Simultaneous carotid PET/MR: feasibility and improvement of magnetic resonance-based attenuation correction

Abstract

Errors in quantification of carotid positron emission tomography (PET) in simultaneous PET/magnetic resonance (PET/MR) imaging when not incorporating bone in MR-based attenuation correction (MRAC) maps, and possible solutions, remain to be fully explored. In this study, we demonstrated techniques to improve carotid vascular PET/MR quantification by adding a bone tissue compartment to MRAC maps and deriving continuous Dixon-based MRAC (MRACCD) maps. We demonstrated the feasibility of applying ultrashort echo time-based bone segmentation and generation of continuous Dixon MRAC to improve PET quantification on five subjects. We examined four different MRAC maps: system standard PET/MR MRAC map (air, lung, fat, soft tissue) (MRACPET/MR), standard PET/MR MRAC map with bone (air, lung, fat, soft tissue, bone) (MRACPET/MRUTE), MRACCD map (no bone) and continuous Dixon-based MRAC map with bone (MRACCDUTE). The same PET emission data was then reconstructed with each respective MRAC map and a CTAC map (PETPET/MR, PETPET/MRUTE, PETCD, PECDUTE) to assess effects of the different attenuation maps on PET quantification in the carotid arteries and neighboring tissues. Quantitative comparison of MRAC attenuation values for each method compared to CTAC showed small differences in the carotid arteries with UTE-based segmentation of bone included and/or continuous Dixon MRAC; however, there was very good correlation for all methods in the voxel-by-voxel comparison. ROI-based analysis showed a similar trend in the carotid arteries with the lowest correlation to PETCTAC being PETPETMR and the highest correlation to PETCTAC being PETCDUTE. We have demonstrated the feasibility of applying UTE-based segmentation and continuous Dixon MRAC maps to improve carotid PET/MR vascular quantification.

Keywords: Attenuation correction; Carotid arteries; Dixon; PET/MR; Ultrashort echo time.

Figure 1

Representative example of the six regions-of interest (ROIs) that were defined: left (red) and right (orange) carotid arteries, left (pink) and right (yellow) jugular veins, spine (blue) and soft tissue (muscle) (brown). ROIs were traced manually in the axial view of the time-of-flight MR images for each ROI for 20 axial slices starting at the carotid bifurcation and descending in the caudal direction.

Figure 2

Sagittal and axial comparisons of CT- and MR-based attenuation maps (A) and their respective PET reconstructions (B).

Figure 3. Percent difference error map showing regional differences in SUV between PET/MR emission data reconstructed with the respective MRAC and CTAC maps

Figure 4

A Voxel-by-voxel Pearson's correlation plots for all voxels in all patients. B Voxel-by-voxel Bland-Altman plots for all voxels in all patients. The mean (yellow dashed line) and the upper and lower limits (red dotted lines) are calculated according to a Bland-Altman analysis [28]. Upper limit is mean + 1.96*standard deviation and lower limit is mean – 1.96*standard deviation.

Figure 4

A Voxel-by-voxel Pearson's correlation plots for all voxels in all patients. B Voxel-by-voxel Bland-Altman plots for all voxels in all patients. The mean (yellow dashed line) and the upper and lower limits (red dotted lines) are calculated according to a Bland-Altman analysis [28]. Upper limit is mean + 1.96*standard deviation and lower limit is mean – 1.96*standard deviation.

Figure 5

Pearson's correlation plots for all ROIs in all patients.

Figure 6

Bland-Altman plots for all ROIs in all patients. The mean (yellow dashed line) and the upper and lower limits (red dotted lines) are calculated according to a Bland-Altman analysis [28]. Upper limit is mean + 1.96*standard deviation and lower limit is mean – 1.96*standard deviation.