Quantitative Stent Graft Motion in ECG Gated CT by Image Registration and Segmentation: In Vitro Validation and Preliminary Clinical Results

Abstract

WHAT THIS PAPER ADDS The present article establishes a novel method to quantify and visualise stent graft motion in multiphasic ECG gated computed tomography using image registration techniques. In vitro validation demonstrated adequate accuracy for quantifying abdominal aortic stent graft displacement. The methodology was successfully applied to clinical data of patients treated by endovascular aneurysm repair (EVAR) with different stent graft designs. This novel methodology enables provision of accurate data characterising the in situ motions of stent grafts in the endovascular environment. This may have a major impact on stent graft design and early prediction of failure in post-market evaluations of new or modified devices.Objectives: The dynamic endovascular environment of stent grafts may influence long term outcome after endovascular aneurysm repair (EVAR). The sealing and fixation of a stent graft to the aortic wall is challenged at every heartbeat, yet knowledge of the cardiac induced dynamics of stent grafts is sparse. Understanding the stenteartery interaction is crucial for device development and may aid the prediction of failure in the individual patient. The aim of this work was to establish quantitative stent graft motion in multiphasic electrocardiogram (ECG) gated computed tomography (CT) by image registration and segmentation techniques. Methods: Experimental validation was performed by evaluating a series of ECG gated CT scans of a stent graft moving at different amplitudes of displacement at different virtual heart rates using a motion generating device with synchronised ECG triggering. The methodology was further tested on clinical data of patients treated with EVAR devices with different stent graft designs. Displacement during the cardiac cycle was analysed for points on the fixating stent rings, the branches or fenestrations, and the spine. Results: Errors for the amplitude of displacement measured in vitro at individual points on the wire frame were at most 0.3 mm. In situ cardiac induced displacement of the devices was found to differ per location and also depended on the type of stent graft. Displacement during the cardiac cycle was greatest in a fenestrated device and smallest in a chimney graft sac anchoring endosystem, with maximum displacement varying from 0.0 to 1.4 mm. There was no substantial displacement measurable in the spine. Conclusions: A novel methodology to quantify and visualise stent graft motion in multiphasic ECG gated CT has been validated in vitro and tested in vivo. This methodology enables further exploration of in situ motion of different stent grafts and branch stents and their interaction with native vessels.

In Vivo Quantification of Cardiac-Pulsatility-Induced Motion Before and After Double-Branched Endovascular Aortic Arch Repair

“…Quantification of the cardiac-pulsatility-induced motion of the native vessel and RelayBranch was done by manual selection of points in the phase-averaged CT volume: the ventral and dorsal ascending aorta (1&2), the top of the aortic arch (3), the ventral and dorsal descending aorta (4&5), the end of the BCT (6&7), the BCT bifurcation (8), the LCCA (9&10), and the LCCA bifurcation (11) (Figure 2). The motion amplitudes, that is, pulsatility, of selected points in x —(lateral), y —(ventral-dorsal), and z —(caudal-cranial) directions were calculated by adding the deformation fields to the point coordinates as described and validated by Koenrades et al 5 with an error of ≤0.3 mm. The pathlength of each selected point was calculated as the sum of the distances between the point locations in subsequent phases.…”

Electrocardiography-gated computed tomography angiography analysis of cardiac pulsatility-induced motion and deformation after endovascular aneurysm sealing with chimney grafts

“…Image analysis was performed using a previously established combination of an image registration and a segmentation algorithm 11 that was validated for motion estimation of endografts in ECG-gated CTA data. 9 The algorithm was customized to quantify motion and deformation of the Nellix stents, the chimney grafts and the stented branch vessels during the cardiac cycle. An overview of the applied methodology is shown in Fig 1 . First, the ECG-gated datasets with a slice thickness of 2.5 mm were interpolated in z-direction by spline interpolation to acquire submillimeter isotropic voxels.…”

“…8 The long-term stability of the endograft depends on its ability to withstand the repetitive stresses posed by the blood flow. Previous research has demonstrated that the degree of endograft motion may differ per fixation site and between devices, 9 which underlines the importance to understand the individual device dynamics to allow for adequate durability tests. To achieve long-term stability, it seems mandatory that the individual stents and chimney grafts move as a single unit.…”

Evaluation and Verification of Fast Computational Simulations of Stent-Graft Deployment in Endovascular Aneurysmal Repair

“…Validation on clinical data is widely used in the field of cardiovascular devices, especially in FEVAR, for example to predict fenestration rotation ( 47 ), iliac complications ( 49 ), or to validate numerical simulation of stent deployment ( 7 , 8 , 18 , 21 , 22 , 25 , 50 ). Other numerical methods have been validated by combining phantom and clinical data ( 11 , 12 , 29 , 51 ).…”