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Pre-Treatment DCE-MRI AI Models Predict Neoadjuvant Chemotherapy Response in HR+/HER2- Breast Cancer

13 juli 2026 bijgewerkt door: Fujian Cancer Hospital

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.

Studie Overzicht

Toestand

Werving

Conditie

Interventie / Behandeling

Studietype

Observationeel

Inschrijving (Geschat)

100

Contacten en locaties

In dit gedeelte vindt u de contactgegevens van degenen die het onderzoek uitvoeren en informatie over waar dit onderzoek wordt uitgevoerd.

Studiecontact

Studie Locaties

  • China
    • Fujian
      • Fuzhou, Fujian, China
        • Werving
        • Fujian Cancer Hospital
        • Contact:
      • Fuzhou, Fujian, China
        • Werving
        • Fujian Provincial Hospital
        • Contact:
      • Quanzhou, Fujian, China
        • Werving
        • The Second Affiliated Hospital of Fujian Medical University
        • Contact:
    • Ningde
      • Ningde, Ningde, China
        • Werving
        • Ningde First Hospital
        • Contact:
    • Sanming
      • Sanming, Sanming, China
        • Werving
        • Sanming Second Hospital
        • Contact:

Deelname Criteria

Onderzoekers zoeken naar mensen die aan een bepaalde beschrijving voldoen, de zogenaamde geschiktheidscriteria. Enkele voorbeelden van deze criteria zijn iemands algemene gezondheidstoestand of eerdere behandelingen.

Geschiktheidscriteria

Leeftijden die in aanmerking komen voor studie

  • Volwassen
  • Oudere volwassene

Accepteert gezonde vrijwilligers

Nee

Bemonsteringsmethode

Niet-waarschijnlijkheidssteekproef

Studie Bevolking

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.

Beschrijving

Inclusion Criteria:

  1. Female patients aged ≥ 18 years old.
  2. Histopathologically confirmed invasive breast carcinoma.
  3. Hormone receptor positive (ER and/or PR ≥1%), HER2-negative status (IHC 0-1+, or IHC 2+ with negative FISH result).
  4. Clinical stage II-III breast cancer per the 8th AJCC staging system, with clinical indication for neoadjuvant chemotherapy or primary surgery.
  5. Standard pre-treatment breast DCE-MRI performed before neoadjuvant chemotherapy, with image quality eligible for AI model analysis.
  6. ECOG performance status 0 or 1; adequate function of major vital organs to tolerate planned clinical treatment.
  7. Voluntary participation with written informed consent obtained.

Exclusion Criteria:

  1. Prior systemic anti-tumor therapy for breast cancer other than planned neoadjuvant chemotherapy.
  2. Inflammatory breast cancer or distant metastatic disease (M1).
  3. Concurrent active malignant tumors of other origins.
  4. Contraindications to MRI examination or unqualified MRI images that cannot support model analysis.
  5. Severe comorbidities incompatible with neoadjuvant chemotherapy or surgical resection.
  6. Any other conditions judged ineligible for enrollment by the investigator.

Studie plan

Dit gedeelte bevat details van het studieplan, inclusief hoe de studie is opgezet en wat de studie meet.

Hoe is de studie opgezet?

Ontwerpdetails

Cohorten en interventies

Groep / Cohort
Interventie / Behandeling
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.
Diagnostische toets: Pre-treatment DCE-MRI-based AI model
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.

Wat meet het onderzoek?

Primaire uitkomstmaten

Uitkomstmaat
Maatregel Beschrijving
Tijdsspanne
Incidence of Residual Cancer Burden (RCB) 0-1
Tijdsspanne: 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.
After completion of neoadjuvant chemotherapy and definitive surgery (approximately 3-6 months after enrollment)

Secundaire uitkomstmaten

Uitkomstmaat
Maatregel Beschrijving
Tijdsspanne
Objective response rate (ORR) of AI-defined high neoadjuvant chemotherapy benefit group
Tijdsspanne: Imaging assessment after completion of neoadjuvant chemotherapy and prior to surgery
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.
Imaging assessment after completion of neoadjuvant chemotherapy and prior to surgery
Between-subgroup differences in RCB 0-1 rate
Tijdsspanne: RCB classification obtained after definitive surgical resection, approximately 3-6 months after enrollment
Compare RCB 0-1 incidence between AI-stratified high benefit subgroup and low benefit subgroup.
RCB classification obtained after definitive surgical resection, approximately 3-6 months after enrollment
Between-subgroup differences in objective response rate (ORR)
Tijdsspanne: ORR imaging assessment after neoadjuvant chemotherapy before surgery
Compare ORR between AI-stratified high benefit subgroup and low benefit subgroup.
ORR imaging assessment after neoadjuvant chemotherapy before surgery
Disease-free survival (DFS) between high and low chemotherapy benefit subgroups
Tijdsspanne: From the date of surgery until the first recurrence, metastasis, or death, whichever came first, assessed up to 60 months
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.
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
Tijdsspanne: From the date of surgery until death from any cause, assessed up to 60 months
Compare OS between AI-stratified high and low chemotherapy benefit subgroups to explore the correlation between AI imaging stratification and long-term survival prognosis.
From the date of surgery until death from any cause, assessed up to 60 months

Medewerkers en onderzoekers

Hier vindt u mensen en organisaties die betrokken zijn bij dit onderzoek.

Sponsor

Fujian Cancer Hospital

Onderzoekers

  • Hoofdonderzoeker: Chuangui Song, doctor, Fujian Cancer Hospital

Studie record data

Deze datums volgen de voortgang van het onderzoeksdossier en de samenvatting van de ingediende resultaten bij ClinicalTrials.gov. Studieverslagen en gerapporteerde resultaten worden beoordeeld door de National Library of Medicine (NLM) om er zeker van te zijn dat ze voldoen aan specifieke kwaliteitscontrolenormen voordat ze op de openbare website worden geplaatst.

Bestudeer belangrijke data

Studie start (Werkelijk)

1 juni 2026

Primaire voltooiing (Geschat)

30 april 2027

Studie voltooiing (Geschat)

30 juni 2027

Studieregistratiedata

Eerst ingediend

6 juli 2026

Eerst ingediend dat voldeed aan de QC-criteria

13 juli 2026

Eerst geplaatst (Werkelijk)

14 juli 2026

Updates van studierecords

Laatste update geplaatst (Werkelijk)

14 juli 2026

Laatste update ingediend die voldeed aan QC-criteria

13 juli 2026

Laatst geverifieerd

1 juli 2026

Meer informatie

Termen gerelateerd aan deze studie

Aanvullende relevante MeSH-voorwaarden

Andere studie-ID-nummers

  • K2026-219-01

Plan Individuele Deelnemersgegevens (IPD)

Bent u van plan om gegevens van individuele deelnemers (IPD) te delen?

NEE

Informatie over medicijnen en apparaten, studiedocumenten

Bestudeert een door de Amerikaanse FDA gereguleerd geneesmiddel

Nee

Bestudeert een door de Amerikaanse FDA gereguleerd apparaatproduct

Nee

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