Robustness of reconstructing the young's modulus distribution of vulnerable atherosclerotic plaques using a parametric plaque model

Assessment of atherosclerotic plaque composition is crucial for quantitative monitoring of atherosclerosis and for quantifying the effect of pharmaceutical plaque-stabilizing treatments during clinical trials. We assessed this composition by applying a geometrically constrained, iterative inverse solution method to reconstruct a modulus elastogram (i.e., Young's modulus image) from a plaque strain elastogram (i.e., radial strain image) that is measured using intravascular ultrasound strain elastography. This reconstruction method is especially suited for thin-cap fibroatheromas (TCFAs) (i.e., plaques with a thin fibrous cap overlaying a lipid pool). Because a strain elastogram of a plaque depends upon the plaque material composition, catheter position within the vessel and measurement noise, this paper investigates how robust the reconstruction is when these parameters are varied. To this end, a standard plaque was defined as the modulus elastogram that was reconstructed from an in vivo measured strain elastogram of a human coronary plaque. This standard plaque was used to computer-simulate different strain elastograms, by varying the 1. geometry and material properties of its plaque components, 2. catheter position and 3. level of added strain noise. Robustness was evaluated by quantifying the correctly reconstructed size, shape and Young's modulus of each plaque component region and minimal cap thickness. The simulations showed that TCFAs can be adequately reconstructed; the thinner and stiffer the cap or the softer and larger the lipid pool, the better is the reconstruction of these components and minimal cap thickness. Furthermore, reconstructions were 1. independent of catheter position and 2. independent of strain noise. As such, this method has potential to monitor robustly and quantitatively atherosclerosis in vivo. (E-mail: r.baldewsing@erasmusmc.nl) (c) 2005 World Federation for Ultrasound in Medicine & Biology.