CT Quantification of Epicardial Fat: Implications for Cardiovascular Risk Assessment

Computed Tomography-derived Characterization of Pericoronary, Epicardial, and Paracardial Adipose Tissue and Its Association With Myocardial Ischemia as Assessed by Computed Fractional Flow Reserve

BACKGROUND

Increased pericoronary adipose tissue (PCAT) attenuation derived from coronary computed tomography (CT) angiography (CTA) relates to coronary inflammation and cardiac mortality. We aimed to investigate the association between CT-derived characterization of different cardiac fat compartments and myocardial ischemia as assessed by computed fractional flow reserve (FFRCT).

METHODS

In all, 133 patients (median 64 y, 74% male) with coronary artery disease (CAD) underwent CTA including FFRCT measurement followed by invasive FFR assessment (FFRINVASIVE). CT attenuation and volume of PCAT were quantified around the proximal right coronary artery (RCA), left anterior descending artery (LAD), and left circumflex artery (LCX). Epicardial adipose tissue (EAT) and paracardial adipose tissue (PAT; all intrathoracic adipose tissue outside the pericardium) were quantified in noncontrast cardiac CT datasets.

RESULTS

Median FFRCT was 0.86 [0.79, 0.91] and median FFRINVASIVE was 0.87 [0.81, 0.93]. Subjects with the presence of myocardial ischemia (n=26) defined by an FFRCT-threshold of ≤0.75 showed significantly higher RCA PCAT attenuation than individuals without myocardial ischemia (n=107) (-75.1±10.8 vs. -81.1±10.6 HU, P=0.011). In multivariable analysis adjusted for age, body mass index, sex and risk factors, increased RCA PCAT attenuation remained a significant predictor of myocardial ischemia. Between individuals with myocardial ischemia compared with individuals without myocardial ischemia, there was no significant difference in the volume and CT attenuation of EAT and PAT or in the PCAT volume of RCA, LAD, and LCX.

CONCLUSIONS

Increased RCA PCAT attenuation is associated with the presence of myocardial ischemia as assessed by FFR, while PCAT volume, EAT, and PAT are not.

Epicardial adipose tissue density and volume are related to subclinical atherosclerosis, inflammation and major adverse cardiac events in asymptomatic subjects

BACKGROUND

We investigated whether epicardial adipose tissue (EAT) volume and density are related to early atherosclerosis, plaque inflammation and major adverse cardiac events (MACE, cardiac death and myocardial infarction) in asymptomatic subjects.

METHODS

EAT volume and density were quantified from non-contrast cardiac CT in 456 asymptomatic individuals (age 60.3 ± 8.3; 68% with CCS>0) from the prospective EISNER trial. EAT volume and density were examined in relation to coronary calcium score (CCS), inflammatory biomarkers and MACE.

RESULTS

EAT volume was higher and EAT density lower in subjects with coronary calcium compared to subjects without [89 vs 74 cm³, p < 0.001] [-76.9 vs -75.7 HU,p = 0.024]. EAT volume was lowest in individuals with no coronary calcium and was significant higher in subjects with early atherosclerosis (CCS 1-99) [74 vs 87 cm³,p = 0.016] and in subjects with more advanced atherosclerosis (CCS≥100) [89 cm³,p = 0.002]). EAT volume was independently related to serum levels of PAI-1, and MCP-1 and inversely related to adiponectin and HDL-cholesterol (p < 0.05). EAT density was inversely related to PAI-1 and LDL-cholesterol and positively associated to adiponectin, sICAM-1 and HDL-cholesterol (p < 0.05). EAT density was more significantly associated with MACE [(HR 0.8, 95%CI:0.7-0.98), p = 0.029] than EAT volume or CCS.

CONCLUSION

EAT volume was higher and density lower in subjects with coronary calcium compared to subjects with CCS = 0, with similar EAT volume in CCS<100 and CCS≥100. Lower EAT density and increased EAT volume were associated with coronary calcification, serum levels of plaque inflammatory markers and MACE, suggesting that dysfunctional EAT may be linked to early plaque formation and inflammation.

Automated pericardium delineation and epicardial fat volume quantification from noncontrast CT

PURPOSE

The authors aimed to develop and validate an automated algorithm for epicardial fat volume (EFV) quantification from noncontrast CT.

METHODS

The authors developed a hybrid algorithm based on initial segmentation with a multiple-patient CT atlas, followed by automated pericardium delineation using geodesic active contours. A coregistered segmented CT atlas was created from manually segmented CT data and stored offline. The heart and pericardium in test CT data are first initialized by image registration to the CT atlas. The pericardium is then detected by a knowledge-based algorithm, which extracts only the membrane representing the pericardium. From its initial atlas position, the pericardium is modeled by geodesic active contours, which iteratively deform and lock onto the detected pericardium. EFV is automatically computed using standard fat attenuation range.

RESULTS

The authors applied their algorithm on 50 patients undergoing routine coronary calcium assessment by CT. Measurement time was 60 s per-patient. EFV quantified by the algorithm (83.60 ± 32.89 cm(3)) and expert readers (81.85 ± 34.28 cm(3)) showed excellent correlation (r = 0.97, p < 0.0001), with no significant differences by comparison of individual data points (p = 0.15). Voxel overlap by Dice coefficient between the algorithm and expert readers was 0.92 (range 0.88-0.95). The mean surface distance and Hausdorff distance in millimeter between manually drawn contours and the automatically obtained contours were 0.6 ± 0.9 mm and 3.9 ± 1.7 mm, respectively. Mean difference between the algorithm and experts was 9.7% ± 7.4%, similar to interobserver variability between 2 readers (8.0% ± 5.3%, p = 0.3).

CONCLUSIONS

The authors' novel automated method based on atlas-initialized active contours accurately and rapidly quantifies EFV from noncontrast CT.

Quantification of epicardial fat: Which method can predict significant coronary artery disease?

AIM: To compare the predictive value of three methods of epicardial fat (EF) assessment for presence of significant coronary artery disease (CAD) [i.e., epicardial fat volume (EFV), EFV indexed with body surface area (EFV/BSA) and EFV indexed with body mass index (EFV/BMI)].

METHODS: The study was performed on 170 patients (85 women and 85 men) with clinical suspicion of CAD. They aged 26-89 years with a median age of 54 years. The patients were classified into three groups: Group 1: 58 patients with normal coronary arteries; group 2: 48 patients with non-significant CAD and group 3: 64 patients with significant CAD. The three methods for assessment of epicardial fat were retrospectively studied to determine the best method to predict the presence of significant CAD.

RESULTS: The three methods for epicardial fat quantification and measurements, i.e., EFV, EFV/BSA and EFV/BMI with post- hoc analysis showed a significant difference between patients with significant coronary artery disease compared to the normal group. Receiver operating characteristic curve analysis showed no significant difference between the three methods of epicardial fat measurements, the area under curve ranging between 0.6 and 0.62. The optimal cut-off was 80.3 cm³ for EFV, 2.4 cm³/m² for EFV indexed with BMI and 41.7 cm³/(kg/m²) for EFV indexed with BSA. For this cut-off the sensitivity ranged between 0.92 and 0.94, while specificity varied from 0.31 to 0.35.

CONCLUSION: Any one of the three methods for assessment of epicardial fat can be used to predict significant CAD since all have the same equivalent predictive value.