Parameterization of left ventricular wall motion for detection of regional ischemia

While qualitative wall motion analysis has proven valuable in clinical cardiology practice, quantitative analyses remain too time-consuming for routine clinical use. Our long-term goal is therefore to develop automated methods for quantitative wall motion analysis. In this paper, we utilize a finite...

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Bibliographic Details
Published in:Annals of biomedical engineering Vol. 33; no. 7; pp. 912 - 919
Main Authors: Herz, Susan L, Ingrassia, Christopher M, Homma, Shunichi, Costa, Kevin D, Holmes, Jeffrey W
Format: Journal Article
Language:English
Published: United States Springer Nature B.V 01-07-2005
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Summary:While qualitative wall motion analysis has proven valuable in clinical cardiology practice, quantitative analyses remain too time-consuming for routine clinical use. Our long-term goal is therefore to develop automated methods for quantitative wall motion analysis. In this paper, we utilize a finite element model of the regionally ischemic canine left ventricle to demonstrate a new approach based on parameterization of the left ventricular endocardial surface in prolate spheroidal coordinates. The parameterization provided a substantial data reduction and enabled simple definition, calculation, and display of three-dimensional fractional shortening (3DFS), a quantitative measure of wall motion analogous to the fractional shortening measure used in 2D analysis. The endocardial surface area displaying akinesis or dyskinesis by 3DFS corresponded closely to simulated ischemic region size and 3DFS identified appropriate wall motion abnormalities during experimental coronary occlusion in a canine pilot study. 3DFS therefore appears to be a reasonable candidate for clinical tests to determine its utility in identifying and quantifying acute regional ischemia in patients. By linking state of the art finite element models to the clinically relevant framework of wall motion analysis, the methods presented here will facilitate formulation, in silico prescreening, and clinical testing of additional candidate measures of wall motion.
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ISSN:0090-6964
1573-9686
DOI:10.1007/s10439-005-3312-7