Project Summary/Abstract:
The objective of this proposal is to create a multi-modal feedback-based navigation system and MR-
compatible robotic platform that enables precise, continuous, and permanent lesion creation during MR-guided
radiofrequency ablation (RFA) for atrial fibrillation (AF) treatment. This research is motivated by the high
incidence of AF in US (1 in 100 people), and the suboptimal treatment outcome of traditional approaches (~30-
50% recurrence rate). Recurrence of AF occurs when there are gaps between ablation lesions, which can be
caused by multiple reasons, including 1) limited ability to manipulate the catheter in a manner that reaches all
desired ablation targets while also 2) maintaining proper catheter-tissue contact force (CTCF) for effective
ablation energy delivery. In addition, there is 3) lack of effective navigation methods that accurately identify sites
of incomplete ablation and guide the catheter to complete ablation. We recently developed MR-tracked
catheterization toolset to perform RFA inside MRI scanner and the MR-based imaging method to assess the
lesion outcome intraoperatively. However, manipulating the catheter towards the desired location and
maintaining proper contact remains a challenging task. To address these problems, we propose to develop an
MR-enabled intraoperative navigation feedback framework and robotic hardware system. From technical
perspective, the proposed platform is innovative since current systems do not integrate accurate catheter
manipulation and CTCF feedback with MRI-based monitoring and lesion assessment to provide a unified system
for AF ablation planning, treatment, and assessment. From the clinical perspective, the proposed platform
enables accurate catheter position and contact force control, which supports the creation of continuous and
chronic ablation lesions for reducing arrhythmia recurrence. The proposed work will be achieved via three Aims.
Aim 1: Navigation feedback. We will further develop navigation software that combines multi-modal sensory
feedback (i.e., MR imaging, MR-catheter tracking, CTCF estimation), and visualizes them in an integrated
software environment to provide feedback to the physician. Aim 2: MRI robot hardware and control. We will
advance our current catheter robot hardware to create a complete system for simultaneous catheter and guiding
sheath manipulation. We will develop hybrid position and CTCF control algorithm that enables accurate and
stable catheter placement for effective ablation energy delivery. Specific Aim 3: Experimental validations. We
will integrate the robot hardware and navigation feedback system, and validate the integrated system first in a
beating heart emulating phantom in a 1.5 MRI scanner, and then in 16 MR-guided LA ablation studies on swine.
