Reconstructive compounding for IVUS palpography

Realistic IVUS image generation in different intraluminal pressures

Intravascular ultrasound (IVUS) phantoms are important to calibrate and evaluate many IVUS imaging processing tasks. However, phantom generation is never the primary focus of related works; hence, it cannot be well covered, and is usually based on more than one platform, which may not be accessible to investigators. Therefore, we present a framework for creating representative IVUS phantoms, for different intraluminal pressures, based on the finite element method and Field II. First, a coronary cross-section model is selected. Second, the coronary regions are identified to apply the properties. Third, the corresponding mesh is generated. Fourth, the intraluminal force is applied and the deformation computed. Finally, the speckle noise is incorporated. The framework was tested taking into account IVUS contrast, noise and strains. The outcomes are in line with related studies and expected values. Moreover, the framework toolbox is freely accessible and fully implemented in a single platform.

Intravascular ultrasound area strain imaging used to characterize tissue components and assess vulnerability of atherosclerotic plaques in a rabbit model

The purpose of this study was to investigate the association of area strain and tissue components and vulnerability of atherosclerotic plaques in a rabbit model. Forty purebred New Zealand rabbits underwent balloon-induced abdominal aorta endothelium injury, then a high-cholesterol diet for 24 weeks. Intravascular ultrasound (IVUS) images of abdominal aortas were acquired in situ and two consecutive frames near the end-diastole were used to construct an IVUS elastogram. Histologic slices matched with corresponding IVUS images were stained for fatty and collagen components, smooth muscle cells (SMCs) and macrophages. Regions-of-interest (ROIs) in plaques were classified as fibrous, fibro-fatty or fatty according to histologic study. Vulnerability indexes of ROIs were calculated as (fat + macrophage)/(collagen + SMCs). The area strain of these ROIs was calculated by use of an in-house-designed software system with a block-matching-based algorithm. Area strain was significantly higher in fatty ROIs (0.056 ± 0.003) than in fibrous (0.019 ± 0.002, p < 0.001) or fibro-fatty ROIs (0.033 ± 0.003, p < 0.001). The sensitivity and specificity of area strain for fatty ROIs characterization was 75.0% and 80.2% (area under the curve [AUC] 0.858, 95% confidence interval [CI] = 0.800-0.916, p < 0.001) and 75.0% and 75.3% (AUC 0.859, 95% CI = 0.801-0.917, p < 0.001) for fibrous ROIs, as demonstrated by receiver operating characteristic curve analysis. Area strain was positively correlated with vulnerability index (r(2) = 0.495, p < 0.001), fatty components (r(2) = 0.332, p < 0.001) and macrophage infiltration (r(2) = 0.406, p < 0.001); and negatively correlated with collagen and SMC composition (r(2) = 0.115 and r(2) = 0.169, p < 0.001, respectively). Area strain calculation with IVUS elastography based on digital B-mode analysis is feasible and can be useful for tissue characterization and plaque vulnerability assessment.

Estimation of the viscoelastic properties of vessel walls using a computational model and Doppler ultrasound

Human arteries affected by atherosclerosis are characterized by altered wall viscoelastic properties. The possibility of noninvasively assessing arterial viscoelasticity in vivo would significantly contribute to the early diagnosis and prevention of this disease. This paper presents a noniterative technique to estimate the viscoelastic parameters of a vascular wall Zener model. The approach requires the simultaneous measurement of flow variations and wall displacements, which can be provided by suitable ultrasound Doppler instruments. Viscoelastic parameters are estimated by fitting the theoretical constitutive equations to the experimental measurements using an ARMA parameter approach. The accuracy and sensitivity of the proposed method are tested using reference data generated by numerical simulations of arterial pulsation in which the physiological conditions and the viscoelastic parameters of the model can be suitably varied. The estimated values quantitatively agree with the reference values, showing that the only parameter affected by changing the physiological conditions is viscosity, whose relative error was about 27% even when a poor signal-to-noise ratio is simulated. Finally, the feasibility of the method is illustrated through three measurements made at different flow regimes on a cylindrical vessel phantom, yielding a parameter mean estimation error of 25%.