Multidimensional Analysis of Descending Aortic Growth After Acute Type A Aortic Dissection.

BACKGROUND: After repair of acute type A aortic dissection, typical geometric variables of conventional aortic surveillance focus on maximum diameter and its rate of growth, potentially missing important geometric changes elsewhere. We determined additional information provided by a semiautomated, 3-dimensional (3D), nonlinear growth model of the descending thoracic aorta after repair of type A aortic dissection. METHODS: Computed tomographic angiography data were retrospectively collected after hemiarch repair of type A aortic dissection. The descending aorta was systematically reconstructed to generate a 3D model made up of individual segments. The baseline and follow-up diameters were measured semiautomatically for each segment, and the nonlinear interval growth was determined. RESULTS: The fastest growing segment expanded at a rate of 3.8 mm/y (interquartile range, 2.2 to 5.4 mm/y) vs 0.6 mm/y (interquartile range, -0.3 to 1.7 mm/y) when measured at the original site of maximum diameter (P < .01). The maximum baseline diameter was a poor predictor of location with fastest growth (r = 0.10, P > .1). Using the society recommended growth limits, a greater proportion of patients would be considered "at risk" when assessed by our method vs conventional surveillance measures. CONCLUSIONS: Our model identifies areas of rapid aortic growth after repair of type A dissection that would likely be missed using current surveillance techniques. The increased precision, resolution, and reproducibility provided by our technique may improve on limitations of current surveillance techniques, provide novel geometric data on aortic remodeling, and contribute to the pursuit of a comprehensive patient-specific approach to aortic risk stratification.

Case Study: Intra-Patient Heterogeneity of Aneurysmal Tissue Properties.

Introduction: Current recommendations for surgical treatment of abdominal aortic aneurysms (AAAs) rely on the assessment of aortic diameter as a marker for risk of rupture. The use of aortic size alone may overlook the role that vessel heterogeneity plays in aneurysmal progression and rupture risk. The aim of the current study was to investigate intra-patient heterogeneity of mechanical and fluid mechanical stresses on the aortic wall and wall tissue histopathology from tissue collected at the time of surgical repair. Methods: Finite element analysis (FEA) and computational fluid dynamics (CFD) simulations were used to predict the mechanical wall stress and the wall shear stress fields for a non-ruptured aneurysm 2 weeks prior to scheduled surgery. During open repair surgery one specimen partitioned into different regions was collected from the patient's diseased aorta according to a pre-operative map. Histological analysis and mechanical testing were performed on the aortic samples and the results were compared with the predicted stresses. Results: The preoperative simulations highlighted the presence of altered local hemodynamics particularly at the proximal segment of the left anterior area of the aneurysm. Results from the post-operative assessment on the surgical samples revealed a considerable heterogeneity throughout the aortic wall. There was a positive correlation between elastin fragmentation and collagen content in the media. The tensile tests demonstrated a good prediction of the locally varying constitutive model properties predicted using geometrical variables, i.e., wall thickness and thrombus thickness. Conclusions: The observed large regional differences highlight the local response of the tissue to both mechanical and biological factors. Aortic size alone appears to be insufficient to characterize the large degree of heterogeneity in the aneurysmal wall. Local assessment of wall vulnerability may provide better risk of rupture predictions.

Local Diameter, Wall Stress, and Thrombus Thickness Influence the Local Growth of Abdominal Aortic Aneurysms.

PURPOSE: To investigate the influence of the local diameter, the intraluminal thrombus (ILT) thickness, and wall stress on the local growth rate of abdominal aortic aneurysms. METHODS: The infrarenal aortas of 90 asymptomatic abdominal aortic aneurysm (AAA) patients (mean age 70 years; 77 men) were retrospectively reconstructed from at least 2 computed tomography angiography scans (median follow-up of 1 year) and biomechanically analyzed with the finite element method. Each individual AAA model was automatically sliced orthogonally to the lumen centerline and represented by 100 cross sections with corresponding diameters, ILT thicknesses, and wall stresses. The data were grouped according to these parameters for comparison of differences among the variables. RESULTS: Diameter growth was continuously distributed over the entire aneurysm sac, reaching absolute and relative median peaks of 3.06 mm/y and 7.3%/y, respectively. The local growth rate was dependent on the local baseline diameter, the local ILT thickness, and for wall segments not covered by ILT, also on the local wall stress level (all p<0.001). For wall segments that were covered by a thick ILT layer, wall stress did not affect the growth rate (p=0.08). CONCLUSION: Diameter is not only a strong global predictor but also a local predictor of aneurysm growth. In addition, and independent of the diameter, the ILT thickness and wall stress (for the ILT-free wall) also influence the local growth rate. The high stress sensitivity of nondilated aortic walls suggests that wall stress peaks could initiate AAA formation. In contrast, local diameters and ILT thicknesses determine AAA growth for dilated and ILT-covered aortic walls.

Is There a Role for Biomechanical Engineering in Helping to Elucidate the Risk Profile of the Thoracic Aorta?

Clinical estimates of rupture and dissection risk of thoracic aortic aneurysms are based on nonsophisticated measurements of maximum diameter and growth rate. The use of aortic size alone may overlook the role that vessel heterogeneity plays in assessing the risk of catastrophic complications. Biomechanics may help provide a more nuanced approach to predict the behavior of thoracic aortic aneurysms. In this report, we review modeling studies with an emphasis on mechanical and fluid dynamics analyses. We identify open problems and highlight the future possibility of a multidisciplinary approach that includes biomechanics and imaging to evaluate the likelihood of rupture or dissection.

On the Impact of Intraluminal Thrombus Mechanical Behavior in AAA Passive Mechanics.

Intraluminal thrombus (ILT) is a pseudo-tissue that develops from coagulated blood, and is found in most abdominal aortic aneurysms (AAAs) of clinically relevant size. A number of studies have suggested that ILT mechanical characteristics may be related to AAA risk of rupture, even though there is still great controversy in this regard. ILT is isotropic and inhomogeneous and may appear as a soft (single-layered) or stiff (multilayered fibrotic) tissue. This paper aims to investigate how ILT constitution and topology influence the magnitude and location of peak wall stress (PWS). In total 21 patient-specific AAAs (diameter 4.2-5.4 cm) were reconstructed from computer tomography images and biomechanically analyzed using state-of-the-art modeling assumptions. Results indicated that PWS correlated stronger with ILT volume (ρ = 0.44, p = 0.05) and minimum thickness of ILT layer (ρ = 0.73, p = 0.001) than with maximum AAA diameter (ρ = 0.05, p = 0.82). On average PWS was 20% (SD 12%) higher for FE models that used soft instead of stiff ILT models (p < 0.001). PWS location strongly correlated with sites of minimum ILT thickness in the section of maximum AAA diameter and was independent from ILT stiffness. In addition, ILT heterogeneity, i.e., the spatial composition of soft and stiff thrombus tissue, can considerably influence stress in the AAA wall. The present study is limited to identification of influential biomechanical factors, and how its findings translate to an AAA rupture risk assessment remains to be explored by clinical studies.

Local Quantification of Wall Thickness and Intraluminal Thrombus Offer Insight into the Mechanical Properties of the Aneurysmal Aorta.

Wall stress is a powerful tool to assist clinical decisions in rupture risk assessment of abdominal aortic aneurysms. Key modeling assumptions that influence wall stress magnitude and distribution are the inclusion or exclusion of the intraluminal thrombus in the model and the assumption of a uniform wall thickness. We employed a combined numerical-experimental approach to test the hypothesis that abdominal aortic aneurysm (AAA) wall tissues with different thickness as well as wall tissues covered by different thrombus thickness, exhibit differences in the mechanical behavior. Ultimate tissue strength was measured from in vitro tensile testing of AAA specimens and material properties of the wall were estimated by fitting the results of the tensile tests to a histo-mechanical constitutive model. Results showed a decrease in tissue strength and collagen stiffness with increasing wall thickness, supporting the hypothesis of wall thickening being mediated by accumulation of non load-bearing components. Additionally, an increase in thrombus deposition resulted in a reduction of elastin content, collagen stiffness and tissue strength. Local wall thickness and thrombus coverage may be used as surrogate measures of local mechanical properties of the tissue, and therefore, are possible candidates to improve the specificity of AAA wall stress and rupture risk evaluations.

In vivo strain assessment of the abdominal aortic aneurysm.

The only criteria currently used to inform surgical decision for abdominal aortic aneurysms are maximum diameter (>5.5 cm) and rate of growth, even though several studies have identified the need for more specific indicators of risk. Patient-specific biomechanical variables likely to affect rupture risk would be a valuable addition to the science of understanding rupture risk and prove to be a life saving benefit for patients. Local deformability of the aorta is related to the local mechanical properties of the wall and may provide indication on the state of weakening of the wall tissue. We propose a 3D image-based approach to compute aortic wall strain maps in vivo. The method is applicable to a variety of imaging modalities that provide sequential images at different phases in the cardiac cycle. We applied the method to a series of abdominal aneurysms imaged using cine-MRI obtaining strain maps at different phases in the cardiac cycle. These maps could be used to evaluate the distensibility of an aneurysm at baseline and at different follow-up times and provide an additional index to clinicians to facilitate decisions on the best course of action for a specific patient.

Multidimensional growth measurements of abdominal aortic aneurysms.

BACKGROUND: Monitoring the expansion of abdominal aortic aneurysms (AAAs) is critical to avoid aneurysm rupture in surveillance programs, for instance. However, measuring the change of the maximum diameter over time can only provide limited information about AAA expansion. Specifically, regions of fast diameter growth may be missed, axial growth cannot be quantified, and shape changes of potential interest for decisions related to endovascular aneurysm repair cannot be captured. METHODS: This study used multiple centerline-based diameter measurements between the renal arteries and the aortic bifurcation to quantify AAA growth in 51 patients from computed tomography angiography (CTA) data. Criteria for inclusion were at least 1 year of patient follow-up and the availability of at least two sufficiently high-resolution CTA scans that allowed an accurate three-dimensional reconstruction. Consequently, 124 CTA scans were systematically analyzed by using A4clinics diagnostic software (VASCOPS GmbH, Graz, Austria), and aneurysm growth was monitored at 100 cross-sections perpendicular to the centerline. RESULTS: Monitoring diameter development over the entire aneurysm revealed the sites of the fastest diameter growth, quantified the axial growth, and showed the evolution of the neck morphology over time. Monitoring the development of an aneurysm's maximum diameter or its volume over time can assess the mean diameter growth (r = 0.69, r = 0.77) but not the maximum diameter growth (r = 0.43, r = 0.34). The diameter growth measured at the site of maximum expansion was ~16%/y, almost four times larger than the mean diameter expansion of 4.4%/y. The sites at which the maximum diameter growth was recorded did not coincide with the position of the maximum baseline diameter (ρ = 0 .12; P = .31). The overall aneurysm sac length increased from 84 to 89 mm during the follow-up (P < .001), which relates to the median longitudinal growth of 3.5%/y. The neck length shortened, on average, by 6.2% per year and was accompanied by a slight increase in neck angulation. CONCLUSIONS: Neither maximum diameter nor volume measurements over time are able to measure the fastest diameter growth of the aneurysm sac. Consequently, expansion-related wall weakening might be inappropriately reflected by this type of surveillance data. In contrast, localized spots of fast diameter growth can be detected through multiple centerline-based diameter measurements over the entire aneurysm sac. This information might further reinforce the quality of aneurysm surveillance programs.

Review: the role of biomechanical modeling in the rupture risk assessment for abdominal aortic aneurysms.

AAA disease is a serious condition and a multidisciplinary approach including biomechanics is needed to better understand and more effectively treat this disease. A rupture risk assessment is central to the management of AAA patients, and biomechanical simulation is a powerful tool to assist clinical decisions. Central to such a simulation approach is a need for robust and physiologically relevant models. Vascular tissue senses and responds actively to changes in its mechanical environment, a crucial tissue property that might also improve the biomechanical AAA rupture risk assessment. Specifically, constitutive modeling should not only focus on the (passive) interaction of structural components within the vascular wall, but also how cells dynamically maintain such a structure. In this article, after specifying the objectives of an AAA rupture risk assessment, the histology and mechanical properties of AAA tissue, with emphasis on the wall, are reviewed. Then a histomechanical constitutive description of the AAA wall is introduced that specifically accounts for collagen turnover. A test case simulation clearly emphasizes the need for constitutive descriptions that remodels with respect to the mechanical loading state. Finally, remarks regarding modeling of realistic clinical problems and possible future trends conclude the article.

Turnover of fibrillar collagen in soft biological tissue with application to the expansion of abdominal aortic aneurysms.

A better understanding of the inherent properties of vascular tissue to adapt to its mechanical environment is crucial to improve the predictability of biomechanical simulations. Fibrillar collagen in the vascular wall plays a central role in tissue adaptation owing to its relatively short lifetime. Pathological alterations of collagen turnover may fail to result in homeostasis and could be responsible for abdominal aortic aneurysm (AAA) growth at later stages of the disease. For this reason our previously reported multiscale constitutive framework (Martufi, G. & Gasser, T. C. 2011 J. Biomech. 44, 2544-2550 (doi:10.1016/j.jbiomech.2011.07.015)) has been enriched by a collagen turnover model. Specifically, the framework's collagen fibril level allowed a sound integration of vascular wall biology, and the impact of collagen turnover on the macroscopic properties of AAAs was studied. To this end, model parameters were taken from the literature and/or estimated from clinical follow-up data of AAAs (on average 50.7 mm-large). Likewise, the in vivo stretch of the AAA wall was set, such that 10 per cent of collagen fibres were engaged. Results showed that the stretch spectrum, at which collagen fibrils are deposed, is the most influential parameter, i.e. it determines whether the vascular geometry grows, shrinks or remains stable over time. Most importantly, collagen turnover also had a remarkable impact on the macroscopic stress field. It avoided high stress gradients across the vessel wall, thus predicted a physiologically reasonable stress field. Although the constitutive model could be successfully calibrated to match the growth of small AAAs, a rigorous validation against experimental data is crucial to further explore the model's descriptive and predictive capabilities.

A constitutive model for vascular tissue that integrates fibril, fiber and continuum levels with application to the isotropic and passive properties of the infrarenal aorta.

A fundamental understanding of the mechanical properties of the extracellular matrix (ECM) is critically important to quantify the amount of macroscopic stress and/or strain transmitted to the cellular level of vascular tissue. Structural constitutive models integrate histological and mechanical information, and hence, allocate stress and strain to the different microstructural components of the vascular wall. The present work proposes a novel multi-scale structural constitutive model of passive vascular tissue, where collagen fibers are assembled by proteoglycan (PG) cross-linked collagen fibrils and reinforce an otherwise isotropic matrix material. Multiplicative kinematics account for the straightening and stretching of collagen fibrils, and an orientation density function captures the spatial organization of collagen fibers in the tissue. Mechanical and structural assumptions at the collagen fibril level define a piece-wise analytical stress-stretch response of collagen fibers, which in turn is integrated over the unit sphere to constitute the tissue's macroscopic mechanical properties. The proposed model displays the salient macroscopic features of vascular tissue, and employs the material and structural parameters of clear physical meaning. Likewise, the constitutive concept renders a highly efficient multi-scale structural approach that allows for the numerical analysis at the organ level. Model parameters were estimated from isotropic mean-population data of the normal and aneurysmatic aortic wall and used to predict in-vivo stress states of patient-specific vascular geometries, thought to demonstrate the robustness of the particular Finite Element (FE) implementation. The collagen fibril level of the multi-scale constitutive formulation provided an interface to integrate vascular wall biology and to account for collagen turnover.

Quantitative assessment of abdominal aortic aneurysm geometry.

Recent studies have shown that the maximum transverse diameter of an abdominal aortic aneurysm (AAA) and expansion rate are not entirely reliable indicators of rupture potential. We hypothesize that aneurysm morphology and wall thickness are more predictive of rupture risk and can be the deciding factors in the clinical management of the disease. A non-invasive, image-based evaluation of AAA shape was implemented on a retrospective study of 10 ruptured and 66 unruptured aneurysms. Three-dimensional models were generated from segmented, contrast-enhanced computed tomography images. Geometric indices and regional variations in wall thickness were estimated based on novel segmentation algorithms. A model was created using a J48 decision tree algorithm and its performance was assessed using ten-fold cross validation. Feature selection was performed using the χ2-test. The model correctly classified 65 datasets and had an average prediction accuracy of 86.6% (κ=0.37). The highest ranked features were sac length, sac height, volume, surface area, maximum diameter, bulge height, and intra-luminal thrombus volume. Given that individual AAAs have complex shapes with local changes in surface curvature and wall thickness, the assessment of AAA rupture risk should be based on the accurate quantification of aneurysmal sac shape and size.

Semiautomatic vessel wall detection and quantification of wall thickness in computed tomography images of human abdominal aortic aneurysms.

PURPOSE: Quantitative measurements of wall thickness in human abdominal aortic aneurysms (AAAs) may lead to more accurate methods for the evaluation of their biomechanical environment. METHODS: The authors describe an algorithm for estimating wall thickness in AAAs based on intensity histograms and neural networks involving segmentation of contrast enhanced abdominal computed tomography images. The algorithm was applied to ten ruptured and ten unruptured AAA image data sets. Two vascular surgeons manually segmented the lumen, inner wall, and outer wall of each data set and a reference standard was defined as the average of their segmentations. Reproducibility was determined by comparing the reference standard to lumen contours generated automatically by the algorithm and a commercially available software package. Repeatability was assessed by comparing the lumen, outer wall, and inner wall contours, as well as wall thickness, made by the two surgeons using the algorithm. RESULTS: There was high correspondence between automatic and manual measurements for the lumen area (r = 0.978 and r = 0.996 for ruptured and unruptured aneurysms, respectively) and between vascular surgeons (r = 0.987 and r = 0.992 for ruptured and unruptured aneurysms, respectively). The authors' automatic algorithm showed better results when compared to the reference with an average lumen error of 3.69%, which is less than half the error between the commercially available application Simpleware and the reference (7.53%). Wall thickness measurements also showed good agreement between vascular surgeons with average coefficients of variation of 10.59% (ruptured aneurysms) and 13.02% (unruptured aneurysms). Ruptured aneurysms exhibit significantly thicker walls (1.78 +/- 0.39 mm) than unruptured ones (1.48 +/- 0.22 mm), p = 0.044. CONCLUSIONS: While further refinement is needed to fully automate the outer wall segmentation algorithm, these preliminary results demonstrate the method's adequate reproducibility and low interobserver variability.

Micromechanical characterization of intra-luminal thrombus tissue from abdominal aortic aneurysms.

The reliable assessment of Abdominal Aortic Aneurysm rupture risk is critically important in reducing related mortality without unnecessarily increasing the rate of elective repair. Intra-luminal thrombus (ILT) has multiple biomechanical and biochemical impacts on the underlying aneurysm wall and thrombus failure might be linked to aneurysm rupture. Histological slices from 7 ILTs were analyzed using a sequence of automatic image processing and feature analyzing steps. Derived microstructural data was used to define Representative Volume Elements (RVE), which in turn allowed the estimation of microscopic material properties using the non-linear Finite Element Method. ILT tissue exhibited complex microstructural arrangement with larger pores in the abluminal layer than in the luminal layer. The microstructure was isotropic in the abluminal layer, whereas pores started to orient along the circumferential direction towards the luminal site. ILT's macroscopic (reversible) deformability was supported by large pores in the microstructure and the inhomogeneous structure explains in part the radially changing macroscopic constitutive properties of ILT. Its microscopic properties decreased just slightly from the luminal to the abluminal layer. The present study provided novel microstructural and micromechanical data of ILT tissue, which is critically important to further explore the role of the ILT in aneurysm rupture. Data provided in this study allow an integration of structural information from medical imaging for example, to estimate ILT's macroscopic mechanical properties.

Three-dimensional geometrical characterization of abdominal aortic aneurysms: image-based wall thickness distribution.

The clinical assessment of abdominal aortic aneurysm (AAA) rupture risk is based on the quantification of AAA size by measuring its maximum diameter from computed tomography (CT) images and estimating the expansion rate of the aneurysm sac over time. Recent findings have shown that geometrical shape and size, as well as local wall thickness may be related to this risk; thus, reliable noninvasive image-based methods to evaluate AAA geometry have a potential to become valuable clinical tools. Utilizing existing CT data, the three-dimensional geometry of nine unruptured human AAAs was reconstructed and characterized quantitatively. We propose and evaluate a series of 1D size, 2D shape, 3D size, 3D shape, and second-order curvature-based indices to quantify AAA geometry, as well as the geometry of a size-matched idealized fusiform aneurysm and a patient-specific normal abdominal aorta used as controls. The wall thickness estimation algorithm, validated in our previous work, is tested against discrete point measurements taken from a cadaver tissue model, yielding an average relative difference in AAA wall thickness of 7.8%. It is unlikely that any one of the proposed geometrical indices alone would be a reliable index of rupture risk or a threshold for elective repair. Rather, the complete geometry and a positive correlation of a set of indices should be considered to assess the potential for rupture. With this quantitative parameter assessment, future research can be directed toward statistical analyses correlating the numerical values of these parameters with the risk of aneurysm rupture or intervention (surgical or endovascular). While this work does not provide direct insight into the possible clinical use of the geometric parameters, we believe it provides the foundation necessary for future efforts in that direction.