Including surrounding tissue improves ultrasound-based 3D mechanical characterization of abdominal aortic aneurysms

\u3cp\u3eObjectives: In this study the influence of surrounding tissues including the presence of the spine on wall stress analysis and mechanical characterization of abdominal aortic aneurysms using ultrasound imaging has been investigated. Methods: Geometries of 7 AAA patients and 11 healthy volunteers were acquired using 3-D ultrasound and converted to finite element based models. Model complexity of externally unsupported (aorta-only) models was complemented with inclusion of both soft tissue around the aorta and a spine support dorsal to the aorta. Computed 3-D motion of the aortic wall was verified by means of ultrasound speckle tracking. Resulting stress, strain, and estimated shear moduli were analyzed to quantify the effect of adding surrounding material supports. Results: An improved agreement was shown between the ultrasound measurements and the finite element tissue and spine models compared to the aorta-only models. Peak and 99-percentile Von Mises stress showed an overall decrease of 23–30%, while estimated shear modulus decreased with 12–20% after addition of the soft tissue. Shear strains in the aortic wall were higher in areas close to the spine compared to the anterior region. Conclusions: Improving model complexity with surrounding tissue and spine showed a homogenization of wall stresses, reduction in homogeneity of shear strain at the posterior side of the AAA, and a decrease in estimated aortic wall shear modulus. Future research will focus on the importance of a patient-specific spine geometry and location.\u3c/p\u3

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

\u3cp\u3eAims 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 (Ï = 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.\u3c/p\u3

Improved ultrasound-based mechanical characterization of abdominal aortic aneurysms

\u3cp\u3eNovel 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.\u3c/p\u3

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

\u3cp\u3eAbdominal 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.\u3c/p\u3

Ultrasound functional imaging in an ex vivo beating porcine heart platform

\u3cp\u3eIn 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.\u3c/p\u3

Patient specific wall stress analysis and mechanical characterization of abdominal aortic aneurysms using 4D ultrasound

Wall stress analysis of abdominal aortic aneurysms (AAAs) using 4D ultrasound (US) is a promising technique to improve rupture risk stratification. This study shows similar wall stress results as reported with other image modalities, now for the entire diameter range. Besides wall stresses, 4D-US offers the opportunity to determine patient specific material properties simultaneously. After calibrating the finite element model to the 4D-US wall motion, larger AAAs reveal stiffer material behavior than the smaller AAAs. This methodology enables longitudinal studies on rupture risk and growth by monitoring patient specific wall stresses and material properties