Title: Design, Modeling, and Image-based Control of Robotically Steerable Systems for Endovascular Interventions

Date: Friday, April 25th, 2025

Time: 02:30 PM - 04:00 PM EST

Location: McIntire Conference Room Whitaker 3115

Zoom Meeting

https://gatech.zoom.us/j/96996827295?pwd=7Zfll2ftnGIk0z4rOwybl5BJvol3ag.1

Meeting ID: 969 9682 7295
Passcode: 419455

Sharan Rajesh Ravigopal

Robotics Ph.D. Student

Georgia Institute of Technology

Dissertation Committee:

Dr. Jaydev P. Desai, PhD (Advisor) - Department of Biomedical Engineering, Georgia Institute of Technology

Dr. Jun Ueda, PhD  - Department of Mechanical Engineering, Georgia Institute of Technology

Dr. Brooks Lindsey, PhD - Department of Biomedical Engineering, Georgia Institute of Technology

Dr. Yue Chen, PhD - Department of Biomedical Engineering, Georgia Institute of Technology

Dr. Omer Inan, PhD - Department of Electrical and Computer Engineering, Georgia Institute of Technology

Abstract:

Endovascular diseases, including chronic total occlusions (CTO) and peripheral arterial disease (PAD), severely impact blood flow in major arteries, leading to complications such as tissue damage, limb loss, and heightened cardiovascular risks. These conditions necessitate precise interventions by skilled clinicians using guidewires, typically navigated through tortuous vasculature under fluoroscopic imaging. However, challenges such as limited steerability and complex anatomy demand innovative solutions. This research presents the design, modeling, and control of robotically steerable guidewire and transcatheter systems aimed at enhancing dexterity, autonomy, and precision in minimally invasive endovascular procedures. First, the fluoroscopic image-based tracking techniques for pose estimation are presented for guidewires and transcatheters. A path-planning algorithm tailored to the motion constraints of steerable guidewires is developed to leverage inverse kinematics models for traversal, and image-based closed-loop feedback is conducted to further enhance navigation accuracy. Additionally, this work explores concentric tube mechanisms combined with tendon-driven designs to improve guidewire dexterity and stability. Experimental validation includes the integration of a forward-viewing ultrasound transducer into a tendon-driven guidewire for real-time imaging in in vivo scenarios. Finally, a novel, dexterous guidewire robot is developed and navigated through neurovascular anatomies via radial access in phantom vasculature. Results demonstrate advancements in guidewire precision, dexterity, and clinical viability across endovascular applications. The proposed robotic systems hold promise for improving patient outcomes by enabling safer and more effective navigation through tortuous anatomy while reducing procedural complexity for clinicians.