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Clinical Trials in China / NCT07692230
Active, not recruiting Observational

MRI-Driven Precision Typing and Response Prediction in Luminal Breast Cancer

NCT07692230 · tracked via the Priya Life Science China tracker
Sponsor
Fudan University
Phase
Observational
Started
2026-01-06
Last updated
2026-07-21

Condition(s) studied

HR Positive/HER-2 Negative Breast Cancer

Study summary

Luminal breast cancer is characterized by marked heterogeneity, resulting in diverse treatment responses and long-term outcomes. This project aims to integrate MRI and multiomics data to achieve non-invasive molecular typing and precise response prediction. By linking imaging phenotypes with underlying molecular and pathological characteristics, the investigators will develop predictive models for treatment resistance, recurrence, and metastasis, ultimately supporting personalized treatment strategies and precision oncology.

Eligibility

Sex
FEMALE
Min age
—
Max age
—
Healthy volunteers
No
Inclusion Criteria: 1. Histopathologically confirmed invasive luminal breast cancer (HR+/HER2-); 2. Patients who underwent breast MRI examination. Exclusion Criteria: 1. Pathological biopsy performed prior to the baseline MRI examination; 2. Patients have received any form of prior treatment for the breast cancer; 3. History of other malignancies; 4. Incomplete or poor-quality MRI and/or pathological images; 5. Missing clinical data.

Primary outcome measure(s)

  • Diagnostic performance of breast MRI for molecular subtyping of luminal breast cancer, with comparison to multiomics — 1 year
    The primary outcome is the diagnostic performance of AI-assisted analysis for molecular subtyping of luminal breast cancer on contrast-enhanced breast MRI. Quantitative radiomic features and deep learning features are extracted from DCE-MRI, followed by classification into multiomics-defined molecular subtypes. Performance metrics include sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and area under the receiver operating characteristic curve (AUC). Participants must have undergone both breast MRI and multiomics profiling of tumor tissue. Performance metrics will be compared with those obtained from multiomics classification within the same participants to evaluate the relative diagnostic performance.

Trial sites (1)

FacilityCityRegionStatus
Fudan university Shanghai Cancer Center Shanghai Shanghai Municipality

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Official registry record

This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.

View NCT07692230 on ClinicalTrials.gov ↗ ← All trials in China