32 mm. The 18F-FDG uptake in the plaques was 1.15-2.66 for uncorrected SUVs, 1.16-3.19 for TBRs, and 0.20-1.79 for cSUVs. There were significant correlations between the different uptake values (r = 0.57-0.99, P < 0.001). Methods with and without blood background correction showed similar, moderate correlations to the amount of inflammation assessed at histology (r = 0.44-0.59, P < 0.02).
In large stenotic carotid plaques, 18F-FDG uptake reflects the inflammatory status as assessed at histology. Increasing number of PET slices or background correction did not change the correlation.
Inflammation is a key factor in the pathophysiology of atherosclerosis with regard to progression and destabilization of plaques.1 Patients with unstable carotid plaques have increased risk of plaque rupture and ischemic stroke,2,3 and there is increasing interest in imaging carotid plaque inflammation in order to detect these unstable plaques.
The aim of this study was to explore different methods for the quantification of 18F-FDG uptake in large carotid artery plaques, and to correlate the uptake values to the amount of inflammation on histology.
Forty-four patients referred to the Department of Neurology at our institution for the evaluation of carotid artery disease were included (Table 1). Inclusion criteria were ultrasound-confirmed atherosclerosis with internal carotid artery stenosis ≥ 70% according to consensus criteria of the Society of Radiologists in Ultrasound.24 Exclusion criteria were prior carotid endarterectomy/angioplasty with stenting, carotid occlusion, vasculitis, malignancy, prior radiation therapy to the neck, or immunotherapy. The Regional Committee for Medical and Health Research Ethics approved the study and all patients provided informed written consent.
Of the 44 included patients, 38 underwent carotid endarterectomy due to ipsilateral ischemic events or as prophylactic treatment before heart surgery. Eight of these plaques were lost to histological assessment due to logistical reasons.
Following overnight fasting blood glucose level was measured before the patient received i.v. injection of 5 MBq/kg (0.14 mCi/kg). After a mean circulation time of 100 minutes (range 68-156), a 18F-FDG PET/CT scan from the base of the skull to the aortic arch was performed with 15 minutes per bed position using a hybrid PET/CT scanner (Siemens Biograph 64, Siemens Medical Systems, Erlangen, Germany). The PET data were reconstructed to 2-mm slices with a pixel size of 2.67 mm using the ordered subset expectation-maximization 2D algorithm with four iterations (i), eight subsets (s)(4i/8s), and Gaussian post-reconstruction filter with full-width at half maximum of 3.5 mm. For attenuation correction, low-dose CT without the use of i.v. contrast was performed immediately before 18F-FDG PET. For patients without a recent CT angiography of the carotid arteries, this was performed after 18F-FDG PET.
Mean SUVmax4 = the mean SUVmax of the four slices with highest SUVmax.
For all blood pool ROIs, SUVmean was obtained. Blood background-corrected values for all the SUV measurements were calculated (target-to-background ratio (TBR); SUV divided by the blood pool activity (mean SUVmean in four venous regions) and corrected SUV (cSUV); blood pool-corrected SUV (subtraction of the blood pool activity (mean SUVmean) from SUV).
A second independent experienced nuclear medicine physician (MER) drew ROIs on the 20 initial patients to assess inter-observer variability of the different quantification methods.
The mean time between PET/CT and endarterectomy was 6 days (range; 0-116, median; 0). The histological analysis has been described previously.25 In brief, plaques were removed en bloc at carotid endarterectomy, fixed in 4% formaldehyde, decalcified in ethylenediaminetetraacetic acid, and cut into 2- to 3-mm slices. After dehydration, the slices were embedded in paraffin and a 5-µm histological section from each slice was cut and stained with hematoxylin and eosin (H&E). The number of histology sections obtained from each plaque ranged from 2 to 9 (mean 4.9, SD 2.0). The plaques were assessed by a pathologist and a research physician blinded for the clinical and the 18F-FDG PET findings. Inflammation was quantified using a modified version of the method used by Jander et al.3 The sections were evaluated with 120× magnification and the percentage area of inflammatory cells (macrophages and leucocytes) per plaque was obtained (Figure 3): For each section, the total area and the area occupied by inflammatory cells were measured manually. The amount of inflammation per plaque was defined as the sum of all areas with inflammatory cells divided by the total area of all the sections. We performed repeated histopathological assessment on selected sections from this study cohort and found that the amount of inflammatory cells was in the same 5% category at both assessments for 73% of the sections (Kappa = 0.73).25 The amount of inflammation per plaque was 6.8% (SD 4.0; range 0.4-17.9).
The SPSS Statistics software for Windows (IBM, version 21.0; SPSS Inc., Chicago, Ill) was used. Groups of data were compared using two-sided t-test and Pearson correlation for normally distributed variables. For non-normal distributions Mann-Whitney test and Spearman correlation were used. Statistical significance was set to 0.05.
The length of the plaques in the cranio-caudal direction was 6-32 mm (mean 19, SD 7.6) and all included the carotid artery bifurcation (Figure 4). Max SUVmax was located between 14 mm below to 18 mm above the bifurcation (mean 1.2 mm below the bifurcation) (Figure 4).
The correlation coefficients between 18F-FDG uptakes calculated from plaques delineated by two nuclear medicine physicians independently were 0.96-0.98 for uncorrected SUVs, 0.63-0.68 for TBRs, and 0.90-0.93 for cSUVs. The correlation coefficient for background blood pool activity was 0.75.
Mean values, SDs, and ranges for the different quantification methods are summarized in Table 2. The 18F-FDG uptake was significantly different for the different quantification approaches (paired samples t-test, P < 0.004 for all pairs). TBR gave the highest mean values and the widest ranges, whereas the background-subtracted values (cSUV) showed the lowest mean values and the narrowest ranges.
18F-FDG uptake for the different quantification methods and corresponding background values for all patients are shown in Figure 5. Mean difference between max SUVmax and mean SUVmax was 0.08 and ranged from 0.02 to 0.66. The effect of background correction is shown in Figure 6. Correlations between 18F-FDG uptake within the groups were 0.93-0.99 for the uncorrected SUV, 0.94-1.0 for TBR, and 0.92-0.99 for cSUV (Table 3).
There were significant moderate (0.44-0.59) correlations between the amount of inflammation and all the different 18F-FDG quantification methods (Table 4). The highest correlations were found for mean SUVmax, and the lowest for max SUVmax independent of background correction. Figure 7 shows scatter plots of inflammation versus max and mean SUVmax with and without background correction.
In this clinical study, we explored different methods for the quantification of 18F-FDG uptake in carotid plaques causing artery stenosis equal to or above 70%. 18F-FDG uptake was homogenously disseminated throughout the entire plaques. Although there were differences in magnitude, quantification of 18F-FDG uptake with and without background correction showed similar, moderate correlations to inflammation on histology.
Mean max SUVmax (mean of the max SUVmax for the study population) was only 13% higher than mean mean SUVmax (Figure 8), whereas the three other quantification methods gave values in between, increasing with decreasing number of included slices. Homogenous 18F-FDG uptake throughout the plaque contrasts findings from microPET of endarterectomized plaques showing patchy 18F-FDG uptake.26 The presence of macrophages reduces the thickness of the fibrous capsule and therefore an increasing number is likely to correlate to increasing vulnerability. As such, the highest 18F-FDG uptake within a plaque could be the most appropriate parameter for risk assessment. Currently, the most used measure for assessment of plaque inflammation has been the mean SUVmax.17,21,22 No clinical studies have assessed the use of whole plaque max SUVmax. Max SUVmax is easily obtained, highly reproducible, and less influenced by partial-volume effects.8,27 Although max SUVmax is prone to image noise,8 our findings suggest that for atherosclerotic plaque assessment in clinical PET, max SUVmax should be explored further.
The strong correlation between the different quantification methods suggests that for this group of patients uncorrected 18F-FDG uptake values may provide similar information as background-corrected values. As such, our findings do not support the superiority of TBR as quantification method as suggested by others.4,10,14,15,16,17 For circulation times above one hour, the blood background is low, but highly variable, whereas carotid plaques have consistent uptake over time.11,13 A slight variation in blood background will therefore give significant variability in TBR. From a physics perspective, Huet et al 9 have explained that there is no legitimate rationale for using TBR instead of SUV because blood contamination is an additive and not a multiplicative process. A purely additive process would require subtraction of the mean luminal blood pool activity from the SUVs (c