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Abstract: 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. [Copyright &y& Elsevier]

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 185 ms, 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 0.4 mm in the x direction and 0.7 mm in the z direction. With the rotation time used in this study, motions up to 2.7 Hz 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. [ABSTRACT FROM AUTHOR]