Pre-Treatment DCE-MRI AI Models Predict Neoadjuvant Chemotherapy Response in HR+/HER2- Breast Cancer
2026年7月13日 更新者：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.
調査の概要
研究の種類
観察的
入学 (推定)
100
連絡先と場所
このセクションには、調査を実施する担当者の連絡先の詳細と、この調査が実施されている場所に関する情報が記載されています。
研究連絡先
- 名前：Chuangui Song, doctor
- 電話番号：13960709993
- メール：songcg1971@outlook.com
研究場所
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Fujian
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Fuzhou、Fujian、中国
- 募集
- Fujian Cancer Hospital
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コンタクト：
- Chuangui Song, doctor
- 電話番号：13960709993
- メール：songcg1971@outlook.com
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Fuzhou、Fujian、中国
- 募集
- Fujian Provincial Hospital
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コンタクト：
- ruijuan wang, doctor
- 電話番号：13799367490
- メール：Rjwang2025@126.com
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Quanzhou、Fujian、中国
- 募集
- The Second Affiliated Hospital of Fujian Medical University
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コンタクト：
- kaiyan Huang, doctor
- 電話番号：15905059388
- メール：kaiyanhuang@fjmu.edu.cn
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Ningde
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Ningde、Ningde、中国
- 募集
- Ningde First Hospital
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コンタクト：
- zirong jiang, doctor
- 電話番号：15892129077
- メール：zirongjiang@outlook.com
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Sanming
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Sanming、Sanming、中国
- 募集
- Sanming Second Hospital
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コンタクト：
- junxiao wang, doctor
- 電話番号：15159110696
- メール：25985991@qq.com
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参加基準
研究者は、適格基準と呼ばれる特定の説明に適合する人を探します。これらの基準のいくつかの例は、人の一般的な健康状態または以前の治療です。
適格基準
就学可能な年齢
- 大人
- 高齢者
健康ボランティアの受け入れ
いいえ
サンプリング方法
非確率サンプル
調査対象母集団
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.
説明
Inclusion Criteria:
- 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.
Exclusion Criteria:
- 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.
研究計画
このセクションでは、研究がどのように設計され、研究が何を測定しているかなど、研究計画の詳細を提供します。
研究はどのように設計されていますか？
デザインの詳細
コホートと介入
グループ/コホート |
介入・治療 |
|---|---|
|
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.
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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.
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この研究は何を測定していますか？
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Incidence of Residual Cancer Burden (RCB) 0-1
時間枠：After completion of neoadjuvant chemotherapy and definitive surgery (approximately 3-6 months after enrollment)
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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.
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After completion of neoadjuvant chemotherapy and definitive surgery (approximately 3-6 months after enrollment)
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二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Objective response rate (ORR) of AI-defined high neoadjuvant chemotherapy benefit group
時間枠：Imaging assessment after completion of neoadjuvant chemotherapy and prior to surgery
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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.
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Imaging assessment after completion of neoadjuvant chemotherapy and prior to surgery
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Between-subgroup differences in RCB 0-1 rate
時間枠：RCB classification obtained after definitive surgical resection, approximately 3-6 months after enrollment
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Compare RCB 0-1 incidence between AI-stratified high benefit subgroup and low benefit subgroup.
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RCB classification obtained after definitive surgical resection, approximately 3-6 months after enrollment
|
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Between-subgroup differences in objective response rate (ORR)
時間枠：ORR imaging assessment after neoadjuvant chemotherapy before surgery
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Compare ORR between AI-stratified high benefit subgroup and low benefit subgroup.
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ORR imaging assessment after neoadjuvant chemotherapy before surgery
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Disease-free survival (DFS) between high and low chemotherapy benefit subgroups
時間枠：From the date of surgery until the first recurrence, metastasis, or death, whichever came first, assessed up to 60 months
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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.
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From the date of surgery until the first recurrence, metastasis, or death, whichever came first, assessed up to 60 months
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Overall survival (OS) between high and low chemotherapy benefit subgroups
時間枠：From the date of surgery until death from any cause, assessed up to 60 months
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Compare OS between AI-stratified high and low chemotherapy benefit subgroups to explore the correlation between AI imaging stratification and long-term survival prognosis.
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From the date of surgery until death from any cause, assessed up to 60 months
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協力者と研究者
ここでは、この調査に関係する人々や組織を見つけることができます。
スポンサー
捜査官
- 主任研究者：Chuangui Song, doctor、Fujian Cancer Hospital
研究記録日
これらの日付は、ClinicalTrials.gov への研究記録と要約結果の提出の進捗状況を追跡します。研究記録と報告された結果は、国立医学図書館 (NLM) によって審査され、公開 Web サイトに掲載される前に、特定の品質管理基準を満たしていることが確認されます。
主要日程の研究
研究開始 (実際)
2026年6月1日
一次修了 (推定)
2027年4月30日
研究の完了 (推定)
2027年6月30日
試験登録日
最初に提出
2026年7月6日
QC基準を満たした最初の提出物
2026年7月13日
最初の投稿 (実際)
2026年7月14日
学習記録の更新
投稿された最後の更新 (実際)
2026年7月14日
QC基準を満たした最後の更新が送信されました
2026年7月13日
最終確認日
2026年7月1日
詳しくは
この情報は、Web サイト clinicaltrials.gov から変更なしで直接取得したものです。研究の詳細を変更、削除、または更新するリクエストがある場合は、register@clinicaltrials.gov。 までご連絡ください。 clinicaltrials.gov に変更が加えられるとすぐに、ウェブサイトでも自動的に更新されます。