NCT07244094

A Study on Predicting the Risk of Distant Metastasis in Breast Cancer Using AI-Generated Spatial Pathological Maps

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 400 (estimated)
• Sponsor: Second Affiliated Hospital, School of Medicine, Zhejiang University · Academic / Other
• Sex: Female
• Age: 18 Years – 95 Years
• Healthy volunteers: Not accepted

Summary

The goal of this observational study is to develop and validate an artificial intelligence (AI) model for predicting the risk of distant metastasis in patients with primary breast cancer. The main question it aims to answer is: Can a multimodal AI model, trained on routinely available histopathological images, accurately predict the long-term risk of breast cancer metastasis? Researchers will analyze existing hematoxylin and eosin (H\&E) and immunohistochemistry (IHC) stained tissue slides from patients who underwent surgery between 2015 and 2025. Clinical data will be used to train the AI model and evaluate its performance in predicting metastasis.

Conditions

• Breast Cancer

Interventions

Type	Name	Description
OTHER	Diagnostic Test: AI-Based Spatial Pathomic Analysis	This is an observational study with no therapeutic or procedural interventions. The "intervention" refers to the analytical method applied to existing data. Archived tissue samples (H\&E and IHC stained slides) will be digitally scanned and analyzed by a multimodal artificial intelligence (AI) model to develop a risk prediction tool for distant metastasis. Patients' clinical data will be collected for model training and validation. No direct interaction with patients occurs, and no treatment decisions are influenced by this study.

Timeline

• Start date: 2025-11-15
• Primary completion: 2026-12-30
• Completion: 2027-03-07
• First posted: 2025-11-24
• Last updated: 2026-02-17

Locations

4 sites across 1 country: China