A MagsL-HUD Endoscopic System for Magnetic Compression Anastomosis Surgery in Unstructured Endoluminal Environment
Yichong SUN, Yitian Xian, Ruoyu Xu, Wai Shing Chan, Hon Chi Yip, Philip, Wai-yan Chiu, Zheng Li
AI summary
Problem
Current magnetic compression anastomosis lacks safe, real-time, radiation-free localization and intuitive guidance for dual magnets in complex endoluminal tracts, forcing reliance on surgeon estimation and resulting in low procedural efficiency.
Approach
The authors developed the MagsL-HUD system, which uses a novel Endo-MagCap device with orthogonal magnets and a magnetic sensor array to calculate real-time six-DoF poses, then overlays this spatial data directly onto the endoscopic video feed for intuitive surgeon guidance.
Key results
- Six-DoF tracking accuracy with ~0.007 m positional and ~0.14–0.17 rad angular errors for dual magnets
- Successful ex vivo stomach-colon anastomosis in porcine tissue with ~0.0025 m compression gap
- 71.4% compression success rate with HUD guidance versus 42.9% without HUD
- Novel Endo-MagCap device with hold/fire mechanism and optimization-based multimagnetic localization algorithm
Why it matters
Provides a radiation-free, minimally invasive navigation framework that enhances surgical precision and could accelerate the clinical adoption of magnetic-assisted endoscopic anastomosis.
Abstract
Magnetic compression anastomosis (MCA) offers a promising solution for minimally invasive anastomosis surgery. However, current MCA schemes lack safe, real-time localization, and guidance for compression magnets, hindering surgeons’ ability to control the compression magnets effectively in complex, unstruc- tured endoluminal environments. To address these limitations, this article introduces the MagsL-HUD endoscopic system, a novel so- lution that enables multimagnetic six-degree-of-freedom (six-DoF) localization and head-up display (HUD) guidance within the en- doscopic view (EV). Specifically, the system integrates a developed Endo-MagCap device with an orthogonal magnet configuration, along with a magnetic sensor array, to achieve real-time full-pose localization. An endoscopic camera model is incorporated for HUD visualization, enhancing intuitive interaction for surgeons’ better- informed decisions. Eventually, the effectiveness of the MagsL- HUD endoscopic system is validated through laboratory experi- ments and ex vivo animal trials. The system demonstrates six-DoF tracking accuracy with average errors of 0.0070 m and 0.1437 rad, and 0.0071 m and 0.1721 rad in the designed trajectory cases for two compression magnets, respectively. Additionally, ex vivo porcine tests confirm the system’s feasibility and applicability, successfully performing a stomach-colon MCA surgery with a final compression gap of approximately 0.00247 m. Further com- parative studies demonstrate that the MagsL-HUD method has a compression success rate of 71.4% versus 42.9% of the non-HUD approaches in the designed tests. This work represents a significant step toward the clinical adoption of magnetic-assisted endoscopy for minimally invasive anastomosis surgeries, holding substantial practical significance for improving the safety and efficacy of MCA procedures in complex, unstructured endoluminal environments. Received 3 March 2025; revised 31 July 2025; accepted 19 September 2025. Date of publication 12 November 2025; date of current version 8 January 2026. This work was supported in part by the Hong Kong Research Grant Council under Project C4042-23GF, Project 14214322, Project 14200623, and Project 14206325. This article was recommended for publication by Associate Editor P. Renaud and Editor A. Menciassi upon evaluation of the reviewers’ comments. (Corresponding author: Zheng Li.) Yichong Sun, Yitian Xian, Ruoyu Xu, Wai Shing Chan, and Hon Chi Yip are with the Department of Surgery, The Chinese University of Hong Kong, Hong Kong, China (e-mail: yichongsun@link.cuhk.edu.hk; yitianxian@ link.cuhk.edu.hk; ruoyuxu@cuhk.edu.hk; waishingchan@link.cuhk.edu.hk; hcyip@cuhk.edu.hk). Philip Wai Yan Chiu and Zheng Li are with the Department of Surgery, Chow Yuk Ho Technology Centre for Innovative Medicine, Li Ka Shing Institute of Health Science and Multi-Scale Medical Robotics Center, The Chinese University of Hong Kong, Hong Kong, China (e-mail: philipchiu@ surgery.cuhk.edu.hk; lizheng@cuhk.edu.hk). This article has supplementary downloadable material available at https://doi.org/10.1109/TRO.2025.3631817, provided by the authors. Digital Object Identifier 10.1109/TRO.2025.3631817