This retrospective + prospective, non-interventional study aims to develop and evaluate artificial intelligence methods for the detection, pathological subtyping, and histological grading of renal tumors using magnetic resonance imaging (MRI). Approximately 900 adult patients with available preoperative renal MRI examinations and postoperative pathological results will be included. The pathological findings will be used as the reference standard for model development and evaluation. In addition to MRI data, selected demographic, clinical, and laboratory information may be incorporated to improve model performance. The study will not change participants' diagnosis, treatment, or follow-up, and no additional examinations or interventions will be required. All study data will be de-identified before analysis. The ultimate goal is to develop an MRI-based intelligent diagnostic approach that may assist clinicians in the preoperative assessment and individualized management of patients with renal tumors.
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.
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.
Cancer Institute and Hospital, Chinese Academy of Medical Sciences
Lead sponsor
Peking University People's Hospital
Collaborator
Shanxi Province Cancer Hospital
Collaborator
Chinese PLA General Hospital
Collaborator
RenJi Hospital
Collaborator
Cancer Hospital Chinese Academy of Medical Science, Shenzhen Center
Collaborator