Supervised Endoscopic Tele-controlled Intelligent Lithotripsy

NCT07411391 | Recruiting

• 1 other identifier: CRE-2025.665
• Study Type: interventional
• Target: 15
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Renal Stone

Keywords

Renal stone; Urolithiasis; RIRS; Flexible URS; Supervised autonomy

Outcome Measures

Primary Outcomes (1)

• Success rate

  Successful RIRS by the robotic system, i.e. without conversion to conventional manual RIRS

  Intra-operative

Secondary Outcomes (13)

• Stone free rate

  Within post-operative 1 month

• Operative time

  Intra-operative

• Total laser energy used

  Intra-operative

• Total radiation dose during operation

  Intra-operative

• Surgeon radiation exposure

  Intra-operative

Study Arms (1)

RIRS arm

EXPERIMENTAL

Use of the TaloStone T1000 RIRS system

Procedure: RIRS using the TaloStone T1000 RIRS platform

Interventions

RIRS using the TaloStone T1000 RIRS platform PROCEDURE

Retrograde intrarenal surgery (RIRS) will be performed using the TaloStone T1000 RIRS system. Beyond teleoperation, the TaloStone T1000 RIRS system integrates advanced AI perception models and decision-making algorithms to enable the autonomous execution of critical tasks within the RIRS workflow. The AI-based vision models coupled with sensors in the fURS allow real-time scene understanding, depth perception, stone size estimation, pressure and temperature feedback, and object tracking - thus establishing a robust foundation for higher level of surgical autonomy. Under supervision by the surgeon, the TaloStone T1000 RIRS system can perform supervised navigation into the collecting system, actively track a target stone, dynamically target the laser fibre tip towards a stone, plan the laser fragmentation route, and perform scope withdrawal for stone suction with re-entry.

RIRS arm

Eligibility Criteria

• Age: 19 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Adult patients \>18 years old
• Renal stone(s) less than 1cm 2cm in maximal length
• Clinically indicated for RIRS
• Willingness to participate as demonstrated by giving informed consent

You may not qualify if:

• Patients with no preoperative CT imaging available
• Patients who are not recommended to receive RIRS
• Severe concomitant illness that drastically shortens life expectancy or increases risk of therapeutic intervention
• Untreated active infection
• Un-corrected coagulopathy
• Presence of another malignancy or distant metastasis
• Emergency surgery
• Vulnerable population (e.g. mentally disabled, pregnant)

Sponsors & Collaborators

• Chinese University of Hong Kong: lead

Study Sites (1)

Prince of Wales Hospital

Hong Kong, 999077, Hong Kong

RECRUITING

Related Publications (11)

• Lu, Y., Chen, W., Lu, B., Zhou, J., Chen, Z., Dou, Q. and Liu, Y.H., 2024. Adaptive online learning and robust 3-d shape servoing of continuum and soft robots in unstructured environments. Soft Robotics, 11(2), pp.320-337.

  BACKGROUND

• Kuntz, A., Emerson, M., Ertop, T.E., Fried, I., Fu, M., Hoelscher, J., Rox, M., Akulian, J., Gillaspie, E.A., Lee, Y.Z. and Maldonado, F., 2023. Autonomous medical needle steering in vivo. Science Robotics, 8(82), p.eadf7614.

  BACKGROUND

• Wei, R., Guo, J., Lu, Y., Zhong, F., Liu, Y., Sun, D. and Dou, Q., 2024. Scale-aware monocular reconstruction via robot kinematics and visual data in neural radiance fields. Artificial Intelligence Surgery, 4(3), pp.187-198.

  BACKGROUND

• Ross T, Reinke A, Full PM, Wagner M, Kenngott H, Apitz M, Hempe H, Mindroc-Filimon D, Scholz P, Tran TN, Bruno P, Arbelaez P, Bian GB, Bodenstedt S, Bolmgren JL, Bravo-Sanchez L, Chen HB, Gonzalez C, Guo D, Halvorsen P, Heng PA, Hosgor E, Hou ZG, Isensee F, Jha D, Jiang T, Jin Y, Kirtac K, Kletz S, Leger S, Li Z, Maier-Hein KH, Ni ZL, Riegler MA, Schoeffmann K, Shi R, Speidel S, Stenzel M, Twick I, Wang G, Wang J, Wang L, Wang L, Zhang Y, Zhou YJ, Zhu L, Wiesenfarth M, Kopp-Schneider A, Muller-Stich BP, Maier-Hein L. Comparative validation of multi-instance instrument segmentation in endoscopy: Results of the ROBUST-MIS 2019 challenge. Med Image Anal. 2021 May;70:101920. doi: 10.1016/j.media.2020.101920. Epub 2020 Nov 28.

  PMID: 33676097 BACKGROUND

• Dupont, P.E. and Degirmenci, A., 2025. The grand challenges of learning medical robot autonomy. Science Robotics, 10(104), p.eadz8279.

  BACKGROUND

• Long, Y., Lin, A., Kwok, D.H.C., Zhang, L., Yang, Z., Shi, K., Song, L., Fu, J., Lin, H., Wei, W. and Chen, K., 2025. Surgical embodied intelligence for generalized task autonomy in laparoscopic robot-assisted surgery. Science Robotics, 10(104), p.eadt3093.

  BACKGROUND

• Lu, Y., Chen, W., Li, B., Lu, B., Zhou, J., Chen, Z. and Liu, Y.H., 2023. A robust graph-based framework for 3-d shape reconstruction of flexible medical instruments using multi-core fbgs. IEEE Transactions on Medical Robotics and Bionics, 5(3), pp.472-485.

  BACKGROUND

• Lu, Y., Lu, B., Li, B., Guo, H. and Liu, Y.H., 2021. Robust three-dimensional shape sensing for flexible endoscopic surgery using multi-core FBG sensors. IEEE Robotics and Automation Letters, 6(3), pp.4835-4842.

  BACKGROUND

• Chen, W., Lu, Y., Li, B., Zhou, J., Cao, H., Chen, F. and Liu, Y.H., 2024, June. Intuitive teleoperation control for flexible robotic endoscopes under unkonwn environmental interferences. In 2024 IEEE 18th International Conference on Control & Automation (ICCA) (pp. 24-29). IEEE.

  BACKGROUND

• Schlenk C, Hagmann K, Steidle F, Oliva Maza L, Kolb A, Hellings-Kuss A, Schob DS, Klodmann J, Miernik A, Albu-Schaffer A. A robotic system for solo surgery in flexible ureteroscopy: development and evaluation with clinical users. Int J Comput Assist Radiol Surg. 2023 Sep;18(9):1559-1569. doi: 10.1007/s11548-023-02883-5. Epub 2023 Apr 9.

  PMID: 37032384 BACKGROUND

• Giusti G, Proietti S, Villa L, Cloutier J, Rosso M, Gadda GM, Doizi S, Suardi N, Montorsi F, Gaboardi F, Traxer O. Current Standard Technique for Modern Flexible Ureteroscopy: Tips and Tricks. Eur Urol. 2016 Jul;70(1):188-194. doi: 10.1016/j.eururo.2016.03.035. Epub 2016 Apr 14.

  PMID: 27086502 BACKGROUND

MeSH Terms

Conditions

Nephrolithiasis; Urolithiasis

Condition Hierarchy (Ancestors)

Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Male Urogenital Diseases

Central Study Contacts

Alex Qinyang Liu, MBBS, MSc, FRCSEd

CONTACT

852+35052625; alexliu@surgery.cuhk.edu.hk

Chi Fai Ng, MBChB, MD, FRCSEd

CONTACT

852+35052625; ngcf@surgery.cuhk.edu.hk

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: TREATMENT
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: January 29, 2026
• First Posted: February 13, 2026
• Study Start: February 15, 2026
• Primary Completion (Estimated): December 31, 2026
• Study Completion (Estimated): March 31, 2027
• Last Updated: April 24, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, CSR, ANALYTIC CODE
• Time Frame: It will be available after the publication of the manuscript (latest 31 Dec 2027 by estimation), and will be available for up to 5 years afterwards
• Access Criteria: IPD will be shared in a de-identified manner for reasonable studies with approved from the relevant institutional review board.

Locations

HK (1)