Aortic atherosclerosis predicts the extent and severity of coronary atherosclerosis detected by multidetector computed tomography coronary angiography

Can aortic atherosclerosis or epicardial adipose tissue volume be used as a marker for predicting coronary artery disease?

PURPOSE

To investigate whether aortic atherosclerosis or epicardial adipose tissue (EAT) volume on multidetector computed tomography (CT) can predict the presence of significant coronary artery disease (CAD).

MATERIALS AND METHODS

Coronary CT angiography was performed in 202 cases of CAD that were known or based on suspicion. Based on coronary CT angiography results, the patients with significant stenosis (≥50%) and without significant stenosis (<50%) were compared in terms of demographic characteristics, traditional cardiovascular risk factors, aortic atherosclerosis, and EAT volume.

RESULTS

Significant coronary artery stenosis was detected in 92 cases (45.5%). Although EAT volume was higher in the patients with significant stenosis, the difference between the two groups was not statistically significant. The presence of calcification in the descending aorta was significantly higher in the patients with significant stenosis than the patients without significant stenosis (50.4% and 15.4%, respectively, p=0.0001). The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy rates of the presence of calcification in the descending aorta in predicting the presence of significant coronary artery stenosis were respectively found as 53.8%, 84.4%, 74.6%, 68.1%, and 70.3%. The sensitivity, specificity, PPV, NPV, and accuracy rates of the ≥2.45mm wall thickness of the descending aorta in predicting the presence of significant coronary artery stenosis were respectively found as 75.3%, 74.3%, 71.4%, 77.9%, and 74.8%.

CONCLUSION

There is a strong relationship between thoracic aortic atherosclerosis and CAD. However, the relationship between EAT volume and CAD is not significant. The presence of aortic atherosclerosis can be used as an additional marker together with traditional cardiovascular risk factors for predicting CAD.

Frequency and predictors of renal artery stenosis in hypertensive patients undergoing coronary angiography

Renal artery stenosis (RAS) and coronary artery disease share common risk factors. We investigated the frequency and predictors of RAS among hypertensive patients who underwent elective coronary angiography. A total of 832 hypertensive patients underwent coronary and renal angiography at the same session. Renal artery stenosis was classified as mild, moderate, or severe. The study population consisted of 4 groups; 71.1% with normal renal arteries, 12.5% with mild, 8.9% with moderate, and 7.5% with severe RAS. The prevalence of significant (≥50%) RAS was 16.3%. The Gensini score showed a stepwise rise with increasing severity of RAS. Age, duration of hypertension, estimated glomerular filtration rate, Gensini score, and multivessel disease were independent predictors for the presence of RAS. Hypertensive patients with those risk factors might need detailed investigation for RAS which may affect their prognosis.

Automated tracing of the adventitial contour of aortoiliac and peripheral arterial walls in CT angiography (CTA) to allow calculation of non-calcified plaque burden

Aortoiliac and lower extremity arterial atherosclerotic plaque burden is a risk factor for the development of visceral and peripheral ischemic and aneurismal vascular disease. While prior research allows automated quantification of calcified plaque in these body regions using CT angiograms, no automated method exists to quantify soft plaque. We developed an automatic algorithm that defines the outer wall contour and wall thickness of vessels to quantify non-calcified plaque in CT angiograms of the chest, abdomen, pelvis, and lower extremities. The algorithm encodes the search space as a constrained graph and calculates the outer wall contour by deriving a minimum cost path through the graph, following the visible outer wall contour while minimizing path tortuosity. Our algorithm was statistically equivalent to a reference standard made by two reviewers. Absolute error was 1.9 ± 2.3% compared to the inter-observer variability of 3.9 ± 3.6%. Wall thickness in vessels with atherosclerosis was 3.4 ± 1.6 mm compared to 1.2 ± 0.4 mm in normal vessels. The algorithm shows promise as a tool for quantification of non-calcified plaque in CT angiography. When combined with previous research, our method has the potential to quantify both non-calcified and calcified plaque in all clinically significant systemic arteries, from the thoracic aorta to the arteries of the calf, over a wide range of diameters. This algorithm has the potential to enable risk stratification of patients and facilitate investigations into the relationships between asymptomatic atherosclerosis and a variety of behavioral, physiologic, pathologic, and genotypic conditions.

Zoom imaging for rapid aortic vessel wall imaging and cardiovascular risk assessment

PURPOSE

To demonstrate the utility of a "reduced field-of-view" (zoom imaging) technique to accelerate free-breathing, ECG-triggered, turbo-spin-echo black-blood sequences, which have been previously described to detect subclinical aortic atherosclerosis.

MATERIALS AND METHODS

Fifteen healthy volunteers underwent MRI of the thoracic and abdominal aorta. Imaging with the conventional full field-of-view sequence was compared with zoom imaging. Total scan time, image quality (i.e., contrast-to-noise ratio and vessel wall sharpness) and vessel wall thickness were analyzed. A subgroup of 10 volunteers also underwent acceleration of imaging using sensitivity encoding (SENSE) for comparison.

RESULTS

Zoom imaging significantly reduced imaging time from a mean of 41 ± 9 min (conventional imaging) to 15 ± 0.5 min (P<0.01). There was no difference in image quality between conventional and zoom imaging with respect to CNR (10.1 ± 6 versus 10.1 ± 6) or vessel wall sharpness (38 ± 4% versus 39 ± 4%). Furthermore, Bland Altman plots showed excellent agreement in vessel wall thickness measurements using the two methods. In comparison, SENSE not only reduced CNR but also resulted in underestimation of vessel wall thickness compared with the conventional sequence.

CONCLUSION

Zoom imaging allows accurate and time-efficient imaging of the abdominal and thoracic aorta for cardiovascular risk prediction. In this application, it is preferable to SENSE.

Epicardial adipose tissue thickness predicts descending thoracic aorta atherosclerosis shown by multidetector computed tomography

Human epicardial adipose tissue (EAT) is a type of visceral adipose tissue functioning as an endocrine organ by secreting hormones and adipocytokines which have an important role in the atherosclerotic process. In this study, we aimed to assess the relationship between EAT measured by dual source multidetector computed tomography (MDCT) and descending thoracic aorta (DTA) atherosclerosis. A total of 148 patients who underwent MDCT for the evaluation of coronary artery disease were enrolled in this study. Thickness of the EAT was measured on contrast enhanced multiplanar reformat images with parasternal short axis view at basal, mid-ventricular and apical levels and horizontal long axis view. The atherosclerotic plaque was scored from 0 to 4 points by the percentage of the luminal surface at the cross sectional area of proximal, mid and distal segments of descending aorta. Among the study population, 84 (56.8%) were male and age was (mean ± standart deviation) 56.9 ± 11.7 years. In patients with critical coronary atherosclerosis, DTA atherosclerosis had a significant relationship with EAT (P = 0.012). Multivariate linear regression analysis revealed that in addition to critical coronary stenosis, age and total epicardial fat thickness were associated with aortic atherosclerosis (β value, 0.058 and 0.035; t value, 4.74 and 2.28, respectively; P < 0.05) after adjustment for traditional cardiovascular risk factors. In this study we demonstrated that atherosclerotic plaque burden of DTA was associated with the amount of EAT thickness among patients with suspected CAD shown by MDCT. Further large scale prospective studies are needed to address the interaction of EAT as well as the mediators of inflammation and adipocytokines with the development of atherosclerotic plaques in aorta and effects on cardiovascular outcomes.