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Recruiting NCT07020169

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

No phase Interventional Renal Cell Cancer

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: an AI-based real-time image-guided kidney model system.
Who it may be relevant to
Registry conditions: Renal Cell Cancer. Basic parameters: 18 years — 80 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
China
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →

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Official title

Artificial Intelligence-Driven 3D Kidney Model for Real-Time Augmented Reality and Surgical Navigation in Minimally Invasive (Robotic/Laparoscopic) Partial Nephrectomy: A Prospective Validation Study

Overview

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?

Detailed 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.

Interventions

  • Procedure an AI-based real-time image-guided kidney model system
    Use the AI-model to locate kidney and tumour, assisting surgeon with the operation

Primary outcome measures

  • Operative Time [Time frame: Intraoperative]
Secondary outcome measures (1)
  • Operating Surgeon's Assessment [Time frame: immediately after the surgery]

Eligibility criteria

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

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation
Randomized
Model
Parallel assignment
Masking
Open label
Primary purpose
Treatment

Study locations

China · 2 centers
  • The First Affiliated Hospital of Nanjing Medical University (Jiangsu Provincial People's H — Nanjing
  • The First Affiliated Hospital of Nanjing Medical University (Jiangsu Provincial People's H — Nanjing

Identifiers

NCT: NCT07020169 · 2025-SR-309

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗