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

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

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?

Study Overview

• Status: Recruiting
• Conditions: Renal Cell Cancer
• Intervention / Treatment: Procedure: an AI-based real-time image-guided kidney model system

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.

• Study Type: Interventional
• Enrollment (Estimated): 232
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Pengfei Shao, Professor; Phone Number: +8613851925825; Email: spf032@hotmail.com
• Study Contact Backup: Name: Haoqi Miao, Postgraduate; Phone Number: +8613276636957; Email: mhq@stu.njmu.edu.cn

Study Locations

• China
  • Jiangsu
    • Nanjing, Jiangsu, China, 210036
      • Not yet recruiting
      • The First Affiliated Hospital of Nanjing Medical University (Jiangsu Provincial People's Hospital)
      • Contact: Pengfei Shao, Professor; Phone Number: +8613851925825; Email: spf032@hotmail.com
      • Contact: Haoqi Miao, Postgraduate; Phone Number: +8613276636957; Email: mhq@stu.njmu.edu.cn
    • Nanjing, Jiangsu, China, 210036
      • Recruiting
      • The First Affiliated Hospital of Nanjing Medical University (Jiangsu Provincial People's Hospital)
      • Contact: Pengfei Shao, Professor; Phone Number: +86 13851925825; Email: spf032@hotmail.com

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

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

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Treatment
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
No Intervention: Conventional Surgical Approaches; perform conventional laparoscopic or robotic-assisted surgical approaches
Experimental: AI model group; Use the AI-model to locate kidney and tumour, assisting surgeon with the operation	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

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Time Frame
Operative Time	Intraoperative

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Operating Surgeon's Assessment	Scoring for Each Surgery(0-5) by navigation accuracy, image rendering smoothness	immediately after the surgery

Collaborators and Investigators

• Sponsor: Shao Pengfei
• Collaborators: Southeast University, China

Study record dates

Study Major Dates

• Study Start (Actual): May 1, 2025
• Primary Completion (Estimated): September 1, 2026
• Study Completion (Estimated): March 1, 2027

Study Registration Dates

• First Submitted: May 24, 2025
• First Submitted That Met QC Criteria: June 12, 2025
• First Posted (Actual): June 13, 2025

Study Record Updates

• Last Update Posted (Actual): June 13, 2025
• Last Update Submitted That Met QC Criteria: June 12, 2025
• Last Verified: June 1, 2025

More Information

Terms related to this study

• Keywords: partial nephrectomy; Articicial Intelligence; Intraoperative Real-Time Navigation
• Additional Relevant MeSH Terms: Urogenital Diseases; Urogenital Neoplasms; Neoplasms by Site; Neoplasms; Male Urogenital Diseases; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Neoplasms by Histologic Type; Neoplasms, Glandular and Epithelial; Adenocarcinoma; Urologic Neoplasms; Carcinoma; Kidney Neoplasms; Carcinoma, Renal Cell
• Other Study ID Numbers: 2025-SR-309

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No