Additive value of epicardial adipose tissue quantification to coronary CT angiography-derived plaque characterization and CT fractional flow reserve for the prediction of lesion-specific ischemia

Relationship between left atrium, epicardial fat and severity of atrial fibrillation

To investigate the relationship between left atrium (LA) and epicardial adipose tissue (EAT) parameters and different disease severities (paroxysmal and persistent) in patients with atrial fibrillation (AF). A total of 115 patients with AF (58 paroxysmal and 57 persistent) who underwent cardiac computed tomography angiography (CTA) at our institution between October 2021 and May 2022 were included. The left atrium volume index (LAVI) and left atrium fractal dimension (LAFD) were measured for each patient. EAT volumes and attenuation values for total heart and LA in early and delayed enhancement phases were calculated using semi-automated software. LA and EAT parameters were compared with patients with paroxysmal and persistent AF. Compared with paroxysmal AF, persistent AF had significantly greater LAVI (33.60 ml/m2 vs. 26.65 ml/m2, P < 0.001) and LAFD (1.31 vs. 1.22, P = 0.001). At both early and late enhancement, the total EAT volume (136.29 cm3 vs. 88.68 cm3, 152.30 cm3 vs. 88.96 cm3; all P < 0.001) and attenuation values (-84.00 HU vs. -87.50 HU, -83.00 HU vs. -86.00 HU; all P < 0.05) were significantly higher in persistent AF than in paroxysmal AF. Additionally, LA EAT volumes (15.53 cm3 vs. 8.19 cm3, 18.57 cm3 vs. 9.26 cm3; all P < 0.001) and attenuation values (-74.00 HU vs. -77.00 HU, -75.00 HU vs. -77.00 HU; all P < 0.05) were significantly larger in persistent AF compared with paroxysmal AF, in both early and late enhancement phases. Correlation analysis showed that both LA (r = 0.381, 0.310; P < 0.05) and EAT parameters (r = 0.524, 0.334, 0.665, 0.208, 0.537, 0.223, 0.606, 0.276; P < 0.05) were positively associated with AF severity. Both EAT (volume and attenuation values) and parameters for assessing LA size and morphology, including LAVI and LAFD, were related to the severity of AF.

Improved evaluation of coronary artery diseases from patients with coronary calcification utilizing FFRCT: a comparative study against CCTA

OBJECTIVE

This multicenter study evaluated the diagnostic accuracy of coronary computed tomography angiography (CCTA) and computed tomography-derived fractional flow reserve (FFRCT) in diagnosing coronary artery disease (CAD), focusing on the impact of coronary calcification, using invasive coronary angiography (ICA) as the reference.

METHODS

The study analyzed 4172 patients from 3 centers who underwent CCTA and FFRCT between August 2021 and August 2022. Exclusion criteria included the absence of ICA within 90 days after CCTA, left main disease, previous coronary revascularization, or unmeasurable Agatston score (AS).

RESULTS

The study included 492 patients. In patients with less than mild calcification (AS < 100), the area under the receiver operating characteristic curve (AUC) for FFRCT was superior to CCTA (0.87 [95% confidence interval (CI): 0.82-0.92] vs. 0.78 [95% CI: 0.73-0.84], P = 0.009). As the severity of calcification increased, both CCTA and FFRCT showed reduced diagnostic efficacy, but FFRCT maintained higher accuracy. In patients with greater than moderate calcification (AS ≥ 100), FFRCT significantly outperformed CCTA (0.80 [95% CI: 0.74-0.85] vs. 0.62 [95% CI: 0.56-0.68], P < 0.001). Furthermore, integrating FFRCT with CCTA and baseline factors using least absolute shrinkage and selection operator (LASSO) improved diagnostic performance in patients with greater than moderate calcification (AS≥100) than FFRCT (0.85 [95% CI: 0.78-0.92] vs. 0.81 [95% CI: 0.72-0.90], P = 0.003).

CONCLUSION

FFRCT offers superior diagnostic accuracy over CCTA, particularly in patients with moderate to severe calcification. Furthermore, the LASSO model enhances diagnostic performance in these cases, demonstrating potential for improving CAD diagnosis in patients with significant coronary calcification.

The prognostic value of epicardial and pericoronary adipose tissue in heart failure with preserved ejection fraction using coronary computed tomography angiography

OBJECTIVES

To assess the prognostic significance of epicardial adipose tissue volume (EATv) and pericoronary adipose tissue attenuation (PCATa) in patients with heart failure with preserved ejection fraction (HFpEF).

METHODS

This retrospective study was based on HFpEF and controls who underwent coronary CT angiography (CCTA) screening to rule out coronary disease. Comparisons of EATv and PCATa were made between HFpEF patients and a control group, using statistical analyses including Kaplan-Meier and Cox regression to assess prognostic significance.

RESULTS

A total of 224 patients were retrospectively analysed. The EATv was 56.1 ± 11.9 cm3 and PCATa in the right coronary artery (PCATa-RCA) was -74.7 HU ± 3.82 in HFpEF patients, which increased significantly compared with controls. Among them, 112 HFpEF patients (mean age: 71.9 ± 8.5 years; 40% male) were followed up for a median of 27 ± 0.6 months (range 2-47 months). EATv and PCATa-RCA were predictive of outcome with an optimal threshold of 56.29 cm3 and -71.17 HU, respectively. In Kaplan-Meier analysis, the high EATv and PCATa-RCA attenuation had significantly higher rates of composite outcomes (log-rank test, all P < .01). EATv and PCATa-RCA were independently predictive of outcome following adjustment for confounding variables (EATv: hazard ratio [HR] 1.03; 95% CI (1.01-1.06); P < .01, PCTAa-RCA: HR 1.44; 95% CI 1.27-1.62; P < .001)).

CONCLUSIONS

Increased EATv and PCATa-RCA are associated with worse clinical outcomes in HFpEF patients.

ADVANCES IN KNOWLEDGE

This study highlights the potential of CCTA-derived adipose tissue metrics as novel, non-invasive biomarkers for risk stratification in HFpEF.

Prognostic utility of dynamic changes in epicardial adipose tissue in patients undergoing transcatheter aortic valve replacement

BACKGROUND

Epicardial Adipose Tissue (EAT) volume is associated with the risk of cardiovascular events, which can be assessed by cardiac computed tomography. However, he optimal method and their prognostic utility in patients following transcatheter aortic valve replacement (TAVR) is unknown.

METHODS

We evaluated 258 participants, focusing on changes in EAT volume using cardiac CT enhancement. EAT volume was automatically computed as three-dimensional voxels between -190 to -30 HU on contrast-enhanced slices. Univariate and multivariable Cox regression analyses were conducted to assess the association of various clinical parameters and EAT volume indices with major adverse cardiovascular events (MACE).

RESULTS

During a median follow-up of 2.0 years [IQR, 1.8-2.3 years], 34 participants (median age 73 [IQR: -13.1 to -8.3) years, 55.4 % male) experiencing MACE. The optimal cutoff values for EAT volume change fraction (EATVCF) was 15.2 %, determined by the Youden-index. Kaplan-Meier curve analysis revealed that patients with high EATVCF were at higher risk (p < .01). In Cox regression, EATVCF (hazard ratio [HR]: 0.92, 95 % CI: 0.87 to 0.97, p = .001) remained significantly associated with MACE after adjusting for clinical factors. The addition of EATVCF to the clinical model increased the net Reclassification Improvement (NRI) by 30.1 % (95 % CI: 0.07-1.16).

CONCLUSION

EAT volume change fraction emerged as a significant predictor of MACE post-TAVR, highlighting the clinical value of EAT volume assessment in cardiovascular risk stratification.

Getting closer to the coronary arteries: A bibliometric analysis of CT-based adipose tissue imaging in coronary artery disease

The aim of this study is to conduct a comprehensive bibliometric analysis of CT-based adipose tissue imaging related to coronary artery disease (CAD) to investigate the dynamic development of this field. Web of Science Core Collection was used as our data source to identify relevant documents limited to articles or review articles and written in English with no time restrictions. Then we analyzed the whole trend of publications and utilized VOSviewer and Bibliometrix to conduct a bibliometric analysis including citations, keywords, countries, institutions, authors as well as co-citation analyses of cited references and sources. A total of 629 documents including 560 articles and 69 reviews from 1992 to 2023 were included. The trend of publications was divided into 3 phases and overall exhibited a constant rise. Based on the co-occurrence network of keywords analysis, 3 clusters centered on visceral, epicardial, pericoronary adipose tissue respectively and 1 cluster related to cardiovascular risk factors were identified, meanwhile determining the evolution of fat research. Co-citation analysis suggested that sources were divided into metabolism-related and cardiovascular-related journals. The USA ranked first with 228 documents and 12,086 citations among 47 countries and 1002 institutions, both at the author and institutional levels. In conclusion, this study demonstrated the thriving research field of the impact of CT-based adipose tissue assessment on coronary artery disease, offering a better understanding of the current state of research and valuable insights for future studies and collaborations.

Intra-individual comparison of epicardial adipose tissue characteristics on coronary CT angiography between photon-counting detector and energy-integrating detector CT systems

PURPOSE

To explore the potential differences in epicardial adipose tissue (EAT) volume and attenuation measurements between photon-counting detector (PCD) and energy-integrating detector (EID)-CT systems.

METHODS

Fifty patients (mean age 69 ± 8 years, 41 male [82 %]) were prospectively enrolled for a research coronary CT angiography (CCTA) on a PCD-CT within 30 days after clinical EID-based CCTA. EID-CT acquisitions were reconstructed using a Bv40 kernel at 0.6 mm slice thickness. The PCD-CT acquisition was reconstructed at a down-sampled resolution (0.6 mm, Bv40; [PCD-DS]) and at ultra-high resolutions (PCD-UHR) with a 0.2 mm slice thickness and Bv40, Bv48, and Bv64 kernels. EAT segmentation was performed semi-automatically at about 1 cm intervals and interpolated to cover the whole epicardium within a threshold of -190 to -30 HU. A subgroup analysis was performed based on quartile groups created from EID-CT data and PCD-UHRBv48 data. Differences were measured using repeated-measures ANOVA and the Friedman test. Correlations were tested using Pearson's and Spearman's rho, and agreement using Bland-Altman plots.

RESULTS

EAT volumes significantly differed between some reconstructions (e.g.

EID-CT

138 ml [IQR 100, 188]; PCD-DS: 147 ml [110, 206]; P<0.001). Overall, correlations between PCD-UHR and EID-CT EAT volumes were excellent, e.g. PCD-UHRBv48: r: 0.976 (95 % CI: 0.958, 0.987); P<0.001; with good agreement (mean bias: -9.5 ml; limits of agreement [LoA]: -40.6, 21.6). On the other hand, correlations regarding EAT attenuation was moderate, e.g. PCD-UHRBV48: r: 0.655 (95 % CI: 0.461, 0.790); P<0.001; mean bias: 6.5 HU; LoA: -2.0, 15.0.

CONCLUSION

EAT attenuation and volume measurements demonstrated different absolute values between PCD-UHR, PCD-DS as well as EID-CT reconstructions, but showed similar tendencies on an intra-individual level. New protocols and threshold ranges need to be developed to allow comparison between PCD-CT and EID-CT data.

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

BACKGROUND

Coronary 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 METHODS

We 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.

RESULTS

Overall, 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.

CONCLUSION

CT-FFR was superior to CT anatomical, plaque morphology, and PCAT assessment to detect functionally significant stenoses in patients with severe AS.

CLINICAL RELEVANCE STATEMENT

CT-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.

Excessive accumulation of epicardial adipose tissue promotes microvascular obstruction formation after myocardial ischemia/reperfusion through modulating macrophages polarization

BACKGROUND

Owing to its unique location and multifaceted metabolic functions, epicardial adipose tissue (EAT) is gradually emerging as a new metabolic target for coronary artery disease risk stratification. Microvascular obstruction (MVO) has been recognized as an independent risk factor for unfavorable prognosis in acute myocardial infarction patients. However, the concrete role of EAT in the pathogenesis of MVO formation in individuals with ST-segment elevation myocardial infarction (STEMI) remains unclear. The objective of the study is to evaluate the correlation between EAT accumulation and MVO formation measured by cardiac magnetic resonance (CMR) in STEMI patients and clarify the underlying mechanisms involved in this relationship.

METHODS

Firstly, we utilized CMR technique to explore the association of EAT distribution and quantity with MVO formation in patients with STEMI. Then we utilized a mouse model with EAT depletion to explore how EAT affected MVO formation under the circumstances of myocardial ischemia/reperfusion (I/R) injury. We further investigated the immunomodulatory effect of EAT on macrophages through co-culture experiments. Finally, we searched for new therapeutic strategies targeting EAT to prevent MVO formation.

RESULTS

The increase of left atrioventricular EAT mass index was independently associated with MVO formation. We also found that increased circulating levels of DPP4 and high DPP4 activity seemed to be associated with EAT increase. EAT accumulation acted as a pro-inflammatory mediator boosting the transition of macrophages towards inflammatory phenotype in myocardial I/R injury through secreting inflammatory EVs. Furthermore, our study declared the potential therapeutic effects of GLP-1 receptor agonist and GLP-1/GLP-2 receptor dual agonist for MVO prevention were at least partially ascribed to its impact on EAT modulation.

CONCLUSIONS

Our work for the first time demonstrated that excessive accumulation of EAT promoted MVO formation by promoting the polarization state of cardiac macrophages towards an inflammatory phenotype. Furthermore, this study identified a very promising therapeutic strategy, GLP-1/GLP-2 receptor dual agonist, targeting EAT for MVO prevention following myocardial I/R injury.

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.

Epicardial adipose tissue as an independent predictor of long-term outcome in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement

BACKGROUND

Accurate risk stratification is important to improve patient selection and outcome of patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). As epicardial adipose tissue (EAT) is discussed to be involved in cardiovascular disease, it could be useful as a marker of poor prognosis in patients with severe AS undergoing TAVR.

METHODS

A total of 416 patients diagnosed with severe AS by transthoracic echocardiography were assigned for TAVR and enrolled for systematic assessment. Patients underwent clinical surveys and 5-year long-term follow-up, with all-cause mortality as the primary endpoint. EAT volume was quantified on pre-TAVR planning CTs. Patients were retrospectively dichotomized at the median of 74 cm3 of EAT into groups with low EAT and high EAT volumes. Mortality rates were compared using Kaplan-Meyer plots and uni- and multivariable cox regression analyses.

RESULTS

A total number of 341 of 416 patients (median age 80.9 years, 45% female) were included in the final analysis. Patients with high EAT volumes had similar short-term outcome (p = 0.794) but significantly worse long-term prognosis (p = 0.023) compared to patients with low EAT volumes. Increased EAT volumes were associated with worse long-term outcome (HR1.59; p = 0.031) independently from concomitant cardiovascular risk factors, general type of AS, and functional echocardiography parameters of AS severity (HR1.69; p = 0.013).

CONCLUSION

Increased EAT volume is an independent predictor of all-cause mortality in patients with severe AS undergoing TAVR. It can be easily obtained from pre-TAVR planning CTs and may thus qualify as a novel marker to improve prognostication and management of patient with severe AS.

TRIAL REGISTRATION

DRKS, DRKS00024479.

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.

Machine learning to predict hemodynamically significant CAD based on traditional risk factors, coronary artery calcium and epicardial fat volume

We sought to establish an explainable machine learning (ML) model to screen for hemodynamically significant coronary artery disease (CAD) based on traditional risk factors, coronary artery calcium (CAC) and epicardial fat volume (EFV) measured from non-contrast CT scans. 184 symptomatic inpatients who underwent Single Photon Emission Computed Tomography/Myocardial Perfusion Imaging (SPECT/MPI) and Invasive Coronary Angiography (ICA) were enrolled. Clinical and imaging features (CAC and EFV) were collected. Hemodynamically significant CAD was defined when coronary stenosis severity ≥ 50% with a matched reversible perfusion defect in SPECT/MPI. Data was randomly split into a training cohort (70%) on which five-fold cross-validation was done and a test cohort (30%). The normalized training phase was preceded by the selection of features using recursive feature elimination (RFE). Three ML classifiers (LR, SVM, and XGBoost) were used to construct and choose the best predictive model for hemodynamically significant CAD. An explainable approach based on ML and the SHapley Additive exPlanations (SHAP) method was deployed to generate individual explanation of the model's decision. In the training cohort, hemodynamically significant CAD patients had significantly higher age, BMI and EFV, higher proportions of hypertension and CAC comparing with controls (P all < .05). In the test cohorts, hemodynamically significant CAD had significantly higher EFV and higher proportion of CAC. EFV, CAC, diabetes mellitus (DM), hypertension, and hyperlipidemia were the highest ranking features by RFE. XGBoost produced better performance (AUC of 0.88) compared with traditional LR model (AUC of 0.82) and SVM (AUC of 0.82) in the training cohort. Decision Curve Analysis (DCA) demonstrated that XGBoost model had the highest Net Benefit index. Validation of the model also yielded a favorable discriminatory ability with the AUC, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of 0.89, 68.0%, 96.8%, 94.4%, 79.0% and 83.9% in the XGBoost model. A XGBoost model based on EFV, CAC, hypertension, DM and hyperlipidemia to assess hemodynamically significant CAD was constructed and validated, which showed favorable predictive value. ML combined with SHAP can offer a transparent explanation of personalized risk prediction, enabling physicians to gain an intuitive understanding of the impact of key features in the model.

Association of Epicardial Adipose Tissue With Left Ventricular Strain and MR Myocardial Perfusion in Patients With Known Coronary Artery Disease

BACKGROUND

Epicardial adipose tissue (EAT) may have a paracrine effect on coronary microcirculation and myocardium. However, it is unclear whether EAT is linked to cardiac function and perfusion.

PURPOSE

To investigate the association of EAT with left ventricular (LV) strain and myocardial perfusion in patients with coronary artery disease (CAD).

STUDY TYPE

Retrospective.

POPULATION

A total of 78 patients with CAD and 20 healthy controls. The patients were further divided into high (n = 39) and low EAT volume (n = 39) groups according to median EAT volume.

FIELD STRENGTH/SEQUENCE

A 1.5 T, balanced steady-state free precession, inversion recovery prepared echo-planar, and segmented-turbo fast low-angle shot (FLASH) phase-sensitive inversion recovery (PSIR) sequences.

ASSESSMENT

EAT volume was measured by manually tracing the epicardial border and the visceral layer of pericardium on the short-axis cine stacks. LV strain parameters included global radial (GRS), circumferential (GCS), and longitudinal peak strain (GLS). Perfusion indices included upslope, perfusion index, time-to-maximum signal intensity (TTM), and maximum signal intensity (MaxSI).

STATISTICAL TESTS

One-way analysis of variance or Kruskal-Wallis rank tests, Chi-squared or Fisher exact tests. Multivariate linear regression analyses. A P value < 0.05 was considered statistically significant.

RESULTS

The parameters of GRS GCS, GLS, upslope, perfusion index, and MaxSI were significantly lower in the patients when compared to the controls. Moreover, the high EAT volume group presented significantly longer TTM values and lower GRS, GCS, GLS, upslope, perfusion index, and MaxSI than the low EAT volume group. Multivariate linear regression analyses demonstrated that EAT was independently associated with GRS, GCS, GLS, upslope, perfusion index, TTM, and MaxSI in patients. EAT and upslope were independently associated with GRS, while EAT and perfusion index were both independently associated with GCS and GLS.

DATA CONCLUSION

EAT was associated with parameters of LV function and perfusion, and myocardial perfusion was independently associated with LV strain in patients with CAD.

EVIDENCE LEVEL

3.

TECHNICAL EFFICACY

Stage 3.

Clinical value of perivascular fat attenuation index and computed tomography derived fractional flow reserve in identification of culprit lesion of subsequent acute coronary syndrome

Purpose

To explore the potential of perivascular fat attenuation index (FAI) and coronary computed tomography angiography (CCTA) derived fractional flow reserve (CT-FFR) in the identification of culprit lesion leading to subsequent acute coronary syndrome (ACS).

Methods

Thirty patients with documented ACS event who underwent invasive coronary angiography (ICA) from February 2019 to February 2021 and had received CCTA in the previous 6 months were collected retrospectively. 40 patients with stable angina pectoris (SAP) were matched as control group according to sex, age and risk factors. The study population has a mean age of 59.3 ± 12.3 years, with a male prevalence of 81.4%. The plaque characteristics, perivascular fat attenuation index (FAI), and coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) of 32 culprit lesions and 30 non-culprit lesions in ACS patients and 40 highest-grade stenosis lesions in SAP patients were statistically analyzed.

Results

FAI around culprit lesions was increased significantly (-72.4 ± 3.2 HU vs. -79.0 ± 7.7 HU, vs. -80.4 ± 7.0HU, all p < 0.001) and CT-FFR was decreased for culprit lesions of ACS patients [0.7(0.1) vs. 0.8(0.1), vs.0.8(0.1), p < 0.001] compared to other lesions. According to multivariate analysis, diameter stenosis (DS), FAI, and CT-FFR were significant predictors for identification of the culprit lesion. The integration model of DS, FAI, and CT-FFR showed the significantly highest area under the curve (AUC) of 0.917, compared with other single predictors (all p < 0.05).

Conclusions

This study proposes a novel integrated prediction model of DS, FAI, and CT-FFR that enhances the diagnostic accuracy of traditional CCTA for identifying culprit lesions that trigger ACS. Furthermore, this model also provides improved risk stratification for patients and offers valuable insights for predicting future cardiovascular events.

Assessment of epicardial adipose tissue on virtual non-contrast images derived from photon-counting detector coronary CTA datasets

OBJECTIVES

To assess epicardial adipose tissue (EAT) volume and attenuation of different virtual non-contrast (VNC) reconstructions derived from coronary CTA (CCTA) datasets of a photon-counting detector (PCD) CT-system to replace true non-contrast (TNC) series.

METHODS

Consecutive patients (n = 42) with clinically indicated CCTA and coronary TNC were included. Two VNC series were reconstructed, using a conventional (VNC_Conv) and a novel calcium-preserving (VNC_PC) algorithm. EAT was segmented on TNC, VNC_Conv, VNC_PC, and CCTA (CTA_-30) series using thresholds of -190 to -30 HU and an additional segmentation on the CCTA series with an upper threshold of 0 HU (CTA₀). EAT volumes and their histograms were assessed for each series. Linear regression was used to correlate EAT volumes and the Euclidian distance for histograms. The paired t-test and the Wilcoxon signed-rank test were used to assess differences for parametric and non-parametric data.

RESULTS

EAT volumes from VNC and CCTA series showed significant differences compared to TNC (all p < .05), but excellent correlation (all R² > 0.9). Measurements on the novel VNC_PC series showed the best correlation (R² = 0.99) and only minor absolute differences compared to TNC values. Mean volume differences were -12%, -3%, -13%, and +10% for VNC_Conv, VNC_PC, CTA_-30, and CTA₀ compared to TNC. Distribution of CT values on VNC_PC showed less difference to TNC than on VNC_Conv (mean attenuation difference +7% vs. +2%; Euclidean distance of histograms 0.029 vs. 0.016).

CONCLUSIONS

VNC_PC-reconstructions of PCD-CCTA datasets can be used to reliably assess EAT volume with a high accuracy and only minor differences in CT values compared to TNC. Substitution of TNC would significantly decrease patient's radiation dose.

KEY POINTS

• Measurement of epicardial adipose tissue (EAT) volume and attenuation are feasible on virtual non-contrast (VNC) series with excellent correlation to true non-contrast series (all R²>0.9). • Differences in VNC algorithms have a significant impact on EAT volume and CT attenuation values. • A novel VNC algorithm (VNC_PC) enables reliable assessment of EAT volume and attenuation with superior accuracy compared to measurements on conventional VNC- and CCTA-series.

Impact of epicardial adipose tissue volume on hemodynamically significant coronary artery disease in Chinese patients with known or suspected coronary artery disease

Background

Epicardial adipose tissue (EAT) is directly related to coronary artery disease (CAD), but little is known about its role in hemodynamically significant CAD. Therefore, our goal is to explore the impact of EAT volume on hemodynamically significant CAD.

Methods

Patients who underwent coronary computed tomography angiography (CCTA) and received coronary angiography within 30 days were retrospectively included. Measurements of EAT volume and coronary artery calcium score (CACs) were performed on a semi-automatic software based on CCTA images, while quantitative flow ratio (QFR) was automatically calculated by the AngioPlus system according to coronary angiographic images.

Results

This study included 277 patients, 112 of whom had hemodynamically significant CAD and showed higher EAT volume. In multivariate analysis, EAT volume was independently and positively correlated with hemodynamically significant CAD [per standard deviation (SD) cm3; odds ratio (OR), 2.78; 95% confidence interval (CI), 1.86-4.15; P < 0.001], but negatively associated with QFRmin (per SD cm3; β coefficient, -0.068; 95% CI, -0.109 to -0.027; P = 0.001) after adjustment for traditional risk factors and CACs. Receiver operating characteristics curve analysis demonstrated a significant improvement in predictive value for hemodynamically significant CAD with the addition of EAT volume to obstructive CAD alone (area under the curve, 0.950 vs. 0.891; P < 0.001).

Conclusion

In this study, we found that EAT volume correlated substantially and positively with the existence and severity of hemodynamically significant CAD in Chinese patients with known or suspected CAD, which was independent of traditional risk factors and CACs. In combination with obstructive CAD, EAT volume significantly improved diagnostic performance for hemodynamically significant CAD, suggesting that EAT could be a reliable noninvasive indicator of hemodynamically significant CAD.

Imaging subclinical coronary atherosclerosis to guide lipid management, are we there yet?

Atherosclerotic cardiovascular disease risk (ASCVD) is an ongoing epidemic, and lipid abnormalities are its primordial cause. Most individuals suffering a first ASCVD event are previously asymptomatic and often do not receive preventative therapies. The cornerstone of primary prevention has been the identification of individuals at risk through risk calculators based on clinical and laboratory traditional risk factors plus risk enhancers. However, it is well accepted that a clinical risk calculator misclassifies a significant proportion of individuals leading to the prescription of a lipid-lowering medication with very little yield or a missed opportunity for lipid-lowering agents with a potentially preventable event. The development of coronary artery calcium scoring (CAC) and CT coronary angiography (CCTA) provide complementary tools to directly visualize coronary plaque and other risk-modifying imaging components that can potentially provide individualized lipid management. Understanding patient selection for CAC or potentially CCTA and the risk implications of the different parameters provided, such as CAC score, coronary stenosis, plaque characteristics and burden, epicardial adipose tissue, and pericoronary adipose tissue, have grown more complex as technologies evolve. These parameters directly affect the shared decision with patients to start or withhold lipid-lowering therapies, to adjust statin intensity or LDL cholesterol goals. Emerging lipid lowering studies with non-invasive imaging as a guide to patient selection and treatment efficacy, plus the evolution of lipid lowering therapies from statins to a diverse armament of newer high-cost agents have pushed these two fields forward with a complex interaction. This review will discuss existing risk estimators, and non-invasive imaging techniques for subclinical coronary atherosclerosis, traditionally studied using CAC and more recently CCTA with qualitative and quantitative measurements. We will also explore the current data, gaps of knowledge and future directions on the use of these techniques in the risk-stratification and guidance of lipid management.

Determinants of Non-calcified Low-Attenuation Coronary Plaque Burden in Patients Without Known Coronary Artery Disease: A Coronary CT Angiography Study

Background

Although epicardial adipose tissue (EAT) is associated with coronary artery disease (CAD), it is unclear whether EAT volume (EAV) can be used to diagnose high-risk coronary plaque burden associated with coronary events. This study aimed to investigate (1) the prognostic impact of low-attenuation non-calcified coronary plaque (LAP) burden on patient level analysis, and (2) the association of EAV with LAP volume in patients without known CAD undergoing coronary computed tomography angiography (CCTA).

Materials and Methods

This retrospective study consisted of 376 patients (male, 57%; mean age, 65.2 ± 13 years) without known CAD undergoing CCTA. Percent LAP volume (%LAP, <30 HU) was calculated as the LAP volume divided by the vessel volume. EAT was defined as adipose tissue with a CT attenuation value ranging from −250 to −30 HU within the pericardial sac. The primary endpoint was a composite event of death, non-fatal myocardial infarction, and unstable angina and worsening symptoms requiring unplanned coronary revascularization >3 months after CCTA. The determinants of %LAP (Q4) were analyzed using a multivariable logistic regression model.

Results

During the follow-up period (mean, 2.2 ± 0.9 years), the primary endpoint was observed in 17 patients (4.5%). The independent predictors of the primary endpoint were %LAP (Q4) (hazard ratio [HR], 3.05; 95% confidence interval [CI], 1.09–8.54; p = 0.033] in the Cox proportional hazard model adjusted by CAD-RADS category. Cox proportional hazard ratio analysis demonstrated that %LAP (Q4) was a predictor of the primary endpoint, independnet of CAD severity, Suita score, EAV, or CACS. The independent determinants of %LAP (Q4) were CACS ≥218.3 (p < 0.0001) and EAV ≥125.3 ml (p < 0.0001). The addition of EAV to CACS significantly improved the area under the curve (AUC) to identify %LAP (Q4) than CACS alone (AUC, EAV + CACS vs. CACS alone: 0.728 vs. 0.637; p = 0.013).

Conclusions

CCTA-based assessment of EAV, CACS, and LAP could help improve personalized cardiac risk management by administering patient-suited therapy.