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Using 3D Kidney Model Based on Artificial Intelligence to Assist Partial Nephrectomy: A Prospective Validation Study

S

Shao Pengfei

Status

Enrolling

Conditions

Renal Cell Cancer

Treatments

Procedure: an AI-based real-time image-guided kidney model system

Study type

Interventional

Funder types

Other

Identifiers

NCT07020169
2025-SR-309

Details and patient eligibility

About

The goal of this study is to develop a real-time artificial intelligence-driven 3D kidney model to assist robotic or laparoscopic partial nephrectomy:

• Can this AI-powered model optimize the workflow of partial nephrectomy and enhance surgical benefits?

Full description

This study aims to evaluate the feasibility of the AI-based real-time image-guided kidney model system in optimizing partial nephrectomy workflows. Patients scheduled for laparoscopic or robotic-assisted partial nephrectomy will be randomized to receive either AI-assisted surgical navigation (utilizing intraoperative 3D model overlay with automated registration) or conventional approaches. Comparative metrics will include ischemia time, margin positivity rate, and operative efficiency indices. Findings will inform iterative refinement of the system architecture based on clinical performance feedback.

Enrollment

232 estimated patients

Sex

All

Ages

18 to 80 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • Ages 18-80 years, regardless of gender
  • Written informed consent obtained from the patient or legally authorized representative after full protocol disclosure
  • Preoperative imaging (CT/MRI) confirming clinical stage T1a or select T1b renal tumors suitable for partial nephrectomy (R.E.N.A.L. nephrometry score ≤10)
  • Localized renal tumors without lymph node/distant metastasis per NCCN Guidelines® (v2023)
  • Elective minimally invasive partial nephrectomy (laparoscopic/robotic) after comprehensive surgical counseling

Exclusion criteria

  • Multifocal renal tumors (bilateral or unilateral)
  • Prior systemic anticancer therapy (targeted agents/immunotherapy/chemotherapy) within 6 months
  • Absolute surgical contraindications (e.g., ASA class ≥IV, uncontrolled coagulopathy)
  • Intraoperative conversion to radical nephrectomy or open approach
  • Postoperative adjuvant therapy during protocol-defined follow-up (12 months)
  • Major comorbidities (e.g., NYHA class III/IV heart failure, eGFR <30 mL/min/1.73m²) affecting outcome assessment
  • Concurrent enrollment in interventional clinical trials
  • Investigator-determined ineligibility based on risk-benefit analysis

Trial design

Primary purpose

Treatment

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

None (Open label)

232 participants in 2 patient groups

Conventional Surgical Approaches
No Intervention group
Description:
perform conventional laparoscopic or robotic-assisted surgical approaches
AI model group
Experimental group
Description:
Use the AI-model to locate kidney and tumour, assisting surgeon with the operation
Treatment:
Procedure: an AI-based real-time image-guided kidney model system

Trial contacts and locations

1

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Central trial contact

Haoqi Miao, Postgraduate; Pengfei Shao, Professor

Data sourced from clinicaltrials.gov

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