AI for Renal Tumors Using Non-Contrast CT
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Renal Neoplasms, Renal Cyst. Basic parameters: 18 years — 80 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
An Artificial Intelligence Model for Screening and Diagnosis of Renal Tumors Based on Non-Contrast CT
Overview
The goal of this observational study is to learn whether the artificial intelligence method can automatically identify and diagnose renal lesions using non-contrast CT or opportunistic screening.
Detailed description
This study first establishes an AI model capable of effectively detecting and diagnosing kidney lesions based on a multicenter retrospective cohort study. Then, the AI model is applied to a large-scale real-world retrospective and prospective population to validate and improve its effectiveness.
Primary outcome measures
- Building an intelligent diagnostic system for renal diseases based on CT scans. [Time frame: 1 year]
Secondary outcome measures (1)
- Further develop artificial intelligence model to effectively diagnose pathological types of common renal tumors. [Time frame: 1 year]
Eligibility criteria
Inclusion criteria
- Patients who underwent an abdominal CT examination.
- Patients with renal lesions were managed according to standard clinical pathways, which included follow-up, biopsy, or surgery.
- Malignant lesions were pathologically confirmed; benign lesions were confirmed by either pathological diagnosis or imaging follow-up.
- No prior treatment had been received for the renal disease.
Exclusion criteria
- Patients refuse to undergo recommended follow-up, biopsy, or surgery, which precluded definitive diagnosis of the renal lesion.
- Absence of complete pathological confirmation for lesions suspected to be malignant.
- Patients have received any form of prior treatment for the renal lesion.
- Poor image quality that hampered diagnostic evaluation.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Study design
- Observational model
- Cohort
Study locations
China · 1 center
- Fudan university Shanghai Cancer Center — Shanghai
Identifiers
NCT: NCT07304492 · 2509-Exp275