Abstract

Background: Arterial aging is characterized by decreased vascular function, caused by arterial stiffness (AS), and vascular morphological changes, caused by arterial dilatation. We analyzed the relationship of pre-AS and AS, as assessed by cardio ankle vascular index (CAVI), with arterial diameters (AD) at nine levels, from the aortic sinus to the abdominal aorta, as measured by artificial intelligence (AI) on non-enhanced chest computed tomography (CT) images.Methods: Overall, 801 patients who underwent both chest CT scan and arterial elasticity test were enrolled. Nine horizontal diameters of the thoracic aorta (from the aortic sinuses of Valsalva to the abdominal aorta at the celiac axis origin) were measured by AI using CT. Patients were divided into non-AS (mean value of the left and right CAVIs [M.CAVI] < 8), pre-AS (8 ≤ M.CAVI < 9), and AS (M.CAVI ≥ 9) groups. We compared AD differences among groups, analyzed the correlation of age, ADs, and M.CAVI or the mean pressure-independent CAVI (M.CAVI0), Furthermore, we evaluated the risk predictors and the diagnostic value of the nine ADs for pre-AS and AS.Results: The AD at mid descending aorta (MD) correlated strongest with CAVI (r = 0.46, p < 0.001) or M.CAVI0 (r = 0.42, p < 0.001). M.CAVI was most affected by the MD AD and by age. An increase in the MD AD independently predicted the occurrence of pre-AS or AS. For MD AD, every 4.37 mm increase caused a 14% increase in the pre-AS and AS risk and a 13% increase in the AS risk. With a cut-off value of 26.95 mm for the MD AD, the area under the curve (AUC) for identifying the risk of AS was 0.743. With a cut-off value of 25.15 mm, the AUC for identifying the risk of the stage after the prophase of AS is 0.739.Conclusions: Aging is associated with an increase in AD and a decrease in arterial elasticity. An increase in AD, particularly at the MD level is an independent predictor of AS development.

Highlights

  • Vascular aging is a characteristic feature of body frailty and is the pathological basis of chronic diseases of various vital organs, such as the cardiac, brain, and kidney

  • Exclusion criteria are as follows:(1) a history of aortic revascularization, replacement, or stent implantation; [2] identified or suspected genetic syndromes associated with thoracic aortic aneurysms and dissections (e.g., Marfan syndrome; Turner syndrome); [3] congenital variation in an entire or important branch of the aorta in adults; [4] inflammatory diseases associated with the thoracic aortic disease; [5] acute arterial syndrome, including aortic dissection and intramural hematoma; [6] aortic Aneurysms; [7] severe insufficiency of blood volume and unstable hemodynamics; [8] severe heart failure with low ejection fraction; [9] patients on hemodialysis

  • Non-normally distributed data were presented as median with IQs, while normally distributed data were presented as mean ± SD, and classified data were presented as amounts with percentage

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Summary

Introduction

Vascular aging is a characteristic feature of body frailty and is the pathological basis of chronic diseases of various vital organs, such as the cardiac, brain, and kidney. Arterial stiffness (AS), with the resultant structural and functional changes, is a consequence of vascular aging [1]. Pathological changes related to AS occur in the vascular wall. Progressive endomyocardial thickening caused by enhanced elastin degradation and collagen deposition in the vascular medium, as well as perivascular fibrosis and abnormal extracellular matrix eventually lead to an increase in vessel diameter [2, 3]. Biological changes in vessel walls during vessel diameter increase lead to decreased vascular compliance. Arterial aging is characterized by decreased vascular function, caused by arterial stiffness (AS), and vascular morphological changes, caused by arterial dilatation. We analyzed the relationship of pre-AS and AS, as assessed by cardio ankle vascular index (CAVI), with arterial diameters (AD) at nine levels, from the aortic sinus to the abdominal aorta, as measured by artificial intelligence (AI) on non-enhanced chest computed tomography (CT) images

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