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

NCT07244094 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 400

Last updated 2026-02-17

No results posted yet for this study

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

Interventions

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.

Sponsors & Collaborators

  • Second Affiliated Hospital, School of Medicine, Zhejiang University

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
95 Years
Sex
FEMALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-11-15
Primary Completion
2026-12-30
Completion
2027-03-07

Countries

  • China

Study Locations

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Entities

Diseases

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 NCT07244094 on ClinicalTrials.gov