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?
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)
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
Parallel
an AI-based real-time image-guided kidney model system
Procedure/SurgeryUse the AI-model to locate kidney and tumour, assisting surgeon with the operation
Operative Time
Operating Surgeon's Assessment
Scoring for Each Surgery(0-5) by navigation accuracy, image rendering smoothness
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Shao Pengfei
Lead sponsor
The First Affiliated Hospital with Nanjing Medical University
Sponsor institution
Southeast University, China
Collaborator
