4.5 Article

A new approach for the evaluation of the severity of coarctation of the aorta using Doppler velocity index and effective orifice area: In vitro validation and clinical implications

Journal

JOURNAL OF BIOMECHANICS
Volume 45, Issue 7, Pages 1239-1245

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jbiomech.2012.01.039

Keywords

Aortic stenosis; Coarctation of the aorta; In vitro study; Hemodynamics

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Early detection and accurate estimation of COA severity are the most important predictors of successful long-term outcome. However, current clinical parameters used for the evaluation of the severity of COA have several limitations and are flow dependent. The objectives of this study are to evaluate the limitations of current existing parameters for the evaluation of the severity of coarctation of the aorta (COA) and suggest two new parameters: COA Doppler velocity index and COA effective orifice area. Three different severities of COAs were tested in a mock flow circulation model under various flow conditions and in the presence of normal and stenotic aortic valves. Catheter trans-COA pressure gradients and Doppler echocardiographic trans-COA pressure gradients were evaluated. COA Doppler velocity index was defined as the ratio of pre-COA to post-COA peak velocities measured by Doppler echocardiography. COA Doppler effective orifice area was determined using continuity equation. The results show that peak-to-peak trans-COA pressure gradient significantly increased with flow rate (from 83% to 85%). Peak Doppler pressure gradient also significantly increased with flow rate (80-85%). A stenotic or bicuspid aortic valve increased peak Doppler pressure gradient by 20-50% for a COA severity of 75%. Both COA Doppler velocity index and COA effective orifice area did not demonstrate significant flow dependence or dependence upon aortic valve condition. As a conclusion, COA Doppler velocity index and COA effective orifice area are flow independent and do not depend on aortic valve conditions. They can, then, more accurately predict the severity of COA. (C) 2012 Elsevier Ltd. All rights reserved.

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