Using breast MRI and AI to predict chemotherapy benefit in triple-negative breast cancer
Tests an AI model on breast MRI scans before chemotherapy in triple-negative breast cancer.
Plain-language title generated from the registry record
Registry title: Pre-Treatment Breast DCE-MRI AI Model to Predict Neoadjuvant Chemotherapy Benefit in Locally Advanced Triple-Negative Breast Cancer
Key facts
- Where
- Fuzhou, Ningde, Quanzhou, and Sanming, ChinaSee the 5 sites
Where in China
- Fujian Cancer HospitalFuzhou, ChinaTaking people
- Fujian Provincial HospitalFuzhou, ChinaNot yet recruiting
- Ningde First HospitalNingde, ChinaNot yet recruiting
- The Second Affiliated Hospital of Fujian Medical UniversityQuanzhou, ChinaNot yet recruiting
- Sanming Second HospitalSanming, ChinaNot yet recruiting
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- Fujian Cancer Hospital
- Trial code
- NCT07880600
- Record updated
- 19 October 2026
- Original description
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 locally advanced triple-negative breast cancer. The study plans to enroll eligible locally advanced triple-negative 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.Read full original descriptionShow less
Multicenter Prospective Observational Cohort Study of Pre-Treatment Breast DCE-MRI-Based Artificial Intelligence Model for Predicting Populations Benefiting From Neoadjuvant Chemotherapy in Locally Advanced Triple-Negative Breast Cancer
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 locally advanced triple-negative breast cancer. The study plans to enroll eligible locally advanced triple-negative 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, pathological complete response (pCR) status, objective response rate (ORR), and long-term survival endpoints including disease-free survival (DFS) and overall survival (OS). The primary objective compares the pCR rate between AI-defined high-benefit patients and published historical control data; secondary analyses compare ORR, pCR 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.
Inclusion: Female patients aged ≥ 18 years; Histologically confirmed invasive triple-negative breast cancer; patients with ER/PR 1%-10% positive and HER2-negative status are also eligible given their biological features resembling triple-negative breast cancer; Clinical stage T2-3N0-3M0 or T1N1-3M0 according to AJCC 8th edition, with potential indication for neoadjuvant chemotherapy; Availability of both MRI and pathological biopsy materials; standardized breast DCE-MRI examination and pathological biopsy completed prior to neoadjuvant chemotherapy, with image quality satisfying requirements for model analysis; Patients planned to receive standard neoadjuvant chemotherapy followed by surgical treatment. Patients who are undergoing standard neoadjuvant chemotherapy or have completed neoadjuvant chemotherapy awaiting surgery are also eligible; Post-operative pathology available to assess neoadjuvant chemotherapy response (pCR or non-pCR); Eastern Cooperative Oncology Group (ECOG) performance status 0-1; adequate function of major organs to tolerate planned therapy; Voluntary participation and provision of written informed consent.
Exclusion: Prior systemic anti-tumor therapy for breast cancer other than neoadjuvant chemotherapy; Concurrent active malignancy during neoadjuvant chemotherapy or surgical period; No definitive surgery performed or incomplete postoperative pathological reports; Severe comorbidities that preclude chemotherapy or surgical intervention; Inflammatory breast cancer or distant metastatic disease (M1); History of autoimmune diseases, such as systemic lupus erythematosus, acanthosis and other related disorders; Documented history of neurological or psychiatric disorders, including epilepsy, dementia, etc; Other conditions rendering the subject inappropriate for enrollment, in the investigator's judgment; Contraindications to MRI or unacceptable image quality for analysis; Missing required clinical information, MRI images, or pathological biopsy specimens for analysis.