A Three-Dimensional Computational Investigation of Intraventricular Fluid Dynamics: Examination Into the Initiation of Systolic Anterior Motion of the Mitral Valve Leaflets
- 1 February 1995
- journal article
- research article
- Published by ASME International in Journal of Biomechanical Engineering
- Vol. 117 (1) , 94-102
- https://doi.org/10.1115/1.2792276
Abstract
Systolic anterior motion of the mitral valve leaflets (SAM) is a disease of the left ventricle which results from an abnormal force balance on the mitral valve. The mechanism by which is initiated is poorly understood, and a complete understanding of this mechanism is required for effective treatment of SAM. There are currently two theories for the initiation mechanism of SAM, the Venturi hypothesis and the altered papillary muscle-mitral valve geometry theory (PM-MV). The Venturi hypothesis states that abnormally high ejection velocities create Venturi forces which initiate SAM. The PM-MV theory asserts that SAM is the result of abnormally distributed chordal forces which are incapable of preventing SAM. To investigate the initiation mechanism of SAM, a computer model of early systolic flow in an anatomically-correct human left ventricle was developed using Peskin’s immersed boundary algorithm. The computer model was used to determine the effect of chordal force distribution and septal thickness of the intraventricular flow field. The results show that the degree of SAM is inversely proportional to the amount of chordal restraint applied to the central portion of the leaflets. Also, the results support the PM-MV theory and indicate the following: (i) fluid forces capable of initiating SAM as always present in a normal human ventricle; (ii) SAM does not occur normally because of the presence of chordal forces on the central portion of the mitral leaflet; (Hi) SAM will occur when these central chordal forces are sufficiently low; (iv) the extent of SAM is inversely proportional to these central chordal forces; and (v) Venturi forces alone can not cause SAM.Keywords
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