Partial volume effect estimation and correction in the aortic vascular wall in PET imaging.

We evaluated the impact of partial volume effect (PVE) in the assessment of arterial diseases with (18)FDG PET. An anthropomorphic digital phantom enabling the modeling of aorta related diseases like atherosclerosis and arteritis was used. Based on this phantom, we performed GATE Monte Carlo simulations to produce realistic PET images with a known organ segmentation and ground truth activity values. Images corresponding to 15 different activity-concentration ratios between the aortic wall and the blood and to 7 different wall thicknesses were generated. Using the PET images, we compared the theoretical wall-to-blood activity-concentration ratios (WBRs) with the measured WBRs obtained with five measurement methods: (1) measurement made by a physician (Expert), (2) automated measurement supposed to mimic the physician measurements (Max), (3) simple correction based on a recovery coefficient (Max-RC), (4) measurement based on an ideal VOI segmentation (Mean-VOI) and (5) measurement corrected for PVE using an ideal geometric transfer matrix (GTM) method. We found that Mean-VOI WBRs values were strongly affected by PVE. WBRs obtained by the physician measurement, by the Max method and by the Max-RC method were more accurate than WBRs obtained with the Mean-VOI approach. However Expert, Max and Max-RC WBRs strongly depended on the wall thickness. Only the GTM corrected WBRs did not depend on the wall thickness. Using the GTM method, we obtained more reproducible ratio values that could be compared across wall thickness. Yet, the feasibility of the implementation of a GTM-like method on real data remains to be studied.