An observational study in Breast Neoplasm Female and Triple -Negative Breast Cancer, sponsored by Fujian Cancer Hospital. Recruiting at 5 sites in China. Open to female participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-10-19.
Sponsored by Fujian Cancer Hospital · Observational
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.
1,163 studies on the registry are indexed under Triple Negative Breast Neoplasms; 447 are open to participants now.
This study's planned enrollment of 120 is below the median of 193 across 106 observational studies indexed under Triple Negative Breast Neoplasms.
Browse Triple Negative Breast Neoplasms studies →Fujian Cancer Hospital is the lead sponsor of 162 studies on the registry; 92 are open to participants now.
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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.
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Exclusion Criteria:
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.
Diagnostic Test: Pre-treatment DCE-MRI-based AI model
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.
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.
Time frame: After completion of neoadjuvant chemotherapy and definitive surgery (approximately 3-6 months after enrollment)
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.
Time frame: 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.
Time frame: 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.
Time frame: 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.
Time frame: 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.
Time frame: From the date of surgery until death from any cause, assessed up to 60 months
Plan to share: No
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From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗
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