Actively Recruiting
Optimising Renal Tumour Management Through Artificial Intelligence Modules
Led by Shao Pengfei · Updated on 2025-03-19
2100
Participants Needed
1
Research Sites
469 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
The goal of this observational study is to improve the management of people with renal tumour by multimodal artificial intelligence(AI). It will also measure the accuracy of the predictions from AI models. The main questions it aims to answer are: 1. whether the AI module can accurately provide tumor-related information such as Benign or malignant, subtypes, grading, stage, etc. by learning from preoperative CT images. 2. whether the AI module can help clinicians find out the most suitable surgical programme for people with renal tumor. 3. whether the AI module can integrate CT images and pathology slides, offering supplementary prognostic information to improve postoperative survival. Participants who complete a CT(usually Contrast-enhanced CT, CECT) examination and undergo radical or partial nephrectomy will carry out active surveillance and record postoperative survival data for 5 years.
CONDITIONS
Official Title
Optimising Renal Tumour Management Through Artificial Intelligence Modules
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Patients with renal tumor which can be treated by surgery
- Complete CECT within 30 days before surgery
- Patients who fully understand this study and sign the informed consent
You will not qualify if you...
- Patients with any item missing from the baseline clinical and pathological information
- Patients who has already metastasized by the time the tumor is discovered
- Previous treatment in any form, including surgery, targeted therapy and immunotherapy
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
The First Affiliated Hospital of Nanjing Medical University (Jiangsu Provincial People's Hospital)
Nanjing, Jiangsu, China, 210036
Actively Recruiting
Research Team
S
Shao Pengfei, Professor
CONTACT
M
Miao Haoqi, Postgraduate
CONTACT
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
0
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