Renal StoneSENTINEL-1NCT07411391
Supervised Endoscopic Tele-controlled Intelligent Lithotripsy
A study testing RIRS using the TaloStone T1000 RIRS platform in people with Renal Stone, run by Chinese University of Hong Kong at 1 site in Hong Kong.
Trial 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. Read more about this study
- Who is it for?
- Ages 19 years and older
- Conditions the study is for
- Renal Stone
- What is being tested?
- RIRS using the TaloStone T1000 RIRS platform
- Type of treatment
- Surgery or procedure
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 15 participants
- Where
- 1 siteHong Kong
- Study dates
- 15 Feb 2026to 31 Mar 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 19 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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
Who cannot join
- 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)
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Hong Kong1 site, 1 recruiting
- Recruiting
Prince of Wales Hospital
Hong Kong, 999077
Alex Qinyang Liu, MBBS, MSc, FRCSEd, 852+35052625, alexliu@surgery.cuhk.edu.hk
Chi Fai Ng, MBChB, MD, FRCSEd, 852+35052625, ngcf@surgery.cuhk.edu.hk
About this study
Official title: A Feasibility Trial of a Novel Robotic System for Retrograde Intrarenal Surgery
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.
Read the detailed description
- 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 stone treatment was investigated. The second and third cadaver studies, focusing on the AI-powered features of the robotic system, were completed at PWH in June and December 2025. Synthetic renal stones of around 3mm were retrogradely inserted to the renal collecting systems, with successful fragmentation via the robotic RIRS system using Holmium:YAG laser. Over 10 doctors from PWH and the Chinese University of Hong Kong, participated in the cadaver studies. The current system response, motion speed of the robotic system, and operations with ergonomic control console can satisfy the requirements of the doctors. In addition to the cadaver studies, the investigators have conducted a set of laboratory testing and experiments, validating its robustness and stability of the system.
Subsequent to successful cadaveric experiments, the investigators planned to further validate of the feasibility of the use of the system in clinical cases. In this study, the investigators aim to evaluate the robotic system's safety and feasibility in RIRS in a stage 1, proof of concept study that follows the concepts outlined in the IDEAL framework (Idea, Development, Exploration, Assessment, Long-term Study).
II. Methods
Aim
The aim of this study is to evaluate the feasibility and safety of performing RIRS using the TaloStone T1000 system.
Study Design
This is a prospective, single-arm study that will be conducted by investigators from The Chinese University of Hong Kong/Prince of Wales Hospital in the period from November 2025 to June 2026. The investigators are experts in endo-urological surgery and robot-assisted surgery. The study design follows the guidelines for stage 1 of the IDEAL framework. The study will be carried out in accordance with the Declaration of Helsinki of the World Medical Association and the International Conference on Harmonization - Good Clinical Practice.
The study information will be provided to subjects during a preoperative consultation by the investigators and the research staff. Subjects will be provided with approved informed consent explaining the study procedure, risks, assessments, and required compliance; and will be given ample time to make their decision regarding participation in the study.
Perioperative data and outcomes from all cases of those participating in the study will be reviewed by an independent Data and Safety Monitoring Committee (consisting two senior urologists not involved in this study) for safety and identification of serious perioperative complications (within 30 days after the surgery) as interim to safeguard study subjects. The Committee will make periodic recommendations to the study team on whether to continue, modify, or prematurely terminate the study. Any adverse events will also be immediately reported to the Clinical Research Ethics Committee of the hospital.
Reporting of this stage 1 study will follow the IDEAL Reporting Guidelines.
- Conditions
- Renal Stone
- Being tested
- RIRS using the TaloStone T1000 RIRS platform
- Keywords
- Renal stone, Urolithiasis, RIRS, Flexible URS, Supervised autonomy
- Medical subject headings
- Nephrolithiasis, Urolithiasis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
RIRS using the TaloStone T1000 RIRS platformProcedure or surgery
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.
| Study group | Role | What they receive |
|---|---|---|
| RIRS arm | Experimental | Use of the TaloStone T1000 RIRS system Receives: Procedure: RIRS using the TaloStone T1000 RIRS platform |
What is being measured
The primary outcome is the main question the study is designed to answer.
Success rate
Successful RIRS by the robotic system, i.e. without conversion to conventional manual RIRS
Measured: Intra-operative
Secondary outcomes (13)
Stone free rate
- by non-contrast computer tomography (NCCT) performed within 1 month of surgery
- without residual stone fragments, or residual stone fragments <2mm
Measured: Within post-operative 1 month
Operative time
- total operative time (time from start of operation to the end of operation)
- console time (from start of control of robotic system to end of control of robotic system)
- robotic control time (defined as time spent manipulating the control for navigation)
- robotic set-up time (from the moment the robot is pushed into the operating room to the moment the flexible ureteroscope is attached to the robot)
- procedure time (total operative time - The robot set-up time)
- lasing time
Measured: Intra-operative
Total laser energy used
Laser energy in terms of kJ
Measured: Intra-operative
Total radiation dose during operation
Radiation dose based on fluoroscopy readings
Measured: Intra-operative
Surgeon radiation exposure
- by radiation dosimeter
Measured: Intra-operative
Length of hospital stay
- days of stay as in-patient
Measured: During admission period (up to 30 days)
Post-operative pain
- by visual analogue scale, from 0-10 with 10 being the most pain
Measured: From immediately post-operatively to discharge (day 0 to day 1)
Post-operative complications
By "Clavien-Dindo Classification"
Measured: Within post-operative 30 days
Surgeon questionnaires
Completed the Subjective Mental Effort Questionnaire (SMEQ) to assess subjective during RIRS surgery.
Measured: Immediately post-operative, day 0
Surgeon questionnaires
Completed the System Usability Scale (SUS) questionnaire to assess the subjective usability of the robotic system during RIRS surgery.
The questionnaire uses a 1-5 scale, where 1 = Strongly disagree and 5 = Strongly agree.
Measured: Immediately post-operative, day 0
Surgeon questionnaires
Completed the NASA Task Load Index (NASA-TLX) questionnaire to assess subjective mental and physical demand during RIRS surgery.
The questionnaire uses a 1-10 scale, where 1 = Very Low and 10 = Very High.
Measured: Immediately post-operative, day 0
Surgeon questionnaires
Completed the Simulator Sickness Questionnaire (SSQ) to assess the subjective symptoms experienced during or after RIRS surgery. The questionnaire uses a 0-3 scale, where 0 = None, 1 = Slight, 2 = Moderate, 3 = Severe
Measured: Immediately post-operative, day 0
Surgeon questionnaires
Completed the Likert Scales on Ergonomics and Comfort questionnaire, which assessed the subjective experience of minimal discomfort or fatigue during RIRS surgery. The questionnaire uses a 1-5 scale, where 1 = Strongly disagree and 5 = Strongly agree.
Measured: Immediately post-operative, day 0
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Feb 2026
- Study start15 Feb 2026
- Primary completion31 Dec 2026 (estimated)
- Study completion31 Mar 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (11)Papers the sponsor has linked to this study.
- Other trials for Renal StoneStudies of the same condition, open and under way.
- More trials run by Chinese University of Hong KongThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 15 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Chinese University of Hong Kong
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Alex Qinyang Liu, Chinese University of Hong Kong
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07411391
- Sponsor's protocol ID
- CRE-2025.665
- Other IDs
- CRE-2025.665
- Acronym
- SENTINEL-1
- Status last verified
- Oct 2026
- First submitted
- 29 Jan 2026
- Last updated
- 13 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Study protocol, statistical analysis plan, informed consent form, clinical study report, analytic code will be available.
Publications
Lu Y, Chen W, Lu B, Zhou J, Chen Z, Dou Q, Liu YH. Adaptive Online Learning and Robust 3-D Shape Servoing of Continuum and Soft Robots in Unstructured Environments. Soft Robot. 2024 Apr;11(2):320-337. doi: 10.1089/soro.2022.0158. Epub 2024 Feb 6.
PubMed 38324014Kuntz A, Emerson M, Ertop TE, Fried I, Fu M, Hoelscher J, Rox M, Akulian J, Gillaspie EA, Lee YZ, Maldonado F, Webster RJ 3rd, Alterovitz R. Autonomous medical needle steering in vivo. Sci Robot. 2023 Sep 20;8(82):eadf7614. doi: 10.1126/scirobotics.adf7614. Epub 2023 Sep 20.
PubMed 37729421Wei, 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.
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.
PubMed 33676097Dupont PE, Degirmenci A. The grand challenges of learning medical robot autonomy. Sci Robot. 2025 Jul 30;10(104):eadz8279. doi: 10.1126/scirobotics.adz8279. Epub 2025 Jul 30.
PubMed 40737383Long Y, Lin A, Kwok DHC, Zhang L, Yang Z, Shi K, Song L, Fu J, Lin H, Wei W, Chen K, Chu X, Hu Y, Yip HC, Chiu PWY, Kazanzides P, Taylor RH, Liu Y, Chen Z, Wang Z, Samuel Kwok Wai Au, Dou Q. Surgical embodied intelligence for generalized task autonomy in laparoscopic robot-assisted surgery. Sci Robot. 2025 Jul 16;10(104):eadt3093. doi: 10.1126/scirobotics.adt3093. Epub 2025 Jul 16.
PubMed 40668896Lu, 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.
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.
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.
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.
PubMed 37032384Giusti 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.
PubMed 27086502
Study at a glance
From the registry record, last updated by the sponsor on 13 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Feasibility Trial of a Novel Robotic System for Retrograde Intrarenal Surgery
- ClinicalTrials.gov ID
- NCT07411391
- Acronym / sponsor ID
- SENTINEL-1 / CRE-2025.665
- Conditions
- Renal Stone
- Keywords
- Renal stone, Urolithiasis, RIRS, Flexible URS, Supervised autonomy
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 15 participants (estimated)
- Lead sponsor
- Chinese University of Hong KongUniversity, hospital or other
- Study start
- 15 Feb 2026 (actual)
- Primary completion
- 31 Dec 2026 (estimated)
- Study completion
- 31 Mar 2027 (estimated)
- First posted
- 13 Feb 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
- 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 stone treatment was investigated. The second and third cadaver studies, focusing on the AI-powered features of the robotic system, were completed at PWH in June and December 2025. Synthetic renal stones of around 3mm were retrogradely inserted to the renal collecting systems, with successful fragmentation via the robotic RIRS system using Holmium:YAG laser. Over 10 doctors from PWH and the Chinese University of Hong Kong, participated in the cadaver studies. The current system response, motion speed of the robotic system, and operations with ergonomic control console can satisfy the requirements of the doctors. In addition to the cadaver studies, the investigators have conducted a set of laboratory testing and experiments, validating its robustness and stability of the system.
Subsequent to successful cadaveric experiments, the investigators planned to further validate of the feasibility of the use of the system in clinical cases. In this study, the investigators aim to evaluate the robotic system's safety and feasibility in RIRS in a stage 1, proof of concept study that follows the concepts outlined in the IDEAL framework (Idea, Development, Exploration, Assessment, Long-term Study).
II. Methods
Aim
The aim of this study is to evaluate the feasibility and safety of performing RIRS using the TaloStone T1000 system.
Study Design
This is a prospective, single-arm study that will be conducted by investigators from The Chinese University of Hong Kong/Prince of Wales Hospital in the period from November 2025 to June 2026. The investigators are experts in endo-urological surgery and robot-assisted surgery. The study design follows the guidelines for stage 1 of the IDEAL framework. The study will be carried out in accordance with the Declaration of Helsinki of the World Medical Association and the International Conference on Harmonization - Good Clinical Practice.
The study information will be provided to subjects during a preoperative consultation by the investigators and the research staff. Subjects will be provided with approved informed consent explaining the study procedure, risks, assessments, and required compliance; and will be given ample time to make their decision regarding participation in the study.
Perioperative data and outcomes from all cases of those participating in the study will be reviewed by an independent Data and Safety Monitoring Committee (consisting two senior urologists not involved in this study) for safety and identification of serious perioperative complications (within 30 days after the surgery) as interim to safeguard study subjects. The Committee will make periodic recommendations to the study team on whether to continue, modify, or prematurely terminate the study. Any adverse events will also be immediately reported to the Clinical Research Ethics Committee of the hospital.
Reporting of this stage 1 study will follow the IDEAL Reporting Guidelines.
Study design
- Primary purpose
- Treatment
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| RIRS arm | Experimental | Procedure: RIRS using the TaloStone T1000 RIRS platformUse of the TaloStone T1000 RIRS system |
Who may qualify
- Ages
- 19 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- 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
Key exclusion criteria (8 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| RIRS using the TaloStone T1000 RIRS platformRetrograde 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. | Procedure or surgery | RIRS arm |
Primary outcome
Success rate
Time frame: Intra-operative
Successful RIRS by the robotic system, i.e. without conversion to conventional manual RIRS
13 secondary outcomes
Stone free rate
Time frame: Within post-operative 1 month
Operative time
Time frame: Intra-operative
Total laser energy used
Time frame: Intra-operative
Total radiation dose during operation
Time frame: Intra-operative
Surgeon radiation exposure
Time frame: Intra-operative
Length of hospital stay
Time frame: During admission period (up to 30 days)
Post-operative pain
Time frame: From immediately post-operatively to discharge (day 0 to day 1)
Post-operative complications
Time frame: Within post-operative 30 days
Surgeon questionnaires
Time frame: Immediately post-operative, day 0
Surgeon questionnaires
Time frame: Immediately post-operative, day 0
Surgeon questionnaires
Time frame: Immediately post-operative, day 0
Surgeon questionnaires
Time frame: Immediately post-operative, day 0
Surgeon questionnaires
Time frame: Immediately post-operative, day 0
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Oct 2026.
- Background: PubMed 38324014Lu Y, Chen W, Lu B, Zhou J, Chen Z, Dou Q, Liu YH. Adaptive Online Learning and Robust 3-D Shape Servoing of Continuum and Soft Robots in Unstructured Environments. Soft Robot. 2024 Apr;11(2):320-337. doi: 10.1089/soro.2022.0158. Epub 2024 Feb 6.
- Background: PubMed 37729421Kuntz A, Emerson M, Ertop TE, Fried I, Fu M, Hoelscher J, Rox M, Akulian J, Gillaspie EA, Lee YZ, Maldonado F, Webster RJ 3rd, Alterovitz R. Autonomous medical needle steering in vivo. Sci Robot. 2023 Sep 20;8(82):eadf7614. doi: 10.1126/scirobotics.adf7614. Epub 2023 Sep 20.
- BackgroundWei, 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: PubMed 33676097Ross 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.
- Background: PubMed 40737383Dupont PE, Degirmenci A. The grand challenges of learning medical robot autonomy. Sci Robot. 2025 Jul 30;10(104):eadz8279. doi: 10.1126/scirobotics.adz8279. Epub 2025 Jul 30.
- Background: PubMed 40668896Long Y, Lin A, Kwok DHC, Zhang L, Yang Z, Shi K, Song L, Fu J, Lin H, Wei W, Chen K, Chu X, Hu Y, Yip HC, Chiu PWY, Kazanzides P, Taylor RH, Liu Y, Chen Z, Wang Z, Samuel Kwok Wai Au, Dou Q. Surgical embodied intelligence for generalized task autonomy in laparoscopic robot-assisted surgery. Sci Robot. 2025 Jul 16;10(104):eadt3093. doi: 10.1126/scirobotics.adt3093. Epub 2025 Jul 16.
- BackgroundLu, 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.
- BackgroundLu, 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.
- BackgroundChen, 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: PubMed 37032384Schlenk 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.
- Background: PubMed 27086502Giusti 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.
- Individual participant dataSharing planned: Yes. Study protocol, statistical analysis plan, informed consent form, clinical study report, analytic code will be available.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing RIRS using the TaloStone T1000 RIRS platform in people with Renal Stone, run by Chinese University of Hong Kong at 1 site in Hong Kong.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 8 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 13 Oct 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Hong Kong. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Alex Qinyang Liu, MBBS, MSc, FRCSEd (852+35052625, alexliu@surgery.cuhk.edu.hk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Success rate (time frame: Intra-operative). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07411391, which also lists 11 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 Oct 2026.