Supervised Endoscopic Tele-controlled Intelligent Lithotripsy

This is a phase I feasibility study to investigate the use of a novel intelligent robotic retrograde intrarenal surgery (RIRS) platform. The TaloStone T1000 RIRS system can manipulate the flexible ureteroscope, with remote control of the instruments (laser fibre or basket) and ureteral access sheath movements. Beyond teleoperation, the TaloStone T1000 RIRS system integrates AI perception models and decision-making algorithms to enable the supervised autonomous execution of critical tasks within the RIRS workflow.

I. Introduction Retrograde intrarenal surgery (RIRS) has become a preferred method for the diagnosis and treatment of urological diseases, such as kidney stone removal. However, the complex urinary and limited visibility of existing endoscope lead to inefficient manipulation of flexible ureteroscopes. Besides, conventional flexible ureteroscopy requires repetitive manual manipulation, which often results in surgeon fatigue, mucosa injury from respiratory motion, and variable stone clearance rates, particularly in complex calyceal anatomies. The research focuses on the development of an novel robotic system for RIRS, currently dubbed "TaloStone T1000". The robotic system platform consists of a surgeon control console, a multi-functional video cart, and patient-side robotic arm with fiber-optic-sensitized flexible ureteroscopy as shown in Fig. 1. The surgeon console with optimized design of ergonomics is equipped with haptic master devices for smooth and precise control of the robotic arm to manipulate the flexible ureteroscope as well as instruments, e.g., stone baskets and laser fibers. The system also supports seamless integration of multiple modalities, including pre-operative CT scans, intra-operative endoscopic videos, and fiber-optic sensing. Besides, the self-developed flexible ureteroscope is embedded with fiber optic sensors for real-time shape sensing, force estimation, and simultaneous intrarenal pressure control and temperature monitoring. Shape sensing enables precise navigation of the ureteroscope within the renal collecting system, and force estimation provides accurate feedback of tip contact interaction to the master devices on the surgeon control. Moreover, AI algorithms are incorporated to assist in diagnostics and higher level of supervised surgical autonomy, thereby improving safety and efficiency. The investigators developed AI-powered diagnostics for stone sensing, laser fiber recognition, depth awareness, and CT-to-endoscopy localization. Based on the sensing results from AI-powered diagnostics, the investigators proposed a supervised framework that can automate repetitive procedures throughout in-sheath and ureter navigation, laser approaching, and laser trajectory planning. The entire operation is under supervision of the surgeon, who can use one trigger on the master device or footswitch to enable or disable the supervised automated features. The foot pedal of laser device remains to trigger laser emission by the surgeon for stone fragmentation, dusting, and pop-corning. The basic safety and essential performance of both hardware and software in the robotic system were developed under clinical standards and medical device regulations. To date, a total of three cadaveric studies have been conducted using the robotic system. In August 2024, the investigators performed the first cadaver study of the robotic system at Prince of Wales Hospital (PWH), where user study of ergonomic manners and tele-operation control of ston trial.show_full_description

Inclusion criteria 1. Adult patients \>18 years old 2. Renal stone(s) less than 1cm 2cm in maximal length 3. Clinically indicated for RIRS 4. Willingness to participate as demonstrated by giving informed consent Exclusion criteria 1. Patients with no preoperative CT imaging available 2. Patients who are not recommended to receive RIRS 3. Severe concomitant illness that drastically shortens life expectancy or increases risk of therapeutic intervention 4. Untreated active infection 5. Un-corrected coagulopathy 6. Presence of another malignancy or distant metastasis 7. Emergency surgery 8. Vulnerable population (e.g. mentally disabled, pregnant)