Pre-Treatment DCE-MRI AI Models Predict Neoadjuvant Chemotherapy Response in HR+/HER2- Breast Cancer

NCT07702708 · tracked via the Priya Life Science China tracker

Sponsor

Fujian Cancer Hospital

Phase

Observational

Started

2026-06-01

Last updated

2026-07-14

Condition(s) studied

HR+/HER2- Breast CancerBreast Neoplasms

Investigational drug(s) / intervention(s)

Pre-treatment DCE-MRI-based AI model

Pre-treatment DCE-MRI-based AI model: Preoperative dynamic contrast-enhanced MRI images are input into an artificial intelligence prediction model to stratify HR+/HER2- breast cancer patients into high and low neoadjuvant chemotherapy benefit subgroups.

Study summary

This study is a multicenter, prospective, observational cohort study to evaluate the predictive performance of pre-treatment DCE-MRI-based artificial intelligence (AI) models for neoadjuvant chemotherapy benefit in HR+/HER2- breast cancer. The study plans to enroll eligible HR+/HER2- breast cancer patients receiving routine standard neoadjuvant chemotherapy and stratify participants into high-benefit and low-benefit subgroups via the established AI model based on baseline breast DCE-MRI images.

All enrolled patients will undergo systematic collection of baseline clinical-pathological data, pre-treatment DCE-MRI scans, neoadjuvant chemotherapy regimens, postoperative residual cancer burden (RCB) classification, objective response rate (ORR), and long-term survival endpoints including disease-free survival (DFS) and overall survival (OS). The primary objective compares the rate of RCB 0-1 between AI-defined high-benefit patients and published historical control data; secondary analyses compare ORR, RCB 0-1 proportion, DFS and OS between AI-stratified high-benefit and low-benefit subgroups to comprehensively verify the clinical value of this imaging AI model for individualized neoadjuvant chemotherapy selection.

Eligibility

Sex

FEMALE

Min age

18 Years

Max age

—

Healthy volunteers

Inclusion Criteria: 1. Female patients aged ≥ 18 years old. 2. Histopathologically confirmed invasive breast carcinoma. 3. Hormone receptor positive (ER and/or PR ≥1%), HER2-negative status (IHC 0-1+, or IHC 2+ with negative FISH result). 4. Clinical stage II-III breast cancer per the 8th AJCC staging system, with clinical indication for neoadjuvant chemotherapy or primary surgery. 5. Standard pre-treatment breast DCE-MRI performed before neoadjuvant chemotherapy, with image quality eligible for AI model analysis. 6. ECOG performance status 0 or 1; adequate function of major vital organs to tolerate planned clinical treatment. 7. Voluntary participation with written informed consent obtained. Exclusion Criteria: 1. Prior systemic anti-tumor therapy for breast cancer other than planned neoadjuvant chemotherapy. 2. Inflammatory breast cancer or distant metastatic disease (M1). 3. Concurrent active malignant tumors of other origins. 4. Contraindications to MRI examination or unqualified MRI images that cannot support model analysis. 5. Severe comorbidities incompatible with neoadjuvant chemotherapy or surgical resection. 6. Any other conditions judged ineligible for enrollment by the investigator.

Primary outcome measure(s)

Incidence of Residual Cancer Burden (RCB) 0-1 — After completion of neoadjuvant chemotherapy and definitive surgery (approximately 3-6 months after enrollment)
Compare the incidence of RCB 0-1 among HR+/HER2- breast cancer patients stratified as high chemotherapy benefit by pre-treatment DCE-MRI AI model against published historical control data to verify the predictive value of the imaging AI model.

Trial sites (5)

Facility	City	Region	Status
Fujian Cancer Hospital	Fuzhou	Fujian	Recruiting
Fujian Provincial Hospital	Fuzhou	Fujian	Recruiting
The Second Affiliated Hospital of Fujian Medical University	Quanzhou	Fujian	Recruiting
Ningde First Hospital	Ningde	Ningde	Recruiting
Sanming Second Hospital	Sanming	Sanming	Recruiting

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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 NCT07702708 on ClinicalTrials.gov ↗ ← All trials in China