title: A personalized-model-based central aortic pressure estimation method.
abstract: Central Aortic Pressure (CAP) can be used to predict cardiovascular structural damage and cardiovascular events, and the development of simple, well-validated and non-invasive methods for CAP waveforms estimation is critical to facilitate the routine clinical applications of CAP. Existing widely applied methods, such as generalized transfer function (GTF-CAP) method and N-Point Moving Average (NPMA-CAP) method, are based on clinical practices, and lack a mathematical foundation. Those methods also have inherent drawback that there is no personalisation, and missing individual aortic characteristics. To overcome this pitfall, we present a personalized-model-based central aortic pressure estimation method (PM-CAP)in this paper. This PM-CAP has a mathematical foundation: a human aortic network model is proposed which is developed based on viscous fluid mechanics theory and could be personalized conveniently. Via measuring the pulse wave at the proximal and distal ends of the radial artery, the least square method is then proposed to estimate patient-specific circuit parameters. Thus the central aortic pulse wave can be obtained via calculating the transfer function between the radial artery and central aorta. An invasive validation study with 18 subjects comparing PM-CAP with direct aortic root pressure measurements during percutaneous transluminal coronary intervention was carried out at the Beijing Hospital. The experimental results show better performance of the PM-CAP method compared to the GTF-CAP method and NPMA-CAP method, which illustrates the feasibility and effectiveness of the proposed method.
authors.affiliation: China Academy of Electronics and Information Technology, Beijing, China. Electronic address: Jiangsheng08@mails.ucas.ac.cn.
authors.forename: Sheng
authors.initials: S
authors.lastname: Jiang
authors.affiliation: School of Electronics and Electrical Engineering, University of Leeds, Leeds, UK. Electronic address: z.zhang3@leeds.ac.uk.
authors.forename: Zhi-Qiang
authors.initials: ZQ
authors.lastname: Zhang
authors.affiliation: Division of Cardiology, Beijing Hospital, Beijing, China.
authors.forename: Fang
authors.initials: F
authors.lastname: Wang
authors.affiliation: Department of Electrical Engineering, University of Chinese Academy of Sciences, Beijing, China.
authors.forename: Jian-Kang
authors.initials: JK
authors.lastname: Wu
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001011:Aorta / Q000503:physiopathology; D062186:Arterial Pressure; D001795:Blood Pressure Determination / Q000379:methods; D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000503:physiopathology; D005260:Female; D006339:Heart Rate; D006801:Humans; D008297:Male; D008875:Middle Aged; D008955:Models, Cardiovascular; D057285:Precision Medicine; D011312:Pressure
keywords: Blood fluid dynamics; Central aortic pressure; Human artery model; Transfer function