NCT06546072

Deep Learning With MRI-based Multimodal-data Fusion Enhanced Postoperative Risk Stratification of Breast Cancer

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 1,199 (actual)
• Sponsor: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University · Academic / Other
• Sex: Female
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

Breast cancer poses a significant global health challenge, especially among women, with high rates of recurrence and distant spread despite early interventions. The timely identification of metastasis risk and accurate prediction of treatment strategies are critical for improving prognosis. However, the complex heterogeneity of breast tumors presents challenges in precise prognosis prediction. Therefore, the development of innovative methods for tumor segmentation and prognosis assessment is essential. The research conducted is a multicenter study that enrolled 1,199 non-metastatic breast cancer patients from four independent centers. Our study leverages the advancements in artificial intelligence (AI) to address this challenge. This study is the first successful application of MRI-based multimodal prediction system to precisely identify the risk of postoperative recurrence in breast cancer patients.

Conditions

• Breast Cancer

Interventions

Type	Name	Description
OTHER	MRI

Timeline

• Start date: 2011-03-23
• Primary completion: 2019-09-21
• Completion: 2021-12-06
• First posted: 2024-08-09
• Last updated: 2024-08-09