Molecular typing provides accurate information for the diagnosis, treatment and prognosis prediction of endometrial cancer, which has important clinical significance. However, due to its high cost and complicated process, it is difficult to be widely used in clinical practice. Based on the artificial intelligence method, this study fused the characteristics of MRI radiomics and pathomics, combined with the clinical pathological information, built a model to predict the molecular typing and prognosis, analyzed the biological characteristics of endometrial cancer from the multi-scale level, guided the personalized and precise diagnosis and treatment, in order to improve the prognosis of patients.
•Pathologically confirmed as endometrial malignant tumor with complete pathological H＆E stained sections;
Age ≥ 18 years and ≤ 80 years;
No other malignant cancers was found;
The complete immunohistochemical and second-generation sequencing results can be used for the molecular typing of ProMisE;
• The image quality is poor or the tumor is too small due to serious graphic artifact and degeneration, and the ROI cannot be accurately delineated;
Patients who received any antitumor therapy before surgery;
Diagnostic endometrial biopsy before MRI
Fujian Cancer Hospital
Lead sponsor
Fujian Provincial Hospital
Collaborator
First Affiliated Hospital of Fujian Medical University
Collaborator
Gutian Hospital
Collaborator