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Pericarotid fat density was associated with carotid plaque vulnerability, especially IPH and TRFC
Miao Yu1, Yankai Meng1, Beiru Wang1, Yaqiong Ge2, and Kai Xu1
1the Affiliated Hospital of Xuzhou Medical University, Xuzhou, China, 2GE Healthcare,Precision health institution,China., Shanghai, China

Synopsis

Inflammation play important roles in the vulnerability of atherosclerotic plaque. Pericoronary fat is associated with coronary heart disease and high-risk plaque, however the value of pericarotid fat density (PFD) remains uncertain. We evaluated the association between PFD on computed tomography angiography (CTA), with the vulnerable composition of carotid plaques. We found that the PFD was independently associated with vulnerability of carotid plaque especially for IPH and TRFC, suggesting that pericarotid fat tissue may play a key role in the occurrence of vulnerable plaques. The identification of local perivascular inflammation may help identify patients who may benefit from targeted therapy.

Objectives: Inflammation and neovascularity play important roles in the vulnerability of atherosclerotic plaque[1]. Serum markers of inflammation, such as C-reactive protein, can help predict patients at high risk of cardiovascular disease, but cannot identify specific areas of vascular inflammation. The identification of local perivascular inflammation may help identify patients who may benefit from targeted therapy aimed at preventing cardiovascular ischemic events[2, 3]. Perivascular adipose tissue can carry inflammatory components[4, 5]. Pericoronary fat is associated with coronary heart disease and high-risk plaque[6-8]. However the value of pericarotid fat density measurements remains uncertain. Our aim was to evaluate the association between pericarotid inflammation, measured by carotid perivascular fat density (PFD) on computed tomography angiography (CTA), with the vulnerable composition of carotid atherosclerotic plaques. Methods: This was a single-center retrospective study. Patients with unilateral carotid plaque and underwent both CTA and magnetic resonance imaging (MRI) within 1 months were analyzed retrospectively (Fig1). Two trained neuroradiologist who blinded to the clinical and MRI imaging placed regions-of-interest (ROI) in the pericarotid fat on the maximal stenosis slice (Fig2). The mean perivascular fat density (mean HU) was measured on both plaque side and non-plaque side, and the bilateral difference (D-value HU) was calculated (plaque side minus non-plaque side). MRI plaque type (American Heart Association lesion type, AHA-LT) and components were evaluated by two other radiologists including calcification (CA), thinning and/or rupture of the fibrous cap (TRFC), lipid-rich necrotic core (LRNC), intraplaque hemorrhage (IPH). SPSS 23.0 software was used for statistical analysis. The t-test, Mann-Whitney U test, and chi-square test were compared the differences between the groups. ROC analysis was used to evaluate the efficacy of the model. P values less than 0.05 were considered statistically significant. Results: 71 eligible patients (mean age, 61.25 ± 10.35 years, 57 (80.3%) male) were collected retrospectively. The mean HU of plaque side (-33.55 ± 19.78, -49.50 ± 20.53, P = 0.014), the D-value HU (33.61 ± 16.72 vs 15.91 ± 14.52, P=0.001) of AHA VI group showed higher than non-AHA VI group. Compared to non-IPH group, higher mean HU of plaque side (-29.63 ± 19.16, -47.68 ± 18.26, P < 0.001) and higher D-value HU (38.03 ± 15.46, 17.80 ± 13.27, P < 0.001), respectively, were observed in IPH group. Patients with TRFC showed higher D-value HU (33.55 ± 17.65, 24.51 ± 16.16, respectively, P =0.042) compared to non-TRFC group (Fig3). D-value of PFD was a better predictor of AHA VI (AUC:0.79, SE:64.41%; SP: 83.33%; P=0.0001) and IPH (AUC:0.83, SE:88.89%; SP:65.38%; P<0.0001) (Fig4). Conclusion: The PFD was independently associated with vulnerability of carotid plaque especially for IPH and TRFC, suggesting that pericarotid fat tissue may play a key role in the occurrence of vulnerable plaques. Our findings may provide a novel marker for carotid plaque risk stratification.

Acknowledgements

No acknowledgement found.

References

References

[1] Ross R. Atherosclerosis--an inflammatory disease. N Engl J Med. 1999. 340(2): 115-26.

[2] Skiba DS, Nosalski R, Mikolajczyk TP, et al. Anti-atherosclerotic effect of the angiotensin 1-7 mimetic AVE0991 is mediated by inhibition of perivascular and plaque inflammation in early atherosclerosis. Br J Pharmacol. 2017. 174(22): 4055-4069.

[3] Xiong W, Zhao X, Villacorta L, et al. Brown Adipocyte-Specific PPARγ (Peroxisome Proliferator-Activated Receptor γ) Deletion Impairs Perivascular Adipose Tissue Development and Enhances Atherosclerosis in Mice. Arterioscler Thromb Vasc Biol. 2018. 38(8): 1738-1747.

[4] Margaritis M, Antonopoulos AS, Digby J, et al. Interactions between vascular wall and perivascular adipose tissue reveal novel roles for adiponectin in the regulation of endothelial nitric oxide synthase function in human vessels. Circulation. 2013. 127(22): 2209-21.

[5] Henrichot E, Juge-Aubry CE, Pernin A, et al. Production of chemokines by perivascular adipose tissue: a role in the pathogenesis of atherosclerosis. Arterioscler Thromb Vasc Biol. 2005. 25(12): 2594-9.

[6] Konishi M, Sugiyama S, Sato Y, et al. Pericardial fat inflammation correlates with coronary artery disease. Atherosclerosis. 2010. 213(2): 649-55.

[7] Lu MT, Park J, Ghemigian K, et al. Epicardial and paracardial adipose tissue volume and attenuation - Association with high-risk coronary plaque on computed tomographic angiography in the ROMICAT II trial. Atherosclerosis. 2016. 251: 47-54.

[8] Oikonomou EK, Williams MC, Kotanidis CP, et al. A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography. Eur Heart J. 2019. 40(43): 3529-3543.

Figures

Figure 1. Flow chart of this study. TC, total cholesterol; TG, triglycerides; HDL: high density lipoprotein; LDL: low density lipoprotein.


Figure 2. A 77-year-old man was detected left frontotemporal lobe acute infarction on MRI (B). CTA imagings (A) showed carotid plaque in the left internal carotid artery (ICA). Two ROIs were placed in the perivascular fat of the maximal plaque of left ICA on the axial slice (yellow arrow). Then, same two ROIs were placed in the perivascular fat of contralateral non-stenotic ICA. In this case, the two ROIs of left stenotic ICA and right non-stenotic were -23 HU, -30 HU and -85.0 HU, -87.0 HU, respectively.


Figure 3. Scatter plots of pericarotid fat density in 5 subgroups. (A) AHA type (non-AHA VI VS AHA VI); (B) intraplaque hemorrhage (IPH VS non-IPH); (C) thinning and/or rupture of the fibrous cap (non-TRFC VS TRFC); (D) lipid-rich necrotic core (non-LRNC VS LRNC); (E) calcification (non-CA VS CA).


Figure 4 The ROC curve of Pericarotid Fat Density (Measured in HU) for prediction AHV VI (A), IPH (B), and TRFC (C). AHA VI: American Heart Association VI plaque; IPH: intraplaque hemorrhage, TRFC: thinning and/or rupture of the fibrous cap.


Proc. Intl. Soc. Mag. Reson. Med. 30 (2022)
4468
DOI: https://doi.org/10.58530/2022/4468