Pericarotid Fat as a Marker of Cerebrovascular Risk

Riccardo Cau; Nicoletta Anzalone; Lorenzo Mannelli; Myriam Edjlali; Antonella Balestrieri; Valentina Nardi; Giuseppe Lanzino; Amir Lerman; Jasjit S. Suri; Luca Saba

doi:10.3174/ajnr.A8300

SUMMARY:

Vascular inflammation is widely recognized as an important factor in the atherosclerotic process, particularly in terms of plaque development and progression. Conventional tests, such as measuring circulating inflammatory biomarkers, lack the precision to identify specific areas of vascular inflammation. In this context, noninvasive imaging modalities can detect perivascular fat changes, serving as a marker of vascular inflammation. This review aims to provide a comprehensive overview of the key concepts related to perivascular carotid fat and its pathophysiology. Additionally, we examine the existing literature on the association of pericarotid fat with features of plaque vulnerability and cerebrovascular events. Finally, we scrutinize the advantages and limitations of the noninvasive assessment of pericarotid fat.

ABBREVIATIONS:

AI: artificial intelligence
AUC: area under the curve
HU: Hounsfield unit
PCF: pericarotid fat
PVAT: perivascular adipose tissue
US: ultrasound
USPIO: ultra-small superparamagnetic iron oxide particles

Carotid artery atherosclerosis, a complex and multifactorial systemic condition, is highly prevalent in the general population and is a well-established risk factor for adverse cardiovascular events worldwide.¹ Growing evidence suggests that vulnerable carotid plaques are associated with a higher risk of cerebrovascular events beyond the mere degree of carotid artery stenosis.² With regard to features of plaque vulnerability, inflammation is an integral element of the pathophysiologic processes that form the basis of atherosclerosis.^3⇓-5 Inflammatory mediators are contained in the perivascular adipose tissue (PVAT), that is anatomically close to the vascular wall.⁶ During atherosclerosis, local PVAT, adjacent to the carotid arteries, namely pericarotid fat (PCF), changes its composition and biology due to inflammatory processes with a “cross-talk” between PVAT and blood vessels.⁷

The levels of systemic inflammatory serum markers can assist in identifying and detecting inflammatory responses,^8,9 but cannot discriminate specific areas of vascular inflammation.

Noninvasive imaging modalities have shown the feasibility of measuring PVAT and its alterations during atherosclerosis.^{10⇓⇓⇓-14} Among them, CT has been demonstrated to be capable to detect the inflammation-induced changes in perivascular carotid fat tissue due to an increase in Hounsfield units (HUs).¹⁴ Several clinical studies have demonstrated the association of PCF and cerebrovascular events.^15⇓⇓-18 Fig 1 provides a graphic overview of the potential association of dysfunctional PCF.

FIG 1.

Graphic overview of potential association of dysfunctional PCF.

This review aims to summarize the key concepts related to PCF and its pathophysiology, examining the existing literature on its applicability as a marker of plaque vulnerability and cerebrovascular events. Finally, we examine the advantages and limitations of the noninvasive assessment of PCF.

PATHOPHYSIOLOGY OF PERIVASCULAR CAROTID FAT

PCF represents the PVAT located adjacent to the carotid arteries.¹⁹ PVAT consists of different cell types, mainly perivascular adipocytes, endothelial cells, and smooth muscle cells and is a metabolically active tissue surrounding most vascular beds, with some differences in large and small vessels. Indeed, in large vessels, PVAT is continuous with adventitial layers, while in small vessels it is an integral component of the vascular wall itself.²⁰ The lack of an anatomic barrier implies that mediators released by perivascular adipocytes can easily penetrate the blood vessel wall.^6,21

Growing evidence emphasizes the association between vascular inflammation and carotid atherosclerosis, from early atherogenesis to the progression of atherosclerotic lesions. The pathogenesis of atherosclerosis involves multiple steps that appear to be initiated by the deposition of low-density lipoproteins in the arterial intima, accompanied by local oxidative stress and immune and inflammatory activation.²² Endothelial and smooth muscle cells respond to such conditions by expressing chemical mediators and recruiting macrophages which, in turn, accumulate intracellular lipids forming pathologic intimal thickening with lipid pools, namely fatty streaks, the first macroscopic sign of atherosclerosis.²² Lesion progression occurs with accumulation of inflammatory leukocytes consisting primarily of macrophages and lymphocytes. Adhesion of monocytes involves the expression of selectins, which facilitate the rolling of white cells, followed by firm attachment to endothelial integrins mediated by immunoglobulin G superfamily members such as vascular cell adhesion molecule-1 and intercellular adhesion molecule-1, and transmigration by way of the endothelial junctional proteins. During atherosclerosis, local PVAT undergoes alterations in its composition and biology, resulting in a shift in the secretome of PVAT.^6,23,24 Dysfunctional PVAT secretes a range of bioactive molecules, including adipokines and cytokines, which promote the activation of inflammatory pathways through paracrine and vasocrine effects. This, in turn, leads to endothelial dysfunction and further promotes inflammation.^{18,23,25⇓-27} Histologic studies have confirmed a marked increase in inflammatory cells in PVAT surrounding atherosclerotic vessels.^24,28⇓-30 Furthermore, dysfunctional PVAT may be potentially linked to nonatherosclerosis vessel diseases through vascular wall inflammation, oxidative stress, vascular smooth muscle cell proliferation, and endothelial dysfunction.^31,32

Quantifying the presence and extent of perivascular inflammation is emerging as a promising approach to predict cerebrovascular events and could lead to the development of personalized medicine with new therapeutic targets. The significance of vascular inflammation was underscored in the newly proposed Plaque-RADS score, which recommends reporting vascular inflammation as an ancillary feature.⁴

NONINVASIVE EVALUATION OF PCF

CT is a highly noninvasive sensitive technique for the comprehensive assessment of PCF, because of its availability and spatial resolution. It allows differentiation of tissue components based on different attenuation via HUs. It is well-established that CT attenuation for adipose tissue ranges from −190 to −30 HU. Inflammatory changes in the fat tissue may lead to impaired lipid development, resulting in less negative HU values.³³ Adipose tissue attenuation can be manually measured in CT angiography by defining a circular/elliptical region of interest close to the point of maximum stenosis while avoiding neighboring tissues such as muscle and venous vessels,³⁴ or semiautomatically through dedicated postprocessing software (Fig 2).¹⁵

FIG 2.

Examples of various methods described in the literature to define PCF. A, PCF is defined as the adipose tissue within a radial distance from the outer vessel wall equal to the diameter of the carotid vessel. B, PCF was obtained by tracking 2 separate regions of interest (each with an area of 2.5 mm²) located at least 1 mm from the outer margin of the carotid artery wall.

CT enables the assessment of carotid anatomy and the identification of carotid plaques simultaneously,³⁴ and the quantification of PCF attenuation does not require extra protocol within routine carotid CT.

In addition to CT assessment of PCF, alternative modalities have been suggested. Skilton et al³⁵ developed a noninvasive ultrasound (US) parameter, called carotid extra-media thickness, defined as “the distance between the carotid media-adventitia interface and the jugular lumen.” Despite this, PCF represents a considerable percentage of extra-media thickness measurement, as demonstrated in histologic specimens.¹⁸ This proposed US parameter is not a direct measurement of PCF, because it also includes interstitial tissue, carotid artery adventitia, and the venous wall.³⁵ These novel proposed US parameters demonstrated notable association with vascular changes associated with cardiovascular risk factors.³⁵ Another US vascular index, namely periarterial adipose tissue intima media adventitia, has been introduced that incorporates carotid indexes (eg, intima-media thickness and extra-media thickness) and echocardiography parameters (eg, epicardial fat thickness).³⁶ This new US parameter has been demonstrated to be associated with the presence and severity of cardiovascular events.³⁶

Other noninvasive imaging modalities have been proposed to directly evaluate the inflammatory state in carotid plaques rather than the PCF, serving as an indirect marker of plaque inflammation. In particular, promising results in the assessment of plaque inflammation are obtained by using MR imaging with ultra-small superparamagnetic iron oxide particles (USPIO).^10⇓-12 USPIO uptake measured by MR imaging has been demonstrated to correlate with the number of macrophages, as in vivo imaging biomarkers for plaque inflammation and vascularity in histologic studies.^12,37

Similarly, [¹⁸FDG]-PET holds promise to identify areas of inflammation.¹³ Johnsrud et al³⁸ demonstrated that ¹⁸FDG uptake reflects the inflammatory status as assessed on histology. Indeed, activated macrophages during an inflammatory state have high glucose metabolism and radioactive ¹⁸FDG is absorbed by macrophages in excised human plaque.³⁹ Encouraging findings are arising from the application of ¹⁸F-sodium fluoride PET in identifying active formation of calcification linked to plaque vulnerability.^{40⇓⇓⇓-44}

Current Limitations of Noninvasive Imaging Modalities

The assessment of PCF as an indirect marker of vascular inflammation presents intrinsic limitations associated with each noninvasive imaging technique. For instance, PCF measurement by using CT has several limitations related to CT parameters including reconstruction algorithm, CT model, and tube voltage.^45,46 As reported by Ma et al,⁴⁷ PVAT demonstrated a positive linear association with tube voltage, suggesting that differences in tube voltage can lead to significant changes in HU values. Because carotid CT scans are acquired at various tube voltages depending on patient characteristics and the CT reconstruction system (which allows for the reduction of radiation and contrast medium volume), adjustments to threshold values for PVAT may be necessary. In addition, measurement approaches for PCF exhibit significant heterogeneity, and a standardized method for measuring and quantifying PCF has not yet been developed. Additionally, CT disadvantages include exposure to ionizing radiation and potential adverse reactions to iodinated contrast media.⁴⁸

Conversely, US assessment, aside from its inability to exclusively target the PCF component, is subject to intrinsic limitations. These include interobserver variability, challenges related to plaque composition (such as calcifications), anatomic considerations, and constraints imposed by a limited anatomic window.^2,48,49

Despite promising results in directly evaluating the vascular inflammatory status, the applicability of MR imaging with USPIO and [¹⁸F]FDG-PET is limited in clinical practice due to long acquisition times, the need for specialized hardware for high-resolution images, the complexity of interpretation, as well as their expense and limited accessibility.⁵⁰

ASSOCIATION WITH FEATURES OF PLAQUE VULNERABILITY

Inflammation is recognized as a crucial contributor to atherosclerotic plaque formation and destabilization and PCF contributes in promoting atherosclerosis by secreting proatherogenic mediators.^51,52 In the retrospective study of Yu et al,¹⁶ 71 patients with carotid atherosclerosis were evaluated by using CT to analyze the relationship between PCF and various risk characteristics of carotid plaque, including American Heart Association type VI, intraplaque hemorrhage, thinning and/or rupture of the fibrous cap, lipid-rich necrotic core, and calcification. The PCF attenuation ipsilateral to vulnerable plaque showed increased values in comparison with the contralateral carotid. PCF attenuation was an independent predictor for intraplaque hemorrhage (β = 0.529, P < .001) in multiple regression analysis. The researchers proposed that para-endocrine pathways secrete inflammatory cytokines, leading to increased vascular oxidation and inflammation, which in turn enhances microvascular permeability. This process may contribute to subsequent intraplaque neovessel rupture.¹⁶ The association between PCF and intraplaque hemorrhage was also reported by Zhang et al.¹⁹ The authors evaluated inflammatory changes in PCF by using CT in 72 patients with carotid atherosclerosis.¹⁹ PCF surrounding plaques with intraplaque hemorrhage demonstrated higher HU values than those without (−41.4 ± 3.9 versus −55.8 ± 6.5 HU; P < .001). This observation was independent of age, calcification, degree of stenosis, maximum plaque thickness, and ulceration (OR, 1.96; 95% CI, 1.41–2.73; P < .001).¹⁹ Similar results were described by Liu et al⁵³ who demonstrated that PCF is an independent risk factor for plaque vulnerability (OR, 1.212; 95% CI, 1.074–1.367; P = .002). Additionally, PCF attenuation was significantly associated with the degree of hypertension, a well-known risk factor for atherosclerosis and cardiovascular and cerebrovascular events.⁵³

ASSOCIATION WITH CEREBROVASCULAR ISCHEMIC EVENTS

Several studies have demonstrated the association of cerebrovascular events and perivascular carotid fat (Online Supplemental Data).^{15,17,53⇓⇓⇓-57} Baradaran et al¹⁷ reported a higher PCF attenuation in carotid arteries ipsilateral to a stroke or transient ischemic attack in comparison with asymptomatic carotid arteries.

Similar results were also reported by Liu et al⁵³ in their retrospective study of 80 patients with carotid atherosclerosis with moderate-to-severe stenosis. Patients with altered PCF demonstrated larger infarct core volume, faster infarct core growth rate, and worse outcome.⁵³ The link between cerebrovascular events and PCF was also explored in the study by Zhang et al.¹⁵ Symptomatic carotid plaques demonstrated higher PCF HU values than those without symptoms (−55.0 ± 10.0 versus −68.0 ± 10.3 HU, P < .001).¹⁵ In multivariate logistic regression after adjusting for confounding factors (eg, hyperlipidemia, statin use, antiplatelet use, calcification, degree of luminal stenosis, maximum plaque thickness, and ulceration), PCF attenuation remained significantly associated with cerebrovascular symptoms (OR, 1.13; 95% CI, 1.07–1.19; P < .001).¹⁵ In addition, PCF attenuation showed excellent diagnostic performance in discriminating between symptomatic and asymptomatic plaques with an area under the curve (AUC), sensitivity and specificity of 0.81, 87.3%, and 60.6%, respectively.¹⁵

Saba et al¹⁴ investigated the inflammatory changes in the fat tissue surrounding the carotid artery in 100 patients with carotid artery stenosis by using CT, demonstrating a statistically significant positive correlation between perivascular fat attenuation and contrast plaque enhancement on CT (ρ = 0.6582, P = .001). In addition, symptomatic patients showed a stronger correlation compared with asymptomatic patients (ρ = 0.7052, P = .001 versus ρ = 0.4092, P = .001), suggesting that perivascular fat attenuation may be an additional indirect marker of plaque instability in the carotid arteries.¹⁴

Increased attenuation in the fat surrounding the carotid artery was also reported in patients with embolic stroke of undetermined source. Hu et al⁵⁸ evaluated 126 patients with embolic stroke of undetermined source and 118 patients with ischemic stroke from large artery atherosclerosis by using brain MR imaging and CT, reporting that the perivascular carotid fat attenuation around the carotid artery ipsilateral to ischemic stroke significantly increased in comparison with contralateral carotid in both patients with embolic stroke of undetermined source (−56.31 ± 18.70 versus −67.31 ± 20.01, P = .000) and in patients with large artery atherosclerosis ischemic stroke (−51.62 ± 19.95 versus −64.58 ± 22.68, P = .000).⁵⁸ Additionally, the authors reported no significant difference between ipsilateral and contralateral PCF attenuation to infarct in both patients with embolic stroke of undetermined source and in patients with large artery atherosclerosis ischemic stroke. These findings indicate the presence of an inflammation extending beyond the vessel lumen in patients with embolic stroke of undetermined source who share similar risk factor profiles with those experiencing large artery atherosclerosis strokes.⁵⁸

PCF may potentially demonstrate influences on the response to intravenous fibrinolysis, as highlighted in a recent study by Gencer et al.⁵⁹ The authors explored the association of PCF and intravenous tissue plasminogen activator through logistic regression models in 174 patients with acute ischemic stroke treated with intravenous tissue plasminogen activator. The study reported that PCF attenuation was an independent predictor for both modified Rankin score 0–2 and mRS 0–1 outcome.⁵⁹

In addition, PCF attenuation measured by CT has been shown to improve risk stratification for obstructive coronary artery stenosis beyond the Framingham risk score and the degree of carotid artery stenosis in patients who have experienced acute ischemic stroke or transient ischemic attack (Fig 3).⁶⁰

FIG 3.

Axial CT image of a 71-year-old-man with left ischemic stroke. Two ROIs were positioned in the PCF surrounding a stenotic left internal carotid artery with a vulnerable plaque (yellow circles), and 2 ROIs were placed in the contralateral carotid artery in the same section (white circles) to measure perivascular fat attenuation. The PCF demonstrates an HU value of 58.3 and 61 in the left carotid artery and 75.2 and 78.5 in the right carotid artery, respectively.

ASSOCIATION WITH POSTOPERATIVE INTERVENTIONAL COMPLICATION/OUTCOME

PCF may potentially demonstrate effect on postoperative complication of interventional carotid treatment. Hu et al⁶¹ evaluated 181 patients with carotid atherosclerosis who underwent carotid artery stent placement and followed them for 2 years in the postoperative period. Patients with early in-stent restenosis (defined as ≥50% of the luminal stenosis occurring at the entire length of the stent or within 3 mm of the stent edge) showed higher mean HU of PCF attenuation in comparison with patients who did not experience in-stent restenosis (−42.26 ± 6.81 versus −59.66 ± 10.75; P < .001). This observation was independent of age, sex, traditional risk factors, predilation and postdilation (OR, 1.353; 95% CI, 1.215–1.506; P < .001).⁶¹ In addition, the authors identified the best cutoff value for predicting the occurrence of early in-stent restenosis with an AUC of 0.912, a sensitivity of 97.67%, and specificity of 69.57%.⁶¹ Similarly, Jin et al⁶² evaluated the changes in PCF by using CT in 183 patients treated with mechanical thrombectomy due to anterior circulation large vessel occlusion. The authors reported that higher perivascular carotid fat was associated with unsuccessful recanalization (adjusted OR, 2.968; 95% CI, 1.292–6.819; P = .010), poor outcome (adjusted OR, 2.704; 95% CI, 1.610–4.541; P < .001), and mortality (adjusted OR, 1.894; 95% CI, 1.040–3.449; P = .037) after adjustment in multivariate analysis.⁶³ Overall, these findings suggest that PCF may serve as an additional marker in treatment and prevention strategies for carotid atherosclerosis diseases. This relationship may be linked to local oxidative stress promoted by PCF after invasive carotid treatment, leading to the secretion of proinflammatory factors, vascular smooth muscle cell dysfunction, and accelerated neointimal hyperplasia.⁶¹

ASSOCIATION WITH NONATHEROSCLEROTIC CAROTID VASCULAR DISEASE

Growing evidence suggests that PVAT plays a key role also in nonatherosclerotic vascular disease. PVAT reacts to mechanical injuries within the arterial endothelium and regulates the subsequent development of neointima by influencing factors that promote the growth of smooth muscle, adventitial inflammation, and neovascularization.⁶³ Experimental in vivo approaches using adipose tissue transplantation have demonstrated that PVAT accelerated neointimal hyperplasia, adventitial macrophage infiltration, and adventitial angiogenesis in carotid arteries.⁶⁴ Based on histopathologic studies, inflammatory mediators in PVAT may also play a role in the pathogenesis of artery dissection.^65⇓-67 In a study by Cheng et al,⁶⁸ the attenuation of PCF was significantly higher in patients with carotid artery dissection compared with those without (−58.7 ± 10.2 versus −69.3 ± 9.3 HU, P < .0001). In addition, patients with carotid dissection demonstrated a significant reduction in the attenuation of PCF compared with the baseline scan during a median follow-up of 108 days (−57.5 ± 13.4 to −74.3 ± 10.5 HU, P < .05). The researchers proposed that the increased inflammation surrounding carotid arteries could contribute to the mechanical stress on arteries, leading to the development of carotid artery dissection.⁶⁸ It has been recognized that PVAT participates in vasculitis pathogenesis. Recently, a prospective cohort study was performed to evaluate the characteristics and significance of PVAT in Takayasu arteritis. The authors found that PVAT had 100% sensitivity and 95% specificity for differentiating active Takayasu arteritis from controls with an AUC of 0.99.⁶⁹

FUTURE DIRECTION: ARTIFICIAL INTELLIGENCE AND RADIOMICS

The application of artificial intelligence (AI) in carotid artery imaging can help in detecting vulnerable plaque features, enhancing decision-making regarding invasive procedures and treatments in cardiovascular care. Several AI models have been proposed to automatically segment carotid arteries, facilitating the assessment of plaque burden and PCF.^70⇓-72 AI models have the potential to address several existing limitations in the noninvasive assessment of PCF. Notably, they can mitigate the lengthy analysis time typically associated with manual evaluation and reduce interobserver variability, thereby enhancing the efficiency and reliability of PCF assessment. In addition, AI models can integrate imaging data, incorporating PCF along with demographics and clinical parameters, opening a new frontier in cardiovascular risk stratification, as demonstrated in coronary arteries.⁷³ AI-based approaches could streamline the noninvasive assessment of PCF and its application in clinical practice, reducing diagnostic time and enabling automatic classification of patients at risk. In recent years, radiomics features have been suggested as an additional tool to characterize features of plaque vulnerability, extracting voxel-based information from images, capturing the inherent complexity and heterogeneity of pixels in relation to their spatial “neighbors.”⁷⁴ Radiomics extracts extensive quantitative information from conventional imaging data, identifying patterns that may not be discernible to a human reader. Therefore, radiomic analysis of PCF may offer more comprehensive insights into the biologic variations of PCF during carotid atherosclerosis.

CONCLUSIONS

The noninvasive assessment of PCF holds promise as an imaging marker, offering insights into carotid atherosclerosis and enhancing risk stratification. The role of PCF in carotid inflammation and plaque progression is crucial due to its bidirectional connection with carotid arteries. CT attenuation-based assessment of PCF shows promise in predicting high-risk plaques, cerebrovascular events, and postprocedural outcomes. Additionally, PCF may contribute to spontaneous carotid dissection and vasculitis. Despite its potential, challenges exist in standardizing PCF measurement across different CT systems. Standardization efforts are needed to integrate PCF assessment into clinical practice effectively. Future trials should focus on standardizing CT parameters to confirm the potential of PCF for risk assessment and guiding preventive measures.

Footnotes

Disclosure forms provided by the authors are available with the full text and PDF of this article at www.ajnr.org.

References

1.↵
1. Dai H,
2. Much AA,
3. Maor E, et al
. Global, regional, and national burden of ischaemic heart disease and its attributable risk factors, 1990-2017: results from the Global Burden of Disease Study 2017. Eur Heart J Qual Care Clin Outcomes 2022;8:50–60 doi:10.1093/ehjqcco/qcaa076 pmid:33017008
CrossRef PubMed
2.↵
1. Saba L,
2. Agarwal N,
3. Cau R, et al
. Review of imaging biomarkers for the vulnerable carotid plaque. JVS Vasc Sci 2021;2:149–58 doi:10.1016/j.jvssci.2021.03.001 pmid:34617065
CrossRef PubMed
3.↵
1. Ross R
. Atherosclerosis—an inflammatory disease. N Engl J Med 1999;340:115–26 doi:10.1056/NEJM199901143400207 pmid:9887164
CrossRef PubMed
4.↵
1. Saba L,
2. Cau R,
3. Murgia A, et al
. Carotid Plaque-RADS, a novel stroke risk classification system. JACC Cardiovasc Imaging 2023;17:62–75 doi:10.1016/j.jcmg.2023.09.005 pmid:37823860
CrossRef PubMed
5.↵
1. Mazighi M,
2. Labreuche J,
3. Gongora-Rivera F, et al
. Autopsy prevalence of intracranial atherosclerosis in patients with fatal stroke. Stroke 2008;39:1142–47 doi:10.1161/STROKEAHA.107.496513 pmid:18309170
Abstract/FREE Full Text
6.↵
1. Rajsheker S,
2. Manka D,
3. Blomkalns AL, et al
. Crosstalk between perivascular adipose tissue and blood vessels. Curr Opin Pharmacol 2010;10:191–96 doi:10.1016/j.coph.2009.11.005 pmid:20060362
CrossRef PubMed
7.↵
1. Mancio J,
2. Oikonomou EK,
3. Antoniades C
. Perivascular adipose tissue and coronary atherosclerosis. Heart 2018;104:1654–62 doi:10.1136/heartjnl-2017-312324 pmid:29853488
Abstract/FREE Full Text
8.↵
1. Ridker PM,
2. Hennekens CH,
3. Buring JE, et al
. C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. N Engl J Med 2000;342:836–43 doi:10.1056/NEJM200003233421202 pmid:10733371
CrossRef PubMed
9.↵
1. Danesh J,
2. Wheeler JG,
3. Hirschfield GM, et al
. C-reactive protein and other circulating markers of inflammation in the prediction of coronary heart disease. N Engl J Med 2004;350:1387–97 doi:10.1056/NEJMoa032804 pmid:15070788
CrossRef PubMed
10.↵
1. Tang TY,
2. Howarth SPS,
3. Miller SR, et al
. Comparison of the inflammatory burden of truly asymptomatic carotid atheroma with atherosclerotic plaques in patients with asymptomatic carotid stenosis undergoing coronary artery bypass grafting: an ultrasmall superparamagnetic iron oxide enhanced magnet. Eur J Vasc Endovasc Surg 2008;35:392–98 doi:10.1016/j.ejvs.2007.10.019 pmid:18171628
CrossRef PubMed
11.↵
1. Tang TY,
2. Howarth SPS,
3. Miller SR, et al
. The ATHEROMA (Atorvastatin Therapy: Effects on Reduction of Macrophage Activity) study. J Am Coll Cardiol 2009;53:2039–50 doi:10.1016/j.jacc.2009.03.018 pmid:19477353
FREE Full Text
12.↵
1. Kooi ME,
2. Cappendijk VC,
3. Cleutjens KBJM, et al
. Accumulation of ultrasmall superparamagnetic particles of iron oxide in human atherosclerotic plaques can be detected by in vivo magnetic resonance imaging. Circulation 2003;107:2453–58 doi:10.1161/01.CIR.0000068315.98705.CC pmid:12719280
Abstract/FREE Full Text
13.↵
1. Poredos P,
2. Gregoric ID,
3. Jezovnik MK
. Inflammation of carotid plaques and risk of cerebrovascular events. Ann Transl Med 2020;8:1281 doi:10.21037/atm-2020-cass-15 pmid:33178813
CrossRef PubMed
14.↵
1. Saba L,
2. Zucca S,
3. Gupta A, et al
. Perivascular fat density and contrast plaque enhancement: does a correlation exist? AJNR Am J Neuroradiol 2020;41:1460–65 doi:10.3174/ajnr.A6710 pmid:32732275
Abstract/FREE Full Text
15.↵
1. Zhang S,
2. Yu X,
3. Gu H, et al
. Identification of high-risk carotid plaque by using carotid perivascular fat density on computed tomography angiography. Eur J Radiology 2022;150:110269 doi:10.1016/j.ejrad.2022.110269 pmid:35349933
CrossRef PubMed
16.↵
1. Yu M,
2. Meng Y,
3. Zhang H, et al
. Associations between pericarotid fat density and image-based risk characteristics of carotid plaque. Eur J Radiology 2022;153:110364 doi:10.1016/j.ejrad.2022.110364 pmid:35609448
CrossRef PubMed
17.↵
1. Baradaran H,
2. Myneni PK,
3. Patel P, et al
. Association between carotid artery perivascular fat density and cerebrovascular ischemic events. J Am Heart Assoc 2018;7:e010383 doi:10.1161/JAHA.118.010383 pmid:30561272
CrossRef PubMed
18.↵
1. Falk E,
2. Thim T,
3. Kristensen IB
. Atherosclerotic plaque, adventitia, perivascular fat, and carotid imaging. JACC Cardiovasc Imaging 2009;2:183–86 doi:10.1016/j.jcmg.2008.11.005 pmid:19356554
FREE Full Text
19.↵
1. Zhang S,
2. Gu H,
3. Yu X, et al
. Association between carotid artery perivascular fat density and intraplaque hemorrhage. Front Cardiovasc Med 2021;8:735794 doi:10.3389/fcvm.2021.735794 pmid:34616788
CrossRef PubMed
20.↵
1. Aghamohammadzadeh R,
2. Withers S,
3. Lynch F, et al
. Perivascular adipose tissue from human systemic and coronary vessels: the emergence of a new pharmacotherapeutic target. Br J Pharmacol 2012;165:670–82 doi:10.1111/j.1476-5381.2011.01479.x pmid:21564083
CrossRef PubMed
21.↵
1. Katsiki N,
2. Mikhailidis DP
. Perivascular adipose tissue: pathophysiological links with inflammation, atherosclerosis, and thrombosis. Angiology 2021;73:195–96 doi:10.1177/00033197211014676 pmid:34030508
CrossRef PubMed
22.↵
1. Falk E
. Pathogenesis of atherosclerosis. J Am Coll Cardiol 2006;47:C7–12 doi:10.1016/j.jacc.2005.09.068 pmid:16631513
FREE Full Text
23.↵
1. Guglielmo M,
2. Lin A,
3. Dey D, et al
. Epicardial fat and coronary artery disease: role of cardiac imaging. Atherosclerosis 2021;321:30–38 doi:10.1016/j.atherosclerosis.2021.02.008 pmid:33636676
CrossRef PubMed
24.↵
1. Pandzic Jaksic V,
2. Grizelj D,
3. Livun A, et al
. Inflammatory gene expression in neck perivascular and subcutaneous adipose tissue in men with carotid stenosis. Angiology 2021;73:234–43 doi:10.1177/00033197211012539 pmid:33906471
CrossRef PubMed
25.↵
1. Cho Y,
2. Lee SE,
3. Lee HC, et al
. Adipokine resistin is a key player to modulate monocytes, endothelial cells, and smooth muscle cells, leading to progression of atherosclerosis in rabbit carotid artery. J Am Coll Cardiol 2011;57:99–109 doi:10.1016/j.jacc.2010.07.035 pmid:21185508
FREE Full Text
26.↵
1. Stanek A,
2. Brożyna-Tkaczyk K,
3. Myśliński W
. The role of obesity-induced perivascular adipose tissue (PVAT) dysfunction in vascular homeostasis. Nutrients 2021;13:3843 doi:10.3390/nu13113843 pmid:34836100
CrossRef PubMed
27.↵
1. Takaoka M,
2. Suzuki H,
3. Shioda S, et al
. Endovascular injury induces rapid phenotypic changes in perivascular adipose tissue. Arterioscler Thromb Vasc Biol 2010;30:1576–82 doi:10.1161/ATVBAHA.110.207175 pmid:20489168
Abstract/FREE Full Text
28.↵
1. Mazurek T,
2. Zhang L,
3. Zalewski A, et al
. Human epicardial adipose tissue is a source of inflammatory mediators. Circulation 2003;108:2460–66 doi:10.1161/01.CIR.0000099542.57313.C5 pmid:14581396
Abstract/FREE Full Text
29.↵
1. Henrichot E,
2. Juge-Aubry CE,
3. Pernin A, et al
. Production of chemokines by perivascular adipose tissue: a role in the pathogenesis of atherosclerosis? Arterioscler Thromb Vasc Biol 2005;25:2594–99 doi:10.1161/01.ATV.0000188508.40052.35 pmid:16195477
Abstract/FREE Full Text
30.↵
1. Tomas L,
2. Edsfeldt A,
3. Mollet IG, et al
. Altered metabolism distinguishes high-risk from stable carotid atherosclerotic plaques. Eur Heart J 2018;39:2301–10 doi:10.1093/eurheartj/ehy124 pmid:29562241
CrossRef PubMed
31.↵
1. Nosalski R,
2. Guzik TJ
. Perivascular adipose tissue inflammation in vascular disease. Br J Pharmacol 2017;174:3496–513 doi:10.1111/bph.13705 pmid:28063251
CrossRef PubMed
32.↵
1. Kim HW,
2. Belin de Chantemèle EJ,
3. Weintraub NL
. Perivascular adipocytes in vascular disease. Arterioscler Thromb Vasc Biol 2019;39:2220–27 doi:10.1161/ATVBAHA.119.312304 pmid:31510794
CrossRef PubMed
33.↵
1. Sagris M,
2. Antonopoulos AS,
3. Simantiris S, et al
. Pericoronary fat attenuation index—a new imaging biomarker and its diagnostic and prognostic utility: a systematic review and meta-analysis. Eur Heart J Cardiovasc Imaging 2022;23:e526–36 doi:10.1093/ehjci/jeac174 pmid:36069510
CrossRef PubMed
34.↵
1. Saba L,
2. Loewe C,
3. Weikert T, et al
. State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: the reporting-a consensus document by the European Society of Cardiovascular Radiology (ESCR). Eur Radiology 2022;33:1088–101 doi:10.1007/s00330-022-09025-6 pmid:36194266
CrossRef PubMed
35.↵
1. Skilton MR,
2. Serusdat A,
3. Sethu AHAU, et al
. Noninvasive measurement of carotid extra-media thickness: associations with cardiovascular risk factors and intima-media thickness. JACC Cardiovasc Imaging 2009;2:176–82 doi:10.1016/j.jcmg.2008.09.013 pmid:19356553
Abstract/FREE Full Text
36.↵
1. Haberka M,
2. Gąsior Z
. A carotid extra-media thickness, PATIMA combined index and coronary artery disease: comparison with well-established indexes of carotid artery and fat depots. Atherosclerosis 2015;243:307–13 doi:10.1016/j.atherosclerosis.2015.09.022 pmid:26414210
CrossRef PubMed
37.↵
1. Metz S,
2. Beer AJ,
3. Settles M, et al
. Characterization of carotid artery plaques with USPIO-enhanced MRI: assessment of inflammation and vascularity as in vivo imaging biomarkers for plaque vulnerability. Int J Cardiovasc Imaging 2011;27:901–12 doi:10.1007/s10554-010-9736-7 pmid:20972832
CrossRef PubMed
38.↵
1. Johnsrud K,
2. Skagen K,
3. Seierstad T, et al
. (18)F-FDG PET/CT for the quantification of inflammation in large carotid artery plaques. J Nucl Cardiol Off Cardiol 2019;26:883–93 doi:10.1007/s12350-017-1121-7 pmid:29209949
CrossRef PubMed
39.↵
1. Rudd JHF,
2. Warburton EA,
3. Fryer TD, et al
. Imaging atherosclerotic plaque inflammation with [18F]-fluorodeoxyglucose positron emission tomography. Circulation 2002;105:2708–11 doi:10.1161/01.cir.0000020548.60110.76 pmid:12057982
Abstract/FREE Full Text
40.↵
1. Hop H,
2. de Boer SA,
3. Reijrink M, et al
. 18F-sodium fluoride positron emission tomography assessed microcalcifications in culprit and non-culprit human carotid plaques. J Nucl Cardiol 2019;26:1064–75 doi:10.1007/s12350-018-1325-5 pmid:29943142
CrossRef PubMed
41.↵
1. Cocker MS,
2. Spence JD,
3. Hammond R, et al
; Canadian Atherosclerosis Imaging Network (CAIN). [18F]-NaF PET/CT identifies active calcification in carotid plaque. JACC Cardiovasc Imaging 2017;10:486–88 doi:10.1016/j.jcmg.2016.03.005 pmid:27318719
FREE Full Text
42.↵
1. Kaczynski J,
2. Sellers S,
3. Seidman MA, et al
. 18F-NaF PET/MRI for detection of carotid atheroma in acute neurovascular syndrome. Radiology 2022;305:137–48 doi:10.1148/radiol.212283 pmid:35670715
CrossRef PubMed
43.↵
1. Mechtouff L,
2. Sigovan M,
3. Douek P, et al
. Simultaneous assessment of microcalcifications and morphological criteria of vulnerability in carotid artery plaque using hybrid (18)F-NaF PET/MRI. J Nucl Cardiol Off Cardiol 2022;29:1064–74 doi:10.1007/s12350-020-02400-0 pmid:33145738
CrossRef PubMed
44.↵
1. Vesey AT,
2. Jenkins WSA,
3. Irkle A, et al
. (18)F-fluoride and (18)F-fluorodeoxyglucose positron emission tomography after transient ischemic attack or minor ischemic stroke: case-control study. Circ Cardiovasc Imaging 2017;10:e004976 doi:10.1161/CIRCIMAGING.116.004976 pmid:28292859
Abstract/FREE Full Text
45.↵
1. Chen X,
2. Dang Y,
3. Hu H, et al
. Pericoronary adipose tissue attenuation assessed by dual-layer spectral detector computed tomography is a sensitive imaging marker of high-risk plaques. Quant Imaging Med Surg 2021;11:2093–103 doi:10.21037/qims-20-860 pmid:33936990
CrossRef PubMed
46.↵
1. Tan N,
2. Dey D,
3. Marwick TH, et al
. Pericoronary adipose tissue as a marker of cardiovascular risk: JACC review topic of the week. J Am Coll Cardiol 2023;81:913–23 doi:10.1016/j.jacc.2022.12.021 pmid:36858711
CrossRef PubMed
47.↵
1. Ma R,
2. Ties D,
3. van Assen M, et al
. Towards reference values of pericoronary adipose tissue attenuation: impact of coronary artery and tube voltage in coronary computed tomography angiography. Eur Radiology 2020;30:6838–46 doi:10.1007/s00330-020-07069-0 pmid:32700017
CrossRef PubMed
48.↵
1. Cau R,
2. Gupta A,
3. Kooi ME, et al
. Pearls and pitfalls of carotid artery imaging: ultrasound, computed tomography angiography, and MR imaging. Radiology Clin North Am 2023;61:405–13 doi:10.1016/j.rcl.2023.01.001 pmid:36931758
CrossRef PubMed
49.↵
1. Cademartiri F,
2. Balestrieri A,
3. Cau R, et al
. Insight from imaging on plaque vulnerability: similarities and differences between coronary and carotid arteries—implications for systemic therapies. Cardiovasc Diagn Ther 2020;10:1150–62 doi:10.21037/cdt-20-528 pmid:32968666
CrossRef PubMed
50.↵
1. Mayer M,
2. Borja AJ,
3. Hancin EC, et al
. Imaging atherosclerosis by PET, with emphasis on the role of FDG and NaF as potential biomarkers for this disorder. Front Physiol 2020;11:511391 doi:10.3389/fphys.2020.511391 pmid:33192540
CrossRef PubMed
51.↵
1. Verhagen SN,
2. Visseren FLJ
. Perivascular adipose tissue as a cause of atherosclerosis. Atherosclerosis 2011;214:3–10 doi:10.1016/j.atherosclerosis.2010.05.034 pmid:20646709
CrossRef PubMed
52.↵
1. Alkhalil M,
2. Edmond E,
3. Edgar L, et al
. The relationship of perivascular adipose tissue and atherosclerosis in the aorta and carotid arteries, determined by magnetic resonance imaging. Diab Vasc Dis Res 2018;15:286–93 doi:10.1177/1479164118757923 pmid:29446645
CrossRef PubMed
53.↵
1. Liu Y,
2. Xu L,
3. Gu Y, et al
. Impact of H-type hypertension on pericarotid adipose tissue and plaque characteristics based on computed tomography (CT) angiography: a propensity score matching study. Med Sci Monit 2021;27:e933351 doi:10.12659/MSM.933351 pmid:34857728
CrossRef PubMed
54.↵
1. Liu Y,
2. Zhao Y,
3. Guo Z, et al
. Pericarotid fat stranding at computed tomography angiography: a marker of the short-term prognosis of acute ischemic stroke. J Comput Assist Tomogr 2024;48:311–16 doi:10.1097/RCT.0000000000001555 pmid:37876252
CrossRef PubMed
55.↵
1. Liu X,
2. Wu F,
3. Jia X, et al
. Pericarotid adipose tissue computed tomography attenuation distinguishes different stages of carotid atherosclerotic disease: a cross-sectional study. Quant Imaging Med Surg 2023;13:8247–58 doi:10.21037/qims-23-454 pmid:38106246
CrossRef PubMed
56.↵
1. Liu Y,
2. Zhao Y,
3. Guo Z, et al
. A novel predictive model based on pericarotid adipose tissue and lumen stenosis for stroke risk in patients with asymptomatic carotid stenosis. J Investig Med 2024;72:270–78 doi:10.1177/10815589241226728 pmid:38183206
CrossRef PubMed
57.↵
1. Zhang DH,
2. Jin JL,
3. Zhu CF, et al
. Association between carotid artery perivascular fat density and cerebral small vessel disease. Aging (Albany NY) 2021;13:18839–51 doi:10.18632/aging.203327 pmid:34289452
CrossRef PubMed
58.↵
1. Hu X,
2. Chen J,
3. Fu H, et al
. Association between carotid artery perivascular fat density and embolic stroke of undetermined source. Front Neurol 2021;12:765962 doi:10.3389/fneur.2021.765962 pmid:35250789
CrossRef PubMed
59.↵
1. Gencer ES,
2. Yilmaz E,
3. Arsava EM, et al
. Carotid artery perivascular adipose tissue density and response to intravenous tissue plasminogen activator in acute ischemic stroke. Angiology 2023;75:472–79 doi:10.1177/00033197231174654
CrossRef
60.↵
1. Lan Y,
2. Shang J,
3. Ma Y, et al
. A new predictor of coronary artery disease in acute ischemic stroke or transient ischemic attack patients: pericarotid fat density. Eur Radiology 2023;34:1667–76 doi:10.1007/s00330-023-10046-y
CrossRef
61.↵
1. Hu J,
2. Hu N,
3. Hu T, et al
. Associations between preprocedural carotid artery perivascular fat density and early in-stent restenosis after carotid artery stenting. Heliyon 2023;9:e16220 doi:10.1016/j.heliyon.2023.e16220 pmid:37346364
CrossRef PubMed
62.↵
1. Jin J,
2. Huang R,
3. Chen Q, et al
. Carotid artery perivascular adipose tissue density relates to recanalization and clinical outcome after mechanical thrombectomy. Front Aging Neurosci 2021;13:761248 doi:10.3389/fnagi.2021.761248 pmid:34899273
CrossRef PubMed
63.↵
1. Horimatsu T,
2. Kim HW,
3. Weintraub NL
. The role of perivascular adipose tissue in non-atherosclerotic vascular disease. Front Physiol 2017;8:969 doi:10.3389/fphys.2017.00969 pmid:29234289
CrossRef PubMed
64.↵
1. Manka D,
2. Chatterjee TK,
3. Stoll LL, et al
. Transplanted perivascular adipose tissue accelerates injury-induced neointimal hyperplasia: role of monocyte chemoattractant protein-1. Arterioscler Thromb Vasc Biol 2014;34:1723–30 doi:10.1161/ATVBAHA.114.303983 pmid:24947528
Abstract/FREE Full Text
65.↵
1. Saw J
. Spontaneous coronary artery dissection. Can J Cardiol 2013;29:1027–33 doi:10.1016/j.cjca.2012.12.018 pmid:23498840
CrossRef PubMed
66.↵
1. Adlam D,
2. Alfonso F,
3. Maas A, et al
; Writing Committee. European Society of Cardiology, acute cardiovascular care association, SCAD study group: a position paper on spontaneous coronary artery dissection. Eur Heart J 2018;39:3353–68 doi:10.1093/eurheartj/ehy080 pmid:29481627
CrossRef PubMed
67.↵
1. Hayes SN,
2. Kim ESH,
3. Saw J, et al
; American Heart Association Council on Peripheral Vascular Disease; Council on Clinical Cardiology; Council on Cardiovascular and Stroke Nursing; Council on Genomic and Precision Medicine; and Stroke Council. Spontaneous coronary artery dissection: current state of the science: a scientific statement from the American Heart Association. Circulation 2018;137:e523–57 doi:10.1161/CIR.0000000000000564 pmid:29472380
Abstract/FREE Full Text
68.↵
1. Cheng K,
2. Lin A,
3. Stecher X, et al
. Association between spontaneous internal carotid artery dissection and perivascular adipose tissue attenuation on computed tomography angiography. Int J Stroke 2023;18:829–38 doi:10.1177/17474930231158538 pmid:36748981
CrossRef PubMed
69.↵
1. Wall C,
2. Huang Y,
3. Le EV, et al
. Pericoronary and periaortic adipose tissue density are associated with inflammatory disease activity in Takayasu arteritis and atherosclerosis. Eur Heart J Open 2021;1:oeab019 doi:10.1093/ehjopen/oeab019 pmid:34661196
CrossRef PubMed
70.↵
1. Zhou R,
2. Fenster A,
3. Xia Y, et al
. Deep learning-based carotid media-adventitia and lumen-intima boundary segmentation from three-dimensional ultrasound images. Med Phys 2019;46:3180–93 doi:10.1002/mp.13581 pmid:31071228
CrossRef PubMed
71.↵
1. Zhou T,
2. Tan T,
3. Pan X, et al
. Fully automatic deep learning trained on limited data for carotid artery segmentation from large image volumes. Quant Imaging Med Surg 2021;11:67–83 doi:10.21037/qims-20-286 pmid:33392012
CrossRef PubMed
72.↵
1. dos Santos FLC,
2. Joutsen A,
3. Paci M, et al
. Automatic detection of carotid arteries in computed tomography angiography: a proof of concept protocol. Int J Cardiovasc Imaging 2016;32:1299–310 doi:10.1007/s10554-016-0880-6 pmid:27142430
CrossRef PubMed
73.↵
1. Oikonomou EK,
2. Antonopoulos AS,
3. Schottlander D, et al
. Standardized measurement of coronary inflammation using cardiovascular computed tomography: integration in clinical care as a prognostic medical device. Cardiovasc Res 2021;117:2677–90 doi:10.1093/cvr/cvab286 pmid:34450625
CrossRef PubMed
74.↵
1. Cau R,
2. Flanders A,
3. Mannelli L, et al
. Artificial intelligence in computed tomography plaque characterization: a review. Eur J Radiology 2021;140:109767 doi:10.1016/j.ejrad.2021.109767 pmid:34000598
CrossRef PubMed

Received January 25, 2024.
Accepted after revision March 27, 2024.

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[1] 1.↵
Dai H,
Much AA,
Maor E, et al
. Global, regional, and national burden of ischaemic heart disease and its attributable risk factors, 1990-2017: results from the Global Burden of Disease Study 2017. Eur Heart J Qual Care Clin Outcomes 2022;8:50–60 doi:10.1093/ehjqcco/qcaa076 pmid:33017008
CrossRef PubMed

[2] Dai H,

[3] Much AA,

[4] Maor E, et al

[5] 2.↵
Saba L,
Agarwal N,
Cau R, et al
. Review of imaging biomarkers for the vulnerable carotid plaque. JVS Vasc Sci 2021;2:149–58 doi:10.1016/j.jvssci.2021.03.001 pmid:34617065
CrossRef PubMed

[6] Saba L,

[7] Agarwal N,

[8] Cau R, et al

[9] 3.↵
Ross R
. Atherosclerosis—an inflammatory disease. N Engl J Med 1999;340:115–26 doi:10.1056/NEJM199901143400207 pmid:9887164
CrossRef PubMed

[10] Ross R

[11] 4.↵
Saba L,
Cau R,
Murgia A, et al
. Carotid Plaque-RADS, a novel stroke risk classification system. JACC Cardiovasc Imaging 2023;17:62–75 doi:10.1016/j.jcmg.2023.09.005 pmid:37823860
CrossRef PubMed

[12] Saba L,

[13] Cau R,

[14] Murgia A, et al

[15] 5.↵
Mazighi M,
Labreuche J,
Gongora-Rivera F, et al
. Autopsy prevalence of intracranial atherosclerosis in patients with fatal stroke. Stroke 2008;39:1142–47 doi:10.1161/STROKEAHA.107.496513 pmid:18309170
Abstract/FREE Full Text

[16] Mazighi M,

[17] Labreuche J,

[18] Gongora-Rivera F, et al

[19] 6.↵
Rajsheker S,
Manka D,
Blomkalns AL, et al
. Crosstalk between perivascular adipose tissue and blood vessels. Curr Opin Pharmacol 2010;10:191–96 doi:10.1016/j.coph.2009.11.005 pmid:20060362
CrossRef PubMed

[20] Rajsheker S,

[21] Manka D,

[22] Blomkalns AL, et al

[23] 7.↵
Mancio J,
Oikonomou EK,
Antoniades C
. Perivascular adipose tissue and coronary atherosclerosis. Heart 2018;104:1654–62 doi:10.1136/heartjnl-2017-312324 pmid:29853488
Abstract/FREE Full Text

[24] Mancio J,

[25] Oikonomou EK,

[26] Antoniades C

[27] 8.↵
Ridker PM,
Hennekens CH,
Buring JE, et al
. C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. N Engl J Med 2000;342:836–43 doi:10.1056/NEJM200003233421202 pmid:10733371
CrossRef PubMed

[28] Ridker PM,

[29] Hennekens CH,

[30] Buring JE, et al

[31] 9.↵
Danesh J,
Wheeler JG,
Hirschfield GM, et al
. C-reactive protein and other circulating markers of inflammation in the prediction of coronary heart disease. N Engl J Med 2004;350:1387–97 doi:10.1056/NEJMoa032804 pmid:15070788
CrossRef PubMed

[32] Danesh J,

[33] Wheeler JG,

[34] Hirschfield GM, et al

[35] 10.↵
Tang TY,
Howarth SPS,
Miller SR, et al
. Comparison of the inflammatory burden of truly asymptomatic carotid atheroma with atherosclerotic plaques in patients with asymptomatic carotid stenosis undergoing coronary artery bypass grafting: an ultrasmall superparamagnetic iron oxide enhanced magnet. Eur J Vasc Endovasc Surg 2008;35:392–98 doi:10.1016/j.ejvs.2007.10.019 pmid:18171628
CrossRef PubMed

[36] Tang TY,

[37] Howarth SPS,

[38] Miller SR, et al

[39] 11.↵
Tang TY,
Howarth SPS,
Miller SR, et al
. The ATHEROMA (Atorvastatin Therapy: Effects on Reduction of Macrophage Activity) study. J Am Coll Cardiol 2009;53:2039–50 doi:10.1016/j.jacc.2009.03.018 pmid:19477353
FREE Full Text

[40] Tang TY,

[41] Howarth SPS,

[42] Miller SR, et al

[43] 12.↵
Kooi ME,
Cappendijk VC,
Cleutjens KBJM, et al
. Accumulation of ultrasmall superparamagnetic particles of iron oxide in human atherosclerotic plaques can be detected by in vivo magnetic resonance imaging. Circulation 2003;107:2453–58 doi:10.1161/01.CIR.0000068315.98705.CC pmid:12719280
Abstract/FREE Full Text

[44] Kooi ME,

[45] Cappendijk VC,

[46] Cleutjens KBJM, et al

[47] 13.↵
Poredos P,
Gregoric ID,
Jezovnik MK
. Inflammation of carotid plaques and risk of cerebrovascular events. Ann Transl Med 2020;8:1281 doi:10.21037/atm-2020-cass-15 pmid:33178813
CrossRef PubMed

[48] Poredos P,

[49] Gregoric ID,

[50] Jezovnik MK

[51] 14.↵
Saba L,
Zucca S,
Gupta A, et al
. Perivascular fat density and contrast plaque enhancement: does a correlation exist? AJNR Am J Neuroradiol 2020;41:1460–65 doi:10.3174/ajnr.A6710 pmid:32732275
Abstract/FREE Full Text

[52] Saba L,

[53] Zucca S,

[54] Gupta A, et al

[55] 15.↵
Zhang S,
Yu X,
Gu H, et al
. Identification of high-risk carotid plaque by using carotid perivascular fat density on computed tomography angiography. Eur J Radiology 2022;150:110269 doi:10.1016/j.ejrad.2022.110269 pmid:35349933
CrossRef PubMed

[56] Zhang S,

[57] Yu X,

[58] Gu H, et al

[59] 16.↵
Yu M,
Meng Y,
Zhang H, et al
. Associations between pericarotid fat density and image-based risk characteristics of carotid plaque. Eur J Radiology 2022;153:110364 doi:10.1016/j.ejrad.2022.110364 pmid:35609448
CrossRef PubMed

[60] Yu M,

[61] Meng Y,

[62] Zhang H, et al

[63] 17.↵
Baradaran H,
Myneni PK,
Patel P, et al
. Association between carotid artery perivascular fat density and cerebrovascular ischemic events. J Am Heart Assoc 2018;7:e010383 doi:10.1161/JAHA.118.010383 pmid:30561272
CrossRef PubMed

[64] Baradaran H,

[65] Myneni PK,

[66] Patel P, et al

[67] 18.↵
Falk E,
Thim T,
Kristensen IB
. Atherosclerotic plaque, adventitia, perivascular fat, and carotid imaging. JACC Cardiovasc Imaging 2009;2:183–86 doi:10.1016/j.jcmg.2008.11.005 pmid:19356554
FREE Full Text

[68] Falk E,

[69] Thim T,

[70] Kristensen IB

[71] 19.↵
Zhang S,
Gu H,
Yu X, et al
. Association between carotid artery perivascular fat density and intraplaque hemorrhage. Front Cardiovasc Med 2021;8:735794 doi:10.3389/fcvm.2021.735794 pmid:34616788
CrossRef PubMed

[72] Zhang S,

[73] Gu H,

[74] Yu X, et al

[75] 20.↵
Aghamohammadzadeh R,
Withers S,
Lynch F, et al
. Perivascular adipose tissue from human systemic and coronary vessels: the emergence of a new pharmacotherapeutic target. Br J Pharmacol 2012;165:670–82 doi:10.1111/j.1476-5381.2011.01479.x pmid:21564083
CrossRef PubMed

[76] Aghamohammadzadeh R,

[77] Withers S,

[78] Lynch F, et al

[79] 21.↵
Katsiki N,
Mikhailidis DP
. Perivascular adipose tissue: pathophysiological links with inflammation, atherosclerosis, and thrombosis. Angiology 2021;73:195–96 doi:10.1177/00033197211014676 pmid:34030508
CrossRef PubMed

[80] Katsiki N,

[81] Mikhailidis DP

[82] 22.↵
Falk E
. Pathogenesis of atherosclerosis. J Am Coll Cardiol 2006;47:C7–12 doi:10.1016/j.jacc.2005.09.068 pmid:16631513
FREE Full Text

[83] Falk E

[84] 23.↵
Guglielmo M,
Lin A,
Dey D, et al
. Epicardial fat and coronary artery disease: role of cardiac imaging. Atherosclerosis 2021;321:30–38 doi:10.1016/j.atherosclerosis.2021.02.008 pmid:33636676
CrossRef PubMed

[85] Guglielmo M,

[86] Lin A,

[87] Dey D, et al

[88] 24.↵
Pandzic Jaksic V,
Grizelj D,
Livun A, et al
. Inflammatory gene expression in neck perivascular and subcutaneous adipose tissue in men with carotid stenosis. Angiology 2021;73:234–43 doi:10.1177/00033197211012539 pmid:33906471
CrossRef PubMed

[89] Pandzic Jaksic V,

[90] Grizelj D,

[91] Livun A, et al

[92] 25.↵
Cho Y,
Lee SE,
Lee HC, et al
. Adipokine resistin is a key player to modulate monocytes, endothelial cells, and smooth muscle cells, leading to progression of atherosclerosis in rabbit carotid artery. J Am Coll Cardiol 2011;57:99–109 doi:10.1016/j.jacc.2010.07.035 pmid:21185508
FREE Full Text

[93] Cho Y,

[94] Lee SE,

[95] Lee HC, et al

[96] 26.↵
Stanek A,
Brożyna-Tkaczyk K,
Myśliński W
. The role of obesity-induced perivascular adipose tissue (PVAT) dysfunction in vascular homeostasis. Nutrients 2021;13:3843 doi:10.3390/nu13113843 pmid:34836100
CrossRef PubMed

[97] Stanek A,

[98] Brożyna-Tkaczyk K,

[99] Myśliński W

[100] 27.↵
Takaoka M,
Suzuki H,
Shioda S, et al
. Endovascular injury induces rapid phenotypic changes in perivascular adipose tissue. Arterioscler Thromb Vasc Biol 2010;30:1576–82 doi:10.1161/ATVBAHA.110.207175 pmid:20489168
Abstract/FREE Full Text

[101] Takaoka M,

[102] Suzuki H,

[103] Shioda S, et al

[104] 28.↵
Mazurek T,
Zhang L,
Zalewski A, et al
. Human epicardial adipose tissue is a source of inflammatory mediators. Circulation 2003;108:2460–66 doi:10.1161/01.CIR.0000099542.57313.C5 pmid:14581396
Abstract/FREE Full Text

[105] Mazurek T,

[106] Zhang L,

[107] Zalewski A, et al

[108] 29.↵
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;25:2594–99 doi:10.1161/01.ATV.0000188508.40052.35 pmid:16195477
Abstract/FREE Full Text

[109] Henrichot E,

[110] Juge-Aubry CE,

[111] Pernin A, et al

[112] 30.↵
Tomas L,
Edsfeldt A,
Mollet IG, et al
. Altered metabolism distinguishes high-risk from stable carotid atherosclerotic plaques. Eur Heart J 2018;39:2301–10 doi:10.1093/eurheartj/ehy124 pmid:29562241
CrossRef PubMed

[113] Tomas L,

[114] Edsfeldt A,

[115] Mollet IG, et al

[116] 31.↵
Nosalski R,
Guzik TJ
. Perivascular adipose tissue inflammation in vascular disease. Br J Pharmacol 2017;174:3496–513 doi:10.1111/bph.13705 pmid:28063251
CrossRef PubMed

[117] Nosalski R,

[118] Guzik TJ

[119] 32.↵
Kim HW,
Belin de Chantemèle EJ,
Weintraub NL
. Perivascular adipocytes in vascular disease. Arterioscler Thromb Vasc Biol 2019;39:2220–27 doi:10.1161/ATVBAHA.119.312304 pmid:31510794
CrossRef PubMed

[120] Kim HW,

[121] Belin de Chantemèle EJ,

[122] Weintraub NL

[123] 33.↵
Sagris M,
Antonopoulos AS,
Simantiris S, et al
. Pericoronary fat attenuation index—a new imaging biomarker and its diagnostic and prognostic utility: a systematic review and meta-analysis. Eur Heart J Cardiovasc Imaging 2022;23:e526–36 doi:10.1093/ehjci/jeac174 pmid:36069510
CrossRef PubMed

[124] Sagris M,

[125] Antonopoulos AS,

[126] Simantiris S, et al

[127] 34.↵
Saba L,
Loewe C,
Weikert T, et al
. State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: the reporting-a consensus document by the European Society of Cardiovascular Radiology (ESCR). Eur Radiology 2022;33:1088–101 doi:10.1007/s00330-022-09025-6 pmid:36194266
CrossRef PubMed

[128] Saba L,

[129] Loewe C,

[130] Weikert T, et al

[131] 35.↵
Skilton MR,
Serusdat A,
Sethu AHAU, et al
. Noninvasive measurement of carotid extra-media thickness: associations with cardiovascular risk factors and intima-media thickness. JACC Cardiovasc Imaging 2009;2:176–82 doi:10.1016/j.jcmg.2008.09.013 pmid:19356553
Abstract/FREE Full Text

[132] Skilton MR,

[133] Serusdat A,

[134] Sethu AHAU, et al

[135] 36.↵
Haberka M,
Gąsior Z
. A carotid extra-media thickness, PATIMA combined index and coronary artery disease: comparison with well-established indexes of carotid artery and fat depots. Atherosclerosis 2015;243:307–13 doi:10.1016/j.atherosclerosis.2015.09.022 pmid:26414210
CrossRef PubMed

[136] Haberka M,

[137] Gąsior Z

[138] 37.↵
Metz S,
Beer AJ,
Settles M, et al
. Characterization of carotid artery plaques with USPIO-enhanced MRI: assessment of inflammation and vascularity as in vivo imaging biomarkers for plaque vulnerability. Int J Cardiovasc Imaging 2011;27:901–12 doi:10.1007/s10554-010-9736-7 pmid:20972832
CrossRef PubMed

[139] Metz S,

[140] Beer AJ,

[141] Settles M, et al

[142] 38.↵
Johnsrud K,
Skagen K,
Seierstad T, et al
. (18)F-FDG PET/CT for the quantification of inflammation in large carotid artery plaques. J Nucl Cardiol Off Cardiol 2019;26:883–93 doi:10.1007/s12350-017-1121-7 pmid:29209949
CrossRef PubMed

[143] Johnsrud K,

[144] Skagen K,

[145] Seierstad T, et al

[146] 39.↵
Rudd JHF,
Warburton EA,
Fryer TD, et al
. Imaging atherosclerotic plaque inflammation with [18F]-fluorodeoxyglucose positron emission tomography. Circulation 2002;105:2708–11 doi:10.1161/01.cir.0000020548.60110.76 pmid:12057982
Abstract/FREE Full Text

[147] Rudd JHF,

[148] Warburton EA,

[149] Fryer TD, et al

[150] 40.↵
Hop H,
de Boer SA,
Reijrink M, et al
. 18F-sodium fluoride positron emission tomography assessed microcalcifications in culprit and non-culprit human carotid plaques. J Nucl Cardiol 2019;26:1064–75 doi:10.1007/s12350-018-1325-5 pmid:29943142
CrossRef PubMed

[151] Hop H,

[152] de Boer SA,

[153] Reijrink M, et al

[154] 41.↵
Cocker MS,
Spence JD,
Hammond R, et al
; Canadian Atherosclerosis Imaging Network (CAIN). [18F]-NaF PET/CT identifies active calcification in carotid plaque. JACC Cardiovasc Imaging 2017;10:486–88 doi:10.1016/j.jcmg.2016.03.005 pmid:27318719
FREE Full Text

[155] Cocker MS,

[156] Spence JD,

[157] Hammond R, et al

[158] 42.↵
Kaczynski J,
Sellers S,
Seidman MA, et al
. 18F-NaF PET/MRI for detection of carotid atheroma in acute neurovascular syndrome. Radiology 2022;305:137–48 doi:10.1148/radiol.212283 pmid:35670715
CrossRef PubMed

[159] Kaczynski J,

[160] Sellers S,

[161] Seidman MA, et al

[162] 43.↵
Mechtouff L,
Sigovan M,
Douek P, et al
. Simultaneous assessment of microcalcifications and morphological criteria of vulnerability in carotid artery plaque using hybrid (18)F-NaF PET/MRI. J Nucl Cardiol Off Cardiol 2022;29:1064–74 doi:10.1007/s12350-020-02400-0 pmid:33145738
CrossRef PubMed

[163] Mechtouff L,

[164] Sigovan M,

[165] Douek P, et al

[166] 44.↵
Vesey AT,
Jenkins WSA,
Irkle A, et al
. (18)F-fluoride and (18)F-fluorodeoxyglucose positron emission tomography after transient ischemic attack or minor ischemic stroke: case-control study. Circ Cardiovasc Imaging 2017;10:e004976 doi:10.1161/CIRCIMAGING.116.004976 pmid:28292859
Abstract/FREE Full Text

[167] Vesey AT,

[168] Jenkins WSA,

[169] Irkle A, et al

[170] 45.↵
Chen X,
Dang Y,
Hu H, et al
. Pericoronary adipose tissue attenuation assessed by dual-layer spectral detector computed tomography is a sensitive imaging marker of high-risk plaques. Quant Imaging Med Surg 2021;11:2093–103 doi:10.21037/qims-20-860 pmid:33936990
CrossRef PubMed

[171] Chen X,

[172] Dang Y,

[173] Hu H, et al

[174] 46.↵
Tan N,
Dey D,
Marwick TH, et al
. Pericoronary adipose tissue as a marker of cardiovascular risk: JACC review topic of the week. J Am Coll Cardiol 2023;81:913–23 doi:10.1016/j.jacc.2022.12.021 pmid:36858711
CrossRef PubMed

[175] Tan N,

[176] Dey D,

[177] Marwick TH, et al

[178] 47.↵
Ma R,
Ties D,
van Assen M, et al
. Towards reference values of pericoronary adipose tissue attenuation: impact of coronary artery and tube voltage in coronary computed tomography angiography. Eur Radiology 2020;30:6838–46 doi:10.1007/s00330-020-07069-0 pmid:32700017
CrossRef PubMed

[179] Ma R,

[180] Ties D,

[181] van Assen M, et al

[182] 48.↵
Cau R,
Gupta A,
Kooi ME, et al
. Pearls and pitfalls of carotid artery imaging: ultrasound, computed tomography angiography, and MR imaging. Radiology Clin North Am 2023;61:405–13 doi:10.1016/j.rcl.2023.01.001 pmid:36931758
CrossRef PubMed

[183] Cau R,

[184] Gupta A,

[185] Kooi ME, et al

[186] 49.↵
Cademartiri F,
Balestrieri A,
Cau R, et al
. Insight from imaging on plaque vulnerability: similarities and differences between coronary and carotid arteries—implications for systemic therapies. Cardiovasc Diagn Ther 2020;10:1150–62 doi:10.21037/cdt-20-528 pmid:32968666
CrossRef PubMed

[187] Cademartiri F,

[188] Balestrieri A,

[189] Cau R, et al

[190] 50.↵
Mayer M,
Borja AJ,
Hancin EC, et al
. Imaging atherosclerosis by PET, with emphasis on the role of FDG and NaF as potential biomarkers for this disorder. Front Physiol 2020;11:511391 doi:10.3389/fphys.2020.511391 pmid:33192540
CrossRef PubMed

[191] Mayer M,

[192] Borja AJ,

[193] Hancin EC, et al

[194] 51.↵
Verhagen SN,
Visseren FLJ
. Perivascular adipose tissue as a cause of atherosclerosis. Atherosclerosis 2011;214:3–10 doi:10.1016/j.atherosclerosis.2010.05.034 pmid:20646709
CrossRef PubMed

[195] Verhagen SN,

[196] Visseren FLJ

[197] 52.↵
Alkhalil M,
Edmond E,
Edgar L, et al
. The relationship of perivascular adipose tissue and atherosclerosis in the aorta and carotid arteries, determined by magnetic resonance imaging. Diab Vasc Dis Res 2018;15:286–93 doi:10.1177/1479164118757923 pmid:29446645
CrossRef PubMed

[198] Alkhalil M,

[199] Edmond E,

[200] Edgar L, et al

[201] 53.↵
Liu Y,
Xu L,
Gu Y, et al
. Impact of H-type hypertension on pericarotid adipose tissue and plaque characteristics based on computed tomography (CT) angiography: a propensity score matching study. Med Sci Monit 2021;27:e933351 doi:10.12659/MSM.933351 pmid:34857728
CrossRef PubMed

[202] Liu Y,

[203] Xu L,

[204] Gu Y, et al

[205] 54.↵
Liu Y,
Zhao Y,
Guo Z, et al
. Pericarotid fat stranding at computed tomography angiography: a marker of the short-term prognosis of acute ischemic stroke. J Comput Assist Tomogr 2024;48:311–16 doi:10.1097/RCT.0000000000001555 pmid:37876252
CrossRef PubMed

[206] Liu Y,

[207] Zhao Y,

[208] Guo Z, et al

[209] 55.↵
Liu X,
Wu F,
Jia X, et al
. Pericarotid adipose tissue computed tomography attenuation distinguishes different stages of carotid atherosclerotic disease: a cross-sectional study. Quant Imaging Med Surg 2023;13:8247–58 doi:10.21037/qims-23-454 pmid:38106246
CrossRef PubMed

[210] Liu X,

[211] Wu F,

[212] Jia X, et al

[213] 56.↵
Liu Y,
Zhao Y,
Guo Z, et al
. A novel predictive model based on pericarotid adipose tissue and lumen stenosis for stroke risk in patients with asymptomatic carotid stenosis. J Investig Med 2024;72:270–78 doi:10.1177/10815589241226728 pmid:38183206
CrossRef PubMed

[214] Liu Y,

[215] Zhao Y,

[216] Guo Z, et al

[217] 57.↵
Zhang DH,
Jin JL,
Zhu CF, et al
. Association between carotid artery perivascular fat density and cerebral small vessel disease. Aging (Albany NY) 2021;13:18839–51 doi:10.18632/aging.203327 pmid:34289452
CrossRef PubMed

[218] Zhang DH,

[219] Jin JL,

[220] Zhu CF, et al

[221] 58.↵
Hu X,
Chen J,
Fu H, et al
. Association between carotid artery perivascular fat density and embolic stroke of undetermined source. Front Neurol 2021;12:765962 doi:10.3389/fneur.2021.765962 pmid:35250789
CrossRef PubMed

[222] Hu X,

[223] Chen J,

[224] Fu H, et al

[225] 59.↵
Gencer ES,
Yilmaz E,
Arsava EM, et al
. Carotid artery perivascular adipose tissue density and response to intravenous tissue plasminogen activator in acute ischemic stroke. Angiology 2023;75:472–79 doi:10.1177/00033197231174654
CrossRef

[226] Gencer ES,

[227] Yilmaz E,

[228] Arsava EM, et al

[229] 60.↵
Lan Y,
Shang J,
Ma Y, et al
. A new predictor of coronary artery disease in acute ischemic stroke or transient ischemic attack patients: pericarotid fat density. Eur Radiology 2023;34:1667–76 doi:10.1007/s00330-023-10046-y
CrossRef

[230] Lan Y,

[231] Shang J,

[232] Ma Y, et al

[233] 61.↵
Hu J,
Hu N,
Hu T, et al
. Associations between preprocedural carotid artery perivascular fat density and early in-stent restenosis after carotid artery stenting. Heliyon 2023;9:e16220 doi:10.1016/j.heliyon.2023.e16220 pmid:37346364
CrossRef PubMed

[234] Hu J,

[235] Hu N,

[236] Hu T, et al

[237] 62.↵
Jin J,
Huang R,
Chen Q, et al
. Carotid artery perivascular adipose tissue density relates to recanalization and clinical outcome after mechanical thrombectomy. Front Aging Neurosci 2021;13:761248 doi:10.3389/fnagi.2021.761248 pmid:34899273
CrossRef PubMed

[238] Jin J,

[239] Huang R,

[240] Chen Q, et al

[241] 63.↵
Horimatsu T,
Kim HW,
Weintraub NL
. The role of perivascular adipose tissue in non-atherosclerotic vascular disease. Front Physiol 2017;8:969 doi:10.3389/fphys.2017.00969 pmid:29234289
CrossRef PubMed

[242] Horimatsu T,

[243] Kim HW,

[244] Weintraub NL

[245] 64.↵
Manka D,
Chatterjee TK,
Stoll LL, et al
. Transplanted perivascular adipose tissue accelerates injury-induced neointimal hyperplasia: role of monocyte chemoattractant protein-1. Arterioscler Thromb Vasc Biol 2014;34:1723–30 doi:10.1161/ATVBAHA.114.303983 pmid:24947528
Abstract/FREE Full Text

[246] Manka D,

[247] Chatterjee TK,

[248] Stoll LL, et al

[249] 65.↵
Saw J
. Spontaneous coronary artery dissection. Can J Cardiol 2013;29:1027–33 doi:10.1016/j.cjca.2012.12.018 pmid:23498840
CrossRef PubMed

[250] Saw J

[251] 66.↵
Adlam D,
Alfonso F,
Maas A, et al
; Writing Committee. European Society of Cardiology, acute cardiovascular care association, SCAD study group: a position paper on spontaneous coronary artery dissection. Eur Heart J 2018;39:3353–68 doi:10.1093/eurheartj/ehy080 pmid:29481627
CrossRef PubMed

[252] Adlam D,

[253] Alfonso F,

[254] Maas A, et al

[255] 67.↵
Hayes SN,
Kim ESH,
Saw J, et al
; American Heart Association Council on Peripheral Vascular Disease; Council on Clinical Cardiology; Council on Cardiovascular and Stroke Nursing; Council on Genomic and Precision Medicine; and Stroke Council. Spontaneous coronary artery dissection: current state of the science: a scientific statement from the American Heart Association. Circulation 2018;137:e523–57 doi:10.1161/CIR.0000000000000564 pmid:29472380
Abstract/FREE Full Text

[256] Hayes SN,

[257] Kim ESH,

[258] Saw J, et al

[259] 68.↵
Cheng K,
Lin A,
Stecher X, et al
. Association between spontaneous internal carotid artery dissection and perivascular adipose tissue attenuation on computed tomography angiography. Int J Stroke 2023;18:829–38 doi:10.1177/17474930231158538 pmid:36748981
CrossRef PubMed

[260] Cheng K,

[261] Lin A,

[262] Stecher X, et al

[263] 69.↵
Wall C,
Huang Y,
Le EV, et al
. Pericoronary and periaortic adipose tissue density are associated with inflammatory disease activity in Takayasu arteritis and atherosclerosis. Eur Heart J Open 2021;1:oeab019 doi:10.1093/ehjopen/oeab019 pmid:34661196
CrossRef PubMed

[264] Wall C,

[265] Huang Y,

[266] Le EV, et al

[267] 70.↵
Zhou R,
Fenster A,
Xia Y, et al
. Deep learning-based carotid media-adventitia and lumen-intima boundary segmentation from three-dimensional ultrasound images. Med Phys 2019;46:3180–93 doi:10.1002/mp.13581 pmid:31071228
CrossRef PubMed

[268] Zhou R,

[269] Fenster A,

[270] Xia Y, et al

[271] 71.↵
Zhou T,
Tan T,
Pan X, et al
. Fully automatic deep learning trained on limited data for carotid artery segmentation from large image volumes. Quant Imaging Med Surg 2021;11:67–83 doi:10.21037/qims-20-286 pmid:33392012
CrossRef PubMed

[272] Zhou T,

[273] Tan T,

[274] Pan X, et al

[275] 72.↵
dos Santos FLC,
Joutsen A,
Paci M, et al
. Automatic detection of carotid arteries in computed tomography angiography: a proof of concept protocol. Int J Cardiovasc Imaging 2016;32:1299–310 doi:10.1007/s10554-016-0880-6 pmid:27142430
CrossRef PubMed

[276] dos Santos FLC,

[277] Joutsen A,

[278] Paci M, et al

[279] 73.↵
Oikonomou EK,
Antonopoulos AS,
Schottlander D, et al
. Standardized measurement of coronary inflammation using cardiovascular computed tomography: integration in clinical care as a prognostic medical device. Cardiovasc Res 2021;117:2677–90 doi:10.1093/cvr/cvab286 pmid:34450625
CrossRef PubMed

[280] Oikonomou EK,

[281] Antonopoulos AS,

[282] Schottlander D, et al

[283] 74.↵
Cau R,
Flanders A,
Mannelli L, et al
. Artificial intelligence in computed tomography plaque characterization: a review. Eur J Radiology 2021;140:109767 doi:10.1016/j.ejrad.2021.109767 pmid:34000598
CrossRef PubMed

[284] Cau R,

[285] Flanders A,

[286] Mannelli L, et al

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American Journal of Neuroradiology

Pericarotid Fat as a Marker of Cerebrovascular Risk

SUMMARY:

ABBREVIATIONS:

PATHOPHYSIOLOGY OF PERIVASCULAR CAROTID FAT

NONINVASIVE EVALUATION OF PCF

Current Limitations of Noninvasive Imaging Modalities

ASSOCIATION WITH FEATURES OF PLAQUE VULNERABILITY

ASSOCIATION WITH CEREBROVASCULAR ISCHEMIC EVENTS

ASSOCIATION WITH POSTOPERATIVE INTERVENTIONAL COMPLICATION/OUTCOME

ASSOCIATION WITH NONATHEROSCLEROTIC CAROTID VASCULAR DISEASE

FUTURE DIRECTION: ARTIFICIAL INTELLIGENCE AND RADIOMICS

CONCLUSIONS

Footnotes

References

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Search

Pericarotid Fat as a Marker of Cerebrovascular Risk

SUMMARY:

ABBREVIATIONS:

PATHOPHYSIOLOGY OF PERIVASCULAR CAROTID FAT

NONINVASIVE EVALUATION OF PCF

Current Limitations of Noninvasive Imaging Modalities

ASSOCIATION WITH FEATURES OF PLAQUE VULNERABILITY

ASSOCIATION WITH CEREBROVASCULAR ISCHEMIC EVENTS

ASSOCIATION WITH POSTOPERATIVE INTERVENTIONAL COMPLICATION/OUTCOME

ASSOCIATION WITH NONATHEROSCLEROTIC CAROTID VASCULAR DISEASE

FUTURE DIRECTION: ARTIFICIAL INTELLIGENCE AND RADIOMICS

CONCLUSIONS

Footnotes

References

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