Predicting the Risk of Rupture of Abdominal Aortic Aneurysms by Utilizing Various Geometrical Parameters: Revisiting the Diameter Criterion

Modelling in congenital heart disease. Art or science?

Despite the advances in imaging modalities and surgical techniques, the management of adults with congenital heart disease (ACHD) over the years has remained largely empirical rather than evidence-based. Animal models have been difficult to develop and very costly, while clinical trials are difficult to design and perform in ACHD, leaving gaps in our understanding of the pathophysiology and treatment of congenital heart disease. Disease modelling, both hypothetical and patient-specific, provides an alternative solution to many of these problems. Advances in cardiovascular imaging and diagnostics have led to the easy acquisition of large quantities of structural and functional information, which cannot be handled "intuitively". Computational modelling introduces mathematical rigour in the analysis and utilisation of these data by quantitative simulation and testing of clinically relevant hypotheses through experimentally validated models. Close multidisciplinary collaboration between bioengineers and clinicians is essential for transforming data and images derived from models of disease into clinically useful information.

Vessel asymmetry as an additional diagnostic tool in the assessment of abdominal aortic aneurysms

OBJECTIVE

Abdominal aortic aneurysm (AAA) rupture is believed to occur when the local mechanical stress exceeds the local mechanical strength of the wall tissue. On the basis of this hypothesis, the knowledge of the stress acting on the wall of an unruptured aneurysm could be useful in determining the risk of rupture. The role of asymmetry has previously been identified in idealized AAA models and is now studied using realistic AAAs in the current work.

METHODS

Fifteen patient-specific AAAs were studied to estimate the relationship between wall stress and geometrical parameters. Three-dimensional AAA models were reconstructed from computed tomography scan data. The stress distribution on the AAA wall was evaluated by the finite element method, and peak wall stress was compared with both diameter and centerline asymmetry. A simple method of determining asymmetry was adapted and developed. Statistical analyses were performed to determine potential significance of results.

RESULTS

Mean von Mises peak wall stress +/- standard deviation was 0.4505 +/- 0.14 MPa (range, 0.3157-0.9048 MPa). Posterior wall stress increases with anterior centerline asymmetry. Peak stress increased by 48% and posterior wall stress by 38% when asymmetry was introduced into a realistic AAA model.

CONCLUSION

The relationship between posterior wall stress and AAA asymmetry showed that excessive bulging of one surface results in elevated wall stress on the opposite surface. Assessing the degree of bulging and asymmetry that is experienced in an individual AAA may be of benefit to surgeons in the decision-making process and may provide a useful adjunct to diameter as a surgical intervention guide.

Beyond fusiform and saccular: a novel quantitative tortuosity index may help classify aneurysm shape and predict aneurysm rupture potential

While saccular abdominal aortic aneurysms (AAAs) are thought to be more prone to rupture than fusiform aneurysms, attempts to validate this observation have been limited by the inability to quantitatively define the three-dimensional shape of an aorta. A quantitative three-dimensional shape model may distinguish among shape classes and ultimately be useful in identifying aneurysms at risk for rupture. Three-dimensional luminal surface data of AAAs were generated from computed tomographic (CT) images of 15 patients with small aneurysms (< or =5.5 cm maximal transverse diameter). The centerline was used to construct a shape classification based upon the orthographic projection of the centerline about its central axis. The extent and direction of the individual deviations were quantified as areas on the plane of projection to create a shape classification. Hierarchical cluster analysis was used to verify distinct shape classes. A tortuosity index was calculated as a function of the centerline projection. AAA shape was calculated as a tortuosity index and classified into distinct classes of minimal or increased three-dimensional tortuosity. Thrombus could change the tortuosity index or shape classification of an aneurysm. In several patients with serial CT scans, the tortuosity index changed over time and was correlated with rupture; in three AAAs that ruptured the mean tortuosity increased 29% whereas the mean transverse diameter increased 3.3%. Expanding AAAs develop specific, quantifiable shapes that can be expressed as a quantitative tortuosity index that may be relevant to their natural history. The three-dimensional features of this shape model provide a novel and potentially clinically relevant adjunct to maximal transverse diameter. Larger studies are needed to correlate the tortuosity index with finite element models and the ability to predict aneurysm rupture.

A comparison of modelling techniques for computing wall stress in abdominal aortic aneurysms

Background

Aneurysms, in particular abdominal aortic aneurysms (AAA), form a significant portion of cardiovascular related deaths. There is much debate as to the most suitable tool for rupture prediction and interventional surgery of AAAs, and currently maximum diameter is used clinically as the determining factor for surgical intervention. Stress analysis techniques, such as finite element analysis (FEA) to compute the wall stress in patient-specific AAAs, have been regarded by some authors to be more clinically important than the use of a "one-size-fits-all" maximum diameter criterion, since some small AAAs have been shown to have higher wall stress than larger AAAs and have been known to rupture.

Methods

A patient-specific AAA was selected from our AAA database and 3D reconstruction was performed. The AAA was then modelled in this study using three different approaches, namely, AAA(SIMP), AAA(MOD) and AAA(COMP), with each model examined using linear and non-linear material properties. All models were analysed using the finite element method for wall stress distributions.

Results

Wall stress results show marked differences in peak wall stress results between the three methods. Peak wall stress was shown to reduce when more realistic parameters were utilised. It was also noted that wall stress was shown to reduce by 59% when modelled using the most accurate non-linear complex approach, compared to the same model without intraluminal thrombus.

Conclusion

The results here show that using more realistic parameters affect resulting wall stress. The use of simplified computational modelling methods can lead to inaccurate stress distributions. Care should be taken when examining stress results found using simplified techniques, in particular, if the wall stress results are to have clinical importance.