Dietsch, Solène; (2025) Sensorised Soft Devices for Tumour Localisation in Robotic-Assisted Minimally Invasive Surgery. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Real-time tumour localisation remains a major challenge in Robotic-Assisted Minimally Invasive Surgery (RAMIS) due to the limited sensory feedback available to surgeons. In addition, the rigidity of conventional robotic surgical tools can restrict access to certain anatomical regions, sometimes necessitating a return to open surgery. Soft robots have emerged as a promising solution to these limitations, offering the ability to navigate otherwise inaccessible areas while providing safer and more adaptive organ manipulation. By enabling compliant interactions with tissues, these innovative systems can incorporate advanced sensing and imaging technologies over extensive surfaces, offering a means to restore tactile feedback for precise tumour detection. Despite a decade of innovation, soft robots have yet to be integrated into surgical practice. While the compliance of soft robots facilitates safe tissue interaction, it also introduces unpredictable deformations, complicating their clinical application. Nevertheless, these devices hold the potential to evolve into versatile sensory platforms, empowering surgeons with tools to make informed decisions. To fully realise their potential in RAMIS, soft surgical devices require advanced sensing capabilities that accommodate their compliant nature while meeting the specific demands of RAMIS. This thesis explores the integration of sensitive soft devices to achieve precise tumour localisation during RAMIS. Focusing on two imaging techniques, it develops core sensing functions that harness the benefits of soft surgical devices. First, a fibre-based shape-sensing sensor is integrated into the Pneumatically Attachable Flexible (PAF) rails - a soft robotic platform that guides an ultrasound probe during Robotic-Assisted Partial Nephrectomy (RAPN). This proprioceptive feedback enabled control of a conventional robotic instrument along the PAF rails and facilitated monitoring of the surgical interaction with the soft robot, demonstrating the potential of soft robots as a multisensory platform. The second innovation introduces the Imaging Skin, a novel soft sensor designed for radiation-based imaging. By conforming to the organ surface, it unlocks new capabilities in RAMIS through surface-level intraoperative imaging. While this research develops proprioception and imaging independently, it is a critical step toward understanding the unique challenges of using soft devices in surgery. Together, these innovations lay the foundation for future fully integrated soft systems to enable safe and precise tumour localisation in RAMIS.

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