Biomechanical characterization of tissue types in murine dissecting aneurysms based on histology and 4D ultrasound-derived strain.

Abdominal aortic aneurysm disease is the local enlargement of the aorta, typically in the infrarenal section, causing up to 200,000 deaths/year. In vivo information to characterize the individual elastic properties of the aneurysm wall in terms of rupture risk is lacking. We used a method that combines 4D ultrasound and direct deformation estimation to compute in vivo 3D Green-Lagrange strain in murine angiotensin II-induced dissecting aortic aneurysms, a commonly used mouse model. After euthanasia, histological staining of cross-sectional sections along the aorta was performed in areas where in vivo strains had previously been measured. The histological sections were segmented into intact and fragmented elastin, thrombus with and without red blood cells, and outer vessel wall including the adventitia. Meshes were then created from the individual contours based on the histological segmentations. The isolated contours of the outer wall and lumen from both imaging modalities were registered individually using a coherent point drift algorithm. 2D finite element models were generated from the meshes, and the displacements from the registration were used as displacement boundaries of the lumen and wall contours. Based on the resulting deformed contours, the strains recorded were grouped according to segmented tissue regions. Strains were highest in areas containing intact elastin without thrombus attachment. Strains in areas with intact elastin and thrombus attachment, as well as areas with disrupted elastin, were significantly lower. Strains in thrombus regions with red blood cells were significantly higher compared to thrombus regions without. We then compared this analysis to statistical distribution indices and found that the results of each aligned, elucidating the relationship between vessel strain and structural changes. This work demonstrates the possibility of advancing in vivo assessments to a microstructural level ultimately improving patient outcomes.

Using averaged models from 4D ultrasound strain imaging allows to significantly differentiate local wall strains in calcified regions of abdominal aortic aneurysms.

Abdominal aortic aneurysms are a degenerative disease of the aorta associated with high mortality. To date, in vivo information to characterize the individual elastic properties of the aneurysm wall in terms of rupture risk is lacking. We have used time-resolved 3D ultrasound strain imaging to calculate spatially resolved in-plane strain distributions characterized by mean and local maximum strains, as well as indices of local variations in strains. Likewise, we here present a method to generate averaged models from multiple segmentations. Strains were then calculated for single segmentations and averaged models. After registration with aneurysm geometries based on CT-A imaging, local strains were divided into two groups with and without calcifications and compared. Geometry comparison from both imaging modalities showed good agreement with a root mean squared error of 1.22 ± 0.15 mm and Hausdorff Distance of 5.45 ± 1.56 mm (mean ± sd, respectively). Using averaged models, circumferential strains in areas with calcifications were 23.2 ± 11.7% (mean ± sd) smaller and significantly distinguishable at the 5% level from areas without calcifications. For single segmentations, this was possible only in 50% of cases. The areas without calcifications showed greater heterogeneity, larger maximum strains, and smaller strain ratios when computed by use of the averaged models. Using these averaged models, reliable conclusions can be made about the local elastic properties of individual aneurysm (and long-term observations of their change), rather than just group comparisons. This is an important prerequisite for clinical application and provides qualitatively new information about the change of an abdominal aortic aneurysm in the course of disease progression compared to the diameter criterion.

Comparison of Abdominal Aortic Aneurysm Sac and Neck Wall Motion with 4D Ultrasound Imaging.

OBJECTIVE: The rupture of abdominal aortic aneurysms (AAAs) is associated with high mortality despite surgical developments. The determination of aneurysm diameter allows for follow up of aneurysm growth but fails in precisely predicting aneurysm rupture. In this study, time resolved three dimensional ultrasound (4D ultrasound) based wall motion indices (WMIs) are investigated to see if they are capable of distinguishing between uneven affected regions of the aneurysm wall. METHODS: In a prospective study, 56 patients with an AAA were examined using 4D ultrasound. Local longitudinal, circumferential, and shear strains were computed using custom methods. The deformation of the neck and sac of each aneurysm was characterised by statistical indices of the obtained distributions of local wall strains (WMIs): mean and peak strain, heterogeneity index, and local strain ratio. The locations of regions with highest local peak strain were determined. RESULTS: Compared with the aneurysm neck, the sac is characterised by low mean strain, but highly heterogeneous deformation, described by high local strain ratio and heterogeneity index. Differences were highly significant (p < .001) for all strain components. The regions with the highest circumferential peak strain were found more often in the posterior part of the aneurysm neck (p < .050) and sac (p < .001) regions, compared with other wall regions. No statistically significant correlation was found between the WMIs and maximum AAA diameter, except for longitudinal mean strain, which decreased with the increasing diameter (rho = -.42, p < .010). CONCLUSION: Characterisation of wall kinematics by 4D ultrasound based WMIs provides a new and independent criterion for the distinction of diseased tissue in the AAA sac and the less affected neck region. This is a promising step towards the establishment of new biomarkers to differentiate between the mechanical instability of the AAA and rupture risk.