Breast Neoplasm FemaleNCT07880600
Pre-Treatment Breast DCE-MRI AI Model to Predict Neoadjuvant Chemotherapy Benefit in Locally Advanced Triple-Negative Breast Cancer
An observational study of Breast Neoplasm Female and Triple -Negative Breast Cancer, run by Fujian Cancer Hospital at 5 sites in China.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Breast Neoplasm Female, Triple -Negative Breast Cancer
- What is being tested?
- Pre-treatment DCE-MRI-based AI model
- How many people
- 120 participants
- Where
- 5 sitesChina
- Study dates
- 8 Oct 2026to 31 Oct 2027
- Phase
- Observational
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- Women only
- No healthy volunteers
- Adult, Older adult
Study population: This study population consists of female patients aged 18 years or older with histologically confirmed invasive triple-negative breast cancer with clinical stage T2-3N0-3M0 or T1N1-3M0 per the 8th AJCC staging system. All participants receive routine standard neoadjuvant chemotherapy in multi-center breast cancer departments, complete standardized pre-treatment DCE-MRI with qualified imaging data, have ECOG performance status 0-1 and intact vital organ function. Subjects must satisfy all inclusion criteria, without meeting any exclusion criteria, and sign written informed consent voluntarily. Approximately 120 eligible patients will be consecutively enrolled from participating hospitals.
Who may be able to join
- 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.
Who cannot join
- Prior systemic anti-tumor therapy for breast cancer other than neoadjuvant chemotherapy.
- Inflammatory breast cancer or distant metastatic disease (M1).
- Concurrent active malignancy during neoadjuvant chemotherapy or surgical period.
- 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.
- Contraindications to MRI or unacceptable image quality for analysis.
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- No definitive surgery performed or incomplete postoperative pathological reports.
- Severe comorbidities that preclude chemotherapy or surgical intervention.
- Missing required clinical information, MRI images, or pathological biopsy specimens for analysis.
- Other conditions rendering the subject inappropriate for enrollment, in the investigator's judgment.
Trial locations and contacts
5 sites in 1 country. Contact the study team or a site near you to ask about taking part.
5 sites in 1 country
China5 sites, 5 recruiting
- Recruiting
Fujian Cancer Hospital
Fuzhou, Fujian
Chuangui Song, doctor, 13960709993, songcg1971@outlook.com
- Not yet recruiting
Fujian Provincial Hospital
Fuzhou, Fujian
ruijuan wang, doctor, 13799367490, Rjwang2025@126.com
- Not yet recruiting
Ningde First Hospital
Ningde, Fujian
zirong jiang, doctor, 15892129077, zirongjiang@outlook.com
- Not yet recruiting
The Second Affiliated Hospital of Fujian Medical University
Quanzhou, Fujian
kaiyan Huang, doctor, 15905059388, kaiyanhuang@fjmu.edu.cn
- Not yet recruiting
Sanming Second Hospital
Sanming, Fujian
junxiao wang, doctor, 15159110696, 25985991@qq.com
About this study
Official title: 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.
- Being tested
- Pre-treatment DCE-MRI-based AI model
- Medical subject headings
- Triple Negative Breast Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Pre-treatment DCE-MRI-based AI modelDiagnostic test
Preoperative dynamic contrast-enhanced MRI images are input into an artificial intelligence prediction model to stratify triple-negative breast cancer patients into high and low neoadjuvant chemotherapy benefit subgroups.
| Study group | Role | What they receive |
|---|---|---|
| Triple-negative Breast Cancer Cohort Receiving Neoadjuvant Chemotherapy | Multicenter prospective observational cohort of patients with Triple-negative invasive breast cancer who receive routine standard neoadjuvant chemotherapy. All participants undergo pre-treatment DCE-MRI scanning, and an MRI-based AI model is applied to stratify patients into high and low chemotherapy benefit subgroups. Receives: Diagnostic Test: Pre-treatment DCE-MRI-based AI model |
What is being measured
The primary outcome is the main question the study is designed to answer.
Incidence of pCR
Compare the incidence of pathological complete response (pCR) among triple-negative 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.
Measured: After completion of neoadjuvant chemotherapy and definitive surgery (approximately 3-6 months after enrollment)
Secondary outcomes (5)
Objective response rate (ORR) of AI-defined high neoadjuvant chemotherapy benefit group
Compare the objective response rate (ORR) assessed by imaging after neoadjuvant chemotherapy before surgery in patients of AI-identified high chemotherapy benefit subgroup with historical control data.
Measured: After completion of neoadjuvant chemotherapy and prior to definitive surgery (approximately 2-5 months after enrollment)
Between-subgroup differences in pCR rate
Compare pCR incidence between AI-stratified high benefit subgroup and low benefit subgroup.
Measured: pCR result obtained after definitive surgical resection, approximately 3-6 months after enrollment
Between-subgroup differences in objective response rate (ORR)
Compare ORR between AI-stratified high benefit subgroup and low benefit subgroup.
Measured: After completion of neoadjuvant chemotherapy and prior to definitive surgery (approximately 2-5 months after enrollment)
Disease-free survival (DFS) between high and low chemotherapy benefit subgroups
Compare DFS (time interval from the date of surgery to first recurrence, metastasis or death) between AI-stratified high and low chemotherapy benefit subgroups to explore the correlation between AI imaging stratification and long-term survival prognosis.
Measured: From the date of surgery until the first recurrence, metastasis, or death, whichever came first, assessed up to 60 months
Overall survival (OS) between high and low chemotherapy benefit subgroups
Compare OS between AI-stratified high and low chemotherapy benefit subgroups to explore the correlation between AI imaging stratification and long-term survival prognosis.
Measured: From the date of surgery until death from any cause, assessed up to 60 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Oct 2026
- Study start8 Oct 2026
- Primary completion31 Aug 2027 (estimated)
- Study completion31 Oct 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Breast Neoplasm FemaleStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 120 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Fujian Cancer Hospital
- Sponsor type
- Other government
- Responsible party
- Sponsor
- Investigators
- Chuangui Song, doctor, Principal investigator, Fujian Cancer Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07880600
- Sponsor's protocol ID
- C2026-440-01
- Status last verified
- Oct 2026
- First submitted
- 8 Oct 2026
- Last updated
- 19 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No