Shape Tracking and Feedback Control of Cardiac Catheter Using MRI-Guided Robotic Platform - Validation with Pulmonary Vein Isolation Simulator in MRI

Cardiacelectrophysiologyisaneffectivetreatmentfor atrial fibrillation, in which a long, steerable catheter is inserted into the heart chamber to conduct radio frequency ablation. Magnetic resonance imaging (MRI) can provide enhanced intraoperative monitoring of the ablation progress as well as the localization of catheter position. However, accurate and real-time tracking of the catheter shape and its efficient manipulation under MRI remains challenging. In this article, we designed a shape tracking system that integrates a multicore fiber Bragg grating (FBG) fiber and tracking coils with a standard cardiac catheter. Both the shape and positional tracking of the bendable section could be achieved. A learning-basedmodelingmethodisdevelopedforcardiaccatheters, which uses FBG-reconstructed three-dimensional curvatures for model initialization. The proposed modeling method was imple- mented on an MRI-guided robotic platform to achieve feedback control of a cardiac catheter. The shape tracking performance was experimentallyverified,demonstrating2.33°averageerrorforeach sensing segment and 1.53 mm positional accuracy at the catheter Manuscript received October 24, 2021; accepted January 6, 2022. This work was supported in part by the Research Grants Council of Hong Kong under Grant 17206818, Grant 17205919, and Grant 17207020; in part by the Innovation and Technology Commission, Hong Kong under Grant MRP/029/20X; and in part by the Multi-Scale Medical Robotics Center Ltd. funded by ITC. This paper was recommended for publication by Associate Editor A. Krupa and Editor A. Menciassi upon evaluation of the reviewers’ comments. (Corresponding author: Ka-Wai Kwok.) Ziyang Dong, Ge Fang, Zhuoliang He, Justin Di-Lang Ho, Chim-Lee Cheung, Wai Lun Tang, Xiaochen Xie, and Ka-Wai Kwok are with the Department of Mechanical Engineering, The University of Hong Kong, Hong Kong (e-mail: ziyang.dong.matthew@gmail.com; fangge@hku.hk; hezl@connect.hku.hk; jdlho@connect.hku.hk; zardchim@hku.hk; at361836@hku.hk; xcxie@ connect.hku.hk; kwokkw@hku.hk). Xiaomei Wang is with the Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, and also with the Multi-Scale Medical Robotics Center Ltd., Hong Kong (e-mail: wangxmei@connect.hku.hk). Liyuan Liang is with the Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong (e-mail: lyliang@connect.hku.hk). Hing-Chiu Chang is with the Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, and also with the Department of Biomed- ical Engineering, The Chinese University of Hong Kong, Hong Kong (e-mail: hcchang@hku.hk). Chi Keong Ching is with the Department of Cardiology, National Heart Centre, Singapore 169609 (e-mail: ching.chi.keong@singhealth.com.sg). This article has supplementary material provided by the au- thors and color versions of one or more figures available at https://doi.org/10.1109/TRO.2022.3154691. Digital Object Identifier 10.1109/TRO.2022.3154691 tip. The feedback control performance was tested by autonomous targeting and path following (average deviation of 0.62 mm) tasks. The overall performance of the integrated robotic system was val- idated by a pulmonary vein isolation simulator with ex-vivo tissue ablation, which employed a left atrial phantom with pulsatile liquid flow. Catheter tracking and feedback control tests were conducted in an MRI scanner, demonstrating the capability of the proposed system under MRI.