Personalized blood flow computations: A hierarchical parameter estimation framework for tuning boundary conditions. (12th July 2016)

• Record Type: Journal Article
• Authors: Itu, Lucian; Sharma, Puneet; Suciu, Constantin; Moldoveanu, Florin; Comaniciu, Dorin
• Is Part Of: International journal for numerical methods in biomedical engineering. Volume 33:Number 3(2017:Mar.)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-07-12
• Subjects: blood flow -- personalization -- parameter estimation -- structured tree -- boundary condition -- multiscale model; Biomedical engineering -- Periodicals; Imaging systems in medicine -- Periodicals; Numerical analysis -- Periodicals; Engineering mathematics -- Periodicals; 610.28
• DOI: 10.1002/cnm.2803
• Languages: English
• ISSNs: 2040-7939

Abstract

Summary: We propose a hierarchical parameter estimation framework for performing patient‐specific hemodynamic computations in arterial models, which use structured tree boundary conditions. A calibration problem is formulated at each stage of the hierarchical framework, which seeks the fixed point solution of a nonlinear system of equations. Common hemodynamic properties, like resistance and compliance, are estimated at the first stage in order to match the objectives given by clinical measurements of pressure and/or flow rate. The second stage estimates the parameters of the structured trees so as to match the values of the hemodynamic properties determined at the first stage. A key feature of the proposed method is that to ensure a large range of variation, two different structured tree parameters are personalized for each hemodynamic property. First, the second stage of the parameter estimation framework is evaluated based on the properties of the outlet boundary conditions in a full body arterial model: the calibration method converges for all structured trees in less than 10 iterations. Next, the proposed framework is successfully evaluated on a patient‐specific aortic model with coarctation: only six iterations are required for the computational model to be in close agreement with the clinical measurements used as objectives, and overall, there is a good agreement between the measured and computed quantities. Copyright © 2016 John Wiley & Sons, Ltd. Abstract : We propose a hierarchical parameter estimation framework for performing patient‐specific hemodynamic computations in arterial models, which use structured tree boundary conditions. The calibration algorithms estimate several structured tree parameters so as to ensure a large range of variation for each hemodynamic property of interest (resistance and compliance). The framework is successfully evaluated on a patient‐specific aortic model with coarctation: only six iterations are required for the computational model to be in close agreement with the clinical measurements.