Status
Conditions
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:
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.
Full description
In this study, AI model will explore and clarify features in renal tumor CT images and pathological images that are difficult to detect manually, and then correlate them with clinical outcomes, thereby improving the diagnosis and treatment process for renal tumors. Firstly, the model can accurately distinguish renal tumor subtypes and predict stage, grade, and complexity so as to svoid misdiagnosis and assist clinicians in formulating treatment plans. Secondly, by learning from surgical videos, the model can provide additional information during surgerys, such as important anatomical landmarks, location of tumors. Finally, combining radiomics and pathomics, the model can differentiate between high-risk and low-risk patients after surgery, thus providing personalized prognostic guidance.
Enrollment
Sex
Ages
Volunteers
Inclusion criteria
Exclusion criteria
Loading...
Central trial contact
Miao Haoqi, Postgraduate; Shao Pengfei, Professor
Data sourced from clinicaltrials.gov
Clinical trials
Research sites
Resources
Legal