Association of coronary inflammation with plaque vulnerability and fractional flow reserve in coronary artery disease.

BACKGROUND: The fat attenuation index (FAI) measured using coronary computed tomography angiography (CCTA) enables the direct evaluation of pericoronary adipose tissue composition and vascular inflammation. We aimed to investigate the association of fractional flow reserve (FFR) and plaque vulnerability with coronary inflammation. METHODS: Patients with suspected coronary artery disease (CAD) who underwent CCTA and invasive FFR measurements within 90-day were included. A cloud-based medical device, CaRi-Heart, serves as a surrogate tool for evaluating coronary inflammation based on FAI by analyzing CCTA images. The correlations between CCTA-defined plaque characteristics, invasive coronary angiographic and physiologic assessments, and CaRi-Heart risk were analyzed. The primary endpoint was the patient-oriented composite outcome (POCO) consisting of all-cause death, any myocardial infarction, and any revascularization. RESULTS: A total of 564 patients (median age 67.0 years; 75.4 â€‹% men) were included. There were no significant differences in quantitative and qualitative plaque characteristics or FFR between the high- and low-CaRi-Heart risk groups (i.e., ≥5 â€‹% and <5 â€‹%). During the median follow-up of 3.2 years [1.13-4.73 years], CaRi-Heart risk ≥5 â€‹% was associated with a significantly higher rate of POCO compared to CaRi-Heart risk <5 â€‹% (0.9 â€‹% vs. 10.1 â€‹%, P â€‹= â€‹0.037). The CaRi-Heart risk was an independent predictor of POCO as a continuous (adjusted HR 1.016, 95 â€‹% CI 1.005-0.027, P â€‹= â€‹0.004) and categorical variable (CaRi-Heart risk ≥5 â€‹%, adjusted HR 2.949, 95 â€‹% CI 1.182-7.360, P â€‹= â€‹0.021), regardless of high-risk plaque characteristics and FFR. CONCLUSION: Coronary inflammation risk assessed using CaRi-Heart risk provides independent prognostic information regardless of plaque vulnerability and physiologic stenosis in patients with CAD.

Pericoronary Fat Attenuation: Diagnosis and Clinical Implications.

PURPOSE OF THE REVIEW: The purpose of this review is to evaluate the current state of knowledge regarding the technical challenges associated with the Post-Acquisition Fat Attenuation Index (PFAI). By examining the limitations and gaps in the current methodologies, this review aims to provide a comprehensive understanding of how various factors impact the accuracy and reliability of PFAI measurements. RECENT FINDINGS: PFAI correlates with plaque instability, as inflammation in coronary plaque alters surrounding adipose tissue composition, increasing its water content and reducing lipid content, which is detectable via cardiac CT as increased attenuation. Recent studies have demonstrated PFA's prognostic value, with elevated levels linked to higher risks of cardiac events and plaque instability. A 2022 meta-analysis confirmed its association with major adverse cardiac events. Machine learning algorithms incorporating PFA and additional imaging features have further enhanced risk prediction beyond traditional metrics. Pericoronary fat attenuation is a promising marker for assessing coronary inflammation and could be useful in predicting plaque development, rupture, and monitoring treatment response, though further prospective studies and technical standardization are needed to fully establish its clinical benefits.

Investigating the peri-saphenous vein graft fat attenuation index on computed tomography angiography: relationship with progression of venous coronary artery bypass graft disease and temporal trends.

BACKGROUND: To clarify the fat attenuation index (FAI) change trend of peri-saphenous vein graft (SVG) and determine the association between FAI and graft disease progression based on CCTA images. METHODS: Patients with venous coronary artery bypass grafts (CABGs) were consecutively enrolled in this retrospective study. In study 1, 72 patients who had undergone 1, 3, and 5 years of CCTA examinations without graft occlusion were recruited, and generalized estimation equation was used to analyze the peri-SVG FAI change trend over time. In study 2, 42 patients with graft disease progression and 84 patients as controls were propensity score-matched. Generalized linear mixed model and continuous net reclassification improvement (NRI) were used for assessing the associations with graft disease progression. Multivariable Cox regression analysis was used for assessing risk factors predicting cardiac events. RESULTS: In study 1, both the FAI of proximal right coronary artery and SVG decreased over time. In study 2, the 1-year CTA-derived FAI of grafts and graft anastomosis were independent indicators of graft disease progression at the 3-year CCTA follow-up (graft: odds ratio [OR] = 1.106; 95% confidence interval [CI] = 1.030-1.188, P = 0.006; graft anastomosis: OR = 1.170, 95% CI = 1.091-1.254, P < 0.001). Inclusion of the graft anastomosis FAI significantly improved reclassification compared with graft FAI (continuous NRI = 0.638, 95% CI: 0.345-0.931, P < 0.001). Moreover, The graft anastomosis FAI was found to be a risk factor for cardiac events after CABG and no statistically significant difference was found in the graft FAI (graft anastomosis: HR = 1.158, 95% CI = 1.034-1.297, P = 0.011; graft: HR = 1.116, 95% CI = 0.995-1.251, P = 0.061). CONCLUSIONS: A synchronism was found in the FAI change trend between native coronary artery and venous graft, which both decreased over time. The CCTA-derived FAI of venous grafts showed the potential of demonstrating SVG disease progression and graft anastomosis served as the optimal measured location.

Association Between Pericoronary Fat Attenuation Index as Evaluated by Coronary Artery CT Angiography and Clinical Interventions in Lipid Management Among Patients with Coronary Artery Disease.

Objective: This study aims to evaluate the relationship between the pericoronary fat attenuation index (FAI), derived from coronary artery computed tomography angiography, and post-lipid management levels of low-density lipoprotein cholesterol in patients with coronary artery disease (CAD). Additionally, the study investigates coronary inflammation across different lipid management strategies. Methods: We selected a cohort comprising 521 CAD patients who met the inclusion criteria. Patients were categorized into well-managed (LDL-C<2.6 mmol/L) and poorly managed (LDL-C≥2.6 mmol/L) groups based on lipid management efficacy. We collected anthropometric measures (height, weight, body mass index, and body surface area) and clinical indicators, including Gensini score, and FAI-related parameters for coronary atherosclerotic lesions. We analyzed the interrelations along these parameters and lipid management using statistical methods and assessed diagnostic value via receiver operating characteristic (ROC) curve analysis of these parameters was assessed through. Results: The poorly managed group exhibited significantly higher levels of total cholesterol, triglycerides, and lower levels of high-density lipoprotein compared to the well-managed group (P < 0.05). Significant differences were observed between the groups in terms of lesion length in the proximal segment of the left anterior descending artery, FAI value in the proximal segment of lesions in the right coronary artery (RCA), volume thickness in the middle segment of RCA lesions, and lesion length in the distal segment of RCA (P < 0.05). ROC curve analysis revealed areas under the curve ranging from 0.484 to 0.660 for the parameters, indicating limited diagnostic efficacy. Conclusion: The FAI in the RCA varies with lipid management strategies, suggesting it as a valuable metric for monitoring both perivascular inflammation and lipid status in CAD patients. However, its current diagnostic efficacy is limited, indicating the need for further research to improve its clinical utility.

Predictive value of CCTA-based pericoronary adipose tissue imaging for major adverse cardiovascular events.

RATIONALE AND OBJECTIVE: To evaluate the ability of the radiomic characteristics of pericoronary adipose tissue (PCAT) as determined by coronary computed tomography angiography (CCTA) to predict the likelihood of major adverse cardiovascular events (MACEs) within the next five years. MATERIALS AND METHODS: In this retrospective casecontrol study, the case group consisted of 210 patients with coronary artery disease (CAD) who developed MACEs within five years, and the control group consisted of 210 CAD patients without MACEs who were matched with the case group patients according to baseline characteristics. Both groups were divided into training and testing cohorts at an 8:2 ratio. After data standardization and the exclusion of features with Pearson correlation coefficients of |r| ≥ 0.9, independent logistic regression models were constructed using selected radiomics features of the proximal PCAT of the left anterior descending (LAD) artery, left circumflex (LCX) artery, and right coronary artery (RCA) via least absolute shrinkage and selection operator (LASSO) techniques. An integrated PCAT radiomics model including all three coronary arteries was also developed. Five models, including individual PCAT radiomics models for the LAD artery, LCX artery, and RCA; an integrated radiomics model; and a fat attenuation index (FAI) model, were assessed for diagnostic accuracy via receiver operating characteristic (ROC) curves, calibration curves, and decision curves. RESULTS: Compared with the FAI model (AUC=0.564 in training, 0.518 in testing), the integrated radiomics model demonstrated superior diagnostic performance (area under the curve [AUC]=0.923 in training, 0.871 in testing). The AUC values of the integrated model were greater than those of the individual coronary radiomics models, with all the models showing goodness of fit (P > 0.05). The decision curves indicated greater clinical utility of the radiomics models than the FAI model. CONCLUSION: PCAT radiomics models derived from CCTA data are highly valuable for predicting future MACE risk and significantly outperform the FAI model.

Effect of Deep Learning Image Reconstruction on Image Quality and Pericoronary Fat Attenuation Index.

To compare the image quality and fat attenuation index (FAI) of coronary artery CT angiography (CCTA) under different tube voltages between deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction V (ASIR-V). Three hundred one patients who underwent CCTA with automatic tube current modulation were prospectively enrolled and divided into two groups: 120 kV group and low tube voltage group. Images were reconstructed using ASIR-V level 50% (ASIR-V50%) and high-strength DLIR (DLIR-H). In the low tube voltage group, the voltage was selected according to Chinese BMI classification: 70 kV (BMI < 24 kg/m2), 80 kV (24 kg/m2 ≤ BMI < 28 kg/m2), 100 kV (BMI ≥ 28 kg/m2). At the same tube voltage, the subjective and objective image quality, edge rise distance (ERD), and FAI between different algorithms were compared. Under different tube voltages, we used DLIR-H to compare the differences between subjective, objective image quality, and ERD. Compared with the 120 kV group, the DLIR-H image noise of 70 kV, 80 kV, and 100 kV groups increased by 36%, 25%, and 12%, respectively (all P < 0.001); contrast-to-noise ratio (CNR), subjective score, and ERD were similar (all P > 0.05). In the 70 kV, 80 kV, 100 kV, and 120 kV groups, compared with ASIR-V50%, DLIR-H image noise decreased by 50%, 53%, 47%, and 38-50%, respectively; CNR, subjective score, and FAI value increased significantly (all P < 0.001), ERD decreased. Compared with 120 kV tube voltage, the combination of DLIR-H and low tube voltage maintains image quality. At the same tube voltage, compared with ASIR-V, DLIR-H improves image quality and FAI value.

Comparative Prognostic Value of Coronary Calcium Score and Perivascular Fat Attenuation Index in Coronary Artery Disease.

Coronary artery disease (CAD) is the leading global cause of mortality, accounting for approximately 30% of all deaths. It is primarily characterized by the accumulation of atherosclerotic plaques within the coronary arteries, leading to reduced blood flow to the heart muscle. Early detection of atherosclerotic plaques is crucial to prevent major adverse cardiac events. Notably, recent studies have shown that 15% of myocardial infarctions occur in patients with non-obstructive CAD, underscoring the importance of comprehensive plaque assessment beyond merely identifying obstructive lesions. Cardiac Computed Tomography Angiography (CCTA) has emerged as a cost-effective and efficient technique for excluding obstructive CAD, particularly in patients with a low-to-intermediate clinical likelihood of the disease. Recent advancements in CCTA technology, such as improved resolution and reduced scan times, have mitigated many technical challenges, allowing for precise quantification and characterization of both calcified and non-calcified atherosclerotic plaques. This review focuses on two critical physiological aspects of atherosclerotic plaques: the burden of calcifications, assessed via the coronary artery calcium score (CACs), and perivascular fat attenuation index (pFAI), an emerging marker of vascular inflammation. The CACs, obtained through non-contrast CT scans, quantifies calcified plaque burden and is widely used to stratify cardiovascular risk, particularly in asymptomatic patients. Despite its prognostic value, the CACs does not provide information on non-calcified plaques or inflammatory status. In contrast, the pFAI, derived from CCTA, serves as an indirect marker of coronary inflammation and has shown potential in predicting adverse cardiac events. Combining both CACs and pFAI assessment could offer a comprehensive risk stratification approach, integrating the established calcification burden with novel inflammatory markers to enhance CAD prevention and management strategies.

Usefulness of fat attenuation index in postmortem CT for identifying responsible vessels in acute coronary syndromes: A case report.

Postmortem imaging, particularly unenhanced postmortem computed tomography (PMCT), has been increasingly utilized for pathological or judicial examination as a substitute for conventional autopsy, to compensate very low autopsy rates. While unenhanced PMCT has a limitation in diagnosing acute coronary syndromes, the fat attenuation index (FAI) which is a novel imaging biomarker measured by clinical coronary CT angiography (CCTA), has been known to noninvasively detect coronary artery inflammation. We investigated the postmortem diagnostic usefulness of perivascular FAI measured by CCTA in a 61-year-old male who died suddenly after chest pain. PMCT and autopsy were conducted 92 hours after death. FAI measurement results were -57 Hounsfield units (HU) in the right coronary artery (RCA), -73 HU in the left anterior descending artery (LAD), and -64 HU in the left circumflex artery (LCX). Autopsy revealed significant stenosis in the RCA and LCX, but no significant stenosis was found in the LAD. The elevated FAI in the RCA suggested acute inflammation, which agreed with the autopsy findings. This case is the first to demonstrate effectiveness of FAI measured with PMCT for identifying the vessels responsible for acute coronary syndromes, indicating its potential in postmortem diagnosis.

Perivascular Fat: A Novel Risk Factor for Coronary Artery Disease.

Perivascular adipose tissue (PVAT) interacts with the vascular wall and secretes bioactive factors which regulate vascular wall physiology. Vice versa, vascular wall inflammation affects the adjacent PVAT via paracrine signals, which induce cachexia-type morphological changes in perivascular fat. These changes can be quantified in pericoronary adipose tissue (PCAT), as an increase in PCAT attenuation in coronary computed tomography angiography images. Fat attenuation index (FAI), a novel imaging biomarker, measures PCAT attenuation around coronary artery segments and is associated with coronary artery disease presence, progression, and plaque instability. Beyond its diagnostic capacity, PCAT attenuation can also ameliorate cardiac risk stratification, thus representing an innovative prognostic biomarker of cardiovascular disease (CVD). However, technical, biological, and anatomical factors are weakly related to PCAT attenuation and cause variation in its measurement. Thus, to integrate FAI, a research tool, into clinical practice, a medical device has been designed to provide FAI values standardized for these factors. In this review, we discuss the interplay of PVAT with the vascular wall, the diagnostic and prognostic value of PCAT attenuation, and its integration as a CVD risk marker in clinical practice.

Coronary computed tomography angiography-derived fat attenuation index predict future percutaneous coronary intervention.

OBJECTIVES: 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-centre registry of sequential patients undergoing coronary computed tomography angiography, referred from inpatient and emergency department settings (n = 261, 63 years ± 8; 188 men). The primary outcome was revascularization by percutaneous coronary revascularization. The computed tomography angiography (CTA) images were analysed 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 vs -80.10 ± 7.75 Hu, P < .001) as well as higher plaque length, calcified, lipid, and fibrous plaque burden and volume. When FAI was incorporated into an 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. ADVANCES IN KNOWLEDGE: Pre-procedural FAI could help guide revascularization in symptomatic coronary artery disease patients.

Morphological Changes of Peri-Coronary Adipose Tissue Together with Elevated NLR in Acute Myocardial Infarction Patients in-Hospital.

Background: 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. Patients and Methods: 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. Results: 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. Conclusion: We found an association between AMI and inflammation in the coronary perivascular adipose tissue and systemic inflammatory response.

The predictive value of lesion-specific pericoronary fat attenuation index for major adverse cardiovascular events in patients with type 2 diabetes.

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.

Association between Pericoronary Fat Attenuation Index Values and Plaque Composition Volume Fraction Measured by Coronary Computed Tomography Angiography.

RATIONALE AND OBJECTIVES: The pericoronary fat attenuation index (FAI) values around plaques may reveal the relationship between periplaque vascular inflammation and different plaque component volume fractions. We aimed to evaluate the potential associations between periplaque FAI values and plaque component volume fractions. MATERIALS AND METHODS: 496 patients (1078 lesions) with coronary artery disease, who underwent computed tomography angiography (CCTA) between September 2022 and August 2023, were analyzed retrospectively. Each lesion was characterized and the plaque component volume fractions and periplaque FAI values were measured. Multiple linear regression, weighted quantile sum (WQS) regression, and quantile g-computation (Qgcomp) were used to explore the relationship between plaque component volume fractions and the risk of elevated periplaque FAI values. RESULTS: After adjusting for clinical characteristics, multiple linear regression identified that lipid components volume fraction (ß = 0.162, P < 0.001) were independent risk factors for elevated periplaque FAI values whereas calcified components volume fraction (ß = -0.066, P = 0.025) were independent protective factors. The WQS regression models indicated an increase in the overall confounding effect of the adjusted lipid indices and plaque composition volume fraction on the risk of elevated periplaque FAI values (P = 0.004). Qgcomp analysis indicated lipid component volume fraction and calcified component volume fraction was positively and negatively correlated with elevated plaque FAI values, respectively (all P < 0.05). CONCLUSIONS: Periplaque FAI values quantified by CCTA were strongly correlated with lipid and calcification component volume fractions.

Using artificial intelligence to study atherosclerosis from computed tomography imaging: A state-of-the-art review of the current literature.

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.

Coronary Computed Tomography Angiography-Derived Modified Duke Index Is Associated with Peri-Coronary Fat Attenuation Index and Predicts Severity of Coronary Inflammation.

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.

Analysis of the perivascular fat attenuation index and quantitative plaque parameters in relation to haemodynamically impaired myocardial ischaemia.

To investigate the correlation between quantitative plaque parameters, the perivascular fat attenuation index, and myocardial ischaemia caused by haemodynamic impairment. Patients with stable angina who had invasive flow reserve fraction (FFR) assessment and coronary artery computed tomography (CT) angiography were retrospectively enrolled. A total of 138 patients were included in this study, which were categorized into the FFR < 0.75 group (n = 43), 0.75 ≤ FFR ≤ 0.8 group (n = 37), and FFR > 0.8 group (n = 58), depending on the range of FFR values. The perivascular FAI and CTA-derived parameters, including plaque length (PL), total plaque volume (TPV), minimum lumen area (MLA), and narrowest degree (ND), were recorded for the lesions. An FFR < 0.75 was defined as myocardial-specific ischaemia. The relationships between myocardial ischaemia and parameters such as the PL, TPV, MLA, ND, and FAI were analysed using a logistic regression model and receiver operating characteristic (ROC) curves to compare the diagnostic accuracy of various indicators for myocardial ischaemia. The PL, TPV, ND, and FAI were greater in the FFR < 0.75 group than in the grey area group and the FFR > 0.80 group (all p < 0.05). The MLA in the FFR < 0.75 group was lower than that in the grey area group and the FFR > 0.80 group (both P < 0.05). There were no significant differences in the PL, TPV, or ND between the grey area and the FFR > 0.80 group, but there was a significant difference in the FAI. The coronary artery lesions with FFRs ≤ 0.75 had the greatest FAI values. Multivariate analysis revealed that the perivascular FAI and PL density are significant predictors of myocardial ischaemia. The FAI has some predictive value for myocardial ischaemia (AUC = 0.781). After building a combination model using the FAI and plaque length, the predictive power increased (AUC, 0.781 vs. 0.918), and the change was statistically significant (P < 0.001). The combined model of PL + FAI demonstrated great diagnostic efficacy in identifying myocardial ischaemia caused by haemodynamic impairment; the lower the FFR was, the greater the FAI. Thus, the PL + FAI could be a combined measure to securely rule out myocardial ischaemia.

Triglyceride glucose index is associated with functional coronary artery stenosis in hypertensive patients.

Background: 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. Methods: 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. Results: 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). Conclusion: 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.

CT-Assessment of Epicardial Fat Identifies Increased Inflammation at the Level of the Left Coronary Circulation in Patients with Atrial Fibrillation.

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.

Evaluation of peri-plaque pericoronary adipose tissue attenuation in coronary atherosclerosis using a dual-layer spectral detector CT.

Purpose: 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. Methods: 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. Results: 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. Conclusion: 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.

Correlations between the peripheral coronary fat attenuation index based on computed tomography images, high-risk plaque and degree of coronary artery stenosis in patients with coronary atherosclerosis.

BACKGROUND: Coronary artery disease can be quantified by measuring the fat attenuation index (FAI). OBJECTIVE: To explore the correlations between FAI, high-risk plaque and the degree of coronary artery stenosis. METHODS: 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. RESULTS: 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. CONCLUSION: 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.