  Embolization, stroke, ischaemic lesion, and perforation remain significant
concerns in endovascular interventions. Intravascular sensing of tool
interaction with the arteries is advantageous to minimize such complications
and enhance navigation safety. Intraluminal information is currently limited
due to the lack of intravascular contact sensing technologies. We present
monitoring of the intraluminal tool interaction with the arterial wall using an
image-based estimation approach within vascular robotic navigation. The
proposed image-based method employs continuous finite element simulation of the
tool using imaging data to estimate multi-point forces along tool-vessel wall
interaction. We implemented imaging algorithms to detect and track contacts,
and compute pose measurements. The model is constructed based on the nonlinear
beam element and flexural rigidity profile over the tool length. During remote
cannulation of aortic arteries, intraluminal monitoring achieved tracking local
contact forces, building a contour map of force on the arterial wall and
estimating tool structural stress. Results suggest that high risk intraluminal
forces may happen even with low insertion force. The presented online
monitoring system delivers insight into the intraluminal behavior of
endovascular tools and is well suited for intraoperative visual guidance for
the clinician, robotic control of vascular procedures and research on
interventional device design.
