high in all vascular segments when SUVmax HS was compared to SUVmax WS. SUVmax HS was consistently higher than SUVmax MDS in all vascular segments. 4. Blood pool activity significantly decreases in all (venous and arterial) segments over time, but does not differ between segments. 5. Image matrix/voxel size does not influence SUVmax.

CONCLUSION
Quantitative measures of vascular wall 18F-FDG uptake are affected mainly by changes in data acquisition parameters. Standardization of methodology needs to be considered when studying atherosclerosis and/or vasculitis.

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