Image-Guided Optimization of Robotic Catheters for Patient-Specific Endovascular Intervention

Abstract

Endovascular intervention for ischemic stroke requires dexterous manipulation of catheters and guidewires. Robot-assisted steerable microcatheters can facilitate navigation along tortuous vasculature and bifurcation selection, thereby reducing the surgical skill demands. To achieve effective catheter deployment, the kinematic parameters of the catheter should ideally be selected to minimize the passive deflection of a given catheter. This paper presents a first-step towards automated selection of catheter parameters for traversal of a target anatomical vessel. The image-segmentation and vessel skeletonisation are presented along with a kinematic model of an antagonistic pair two-segment continuum robot. The nonlinear kinematic model is captured using a sparse representation achieved via a Krönecker product solution to a least-squares formulation of a matrix equation. The path planning is cast as a nonlinear parameter optimization that includes the lengths of the segments and their relative angles. The initial results suggest the possible utility of this approach for the development of a library of catheters that may be designed a-priori for anatomical regions while taking into account across-patient anatomical variabilities. For clinical-deployment, the same methods can be used to select the best catheter candidate from a library of catheters.