A preliminary coronary computed tomography angiography-based study of perivascular fat attenuation index: relation with epicardial adipose tissue and its distribution over the entire coronary vasculature

Phenotyping atherosclerotic plaque and perivascular adipose tissue: signalling pathways and clinical biomarkers in atherosclerosis

Computed tomography coronary angiography provides a non-invasive evaluation of coronary artery disease that includes phenotyping of atherosclerotic plaques and the surrounding perivascular adipose tissue (PVAT). Image analysis techniques have been developed to quantify atherosclerotic plaque burden and morphology as well as the associated PVAT attenuation, and emerging radiomic approaches can add further contextual information. PVAT attenuation might provide a novel measure of vascular health that could be indicative of the pathogenetic processes implicated in atherosclerosis such as inflammation, fibrosis or increased vascularity. Bidirectional signalling between the coronary artery and adjacent PVAT has been hypothesized to contribute to coronary artery disease progression and provide a potential novel measure of the risk of future cardiovascular events. However, despite the development of more advanced radiomic and artificial intelligence-based algorithms, studies involving large datasets suggest that the measurement of PVAT attenuation contributes only modest additional predictive discrimination to standard cardiovascular risk scores. In this Review, we explore the pathobiology of coronary atherosclerotic plaques and PVAT, describe their phenotyping with computed tomography coronary angiography, and discuss potential future applications in clinical risk prediction and patient management.

Evaluating Pericoronary Adipose Tissue Attenuation to Predict Cardiovascular Events: A Multicenter Study in East Asians

Background

Pericoronary adipose tissue attenuation (PCATA) is a novel imaging biomarker of pericoronary inflammation associated with coronary artery disease. Several studies have reported the usefulness of PCATA among people of European ethnicity; however, data are lacking concerning those of Asian ethnicity.

Objectives

This multicenter study aimed to evaluate the effect of PCATA on prognosis in East Asian patients.

Methods

Between August 2011 and December 2016, 2,172 patients underwent clinically indicated coronary computed tomography angiography (CTA) at 4 hospitals in Japan. Among them, 1,270 patients were analyzed. PCATA was evaluated using coronary CTA to measure pericoronary adipose tissue density surrounding the 3 major coronary arteries. The outcomes were composite cardiovascular events, including cardiovascular death and acute coronary syndrome; 33 cardiovascular events observed during a median follow-up of 6.0 years (Q1-Q3: 3.6-8.2 years).

Results

Right coronary artery (RCA)-PCATA was significantly higher in patients with cardiovascular events than in those without (-63.7 ± 8.9 HU vs -67.4 ± 9.1 HU, respectively; P = 0.021). High RCA-PCATA was significantly associated with cardiovascular events in a model that included the Hisayama risk score and adverse coronary CTA findings (HR: 1.55; 95% CI: 1.07-2.24; P = 0.019).

Conclusions

High RCA-PCATA showed significant association with future cardiovascular events after adjusting conventional risk factors and adverse coronary CTA findings in East Asian patients who underwent clinically indicated coronary CTA.

Quantitative plaque characteristics and pericoronary fat attenuation index enhance risk prediction of unstable angina in nonobstructive lesions

AIM

The role of quantitative plaque characterization and pericoronary fat attenuation index (FAI) in nonobstructive lesions is uncertain. Hence, this study aimed to investigate artificial intelligence (AI)-based plaque characterization and pericoronary FAI in patients with nonobstructive lesions to enhance risk prediction of unstable angina.

MATERIALS AND METHODS

This study was conducted using the clinical data of 408 patients with cardiovascular disease diagnosed with angina pectoris. A coronary computed tomography angiography examination was performed, and quantitative plaque characteristics and pericoronary FAI were analyzed.

RESULTS

Of the 408 patients with angina, 130 had nonobstructive lesions and 278 had obstructive ones. No significant difference in pericoronary FAI was observed between patients with nonobstructive and obstructive lesions. In patients with nonobstructive lesions, the plaque length and pericoronary FAI were significantly higher in patients with unstable angina than in those with stable angina. In patients with obstructive lesions, the plaque fibrolipid volume and percentage were significantly higher in patients with unstable angina than in those with stable angina, and the narrowest lumen area was significantly smaller. Left anterior descending peripheral (peri-LAD) FAI > -83 HU or total plaque length >20.17 mm were independent predictors of unstable angina in patients with nonobstructive lesions. In patients with obstructive lesions, peri-LAD FAI > -77 HU, total lipid volume >12.6 mm3, and narrowest lumen area ≤2.25 mm2 were independent predictors of unstable angina.

CONCLUSION

Pericoronary FAI and total plaque length may be suitable imaging biomarkers for AI-based prediction of the occurrence of unstable angina in patients with nonobstructive lesions.

Predictive value of pericoronary fat attenuation index for graft occlusion after coronary artery bypass grafting

PURPOSE

Based on coronary computed tomography angiography (CCTA), this study aimed to evaluate the predictive value of pericoronary fat attenuation index (FAI) for graft occlusion in patients following coronary artery bypass grafting (CABG).

MATERIALS AND METHODS

The clinical and imaging data of 100 patients with coronary artery disease (CAD) who underwent CCTA and subsequently received successful CABG between December 2012 and March 2024 were retrospectively collected. According to the subsequent CCTA evaluation of grafts, they were categorized into occlusion group (n = 27) and patency group (n = 73). Based on CCTA images, FAI of the proximal segment of the three coronary arteries and epicardial adipose tissue (EAT) parameters were measured and compared between the two groups. The Cox regression model was employed to screen the independent predictors of graft occlusion. The predictive model was constructed, and the receiver operating characteristic (ROC) curve was drawn to evaluate the diagnostic performance of the model.

RESULTS

Among the 100 cases, 74 were males, with a mean age was 62.42 ± 7.57 years. During the 15.50 (5.00, 36.75) months follow-up period, grafting vessel occlusion occurred in 27 patients (27.0%). The right coronary artery (RCA) in occlusion group was -73.36 ± 7.24HU, which was notably higher compared to patency group (-79.93 ± 9.75HU) (P < 0.05). Multivariable Cox regression analysis indicated that RCA FAI (HR = 5.205, 95% CI 1.938-13.979; P = 0.001) was independently correlated with graft occlusion, with an optimal cutoff value of -79.39 HU.RCA FAI added incremental prognostic value beyond clinical characteristics for patients following CABG (AUC 0.784 vs. 0.677, P = 0.027).

CONCLUSIONS

The RCA FAI can serve as a crucial predictor for graft occlusion in patients following CABG, enabling early identification of high-risk individuals and facilitating timely and effective intervention measures to enhance patient prognosis.

Patient-Level Pericoronary Adipose Tissue Mean Attenuation: Associations with Plaque Characteristics

Pericoronary adipose tissue attenuation (PCATa), observed from coronary computed tomography angiography (CCTA), is emerging as an inflammation marker. This study evaluated the relationship between PCATa and plaque characteristics, including plaque type, burden, and coronary calcification. An observational study was conducted on 466 patients with suspected chronic coronary syndrome who underwent clinically indicated CCTA. PCATa was measured along the proximal 40 mm of the coronary arteries and averaged to represent the patient's level. Plaque type was assessed, compositional plaque volumes were measured, and plaque burdens were quantified. The coronary calcification scores (CCSs) were categorized into groups. Statistical methods included t-tests, ANOVA, and multivariate regression analysis. PCATa differed significantly between calcified (-81.7 Hounsfield units (HU)) and soft (-77.5 HU) plaques. PCATa was positively associated with total plaque burden (β = 3.6) and non-calcified plaque burden (β = 7.0), but negatively correlated with calcified plaque burden (β = -3.5), independent of clinical factors and tube voltage (p < 0.05). The effect of PCATa was stronger when plaques of a different composition were absent. No significant differences in PCATa were found among different CCS groups. PCATa increased for calcified compared to soft plaques. The non-calcified plaque burden was associated with a higher PCATa, while the calcified plaque burden was associated with a lower PCATa.

Epicardial and pericoronary adipose tissue and coronary plaque burden in patients with Cushing's syndrome: a propensity score-matched study

PURPOSE

To assess coronary inflammation by measuring the volume and density of the epicardial adipose tissue (EAT), perivascular fat attenuation index (FAI) and coronary plaque burden in patients with Cushing's syndrome (CS) based on coronary computed tomography angiography (CCTA).

METHODS

This study included 29 patients with CS and 58 matched patients without CS who underwent CCTA. The EAT volume, EAT density, FAI and coronary plaque burden were measured. The high-risk plaque (HRP) was also evaluated. CS duration from diagnosis, 24-h urinary free cortisol (UFC), and abdominal visceral adipose tissue volume (VAT) of CS patients were recorded.

RESULTS

The CS group had higher EAT volume (146.9 [115.4, 184.2] vs. 119.6 [69.0, 147.1] mL, P = 0.006), lower EAT density (- 78.79 ± 5.89 vs. - 75.98 ± 6.03 HU, P = 0.042), lower FAI (- 84.0 ± 8.92 vs. - 79.40 ± 10.04 HU, P = 0.038), higher total plaque volume (88.81 [36.26, 522.5] vs. 44.45 [0, 198.16] mL, P = 0.010) and more HRP plaques (7.3% vs. 1.8%, P = 0.026) than the controls. The multivariate analysis suggested that CS itself (β [95% CI], 29.233 [10.436, 48.03], P = 0.014), CS duration (β [95% CI], 0.176 [0.185, 4.242], P = 0.033), and UFC (β [95% CI], 0.197 [1.803, 19.719], P = 0.019) were strongly associated with EAT volume but not EAT density, and EAT volume (β [95% CI] - 0.037[- 0.058, - 0.016], P = 0.001) not CS was strongly associated with EAT density. EAT volume, FAI and plaque burden increased (all P < 0.05) in 6 CS patients with follow-up CCTA. The EAT volume had a moderate correlation with abdominal VAT volume (r = 0.526, P = 0.008) in CS patients.

CONCLUSIONS

Patients with CS have higher EAT volume and coronary plaque burden but less inflammation as detected by EAT density and FAI. The EAT density is associated with EAT volume but not CS itself.

CT radiomic features reproducibility of virtual non-contrast series derived from photon-counting CCTA datasets using a novel calcium-preserving reconstruction algorithm compared with standard non-contrast series: focusing on epicardial adipose tissue

PURPOSE

We aimed to evaluate the reproducibility of computed tomography (CT) radiomic features (RFs) about Epicardial Adipose Tissue (EAT). The features derived from coronary photon-counting computed tomography (PCCT) angiography datasets using the PureCalcium (VNCPC) and conventional virtual non-contrast (VNCConv) algorithm were compared with true non-contrast (TNC) series.

METHODS

RFs of EAT from 52 patients who underwent PCCT were quantified using VNCPC, VNCConv, and TNC series. The agreement of EAT volume (EATV) and EAT density (EATD) was evaluated using Pearson's correlation coefficient and Bland-Altman analysis. A total of 1530 RFs were included. They are divided into 17 feature categories, each containing 90 RFs. The intraclass correlation coefficients (ICCs) and concordance correlation coefficients (CCCs) were calculated to assess the reproducibility of RFs. The cutoff value considered indicative of reproducible features was > 0.75.

RESULTS

the VNCPC and VNCConv tended to underestimate EATVs and overestimate EATDs. Both EATV and EATD of VNCPC series showed higher correlation and agreement with TNC than VNCConv series. All types of RFs from VNCPC series showed greater reproducibility than VNCConv series. Across all image filters, the Square filter exhibited the highest level of reproducibility (ICC = 67/90, 74.4%; CCC = 67/90, 74.4%). GLDM_GrayLevelNonUniformity feature had the highest reproducibility in the original image (ICC = 0.957, CCC = 0.958), exhibiting a high degree of reproducibility across all image filters.

CONCLUSION

The accuracy evaluation of EATV and EATD and the reproducibility of RFs from VNCPC series make it an excellent substitute for TNC series exceeding VNCConv series.

Stent-specific fat attenuation index is associated with target vessel revascularization after PCI

OBJECTIVES

To explore the clinical relevance of stent-specific perivascular fat attenuation index (FAI) in patients with stent implantation.

METHODS

A total of 162 consecutive patients who underwent coronary computed tomography angiography (CCTA) following stent implantation were retrospectively included. The stent-specific FAI at 2 cm adjacent to the stent edge was calculated. The endpoints were defined as target vessel revascularization (TVR) on the stented vessel after CCTA and readmission times due to chest pain after stent implantation. Binary logistic regression analysis for TVR and ordinal regression models were conducted to identify readmission times (0, 1, and ≥ 2) with generalized estimating equations on a per-stent basis.

RESULTS

On a per-stent basis, 9 stents (4.5%) experienced TVR after PCI at a median 30 months' follow-up duration. Stent-specific FAI differed significantly among subgroups of patients with stent implantation and different readmission times (p = 0.002); patients with at least one readmission had higher stent-specific FAI than those without readmission (p < 0.001). Bifurcated stents (odds ratio [OR]: 11.192, p = 0.001) and stent-specific FAI (OR: 1.189, p = 0.04) were independently associated with TVR. With no readmission as a reference, stent-specific FAI (OR: 0.984, p = 0.007) was an independent predictor for hospital readmission times ≥ 2 (p = 0.003).

CONCLUSION

Non-invasive stent-specific FAI derived from CCTA was found to be associated with TVR, which was a promising imaging marker for functional assessment in patients who underwent stent implantation.

CLINICAL RELEVANCE STATEMENT

Noninvasive fat attenuation index adjacent to the stents edge derived from CCTA, an imaging marker reflecting the presence of inflammation acting on the neointimal tissue at the sites of coronary stenting, might be relevant clinically with target vessel revascularization.

KEY POINTS

• Non-invasive stent-specific FAI derived from CCTA was associated with TVR (OR: 1.189 [95% CI: 1.007-1.043], p = 0.04) in patients who underwent stent implantation. • Stent-specific FAI significantly differed among a subgroup of patients with chest pain after stent implantation and with different readmission times (p = 0.002); the patients with at least one readmission had higher stent-specific FAI than those without readmission (p < 0.001). • Non-invasive stent-specific FAI derived from CCTA could be used as an imaging maker for the functional assessment of patients following stent implantation.

Diagnostic Performance of Machine Learning-Derived Radiomics Signature of Pericoronary Adipose Tissue in Coronary Computed Tomography Angiography for Coronary Artery In-Stent Restenosis

RATIONALE AND OBJECTIVES

Coronary inflammation can alter the perivascular fat phenotype. Hence, we aimed to assess the diagnostic performance of radiomics features of pericoronary adipose tissue (PCAT) in coronary computed tomography angiography (CCTA) for in-stent restenosis (ISR) after percutaneous coronary intervention.

MATERIALS AND METHODS

In this study, 165 patients with 214 eligible vessels were included, and ISR was found in 79 vessels. After evaluating clinical and stent characteristics, peri-stent fat attenuation index, and PCAT volume, 1688 radiomics features were extracted from each peri-stent PCAT segmentation. The eligible vessels were randomly categorized into training and validation groups in a ratio of 7:3. After performing feature selection using Pearson's correlation, F test, and least absolute shrinkage and selection operator analysis, radiomics models and integrated models that combined selected clinical features and Radscore were established using five different machine learning algorithms (logistic regression, support vector machine, random forest, stochastic gradient descent, and XGBoost). Subgroup analysis was performed using the same method for patients with stent diameters of ≤ 3 mm.

RESULTS

Nine significant radiomics features were selected, and the areas under the curves (AUCs) for the radiomics model and the integrated model were 0.69 and 0.79, respectively, for the validation group. The AUCs of the subgroup radiomics model based on 15 selected radiomics features and the subgroup integrated model were 0.82 and 0.85, respectively, for the validation group, which showed better diagnostic performance.

CONCLUSION

CCTA-based radiomics signature of PCAT has the potential to identify coronary artery ISR without additional costs or radiation exposure.

Exploring the Associations Between Non-Traditional Lipid Parameters and Epicardial Adipose Tissue Volume

The aim of this retrospective study was to determine the relationship between non-traditional lipid parameters and epicardial adipose tissue (EAT). A total of 770 patients with coronary computed tomography angiography examinations were included. The non-traditional lipid parameters included the atherogenic index of plasma (AIP), the atherogenic coefficient (AC), monocyte to high-density lipoprotein cholesterol (HDL-C) ratio (MHR), and lipoprotein combined index (LCI). To investigate the association between non-conventional lipid markers and the EAT-volume (EAT-v), a univariate and multivariate analyses were conducted. The receiver operating characteristic (ROC) analysis was used to compare the predictive ability among the four non-traditional lipid parameters. In the univariate analysis, we identified factors that might have effects on EAT-v (all P<.05) and adjusted for these in the multivariate analysis. We found that except for MHR, other non-traditional lipid parameters were still associated with high EAT-v after adjustment (all P<.05). In the ROC analysis, the area under the curve (AUC) of AIP was greater than that of other non-traditional lipid parameters and lipid profiles. There was an association between both non-traditional lipid parameters and EAT-v. After adjustment, the AIP remained an independent predictor of EAT-v and it outperformed other non-traditional lipid parameters.

Impact of pericoronary adipose tissue attenuation on recurrence after radiofrequency catheter ablation for atrial fibrillation

BACKGROUND

Inflammation plays a vital role in the occurrence and progression of atrial fibrillation (AF). The association between pericoronary adipose tissue attenuation (PCATA) and AF recurrence following ablation has not been fully clarified.

HYPOTHESIS

We aimed to evaluate the association between PCATA and AF recurrence after radiofrequency catheter ablation (RFCA).

METHODS

Patients who underwent the first RFCA for AF and performed coronary computed tomography angiography before ablation between 2018 and 2021 were enrolled. The predictive values of PCATA for AF recurrence after ablation were investigated. The area under curve (AUC), relative integrated discrimination improvement (IDI), and categorical free net reclassification improvement (NRI) were used to assess the discrimination ability of different models for AF recurrence.

RESULTS

During 1-year follow-up, 34.1% patients experienced AF recurrence. The multivariable analysis model revealed that PCATA of the right coronary artery (RCA) was an independent risk factor for AF recurrence. Patients with a high level of RCA-PCATA had a high risk of recurrence, after adjusting for other risk factors by restricted cubic splines. The performance in predicting AF recurrence was significantly improved by adding the marker of RCA-PCATA to the clinical model (AUC: 0.724 vs. 0.686, p = .024), with a relative IDI of 0.043 (p = .006) and continuous NRI of 0.521 (p < .001).

CONCLUSIONS

PCATA of RCA was independently associated with AF recurrence after ablation. PCATA may be helpful for risk classification for AF ablation patients.

Pericoronary Adipose Tissue as a Marker of Cardiovascular Risk: JACC Review Topic of the Week

Vascular inflammation is a key driver in atherosclerotic progression and plaque rupture. Recent evidence has shown that coronary computed tomography provides a noninvasive method of quantifying coronary inflammation by mapping changes in pericoronary adipose tissue (PCAT) radiodensity, which are associated with cardiovascular diseases. However, there are significant knowledge gaps in the performance and measurement of PCAT that complicate its interpretation. In this review the authors aim to summarize the role of PCAT in cardiac imaging and explore the clinical implications and applicability as a novel biomarker of cardiovascular risk, as well as to discuss its limitations and potential pitfalls.