Almar Klein

Detectability of motions in AAA with ECG-gated CTA : A quantitative study

PURPOSE ECG-gated CT enables the visualization of motions caused by the beating of the heart. Although ECG gating is frequently used in cardiac CT imaging, this technique is also very promising for evaluating vessel wall motion of the aortic artery and the motions of (stent grafts inside) abdominal aortic aneurysms (AAA). Late stent graft failure is a serious complication in endovascular repair of aortic aneurysms. Better understanding of the motion characteristics of stent grafts will be beneficial for designing future devices. In addition, these data can be valuable in predicting stent graft failure in patients. To be able to reliably quantify the motion, however, it is of importance to know the performance and limitations of ECG gating, especially when the motions are small, as is the case in AAA. Since the details of the reconstruction algorithms are proprietary information on the CT manufacturers and not in the public domain, empirical experiments are required. The goal of this study is to investigate as to what extent the motions in AAA can be measured using ECG-gated CT. The authors quantitatively investigate four aspects of motion in ECG-gated CT: The detectability of the motion of objects at different amplitudes and different periodic motions, the temporal resolution, and the volume gaps that occur as a function of heart rate. METHODS They designed an experiment on a standard static phantom to empirically determine temporal resolution. To investigate motion amplitude and frequency, as well as patient heart rate, they designed dynamic experiments in which a home-made phantom driven by a motion unit moves in a predetermined pattern. RESULTS The duration of each ECG-gated phase was found to be 185ms, which corresponds to half of the rotation time and is thus in accordance with half scan reconstruction applied by the scanner. By using subpixel localization, motions become detectable from amplitudes of as small as 0.4mm in the x direction and 0.7mm in the z direction. With the rotation time used in this study, motions up to 2.7Hz can be reliably detected. The reconstruction algorithm fills volume gaps with noisy data using interpolation, but objects within these gaps remain hidden. CONCLUSIONS This study gives insight into the possibilities and limitations for measuring small motions using ECG-gated CT. Application of the experimental method is not restricted to the CT scanner of a single manufacturer. From the results, they conclude that ECG-gated CTA is a suitable technique for studying the expected motions of the stent graft and vessel wall in AAA.

Automatic segmentation of the wire frame of stent grafts from CT data

Endovascular aortic replacement (EVAR) is an established technique, which uses stent grafts to treat aortic aneurysms in patients at risk of aneurysm rupture. Late stent graft failure is a serious complication in endovascular repair of aortic aneurysms. Better understanding of the motion characteristics of stent grafts will be beneficial for designing future devices. In addition, analysis of stent graft movement in individual patients in vivo can be valuable for predicting stent graft failure in these patients. To be able to gather information on stent graft motion in a quick and robust fashion, we propose an automatic method to segment stent grafts from CT data, consisting of three steps: the detection of seed points, finding the connections between these points to produce a graph, and graph processing to obtain the final geometric model in the form of an undirected graph. Using annotated reference data, the method was optimized and its accuracy was evaluated. The experiments were performed using data containing the AneuRx and Zenith stent grafts. The algorithm is robust for noise and small variations in the used parameter values, does not require much memory according to modern standards, and is fast enough to be used in a clinical setting (65 and 30s for the two stent types, respectively). Further, it is shown that the resulting graphs have a 95% (AneuRx) and 92% (Zenith) correspondence with the annotated data. The geometric model produced by the algorithm allows incorporation of high level information and material properties. This enables us to study the in vivo motions and forces that act on the frame of the stent. We believe that such studies will provide new insights into the behavior of the stent graft in vivo, enables the detection and prediction of stent failure in individual patients, and can help in designing better stent grafts in the future.

Evolution of the Proximal Sealing Rings of the Anaconda Stent-Graft After Endovascular Aneurysm Repair

Purpose: To provide insight into the evolution of the saddle-shaped proximal sealing rings of the Anaconda stent-graft after endovascular aneurysm repair (EVAR). Methods: Eighteen abdominal aortic aneurysm patients were consecutively enrolled in a single-center, prospective, observational cohort study (LSPEAS; Trialregister.nl identifier NTR4276). The patients were treated electively using an Anaconda stent-graft with a mean 31% oversizing (range 17–47). According to protocol, participants were to be followed for 2 years, during which 5 noncontrast electrocardiogram-gated computed tomography scans would be conducted. Three patients were eliminated within 30 days (1 withdrew, 1 died, and a third was converted before stent-graft deployment), leaving 15 patients (mean age 72.8±3.7 years; 14 men) for this analysis. Evolution in size and shape (symmetry) of both proximal infrarenal sealing rings were assessed from discharge to 24 months using dedicated postprocessing algorithms. Results: At 24 months, the mean diameters of the first and second ring stents had increased significantly (first ring: 2.2±1.0 mm, p<0.001; second ring: 2.7±1.1 mm, p<0.001). At 6 months, the first and second rings had expanded to a mean 96.6%±2.1% and 94.8%±2.7%, respectively, of their nominal diameter, after which the rings expanded slowly; ring diameters stabilized to near nominal size (first ring, 98.3%±1.1%; second ring, 97.2%±1.4%) at 24 months irrespective of initial oversizing. No type I or III endoleaks or aneurysm-, device-, or procedure-related adverse events were noted in follow-up. The difference in the diametric distances between the peaks and valleys of the saddle-shaped rings was marked at discharge but became smaller after 24 months for both rings (first ring: median 2.0 vs 1.2 mm, p=0.191; second ring: median 2.8 vs 0.8 mm; p=0.013). Conclusion: Irrespective of initial oversizing, the Anaconda proximal sealing rings radially expanded to near nominal size within 6 months after EVAR. Initial oval-shaped rings conformed symmetrically and became nearly circular through 24 months. These findings should be taken into account in planning and follow-up.

A comparison of two methods to segment stent grafts in CT data

Late stent graft failure is a serious complication in endovascular repair of aortic aneurysms. Better understanding of the motion characteristics of stent grafts will be beneficial for designing future devices. In addition, analysis of stent graft movement in individual patients in vivo can be valuable for predicting stent graft failure in these patients. To be able to gather information on stent graft motion in a quick and robust fashion, an automatic segmentation method is required. In this work we compare two segmentation methods that produce a geometric model in the form of an undirected graph. The first method tracks along the centerline of the stent and segments the stent in 2D slices sampled orthogonal to it. The second method used a modified version of the minimum cost path (MCP) method to segment the stent directly in 3D. Using annotated reference data both methods were evaluated in an experiment. The results show that the centerline-based method and the MCP-based method have an accuracy of approximately 65% and 92%, respectively. The difference in accuracy can be explained by the fact that the centerline method makes assumptions about the topology of the stent which do not always hold in practice. This causes difficulties that are hard and sometimes impossible to overcome. In contrast, the MCP-based method works directly in 3D and is capable of segmenting a large variety of stent shapes and stent types.

Segmentation and motion estimation of stent grafts in abdominal aortic aneurysms

Patients with an Abdominal Aortic Aneurysm have a high risk of dying due to the rupture of a dilated aorta. Endovascular aneurysm repair is a technique to threat AAA, by which a stent graft prosthesis is implanted in the aorta of the patient. Due to its minimal invasive character, this intervention has smaller risks for the patient compared to the conventional approach. Unfortunately, due to effects such as metal fatigue, leakage and stent migration, this technique is less successful on the long term. These problems are caused by the forces applied by the pressure waves of the blood flow. It is therefore important to understand the motion behavior of the stent graft inside the human body. The technique of ECG-gated CT can be used to obtain multiple 3D images of the patient. Each of these images corresponds to a different phase of the heart cycle. Given these images, the goal is to measure the motions of the stent graft. This is done in two steps. The first is segmentation: detecting where the stent is located and subsequently creating a geometric model of the stent. This geometric model is represented as a graph consisting of nodes that are connected by edges. The nodes represent the corners and crossings in the stent’s frame, and the edges represent the wires in between. The second step is registration, by which the deformation between the different images is calculated. The motion of the stent is determined from the deformation fields and incorporated in the geometric stent model. The obtained dynamic model can be used for visualization of the motion of the stent, as well as for performing further calculations such as estimating the forces in the stent.

Motion Calculations on Stent Grafts in AAA

Endovascular aortic repair (EVAR) is a technique which uses stent grafts to treat aortic aneurysms in patients at risk of aneurysm rupture. Although this technique has been shown to be very successful on the short term, the long term results are less optimistic due to failure of the stent graft. The pulsating blood flow applies stresses and forces to the stent graft, which can cause problems such as breakage, leakage, and migration. Therefore it is of importance to gain more insight into the in vivo motion behavior of these devices. If we know more about the motion patterns in well-behaved stent graft as well as ill-behaving devices, we shall be better able to distinguish between these type of behaviors These insights will enable us to detect stent-related problems and might even be used to predict problems beforehand. Further, these insights will help in designing the next generation stent grafts. Firstly, this work discusses the applicability of ECG-gated CT for measuring the motions of stent grafts in AAA. Secondly, multiple methods to segment the stent graft from these data are discussed. Thirdly, this work proposes a method that uses image registration to apply motion to the segmented stent model