Pericoronary Adipose Tissue Research Articles

Use of coronary artery calcium score and coronary CT angiography to guide cardiovascular prevention and treatment.

Currently, cardiovascular risk stratification to guide preventive therapy relies on clinical scores based on cardiovascular risk factors. However, the discriminative power of these scores is relatively modest. The use of coronary artery calcium score (CACS) and coronary CT angiography (CCTA) has surfaced as methods for enhancing the estimation of risk and potentially providing insights for personalized treatment in individual patients. CACS improves overall cardiovascular risk prediction and may be used to improve the yield of statin therapy in primary prevention, and possibly identify patients with a favorable risk/benefit relationship for antiplatelet therapies. CCTA holds promise to guide anti-atherosclerotic therapies and to monitor individual response to these treatments by assessing individual plaque features, quantifying total plaque volume and composition, and assessing peri-coronary adipose tissue. In this review, we aim to summarize current evidence regarding the use of CACS and CCTA for guiding lipid-lowering and antiplatelet therapy and discuss the possibility of using plaque burden and plaque phenotyping to monitor response to anti-atherosclerotic therapies.

Impact of Pericoronary Adipose Tissue Attenuation on Periprocedural Myocardial Injury in Patients With Chronic Coronary Syndrome.

Perivascular inflammation contributes to the development of atherosclerosis and microcirculatory dysfunction. Pericoronary adipose tissue (PCAT) attenuation, measured by coronary computed tomography angiography, is a potential indicator of coronary inflammation. However, the relationship between PCAT attenuation, microcirculatory dysfunction, and periprocedural myocardial injury (PMI) remains unclear. Patients with chronic coronary syndrome who underwent coronary computed tomography angiography before percutaneous coronary intervention were retrospectively identified. PCAT attenuation and adverse plaque characteristics were assessed using coronary computed tomography angiography. The extent of microcirculatory dysfunction was evaluated using the angio-based index of microcirculatory resistance before and after percutaneous coronary intervention. Overall, 125 consecutive patients were included, with 50 experiencing PMI (PMI group) and 75 without PMI (non-PMI group). Multivariable analysis showed that older age, higher angio-based index of microcirculatory resistance, presence of adverse plaque characteristics, and higher lesion-based PCAT attenuation were independently associated with PMI occurrence (odds ratio [OR], 1.07 [95% CI, 1.01-1.13]; P=0.02; OR, 1.06 [95% CI, 1.00-1.12]; P=0.04; OR, 6.62 [95% CI, 2.13-20.6]; P=0.001; and OR, 2.89 [95% CI, 1.63-5.11]; P<0.001, respectively). High PCAT attenuation was correlated with microcirculatory dysfunction before and after percutaneous coronary intervention and its exacerbation during percutaneous coronary intervention. Adding lesion-based PCAT attenuation to the presence of adverse plaque characteristics improved the discriminatory and reclassification ability in predicting PMI. Adding PCAT attenuation at the culprit lesion level to coronary computed tomography angiography-derived adverse plaque characteristics may provide incremental benefit in identifying patients at risk of PMI. Our results highlight the importance of microcirculatory dysfunction in PMI development, particularly in the presence of lesions with high PCAT attenuation. URL: https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000057722; Unique identifier: UMIN000050662.

Coronary inflammation on chest computed tomography and COVID-19 mortality.

The main factors associated with coronavirus disease-19 (COVID-19) mortality are age, comorbidities, pattern of inflammatory response, and SARS-CoV-2 lineage involved in infection. However, the clinical course of the disease is extremely heterogeneous, and reliable biomarkers predicting adverse prognosis are lacking. Our aim was to elucidate the prognostic role of a novel marker of coronary artery disease inflammation, peri-coronary adipose tissue attenuation (PCAT), available from high-resolution chest computed tomography (HRCT) in COVID-19 patients with severe disease requiring hospitalization. Two distinct groups of patients were admitted to Parma University Hospital in Italy with COVID-19 in March 2020 and March 2021 (first- and third-wave peaks of the COVID-19 pandemic in Italy, with the prevalence of wild-type and B.1.1.7 SARS-CoV-2 lineage, respectively) were retrospectively enrolled. The primary endpoint was in-hospital mortality. Demographic, clinical, laboratory, HRCT data, and coronary artery HRCT features (coronary calcium score and PCAT attenuation) were collected to show which variables were associated with mortality. Among the 769 patients enrolled, 555 (72%) were discharged alive, and 214 (28%) died. In multivariable logistic regression analysis age (p< 0.001), number of chronic illnesses (p< 0.001), smoking habit (p= 0.006), P/F ratio (p= 0.001), platelet count (p= 0.002), blood creatinine (p< 0.001), non-invasive mechanical ventilation (p< 0.001), HRCT visual score (p< 0.001), and PCAT (p <0.001), but not the calcium score, were independently associated with in-hospital mortality. Coronary inflammation, measured with PCAT on non-triggered HRCT, appeared to be independently associated with higher mortality in patients with severe COVID-19, while the pre-existent coronary atherosclerotic burden was not associated with adverse outcomes after adjustment for covariates. The current study demonstrates that a relatively simple measurement, peri-coronary adipose tissue attenuation (PCAT), available ex-post from standard high-resolution computed tomography, is strongly and independently associated with in-hospital mortality. • Coronary inflammation can be measured by the attenuation of peri-coronary adipose tissue (PCAT) on high-resolution CT (HRCT) without contrast media. • PCAT is strongly and independently associated with in-hospital mortality in SARS-CoV-2 patients. • PCAT might be considered an independent prognostic marker in COVID-19 patients if confirmed in other studies.

Advanced CT measures of coronary artery disease with intermediate stenosis in patients with severe aortic valve stenosis

BackgroundCoronary artery disease (CAD) and severe aortic valve stenosis (AS) frequently coexist. While pre-transcatheter aortic valve replacement (TAVR) computed tomography angiography (CTA) allows to rule out obstructive CAD, interpreting hemodynamic significance of intermediate stenoses is challenging. This study investigates the incremental value of CT-derived fractional flow reserve (CT-FFR), quantitative coronary plaque characteristics (e.g., stenosis degree, plaque volume, and composition), and peri-coronary adipose tissue (PCAT) density to detect hemodynamically significant lesions among those with AS and CAD.Materials and methodsWe included patients with severe AS and intermediate coronary lesions (20–80% diameter stenosis) who underwent pre-TAVR CTA and invasive coronary angiogram (ICA) with resting full-cycle ratio (RFR) assessment between 08/16 and 04/22. CTA image analysis included assessment of CT-FFR, quantitative coronary plaque analysis, and PCAT density. Coronary lesions with RFR ≤ 0.89 indicated hemodynamic significance as reference standard.ResultsOverall, 87 patients (age 77.9 ± 7.4 years, 38% female) with 95 intermediate coronary artery lesions were included. CT-FFR showed good discriminatory capacity (area under receiver operator curve (AUC) = 0.89, 95% confidence interval (CI) 0.81–0.96, p < 0.001) to identify hemodynamically significant lesions, superior to anatomical assessment, plaque morphology, and PCAT density. Plaque composition and PCAT density did not differ between lesions with and without hemodynamic significance. Univariable and multivariable analyses revealed CT-FFR as the only predictor for functionally significant lesions (odds ratio 1.28 (95% CI 1.17–1.43), p < 0.001). Overall, CT-FFR ≤ 0.80 showed diagnostic accuracy, sensitivity, and specificity of 88.4% (95%CI 80.2–94.1), 78.5% (95%CI 63.2–89.7), and 96.2% (95%CI 87.0–99.5), respectively.ConclusionCT-FFR was superior to CT anatomical, plaque morphology, and PCAT assessment to detect functionally significant stenoses in patients with severe AS.Clinical relevance statementCT-derived fractional flow reserve in patients with severe aortic valve stenosis may be a useful tool for non-invasive hemodynamic assessment of intermediate coronary lesions, while CT anatomical, plaque morphology, and peri-coronary adipose tissue assessment have no incremental or additional benefit. These findings might help to reduce pre-transcatheter aortic valve replacement invasive coronary angiogram.Key Points• Interpreting the hemodynamic significance of intermediate coronary stenoses is challenging in pre-transcatheter aortic valve replacement CT.• CT-derived fractional flow reserve (CT-FFR) has a good discriminatory capacity in the identification of hemodynamically significant coronary lesions.• CT-derived anatomical, plaque morphology, and peri-coronary adipose tissue assessment did not improve the diagnostic capability of CT-FFR in the hemodynamic assessment of intermediate coronary stenoses.

Pericoronary adipose tissue attenuation in patients with acute aortic dissection based on coronary computed tomography angiography.

Periaortic fat is associated with coronary disease. Thus, it was hypothesized that the inflammation associated with acute aortic dissection (AAD) spreads to pericoronary adipose tissue (PCAT) via thoracic periaortic fat. Pericoronary adipose tissue attenuation (PCATa) serves as a marker for inflammation of perivascular adipose tissue (PVAT). This study sought to examine PCATa in individuals diagnosed with AAD. Consecutive patients with chest pain from May 2020 to September 2022 were prospectively enrolled in this study and underwent coronary computed tomography angiography (CCTA) and/or aorta computed tomography angiography (CTA). Based on the results of the CTA, the patients were divided into the following two groups: (I) the AAD group; and (II) the non-AAD group. PCATa of the right coronary angiography (RCA), left anterior descending (LAD), and left circumflex (LCx) was quantified for each patient using semi-automated software. The PCATa values were compared between the AAD and non-AAD patients according to the atherosclerosis of the coronary arteries. Similarly, the PCATa values of the AAD patients were compared between the preoperative and postoperative steady states. A total of 136 patients (42 female, 94 male; mean age: 63.3±11.9 years) were divided into the two groups according to the presence of aortic dissection on CTA. The RCAPCATa, LADPCATa, and LCxPCATa values were significantly higher in the AAD subjects than the non-AAD subjects, regardless of the presence or absence of atherosclerosis in the coronary arteries [-85.1±9.3 vs. -92.9±10.0 Hounsfield unit (HU); -83.2±7.4 vs. -89.9±9.1 HU; -77.5±8.4 vs. -85.6±7.9 HU, all P<0.001). The preoperative RCAPCATa, LADPCATa, and LCxPCATa values were higher in the AAD patients than the postoperative steady-state patients (-82.9±8.7 vs. -97.6±8.8 HU; -79.8±7.6 vs. -92.8±6.8 HU; -74.6±7.1 vs. -87.7±6.9 HU, all P<0.001). According to the multivariable logistic regression analysis, high RCAPCATa and LADPCATa values were associated with AAD regardless of the degree of stenosis [odds ratio (OR) =0.014; 95% confidence interval (CI): 0.001-0.177; P=0.001 and OR =0.010; 95% CI: 0.001-0.189; P=0.002]. PCATa on computed tomography was increased in patients with AAD regardless of the presence or absence of coronary artery disease (CAD). This suggests that vascular inflammation is present in AAD independent of CAD. Further research should be conducted to investigate the potential of this imaging biomarker to predict AAD and monitor patients' responses to therapies for AAD.

Higher Noncalcified Plaque Volume Is Associated With Increased Plaque Vulnerability and Vascular Inflammation.

Recently, it was reported that noncalcified plaque (NCP) volume was an independent predictor for cardiac events. Pericoronary adipose tissue (PCAT) attenuation is a marker of vascular inflammation and has been associated with increased cardiac mortality. The aim of this study was to evaluate the relationships between NCP volume, plaque vulnerability, and PCAT attenuation. Patients who underwent preintervention coronary computed tomography angiography and optical coherence tomography were enrolled. Plaque volume was measured by computed tomography angiography, plaque vulnerability by optical coherence tomography, and the level of coronary inflammation by PCAT attenuation. The plaques were divided into 2 groups of high or low NCP volume based on the median NCP volume. Among 704 plaques in 454 patients, the group with high NCP volume had a higher prevalence of lipid-rich plaque (87.2% versus 75.9%; P<0.001), thin-cap fibroatheroma (38.1% versus 20.7%; P<0.001), macrophage (77.8% versus 63.4%; P<0.001), microvessel (58.2% versus 42.9%; P<0.001), and cholesterol crystal (42.0% versus 26.7%; P<0.001) than the group with low NCP plaque volume. The group with high NCP volume also had higher PCAT attenuation than the group with low NCP volume (-69.6±10.0 versus -73.5±10.6 Hounsfield unit; P<0.001). In multivariable analysis, NCP volume was significantly associated with thin-cap fibroatheroma and high PCAT attenuation. In the analysis of the combination of PCAT attenuation and NCP volume, the prevalence of thin-cap fibroatheroma was the highest in the high PCAT attenuation and high NCP volume group and the lowest in the low PCAT attenuation and low NCP volume group. Higher NCP volume was associated with higher plaque vulnerability and vascular inflammation. The combination of PCAT attenuation and NCP volume may help identify plaque vulnerability noninvasively. URL: https://www.clinicaltrials.gov; Unique identifier: NCT04523194.

CT Pericoronary Adipose Tissue Density Predicts Coronary Allograft Vasculopathy And Adverse Clinical Outcomes After Cardiac Transplantation

CT Pericoronary Adipose Tissue Density Predicts Coronary Allograft Vasculopathy And Adverse Clinical Outcomes After Cardiac Transplantation

Association of mean pericoronary adipose tissue attenuation with different demographic factors in a subgroup of patients without coronary artery disease stratified by sex, body mass index, and age.

In patients without coronary artery disease (CAD), few studies have evaluated the association between mean pericoronary adipose tissue attenuation (PCATMA) and patient-based demographic factors, for example, age or sex. Therefore, the purpose of this study is to investigate the association between PCATMA and various demographic factors in patients without CAD. In this case-control study, the 806 patients who underwent coronary computed tomography angiography and were not diagnosed with CAD between July 2020 and July 2022 were retrospectively enrolled. Their PCATMA values of the proximal right coronary artery were measured automatically. Patients without CAD were stratified according to sex, body mass index (BMI), and age, and the relationship between PCATMA and different clinical characteristics was explored using Fisher's exact test or Chi-squared test and independent t-tests or Wilcoxon Mann-Whitney U tests. Compared to non-smoking women [-88.00 (-95.00, -81.00) HU], women who smoked [-84.00 (-94.00, -78.00) HU, P=0.037] had higher PCATMA values and a positive correlation with PCATMA (rs=0.101, P=0.036). Compared to non-hypertensive patients with BMI ≥24.91 kg/m2 [-87.00 (-95.00, -81.00) HU], hypertensive patients with BMI ≥24.91 kg/m2 [-84.00 (-92.00, -78.00) HU, P=0.004] had higher PCATMA values, and a positive correlation with PCATMA (rs=0.144, P=0.004). In a subgroup of patients without CAD stratified by sex, BMI, and age, PCATMA values were all higher in patients with dyslipidemia (women, men, BMI ≥24.91 kg/m2, BMI <24.91 kg/m2, age ≥55 years, and age <55 years: -82.00, -82.00, -81.50, -82.00, -81.00 and -83.50 HU, respectively) than in those without dyslipidemia (-89.00, -89.00, -89.00, -90.00, -90.00 and -88.00 HU, respectively; all P<0.001) and showed a positive relationship (rs=0.328, 0.339, 0.342, 0.326, 0.367, and 0.298, respectively; all P<0.001). Higher PCATMA attenuation values were observed in patients with dyslipidemia, smoking women, and hypertensive patients with BMI ≥24.91 kg/m2, suggesting that PCATMA values can be used to detect patients at high risk for future events with CAD even if they do not currently have atherosclerosis.

Hybrid model of CT-fractional flow reserve, pericoronary fat attenuation index and radiomics for predicting the progression of WMH: a dual-center pilot study.

To develop and validate a hybrid model incorporating CT-fractional flow reserve (CT-FFR), pericoronary fat attenuation index (pFAI), and radiomics signatures for predicting progression of white matter hyperintensity (WMH). A total of 226 patients who received coronary computer tomography angiography (CCTA) and brain magnetic resonance imaging from two hospitals were divided into a training set (n = 116), an internal validation set (n = 30), and an external validation set (n = 80). Patients who experienced progression of WMH were identified from subsequent MRI results. We calculated CT-FFR and pFAI from CCTA images using semi-automated software, and segmented the pericoronary adipose tissue (PCAT) and myocardial ROI. A total of 1,073 features were extracted from each ROI, and were then refined by Elastic Net Regression. Firstly, different machine learning algorithms (Logistic Regression [LR], Support Vector Machine [SVM], Random Forest [RF], k-nearest neighbor [KNN] and eXtreme Gradient Gradient Boosting Machine [XGBoost]) were used to evaluate the effectiveness of radiomics signatures for predicting WMH progression. Then, the optimal machine learning algorithm was used to compare the predictive performance of individual and hybrid models based on independent risk factors of WMH progression. Receiver operating characteristic (ROC) curve analysis, calibration and decision curve analysis were used to evaluate predictive performance and clinical value of the different models. CT-FFR, pFAI, and radiomics signatures were independent predictors of WMH progression. Based on the machine learning algorithms, the PCAT signatures led to slightly better predictions than the myocardial signatures and showed the highest AUC value in the XGBoost algorithm for predicting WMH progression (AUC: 0.731 [95% CI: 0.603-0.838] vs.0.711 [95% CI: 0.584-0.822]). In addition, pFAI provided better predictions than CT-FFR (AUC: 0.762 [95% CI: 0.651-0.863] vs. 0.682 [95% CI: 0.547-0.799]). A hybrid model that combined CT-FFR, pFAI, and two radiomics signatures provided the best predictions of WMH progression [AUC: 0.893 (95%CI: 0.815-0.956)]. pFAI was more effective than CT-FFR, and PCAT signatures were more effective than myocardial signatures in predicting WMH progression. A hybrid model that combines pFAI, CT-FFR, and two radiomics signatures has potential use for identifying WMH progression.

Lesion-specific pericoronary adipose tissue CT attenuation improves risk prediction of major adverse cardiovascular events in coronary artery disease.

To determine whether lesion-specific pericoronary adipose tissue CT attenuation (PCATa) is superior to PCATa around the proximal right coronary artery (PCATa-RCA) and left anterior descending artery (PCATa-LAD) for major adverse cardiovascular events (MACE) prediction in coronary artery disease (CAD). Six hundred and eight CAD patients who underwent coronary CTA from January 2014 to December 2018 were retrospectively included, with clinical risk factors, plaque features, lesion-specific PCATa, PCATa-RCA, and PCATa-LAD collected. MACE was defined as cardiovascular death, non-fatal myocardial infarction, unplanned revascularization, and hospitalization for unstable angina. Four models were established, encapsulating traditional factors (Model A), traditional factors and PCATa-RCA (Model B), traditional factors and PCATa-LAD (Model C), and traditional factors and lesion-specific PCATa (Model D). Prognostic performance was evaluated with C-statistic, area under receiver operator characteristic curve (AUC), and net reclassification index (NRI). Lesion-specific PCATa was an independent predictor for MACE (adjusted hazard ratio = 1.108, P < .001). The C-statistic increased from 0.750 for model A to 0.762 for model B (P = .078), 0.773 for model C (P = .046), and 0.791 for model D (P = .005). The AUC increased from 0.770 for model A to 0.793 for model B (P = .027), 0.793 for model C (P = .387), and 0.820 for model D (P = .019). Compared with model A, the NRIs for models B, C, and D were 0.243 (-0.323 to 0.792, P = .392), 0.428 (-0.012 to 0.835, P = .048), and 0.708 (0.152-1.016, P = .001), respectively. Lesion-specific PCATa improves risk prediction of MACE in CAD, which is better than PCATa-RCA and PCATa-LAD. Lesion-specific PCATa was superior to PCATa-RCA and PCATa-LAD for MACE prediction.

Differences in the Fat Attenuation Index Ratio of Pericoronary Adipose Tissue And Aortic Root Epicardial Adipose Tissue in Various Plaques.

The fat attenuation index (FAI) of pericoronary adipose tissue is associated with coronary inflammatory reactions. This study aimed to analyze the difference in the FAI ratio between pericoronary adipose tissue volume and aortic root epicardial adipose tissue volume (AO-EATV) using computed tomography (CT) in various plaques. In total, 645 coronary artery CT angiogram images from 215 patients were collected. The types and number of coronary plaques were recorded, and the plaque volume and pericoronary FAI of each branch were compared between the groups. The ratio of the FAI in branches with or without plaques to the AO-EATV was determined and statistically analyzed between the groups. No significant difference in the plaque volume among the left anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA) (P > 0.05) as well as in the FAI was observed among various plaque groups (P > 0.05). FAI[LAD]/AO-EATV was in the following order: noncalcified plaques (0.70 ± 0.06) < mixed plaques (0.72 ± 0.06) < calcified plaques (0.73 ± 0.08) < no plaques (0.74 ± 0.07); FAI[LCX]/AOEATV was in the following order: noncalcified plaques (0.71 ± 0.06) < mixed plaques (0.72 ± 0.08) < calcified plaques (0.73 ± 0.09) < no plaques (0.74 ± 0.06); and FAI[RCA]/AO-EATV was in the following order: noncalcified plaques (0.71 ± 0.06) < mixed plaques (0.73 ± 0.07) < calcified plaques (0.74 ± 0.07) < no plaques (0.75 ± 0.09); the differences were statistically significant in each group (P = 0.041, 0.043, and 0.028, respectively). Compared to simply comparing FAI, FAI/AO-EATV varied in the coronary arteries in various plaque groups. FAI/AO-EATV was lower in noncalcified or mixed plaques and was associated with coronary inflammatory reactions.

Epicardial and Pericoronary Adipose Tissue, Coronary Inflammation, and Acute Coronary Syndromes

Vascular inflammation is recognized as the primary trigger of acute coronary syndrome (ACS). However, current noninvasive methods are not capable of accurately detecting coronary inflammation. Epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT), in addition to their role as an energy reserve system, have been found to contribute to the development and progression of coronary artery calcification, inflammation, and plaque vulnerability. They also participate in the vascular response during ischemia, sympathetic stimuli, and arrhythmia. As a result, the evaluation of EAT and PCAT using imaging techniques such as computed tomography (CT), cardiac magnetic resonance (CMR), and nuclear imaging has gained significant attention. PCAT-CT attenuation, which measures the average CT attenuation in Hounsfield units (HU) of the adipose tissue, reflects adipocyte differentiation/size and leukocyte infiltration. It is emerging as a marker of tissue inflammation and has shown prognostic value in coronary artery disease (CAD), being associated with plaque development, vulnerability, and rupture. In patients with acute myocardial infarction (AMI), an inflammatory pericoronary microenvironment promoted by dysfunctional EAT/PCAT has been demonstrated, and more recently, it has been associated with plaque rupture in non-ST-segment elevation myocardial infarction (NSTEMI). Endothelial dysfunction, known for its detrimental effects on coronary vessels and its association with plaque progression, is bidirectionally linked to PCAT. PCAT modulates the secretory profile of endothelial cells in response to inflammation and also plays a crucial role in regulating vascular tone in the coronary district. Consequently, dysregulated PCAT has been hypothesized to contribute to type 2 myocardial infarction with non-obstructive coronary arteries (MINOCA) and coronary vasculitis. Recently, quantitative measures of EAT derived from coronary CT angiography (CCTA) have been included in artificial intelligence (AI) models for cardiovascular risk stratification. These models have shown incremental utility in predicting major adverse cardiovascular events (MACEs) compared to plaque characteristics alone. Therefore, the analysis of PCAT and EAT, particularly through PCAT-CT attenuation, appears to be a safe, valuable, and sufficiently specific noninvasive method for accurately identifying coronary inflammation and subsequent high-risk plaque. These findings are supported by biopsy and in vivo evidence. Although speculative, these pieces of evidence open the door for a fascinating new strategy in cardiovascular risk stratification. The incorporation of PCAT and EAT analysis, mainly through PCAT-CT attenuation, could potentially lead to improved risk stratification and guide early targeted primary prevention and intensive secondary prevention in patients at higher risk of cardiac events.

CAD-RADS score, vascular inflammation, and plaque vulnerability

Abstract Background Coronary artery disease reporting and data system (CAD-RADS), which is widely used to report the severity of coronary artery disease on coronary computed tomography angiography (CTA), predicts the risk of future cardiovascular events. However, the relationship between the CAD-RADS score and vascular inflammation and plaque vulnerability has not been investigated. Objective The aim of this study was to correlate the CAD-RADS score with vascular inflammation and plaque vulnerability. Methods This is an observational, single-center cohort study with prospective clinical follow-up. Patients who underwent both coronary CTA and optical coherence tomography (OCT) before coronary intervention were enrolled. All OCT and CTA images were analyzed at the core laboratory. Patients were categorized into two groups according to the CAD-RADS score (≤4a or 4b/5). All coronary arteries were analyzed for high-risk plaque features (positive remodeling, low-attenuation plaque, napkin-ring sign, and spotty calcification) and peri-coronary adipose tissue (PCAT) attenuation. PCAT attenuation was measured around the culprit lesion and in the proximal segment of all 3 coronary arteries. OCT features of plaque vulnerability were evaluated in culprit vessels. Major adverse cardiovascular and cerebrovascular events (MACCE) were defined as composite endpoints of unplanned target vessel revascularization, unplanned non-target vessel revascularization, nonfatal acute coronary syndrome, stroke, and cardiac death. Results Among 369 patients with 902 lesions, 104 (28.2%) were categorized in CAD-RADS 4b/5 and 265 (61.8%) in CAD-RADS ≤4a. Patients with CAD-RADS 4b/5 had higher PCAT attenuation than those with CAD-RADS ≤4a at all three levels (mean of 3 coronary vessels: -67.9 ± 6.9 HU vs. -70.2 ± 6.5, P=0.004; culprit vessel: -67.4 ± 7.9 vs. -70.2 ± 7.6, P=0.004; culprit plaque: -67.0 ± 9.3 vs. -69.9 ± 10.5, P=0.009; respectively) (Figure 1 A). Lipid-rich plaque and macrophage, as detected by OCT, were more prevalent in the culprit vessel in patients with CAD-RADS 4b/5 than in those with CAD-RADS ≤4a (89.0% vs. 78.5%, P=0.001; 76.6% vs. 64.9%, P=0.001; respectively) (Figure 1B). All HRP features, as detected by CTA, were more frequently observed in patients with CAD-RADS 4b/5 than those with CAD-RADS ≤4a (P for all &amp;lt;0.001) (Figure 2). The cumulative incidence of MACCE was higher in patients with CAD-RADS 4b/5 than in those with CAD-RADS ≤4a (15.0% vs. 5.8%, P=0.045). Conclusions Higher CAD-RADS score was associated with a higher level of pan-coronary vascular inflammation and plaque vulnerability.Figure 1Figure 2

CT pericoronary adipose tissue density predicts coronary allograft vasculopathy and adverse clinical outcomes after cardiac transplantation

Abstract Background Coronary allograft vasculopathy (CAV) is a common cause of heart transplant failure. Coronary Computed Tomography Angiography (CCTA) is used to assess for luminal stenoses in patients with suspected CAV, but additional non-invasive markers are needed to detect early disease and guide the use of treatments that can prevent or slow CAV progression. Purpose We tested the hypotheses that: 1) coronary artery inflammation assessed by pericoronary adipose tissue (PCAT) density and/or total vessel volume-to-myocardial mass ratio (V/M) measured by CCTA could improve the ability to detect CAV in heart transplant patients; and 2) these semi-automated quantitative CCTA metrics would be associated with adverse clinical outcomes. Methods In this retrospective observational cohort study, PCAT density, V/M, and lesion composition were measured in consecutive CCTAs from patients who underwent heart transplantation at a single site between 2010 to 2021. These parameters were incorporated into predictive models for CAV as defined by International Society for Heart &amp; Lung Transplant criteria, and evaluated against long-term clinical outcomes. Results A total of 126 CCTAs were analysed from 94 patients after heart transplant (mean age 49 [SD 14.5] years, 40% female) without CAV (n=86) and with CAV (n=40). PCAT density was higher in transplant patients with CAV (-73.0 HU [SD 9.26]) than without CAV (-77.9 HU [SD 8.23]), and age and sex-matched controls (n=12; -86.19 HU, [SD 5.38]), p&amp;lt;0.001 for both. Unlike patients with atherosclerotic coronary artery disease (n=32), CAV lesions were predominately non-calcified, comprised of mostly fibrous or fibrofatty tissue. V/M was lower in patients with CAV than without (32.4 mm3/g vs. 44.4 mm3/g, p&amp;lt;0.001). PCAT density and V/M improved the ability to predict CAV from AUC 0.78 to 0.87 on receiver operating characteristic analysis (Figure A) when added to donor age and donor/recipient hypertension status (p&amp;lt;0.0001). PCAT density above -66 HU was associated with a greater incidence of all-cause mortality (OR 16.6 95%CI 2.88-109.98, p&amp;lt;0.01; Figure B, box-plot) and the composite endpoint of death, CAV progression, acute rejection, and coronary revascularisation (OR 6.3 95%CI 1.6-32.9, p=0.01) over 5.25 (SD 2.1) years. Conclusions Heart transplant patients with CAV have higher PCAT density and lower V/M than those without. Patients with very high PCAT density on CT had markedly increased incidence of all-cause mortality and major adverse clinical events. These semi-automated metrics could be a useful addition to standard clinical CCTA reporting for diagnosis and monitoring of CAV.Diagnostic Benefit of CTCA MetricsPCAT is predictor of Future Mortality

Prognostic value of preprocedural pericoronary adipose tissue CT-Attenuation in patients with non ST-elevation acute coronary syndrome

Abstract Background Pericoronary adipose tissue attenuation expressed by fat attenuation index (FAI) on coronary CT angiography (CCTA) reflects pericoronary inflammation. FAI has been reported to be associated with cardiac mortality in patients with suspected coronary artery disease. However, the prognostic value of FAI in patients with non ST-elevation acute coronary syndrome (NSTE-ACS) after percutaneous coronary intervention (PCI) remains elusive. Methods This retrospective single-center observational study included a total of 358 patients with NSTE-ACS who underwent preprocedural 320-slice CCTA and emergent PCI within 24 hours from admission. Perivascular fat attenuation mapping was done around the three major coronary arteries-the proximal (4cm) right coronary artery (RCA), the left anterior descending artery (LAD), and the left circumflex artery (LCx). We assessed the prognostic value of FAI for all-cause and cardiac mortality. Clinical outcomes were assessed by death and cardiac death. Results During a median follow-up period of 1715 days (1008-2538), death and cardiac death occurred in 36 (10.1%) patients and 18 (5.0%) patients, respectively. High FAI values around LAD and LCx (but not around RCA) were predictive of all-cause mortality. High FAI values around RCA, LAD, and LCx were predictive of cardiac mortality. FAI in culprit vessels and average FAI values in three vessels were predictive of all-cause and cardiac mortality. ROC analysis revealed that the best cut-off FAI value in three vessels for predicting cardiac death is -65.8 (AUC: 0.752, 0.637-0.867.) Kaplan-Meier analysis revealed that patients with average FAI values in three vessels &amp;gt;-65.8 were significantly associated with poor prognosis of cardiac mortality. (P&amp;lt;0.001). Conclusion High perivascular FAI values are an indicator of increased cardiac mortality and, therefore, could guide early targeted secondary prevention and intensive medical management in patients with NSTE-ACS after PCI.Kaplan Meier analysis for cardiac death

Discovering pericoronary adipose tissue differences between normal and atherosclerotic coronary segments with radiomics analysis

Abstract Introduction Pericoronary adipose tissue (PCAT) extracted from coronary CT angiography (CCTA) is a novel marker for coronary inflammation. Establishing correlation between PCAT changes and the vascular lesion itself is essential for using PCAT to monitor clinical and subclinical disease status. Past studies focused on patient-level and vessel-level PCAT differences. However, lesion-level PCAT differences beyond mean attenuation values are not well understood. Purpose To investigate the differences between PCAT adjacent to atherosclerotic plaques and PCAT adjacent to normal coronary segments using radiomics analysis. Material and Methods This study enrolled 100 consecutive patients who underwent CCTA. A total of 446 plaques were successfully annotated in 89 patients. The PCAT of these 446 plaques and also their normal segment counterparts were extracted. Following prior literature, adipose tissue was defined as voxels with attenuation ranging -190 to -30 HU. PCAT was extracted within 3 mm distance from the vessel wall, along the middle 10 mm of each plaque. The PCAT of normal coronary artery segments were extracted both proximal and distal with distance D mm to the plaque with 10 mm length. We used 3 different distances to define the normal segments (D={10, 20, 30}). PyRadiomics was used to generate radiomics features and the random forest classifier from Scikit-Learn was used to distinguish PCAT extracted adjacent to atherosclerotic plaques and PCAT adjacent to normal coronary segments. To minimize bias due to vessel diameter or shape and focus on the texture of PCAT, we included only the First Order, GLCM, GLDM, GLRLM, GLSZM and NGTDM features (total 93 features) from PyRadiomics. We used 5-fold cross validation splitted at patient-level to develop the classifier. Result The radiomics model achieved acceptable discrimination for D=30 mm (mean AUROC = 0.70), borderline discrimination for D=20 mm (mean AUROC=0.68) and D=10 mm (mean AUROC = 0.60). These results suggest a trend toward greater differences between PCAT further away from the lesion compared with PCAT adjacent to the lesion. The feature "Gray Level Size Zone Matrix (GLSZM): Low Gray Level Zone Emphasis" had the highest importance in 4 out of 5 folds in our D = 30 mm experiment. The mean value of this feature is significantly different for the PCAT adjacent to the lesions compared to PCAT extracted from the normal segments (0.152 vs 0.166, p=0.001). Conclusion We investigated the difference between PCAT adjacent to atherosclerotic plaques and PCAT adjacent to normal coronary segments using radiomics analysis. We found greater discrimination when the normal segments were extracted further away from the lesion, suggesting PCAT changes due to atherosclerosis may exist beyond the length of the plaque. Moreover, "Gray Level Size Zone Matrix (GLSZM): Low Gray Level Zone Emphasis" could serve as a novel radiomic biomarker to correlate PCAT changes to atherosclerosis.

Abstract 18628: Focal Pericoronary Adipose Tissue Evaluated by Electron Density Numbers on Contrast Spectral Computed Tomography Was Associated With Coronary Arterial Plaques: A Site-by-Site Analysis

Introduction: Inflammation in pericoronary adipose tissue (PCAT) around the coronary arterial wall causes coronary arterial sclerosis. Many studies evaluated the relationship between total PCAT volume and coronary arterial sclerosis on a patient-by-patient basis. Hypothesis: Inflammation in PCAT may occur focally in coronary arterial system to which coronary arterial plaques localize. Using novel spectral CT, based on electron density number (EDN) as a new parameter, the focal characteristics of PCAT were evaluated. Methods: 17 patients (10 males, mean age 70 years) underwent cardiac spectral CT (7500, Philips, Tokyo, Japan). From contrast data, EDNs of PCAT were determined at a 1) right side site and 2) left anterior side site of a proximal portion of the right coronary arteries (RCA), 3) anterior side site of the left main coronary arteries, 4) left side site of a proximal portion of the left circumflex artery, and left side site of a distal portion of the RCA (five sites each patient). We also evaluated coronary arterial plaques on enhanced CT images at five corresponding sites for which EDNs were determined. Results: For a total of 85 sites among 17 patients using enhanced CT, 31 sites had no plaques (group 1), 14 sites had only non-calcified plaques (group 2), 20 sites had only calcified plaques (group 3), 16 sites had mixed plaques (group 4), and four sites had stent implantations (group 5). The mean of EDNS (%EDW) for 81 sites, excluding four sites with a stent implantation, were 93.7, 93.9, 94.0, and 94.3 in groups 1-4, respectively (P=NS). For a total of 81 sites, excluding four implantation sites, we evaluated the relationship between age and EDNs in groups 1-4. No correlations were observed in group 1 (R= 0.05), 3 (R= 0.09), and 4 (R= 0,15), however negative correlation was observed in group 2 (R= -0.42) between age and EDNs. No significant differences in EDNs were noted between males and females (P=NS). Conclusions: This is the first study in which focal PCAT was evaluated by EDNs and the relationship to coronary arterial plaques determined by site-by-site analysis. This new CT parameter may evaluate the status of PCAT and be a predictor of the future occurrence of coronary arterial plaques, which are related to PCAT inflammation.

Abstract 18549: Focal Pericoronary Adipose Tissue Evaluated by Atomic Numbers on Contrast Spectral Computed Tomography Was Associated With Coronary Arterial Plaques: A Site-by-Site Analysis

Introduction: Inflammation in pericoronary adipose tissue (PCAT) around the coronary arterial wall causes coronary arterial sclerosis. Many studies evaluated the relationship between total PCAT volume and coronary arterial sclerosis on a patient-by-patient basis. Hypothesis: Inflammation in PCAT may occur focally in coronary arterial system to which coronary arterial plaques localize. Using novel spectral CT, based on atomic number as a new parameter, the focal characteristics of PCAT were evaluated. Methods: 17 patients (10 males, mean age 70 years) underwent cardiac spectral CT (7500, Philips, Tokyo, Japan). From contrast data, atomic numbers of PCAT were determined at a 1) right side site and 2) left anterior side site of a proximal portion of the right coronary arteries (RCA), 3) anterior side site of the left main coronary arteries, 4) left side site of a proximal portion of the left circumflex artery, and left side site of a distal portion of the RCA (five sites each patient). We also evaluated coronary arterial plaques on enhanced CT images at five corresponding sites for which atomic numbers were determined. Results: For a total of 85 sites among 17 patients using enhanced CT, 31 sites had no plaques (group 1), 14 sites had only non-calcified plaques (group 2), 20 sites had only calcified plaques (group 3), 16 sites had mixed plaques (group 4), and four sites had stent implantations (group 5). The mean of atomic numbers for 81 sites, excluding four sites with a stent implantation, were 6.4, 6.8, 6.4, and 6.1 in groups 1-4, respectively (P=NS). For a total of 81 sites, excluding four implantation sites, we evaluated relationship between age and atomic numbers in groups 1-4. Positive correlations were observed in group 1 (R= 0.25) and 3 (R= 0.39), however negative correlation was observed in group 2 (R= -0.37) and 4 (R= -0.40) between age and atomic numbers. No significant differences in atomic numbers were noted between males and females. Conclusions: This is the first study in which focal PCAT was evaluated by atomic numbers and the relationship to coronary arterial plaques determined by site-by-site analysis. This new CT parameter may evaluate the status of PCAT and be a predictor of future occurrence of coronary arterial plaques, which are related to PCAT inflammation.

Abstract 18610: Focal Pericoronary Adipose Tissue Evaluated by Electron Density Numbers on Non-Contrast Spectral Computed Tomography Was Associated With Coronary Arterial Plaques: A Site-by-Site Analysis

Introduction: Inflammation in pericoronary adipose tissue (PCAT) around the coronary arterial wall causes coronary arterial sclerosis. Many studies evaluated the relationship between total PCAT volume and coronary arterial sclerosis on a patient-by-patient basis. Hypothesis: Inflammation in PCAT may occur focally in coronary arterial system to which coronary arterial plaques localize. Using novel spectral CT, based on electron density number (EDN) as a new parameter, the focal characteristics of PCAT were evaluated. Methods: 17 patients (10 males, mean age 70 years) underwent cardiac spectral CT (7500, Philips, Tokyo, Japan). From non-contrast data, EDNs of PCAT were determined at a 1) right side site and 2) left anterior side site of a proximal portion of right coronary arteries (RCA), 3) anterior side site of the left main coronary arteries, 4) left side site of a proximal portion of the left circumflex artery, and left side site of a distal portion of the RCA (five sites each patient). We also evaluated coronary arterial plaques on enhanced CT images at five corresponding sites for which EDNs were determined. Results: For a total of 85 sites among 17 patients using enhanced CT, 31 sites had no plaques (group 1), 14 sites had only non-calcified plaques (group 2), 20 sites had only calcified plaques (group 3), 16 sites had mixed plaques (group 4), and four sites had stent implantations (group 5). The mean of EDNS (%EDW) for 81 sites, excluding four sites with a stent implantation, were 93.5, 93.3, 93.2, and 93.8 in groups 1-4, respectively (P=NS). For a total of 81 sites, excluding four implantation sites, we evaluated the relationship between age and EDNs in groups 1-4. Positive correlations were observed in group 1 (R= 0.40), and 3 (R= 0.40), however negative correlation was observed in group 2 (R= -0.22) and 3 (R= -0.22) between age and EDNs. No significant differences in EDNs were noted between males and females (P=NS). Conclusions: This is the first study in which focal PCAT was evaluated by EDNs and the relationship to coronary arterial plaques determined by site-by-site analysis. This new CT parameter may evaluate the status of PCAT and be a predictor of the future occurrence of coronary arterial plaques, which are related to PCAT inflammation even on non-contrast CT alone.

Abstract 14643: Coronary Spotty Calcification is Associated With a Higher Level of Plaque Vulnerability and Vascular Inflammation in Patients With Stable Angina

Background: There is controversy on clinical implication of spotty calcification in the coronary arteries. Optical coherence tomography (OCT) enables detailed plaque characterization including features of plaque vulnerability. Pericoronary adipose tissue (PCAT) attenuation is a recently developed marker for perivascular inflammation. Methods: Patients with stable angina pectoris (SAP) who had both computed tomography angiography (CTA) and OCT prior to coronary intervention were included. They were classified into two groups: spotty calcification group (calcification arc &lt;90°, length &lt;4mm) and macro calcification group. Non-calcified plaques or plaques with mixed spotty and macro calcification were excluded. The OCT findings of the culprit lesion and PCAT attenuation of the culprit vessel were compared between the two groups. Results: Among 316 patients, 62 had spotty calcifications and 66 had macro calcification in the culprit lesion. The spotty calcification group showed a significantly higher prevalence of lipid rich plaque (91.9% vs. 74.2%, p=0.008; Figure A), greater mean lipid arc (183.1 vs. 150.5°, p=0.01), and a higher level of PCAT attenuation (-71.7 ± 7.68 vs. -74.9 ± 9.17 HU, p=0.03; Figure B), compared with the macro calcification group. Conclusion: Plaques with spotty calcification are associated with a higher prevalence of lipid-rich plaques and a higher level of perivascular inflammation, compared to those with macro calcification.