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Perivascular Epicardial Fat Stranding at Coronary CT Angiography: A Marker of Acute Plaque Rupture and Spontaneous Coronary Artery Dissection.

ABSTRACT: Purpose To evaluate the frequency and implications of perivascular fat stranding on coronary computed tomography (CT) angiograms obtained for suspected acute coronary syndrome (ACS). Materials and Methods This retrospective registry study was approved by the institutional review board. The authors reviewed the medical records and images of 1403 consecutive patients (796 men, 607 women; mean age, 52.8 years) who underwent coronary CT angiography at the emergency department from February 2012 to March 2016. Fat attenuation, length and number of circumferential quadrants of the affected segment, and attenuation values in the unaffected epicardial and subcutaneous fat were measured. "Cases" were defined as patients with perivascular fat stranding. Patients with significant stenosis but without fat stranding were considered control subjects. Baseline imaging characteristics, ACS frequency, and results of subsequent downstream testing were compared between cases and control subjects by using two-sample t, Mann-Whitney U, and Fisher tests. Results Perivascular fat stranding was seen in 11 subjects, nine with atherosclerotic lesions and two with spontaneous coronary artery dissections, with a mean fat stranding length of 19.2 mm and circumferential extent averaging 2.9 quadrants. The mean attenuation of perivascular fat stranding, normal epicardial fat, and normal subcutaneous fat was 17, -93.2, and -109.3 HU, respectively (P < .001). Significant differences (P < .05) between cases and control subjects included lower Agatston score, presence of wall motion abnormality, and initial elevation of serum troponin level. ACS frequency was 45.4% in cases and 3.8% in control subjects (P = .001). Conclusion Recognition of perivascular fat stranding may be a helpful additional predictor of culprit lesion and marker of risk for ACS in patients with significant stenosis or spontaneous coronary artery dissection. ^© RSNA, 2018 Online supplemental material is available for this article.

SUBMITTER: Hedgire S

PROVIDER: S-EPMC8382040 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Purpose To assess the relationship between total, calcified, and noncalcified coronary plaque burdens throughout the entire coronary vasculature at coronary computed tomographic (CT) angiography in relationship to cardiovascular risk factors in asymptomatic individuals with low-to-moderate risk. Materials and Methods This HIPAA-compliant study had institutional review board approval, and written informed consent was obtained. Two hundred two subjects were recruited to an ongoing prospective study designed to evaluate the effect of HMG-CoA reductase inhibitors on atherosclerosis. Eligible subjects were asymptomatic individuals older than 55 years who were eligible for statin therapy. Coronary CT angiography was performed by using a 320-detector row scanner. Coronary wall thickness and plaque were evaluated in all epicardial coronary arteries greater than 2 mm in diameter. Images were analyzed by using dedicated software involving an adaptive lumen attenuation algorithm. Total plaque index (calcified plus noncalcified plaque) was defined as plaque volume divided by vessel length. Multivariable regression analysis was performed to determine the relationship between risk factors and plaque indexes. Results The mean age of the subjects was 65.5 years ± 6.9 (standard deviation) (36% women), and the median coronary artery calcium (CAC) score was 73 (interquartile range, 1-434). The total coronary plaque index was higher in men than in women (42.06 mm(2) ± 9.22 vs 34.33 mm(2) ± 8.35; P < .001). In multivariable analysis controlling for all risk factors, total plaque index remained higher in men than in women (by 5.01 mm(2); P = .03) and in those with higher simvastatin doses (by 0.44 mm(2)/10 mg simvastatin dose equivalent; P = .02). Noncalcified plaque index was positively correlated with systolic blood pressure (β = 0.80 mm(2)/10 mm Hg; P = .03), diabetes (β = 4.47 mm(2); P = .03), and low-density lipoprotein (LDL) cholesterol level (β = 0.04 mm(2)/mg/dL; P = .02); the association with LDL cholesterol level remained significant (P = .02) after additional adjustment for the CAC score. Conclusion LDL cholesterol level, systolic blood pressure, and diabetes were associated with noncalcified plaque burden at coronary CT angiography in asymptomatic individuals with low-to-moderate risk. (©) RSNA, 2015 Online supplemental material is available for this article.

Project description:PurposeTo assess the effect of ultra-high-resolution coronary CT angiography (CCTA) with photon-counting detector (PCD) CT on quantitative coronary plaque characterization.Materials and methodsIn this IRB-approved study, 22 plaques of 20 patients (7 women; mean age 77 ± 8 years, mean body mass index 26.1 ± 3.6 kg/m2) undergoing electrocardiography (ECG)-gated ultra-high-resolution CCTA with PCD-CT were included. Images were reconstructed with a smooth (Bv40) and a sharp (Bv64) vascular kernel, with quantum iterative reconstruction (strength level 4), and using a slice thickness of 0.6, 0.4, and 0.2 mm, respectively (field-of-view 200 mm × 200 mm, matrix size 512 × 512 pixels). Reconstructions with the Bv40 kernel and slice thickness of 0.6 mm served as the reference standard. After identification of a plaque in coronary arteries with a vessel diameter ≥2 mm, plaque composition was determined using a dedicated, semi-automated plaque quantification software. Total plaque, calcified, fibrotic, and lipid-rich plaque components were quantified in all datasets.ResultsMedian plaque volume was highest (23.5 mm3, interquartiles 17.9-34.3 mm3) for reconstructions with the reference standard and lowest for ultra-high-resolution reconstructions with a slice thickness of 0.2 mm and the Bv64 kernel (18.1 mm3, interquartiles 14.1-25.8 mm3, p < 0.001). Reconstructions with the reference standard showed largest calcified (85.1%, interquartiles 76.4-91.1%) and smallest lipid-rich plaque components (0.5%, interquartiles 0.0-1.5%). Smallest calcified plaque components (75.2%, interquartiles 69.9-80.8%) and largest lipid-rich components (6.7%, interquartiles 5.1-8.4%) were found for ultra-high-resolution reconstructions with a slice thickness of 0.2 mm and the Bv64 kernel. At an identical slice thickness, volume of calcified components was always lower, and volume of lipid-rich components was always higher for reconstructions with the Bv64 kernel compared with reconstructions with the Bv40 kernel (all, p < 0.001).ConclusionThis patient study indicates significant differences of ultra-high-resolution scanning with PCD-CT on quantitative coronary plaque characterization. Reduced blooming artifacts may allow improved visualization of fibrotic and lipid-rich plaque components with the ultra-high-resolution mode of PCD-CT.

Project description:BackgroundCoronary inflammation induces dynamic changes in the balance between water and lipid content in perivascular adipose tissue (PVAT), as captured by perivascular Fat Attenuation Index (FAI) in standard coronary CT angiography (CCTA). However, inflammation is not the only process involved in atherogenesis and we hypothesized that additional radiomic signatures of adverse fibrotic and microvascular PVAT remodelling, may further improve cardiac risk prediction.Methods and resultsWe present a new artificial intelligence-powered method to predict cardiac risk by analysing the radiomic profile of coronary PVAT, developed and validated in patient cohorts acquired in three different studies. In Study 1, adipose tissue biopsies were obtained from 167 patients undergoing cardiac surgery, and the expression of genes representing inflammation, fibrosis and vascularity was linked with the radiomic features extracted from tissue CT images. Adipose tissue wavelet-transformed mean attenuation (captured by FAI) was the most sensitive radiomic feature in describing tissue inflammation (TNFA expression), while features of radiomic texture were related to adipose tissue fibrosis (COL1A1 expression) and vascularity (CD31 expression). In Study 2, we analysed 1391 coronary PVAT radiomic features in 101 patients who experienced major adverse cardiac events (MACE) within 5 years of having a CCTA and 101 matched controls, training and validating a machine learning (random forest) algorithm (fat radiomic profile, FRP) to discriminate cases from controls (C-statistic 0.77 [95%CI: 0.62-0.93] in the external validation set). The coronary FRP signature was then tested in 1575 consecutive eligible participants in the SCOT-HEART trial, where it significantly improved MACE prediction beyond traditional risk stratification that included risk factors, coronary calcium score, coronary stenosis, and high-risk plaque features on CCTA (Δ[C-statistic] = 0.126, P < 0.001). In Study 3, FRP was significantly higher in 44 patients presenting with acute myocardial infarction compared with 44 matched controls, but unlike FAI, remained unchanged 6 months after the index event, confirming that FRP detects persistent PVAT changes not captured by FAI.ConclusionThe CCTA-based radiomic profiling of coronary artery PVAT detects perivascular structural remodelling associated with coronary artery disease, beyond inflammation. A new artificial intelligence (AI)-powered imaging biomarker (FRP) leads to a striking improvement of cardiac risk prediction over and above the current state-of-the-art.

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Perivascular Epicardial Fat Stranding at Coronary CT Angiography: A Marker of Acute Plaque Rupture and Spontaneous Coronary Artery Dissection.

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