NCT06126393

MRI Radiomics Combined With Pathomics on the Prediction of Molecular Classification and Prognosis of Endometrial Cancer

Study on the Prediction of Molecular Classification and Prognosis of Endometrial Cancer Using a Model Constructed by Magnetic Resonance Imaging Radiomics Combined With Pathomics

• Status: Not Yet Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 350 (estimated)
• Sponsor: Fujian Cancer Hospital · Other Government
• Sex: Female
• Age: 18 Years – 80 Years
• Healthy volunteers: —

Summary

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.

Detailed description

In this project, 150 cases of endometrial cancer were retrospectively collected, and 200 cases of endometrial cancer will be prospectively collected. All patients were pathologically confirmed and underwent Promise molecular typing. Before treatment, all patients completed abdominal MRI. Based on artificial intelligence technology, image features were extracted from magnetic resonance imaging, pathological features were extracted from pathological data, and clinical pathological data were collected at the same time. The treatment effect, recurrence and metastasis of patients were followed up, and the five-year survival rate and five-year progression free survival rate were calculated. It is proposed to focus on the following research: 1. Construction of molecular typing and prognosis prediction model of endometrial cancer based on magnetic resonance imaging Radiomics 2. Construction of molecular typing and prognosis prediction model of endometrial cancer based on pathomics. 3. Construction of a prediction model for molecular typing of endometrial cancer by integrating pathomics and radiomics.

Conditions

• Endometrial Neoplasms

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	next generation sequencing AND Immunohistochemical examination	First, the mismatch repair (MMR) proteins were detected by immunohistochemistry, and the deletion of one or more proteins was classified as d-MMR subtype; Then the POLE gene mutation detection was performed, and the mutation Changes were classified as POLE mutation; Finally, p53 was detected by immunohistochemistry, and p53 mutant (p53 abn) and p53 wild-type (p53wt) were distinguished.

Timeline

• Start date: 2024-01-01
• Primary completion: 2027-03-31
• Completion: 2027-06-30
• First posted: 2023-11-13
• Last updated: 2023-11-15

Locations

1 site across 1 country: China