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Comparison of stenosis models for usage in the estimation of pressure gradient across aortic coarctation

Authors: Yubing Shi; Israel Valverde; Patricia V. Lawford; Heynric B. Grotenhuis; Philipp Beerbaum; D. Rodney Hose;

Comparison of stenosis models for usage in the estimation of pressure gradient across aortic coarctation

Abstract

Non-invasive estimation of the pressure gradient in cardiovascular stenosis has much clinical importance in assisting the diagnosis and treatment of stenotic diseases. In this research, a systematic comparison is conducted to investigate the accuracy of a group of stenosis models against the MRI- and catheter-measured patient data under the aortic coarctation condition. Eight analytical stenosis models, including six from the literature and two proposed in this study, are investigated to examine their prediction accuracy against the clinical data. The two improved models proposed in this study consider comprehensively the Poiseuille loss, the Bernoulli loss in its exact form, and the entrance effect, of the blood flow. Comparison of the results shows that one of the proposed models demonstrates a cycle-averaged mean prediction error of -0.15 ± 3.03 mmHg, a peak-to-peak prediction error of -1.8 ± 6.89 mmHg, which is the best among the models studied.

Countries
Spain, United Kingdom
Keywords

Poiseuille loss, Hemodynamics, 610, Constriction, Pathologic, Stenosis model, Pressure gradient, Aortic Coarctation, 576, Aortic coarctation, Humans, Bernoulli loss, Entrance effect

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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