OBJECTIVE: This study aims to investigate the differences in plaque characteristics and fat attenuation index (FAI) between in patients who received revascularization versus those who did not receive revascularization and examine whether the machine-learning (ML) based model constructed by plaque characteristics and FAI can predict revascularization.
METHODS: This study was a post hoc analysis of a prospective single-center registry of sequential patients undergoing CCTA, referred from inpatient and emergency department settings (n = 261, 63 years ± 8; 188 men). The primary outcome was revascularization by percutaneous coronary revascularization. The CTA images were analyzed by experienced radiologists using a dedicated workstation in a blinded fashion. The ML-based model was automatically computed.
RESULTS: The study cohort consisted of 261 subjects. Revascularization was performed in 105 subjects. Patients receiving revascularization had higher FAI value (67.35±5.49 Hu vs -80.10±7.75 Hu, p < 0.001) as well as higher plaque length, calcified, lipid and fibrous plaque burden and volume. When FAI was incorporated into a ML risk model based on plaque characteristics to predict revascularization, the area under the curve increased from 0.84 (95% CI: 0.68-0.99) to 0.95 (95% CI: 0.88-1.00).
CONCLUSIONS: ML-algorithms based on FAI and characteristics could help improve the prediction of future revascularization and identify patients likely to receive revascularization.
CONCLUSIONS: Pre-procedural FAI could help guide revascularization in symptomatic CAD patients.

UNASSIGNED: Coronary inflammation causes significantly increased risk of cardiovascular disease (CVD) in diabetic patients. This study investigated the relationship between coronary local inflammation, detected by pericoronary fat attenuation index (FAI), and different blood glucose control levels in low-risk acute coronary syndrome (ACS) patients with or without diabetes.
UNASSIGNED: A total of 309 patients with low-risk ACS were classified into three groups: non-diabetes, well-regulated diabetes, and poorly regulated diabetes. Pericoronary FAI around the proximal or left anterior descending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA), were evaluated by coronary computed tomography angiography (CCTA), and systemic inflammatory variables and other biochemical indicators were detected by flow cytometry.
UNASSIGNED: Pericoronary FAI values around the proximal LAD, LCX, and RCA in poorly regulated diabetes were significantly higher than those in well-regulated diabetes and non-diabetes, whereas those in well-regulated diabetes were not statistically different from those in non-diabetes. Further, plasma glycated hemoglobin (HbA1c) level was positively correlated with the pericoronary FAI values in LAD, LCX, and RCA. However, no significantly increased systemic inflammatory mediators were found in diabetic patients with poor glycemic control.
UNASSIGNED: Diabetic patients with poor glycemic control may have higher coronary local inflammation as detected by pericoronary FAI surrounding the three major coronary arteries.
UNASSIGNED: NCT05590858.

UNASSIGNED: Inflammation triggers atherosclerotic plaque rupture, leading to acute myocardial infarction (AMI). Following AMI, peri-coronary adipose tissue (PCAT) undergoes a transition from lipid-rich to hydrophilic characteristics due to vascular inflammation. This study investigates PCAT changes and neutrophil-to-lymphocyte ratio levels during AMI.
UNASSIGNED: 60 AMI patients undergoing coronary computed tomography angiography and angiography (Jan 2020-Jun 2022) were studied 60 age, gender, BMI-matched stable angina, and 60 non-coronary artery disease patients were included. Siemens VB20.0 measured PCAT-volume and fat attenuation index (FAI). Neutrophil-to-lymphocyte ratio levels were calculated by peripheral blood tests.
UNASSIGNED: The PCAT volume and PCAT-FAI gradually increased across the control, stable angina, and AMI groups, with a corresponding gradual rise in NLR. NLR exhibited weak positive correlation with PCAT-FAI (r=0.35) and PCAT-volume (r=0.24). Multivariable logistic regression identified increased PCAT-volume, PCAT-FAI and neutrophil-to-lymphocyte ratio as possible independent AMI risk factors. No significant PCAT-volume difference was observed between infarct-related artery (IRA) and non-IRA for all three coronary arteries. Only PCAT-FAI around IRA-LAD was higher than non-IRA-LAD (-74.84±6.93 HU vs -79.04±8.68 HU). PCAT-FAI around culprit vessels in AMI was higher than corresponding lesion related vessel in SA. PCAT-volume around narrowed non-IRA in AMI was higher than that of corresponding LRV in SA. PCAT-FAI of narrowed non-IRA-LADs and non-IRA-LCXs in AMI were elevated compared to LADs (-78.46±8.56HU vs -83.13±8.34 HU) and LCXs (-73.83±10.63 HU vs -81.38±7.88 HU) of lesion related vessel in stable angina.
UNASSIGNED: We found an association between AMI and inflammation in the coronary perivascular adipose tissue and systemic inflammatory response.

With the enormous progress in the field of cardiovascular imaging in recent years, computed tomography (CT) has become readily available to phenotype atherosclerotic coronary artery disease. New analytical methods using artificial intelligence (AI) enable the analysis of complex phenotypic information of atherosclerotic plaques. In particular, deep learning-based approaches using convolutional neural networks (CNNs) facilitate tasks such as lesion detection, segmentation, and classification. New radiotranscriptomic techniques even capture underlying bio-histochemical processes through higher-order structural analysis of voxels on CT images. In the near future, the international large-scale Oxford Risk Factors And Non-invasive Imaging (ORFAN) study will provide a powerful platform for testing and validating prognostic AI-based models. The goal is the transition of these new approaches from research settings into a clinical workflow. In this review, we present an overview of existing AI-based techniques with focus on imaging biomarkers to determine the degree of coronary inflammation, coronary plaques, and the associated risk. Further, current limitations using AI-based approaches as well as the priorities to address these challenges will be discussed. This will pave the way for an AI-enabled risk assessment tool to detect vulnerable atherosclerotic plaques and to guide treatment strategies for patients.

BACKGROUND: The purpose of this study was to explore the prognostic significance of the lesion-specific pericoronary fat attenuation index (FAI) in forecasting major adverse cardiovascular events (MACE) among patients with type 2 diabetes mellitus (T2DM).
METHODS: This study conducted a retrospective analysis of 304 patients diagnosed with T2DM who underwent coronary computed tomography angiography (CCTA) in our hospital from December 2011 to October 2021. All participants were followed for a period exceeding three years. Detailed clinical data and CCTA imaging features were carefully recorded, encompassing lesion-specific pericoronary FAI, FAI of the three prime coronary arteries, features of high-risk plaques, and the coronary artery calcium score (CACS). The MACE included in the study comprised cardiac death, acute coronary syndrome (which encompasses unstable angina pectoris and myocardial infarction), late-phase coronary revascularization procedures, and hospital admissions prompted by heart failure.
RESULTS: Within the three-year follow-up, 76 patients with T2DM suffered from MACE. The lesion-specific pericoronary FAI in patients who experienced MACE was notably higher compared to those without MACE (-84.87 ± 11.36 Hounsfield Units (HU) vs. -88.65 ± 11.89 HU, p = 0.016). Multivariate Cox regression analysis revealed that CACS ≥ 100 (hazard ratio [HR] = 4.071, 95% confidence interval [CI] 2.157-7.683, p < 0.001) and lesion-specific pericoronary FAI higher than - 83.5 HU (HR = 2.400, 95% CI 1.399-4.120, p = 0.001) were independently associated with heightened risk of MACE in patients with T2DM over a three-year period. Kaplan-Meier analysis showed that patients with higher lesion-specific pericoronary FAI were more likely to develop MACE (p = 0.0023). Additionally, lesions characterized by higher lesion-specific pericoronary FAI values were found to have a greater proportion of high-risk plaques (p = 0.015). Subgroup analysis indicated that lesion-specific pericoronary FAI higher than - 83.5 HU (HR = 2.017, 95% CI 1.143-3.559, p = 0.015) was independently correlated with MACE in patients with T2DM who have moderate to severe coronary calcification. Moreover, the combination of CACS ≥ 100 and lesion-specific pericoronary FAI>-83.5 HU significantly enhanced the predictive value of MACE in patients with T2DM within 3 years.
CONCLUSIONS: The elevated lesion-specific pericoronary FAI emerged as an independent prognostic factor for MACE in patients with T2DM, inclusive of those with moderate to severe coronary artery calcification. Incorporating lesion-specific pericoronary FAI with the CACS provided incremental predictive power for MACE in patients with T2DM.

Background and Objectives: The modified Duke index derived from coronary computed tomography angiography (CCTA) was designed to predict cardiovascular outcomes based on the severity of coronary stenosis. However, it does not take into consideration the presence or severity of peri-coronary inflammation. The peri-coronary fat attenuation index (FAI) is a novel imaging marker determined by CCTA which reflects the degree of inflammation in the coronary tree in patients with coronary artery disease. To assess the association between the modified Duke index assessed by CCTA, cardiovascular risk factors, and peri-coronary inflammation in the coronary arteries of patients with coronary artery disease. Materials and Methods: One hundred seventy-two patients who underwent CCTA for typical angina were assigned into two groups based on the modified Duke index: group 1-patients with low index, ≤3 (n = 107), and group 2-patients with high index, >3 (n = 65). Demographic, clinical, and CCTA data were collected for all patients, and FAI analysis of coronary inflammation was performed. Results: Patients with increased values of the modified Duke index were significantly older compared to those with a low index (61.83 ± 9.89 vs. 64.78 ± 8.9; p = 0.002). No differences were found between the two groups in terms of gender distribution, hypertension, hypercholesterolemia, or smoking history (all p > 0.5). The FAI score was significantly higher in patients from group 2, who presented a significantly higher score of inflammation compared to the patients in group 1, especially at the level of the right coronary artery (FAI score, 20.85 ± 15.80 vs. 14.61 ± 16.66; p = 0.01 for the right coronary artery, 13.85 ± 8.04 vs. 10.91 ± 6.5; p = 0.01 for the circumflex artery, 13.26 ± 10.18 vs. 11.37 ± 8.84; p = 0.2 for the left anterior descending artery). CaRi-Heart® analysis identified a significantly higher risk of future events among patients with a high modified Duke index (34.84% ± 25.86% vs. 16.87% ± 15.80%; p < 0.0001). ROC analysis identified a cut-off value of 12.1% of the CaRi-Heart® risk score for predicting a high severity of coronary lesions, with an AUC of 0.69. Conclusions: The CT-derived modified Duke index correlates well with local perilesional inflammation as assessed using the FAI score at different levels of the coronary circulation.

Background: Atrial fibrillation (AF) can often be triggered by an inflammatory substrate. Perivascular inflammation may be assessed nowadays using coronary computed tomography angiography (CCTA) imaging. The new pericoronary fat attenuation index (FAI HU) and the FAI Score have prognostic value for predicting future cardiovascular events. Our purpose was to investigate the correlation between pericoronary fat inflammation and the presence of AF among patients with coronary artery disease. Patients and methods: Eighty-one patients (mean age 64.75 ± 7.84 years) who underwent 128-slice CCTA were included in this study and divided into two groups: group 1 comprised thirty-six patients with documented AF and group 2 comprised forty-five patients without a known history of AF. Results: There were no significant differences in the absolute value of fat attenuation between the study groups (p > 0.05). However, the mean FAI Score was significantly higher in patients with AF (15.53 ± 10.29 vs. 11.09 ± 6.70, p < 0.05). Regional analysis of coronary inflammation indicated a higher level of this process, especially at the level of the left anterior descending artery (13.17 ± 7.91 in group 1 vs. 8.80 ± 4.75 in group 2, p = 0.008). Conclusions: Patients with AF present a higher level of perivascular inflammation, especially in the region of the left coronary circulation, and this seems to be associated with a higher risk of AF development.

UNASSIGNED: The triglyceride glucose (TyG) index is an effective method for determining insulin resistance (IR). Limited research has explored the connection between the TyG index and functionally significant stenosis in hypertensive patients. Furthermore, the connections between the TyG index, fat attenuation index (FAI) and atherosclerotic plaque characteristics are also worth exploring.
UNASSIGNED: The study screened 1622 hypertensive participants without coronary artery disease history who underwent coronary computed tomography angiography. The TyG index was calculated as ln (fasting glucose [mg/dL] * fasting TG [mg/dL]/2). Adverse plaque characteristics (HRPCs), high-risk plaques (HRPs), FAI, and CT-derived fractional flow reserve (FFRCT) were analyzed and measured for all patients. Functionally significant stenosis causing ischemia is defined as FFRCT ≤ 0.80. Two patient groups were created based on the FFRCT: the FFRCT < 0.80 group and the FFRCT > 0.80 group. In hypertensive patients, the association between the TyG index and FFRCT was examined applying a logistic regression model.
UNASSIGNED: The TyG index was higher for people with FFRCT ≤ 0.80 contrast to those with FFRCT > 0.80. After controlling for additional confounding factors, the logistic regression model revealed a clear connection between the TyG index and FFRCT ≤ 0.80 (OR = 1.718, 95% CI 1.097-2.690, p = 0.018). The restricted cubic spline analysis displayed a nonlinear connection between the TyG index and FFRCT ≤ 0.80 (p for nonlinear = 0.001). The TyG index increased the fraction of individuals with HRPs and HRPCs, FAI raised, and FFRCT decreased (p < 0.05). The multivariate linear regression analysis illustrated a powerfulcorrelation between high TyG index levels and FAI, FFRCT, positive remodeling (PR), and low-attenuation plaque (LAPs) (standardized regression coefficients: 0.029 [p = 0.007], -0.051 [p < 0.001], 0.029 [p = 0.027], and 0.026 [p = 0.046], separately).
UNASSIGNED: In hypertensive patients, the TyG index showed an excellent association with a risk of FFRCT ≤ 0.80. Additionally, the TyG index was also linked to FAI, FFRCT, PR, and LAPs.

UNASSIGNED: This study aimed to evaluate the differences between pericoronary adipose tissue (PCAT) attenuation at different measured locations in evaluating coronary atherosclerosis using spectral computed tomography (CT) and to explore valuable imaging indicators.
UNASSIGNED: A total of 330 patients with suspicious coronary atherosclerosis were enrolled and underwent coronary CT angiography with dual-layer spectral detector CT (SDCT). Proximal and peri-plaque fat attenuation index (FAI) of stenosis coronary arteries were measured using both conventional images (CIs) and virtual monoenergetic images (VMIs) ranging from 40 keV to 100 keV. The slopes of the spectral attenuation curve (λ) of proximal and peri-plaque PCAT at three different monoenergetic intervals were calculated. Additionally, peri-plaque FAI on CI and virtual non-contrast images, and effective atomic number were measured manually.
UNASSIGNED: A total of 231 coronary arteries with plaques and lumen stenosis were finally enrolled. Peri-plaque FAICI and FAIVMI were significantly higher in severe stenosis than in mild and moderate stenosis (p < 0.05), while peri-plaque λ, proximal FAI, and proximal λ were not statistically different. Proximal FAI, peri-plaque FAI, and peri-plaque λ were significantly higher in low-density non-calcified plaque (LD-NCP) and non-calcified plaque (NCP) than in calcified plaque (p < 0.01). Peri-plaque FAI was the highest in the LD-NCP group, while proximal FAI was the highest in the NCP group. In severe stenosis and in LD-NCP, peri-plaque FAI was significantly higher than proximal FAI (p < 0.05). The manually measured parameters related to peri-plaque PCAT attenuation had a positive correlation with the results of peri-plaque FAI measured automatically.
UNASSIGNED: Peri-plaque PCAT has more value in assessing coronary atherosclerosis than proximal PCAT. Peri-plaque PCAT attenuation is expected to be used as a standard biomarker for evaluating plaque vulnerability and hemodynamic characteristics.

UNASSIGNED: Coronary artery disease can be quantified by measuring the fat attenuation index (FAI).
UNASSIGNED: To explore the correlations between FAI, high-risk plaque and the degree of coronary artery stenosis.
UNASSIGNED: The clinical data of patients with coronary atherosclerosis who underwent a coronary computed tomography (CT) angiography examination between July 2020 and June 2023 were selected for retrospective analysis. These patients were classified into a high-risk plaque group and non-high-risk plaque group according to the presence of CT high-risk plaque. The diagnostic value of FAI and FAI combined with the degree of stenosis was evaluated for CT high-risk plaque.
UNASSIGNED: Differences in age, body mass index, smoking history, FAI and the degree of stenosis between the two groups were statistically significant (all P< 0.05). The results of a binary logistic regression analysis revealed that FAI (odds ratio (OR): 1.131, 95% confidence interval (CI): 1.101-1.173, P< 0.001) and the degree of stenosis (OR: 1.021, 95% CI: 1.012-1.107, P< 0.001) were risk factors for high-risk plaque.
UNASSIGNED: The FAI can be used to monitor the inflammation level of the coronary artery; the higher the FAI is, the higher the risk of plaque and degree of stenosis.