Ultrasound-Assisted Guidance With Force Cues for Intravascular Interventions

Abstract

Image guidance during minimally invasive intravascular interventions is primarily achieved based on X-ray fluoroscopy, which has several limitations including limited 3-D imaging capability, significant doses of radiation to operators, and lack of contact force measurement between the cardiovascular tissue and interventional tools. Ultrasound imaging can be adopted to complement or possibly replace 2-D fluoroscopy for intravascular interventions due to its portability, safety to use, and the ability of providing depth information. However, it is challenging to precisely visualize catheters and guidewires in the ultrasound images. In this paper, we propose a novel method to figure out both the position and orientation of the catheter tip in 2-D ultrasound images in real time by detecting and tracking a passive marker attached to the catheter tip. Moreover, the contact force can be estimated simultaneously as well via measuring the length variation of the marker. A geometrical model-based method is introduced to detect the initial position of the marker, and a Kanade–Lucas–Tomasi-based algorithm is developed to track the position, orientation, and length of the marker. The ex vivo experiment results validate the effectiveness of the proposed approach in automatically locating the catheter tip in ultrasound images and its capability of sensing the contact force. Therefore, it can be concluded that the presented method can be utilized to better facilitate operators during intravascular interventions. Note to Practitioners—This paper is motivated by the vision-based force sensing mechanism. A coil spring marker is used to visualize and locate the catheter tip in ultrasound images. The metallic helical structure of the marker can result in remarkable features in 2-D in-plane ultrasound images. A geometrical model-based detection algorithm is proposed to detect the passive marker in initial frame regardless of its length and orientation variation. A prediction–detection-combined tracking algorithm is developed to automatically track the catheter tip for the subsequent frames in real time. Most importantly, the distal force can be simultaneously estimated due to the length variation of the passive marker. The sensed force can be fed back to a robotic catheterization system during intravascular interventions.