Nonalcoholic fatty liver disease is associated with myocardial ischemia by CT myocardial perfusion imaging, independent of clinical and coronary CT angiography characteristics

Association study of NAFLD with pericoronary adipose tissue and pericardial adipose tissue: Diagnosis of stable CAD patients with NAFLD based on radiomic features

BACKGROUND AND AIM

Nonalcoholic fatty liver disease (NAFLD) is prone to complicated cardiovascular disease, and we aimed to identify patients with NAFLD who are prone to developing stable coronary artery disease (CAD).

METHODS AND RESULTS

We retrospectively recruited adults who underwent coronary computed tomography angiography (CTA). A total of 127 NAFLD patients and 127 non-NAFLD patients were included in this study. Clinical features and imaging parameters were analysed, mainly including pericardial adipose tissue (PAT), pericoronary adipose tissue (PCAT), and radiomic features of 6792 PCATs. The inflammatory associations of NAFLD patients with PAT and PCAT were analysed. Clinical features (model 1), CTA parameters (model 2), the radscore (model 3), and a composite model (model 4) were constructed to identify patients with NAFLD with stable CAD. The presence of NAFLD resulted in a greater inflammatory involvement in all three coronary arteries (all P < 0.01) and was associated with increased PAT volume (r = 0.178**, P < 0.05). In the presence of NAFLD, the mean CT value of the PAT was significantly correlated with the fat attenuation index (FAI) in all three vessels and had the strongest correlation with the RCA FAI (r = 0.55, p < 0.001). A total of 9 radiomic features were screened by LASSO regression to calculate radiomic scores. In the model comparison, model 4 had the best performance of all models (AUC 0.914 [0.863-0.965]) and the highest overall diagnostic value of the model (sensitivity: 0.814, specificity: 0.941).

CONCLUSIONS

NAFLD correlates with PAT volume and PCAT inflammation. Furthermore, combining clinical features, CTA parameters, and radiomic scores can improve the efficiency of early diagnosis of stable CAD in patients with NAFLD.

Association between severity of nonalcoholic fatty liver disease and major adverse cardiovascular events in patients assessed by coronary computed tomography angiography

BACKGROUND

The effect of nonalcoholic fatty liver disease (NAFLD) on major adverse cardiovascular events (MACEs) can be influenced by the degree of coronary artery stenosis. However, the association between the severity of NAFLD and MACEs in patients who underwent coronary computed tomography angiography (CCTA) is unclear.

METHODS

A total of 341 NAFLD patients who underwent CCTA were enrolled. The severity of NAFLD was divided into mild NAFLD and moderate-severe NAFLD by abdominal CT results. The degree of coronary artery stenosis was evaluated by using Coronary Artery Disease Reporting and Data System (CAD-RADS) category. Cox regression analysis and Kaplan-Meier analysis were used to assess poor prognosis.

RESULTS

During the follow-up period, 45 of 341 NAFLD patients (13.20%) who underwent CCTA occurred MACEs. The severity of NAFLD (hazard ratio [HR] = 2.95[1.54-5.66]; p = 0.001) and CAD-RADS categories 3-5 (HR = 16.31[6.34-41.92]; p < 0.001) were independent risk factors for MACEs. The Kaplan-Meier analysis showed that moderate to severe NAFLD patients had a worsen prognosis than mild NAFLD patients (log-rank p < 0.001). Moreover, the combined receiver operating characteristic curve of the severity of NAFLD and CAD-RADS category showed a good predicting performance for the risk of MACEs, with an area under the curve of 0.849 (95% CI = 0.786-0.911).

CONCLUSION

The severity of NAFLD was independent risk factor for MACEs in patients with obstructive CAD, having CAD-RADS 3-5 categories on CCTA.

The differences between patients with nonalcoholic fatty liver disease (NAFLD) and those without NAFLD, as well as predictors of functional coronary artery ischemia in patients with NAFLD

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) is a chronic liver disease associated with metabolic syndrome. It is the most common cause of cryptogenic cirrhosis. The disease is also involved in the occurrence and development of type 2 diabetes and atherosclerosis and can directly affect the outcome of patients with coronary heart disease. Therefore, the focus of treatment of nonalcoholic fatty liver disease has also begun to focus on the treatment of risk factors for atherosclerotic heart disease. In this study, we investigated the difference between patients with coronary artery stenosis combined with NAFLD and those without NAFLD and evaluated the predictive factors and value of functional coronary artery ischemia in patients with NAFLD.

HYPOTHESIS

Many clinical factors (such as age, BMI, hyperglycemia) and imaging parameters (such as CACS grade) in the NAFLD group were different from those in the non-NAFLD group. The predictive model combined with multiple influencing factors has a good value in predicting coronary artery ischemia in patients with NAFLD.

METHODS

We collected the clinical and imaging data of patients who underwent coronary computed tomography angiography and coronary artery calcification score (CACS) scans between January and June 2023. A total of 392 patients were included and divided into the NAFLD group and the non-NAFLD group. Based on CT fractional flow reserve (CT-FFR), patients with NAFLD were divided into CT-FFR ≤ 0.08 group and CT-FFR > 0.08 group.

RESULTS

Significant differences were observed between the non-NAFLD and NAFLD groups in terms of age, body mass index, hyperglycemia, hyperlipidemia, triglyceride, high-density lipoprotein, coronary artery disease-reporting and data system (CAD-RADS) classification, CACS classification, number of diseased coronary arteries, and CT-FFR ≤ 0.80 ratio (p < .05). The CAD-RADS and CACS classifications can independently predict functional coronary artery ischemia in NAFLD patients. The combined use of CAD-RADS and CACS classifications resulted in an area under the curve of 0.819 (95% confidence interval: 0.761-0.876) for predicting coronary artery ischemia in NAFLD patients, which was higher than the individual classification methods (CAD-RADS: 0.762, CACS: 0.742) (p = .000).

CONCLUSIONS

There are differences between patients with coronary artery stenosis and NAFLD and those without NAFLD. The CAD-RADS classification and CACS classification can economically and efficiently predict functional coronary artery ischemia in patients with NAFLD, which has crucial value in clinical diagnosis and treatment.

Decreased liver-to-spleen ratio in low-dose computed tomography as a biomarker of fatty liver disease reflects risk for myocardial ischaemia

Aims

A strong association between fatty liver disease (FLD) and coronary artery disease is consistently reported. Our aim was to evaluate whether FLD diagnosed using low-dose non-contrast computed tomography (LDCT), as a by-product of myocardial perfusion imaging (MPI), is associated with myocardial ischaemia or left ventricular function parameters.

Methods and results

We analysed 742 patients who had undergone MPI using single photon emission computed tomography (SPECT) and LDCT. A liver-to-spleen ratio (in Hounsfield units) of <1 was defined as FLD. Myocardial ischaemia was defined as a summed difference score (SDS) ≥3. Left ventricular size and systolic function were assessed from the electrocardiogram-gated SPECT. FLD patients were younger (63 vs. 68 years) and had a higher body mass index (34.6 vs. 29.0 kg/m2) and a higher SDS (2.65 vs. 1.63), P < 0.001 for all. Independently of several possible confounding factors including traditional risk factors, patients with FLD had a 1.70-fold risk of ischaemia (95% confidence interval 1.11-2.58, P = 0.014). Left ventricular end-diastolic volume (109 vs. 109 mL) and ejection fraction (61 vs. 61%) were comparable in those with and without FLD (non-significant for both).

Conclusions

With the help of LDCT, it is possible to identify FLD, which is associated with an increased risk of myocardial ischaemia. Therefore, evaluation of FLD from LDCT is recommended along with MPI.