NCT04003558

Deep Learning Algorithms for Prediction of Lymph Node Metastasis and Prognosis in Breast Cancer MRI Radiomics (RBC-01)

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 1,500 (estimated)
• Sponsor: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University · Academic / Other
• Sex: Female
• Age: 18 Years – 75 Years
• Healthy volunteers: Not accepted

Summary

This bi-directional, multicentre study aims to assess multiparametric MRI Radiomics-based prediction model for identifying metastasis lymph nodes and prognostic prediction in breast cancer.

Detailed description

Sensitivity for prediction of lymph node metastasis and survival of currently available prognostic scores in limited. This study proposes to establish a deep learning algorithms of multiparametric MRI radiomics and nomogram for identifying lymph node metastasis and prognostic prediction of breast cancer. The study will investigate the relationship between the radiomics and the tumor microenvironment. The study includes the construction of multiparametric MRI radiomics-based prediction model and the validation of the prediction model.

Conditions

• Breast Neoplasm Female
• Early-stage Breast Cancer
• Radiomics
• Axillary Lymph Node
• Survival, Prosthesis

Interventions

Type	Name	Description
OTHER	No interventions	As this is a patient registry, there are no interventions.

Timeline

• Start date: 2019-05-28
• Primary completion: 2020-05-31
• Completion: 2025-01-01
• First posted: 2019-07-01
• Last updated: 2019-08-15

Locations

5 sites across 1 country: China