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

NCT06546072 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 1199

Last updated 2024-08-09

No results posted yet for this study

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

Interventions

OTHER

MRI

Sponsors & Collaborators

  • Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

    lead OTHER

Eligibility

Min Age
18 Years
Sex
FEMALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2011-03-23
Primary Completion
2019-09-21
Completion
2021-12-06

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06546072 on ClinicalTrials.gov