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

Last updated: June 12, 2025
Sponsor: Shao Pengfei
Overall Status: Active - Recruiting

Phase

N/A

Condition

Renal Cell Carcinoma

Kidney Cancer

Renal Cell Cancer

Treatment

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

Clinical Study ID

NCT07020169
2025-SR-309
  • Ages 18-80
  • All Genders

Study Summary

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?

Eligibility Criteria

Inclusion

Inclusion Criteria:

  • Ages 18-80 years, regardless of gender

  • Written informed consent obtained from the patient or legally authorizedrepresentative after full protocol disclosure

  • Preoperative imaging (CT/MRI) confirming clinical stage T1a or select T1b renaltumors 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) aftercomprehensive surgical counseling

Exclusion

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

Study Design

Total Participants: 232
Treatment Group(s): 1
Primary Treatment: an AI-based real-time image-guided kidney model system
Phase:
Study Start date:
May 01, 2025
Estimated Completion Date:
March 01, 2027

Study 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.

Connect with a study center

  • The First Affiliated Hospital of Nanjing Medical University (Jiangsu Provincial People's Hospital)

    Nanjing, Jiangsu 210036
    China

    Site Not Available

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