Nj Niels Petterson

Influence of limited field-of-view on wall stress analysis in abdominal aortic aneurysms

Abdominal aortic aneurysms (AAAs) are local dilations of the aorta which can lead to a fatal hemorrhage when ruptured. Wall stress analysis of AAAs has been widely reported in literature to predict the risk of rupture. Usually, the complete AAA geometry including the aortic bifurcation is obtained by computed tomography (CT). However, performing wall stress analysis based on 3D ultrasound (3D US) has many advantages over CT, although, the field-of-view (FOV) of 3D US is limited and the aortic bifurcation is not easily imaged. In this study, the influence of a limited FOV is examined by performing wall stress analysis on CT-based (total) AAA geometries in 10 patients, and observing the changes in 99th percentile stresses and median stresses while systematically limiting the FOV. Results reveal that changes in the 99th percentile wall stresses are less than 10% when the proximal and distal shoulders of the aneurysm are in the shortened FOV. Wall stress results show that the presence of the aortic bifurcation in the FOV does not influence the wall stresses in high stress regions. Hence, the necessity of assessing the complete FOV, including the aortic bifurcation, is of minor importance. When the proximal and distal shoulders of the AAA are in the FOV, peak wall stresses can be detected adequately.

Semi-3D strain imaging in normal and LVAD supported ex vivo beating hearts

Cardiac strain imaging (CSI) is a powerful technique which is able to quantify and localize cardiac defects. However, validation and reproducibility remain major issues. In this study, semi-3D CSI was performed on ex vivo beating porcine hearts to quantify the reproducibility of CSI and examine the feasibility of clinical application of CSI for the assessment of cardiac function in patients with a left ventricular assist device. Results reveal highly reproducible strain results between heartbeats. However, differences were found between hearts, due to biological variation and condition of the hearts. Supported hearts showed a decrease in strain and strain rate, and strain pattern with higher pump speeds. Future work should include translation of the measured parameters into quantitive assessment of cardiac function and validation in a long-term patient study.

Quantification of aortic stiffness and wall stress in healthy volunteers and abdominal aortic aneurysm patients using time-resolved 3D ultrasound: a comparison study

Aims Using non-invasive 3D ultrasound, peak wall stress (PWS) and aortic stiffness can be evaluated, which may provide additional criteria in abdominal aortic aneurysm (AAA) risk assessment. In this study, these measures were determined in both young and age-matched individuals, and AAA patients while its relation to age, maximum diameter, and growth was assessed statistically. Methods and results Time-resolved 3D-US data were acquired for 30 volunteers and 65 AAA patients. The aortic geometry was segmented, and tracked over the cardiac cycle using 3D speckle tracking to characterize the wall motion. Wall stress analysis was performed using finite element analysis. Model parameters were optimized until the model output matched the measured 3D displacements. A significant increase in aortic stiffness was measured between the age-matched volunteers [median 0.58, interquartile range (IQR) 0.48-0.71 kPa⋅m] and the small AAA patients (median 1.84, IQR 1.38-2.46 kPa⋅m; P < 0.001). In addition, an increase in aortic stiffness was evaluated between the small (30-39 mm) and large (≥50 mm) AAAs (median 2.72, IQR 1.99-3.14 kPa⋅m; P = 0.01). The 99th percentile wall stress showed a positive correlation with diameter (ρ = 0.73, P < 0.001), and significant differences between age-matched volunteers and AAA patients. Conclusion The AAA pathology causes an early and significant increase in aortic stiffness of the abdominal aorta, even after correcting for the expected effect of ageing and differences in arterial pressure. Moreover, some AAAs revealed relatively high PWS, although the maximum diameter was below the threshold for surgical repair. Using the current method, these measures become available during follow-up, which could improve AAA rupture risk assessment.

Improved ultrasound-based mechanical characterization of abdominal aortic aneurysms

Novel methods for determining rupture risk in abdominal aortic aneurysms (AAAs) have focused primarily on CT-based wall stress analysis using finite element models (FEMs). Recent studies have demonstrated ultrasound (US) based FEM, and the possibility of using inverse FEM analysis: matching displacements between the models and US to find patient specific aortic stiffness. This requires an accurate representation of deformation of the FEM-based aorta, which could be highly influenced by the presence of surrounding tissue. Typically, these methods solely include the vessel, fixed on both ends. The abdominal aorta (AA) however is surrounded by other tissue including the spine, which acts as a stiff boundary. In this study, AA(A) models based on 4D US were constructed with increasing complexity. The importance of modelling surrounding tissues was investigated by comparing mechanical parameters.

In-vivo mechanical characterization of abdominal aortic aneurysms and healthy aortas using 4D ultrasound: A comparison study

Abdominal aortic aneurysms are lethal in 80% of all cases when ruptured. Current guidelines for AAA repair are mainly based on the diameter, which has its shortcomings. Hence, a more patient-specific rupture risk assessment is needed. In this study, methods for elastography and wall stress analysis using 4D ultrasound (US) were developed. Patient-specific material properties and peak wall stresses were compared between young and age-matched volunteers, and AAA patients.

Ultrasound functional imaging in an ex vivo beating porcine heart platform

In recent years, novel ultrasound functional imaging (UFI) techniques have been introduced to assess cardiac function by measuring, e.g. cardiac output (CO) and/or myocardial strain. Verification and reproducibility assessment in a realistic setting remain major issues. Simulations and phantoms are often unrealistic, whereas in vivo measurements often lack crucial hemodynamic parameters or ground truth data, or suffer from the large physiological and clinical variation between patients when attempting clinical validation. Controlled validation in certain pathologies is cumbersome and often requires the use of lab animals. In this study, an isolated beating pig heart setup was adapted and used for performance assessment of UFI techniques such as volume assessment and ultrasound strain imaging. The potential of performing verification and reproducibility studies was demonstrated. For proof-of-principle, validation of UFI in pathological hearts was examined. Ex vivo porcine hearts (n  =  6, slaughterhouse waste) were resuscitated and attached to a mock circulatory system. Radio frequency ultrasound data of the left ventricle were acquired in five short axis views and one long axis view. Based on these slices, the CO was measured, where verification was performed using flow sensor measurements in the aorta. Strain imaging was performed providing radial, circumferential and longitudinal strain to assess reproducibility and inter-subject variability under steady conditions. Finally, strains in healthy hearts were compared to a heart with an implanted left ventricular assist device, simulating a failing, supported heart. Good agreement between ultrasound and flow sensor based CO measurements was found. Strains were highly reproducible (intraclass correlation coefficients  >0.8). Differences were found due to biological variation and condition of the hearts. Strain magnitude and patterns in the assisted heart were available for different pump action, revealing large changes compared to the normal condition. The setup provides a valuable benchmarking platform for UFI techniques. Future studies will include work on different pathologies and other means of measurement verification.

Influence of surrounding tissue on 3D abdominal aortic elastography

Combining ultrasound measurements with finite element models (FEMs) is a novel technique to assess mechanical material parameters of vasculature. The stiffness of the FEM is calibrated iteratively until the displacements of the FEM match those measured by US. However, the influence of surrounding tissue, e.g. the spine in the case of abdominal aortas, is not taken into account. These could have a significant effect on the displacements obtained from the FEM.

A dedicated guided-search displacement algorithm for cardiovascular strain imaging

Traditionally, an exhaustive search is performed for 2D strain imaging, often using a priori knowledge or an iterative, multi-level (ML) approach to improve strain quality. In this study, a dedicated guided-search algorithm (CGS), using a seeding procedure that was specifically designed for cardiovascular applications, is introduced and applied to simulation data, and data of aortas, both in vitro and in vitro. The method was compared to two existing methods, a multi-level algorithm and a conventional guided-search approach (GS). Results reveal an improvement of SNRe for the simulation data improvement. The (C)GS method showed good strain results, even when no filtering was applied to the displacements. The in vitro data revealed similar results, however, the in vivo data revealed significant improvement when using the CGS approach over the ML algorithm, whereas the GS method was not able to track the vessel wall over time. A next step will be to apply this algorithm to cardiac data and incorporate stretching.