CT-Enabled Patient-Specific Simulation and Contact-Aware Robotic Planning for Cochlear Implantation

TL;DR

This paper introduces a CT-based simulation and planning pipeline for robotic cochlear implant insertion, improving safety and precision by modeling contact forces and anatomy-specific constraints.

Contribution

It presents a novel CT-to-simulation pipeline with a differentiable electrode model and contact-aware planning for safer, patient-specific cochlear implant procedures.

Findings

Reduced locking and buckling risk during insertion

Enhanced insertion depth accuracy

Validated with simulations and benchtop experiments

Abstract

Robotic cochlear-implant (CI) insertion requires precise prediction and regulation of contact forces to minimize intracochlear trauma and prevent failure modes such as locking and buckling. Aligned with the integration of advanced medical imaging and robotics for autonomous, precision interventions, this paper presents a unified CT-to-simulation pipeline for contact-aware insertion planning and validation. We develop a low-dimensional, differentiable Cosserat-rod model of the electrode array coupled with frictional contact and pseudo-dynamics regularization to ensure continuous stick-slip transitions. Patient-specific cochlear anatomy is reconstructed from CT imaging and encoded via an analytic parametrization of the scala-tympani lumen, enabling efficient and differentiable contact queries through closest-point projection. Based on a differentiated equilibrium-constraint formulation, we derive an online direction-update law under an RCM-like constraint that suppresses lateral insertion forces while maintaining axial advancement. Simulations and benchtop experiments validate deformation and force trends, demonstrating reduced locking/buckling risk and improved insertion depth. The study highlights how CT-based imaging enhances modeling, planning, and safety capabilities in robot-assisted inner-ear procedures.