4.6 Article

Left ventricular wall stress in patients with severe aortic insufficiency with finite element analysis

Journal

ANNALS OF THORACIC SURGERY
Volume 82, Issue 3, Pages 840-846

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.athoracsur.2006.03.100

Keywords

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Funding

  1. NHLBI NIH HHS [R01 HL64869] Funding Source: Medline

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Background. Severe aortic insufficiency ( AI) with preserved left ventricular ( LV) function may be associated with a long asymptomatic period and unpredictable course on medical therapy. Since myocardial wall stress is closely related to both pathologic cardiac remodeling and ultimately to LV decompensation, a more accurate description of regional wall stress may improve our ability to appropriately manage these patients. The objective of this study was to define differences in instantaneous global and regional three-dimensional end-systolic maximum principal stress ( ESS) between normal patients and patients with AI, both before and after aortic valve replacement ( AVR) using magnetic resonance imaging ( MRI) and finite element analysis ( FEA). Methods. Magnetic resonance imaging was performed on 20 normal volunteers and 14 patients with moderate to severe AI with normal systolic function ( ejection fraction: 57 +/- 0.6) before and after AVR. Finite element analysis was utilized to estimate global and regional ESS. Results. Both global ( p < 0.001) and regional ( p < 0.001 in all segments) ESS were significantly higher in the preoperative AI patients when compared with their postoperative values and normal controls. Postoperative ESS was significantly lower than the normal controls ( p = 0.002). Conclusions. Three-dimensional regional and global end-systolic LV wall stress can be determined by MRI and finite element analysis. Values of ESS in patients with chronic AI were elevated prior to AVR and normalized after AVR. This method may have considerable potential as a noninvasive, clinically applicable index of regional LV geometry and function that may help with the serial evaluation of patients with AI.

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