HR+/HER2- Breast CancerNCT07702708
Pre-Treatment DCE-MRI AI Models Predict Neoadjuvant Chemotherapy Response in HR+/HER2- Breast Cancer
An observational study of HR+/HER2- Breast Cancer and Breast Neoplasms, 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 HR+/HER2- breast cancer. Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- HR+/HER2- Breast Cancer, Breast Neoplasms
- What is being tested?
- Pre-treatment DCE-MRI-based AI model
- How many people
- 100 participants
- Where
- 5 sitesChina
- Study dates
- 1 Jun 2026to 30 Jun 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 stage II-III HR+/HER2-negative invasive breast cancer according to 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 100 eligible patients will be consecutively enrolled from participating hospitals.
Who may be able to join
- Female patients aged ≥ 18 years old.
- Histopathologically confirmed invasive breast carcinoma.
- Hormone receptor positive (ER and/or PR ≥1%), HER2-negative status (IHC 0-1+, or IHC 2+ with negative FISH result).
- Clinical stage II-III breast cancer per the 8th AJCC staging system, with clinical indication for neoadjuvant chemotherapy or primary surgery.
- Standard pre-treatment breast DCE-MRI performed before neoadjuvant chemotherapy, with image quality eligible for AI model analysis.
- ECOG performance status 0 or 1; adequate function of major vital organs to tolerate planned clinical treatment.
- Voluntary participation with written informed consent obtained.
Who cannot join
- Prior systemic anti-tumor therapy for breast cancer other than planned neoadjuvant chemotherapy.
- Inflammatory breast cancer or distant metastatic disease (M1).
- Concurrent active malignant tumors of other origins.
- Contraindications to MRI examination or unqualified MRI images that cannot support model analysis.
- Severe comorbidities incompatible with neoadjuvant chemotherapy or surgical resection.
- Any other conditions judged ineligible for enrollment by the investigator.
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
- Recruiting
Fujian Provincial Hospital
Fuzhou, Fujian
ruijuan wang, doctor, 13799367490, Rjwang2025@126.com
- Recruiting
Ningde First Hospital
Ningde, Ningde
zirong jiang, doctor, 15892129077, zirongjiang@outlook.com
- Recruiting
The Second Affiliated Hospital of Fujian Medical University
Quanzhou, Fujian
kaiyan Huang, doctor, 15905059388, kaiyanhuang@fjmu.edu.cn
- Recruiting
Sanming Second Hospital
Sanming, Sanming
junxiao wang, doctor, 15159110696, 25985991@qq.com
About this study
Official title: A Multicenter Prospective Observational Cohort Study: Predicting Neoadjuvant Chemotherapy Response Using Pre-Treatment DCE-MRI-Based AI Models in HR+/HER2- 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 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.
- Conditions
- HR+/HER2- Breast Cancer, Breast Neoplasms
- Being tested
- Pre-treatment DCE-MRI-based AI model
- Medical subject headings
- 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 HR+/HER2- breast cancer patients into high and low neoadjuvant chemotherapy benefit subgroups.
| Study group | Role | What they receive |
|---|---|---|
| HR+/HER2- Breast Cancer Cohort Receiving Neoadjuvant Chemotherapy | Multicenter prospective observational cohort of patients with HR+/HER2- 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 Residual Cancer Burden (RCB) 0-1
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.
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: Imaging assessment after completion of neoadjuvant chemotherapy and prior to surgery
Between-subgroup differences in RCB 0-1 rate
Compare RCB 0-1 incidence between AI-stratified high benefit subgroup and low benefit subgroup.
Measured: RCB classification 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: ORR imaging assessment after neoadjuvant chemotherapy before surgery
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 posted14 Jul 2026
- Study start1 Jun 2026
- Primary completion30 Apr 2027 (estimated)
- Study completion30 Jun 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for HR+/HER2- Breast CancerStudies of the same condition, open and under way.
- More trials run by Fujian Cancer HospitalThe sponsor's other registered studies.
- 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
- 100 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
- NCT07702708
- Sponsor's protocol ID
- K2026-219-01
- Status last verified
- Jul 2026
- First submitted
- 6 Jul 2026
- Last updated
- 14 Jul 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 14 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Multicenter Prospective Observational Cohort Study: Predicting Neoadjuvant Chemotherapy Response Using Pre-Treatment DCE-MRI-Based AI Models in HR+/HER2- Breast Cancer
- ClinicalTrials.gov ID
- NCT07702708
- Acronym / sponsor ID
- K2026-219-01
- Conditions
- HR+/HER2- Breast Cancer, Breast Neoplasms
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 100 participants (estimated)
- Lead sponsor
- Fujian Cancer HospitalOther government
- Study start
- 1 Jun 2026 (actual)
- Primary completion
- 30 Apr 2027 (estimated)
- Study completion
- 30 Jun 2027 (estimated)
- First posted
- 14 Jul 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| HR+/HER2- Breast Cancer Cohort Receiving Neoadjuvant Chemotherapy | – | Diagnostic Test: Pre-treatment DCE-MRI-based AI modelMulticenter prospective observational cohort of patients with HR+/HER2- 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- This study population consists of female patients aged 18 years or older with histologically confirmed stage II-III HR+/HER2-negative invasive breast cancer according to 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 100 eligible patients will be consecutively enrolled from participating hospitals.
Key inclusion criteria (7 listed)
- Female patients aged ≥ 18 years old.
- Histopathologically confirmed invasive breast carcinoma.
- Hormone receptor positive (ER and/or PR ≥1%), HER2-negative status (IHC 0-1+, or IHC 2+ with negative FISH result).
- Clinical stage II-III breast cancer per the 8th AJCC staging system, with clinical indication for neoadjuvant chemotherapy or primary surgery.
- Standard pre-treatment breast DCE-MRI performed before neoadjuvant chemotherapy, with image quality eligible for AI model analysis.
Key exclusion criteria (6 listed)
- Prior systemic anti-tumor therapy for breast cancer other than planned neoadjuvant chemotherapy.
- Inflammatory breast cancer or distant metastatic disease (M1).
- Concurrent active malignant tumors of other origins.
- Contraindications to MRI examination or unqualified MRI images that cannot support model analysis.
- Severe comorbidities incompatible with neoadjuvant chemotherapy or surgical resection.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Pre-treatment DCE-MRI-based AI modelPreoperative 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. | Diagnostic test | HR+/HER2- Breast Cancer Cohort Receiving Neoadjuvant Chemotherapy |
Primary outcome
Incidence of Residual Cancer Burden (RCB) 0-1
Time frame: 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.
5 secondary outcomes
Objective response rate (ORR) of AI-defined high neoadjuvant chemotherapy benefit group
Time frame: Imaging assessment after completion of neoadjuvant chemotherapy and prior to surgery
Between-subgroup differences in RCB 0-1 rate
Time frame: RCB classification obtained after definitive surgical resection, approximately 3-6 months after enrollment
Between-subgroup differences in objective response rate (ORR)
Time frame: ORR imaging assessment after neoadjuvant chemotherapy before surgery
Disease-free survival (DFS) between high and low chemotherapy benefit subgroups
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
Time frame: From the date of surgery until death from any cause, assessed up to 60 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 14 Jul 2026.
- Individual participant dataSharing planned: No
Related trials for HR+/HER2- Breast Cancer
RecruitingPhase 3
Adding an Immunotherapy Drug, MEDI4736 (Durvalumab), to the Usual Chemotherapy Treatment (Paclitaxel, Cyclophosphamide, and Doxorubicin) for Stage II-III Breast Cancer
Anatomic Stage II Breast Cancer AJCC v8, Anatomic Stage III Breast Cancer AJCC v8
RecruitingPhase 2
To Study the Effect of Inavolisib in Combination With Fulvestrant in Participants With Breast Cancer
Breast Cancer
RecruitingPhase 1
Study of IEV407 as Single Agent or in Combination in Patients With Advanced HR+/HER2- Breast Cancer
Advanced HR+/HER2- Breast Cancer
Active, not recruitingPhase 3
Phase IIIb Study of Ribociclib + ET in Early Breast Cancer
Early Breast Cancer
Not yet recruiting
Prospective Study to Evaluate the Clinical Utility of ctDNA Tumor Fraction (TF) for Detection of ESR1 Mutations in HR+/HER2- Metastatic Breast Cancer (MBC)
Breast Cancer, Metastatic Breast Cancer
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Chuangui Song, doctor principal investigator
Fujian Cancer Hospital
5 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of HR+/HER2- Breast Cancer and Breast Neoplasms, run by Fujian Cancer Hospital at 5 sites in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 7 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 14 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 5 sites in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Chuangui Song, doctor (13960709993, songcg1971@outlook.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Incidence of Residual Cancer Burden (RCB) 0-1 (time frame: After completion of neoadjuvant chemotherapy and definitive surgery (approximately 3-6 months after enrollment)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 14 Jul 2026.