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?
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
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
NONE
Enrollment
232
Use the AI-model to locate kidney and tumour, assisting surgeon with the operation
The First Affiliated Hospital of Nanjing Medical University (Jiangsu Provincial People's Hospital)
Nanjing, Jiangsu, China
NOT_YET_RECRUITINGThe First Affiliated Hospital of Nanjing Medical University (Jiangsu Provincial People's Hospital)
Nanjing, Jiangsu, China
RECRUITINGOperative Time
Time frame: Intraoperative
Operating Surgeon's Assessment
Scoring for Each Surgery(0-5) by navigation accuracy, image rendering smoothness
Time frame: immediately after the surgery
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