MRI-based AI to classify and grade renal tumors

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This is an observational, non-interventional study that uses existing and new MRI data to train and evaluate artificial intelligence models for detecting renal tumors, determining their pathological subtype, and grading them histologically. The research combines retrospective and prospective data, with pathological results serving as the reference standard. No changes to diagnosis or treatment occur, and no extra procedures are required beyond standard care. Data will be de-identified prior to analysis, and multiple MRI sequences may be used to improve model performance. The aim is to support preoperative assessment and personalized management of renal tumors.

Why it matters

Who can join: the full rules

Inclusion Criteria:

* Patients aged 18 years or older.
* Patients diagnosed with a renal tumor.
* Availability of preoperative renal magnetic resonance imaging examinations.
* Availability of a corresponding pathological diagnosis, including pathological subtype and, where applicable, histological grade.
* Magnetic resonance images that can be successfully retrieved and are of - - sufficient quality for image analysis.

Exclusion Criteria:

* Absence of renal magnetic resonance imaging data.
* Absence of a corresponding pathological diagnosis or insufficient pathological subtype or grading information.
* Magnetic resonance images that cannot be retrieved, opened, or read.
* Poor image quality that precludes reliable image annotation or artificial intelligence analysis.

Where it's running

• Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College
  Beijing, China Recruiting

Study contacts

• Study coordinator: Xiongjun Ye
• Email: yexiongjun@cicams.ac.cn
• Phone: 010-87787170

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.