Novel risk predictor for thrombus deposition in abdominal aortic aneurysms

¹ University Campus Bio-Medico of Rome, Department of Engineering - Via A. del Portillo 21, 00128 Rome, Italy
² Università della Svizzera italiana, Faculty of Informatics - Via Giuseppe Buffi 13, 6904 Lugano, Switzerland
³ International Center for Relativistic Astrophysics Network, ICRANet - Piazza della Repubblica 10, Pescara, Italy
⁴ Mauro Picone Institute, CNR - Via dei Taurini 19, 00185 Rome, Italy
⁵ Institute for Applied Computational Science, IACS - Harvard School of Engineering and Applied Sciences Northwest B162, 52 Oxford Street, Cambridge MA 02138, USA

Received: 16 July 2015
Accepted: 16 October 2015

Abstract

The identification of the basic mechanisms responsible for cardiovascular diseases stands as one of the most challenging problems in modern medical research including various mechanisms which encompass a broad spectrum of space and time scales. Major implications for clinical practice and pre-emptive medicine rely on the onset and development of intraluminal thrombus in which effective clinical therapies require synthetic risk predictors/indicators capable of informing real-time decision-making protocols. In the present contribution, two novel hemodynamics synthetic indicators, based on a three-band decomposition (TBD) of the shear stress signal, are introduced. Extensive fluid-structure computer simulations of patient-specific scenarios confirm the enhanced risk-prediction capabilities of the TBD indicators. In particular, they permit a quantitative and accurate localization of the most likely thrombus deposition in realistic aortic geometries, where previous indicators would predict healthy operation. The proposed methodology is also shown to provide additional information and discrimination criteria on other factors of major clinical relevance, such as the size of the aneurysm.