Thoracic Aorta Diameter Calculation by Artificial Intelligence Can Predict the Degree of Arterial Stiffness

作者：Yaoling Wang, Jinrong Yang, Yichen Lu, Wenliang Fan, Lijuan Bai, Zhuang Nie, Ruiyun Wang, Jie Yu, Lihua Liu, Yun Liu, Linfeng He, Kai Wen, Li Chen, Fan Yang, Benling Qi · 发表于：Frontiers in Cardiovascular Medicine · 年份：2021 · DOI：10.3389/fcvm.2021.737161 · 被引用次数：6 · 研究领域：Cardiovascular Health and Disease Prevention、Cardiovascular Function and Risk Factors、Cardiovascular Disease and Adiposity

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.CAVI 0 ), 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.CAVI 0 ( 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 r...