Morphological and mechanical information of coronary arteries obtained with intravascular elastography; feasibility study in vivo.

AIMS: Plaque composition is a major determinant of coronary related clinical syndromes. In vitro experiments on human coronary and femoral arteries have demonstrated that different plaque types were detectable with intravascular ultrasound elastography. The aim of this study was to investigate the feasibility of applying intravascular elastography during interventional catheterization procedures. METHODS AND RESULTS: Data were acquired in patients (n=12) during PTCA procedures with an EndoSonics InVision echoapparatus equipped with radiofrequency output. The systemic pressure was used to strain the tissue, and the strain was determined using cross-correlation analysis of sequential frames. A likelihood function was determined to obtain the frames with minimal motion of the catheter in the lumen, since motion of the catheter prevents reliable strain estimation. Minimal motion was observed near end-diastole. Reproducible strain estimates were obtained within one pressure cycle and over several pressure cycles. Validation of the results was limited to the information provided by the echogram. Strain in calcified material (0.20%+/-0.07) was lower (P<0.001) than in non-calcified tissue (0.51%+/-0.20). CONCLUSION: In vivo intravascular elastography is feasible. Significantly higher strain values were found in non-calcified plaques than in calcified plaques

Proximal methods for the elastography inverse problem of tumor identification using an equation error approach

In this chapter, we study a nonlinear inverse problem in linear elasticity relating to tumor identification by an equation error formulation. This approach leads to a variational inequality as a necessary and sufficient optimality condition. We give complete convergence analysis for the proposed equation error method. Since the considered problem is highly ill-posed, we develop a stable computational framework by employing a variety of proximal point methods and compare their performance with the more commonly used Tikhonov regularization