NCT07020169

Brief 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?

Trial Health

77
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
232

participants targeted

Target at P75+ for not_applicable

Timeline
10mo left

Started May 2025

Typical duration for not_applicable

Geographic Reach
1 country

2 active sites

Status
recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Progress56%
May 2025Mar 2027

Study Start

First participant enrolled

May 1, 2025

Completed
23 days until next milestone

First Submitted

Initial submission to the registry

May 24, 2025

Completed
20 days until next milestone

First Posted

Study publicly available on registry

June 13, 2025

Completed
1.2 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

September 1, 2026

Expected
6 months until next milestone

Study Completion

Last participant's last visit for all outcomes

March 1, 2027

Last Updated

June 13, 2025

Status Verified

June 1, 2025

Enrollment Period

1.3 years

First QC Date

May 24, 2025

Last Update Submit

June 12, 2025

Conditions

Renal Cell Cancer

Keywords

partial nephrectomyArticicial IntelligenceIntraoperative Real-Time Navigation

Outcome Measures

Primary Outcomes (1)

  • Operative Time

    Intraoperative

Secondary Outcomes (1)

  • Operating Surgeon's Assessment

    immediately after the surgery

Study Arms (2)

Conventional Surgical Approaches

NO INTERVENTION

perform conventional laparoscopic or robotic-assisted surgical approaches

AI model group

EXPERIMENTAL

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

Interventions

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

Use the AI-model to locate kidney and tumour, assisting surgeon with the operation

AI model group

Eligibility Criteria

Age18 Years - 80 Years
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • 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

You may not qualify if:

  • 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

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (2)

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

Nanjing, Jiangsu, 210036, China

NOT YET RECRUITING

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

Nanjing, Jiangsu, 210036, China

RECRUITING

MeSH Terms

Conditions

Carcinoma, Renal Cell

Condition Hierarchy (Ancestors)

AdenocarcinomaCarcinomaNeoplasms, Glandular and EpithelialNeoplasms by Histologic TypeNeoplasmsKidney NeoplasmsUrologic NeoplasmsUrogenital NeoplasmsNeoplasms by SiteFemale Urogenital DiseasesFemale Urogenital Diseases and Pregnancy ComplicationsUrogenital DiseasesKidney DiseasesUrologic DiseasesMale Urogenital Diseases

Central Study Contacts

Pengfei Shao, Professor

CONTACT

+8613851925825spf032@hotmail.com

Haoqi Miao, Postgraduate

CONTACT

+8613276636957mhq@stu.njmu.edu.cn

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
NONE
Purpose
TREATMENT
Intervention Model
PARALLEL
Sponsor Type
OTHER
Responsible Party
SPONSOR INVESTIGATOR
PI Title
chief physician

Study Record Dates

First Submitted

May 24, 2025

First Posted

June 13, 2025

Study Start

May 1, 2025

Primary Completion (Estimated)

September 1, 2026

Study Completion (Estimated)

March 1, 2027

Last Updated

June 13, 2025

Record last verified: 2025-06

Locations

CN(2)