Mechanical analysis of aortic aneurysms using 3D ultrasound : towards patient-specific risk assessment

Stijfheid van verwijde buikslagader is mogelijke indicator voor chirurgische ingree

Neurovascular coupling and the influence of luminal agonists via the endothelium

\u3cp\u3eA numerical model of neurovascular coupling (NVC) is presented based on neuronal activity coupled to vasodilation/contraction models via the astrocytic mediated perivascular K\u3csup\u3e+\u3c/sup\u3e and the smooth muscle cell Ca\u3csup\u3e2+\u3c/sup\u3e pathway. Luminal agonists acting on P2Y receptors on the endothelial cell surface provide a flux of IP\u3csub\u3e3\u3c/sub\u3e into the endothelial cytosol. This concentration of IP\u3csub\u3e3\u3c/sub\u3e is transported via gap junctions between endothelial and smooth muscle cells providing a source of sacroplasmic derived Ca\u3csup\u3e2+\u3c/sup\u3e in the smooth muscle cell. The model is able to relate a neuronal input signal to the corresponding vessel reaction. Results indicate that blood flow mediated IP\u3csub\u3e3\u3c/sub\u3e production via the agonist ATP has a substantial effect on the contraction/dilation dynamics of the SMC. The resulting variation in cytosolic Ca\u3csup\u3e2+\u3c/sup\u3e can enhance and inhibit the flow of blood to the cortical tissue. IP\u3csub\u3e3\u3c/sub\u3e coupling between endothelial and smooth muscle cells seems to be important in the dynamics of the smooth muscle cell. The VOCC channels are, due to the hyperpolarisation from K\u3csup\u3e+\u3c/sup\u3e SMC efflux, almost entirely closed and do not seem to play a significant role during neuronal activity. The current model shows that astrocytic Ca\u3csup\u3e2+\u3c/sup\u3e is not necessary for neurovascular coupling to occur in contrast to a number of experiments outlining the importance of astrocytic Ca\u3csup\u3e2+\u3c/sup\u3e in NVC, however this Ca\u3csup\u3e2+\u3c/sup\u3e pathway is not the only one mediating NVC. Importantly agonists in flowing blood have a significant influence on the endothelial and smooth muscle cell dynamics.\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

Reproducibility assessment of ultrasound-based aortic stiffness quantification and verification using Bi-axial tensile testing

\u3cp\u3eCurrent guidelines for abdominal aortic aneurysm (AAA) repair are primarily based on the maximum diameter. Since these methods lack robustness in decision making, new image-based methods for mechanical characterization have been proposed. Recently, time-resolved 3D ultrasound (4D US) in combination with finite element analysis was shown to provide additional risk estimators such as patient-specific peak wall stresses and wall stiffness in a non-invasive way. The aim of this study is to: 1) assess the reproducibility of this US-based stiffness measurement in vitro and in vivo, and 2) verify this 4D US stiffness using the gold standard: bi-axial tensile testing of the excised aortic tissue. For the in vitro study, 4D US data were acquired in an idealized inflation experiment using porcine aortas. The full aortic geometry was segmented and tracked over the cardiac cycle, and afterwards finite element analysis was performed by calibrating the finite element model to the measured US displacements to find the global aortic wall stiffness. For verification purposes, the porcine tissue was subjected to bi-axial tensile testing. Secondly, four AAA patients were included and 4D US data were acquired before open aortic surgery was performed. Similar to the experimental approach, the 4D US data were analyzed using the iterative finite element approach. During surgery, aortic tissue was harvested and the resulting tissue specimens were analyzed using bi-axial tensile testing. Finally, reproducibility was quantified for both methods. A high reproducibility was observed for the wall stiffness measurements using 4D US, i.e., an ICC of 0.91 (95% CI: 0.78–0.98) for the porcine aortas and an ICC of 0.98 (95% CI: 0.84–1.00) for the AAA samples. Verification with bi-axial tensile testing revealed a good agreement for the inflation experiment and a moderate agreement for the AAA patients, partially caused by the diseased state and inhomogeneities of the tissue. The performance of aortic stiffness characterization using 4D US revealed overall a high reproducibility and a moderate agreement with ex vivo mechanical testing. Future research should include more patient samples, to statistically assess the accuracy of the current in vivo method, which is not trivial due to the low number of open surgical interventions.\u3c/p\u3

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

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 based wall stress analysis of abdominal aortic aneurysms using multiperspective imaging

\u3cp\u3eBackground: Current clinical guidelines for surgical repair of abdominal aortic aneurysms (AAAs) are primarily based on maximum diameter assessment. From a biomechanical point of view, not only the diameter but also peak wall stresses will play an important role in rupture risk assessment. These methods require patient specific geometry which typically uses computed tomography (CT) or magnetic resonance imaging. Recently, wall stress analysis based on 3D ultrasound (US) has been proposed, and shows promising results. However, the major limitations in these studies were the use of manual segmentation and the limiting field of view of US. Therefore in this study, the AAA is imaged with multiperspective 3D ultrasound, merged to obtain a large field of view, and afterwards automatically segmented. Geometry and wall stress results were validated using CT imaging. Methods: Three dimensional US and CT data were available for 40 AAA patients (maximum diameter 34–61 mm). The full US based AAA geometry was determined using automatic segmentation, and when the aneurysm exceeded a single 3D volume, automatic fusion of multiple 3D US volumes was used. Wall stress analysis was performed for all AAA patients and percentile wall stresses were derived. The accuracy of the US based geometry and wall stress prediction was measured by comparison with CT data. Results: Estimated geometries derived from 3D US and CT data showed good similarity, with an overall median similarity index (SI) of 0.89 and interquartile range of 0.87–0.92, whereas the median Hausdorff distances (HD), a measure for the maximum local mismatch, was 4.6 (4.0–5.9) mm for all AAA geometries. Thereby, the wall stress results based on merged multiperspective 3D US data revealed a greater similarity to CT than single 3D US data. Conclusion: This study showed that large volume geometry assessment of AAAs using multiperspective 3D ultrasound, segmentation and fusion, and wall stress analysis is feasible in a robust and labour efficient manner.\u3c/p\u3

Automatic segmentation and registration of abdominal aortic aneurysms using 3D ultrasound

\u3cp\u3eAbdominal aortic aneurysms (AAAs) can lead to a fatal haemorrhage when ruptured. To predict the rupture risk of an AAA, Computed Tomography (CT) based wall stress analysis has been proposed and showed its merit in rupture risk assessment. However, CT has some drawbacks, e.g., ionising radiation exposure. As an alternative, 3D ultrasound (US) has shown its feasibility to determine AAA geometry. The major limitations were the lack of automated segmentation and the suboptimal field-of-view. Therefore, this study aims to assess 3D AAA geometry based on multiple 3D datasets using automatic segmentation and registration. Thirteen patients were included prospectively. For each patient CT data were available. For 8 patients one 3D US acquisition was insufficient to capture the complete AAA geometry. Therefore, a proximal and distal sub-volume were acquired and registered. Subsequently, an active contour model was applied to segment the 3D AAA geometry. Results reveal a good agreement with the CT geometries (Similarity indices = 0.78 - 0.93). The Hausdorff distance (HD) values were higher (median = 7.0 mm) at the proximal and distal sides compared to the middle (median = 5.4 mm). Moreover, the median HD decreased by 23% when registration and re-segmentation were applied. This study shows that automatic segmentation and registration of multiple 3D US volumes of AAAs is feasible to determine AAA geometry using 3D US.\u3c/p\u3