Planning image-guided endovascular interventions: guidewire simulation using shortest path algorithms

Abstract

Endovascular interventional procedures are being used more frequently in cardiovascular surgery. Unfortunately, procedural failure, e.g., vessel dissection, may occur and is often related to improper guidewire and/or device selection. To support the surgeon's decision process and because of the importance of the guidewire in positioning devices, we propose a method to determine the guidewire path prior to insertion using a model of its elastic potential energy coupled with a representative graph construction.The 3D vessel centerline and sizes are determined for a specified vessel. Points in planes perpendicular to the vessel centerline are generated. For each pair of consecutive planes, a vector set is generated which joins all points in these planes. We construct a graph representing these vector sets as nodes. The nodes representing adjacent vector sets are joined by edges with weights calculated as a function of the angle between the corresponding vectors (nodes). The optimal path through this weighted directed graph is then determined using shortest path algorithms, such as topological sort based shortest path algorithm or Dijkstra's algorithm. Volumetric data of an internal carotid artery phantom (Ø 3.5mm) were acquired. Several independent guidewire (Ø 0.4mm) placements were performed, and the 3D paths were determined using rotational angiography.The average RMS distance between the actual and the average simulated guidewire path was 0.7mm; the computation time to determine the path was 3 seconds. The ability to predict the guidewire path inside vessels may facilitate calculation of vessel-branch access and force estimation on devices and the vessel wall.

Real-time endovascular guidewire position simulation using shortest path algorithms

“…Results for α showed the best results for values of 1.6-2.4 for plastic-coated guidewires and for stainless steel guidewires in all the phantoms. These results combined with those in our previous study [15] indicate that the materials stiffness (α) has only a minor influence on the final position. It may be that the spatial constraints imposed by the vessel geometry limit the guidewire position (more or less independent of material stiffness).…”

“…As a result, the path would be forced to go through the non-crossed region of the plane, distorting the result. Techniques for identifying crossing planes have been presented in Schafer et al [15].…”

“…Thus, we present a graph-based modeling of straight tipped guidewires which takes advantage of the analytical modeling ideas while allowing efficient determination of the minimal energy state, i.e., the relaxed state in a given 3D vessel topology. This work is an extension of initial results presented [15] thoroughly analyzing the proposed algorithm parameters, as well as investigating its capabilities in different vessel geometries and for different guidewire materials. "Materials and methods" will detail the construction of the acyclic, directed graph and the acquisition of experimental data.…”

Evaluation of the effect of catheter on the guidewire motion in a blood vessel model by physical and numerical simulations

“…Moreover, the length and flexibility of catheters and guidewires, as well as their limited number of degrees of freedom, may severely reduce the surgeon's visual and tactile perception when manipulating these tools during the treatment. Therefore, various catheter simulators using a computer have been developed to improve safety in endovascular treatments (Otani et al, 2015;Chiang et al, 2013;Irie et al, 2012;Hirayama et al, 2011;Schafer et al, 2007;Cai et al, 2006;Lenoir et al, 2006;Bhat et al, 2005;Konings et al, 2003;Yamamura et al, 2003;Dawson et al, 2000;Lawton et al, 2000;Wang et al, 1998;Barnes et al, 1997;Martin and Johnson, 1989). Many of them are physically-based numerical simulators, using multibody dynamics or finite element method (FEM).…”

Clinical evaluation of angiographic multiple-view 3D reconstruction

“…Moreover, with quantitative 3D data available, quantitative and visualization techniques can be employed for treatment planning prior to and during the procedure. Guidewire reconstructions and path estimation [26] can be facilitated. The tortuosity and curvature of the vessel can be calculated [27][28][29] facilitating the determination of whether various interventional devices, such as stents, will be able to access the interventional site.…”