This study aimed to evaluate the association between abdominal fat distribution (AFD) and coronary artery disease (CAD) complexities using the computed tomography (CT)-derived SYNTAX score (CT-SXscore). Coronary computed tomographic angiography (CCTA) was performed in patients with suspected CAD. Plain abdominal CT was performed to measure visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) areas. To assess AFD, VAT/SAT (V/S) ratios were calculated. The CT-SXscore was calculated in patients with significant stenoses assessed by CCTA. Of 942 enrolled patients, 310 (32.9%) had 1 or more significant stenoses. The CT-SXscore showed a positive correlation with the V/S ratio (r = 0.33, p < 0.001). In the multivariate regression analysis, the V/S ratio was the only independent predictor for CAD severity based on the CT-SXscore (β = 0.25; t = 4.14; p < 0.001), even though the absolute SAT and VAT areas showed no relationship to the CT-SXscore. Regarding the 4 CAD-patient groups divided according to their median VAT and SAT areas, the CT-SXscore was significantly higher for the high VAT/low SAT group than for any other group (19.6 ± 11.5 vs 13.3 ± 9.6 in the low VAT/low SAT, 10.1 ± 8.5 in the low VAT/high SAT, and 12.2 ± 8.7 in the high VAT/high SAT groups; p < 0.001 for all). In conclusion, it was found that the V/S ratio is a useful index for predicting CAD severity and that AFD may be a more important risk factor for CAD than the absolute amount of each abdominal fat.
Previous studies have reported a strong association between abdominal obesity and coronary artery disease (CAD). Recently, abdominal fat distribution (AFD) assessed by the ratio of visceral-to-subcutaneous adipose tissue area (V/S ratio) has been identified as a more important risk factor for CAD than the absolute amounts of visceral adipose tissue (VAT) or subcutaneous adipose tissue (SAT). The SYNergy between percutaneous coronary intervention (PCI) with TAXus and cardiac surgery (SYNTAX) score has been established to assess the complexity of CAD based on invasive coronary angiography (ICA). Based on coronary computed tomographic angiography (CCTA) improvements over the past decade, the computed tomography (CT)-derived SYNTAX score (CT-SXscore) has been proposed as a feasible method of grading CAD severity assessed by CCTA. , This study aimed to evaluate the association between AFD and CAD complexity using the CT-SXscore.
Methods
This was a single-center, simple, cross-sectional study. We evaluated consecutive patients who met the following inclusion criteria: (1) suspected CAD patients with/without chest pain; (2) >16 years old; (3) no prior PCI or coronary artery bypass graft surgery (CABG); (4) no history of myocardial infarction; (5) no severe heart failure; (6) no severe asthma; and (7) no pregnancy. This study was performed in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Ina Central Hospital. Informed consent was obtained from each patient.
CCTA using a 320-row multi-detector CT scanner (Aquilion One, Canon Medical Systems, Tokyo, Japan) was performed in the patients with suspected CAD. All patients with an initial heart rate > 55 beats/min were administered an oral β-blocking agent (20 mg or 40 mg metoprolol depending on their heart rate) 1 hour prior to CT scanning. Immediately before image acquisition, 0.3 mg sublingual nitroglycerin was administered to all patients. During CCTA image acquisition, 50 to 80 cc of contrast iohexol or iopamidol (Omnipaque 300 or 350 mg/dl; GE Healthcare, Princeton, New Jersey; Oiparomine 300 mg/dl, Fuji Pharma, Tokyo, Japan) was injected, followed by a saline flush. Contrast medium injection was performed via a two-phase injection method: contrast medium for 12 seconds and saline solution for 10 seconds. Scanning was performed at a tube voltage of 120 kV, a gantry rotation time of 275 to 400 msec depending on each patient’s heart rate, a scan slice thickness of 0.5 mm, an image slice thickness of 0.5 mm, and a reconstruction interval of 0.3 mm.
CCTA images were evaluated on axial, coronal, sagittal, cross-sectional, curved multi-planar reconstruction, and maximal intensity projection images. Two experienced reviewers visually assessed all coronary segments ≥ 1.5 mm in diameter for detecting the presence of significant stenotic lesions defined as luminal diameter stenosis ≥ 50%. , Each stenotic lesion was evaluated to calculate the CT-SXscore in the same manner as the ICA assessment, as previously described.
Plain abdominal CT scanning at the umbilical cord level was performed at the same time during CCTA to measure VAT and SAT areas. Abdominal adipose tissue areas in the images were determined by using commercially available software included with the CT system. The total adipose tissue (TAT) area was defined as the sum of the VAT area and SAT area. To assess AFD, especially as an index of visceral fat accumulation, the V/S ratios were also calculated as the VAT area divided by the SAT area in each case. Patients with 1 or more significant stenoses were defined as CAD patients and divided into 2 groups on the basis of their median V/S ratio to assess the effect of the V/S ratio on the CT-SXscore. These patients were also divided into 4 groups according to their SAT and VAT median areas to evaluate the effect of abdominal adipose tissue distribution on the CT-SXscore.
Statistical analysis was performed by using the Statistical Package for Social Science, version 21 for Windows (IBM Corp., Armonk, NY, USA). For continuous variables, the unpaired t test and analysis of variance with Scheffe post-hoc test were used for comparisons depending on the number of groups. Quantitative data were expressed as the mean ± standard deviation. Multivariate logistic proportional hazard models were used to adjust for the effects of baseline risk factors on the prevalence of CAD. Multiple regression analyses were performed to assess the effects of the body mass index (BMI), each abdominal fat area, and V/S ratios on the CT-SXscores. Differences were considered to be significant for p < 0.05.
Results
From October 2014 to March 2020 at Ina Central Hospital, 1104 consecutive patients with suspected CAD were enrolled in the present program. A total of 162 patients were excluded from this study because of previous PCI or CABG (54 patients), lack of abdominal fat measurements (68 patients), inadequate quality of CCTA images caused by high heart rate of the subject (6 patients), and duplicate cases (n = 34) ( Figure 1 ). Finally, we analyzed 942 patients (542 men, mean age: 66.7 ± 13.0 years). Of 942 enrolled patients, 310 (32.9%) had 1 or more significant stenoses. Age, proportion of males, and prevalence of hypertension and diabetes mellitus were higher in the CAD group than in the non-CAD group. Although the body composition indicators such as BMI and each abdominal adipose tissue (i.e., TAT, SAT, VAT) area were not different between the CAD and non-CAD groups, the V/S ratio was significantly higher in the CAD group than in the non-CAD group ( Table 1 ). In the univariate analysis, the V/S ratio was the only predictor for CAD prevalence among the body composition indicators. However, the multivariate logistic hazard models adjusted for the traditional coronary risks (i.e., age, sex, hypertension, diabetes mellitus, dyslipidemia, and current smoking) revealed no predictive value for any of the body composition indicators ( Table 2 ).
| Coronary Artery Disease | ||||
|---|---|---|---|---|
| Overall | Yes | No | p value | |
| Variable | (n = 942) | (n = 310) | (n = 632) | |
| Age, (years) | 66.7 ± 13.0 | 70.9 ± 10.6 | 64.6 ± 13.5 | <0.001 |
| Men | 542 (57.5%) | 216 (69.7%) | 326 (51.6%) | <0.001 |
| Hypertension | 505 (53.6%) | 201 (64.8%) | 304 (48.1%) | <0.001 |
| Dyslipidemia | 330 (35.0%) | 112 (36.1%) | 218 (34.5%) | 0.62 |
| Diabetes mellitus | 181 (19.2%) | 89 (28.7%) | 92 (14.6%) | <0.001 |
| Current smoker | 120 (12.7%) | 43 (13.9%) | 77 (12.2%) | 0.47 |
| Total cholesterol (mg/dl) | 196.1 ± 38.1 | 191.4 ± 36.9 | 198.6 ± 38.6 | 0.015 |
| LDL cholesterol (mg/dl) | 116.0 ± 31.7 | 114.1 ± 32.3 | 117.0 ± 31.3 | 0.22 |
| HDL cholesterol (mg/dl) | 58.3 ± 16.7 | 54.5 ± 14.5 | 60.3 ± 17.4 | <0.001 |
| Triglyceride (mg/dl) | 141.4 ± 102.1 | 144.1 ± 94.9 | 140.0 ± 105.7 | 0.59 |
| Hemoglobin A1c (%) | 6.1 ± 0.9 | 6.3 ± 1.0 | 6.0 ± 0.8 | <0.001 |
| eGFR (ml/min/1.73 m 2 ) | 67.5 ± 19.3 | 64.6 ± 20.2 | 68.9 ± 18.7 | 0.002 |
| BMI (kg/m 2 ) | 24.2 ± 4.0 | 24.2 ± 4.1 | 24.1 ± 3.9 | 0.68 |
| TAT area (cm 2 ) | 209.0 ± 104.9 | 207.6 ± 105.1 | 209.7 ± 104.8 | 0.78 |
| SAT area (cm 2 ) | 127.5 ± 70.4 | 122.5 ± 68.3 | 129.9 ± 71.3 | 0.13 |
| VAT area (cm 2 ) | 81.5 ± 48.0 | 85.0 ± 48.7 | 79.8 ± 47.5 | 0.11 |
| V/S ratio | 0.71 ± 0.39 | 0.76 ± 0.38 | 0.68 ± 0.39 | 0.005 |
| Variable | Unadjusted HR (95%CI) | P value | Adjusted HR (95%CI) | P value |
|---|---|---|---|---|
| BMI | 1.007 (0.973 – 1.042) | 0.68 | 1.006 (0.966 – 1.048) | 0.77 |
| TAT area | 1.000 (0.999 – 1.001) | 0.78 | 1.000 (0.999 – 1.002) | 0.72 |
| SAT area | 0.998 (0.997 – 1.000) | 0.13 | 1.001 (0.999 – 1.003) | 0.36 |
| VAT area | 1.002 (0.999 – 1.005) | 0.11 | 0.999 (0.996 – 1.002) | 0.60 |
| V/S ratio | 1.628 (1.155 – 2.296) | 0.005 | 0.696 (0.459 – 1.053) | 0.086 |
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