Affiliation:
1. Department of Nuclear Medicine & Molecular Imaging Medical Imaging Center University of Groningen University Medical Center Groningen Groningen The Netherlands
2. Department of Applied Mathematics and Technical Medicine Center University of Twente Enschede The Netherlands
3. Department of Biomedical Photonic Imaging University of Twente Enschede The Netherlands
Abstract
AbstractBackgroundCurrently, computed tomography (CT) is used for risk profiling of (asymptomatic) individuals by calculating coronary artery calcium scores. Although this score is a strong predictor of major adverse cardiovascular events, this method has limitations. Sodium [18F]fluoride (Na[18F]F) positron emission tomography (PET) has shown promise as an early marker for atherosclerotic progression. However, evidence on Na[18F]F as a marker for high‐risk plaques is limited, particularly on its presentation in clinical PET/CT. Besides, the relationship between microcalcifications visualized by Na[18F]F PET and macrocalcifications detectable on CT is unknown.PurposeTo establish a match/mismatch score in the aorta between macrocalcified plaque content on CT and microcalcification Na[18F]F PET uptake.MethodsNa[18F]F‐PET/CT scans acquired in our centre in 2019–2020 were retrospectively collected. The aorta of each low‐dose CT was manually segmented. Background measurements were placed in the superior vena cava. The vertebrae were automatically segmented using an open‐source convolutional neural network, dilated with 10 mm, and subtracted from the aortic mask. Per patient, calcium and Na[18F]F‐hotspot masks were retrieved using an in‐house developed algorithm. Three match/mismatch analyses were performed: a population analysis, a per slice analysis, and an overlap score. To generate a population image of calcium and Na[18F]F hotspot distribution, all aortic masks were aligned. Then, a heatmap of calcium HU and Na[18F]F‐uptake on the surface was obtained by outward projection of HU and uptake values from the centerline. In each slice of the aortic wall of each patient, the calcium mass score and target‐to‐bloodpool ratios (TBR) were calculated within the calcium masks, in the aortic wall except the calcium masks, and in the aortic wall in slices without calcium. For the overlap score, three volumes were identified in the calcium and Na[18F]F masks: volume of PET (PET+/CT‐), volume of CT (PET‐/CT+), and overlapping volumes (PET+/CT+). A Spearman's correlation analysis with Bonferroni correction was performed on the population image, assessing the correlation between all HU and Na[18F]F vertex values. In the per slice analysis, a paired Wilcoxon signed‐rank test was used to compare TBR values within each slice, while an ANOVA with post‐hoc Kruskal–Wallis test was employed to compare TBR values between slices. p‐values < 0.05 were considered significant.ResultsIn total, 186 Na[18F]F‐PET/CT scans were included. A moderate positive exponential correlation was observed between total aortic calcium mass and total aortic TBR (r = 0.68, p < 0.001). A strong positive correlation (r = 0.77, p < 0.0001) was observed between CT values and Na[18F]F values on the population image. Significantly higher TBR values were found outside calcium masks than inside calcium masks (p < 0.0001). TBR values in slices where no calcium was present, were significantly lower compared with outside calcium and inside calcium (both p < 0.0001). On average, only 3.7% of the mask volumes were overlapping.ConclusionsNa[18F]F‐uptake in the aorta behaves similarly to macrocalcification detectable on CT. Na[18F]F‐uptake values are also moderately correlated to calcium mass scores (match). Higher uptake values were found just outside macrocalcification masks instead of inside the macrocalcification masks (mismatch). Also, only a small percentage of the Na[18F]F‐uptake volumes overlapped with the calcium volumes (mismatch).