Eversion-based robots can enable safe access,steering and endoscopic imaging within the spinal subarachnoid space
Authors: Zicong Wu, Panagiotis Kalozoumis, S. M. Hadi Sadati, Aminul I. Ahmed, Jonathan Shapey, Christian Baker, Thomas Booth, Wenfeng Xia, +3 more
Organizations: Department of Surgical & Interventional Engineering, School of Biomedical Engineering & Imaging Sciences, Faculty of Life Sciences & Medicine, King’s College London, London WC2R 2LS, United Kingdom · Department of Computer Science & Biomedical Informatics, University of Thessaly, Lamia 35131, Greece · School of Engineering and Materials Science, Queen Mary University London, London E1 4NS, United Kingdom · Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London WC2R 2LS, United Kingdom · School of Electrical and Computer Engineering, National Technical University of Athens, Zografou 15773, Greece
Abstract
Safe navigation within the spinal subarachnoid space is constrained by its narrow, compliant, and delicate anatomy. Conventional catheters and continuum robots rely on proximal pushing, generating friction and shear along the tissue device interface that limit distal controllability and increase the risk of neural injury. Here, we present a 2 mm diameter eversion-growing robotic platform that enables friction minimised extension and steering within the human spinal subarachnoid space, validated through computational modelling, phantom experiments, and intact human cadaver studies. The robot integrates a miniature endoscope for real time intrathecal visualisation and advances by pressure driven tip eversion, localising motion to the distal tip while minimising translational sliding of the deployed body. Phantom experiments demonstrated reductions of 65.2% in mean interaction force and 48.0% in peak interaction force compared with matched push-based insertion. Physics based modelling showed that eversion based growth redistributed tissue loading, reducing local stress concentrations and interfacial shear relative to conventional insertion. In an intact human cadaver, the system achieved 150 mm of controlled intrathecal extension with concurrent fluoroscopic and endoscopic visualisation, providing access across multiple vertebral levels from a standard lumbar entry point. Postprocedural laminectomy and durotomy revealed no observable macroscopic disruption of the dura mater or surrounding neural structures. These results provide the first mechanically characterised and multimodally validated demonstration of eversion-based robotic navigation in intact human spinal anatomy, establishing a quantitative and procedural foundation for future intrathecal interventions. Further validation in larger anatomical cohorts and under physiological conditions will be required before clinical translation.
Conventional colonoscopy remains limited by patient discomfort and procedural risks, motivating research into compliant robotic alternatives. Eversion robots, which advance via pressure-driven tip growth, eliminate sliding friction against the colon wall and offer a less intrusive approach to traversal. However, no existing design simultaneously satisfies all clinical requirements. This paper benchmarks four recent eversion robot architectures against the key anatomical and clinical constraints of colonoscopy, including colon length, minimum luminal diameter, bending angle, and working-channel needs. We identify the central trade-offs each design reveals, particularly the difficulty of integrating steering and payload delivery without sacrificing the soft, low-friction behaviour that makes eversion robots attractive. We then provide design guidance across material selection, steering strategy, and payload delivery, and highlight open problems for clinical translation.
Soft eversion robots, also known as vine robots, have attracted growing interest for navigation and inspection tasks, including minimally invasive medical applications [1]. A vine robot consists of a thin, flexible, inextensible tube folded inward that everts and grows forward when pressurized. This tip-growth enables navigation with minimal friction, making vine robots well suited for complex environments such as the human colon [2]. While their inherent softness allows passive conforma- tion to curved pathways in confined spaces, navigation performance strongly depends on environmental inter- actions, including contact angle and the length of un- constrained deployed material [3], [4]. Sharp directional changes, such as those in the sigmoid colon, often limit passive growth and necessitate active steering. Existing solutions include distributed artificial muscles [5] or dedicated tip-based steering mechanisms [6]. In addition, many applications require payload delivery, such as sensors and tools [7], [8]. Within the ERC Synergy project EndoTheranostics, this motivates the development of vine robots capable of delivering micro- surgical tools during growth. Prior work has integrated working channels within the vine body [8], [9], but these approaches constrain tool size, introduce friction, and limit access to the environment to the robot tip. In this work, we propose a multi-vine architecture in which two vine robots are coupled to an externally integrated working channel via soft mounting tips [10]. Independent vine actuation enables active tip steering while advancing the working channel without embed- ding it within the vine bodies Figure 1. Experiments demonstrate sharp steering of nearly 90 degrees during growth, highlighting the potential of this architecture for versatile medical and non-medical applications.
Reza Kashef, Cem Suulker, Mohammad Sheikh Sofla +1
Objective: To evaluate robotic controller interfaces for interventional neuroradiology procedures in-vitro incorporating a force-sensing platform to assess safety. Methods: A custom endovascular robot, device-mimicking controller, and sensorized neurovascular phantom were developed. Ten interventional neuroradiologists (4 novices, 6 experts) performed simulated navigations using four control modalities: device-mimicking controllers with and without haptic feedback, joystick-based input, and manual navigation. Navigation time, peak vessel-wall forces, incorrect catheterisations, and prolapse events were assessed, alongside user analyses. Results: Manual navigation was fastest (mean 47.7 s) compared to haptic-on (248.7 s), haptic-off (314.7 s), and joystick (392.6 s) modalities (p<0.001). Regardless of controller type, vessel-wall forces were below the 0.70 N puncture threshold; therefore all modalities were considered safe. Joystick produced significantly more prolapse events than manual control (1.56 vs 0.13; p=0.018). Operator experience was relevant to performance: experts made fewer incorrect catheterisations than novices (0.25 vs 0.62; p=0.035) and applied less vessel-wall force (p<0.0005); these effects were sustained across controllers but accentuated when haptics were on. Users perceived haptic on and haptic off as similarly intuitive, and more intuitive than joystick (p=0.033). Conclusion: Device-mimicking robotic controllers outperform joystick interfaces on most metrics; haptic feedback shows promising but non-significant performance benefits.
Benjamin Jackson, Nikola Fischer, Harry Robershaw +16