Denne side blev automatisk oversat, og nøjagtigheden af ​​oversættelsen er ikke garanteret. Der henvises til engelsk version for en kildetekst.

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

13. juli 2026 opdateret af: 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.

Studieoversigt

Status

Rekruttering

Betingelser

Intervention / Behandling

Undersøgelsestype

Observationel

Tilmelding (Anslået)

100

Kontakter og lokationer

Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.

Studiekontakt

Studiesteder

  • Kina
    • Fujian
      • Fuzhou, Fujian, Kina
        • Rekruttering
        • Fujian Cancer Hospital
        • Kontakt:
      • Fuzhou, Fujian, Kina
        • Rekruttering
        • Fujian Provincial Hospital
        • Kontakt:
      • Quanzhou, Fujian, Kina
        • Rekruttering
        • The Second Affiliated Hospital of Fujian Medical University
        • Kontakt:
    • Ningde
      • Ningde, Ningde, Kina
        • Rekruttering
        • Ningde First Hospital
        • Kontakt:
    • Sanming
      • Sanming, Sanming, Kina
        • Rekruttering
        • Sanming Second Hospital
        • Kontakt:

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

  • Voksen
  • Ældre voksen

Tager imod sunde frivillige

Ingen

Prøveudtagningsmetode

Ikke-sandsynlighedsprøve

Studiebefolkning

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.

Beskrivelse

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.

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

Kohorter og interventioner

Gruppe / kohorte
Intervention / Behandling
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.
Diagnostisk test: 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.

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Incidence of Residual Cancer Burden (RCB) 0-1
Tidsramme: 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)

Sekundære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Objective response rate (ORR) of AI-defined high neoadjuvant chemotherapy benefit group
Tidsramme: 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
Tidsramme: 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)
Tidsramme: 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
Tidsramme: 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
Tidsramme: 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

Samarbejdspartnere og efterforskere

Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.

Sponsor

Fujian Cancer Hospital

Efterforskere

  • Ledende efterforsker: Chuangui Song, doctor, Fujian Cancer Hospital

Datoer for undersøgelser

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Faktiske)

1. juni 2026

Primær færdiggørelse (Anslået)

30. april 2027

Studieafslutning (Anslået)

30. juni 2027

Datoer for studieregistrering

Først indsendt

6. juli 2026

Først indsendt, der opfyldte QC-kriterier

13. juli 2026

Først opslået (Faktiske)

14. juli 2026

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

14. juli 2026

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

13. juli 2026

Sidst verificeret

1. juli 2026

Mere information

Begreber relateret til denne undersøgelse

Yderligere relevante MeSH-vilkår

Andre undersøgelses-id-numre

  • K2026-219-01

Plan for individuelle deltagerdata (IPD)

Planlægger du at dele individuelle deltagerdata (IPD)?

INGEN

Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter

Studerer et amerikansk FDA-reguleret lægemiddelprodukt

Ingen

Studerer et amerikansk FDA-reguleret enhedsprodukt

Ingen

Disse oplysninger blev hentet direkte fra webstedet clinicaltrials.gov uden ændringer. Hvis du har nogen anmodninger om at ændre, fjerne eller opdatere dine undersøgelsesoplysninger, bedes du kontakte register@clinicaltrials.gov. Så snart en ændring er implementeret på clinicaltrials.gov, vil denne også blive opdateret automatisk på vores hjemmeside .

Abonner