Automatic determination of the dynamic geometry of abdominal aortic aneurysm from MR with application to wall stress simulations

Geometrical methods for level set based abdominal aortic aneurysm thrombus and outer wall 2D image segmentation

Abdominal aortic aneurysm (AAA) is a localized dilatation of the aortic wall. Accurate measurements of its geometric characteristics are critical for a reliable estimate of AAA rupture risk. However, current imaging modalities do not provide sufficient contrast to distinguish thrombus from surrounding tissue thus making the task of segmentation quite challenging. The main objective of this paper is to address this problem and accurately extract the thrombus and outer wall boundaries from cross sections of a 3D AAA image data set (CTA). This is achieved by new geometrical methods applied to the boundary curves obtained by a Level Set Method (LSM). Such methods address the problem of leakage of a moving front into sectors of similar intensity and that of the presence of calcifications. The versatility of the methods is tested by creating artificial images which simulate the real cases. Segmentation quality is quantified by comparing the results with a manual segmentation of the slices of ten patient data sets. Sensitivity to the parameter settings and reproducibility are analyzed. This is the first work to our knowledge that utilizes the level set framework to extract both the thrombus and external AAA wall boundaries.

Towards patient-specific risk assessment of abdominal aortic aneurysm

Diagnosis of vascular disease and selection and planning of therapy are to a large extent based on the geometry of the diseased vessel. Treatment of a particular vascular disease is usually considered if the geometrical parameter that characterizes the severity of the disease, e.g. % vessel narrowing, exceeds a threshold. The thresholds that are used in clinical practice are based on epidemiological knowledge, which has been obtained by clinical studies including large numbers of patients. They may apply "on average", but they can be sub-optimal for individual patients. To realize more patient-specific treatment decision criteria, more detailed knowledge may be required about the vascular hemodynamics, i.e. the blood flow and pressure in the diseased vessel and the biomechanical reaction of the vessel wall to this flow and pressure. Over the last decade, a substantial number of publications have appeared on hemodynamic modeling. Some studies have provided first evidence that this modeling may indeed be used to support therapeutic decisions. The goal of the research reported in this paper is to go one step further, namely to investigate the feasibility of a patient-specific hemodynamic modeling methodology that is not only effective (improves therapeutic decisions), but that is also efficient (easy to use, fast, as much as possible automatic) and robust (insensitive to variation in the quality of the input data, same outcome for different users). A review is presented of our research performed during the last 5 years and the results that were achieved. This research focused on the risk assessment for one particular disease, namely abdominal aortic aneurysm, a life-threatening dilatation of the abdominal aorta.

Patient-specific initial wall stress in abdominal aortic aneurysms with a backward incremental method

Patient-specific wall stress simulations on abdominal aortic aneurysms may provide a better criterion for surgical intervention than the currently used maximum transverse diameter. In these simulations, it is common practice to compute the peak wall stress by applying the full systolic pressure directly on the aneurysm geometry as it appears in medical images. Since this approach does not account for the fact that the measured geometry is already experiencing a substantial load, it may lead to an incorrect systolic aneurysm shape. We have developed an approach to compute the wall stress on the true diastolic geometry at a given pressure with a backward incremental method. The method has been evaluated with a neo-Hookean material law for several simple test problems. The results show that the method can predict an unloaded configuration if the loaded geometry and the load applied are known. The effect of incorporating the initial diastolic stress has been assessed by using three patient-specific geometries acquired with cardiac triggered MR. The comparison shows that the commonly used approach leads to an unrealistically smooth systolic geometry and therefore provides an underestimation for the peak wall stress. Our backward incremental modelling approach overcomes these issues and provides a more plausible estimate for the systolic aneurysm volume and a significantly different estimate for the peak wall stress. When the approach is applied with a more complex material law which has been proposed specifically for abdominal aortic aneurysm similar effects are observed and the same conclusion can be drawn.