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Recruiting NCT07880600

NCT07880600 Pre-Treatment Breast DCE-MRI AI Model to Predict Neoadjuvant Chemotherapy Benefit in Locally Advanced Triple-Negative Breast Cancer

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Clinical Trial Summary
NCT ID NCT07880600
Status Recruiting
Phase —
Sponsor Fujian Cancer Hospital
Condition Breast Neoplasm Female
Study Type OBSERVATIONAL
Enrollment 120 participants
Start Date 2026-10-08
Primary Completion 2027-08-31

Eligibility & Interventions

Sex Female only
Min Age 18 Years
Max Age N/A
Study Type OBSERVATIONAL
Interventions
Pre-treatment DCE-MRI-based AI model

Eligibility Fast-Check

Enter your details for a quick preliminary check. This does not replace medical advice.

What to Expect as a Participant

This is an observational study. You will not receive an experimental treatment; researchers will collect data based on your existing condition or standard treatment.

This trial targets 120 participants in total. It began in 2026-10-08 with a primary completion date of 2027-08-31.

⚠ This information is for research awareness only. Always consult your physician before joining any clinical trial. Participation is voluntary and you may withdraw at any time.

Brief 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 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.

Eligibility Criteria

Inclusion Criteria: 1. Female patients aged ≥ 18 years. 2. 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. 3. Clinical stage T2-3N0-3M0 or T1N1-3M0 according to AJCC 8th edition, with potential indication for neoadjuvant chemotherapy. 4. 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. 5. 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. 6. Post-operative pathology available to assess neoadjuvant chemotherapy response (pCR or non-pCR). 7. Eastern Cooperative Oncology Group (ECOG) performance status 0-1; adequate function of major organs to tolerate planned therapy. 8. Voluntary participation and provision of written informed consent. Exclusion Criteria: 1. Prior systemic anti-tumor therapy for breast cancer other than neoadjuvant chemotherapy. 2. Inflammatory breast cancer or distant metastatic disease (M1). 3. Concurrent active malignancy during neoadjuvant chemotherapy or surgical period. 4. History of autoimmune diseases, such as systemic lupus erythematosus, acanthosis and other related disorders. 5. Documented history of neurological or psychiatric disorders, including epilepsy, dementia, etc. 6. Contraindications to MRI or unacceptable image quality for analysis. 7. No definitive surgery performed or incomplete postoperative pathological reports. 8. Severe comorbidities that preclude chemotherapy or surgical intervention. 9. Missing required clinical information, MRI images, or pathological biopsy specimens for analysis. 10. Other conditions rendering the subject inappropriate for enrollment, in the investigator's judgment.

Contact & Investigator

Central Contact

Chuangui Song, doctor

✉ songcg1971@outlook.com

📞 13960709993

Principal Investigator

Chuangui Song, doctor

PRINCIPAL INVESTIGATOR

Fujian Cancer Hospital

Frequently Asked Questions

Who can join the NCT07880600 clinical trial?

This trial is open to female participants only, aged 18 Years or older, studying Breast Neoplasm Female. Full inclusion and exclusion criteria are listed in the Eligibility Criteria section. Always confirm your eligibility with the research team before applying.

Is NCT07880600 currently recruiting?

Yes, NCT07880600 is actively recruiting participants. Contact the research team at songcg1971@outlook.com for enrollment information.

Where is the NCT07880600 trial being conducted?

This trial is being conducted at Fuzhou, China, Fuzhou, China, Ningde, China, Quanzhou, China and 1 additional location.

Who is sponsoring the NCT07880600 clinical trial?

NCT07880600 is sponsored by Fujian Cancer Hospital. The principal investigator is Chuangui Song, doctor at Fujian Cancer Hospital. The trial plans to enroll 120 participants.

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ClinicalMetric — Independent clinical trial intelligence platform. Not affiliated with NIH, ClinicalTrials.gov, the U.S. FDA, or any pharmaceutical company, hospital, or clinical research organization. Trial data is sourced from ClinicalTrials.gov for informational purposes only and does not constitute medical advice. Do not make any treatment, enrollment, or health decisions based solely on information found here — always consult a qualified healthcare professional. Full Disclaimer  ·  Last Reviewed: November 2026  ·  Data Methodology